CMP Associates Regulation Blog: Dollar Revaluation and Increase of Valuation of Risk Financial Assets, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, IMF View of World Economy and Finance, United States Commercial Banks Assets and Liabilities, Cyclically Stagnating Real Private Fixed Investment, United States Housing, World Cyclical Slow Growth and Global Recession Risk: Part II

CANNOT UPLOAD CHARTS AND IMAGES

Dollar Revaluation and Increase of Valuation of Risk Financial Assets, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, IMF View of World Economy and Finance, United States Commercial Banks Assets and Liabilities, Cyclically Stagnating Real Private Fixed Investment, United States Housing, World Cyclical Slow Growth and Global Recession Risk

I Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend

IA Mediocre Cyclical United States Economic Growth

IA1 Stagnating Real Private Fixed Investment

II IMF View of World Economy and Finance

IIA United States Commercial Banks Assets and Liabilities

IA Transmission of Monetary Policy

IB Functions of Banking

IC United States Commercial Banks Assets and Liabilities

ID Theory and Reality of Economic History, Cyclical Slow Growth Not Secular Stagnation and Monetary Policy Based on Fear of Deflation

IIB United States Housing Collapse

IIA1 Sales of New Houses

IIA2 United States House Prices

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

IIID Appendix on European Central Bank Large Scale Lender of Last Resort

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during the Debt Crisis of the 1980s

I United States Commercial Banks Assets and Liabilities. Subsection IA

Transmission of Monetary Policy recapitulates the mechanism of transmission of monetary policy. Subsection IB Functions of Banking analyzes the functions of banks in modern banking theory. Subsection IC United States Commercial Bank Assets and Liabilities provides data and analysis of US commercial ban balance sheets in report H.8 of the Board of Governors of the Federal Reserve System on Assets and Liabilities of Commercial Banks in the United States (http://www.federalreserve.gov/releases/h8/current/default.htm). Subsection ID Theory and Reality of Economic History, Cyclical Slow Growth Not Secular Stagnation and Monetary Policy Based on Fear of Deflation analyzes and compares unconventional monetary policy.

IA Transmission of Monetary Policy. The critical fact of current world financial markets is the combination of “unconventional” monetary policy with intermittent shocks of financial risk aversion. There are two interrelated unconventional monetary policies. First, unconventional monetary policy consists primarily of reducing short-term policy interest rates toward the “zero bound” such as fixing the fed funds rate at 0 to ¼ percent by decision of the Federal Open Market Committee (FOMC) since Dec 16, 2008 (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm). The FOMC raised the fed funds rate to ¼ to ½ at its meeting on Dec 16, 2015 (http://www.federalreserve.gov/newsevents/press/monetary/20151216a.htm) and increased the fed funds rate to ½ to ¾ percent at its meeting on Dec 14, 2016 (https://www.federalreserve.gov/newsevents/press/monetary/20161214a.htm). The FOMC raised the fed funds rate to ¾ to 1 percent at its meeting on Mar 15, 2017 (https://www.federalreserve.gov/newsevents/pressreleases/monetary20170315a.htm). The FOMC raised the fed funds rate to 1 to 1 ¼ percent at its meeting on Jun 14, 2017 (https://www.federalreserve.gov/newsevents/pressreleases/monetary20170201a.htm). Fixing policy rates at zero is the strongest measure of monetary policy with collateral effects of inducing carry trades from zero interest rates to exposures in risk financial assets such as commodities, exchange rates, stocks and higher yielding fixed income. Second, unconventional monetary policy also includes a battery of measures in also reducing long-term interest rates of government securities and asset-backed securities such as mortgage-backed securities.

When inflation is low, the central bank lowers interest rates to stimulate aggregate demand in the economy, which consists of consumption and investment. When inflation is subdued and unemployment high, monetary policy would lower interest rates to stimulate aggregate demand, reducing unemployment. When interest rates decline to zero, unconventional monetary policy would consist of policies such as large-scale purchases of long-term securities to lower their yields. Long-term asset-backed securities finance a major portion of credit in the economy. Loans for purchasing houses, automobiles and other consumer products are bundled in securities that in turn are sold to investors. Corporations borrow funds for investment by issuing corporate bonds. Loans to small businesses are also financed by bundling them in long-term bonds. Securities markets bridge the needs of higher returns by savers obtaining funds from investors that are channeled to consumers and business for consumption and investment. Lowering the yields of these long-term bonds could lower costs of financing purchases of consumer durables and investment by business. The essential mechanism of transmission from lower interest rates to increases in aggregate demand is portfolio rebalancing. Withdrawal of bonds in a specific maturity segment or directly in a bond category such as currently mortgage-backed securities causes reductions in yields that are equivalent to increases in the prices of the bonds. There can be secondary increases in purchases of those bonds in private portfolios in pursuit of their increasing prices. Lower yields translate into lower costs of buying homes and consumer durables such as automobiles and also lower costs of investment for business. There are two additional intended routes of transmission.

1. Unconventional monetary policy or its expectation can increase stock market valuations (Bernanke 2010WP). Increases in equities traded in stock markets can augment perceptions of the wealth of consumers inducing increases in consumption.

2. Unconventional monetary policy causes devaluation of the dollar relative to other currencies, which can cause increases in net exports of the US that increase aggregate economic activity (Yellen 2011AS).

Monetary policy can lower short-term interest rates quite effectively. Lowering long-term yields is somewhat more difficult. The critical issue is that monetary policy cannot ensure that increasing credit at low interest cost increases consumption and investment. There is a large variety of possible allocation of funds at low interest rates from consumption and investment to multiple risk financial assets. Monetary policy does not control how investors will allocate asset categories. A critical financial practice is to borrow at low short-term interest rates to invest in high-risk, leveraged financial assets. Investors may increase in their portfolios asset categories such as equities, emerging market equities, high-yield bonds, currencies, commodity futures and options and multiple other risk financial assets including structured products. If there is risk appetite, the carry trade from zero interest rates to risk financial assets will consist of short positions at short-term interest rates (or borrowing) and short dollar assets with simultaneous long positions in high-risk, leveraged financial assets such as equities, commodities and high-yield bonds. Low interest rates may induce increases in valuations of risk financial assets that may fluctuate in accordance with perceptions of risk aversion by investors and the public. During periods of muted risk aversion, carry trades from zero interest rates to exposures in risk financial assets cause temporary waves of inflation that may foster instead of preventing financial instability. During periods of risk aversion such as fears of disruption of world financial markets and the global economy resulting from events such as collapse of the European Monetary Union, carry trades are unwound with sharp deterioration of valuations of risk financial assets. More technical discussion is in IA Appendix: Transmission of Unconventional Monetary Policy.

In the effort to increase transparency, the Federal Open Market Committee (FOMC) provides both economic projections of its participants and views on future paths of the policy rate that in the US is the federal funds rate or interest on interbank lending of reserves deposited at Federal Reserve Banks. These policies and views are discussed initially followed with appropriate analysis.

Charles Evans, President of the Federal Reserve Bank of Chicago, proposed an “economic state-contingent policy” or “7/3” approach (Evans 2012 Aug 27):

“I think the best way to provide forward guidance is by tying our policy actions to explicit measures of economic performance. There are many ways of doing this, including setting a target for the level of nominal GDP. But recognizing the difficult nature of that policy approach, I have a more modest proposal: I think the Fed should make it clear that the federal funds rate will not be increased until the unemployment rate falls below 7 percent. Knowing that rates would stay low until significant progress is made in reducing unemployment would reassure markets and the public that the Fed would not prematurely reduce its accommodation.

Based on the work I have seen, I do not expect that such policy would lead to a major problem with inflation. But I recognize that there is a chance that the models and other analysis supporting this approach could be wrong. Accordingly, I believe that the commitment to low rates should be dropped if the outlook for inflation over the medium term rises above 3 percent.

The economic conditionality in this 7/3 threshold policy would clarify our forward policy intentions greatly and provide a more meaningful guide on how long the federal funds rate will remain low. In addition, I would indicate that clear and steady progress toward stronger growth is essential.”

Evans (2012Nov27) modified the “7/3” approach to a “6.5/2.5” approach:

“I have reassessed my previous 7/3 proposal. I now think a threshold of 6-1/2 percent for the unemployment rate and an inflation safeguard of 2-1/2 percent, measured in terms of the outlook for total PCE (Personal Consumption Expenditures Price Index) inflation over the next two to three years, would be appropriate.”

The Federal Open Market Committee (FOMC) decided at its meeting on Dec 12, 2012 to implement the “6.5/2.5” approach (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm):

“To support continued progress toward maximum employment and price stability, the Committee expects that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the asset purchase program ends and the economic recovery strengthens. In particular, the Committee decided to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that this exceptionally low range for the federal funds rate will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee’s 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored.”

Another rising risk is division within the Federal Open Market Committee (FOMC) on risks and benefits of current policies as expressed in the minutes of the meeting held on Jan 29-30, 2013 (http://www.federalreserve.gov/monetarypolicy/files/fomcminutes20130130.pdf 13):

“However, many participants also expressed some concerns about potential costs and risks arising from further asset purchases. Several participants discussed the possible complications that additional purchases could cause for the eventual withdrawal of policy accommodation, a few mentioned the prospect of inflationary risks, and some noted that further asset purchases could foster market behavior that could undermine financial stability. Several participants noted that a very large portfolio of long-duration assets would, under certain circumstances, expose the Federal Reserve to significant capital losses when these holdings were unwound, but others pointed to offsetting factors and one noted that losses would not impede the effective operation of monetary policy.”

Jon Hilsenrath, writing on “Fed maps exit from stimulus,” on May 11, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887324744104578475273101471896.html?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes the development of strategy for unwinding quantitative easing and how it can create uncertainty in financial markets. Jon Hilsenrath and Victoria McGrane, writing on “Fed slip over how long to keep cash spigot open,” published on Feb 20, 2013 in the Wall street Journal (http://professional.wsj.com/article/SB10001424127887323511804578298121033876536.html), analyze the minutes of the Fed, comments by members of the FOMC and data showing increase in holdings of riskier debt by investors, record issuance of junk bonds, mortgage securities and corporate loans. Jon Hilsenrath, writing on “Jobs upturn isn’t enough to satisfy Fed,” on Mar 8, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324582804578348293647760204.html), finds that much stronger labor market conditions are required for the Fed to end quantitative easing. Unconventional monetary policy with zero interest rates and quantitative easing is quite difficult to unwind because of the adverse effects of raising interest rates on valuations of risk financial assets and home prices, including the very own valuation of the securities held outright in the Fed balance sheet. Gradual unwinding of 1 percent fed funds rates from Jun 2003 to Jun 2004 by seventeen consecutive increases of 25 percentage points from Jun 2004 to Jun 2006 to reach 5.25 percent caused default of subprime mortgages and adjustable-rate mortgages linked to the overnight fed funds rate. The zero interest rate has penalized liquidity and increased risks by inducing carry trades from zero interest rates to speculative positions in risk financial assets. There is no exit from zero interest rates without provoking another financial crash.

Unconventional monetary policy, or reinvestment of principal in securities and issue of bank reserves to maintain policy interest rates below what would be without central bank intervention, will remain in perpetuity, or QE→∞, changing to a “growth mandate.” The FOMC is implementing gradual reduction of the portfolio of government securities in the balance sheet of the Fed beginning in Oct 2017. There are two reasons explaining unconventional monetary policy of QE→∞: insufficiency of job creation to reduce unemployment/underemployment at current rates of job creation; and growth of GDP at around 2.0 percent, which is well below 3.0 percent estimated by Lucas (2011May) from 1870 to 2010. Unconventional monetary policy interprets the dual mandate of low inflation and maximum employment as mainly a “growth mandate” of forcing economic growth in the US at a rate that generates full employment. A hurdle to this “growth mandate” is that long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 33 quarters from IIIQ2009 to IIIQ2017. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the first estimate of GDP for IIIQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp3q17_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2842.2 billion than actual $17,156.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 21.1 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.5 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/10/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/twenty-two-million-unemployed-or.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,156.9 billion in IIIQ2017 or 14.4 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Sep 1919 to Sep 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 145.7662 in Sep 2017. The actual index NSA in Sep 2017 is 104.2863, which is 28.5 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Sep 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.2915 in Sep 2017. The output of manufacturing at 104.2863 in Sep 2017 is 20.6 percent below trend under this alternative calculation.

First, total nonfarm payroll employment seasonally adjusted (SA) decreased 33,000 in Sep 2017 and private payroll employment decreased 40,000. The Bureau of Labor Statistics states (https://www.bls.gov/news.release/empsit.nr0.htm): “Our analysis suggests that the net effect of these hurricanes [Harvey and Irma] was to reduce the estimate of total nonfarm payroll employment for September. There was no discernible effect on the national unemployment rate. No changes were made to either the establishment or household survey estimation procedures for the September figures.” The average monthly number of nonfarm jobs created from Sep 2015 to Sep 2016 was 219,083 using seasonally adjusted data, while the average number of nonfarm jobs created from Sep 2016 to Sep 2017 was 148,083, or decrease by 32.4 percent. The average number of private jobs created in the US from Sep 2015 to Sep 2016 was 197,500, using seasonally adjusted data, while the average from Sep 2016 to Sep 2017 was 146,333, or decrease by 25.9 percent. This blog calculates the effective labor force of the US at 169,182 million in Sep 2017 and 168,208 million in Sep 2016 (Table I-4), for growth of 0.974 million at average 81,167 per month. The difference between the average increase of 146,333 new private nonfarm jobs per month in the US from Sep 2016 to Sep 2017 and the 81,167-average monthly increase in the labor force from Sep 2016 to Sep 2017 is 65,166 monthly new jobs net of absorption of new entrants in the labor force. There are 21.076 million in job stress in the US currently. Creation of 65,166 new jobs per month net of absorption of new entrants in the labor force would require 323 months to provide jobs for the unemployed and underemployed (21.076 million divided by 65,166) or 27 years (323 divided by 12). The civilian labor force of the US in Sep 2017 not seasonally adjusted stood at 161.049 million with 6.556 million unemployed or effectively 14.689 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 169.182 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 1.28 years (1 million divided by product of 65,166 by 12, which is 781,992). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 8.052 million (0.05 times labor force of 161.049 million). New net job creation would be minus 1.496 million (6.556 million unemployed minus 8.052 million unemployed at rate of 5 percent) that at the current rate would take 0.0 years (-1.496 million divided by 0.781992). Under the calculation in this blog, there are 14.689 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 169.182 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 6.230 million jobs net of labor force growth that at the current rate would take 8.0 years (14.689 million minus 0.05(169.182 million) = 6.230 million divided by 0.781992 using LF PART 66.2% and Total UEM in Table I-4). These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply. The number employed in Sep 2017 was 154.494 million (NSA) or 7.179 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 255.562 million in Sep 2017 or by 23.604 million. The number employed increased 4.9 percent from Jul 2007 to Sep 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 10.2 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Sep 2017 would result in 162.282 million jobs (0.635 multiplied by noninstitutional civilian population of 255.562 million). There are effectively 7.788 million fewer jobs in Sep 2017 than in Jul 2007, or 162.282 million minus 154.494 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

“Not until the problem of full employment of our productive resources from the long-run, secular standpoint was upon us, were we compelled to give serious consideration to those factors and forces in our economy which tend to make business recoveries weak and anaemic (sic) and which tend to prolong and deepen the course of depressions. This is the essence of secular stagnation-sick recoveries which die in their infancy and depressions which feed on them-selves and leave a hard and seemingly immovable core of unemployment. Now the rate of population growth must necessarily play an important role in determining the character of the output; in other words, the com-position of the flow of final goods. Thus a rapidly growing population will demand a much larger per capita volume of new residential building construction than will a stationary population. A stationary population with its larger proportion of old people may perhaps demand more personal services; and the composition of consumer demand will have an important influence on the quantity of capital required. The demand for housing calls for large capital outlays, while the demand for personal services can be met without making large investment expenditures. It is therefore not unlikely that a shift from a rapidly growing population to a stationary or declining one may so alter the composition of the final flow of consumption goods that the ratio of capital to output as a whole will tend to decline.”

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (https://cmpassocregulationblog.blogspot.com/2017/10/increasing-valuations-of-risk-financial.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/dollar-devaluation-world-inflation.html).

Second, long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 33 quarters from IIIQ2009 to IIIQ2017. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the first estimate of GDP for IIIQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp3q17_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2842.2 billion than actual $17,156.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 21.1 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.5 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/10/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/twenty-two-million-unemployed-or.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,156.9 billion in IIIQ2017 or 14.4 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Sep 1919 to Sep 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 145.7662 in Sep 2017. The actual index NSA in Sep 2017 is 104.2863, which is 28.5 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Sep 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.2915 in Sep 2017. The output of manufacturing at 104.2863 in Sep 2017 is 20.6 percent below trend under this alternative calculation.

The economy of the US can be summarized in growth of economic activity or GDP as fluctuating from mediocre growth of 2.5 percent on an annual basis in 2010 to 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.6 percent in 2014 and 2.9 percent in 2015. GDP growth was 1.5 percent in 2016. The following calculations show that actual growth is around 2.1 percent per year. The rate of growth of 1.3 percent in the entire cycle from 2007 to 2016 is well below 3 percent per year in trend from 1870 to 2010, which the economy of the US always attained for entire cycles in expansions after events such as wars and recessions (Lucas 2011May). Revisions and enhancements of United States GDP and personal income accounts by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) provides valuable information on long-term growth and cyclical behavior. Table Summary provides relevant data.

Table Summary, Long-term and Cyclical Growth of GDP, Real Disposable Income and Real Disposable Income per Capita

	GDP
Long-Term
1929-2016	3.2
1947-2016	3.2
Whole Cycles
1980-1989	3.5
2006-2016	1.4
2007-2016	1.3
Cyclical Contractions ∆%
IQ1980 to IIIQ1980, IIIQ1981 to IVQ1982	-4.7
IVQ2007 to IIQ2009	-4.2
Cyclical Expansions Average Annual Equivalent ∆%
IQ1983 to IVQ1985 IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987 IQ1983-IIQ1987 IQ1983-IIIQ1987 IQ1983 to IVQ1987 IQ1983 to IQ1988 IQ1983 to IIQ1988 IQ1983 to IIIQ1988 IQ1983 to IVQ1988 IQ1983 to IQ1989 IQ1983 to IIQ1989 IQ1983 to IIIQ1989 IQ1983 to IVQ1989 IQ1983 to IQ1990 IQ1983 to IIQ1990 IQ1983 to IIIQ1990 IQ1983 to IVQ1990	5.9 5.7 5.4 5.2 5.0 5.0 4.9 5.0 4.9 4.9 4.8 4.8 4.8 4.7 4.7 4.5 4.5 4.4 4.3 4.0
IQ1983 to IQ1991	3.8
First Four Quarters IQ1983 to IVQ1983	7.8
IIIQ2009 to IIIQ2017	2.2
First Four Quarters IIIQ2009 to IIQ2010	2.7
	Real Disposable Income	Real Disposable Income per Capita
Long-Term
1929-2016	3.2	2.0
1947-1999	3.7	2.3
Whole Cycles
1980-1989	3.5	2.6
2006-2016	1.8	1.0

Source: Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

The revisions and enhancements of United States GDP and personal income accounts by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) also provide critical information in assessing the current rhythm of US economic growth. The economy appears to be moving at a pace around 2.1 percent per year. Table Summary GDP provides the data.

1. Average Annual Growth in the Past Twenty-Two Quarters. GDP growth in the four quarters of 2012, the four quarters of 2013, the four quarters of 2014, the four quarters of 2015, the four quarters of 2016 and the three quarters of 2017 accumulated to 12.9 percent. This growth is equivalent to 2.1 percent per year, obtained by dividing GDP in IIIQ2017 of $17,156.9 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/23: {[($17,156.9/$15,190.3)^4/23 -1]100 = 2.1 percent}.

2. Average Annual Growth in the Past Four Quarters. GDP growth in the four quarters from IIQ2016 to IIIQ2017 accumulated to 2.3 percent that is equivalent to 2.3 percent in a year. This is obtained by dividing GDP in IIIQ2017 of $17,156.9 billion by GDP in IIIQ2006 of $16,778.1 billion and compounding by 4/4: {[($17,156.9/$16,778.1)^4/4 -1]100 = 2.3%}. The US economy grew 2.3 percent in IIIQ2017 relative to the same quarter a year earlier in IIIQ2016. Growth was at annual equivalent 4.6 percent in IIQ2014 and 5.2 percent IIIQ2014 and only at 2.0 percent in IVQ2014. GDP grew at annual equivalent 3.2 percent in IQ2015, 2.7 percent in IIQ2015, 1.6 percent in IIIQ2015 and 0.5 percent in IVQ2015. GDP grew at annual equivalent 0.6 percent in IQ2016 and at 2.2 percent annual equivalent in IIQ2016. GDP increased at 2.8 percent annual equivalent in IIIQ2016 and at 1.8 percent in IVQ2016. GDP grew at annual equivalent 1.2 percent in IQ2017 and at annual equivalent 3.1 percent in IIQ2017. GDP grew at annual equivalent 3.0 percent in IIIQ2017. Another important revelation of the revisions and enhancements is that GDP was flat in IVQ2012, which is in the borderline of contraction, and negative in IQ2014. US GDP fell 0.2 percent in IQ2014. The rate of growth of GDP in the revision of IIIQ2013 is 3.1 percent in seasonally adjusted annual rate (SAAR).

Table Summary GDP, US, Real GDP and Percentage Change Relative to IVQ2007 and Prior Quarter, Billions Chained 2009 Dollars and ∆%

	Real GDP, Billions Chained 2009 Dollars	∆% Relative to IVQ2007	∆% Relative to Prior Quarter	∆% over Year Earlier
IVQ2007	14,991.8	NA	0.4	1.9
IVQ2011	15,190.3	1.3	1.1	1.7
IQ2012	15,291.0	2.0	0.7	2.8
IIQ2012	15,362.4	2.5	0.5	2.5
IIIQ2012	15,380.8	2.6	0.1	2.4
IVQ2012	15,384.3	2.6	0.0	1.3
IQ2013	15,491.9	3.3	0.7	1.3
IIQ2013	15,521.6	3.5	0.2	1.0
IIIQ2013	15,641.3	4.3	0.8	1.7
IVQ2013	15,793.9	5.4	1.0	2.7
IQ2014	15,757.6	5.1	-0.2	1.7
IIQ2014	15,935.8	6.3	1.1	2.7
IIIQ2014	16,139.5	7.7	1.3	3.2
IVQ2014	16,220.2	8.2	0.5	2.7
IQ2015	16,350.0	9.1	0.8	3.8
IIQ2015	16,460.9	9.8	0.7	3.3
IIIQ2015	16,527.6	10.2	0.4	2.4
IVQ2015	16,547.6	10.4	0.1	2.0
IQ2016	16,571.6	10.5	0.1	1.4
IIQ2016	16,663.5	11.2	0.6	1.2
IIIQ2016	16,778.1	11.9	0.7	1.5
IVQ2016	16,851.4	12.4	0.4	1.8
IQ2017	16,903.2	12.7	0.3	2.0
IIQ2017	17,031.1	13.6	0.8	2.2
IIIQ2017	17,156.9	14.4	0.7	2.3
Cumulative ∆% IQ2012 to IIIQ2017	12.9		13.0
Annual Equivalent ∆%	2.1		2.2

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

Chart GDP of the US Bureau of Economic Analysis provides the rates of growth of GDP at SAAR (seasonally adjusted annual rate) in the 16 quarters from IVQ2013 to IIIQ2017. Growth has been fluctuating.

Chart GDP, Seasonally Adjusted Quarterly Rates of Growth of United States GDP, ∆%

Source: US Bureau of Economic Analysis

http://www.bea.gov/newsreleases/national/gdp/gdp_glance.htm

In fact, it is evident to the public that this policy will be abandoned if inflation costs rise. There is concern of the production and employment costs of controlling future inflation. Even if there is no inflation, QE→∞, or reinvestment of principal in securities and issue of bank reserves to maintain interest rates below what would be without central bank intervention, cannot be abandoned because of the fear of rising interest rates. The FOMC is implementing gradual reduction of the portfolio of government securities in the balance sheet of the Fed. The economy would operate in an inferior allocation of resources and suboptimal growth path, or interior point of the production possibilities frontier where the optimum of productive efficiency and wellbeing is attained, because of the distortion of risk/return decisions caused by perpetual financial repression. Not even a second-best allocation is feasible with the shocks to efficiency of financial repression in perpetuity.

The statement of the FOMC at the conclusion of its meeting on Dec 12, 2012, revealed policy intentions (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm). The FOMC updated in the statement at its meeting on Dec 16, 2015 with maintenance of the current level of the balance sheet and liftoff of interest rates (http://www.federalreserve.gov/newsevents/press/monetary/20151216a.htm) followed by the statement of the meeting on Sep 20, 2017 (https://www.federalreserve.gov/newsevents/pressreleases/monetary20170920a.htm):

Press Release

September 20, 2017

Federal Reserve issues FOMC statement

For release at 2:00 p.m. EDT

Information received since the Federal Open Market Committee met in July indicates that the labor market has continued to strengthen and that economic activity has been rising moderately so far this year. Job gains have remained solid in recent months, and the unemployment rate has stayed low. Household spending has been expanding at a moderate rate, and growth in business fixed investment has picked up in recent quarters. On a 12-month basis, overall inflation and the measure excluding food and energy prices have declined this year and are running below 2 percent. Market-based measures of inflation compensation remain low; survey-based measures of longer-term inflation expectations are little changed, on balance.

Consistent with its statutory mandate, the Committee seeks to foster maximum employment and price stability. Hurricanes Harvey, Irma, and Maria have devastated many communities, inflicting severe hardship. Storm-related disruptions and rebuilding will affect economic activity in the near term, but past experience suggests that the storms are unlikely to materially alter the course of the national economy over the medium term. Consequently, the Committee continues to expect that, with gradual adjustments in the stance of monetary policy, economic activity will expand at a moderate pace, and labor market conditions will strengthen somewhat further. Higher prices for gasoline and some other items in the aftermath of the hurricanes will likely boost inflation temporarily; apart from that effect, inflation on a 12-month basis is expected to remain somewhat below 2 percent in the near term but to stabilize around the Committee's 2 percent objective over the medium term. Near-term risks to the economic outlook appear roughly balanced, but the Committee is monitoring inflation developments closely.

In view of realized and expected labor market conditions and inflation, the Committee decided to maintain the target range for the federal funds rate at 1 to 1-1/4 percent. The stance of monetary policy remains accommodative, thereby supporting some further strengthening in labor market conditions and a sustained return to 2 percent inflation.

In determining the timing and size of future adjustments to the target range for the federal funds rate, the Committee will assess realized and expected economic conditions relative to its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial and international developments. The Committee will carefully monitor actual and expected inflation developments relative to its symmetric inflation goal. The Committee expects that economic conditions will evolve in a manner that will warrant gradual increases in the federal funds rate; the federal funds rate is likely to remain, for some time, below levels that are expected to prevail in the longer run. However, the actual path of the federal funds rate will depend on the economic outlook as informed by incoming data.

In October, the Committee will initiate the balance sheet normalization program described in the June 2017 Addendum to the Committee's Policy Normalization Principles and Plans.

Voting for the FOMC monetary policy action were: Janet L. Yellen, Chair; William C. Dudley, Vice Chairman; Lael Brainard; Charles L. Evans; Stanley Fischer; Patrick Harker; Robert S. Kaplan; Neel Kashkari; and Jerome H. Powell.

Implementation Note issued September 20, 2017

There are several important issues in this statement.

1. Mandate. The FOMC pursues a policy of attaining its “dual mandate” of (http://www.federalreserve.gov/aboutthefed/mission.htm): “Conducting the nation's monetary policy by influencing the monetary and credit conditions in the economy in pursuit of maximum employment, stable prices, and moderate long-term interest rates.”

2. Initiation of Balance Sheet Normalization. “In October, the Committee will initiate the balance sheet normalization program described in the June 2017 Addendum to the Committee's Policy Normalization Principles and Plans.”

3. Unchanged Policy Interest Rates: “In view of realized and expected labor market conditions and inflation, the Committee decided to maintain the target range for the federal funds rate at 1 to 1-1/4 percent. The stance of monetary policy remains accommodative, thereby supporting some further strengthening in labor market conditions and a sustained return to 2 percent inflation.”

4. New Advance Guidance. “In determining the timing and size of future adjustments to the target range for the federal funds rate, the Committee will assess realized and expected economic conditions relative to its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial and international developments. The Committee will carefully monitor actual and expected inflation developments relative to its symmetric inflation goal. The Committee expects that economic conditions will evolve in a manner that will warrant gradual increases in the federal funds rate; the federal funds rate is likely to remain, for some time, below levels that are expected to prevail in the longer run. However, the actual path of the federal funds rate will depend on the economic outlook as informed by incoming data” (emphasis added).

5. Policy Commitment with Maximum Employment. “In determining the timing and size of future adjustments to the target range for the federal funds rate, the Committee will assess realized and expected economic conditions relative to its objectives of maximum employment and 2 percent inflation.”

6. Concern with Inflation and Symmetric Inflation Goal. “Near-term risks to the economic outlook appear roughly balanced, but the Committee is monitoring inflation developments closely” (emphasis added).

7. All Measures Depend on Data. “However, the actual path of the federal funds rate will depend on the economic outlook as informed by incoming data” (emphasis added).

Focus is shifting from tapering quantitative easing by the Federal Open Market Committee (FOMC). There is sharp distinction between the two measures of unconventional monetary policy: (1) fixing of the overnight rate of fed funds now currently at 1 to 1 ¼ percent and (2) outright purchase of Treasury and agency securities and mortgage-backed securities for the balance sheet of the Federal Reserve. Markets overreacted to the so-called “paring” of outright purchases to $25 billion of securities per month for the balance sheet of the Fed. What is truly important is the fixing of the overnight fed funds at 1 to 1 ¼ percent with gradual consideration of further rate increases with all measures depending on “incoming data” (https://www.federalreserve.gov/newsevents/pressreleases/monetary20170920a.htm): “In determining the timing and size of future adjustments to the target range for the federal funds rate, the Committee will assess realized and expected economic conditions relative to its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial and international developments. The Committee will carefully monitor actual and expected inflation developments relative to its symmetric inflation goal. The Committee expects that economic conditions will evolve in a manner that will warrant gradual increases in the federal funds rate; the federal funds rate is likely to remain, for some time, below levels that are expected to prevail in the longer run. However, the actual path of the federal funds rate will depend on the economic outlook as informed by incoming data” (emphasis added). The FOMC is initiating the “normalization” or reduction of the balance sheet of securities held outright for monetary policy.

How long is “considerable time”? At the press conference following the meeting on Mar 19, 2014, Chair Yellen answered a question of Jon Hilsenrath of the Wall Street Journal explaining “In particular, the Committee has endorsed the view that it anticipates that will be a considerable period after the asset purchase program ends before it will be appropriate to begin to raise rates. And of course on our present path, well, that's not utterly preset. We would be looking at next, next fall. So, I think that's important guidance” (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20140319.pdf). Many focused on “next fall,” ignoring that the path of increasing rates is not “utterly preset.”

At the press conference following the meeting on Dec 17, 2014, Chair Yellen answered a question by Jon Hilseranth of the Wall Street Journal explaining “patience” (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20141217.pdf):

“So I did say that this statement that the committee can be patient should be interpreted as meaning that it is unlikely to begin the normalization process, for at least the next couple of meetings. Now that doesn't point to any preset or predetermined time at which normalization is -- will begin. There are a range of views on the committee, and it will be dependent on how incoming data bears on the progress, the economy is making. First of all, I want to emphasize that no meeting is completely off the table in the sense that if we do see faster progress toward our objectives than we currently expect, then it is possible that the process of normalization would occur sooner than we now anticipated. And of course the converse is also true. So at this point, we think it unlikely that it will be appropriate, that we will see conditions for at least the next couple of meetings that will make it appropriate for us to decide to begin normalization. A number of committee participants have indicated that in their view, conditions could be appropriate by the middle of next year. But there is no preset time.”

Chair Yellen explained the removal of the word “patience” from the advanced guidance at the press conference following the FOMC meeting on Mar 18, 2015(http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20150318.pdf):

“In other words, just because we removed the word “patient” from the statement doesn’t mean we are going to be impatient. Moreover, even after the initial increase in the target funds rate, our policy is likely to remain highly accommodative to support continued progress toward our objectives of maximum employment and 2 percent inflation.”

At a speech on Mar 31, 2014, Chair Yellen analyzed labor market conditions as follows (http://www.federalreserve.gov/newsevents/speech/yellen20140331a.htm):

“And based on the evidence available, it is clear to me that the U.S. economy is still considerably short of the two goals assigned to the Federal Reserve by the Congress. The first of those goals is maximum sustainable employment, the highest level of employment that can be sustained while maintaining a stable inflation rate. Most of my colleagues on the Federal Open Market Committee and I estimate that the unemployment rate consistent with maximum sustainable employment is now between 5.2 percent and 5.6 percent, well below the 6.7 percent rate in February.

Let me explain what I mean by that word "slack" and why it is so important.

Slack means that there are significantly more people willing and capable of filling a job than there are jobs for them to fill. During a period of little or no slack, there still may be vacant jobs and people who want to work, but a large share of those willing to work lack the skills or are otherwise not well suited for the jobs that are available. With 6.7 percent unemployment, it might seem that there must be a lot of slack in the U.S. economy, but there are reasons why that may not be true.”

Yellen (2014Aug22) provides comprehensive review of the theory and measurement of labor markets. Monetary policy pursues a policy of attaining its “dual mandate” of (http://www.federalreserve.gov/aboutthefed/mission.htm):

“Conducting the nation's monetary policy by influencing the monetary and credit conditions in the economy in pursuit of maximum employment, stable prices, and moderate long-term interest rates”

Yellen (2014Aug22) finds that the unemployment rate is not sufficient in determining slack:

“One convenient way to summarize the information contained in a large number of indicators is through the use of so-called factor models. Following this methodology, Federal Reserve Board staff developed a labor market conditions index from 19 labor market indicators, including four I just discussed. This broadly based metric supports the conclusion that the labor market has improved significantly over the past year, but it also suggests that the decline in the unemployment rate over this period somewhat overstates the improvement in overall labor market conditions.”

Yellen (2014Aug22) restates that the FOMC determines monetary policy on newly available information and interpretation of labor markets and inflation and does not follow a preset path:

“But if progress in the labor market continues to be more rapid than anticipated by the Committee or if inflation moves up more rapidly than anticipated, resulting in faster convergence toward our dual objectives, then increases in the federal funds rate target could come sooner than the Committee currently expects and could be more rapid thereafter. Of course, if economic performance turns out to be disappointing and progress toward our goals proceeds more slowly than we expect, then the future path of interest rates likely would be more accommodative than we currently anticipate. As I have noted many times, monetary policy is not on a preset path. The Committee will be closely monitoring incoming information on the labor market and inflation in determining the appropriate stance of monetary policy.”

Yellen (2014Aug22) states that “Historically, slack has accounted for only a small portion of the fluctuations in inflation. Indeed, unusual aspects of the current recovery may have shifted the lead-lag relationship between a tightening labor market and rising inflation pressures in either direction.”

The minutes of the meeting of the Federal Open Market Committee (FOMC) on Sep 16-17, 2014, reveal concern with global economic conditions (http://www.federalreserve.gov/monetarypolicy/fomcminutes20140917.htm):

“Most viewed the risks to the outlook for economic activity and the labor market as broadly balanced. However, a number of participants noted that economic growth over the medium term might be slower than they expected if foreign economic growth came in weaker than anticipated, structural productivity continued to increase only slowly, or the recovery in residential construction continued to lag.”

There is similar concern in the minutes of the meeting of the FOMC on Dec 16-17, 2014 (http://www.federalreserve.gov/monetarypolicy/fomcminutes20141217.htm):

“In their discussion of the foreign economic outlook, participants noted that the implications of the drop in crude oil prices would differ across regions, especially if the price declines affected inflation expectations and financial markets; a few participants said that the effect on overseas employment and output as a whole was likely to be positive. While some participants had lowered their assessments of the prospects for global economic growth, several noted that the likelihood of further responses by policymakers abroad had increased. Several participants indicated that they expected slower economic growth abroad to negatively affect the U.S. economy, principally through lower net exports, but the net effect of lower oil prices on U.S. economic activity was anticipated to be positive.”

Chair Yellen analyzes the view of inflation (http://www.federalreserve.gov/newsevents/speech/yellen20140416a.htm):

“Inflation, as measured by the price index for personal consumption expenditures, has slowed from an annual rate of about 2-1/2 percent in early 2012 to less than 1 percent in February of this year. This rate is well below the Committee's 2 percent longer-run objective. Many advanced economies are observing a similar softness in inflation.

To some extent, the low rate of inflation seems due to influences that are likely to be temporary, including a deceleration in consumer energy prices and outright declines in core import prices in recent quarters. Longer-run inflation expectations have remained remarkably steady, however. We anticipate that, as the effects of transitory factors subside and as labor market gains continue, inflation will gradually move back toward 2 percent.”

There is a critical phrase in the statement of Sep 19, 2013 (http://www.federalreserve.gov/newsevents/press/monetary/20130918a.htm): “but mortgage rates have risen further.” Did the increase of mortgage rates influence the decision of the FOMC not to taper? Is FOMC “communication” and “guidance” successful? Will the FOMC increase purchases of mortgage-backed securities if mortgage rates increase?

A competing event is the high level of valuations of risk financial assets (http://cmpassocregulationblog.blogspot.com/2017/01/unconventional-monetary-policy-and.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/unconventional-monetary-policy-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/peaking-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/theory-and-reality-of-secular.html). Matt Jarzemsky, writing on “Dow industrials set record,” on Mar 5, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324156204578275560657416332.html), analyzes that the DJIA broke the closing high of 14,164.53 set on Oct 9, 2007, and subsequently also broke the intraday high of 14,198.10 reached on Oct 11, 2007. The DJIA closed at 23,434.19 on Oct 27, 2017, which is higher by 65.4 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 65.1 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial assets have been approaching or exceeding historical highs.

Perhaps one of the most critical statements on policy is the answer to a question of Peter Barnes by Chair Janet Yellen at the press conference following the meeting on Jun 18, 2014 (page 19 at http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20140618.pdf):

So I don't have a sense--the committee doesn't try to gauge what is the right level of equity prices. But we do certainly monitor a number of different metrics that give us a feeling for where valuations are relative to things like earnings or dividends, and look at where these metrics stand in comparison with previous history to get a sense of whether or not we're moving to valuation levels that are outside of historical norms, and I still don't see that. I still don't see that for equity prices broadly” (emphasis added).

In a speech at the IMF on Jul 2, 2014, Chair Yellen analyzed the link between monetary policy and financial risks (http://www.federalreserve.gov/newsevents/speech/yellen20140702a.htm):

“Monetary policy has powerful effects on risk taking. Indeed, the accommodative policy stance of recent years has supported the recovery, in part, by providing increased incentives for households and businesses to take on the risk of potentially productive investments. But such risk-taking can go too far, thereby contributing to fragility in the financial system. This possibility does not obviate the need for monetary policy to focus primarily on price stability and full employment--the costs to society in terms of deviations from price stability and full employment that would arise would likely be significant. In the private sector, key vulnerabilities included high levels of leverage, excessive dependence on unstable short-term funding, weak underwriting of loans, deficiencies in risk measurement and risk management, and the use of exotic financial instruments that redistributed risk in nontransparent ways.”

Yellen (2014Jul14) warned again at the Committee on Banking, Housing and Urban Affairs on Jul 15, 2014:

“The Committee recognizes that low interest rates may provide incentives for some investors to “reach for yield,” and those actions could increase vulnerabilities in the financial system to adverse events. While prices of real estate, equities, and corporate bonds have risen appreciably and valuation metrics have increased, they remain generally in line with historical norms. In some sectors, such as lower-rated corporate debt, valuations appear stretched and issuance has been brisk. Accordingly, we are closely monitoring developments in the leveraged loan market and are working to enhance the effectiveness of our supervisory guidance. More broadly, the financial sector has continued to become more resilient, as banks have continued to boost their capital and liquidity positions, and growth in wholesale short-term funding in financial markets has been modest” (emphasis added).

Greenspan (1996) made similar warnings:

“Clearly, sustained low inflation implies less uncertainty about the future, and lower risk premiums imply higher prices of stocks and other earning assets. We can see that in the inverse relationship exhibited by price/earnings ratios and the rate of inflation in the past. But how do we know when irrational exuberance has unduly escalated asset values, which then become subject to unexpected and prolonged contractions as they have in Japan over the past decade? And how do we factor that assessment into monetary policy? We as central bankers need not be concerned if a collapsing financial asset bubble does not threaten to impair the real economy, its production, jobs, and price stability. Indeed, the sharp stock market break of 1987 had few negative consequences for the economy. But we should not underestimate or become complacent about the complexity of the interactions of asset markets and the economy. Thus, evaluating shifts in balance sheets generally, and in asset prices particularly, must be an integral part of the development of monetary policy” (emphasis added).

Bernanke (2010WP) and Yellen (2011AS) reveal the emphasis of monetary policy on the impact of the rise of stock market valuations in stimulating consumption by wealth effects on household confidence. What is the success in evaluating deviations of valuations of risk financial assets from “historical norms”? What are the consequences on economic activity and employment of deviations of valuations of risk financial assets from those “historical norms”? What are the policy tools and their effectiveness in returning valuations of risk financial assets to their “historical norms”?

The key policy is maintaining fed funds rate between 0 and ¼ percent. An increase in fed funds rates could cause flight out of risk financial markets worldwide. There is no exit from this policy without major financial market repercussions. There are high costs and risks of this policy because indefinite financial repression induces carry trades with high leverage, risks and illiquidity.

The Communiqué of the Istanbul meeting of G20 Finance Ministers and Central Bank Governors on February 10, 2015, sanctions the need of unconventional monetary policy with warning on collateral effects (http://www.g20.utoronto.ca/2015/150210-finance.html):

“We agree that consistent with central banks' mandates, current economic conditions require accommodative monetary policies in some economies. In this regard, we welcome that central banks take appropriate monetary policy action. The recent policy decision by the ECB aims at fulfilling its price stability mandate, and will further support the recovery in the euro area. We also note that some advanced economies with stronger growth prospects are moving closer to conditions that would allow for policy normalization. In an environment of diverging monetary policy settings and rising financial market volatility, policy settings should be carefully calibrated and clearly communicated to minimize negative spillovers.”

Professor Raguram G Rajan, former governor of the Reserve Bank of India, which is India’s central bank, warned about risks in high valuations of asset prices in an interview with Christopher Jeffery of Central Banking Journal on Aug 6, 2014 (http://www.centralbanking.com/central-banking-journal/interview/2358995/raghuram-rajan-on-the-dangers-of-asset-prices-policy-spillovers-and-finance-in-india). Professor Rajan demystifies in the interview “competitive easing” by major central banks as equivalent to competitive devaluation. Rajan (2005) anticipated the risks of the world financial crisis. Professor John B. Taylor (2016Dec 7, 2016Dec20), in Testimony to the Subcommittee on Monetary Policy and Trade Committee on Financial Services, on Dec 7, 2016, analyzes the adverse effects of unconventional monetary policy:

“My research and that of others over the years shows that these policies were not effective, and may have been counterproductive. Economic growth was consistently below the Fed’s forecasts with the policies, and was much weaker than in earlier U.S. recoveries from deep recessions. Job growth has been insufficient to raise the percentage of the population that is working above pre-recession levels. There is a growing consensus that the extra low interest rates and unconventional monetary policy have reached diminishing or negative returns. Many have argued that these policies widen the income distribution, adversely affect savers, and increase the volatility of the dollar exchange rate. Experienced market participants have expressed concerns about bubbles, imbalances, and distortions caused by the policies. The unconventional policies have also raised public policy concerns about the Fed being transformed into a multipurpose institution, intervening in particular sectors and allocating credit, areas where Congress may have a role, but not a limited-purpose independent agency of government.”

Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html).

The key policy is maintaining fed funds rate between 1 and 1 ½ percent. Accelerated increase in fed funds rates could cause flight out of risk financial markets worldwide. There is no exit from this policy without major financial market repercussions. There are high costs and risks of this policy because indefinite financial repression induces carry trades with high leverage, risks and illiquidity.

The FOMC provides guidelines on the process of normalization of monetary policy at the meeting on Dec 16, 2015 (http://www.federalreserve.gov/newsevents/press/monetary/20151216a1.htm):

“The Federal Reserve has made the following decisions to implement the monetary policy stance announced by the Federal Open Market Committee in its statement on December 16, 2015:

The Board of Governors of the Federal Reserve System voted unanimously to raise the interest rate paid on required and excess reserve balances to 0.50 percent, effective December 17, 2015.
As part of its policy decision, the Federal Open Market Committee voted to authorize and direct the Open Market Desk at the Federal Reserve Bank of New York, until instructed otherwise, to execute transactions in the System Open Market Account in accordance with the following domestic policy directive:¹

"Effective December 17, 2015, the Federal Open Market Committee directs the Desk to undertake open market operations as necessary to maintain the federal funds rate in a target range of 1/4 to 1/2 percent, including: (1) overnight reverse repurchase operations (and reverse repurchase operations with maturities of more than one day when necessary to accommodate weekend, holiday, or similar trading conventions) at an offering rate of 0.25 percent, in amounts limited only by the value of Treasury securities held outright in the System Open Market Account that are available for such operations and by a per-counterparty limit of $30 billion per day; and (2) term reverse repurchase operations to the extent approved in the resolution on term RRP operations approved by the Committee at its March 17-18, 2015, meeting.

The Committee directs the Desk to continue rolling over maturing Treasury securities at auction and to continue reinvesting principal payments on all agency debt and agency mortgage-backed securities in agency mortgage-backed securities. The Committee also directs the Desk to engage in dollar roll and coupon swap transactions as necessary to facilitate settlement of the Federal Reserve's agency mortgage-backed securities transactions."

More information regarding open market operations may be found on the Federal Reserve Bank of New York's website.

In a related action, the Board of Governors of the Federal Reserve System voted unanimously to approve a 1/4 percentage point increase in the discount rate (the primary credit rate) to 1.00 percent, effective December 17, 2015. In taking this action, the Board approved requests submitted by the Boards of Directors of the Federal Reserve Banks of Boston, Philadelphia, Cleveland, Richmond, Atlanta, Chicago, St. Louis, Kansas City, Dallas, and San Francisco.

This information will be updated as appropriate to reflect decisions of the Federal Open Market Committee or the Board of Governors regarding details of the Federal Reserve's operational tools and approach used to implement monetary policy.”

In the Semiannual Monetary Policy Report to Congress on Feb 24, 2015, Chair Yellen analyzes the timing of interest rate increases (http://www.federalreserve.gov/newsevents/testimony/yellen20150224a.htm):

“The FOMC's assessment that it can be patient in beginning to normalize policy means that the Committee considers it unlikely that economic conditions will warrant an increase in the target range for the federal funds rate for at least the next couple of FOMC meetings. If economic conditions continue to improve, as the Committee anticipates, the Committee will at some point begin considering an increase in the target range for the federal funds rate on a meeting-by-meeting basis. Before then, the Committee will change its forward guidance. However, it is important to emphasize that a modification of the forward guidance should not be read as indicating that the Committee will necessarily increase the target range in a couple of meetings. Instead the modification should be understood as reflecting the Committee's judgment that conditions have improved to the point where it will soon be the case that a change in the target range could be warranted at any meeting. Provided that labor market conditions continue to improve and further improvement is expected, the Committee anticipates that it will be appropriate to raise the target range for the federal funds rate when, on the basis of incoming data, the Committee is reasonably confident that inflation will move back over the medium term toward our 2 percent objective.”

In testimony on the Semiannual Monetary Policy Report to the Congress before the Committee on Financial Services, US House of Representatives, on Feb 11, 2014, Chair Janet Yellen states (http://www.federalreserve.gov/newsevents/testimony/yellen20140211a.htm):

“Turning to monetary policy, let me emphasize that I expect a great deal of continuity in the FOMC's approach to monetary policy. I served on the Committee as we formulated our current policy strategy and I strongly support that strategy, which is designed to fulfill the Federal Reserve's statutory mandate of maximum employment and price stability. If incoming information broadly supports the Committee's expectation of ongoing improvement in labor market conditions and inflation moving back toward its longer-run objective, the Committee will likely reduce the pace of asset purchases in further measured steps at future meetings. That said, purchases are not on a preset course, and the Committee's decisions about their pace will remain contingent on its outlook for the labor market and inflation as well as its assessment of the likely efficacy and costs of such purchases. In December of last year and again this January, the Committee said that its current expectation--based on its assessment of a broad range of measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial developments--is that it likely will be appropriate to maintain the current target range for the federal funds rate well past the time that the unemployment rate declines below 6-1/2 percent, especially if projected inflation continues to run below the 2 percent goal. I am committed to achieving both parts of our dual mandate: helping the economy return to full employment and returning inflation to 2 percent while ensuring that it does not run persistently above or below that level (emphasis added).”

At the confirmation hearing on nomination for Chair of the Board of Governors of the Federal Reserve System, Vice Chair Yellen (2013Nov14 http://www.federalreserve.gov/newsevents/testimony/yellen20131114a.htm), states needs and intentions of policy:

“We have made good progress, but we have farther to go to regain the ground lost in the crisis and the recession. Unemployment is down from a peak of 10 percent, but at 7.3 percent in October, it is still too high, reflecting a labor market and economy performing far short of their potential. At the same time, inflation has been running below the Federal Reserve's goal of 2 percent and is expected to continue to do so for some time.

For these reasons, the Federal Reserve is using its monetary policy tools to promote a more robust recovery. A strong recovery will ultimately enable the Fed to reduce its monetary accommodation and reliance on unconventional policy tools such as asset purchases. I believe that supporting the recovery today is the surest path to returning to a more normal approach to monetary policy.”

In testimony before the Committee on the Budget of the US Senate on May 8, 2004, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm):

“The economy has continued to recover from the steep recession of 2008 and 2009. Real gross domestic product (GDP) growth stepped up to an average annual rate of about 3-1/4 percent over the second half of last year, a faster pace than in the first half and during the preceding two years. Although real GDP growth is currently estimated to have paused in the first quarter of this year, I see that pause as mostly reflecting transitory factors, including the effects of the unusually cold and snowy winter weather. With the harsh winter behind us, many recent indicators suggest that a rebound in spending and production is already under way, putting the overall economy on track for solid growth in the current quarter. One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.

Conditions in the labor market have continued to improve. The unemployment rate was 6.3 percent in April, about 1-1/4 percentage points below where it was a year ago. Moreover, gains in payroll employment averaged nearly 200,000 jobs per month over the past year. During the economic recovery so far, payroll employment has increased by about 8-1/2 million jobs since its low point, and the unemployment rate has declined about 3-3/4 percentage points since its peak.

While conditions in the labor market have improved appreciably, they are still far from satisfactory. Even with recent declines in the unemployment rate, it continues to be elevated. Moreover, both the share of the labor force that has been unemployed for more than six months and the number of individuals who work part time but would prefer a full-time job are at historically high levels. In addition, most measures of labor compensation have been rising slowly--another signal that a substantial amount of slack remains in the labor market.

Inflation has been quite low even as the economy has continued to expand. Some of the factors contributing to the softness in inflation over the past year, such as the declines seen in non-oil import prices, will probably be transitory. Importantly, measures of longer-run inflation expectations have remained stable. That said, the Federal Open Market Committee (FOMC) recognizes that inflation persistently below 2 percent--the rate that the Committee judges to be most consistent with its dual mandate--could pose risks to economic performance, and we are monitoring inflation developments closely.

Looking ahead, I expect that economic activity will expand at a somewhat faster pace this year than it did last year, that the unemployment rate will continue to decline gradually, and that inflation will begin to move up toward 2 percent. A faster rate of economic growth this year should be supported by reduced restraint from changes in fiscal policy, gains in household net worth from increases in home prices and equity values, a firming in foreign economic growth, and further improvements in household and business confidence as the economy continues to strengthen. Moreover, U.S. financial conditions remain supportive of growth in economic activity and employment.”

In his classic restatement of the Keynesian demand function in terms of “liquidity preference as behavior toward risk,” James Tobin (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/1981/tobin-bio.html) identifies the risks of low interest rates in terms of portfolio allocation (Tobin 1958, 86):

“The assumption that investors expect on balance no change in the rate of interest has been adopted for the theoretical reasons explained in section 2.6 rather than for reasons of realism. Clearly investors do form expectations of changes in interest rates and differ from each other in their expectations. For the purposes of dynamic theory and of analysis of specific market situations, the theories of sections 2 and 3 are complementary rather than competitive. The formal apparatus of section 3 will serve just as well for a non-zero expected capital gain or loss as for a zero expected value of g. Stickiness of interest rate expectations would mean that the expected value of g is a function of the rate of interest r, going down when r goes down and rising when r goes up. In addition to the rotation of the opportunity locus due to a change in r itself, there would be a further rotation in the same direction due to the accompanying change in the expected capital gain or loss. At low interest rates expectation of capital loss may push the opportunity locus into the negative quadrant, so that the optimal position is clearly no consols, all cash. At the other extreme, expectation of capital gain at high interest rates would increase sharply the slope of the opportunity locus and the frequency of no cash, all consols positions, like that of Figure 3.3. The stickier the investor's expectations, the more sensitive his demand for cash will be to changes in the rate of interest (emphasis added).”

Tobin (1969) provides more elegant, complete analysis of portfolio allocation in a general equilibrium model. The major point is equally clear in a portfolio consisting of only cash balances and a perpetuity or consol. Let g be the capital gain, r the rate of interest on the consol and r^e the expected rate of interest. The rates are expressed as proportions. The price of the consol is the inverse of the interest rate, (1+r^e). Thus, g = [(r/r^e) – 1]. The critical analysis of Tobin is that at extremely low interest rates there is only expectation of interest rate increases, that is, dr^e>0, such that there is expectation of capital losses on the consol, dg<0. Investors move into positions combining only cash and no consols. Valuations of risk financial assets would collapse in reversal of long positions in carry trades with short exposures in a flight to cash. There is no exit from a central bank created liquidity trap without risks of financial crash and another global recession. The net worth of the economy depends on interest rates. In theory, “income is generally defined as the amount a consumer unit could consume (or believe that it could) while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is a flow that is obtained by applying a rate of return, r, to a stock of wealth, W, or Y = rW (Ibid). According to a subsequent statement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption is the long-run expected yield from wealth r*W. This yield was named permanent income: Y* = r*W” (Darby 1974, 229), where * denotes permanent. The simplified relation of income and wealth can be restated as:

W = Y/r (10

Equation (1) shows that as r goes to zero, r→0, W grows without bound, W→∞. Unconventional monetary policy lowers interest rates to increase the present value of cash flows derived from projects of firms, creating the impression of long-term increase in net worth. An attempt to reverse unconventional monetary policy necessarily causes increases in interest rates, creating the opposite perception of declining net worth. As r→∞, W = Y/r →0. There is no exit from unconventional monetary policy without increasing interest rates with resulting pain of financial crisis and adverse effects on production, investment and employment.

In delivering the biannual report on monetary policy (Board of Governors 2013Jul17), Chairman Bernanke (2013Jul17) advised Congress that:

“Instead, we are providing additional policy accommodation through two distinct yet complementary policy tools. The first tool is expanding the Federal Reserve's portfolio of longer-term Treasury securities and agency mortgage-backed securities (MBS); we are currently purchasing $40 billion per month in agency MBS and $45 billion per month in Treasuries. We are using asset purchases and the resulting expansion of the Federal Reserve's balance sheet primarily to increase the near-term momentum of the economy, with the specific goal of achieving a substantial improvement in the outlook for the labor market in a context of price stability. We have made some progress toward this goal, and, with inflation subdued, we intend to continue our purchases until a substantial improvement in the labor market outlook has been realized. We are relying on near-zero short-term interest rates, together with our forward guidance that rates will continue to be exceptionally low--our second tool--to help maintain a high degree of monetary accommodation for an extended period after asset purchases end, even as the economic recovery strengthens and unemployment declines toward more-normal levels. In appropriate combination, these two tools can provide the high level of policy accommodation needed to promote a stronger economic recovery with price stability.

The Committee's decisions regarding the asset purchase program (and the overall stance of monetary policy) depend on our assessment of the economic outlook and of the cumulative progress toward our objectives. Of course, economic forecasts must be revised when new information arrives and are thus necessarily provisional.”

Friedman (1953) argues there are three lags in effects of monetary policy: (1) between the need for action and recognition of the need; (2) the recognition of the need and taking of actions; and (3) taking of action and actual effects. Friedman (1953) finds that the combination of these lags with insufficient knowledge of the current and future behavior of the economy causes discretionary economic policy to increase instability of the economy or standard deviations of real income σ_y and prices σ_p. Policy attempts to circumvent the lags by policy impulses based on forecasts. We are all naïve about forecasting. Data are available with lags and revised to maintain high standards of estimation. Policy simulation models estimate economic relations with structures prevailing before simulations of policy impulses such that parameters change as discovered by Lucas (1977). Economic agents adjust their behavior in ways that cause opposite results from those intended by optimal control policy as discovered by Kydland and Prescott (1977). Advance guidance attempts to circumvent expectations by economic agents that could reverse policy impulses but is of dubious effectiveness. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html).

The key policy is maintaining the fed funds rate between 1 and 1¼ percent with gradual increases. Accelerated increase in fed funds rates could cause flight out of risk financial markets worldwide. There is no exit from this policy without major financial market repercussions. Indefinite financial repression induces carry trades with high leverage, risks and illiquidity.

Unconventional monetary policy drives wide swings in allocations of positions into risk financial assets that generate instability instead of intended pursuit of prosperity without inflation. There is insufficient knowledge and imperfect tools to maintain the gap of actual relative to potential output constantly at zero while restraining inflation in an open interval of (1.99, 2.0). Symmetric targets appear to have been abandoned in favor of a self-imposed single jobs mandate of easing monetary policy even with the economy growing at or close to potential output that is actually a target of growth forecast. The impact on the overall economy and the financial system of errors of policy are magnified by large-scale policy doses of trillions of dollars of quantitative easing and zero interest rates. The US economy has been experiencing financial repression as a result of negative real rates of interest during nearly a decade and programmed in monetary policy statements until 2015 or, for practical purposes, forever. The essential calculus of risk/return in capital budgeting and financial allocations has been distorted. If economic perspectives are doomed until 2015 such as to warrant zero interest rates and open-ended bond-buying by “printing” digital bank reserves (http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html; see Shultz et al 2012), rational investors and consumers will not invest and consume until just before interest rates are likely to increase. Monetary policy statements on intentions of zero interest rates for another three years or now virtually forever discourage investment and consumption or aggregate demand that can increase economic growth and generate more hiring and opportunities to increase wages and salaries. The doom scenario used to justify monetary policy accentuates adverse expectations on discounted future cash flows of potential economic projects that can revive the economy and create jobs. If it were possible to project the future with the central tendency of the monetary policy scenario and monetary policy tools do exist to reverse this adversity, why the tools have not worked before and even prevented the financial crisis? If there is such thing as “monetary policy science”, why it has such poor record and current inability to reverse production and employment adversity? There is no excuse of arguing that additional fiscal measures are needed because they were deployed simultaneously with similar ineffectiveness. Jon Hilsenrath, writing on “New view into Fed’s response to crisis,” on Feb 21, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303775504579396803024281322?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes 1865 pages of transcripts of eight formal and six emergency policy meetings at the Fed in 2008 (http://www.federalreserve.gov/monetarypolicy/fomchistorical2008.htm). If there were an infallible science of central banking, models and forecasts would provide accurate information to policymakers on the future course of the economy in advance. Such forewarning is essential to central bank science because of the long lag between the actual impulse of monetary policy and the actual full effects on income and prices many months and even years ahead (Romer and Romer 2004, Friedman 1961, 1953, Culbertson 1960, 1961, Batini and Nelson 2002). The transcripts of the Fed meetings in 2008 (http://www.federalreserve.gov/monetarypolicy/fomchistorical2008.htm) analyzed by Jon Hilsenrath demonstrate that Fed policymakers frequently did not understand the current state of the US economy in 2008 and much less the direction of income and prices. The conclusion of Friedman (1953) is that monetary impulses increase financial and economic instability because of lags in anticipating needs of policy, taking policy decisions and effects of decisions. This is a fortiori true when untested unconventional monetary policy in gargantuan doses shocks the economy and financial markets.

In remarkable anticipation in 2005, Professor Raghuram G. Rajan (2005) warned of low liquidity and high risks of central bank policy rates approaching the zero bound (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 218-9). Professor Rajan excelled in a distinguished career as an academic economist in finance and was chief economist of the International Monetary Fund (IMF). Shefali Anand and Jon Hilsenrath, writing on Oct 13, 2013, on “India’s central banker lobbies Fed,” published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304330904579133530766149484?KEYWORDS=Rajan), interviewed Raghuram G Rajan, who is the current Governor of the Reserve Bank of India, which is India’s central bank (http://www.rbi.org.in/scripts/AboutusDisplay.aspx). In this interview, Rajan argues that central banks should avoid unintended consequences on emerging market economies of inflows and outflows of capital triggered by monetary policy. Portfolio reallocations induced by combination of zero interest rates and risk events stimulate carry trades that generate wide swings in world capital flows. Professor Rajan, in an interview with Kartik Goyal of Bloomberg (http://www.bloomberg.com/news/2014-01-30/rajan-warns-of-global-policy-breakdown-as-emerging-markets-slide.html), warns of breakdown of global policy coordination. Professor Raguram G Rajan, former governor of the Reserve Bank of India, which is India’s central bank, warned about risks in high valuations of asset prices in an interview with Christopher Jeffery of Central Banking Journal on Aug 6, 2014 (http://www.centralbanking.com/central-banking-journal/interview/2358995/raghuram-rajan-on-the-dangers-of-asset-prices-policy-spillovers-and-finance-in-india). Professor Rajan demystifies in the interview “competitive easing” by major central banks as equivalent to competitive devaluation.

The Swiss National Bank (SNB) announced on Jan 15, 2015, the termination of its peg of the exchange rate of the Swiss franc to the euro (http://www.snb.ch/en/mmr/speeches/id/ref_20150115_tjn/source/ref_20150115_tjn.en.pdf):

“The Swiss National Bank (SNB) has decided to discontinue the minimum exchange rate of

CHF 1.20 per euro with immediate effect and to cease foreign currency purchases associated with enforcing it.”

The SNB also lowered interest rates to nominal negative percentages (http://www.snb.ch/en/mmr/speeches/id/ref_20150115_tjn/source/ref_20150115_tjn.en.pdf):

“At the same time as discontinuing the minimum exchange rate, the SNB will be lowering the interest rate for balances held on sight deposit accounts to –0.75% from 22 January. The exemption thresholds remain unchanged. Further lowering the interest rate makes Swiss-franc investments considerably less attractive and will mitigate the effects of the decision to discontinue the minimum exchange rate. The target range for the three-month Libor is being lowered by 0.5 percentage points to between –1.25% and –0.25%.”

The Swiss franc rate relative to the euro (CHF/EUR) appreciated 18.7 percent on Jan 15, 2015. The Swiss franc rate relative to the dollar (CHF/USD) appreciated 17.7 percent. Central banks are taking measures in anticipation of the quantitative easing by the European Central Bank.

On Jan 22, 2015, the European Central Bank (ECB) decided to implement an “expanded asset purchase program” with combined asset purchases of €60 billion per month “until at least Sep 2016 (http://www.ecb.europa.eu/press/pr/date/2015/html/pr150122_1.en.html). The objective of the program is that (http://www.ecb.europa.eu/press/pr/date/2015/html/pr150122_1.en.html):

“Asset purchases provide monetary stimulus to the economy in a context where key ECB interest rates are at their lower bound. They further ease monetary and financial conditions, making access to finance cheaper for firms and households. This tends to support investment and consumption, and ultimately contributes to a return of inflation rates towards 2%.”

The President of the ECB, Mario Draghi, explains the coordination of asset purchases with NCBs (National Central Banks) of the euro area and risk sharing (http://www.ecb.europa.eu/press/pressconf/2015/html/is150122.en.html):

“In March 2015 the Eurosystem will start to purchase euro-denominated investment-grade securities issued by euro area governments and agencies and European institutions in the secondary market. The purchases of securities issued by euro area governments and agencies will be based on the Eurosystem NCBs’ shares in the ECB’s capital key. Some additional eligibility criteria will be applied in the case of countries under an EU/IMF adjustment programme. As regards the additional asset purchases, the Governing Council retains control over all the design features of the programme and the ECB will coordinate the purchases, thereby safeguarding the singleness of the Eurosystem’s monetary policy. The Eurosystem will make use of decentralised implementation to mobilise its resources. With regard to the sharing of hypothetical losses, the Governing Council decided that purchases of securities of European institutions (which will be 12% of the additional asset purchases, and which will be purchased by NCBs) will be subject to loss sharing. The rest of the NCBs’ additional asset purchases will not be subject to loss sharing. The ECB will hold 8% of the additional asset purchases. This implies that 20% of the additional asset purchases will be subject to a regime of risk sharing.”

The President of the ECB, Mario Draghi, rejected the possibility of seigniorage in the new asset purchase program, or central bank financing of fiscal expansion (http://www.ecb.europa.eu/press/pressconf/2015/html/is150122.en.html):

“As I just said, it would be a big mistake if countries were to consider that the presence of this programme might be an incentive to fiscal expansion. They would undermine the confidence, so it’s not directed to monetary financing at all. Actually, it’s been designed as to avoid any monetary financing.”

The President of the ECB, Mario Draghi, does not find effects of monetary policy in inflating asset prices (http://www.ecb.europa.eu/press/pressconf/2015/html/is150122.en.html):

“On the first question, we monitor closely any potential instance of risk to financial stability. So we're very alert to that risk. So far we don't see bubbles. There may be some local episodes of certain specific markets where prices are going up fast. But to have a bubble, besides having that, one should also identify, detect an increase, dramatic increase in leverage or in bank credit, and we don't see that now. However, we, as I said, we are alert. If bubbles are of a local nature, they should be addressed by local instruments, namely macro-prudential instruments rather than by monetary policy.”

The DAX index of German equities increased 1.3 percent on Jan 22, 2015 and 2.1 percent on Jan 23, 2015. The euro depreciated from EUR 1.1611/USD (EUR 0.8613/USD) on Wed Jan 21, 2015, to EUR 1.1206/USD (EUR 0.8924/USD) on Fri Jan 23, 2015, or 3.6 percent. Yellen (2011AS, 6) admits that Fed monetary policy results in dollar devaluation with the objective of increasing net exports, which was the policy that Joan Robinson (1947) labeled as “beggar-my-neighbor” remedies for unemployment. Risk aversion erodes devaluation of the dollar.

Dan Strumpf and Pedro Nicolaci da Costa, writing on “Fed’s Yellen: Stock Valuations ‘Generally are Quite High,’” on May 6, 2015, published in the Wall Street Journal (http://www.wsj.com/articles/feds-yellen-cites-progress-on-bank-regulation-1430918155?tesla=y ), quote Chair Yellen at open conversation with Christine Lagarde, Managing Director of the IMF, finding “equity-market valuations” as “quite high” with “potential dangers” in bond valuations. The DJIA fell 0.5 percent on May 6, 2015, after the comments and then increased 0.5 percent on May 7, 2015 and 1.5 percent on May 8, 2015.

Fri May 1

Mon 4

Tue 5

Wed 6

Thu 7

Fri 8

DJIA

18024.06

-0.3%

1.0%

18070.40

0.3%

17928.20

-0.5%

-0.8%

17841.98

-1.0%

-0.5%

17924.06

-0.6%

0.5%

18191.11

0.9%

1.5%

There are two approaches in theory considered by Bordo (2012Nov20) and Bordo and Lane (2013). The first approach is in the classical works of Milton Friedman and Anna Jacobson Schwartz (1963a, 1987) and Karl Brunner and Allan H. Meltzer (1973). There is a similar approach in Tobin (1969). Friedman and Schwartz (1963a, 66) trace the effects of expansionary monetary policy into increasing initially financial asset prices: “It seems plausible that both nonbank and bank holders of redundant balances will turn first to securities comparable to those they have sold, say, fixed-interest coupon, low-risk obligations. But as they seek to purchase these they will tend to bid up the prices of those issues. Hence they, and also other holders not involved in the initial central bank open-market transactions, will look farther afield: the banks, to their loans; the nonbank holders, to other categories of securities-higher risk fixed-coupon obligations, equities, real property, and so forth.”

The second approach is by the Austrian School arguing that increases in asset prices can become bubbles if monetary policy allows their financing with bank credit. Professor Michael D. Bordo provides clear thought and empirical evidence on the role of “expansionary monetary policy” in inflating asset prices (Bordo2012Nov20, Bordo and Lane 2013). Bordo and Lane (2013) provide revealing narrative of historical episodes of expansionary monetary policy. Bordo and Lane (2013) conclude that policies of depressing interest rates below the target rate or growth of money above the target influences higher asset prices, using a panel of 18 OECD countries from 1920 to 2011. Bordo (2012Nov20) concludes: “that expansionary money is a significant trigger” and “central banks should follow stable monetary policies…based on well understood and credible monetary rules.” Taylor (2007, 2009) explains the housing boom and financial crisis in terms of expansionary monetary policy. Professor Martin Feldstein (2016), at Harvard University, writing on “A Federal Reserve oblivious to its effects on financial markets,” on Jan 13, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/a-federal-reserve-oblivious-to-its-effect-on-financial-markets-1452729166), analyzes how unconventional monetary policy drove values of risk financial assets to high levels. Quantitative easing and zero interest rates distorted calculation of risks with resulting vulnerabilities in financial markets.

Another hurdle of exit from zero interest rates is “competitive easing” that Professor Raghuram Rajan, governor of the Reserve Bank of India, characterizes as disguised “competitive devaluation” (http://www.centralbanking.com/central-banking-journal/interview/2358995/raghuram-rajan-on-the-dangers-of-asset-prices-policy-spillovers-and-finance-in-india). The fed has been considering increasing interest rates. The European Central Bank (ECB) announced, on Mar 5, 2015, the beginning on Mar 9, 2015 of its quantitative easing program denominated as Public Sector Purchase Program (PSPP), consisting of “combined monthly purchases of EUR 60 bn [billion] in public and private sector securities” (http://www.ecb.europa.eu/mopo/liq/html/pspp.en.html). Expectation of increasing interest rates in the US together with euro rates close to zero or negative cause revaluation of the dollar (or devaluation of the euro and of most currencies worldwide). US corporations suffer currency translation losses of their foreign transactions and investments (http://www.fasb.org/jsp/FASB/Pronouncement_C/SummaryPage&cid=900000010318) while the US becomes less competitive in world trade (Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), Government Intervention in Globalization (2008c)). The DJIA fell 1.5 percent on Mar 6, 2015 and the dollar revalued 2.2 percent from Mar 5 to Mar 6, 2015. The euro has devalued 37.0 percent relative to the dollar from the high on Jul 15, 2008 to Oct 27, 2017.

Fri 27 Feb

Mon 3/2

Tue 3/3

Wed 3/4

Thu 3/5

Fri 3/6

USD/ EUR

1.1197

1.6%

0.0%

1.1185

0.1%

1.1176

0.2%

0.1%

1.1081

1.0%

0.9%

1.1030

1.5%

0.5%

1.0843

3.2%

1.7%

Chair Yellen explained the removal of the word “patience” from the advanced guidance at the press conference following the FOMC meeting on Mar 18, 2015 (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20150318.pdf):

Exchange rate volatility is increasing in response of “impatience” in financial markets with monetary policy guidance and measures:

Fri Mar 6

Mon 9

Tue 10

Wed 11

Thu 12

Fri 13

USD/ EUR

1.0843

3.2%

1.7%

1.0853

-0.1%

1.0700

1.3%

1.4%

1.0548

2.7%

1.4%

1.0637

1.9%

-0.8%

1.0497

3.2%

1.3%

Fri Mar 13

Mon 16

Tue 17

Wed 18

Thu 19

Fri 20

USD/ EUR

1.0497

3.2%

1.3%

1.0570

-0.7%

1.0598

-1.0%

-0.3%

1.0864

-3.5%

-2.5%

1.0661

-1.6%

1.9%

1.0821

-3.1%

-1.5%

Fri Apr 24

Mon 27

Tue 28

Wed 29

Thu 30

May Fri 1

USD/ EUR

1.0874

-0.6%

-0.4%

1.0891

-0.2%

1.0983

-1.0%

-0.8%

1.1130

-2.4%

-1.3%

1.1223

-3.2%

-0.8%

1.1199

-3.0%

0.2%

In a speech at Brown University on May 22, 2015, Chair Yellen stated (http://www.federalreserve.gov/newsevents/speech/yellen20150522a.htm):

“For this reason, if the economy continues to improve as I expect, I think it will be appropriate at some point this year to take the initial step to raise the federal funds rate target and begin the process of normalizing monetary policy. To support taking this step, however, I will need to see continued improvement in labor market conditions, and I will need to be reasonably confident that inflation will move back to 2 percent over the medium term. After we begin raising the federal funds rate, I anticipate that the pace of normalization is likely to be gradual. The various headwinds that are still restraining the economy, as I said, will likely take some time to fully abate, and the pace of that improvement is highly uncertain.”

The US dollar appreciated 3.8 percent relative to the euro in the week of May 22, 2015:

Fri May 15

Mon 18

Tue 19

Wed 20

Thu 21

Fri 22

USD/ EUR

1.1449

-2.2%

-0.3%

1.1317

1.2%

1.1150

2.6%

1.5%

1.1096

3.1%

0.5%

1.1113

2.9%

-0.2%

1.1015

3.8%

0.9%

The Managing Director of the International Monetary Fund (IMF), Christine Lagarde, warned on Jun 4, 2015, that: (http://blog-imfdirect.imf.org/2015/06/04/u-s-economy-returning-to-growth-but-pockets-of-vulnerability/):

“The Fed’s first rate increase in almost 9 years is being carefully prepared and telegraphed. Nevertheless, regardless of the timing, higher US policy rates could still result in significant market volatility with financial stability consequences that go well beyond US borders. I weighing these risks, we think there is a case for waiting to raise rates until there are more tangible signs of wage or price inflation than are currently evident. Even after the first rate increase, a gradual rise in the federal fund rates will likely be appropriate.”

The President of the European Central Bank (ECB), Mario Draghi, warned on Jun 3, 2015 that (http://www.ecb.europa.eu/press/pressconf/2015/html/is150603.en.html):

“But certainly one lesson is that we should get used to periods of higher volatility. At very low levels of interest rates, asset prices tend to show higher volatility…the Governing Council was unanimous in its assessment that we should look through these developments and maintain a steady monetary policy stance.”

The Chair of the Board of Governors of the Federal Reserve System, Janet L. Yellen, stated on Jul 10, 2015 that (http://www.federalreserve.gov/newsevents/speech/yellen20150710a.htm):

“Based on my outlook, I expect that it will be appropriate at some point later this year to take the first step to raise the federal funds rate and thus begin normalizing monetary policy. But I want to emphasize that the course of the economy and inflation remains highly uncertain, and unanticipated developments could delay or accelerate this first step. I currently anticipate that the appropriate pace of normalization will be gradual, and that monetary policy will need to be highly supportive of economic activity for quite some time. The projections of most of my FOMC colleagues indicate that they have similar expectations for the likely path of the federal funds rate. But, again, both the course of the economy and inflation are uncertain. If progress toward our employment and inflation goals is more rapid than expected, it may be appropriate to remove monetary policy accommodation more quickly. However, if progress toward our goals is slower than anticipated, then the Committee may move more slowly in normalizing policy.”

There is essentially the same view in the Testimony of Chair Yellen in delivering the Semiannual Monetary Policy Report to the Congress on Jul 15, 2015 (http://www.federalreserve.gov/newsevents/testimony/yellen20150715a.htm).

At the press conference after the meeting of the FOMC on Sep 17, 2015, Chair Yellen states (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20150917.pdf 4):

“The outlook abroad appears to have become more uncertain of late, and heightened concerns about growth in China and other emerging market economies have led to notable volatility in financial markets. Developments since our July meeting, including the drop in equity prices, the further appreciation of the dollar, and a widening in risk spreads, have tightened overall financial conditions to some extent. These developments may restrain U.S. economic activity somewhat and are likely to put further downward pressure on inflation in the near term. Given the significant economic and financial interconnections between the United States and the rest of the world, the situation abroad bears close watching.”

Some equity markets fell on Fri Sep 18, 2015:

Fri Sep 11

Mon 14

Tue 15

Wed 16

Thu 17

Fri 18

DJIA

16433.09

2.1%

0.6%

16370.96

-0.4%

16599.85

1.0%

1.4%

16739.95

1.9%

0.8%

16674.74

1.5%

-0.4%

16384.58

-0.3%

-1.7%

Nikkei 225

18264.22

2.7%

-0.2%

17965.70

-1.6%

18026.48

-1.3%

0.3%

18171.60

-0.5%

0.8%

18432.27

0.9%

1.4%

18070.21

-1.1%

-2.0%

DAX

10123.56

0.9%

-0.9%

10131.74

0.1%

10188.13

0.6%

10227.21

1.0%

0.4%

10229.58

1.0%

0.0%

9916.16

-2.0%

-3.1%

Frank H. Knight (1963, 233), in Risk, uncertainty and profit, distinguishes between measurable risk and unmeasurable uncertainty. Chair Yellen, in a lecture on “Inflation dynamics and monetary policy,” on Sep 24, 2015 (http://www.federalreserve.gov/newsevents/speech/yellen20150924a.htm), states that (emphasis added):

· “The economic outlook, of course, is highly uncertain”

· “Considerable uncertainties also surround the outlook for economic activity”

· “Given the highly uncertain nature of the outlook…”

Is there a “science” or even “art” of central banking under this extreme uncertainty in which policy does not generate higher volatility of money, income, prices and values of financial assets?

Lingling Wei, writing on Oct 23, 2015, on China’s central bank moves to spur economic growth,” published in the Wall Street Journal (http://www.wsj.com/articles/chinas-central-bank-cuts-rates-1445601495), analyzes the reduction by the People’s Bank of China (http://www.pbc.gov.cn/ http://www.pbc.gov.cn/english/130437/index.html) of borrowing and lending rates of banks by 50 basis points and reserve requirements of banks by 50 basis points. Paul Vigna, writing on Oct 23, 2015, on “Stocks rally out of correction territory on latest central bank boost,” published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2015/10/23/stocks-rally-out-of-correction-territory-on-latest-central-bank-boost/), analyzes the rally in financial markets following the statement on Oct 22, 2015, by the President of the European Central Bank (ECB) Mario Draghi of consideration of new quantitative measures in Dec 2015 (https://www.youtube.com/watch?v=0814riKW25k&rel=0) and the reduction of bank lending/deposit rates and reserve requirements of banks by the People’s Bank of China on Oct 23, 2015. The dollar revalued 2.8 percent from Oct 21 to Oct 23, 2015, following the intended easing of the European Central Bank. The DJIA rose 2.8 percent from Oct 21 to Oct 23 and the DAX index of German equities rose 5.4 percent from Oct 21 to Oct 23, 2015.

Fri Oct 16

Mon 19

Tue 20

Wed 21

Thu 22

Fri 23

USD/ EUR

1.1350

0.1%

0.3%

1.1327

0.2%

1.1348

0.0%

-0.2%

1.1340

0.1%

1.1110

2.1%

2.0%

1.1018

2.9%

0.8%

DJIA

17215.97

0.8%

0.4%

17230.54

0.1%

17217.11

0.0%

-0.1%

17168.61

-0.3%

17489.16

1.6%

1.9%

17646.70

2.5%

0.9%

Dow Global

2421.58

0.3%

0.6%

2414.33

-0.3%

2411.03

-0.4%

-0.1%

2411.27

-0.4%

0.0%

2434.79

0.5%

1.0%

2458.13

1.5%

1.0%

DJ Asia Pacific

1402.31

1.1%

0.3%

1398.80

-0.3%

1395.06

-0.5%

-0.3%

1402.68

0.0%

0.5%

1396.03

-0.4%

-0.5%

1415.50

0.9%

1.4%

Nikkei 225

18291.80

-0.8%

1.1%

18131.23

-0.9%

18207.15

-0.5%

0.4%

18554.28

1.4%

1.9%

18435.87

0.8%

-0.6%

18825.30

2.9%

2.1%

Shanghai

3391.35

6.5%

1.6%

3386.70

-0.1%

3425.33

1.0%

1.1%

3320.68

-2.1%

-3.1%

3368.74

-0.7%

1.4%

3412.43

0.6%

1.3%

DAX

10104.43

0.1%

0.4%

10164.31

0.6%

10147.68

0.4%

-0.2%

10238.10

1.3%

0.9%

10491.97

3.8%

2.5%

10794.54

6.8%

2.9%

Ben Leubsdorf, writing on “Fed’s Yellen: December is “Live Possibility” for First Rate Increase,” on Nov 4, 2015, published in the Wall Street Journal (http://www.wsj.com/articles/feds-yellen-december-is-live-possibility-for-first-rate-increase-1446654282) quotes Chair Yellen that a rate increase in “December would be a live possibility.” The remark of Chair Yellen was during a hearing on supervision and regulation before the Committee on Financial Services, US House of Representatives (http://www.federalreserve.gov/newsevents/testimony/yellen20151104a.htm) and a day before the release of the employment situation report for Oct 2015 (Section I). The dollar revalued 2.4 percent during the week. The euro has devalued 37.0 percent relative to the dollar from the high on Jul 15, 2008 to Oct 27, 2017.

Fri Oct 30

Mon 2

Tue 3

Wed 4

Thu 5

Fri 6

USD/ EUR

1.1007

0.1%

-0.3%

1.1016

-0.1%

1.0965

0.4%

0.5%

1.0867

1.3%

0.9%

1.0884

1.1%

-0.2%

1.0742

2.4%

1.3%

The release on Nov 18, 2015 of the minutes of the FOMC (Federal Open Market Committee) meeting held on Oct 28, 2015 (http://www.federalreserve.gov/monetarypolicy/fomcminutes20151028.htm) states:

“Most participants anticipated that, based on their assessment of the current economic situation and their outlook for economic activity, the labor market, and inflation, these conditions [for interest rate increase] could well be met by the time of the next meeting. Nonetheless, they emphasized that the actual decision would depend on the implications for the medium-term economic outlook of the data received over the upcoming intermeeting period… It was noted that beginning the normalization process relatively soon would make it more likely that the policy trajectory after liftoff could be shallow.”

Markets could have interpreted a symbolic increase in the fed funds rate at the meeting of the FOMC on Dec 15-16, 2015 (http://www.federalreserve.gov/monetarypolicy/fomccalendars.htm) followed by “shallow” increases, explaining the sharp increase in stock market values and appreciation of the dollar after the release of the minutes on Nov 18, 2015:

Fri Nov 13

Mon 16

Tue 17

Wed 18

Thu 19

Fri 20

USD/ EUR

1.0774

-0.3%

0.4%

1.0686

0.8%

1.0644

1.2%

0.4%

1.0660

1.1%

-0.2%

1.0735

0.4%

-0.7%

1.0647

1.2%

0.8%

DJIA

17245.24

-3.7%

-1.2%

17483.01

1.4%

17489.50

1.4%

0.0%

17737.16

2.9%

1.4%

17732.75

2.8%

0.0%

17823.81

3.4%

0.5%

DAX

10708.40

-2.5%

-0.7%

10713.23

0.0%

10971.04

2.5%

2.4%

10959.95

2.3%

-0.1%

11085.44

3.5%

1.1%

11119.83

3.8%

0.3%

In testimony before The Joint Economic Committee of Congress on Dec 3, 2015 (http://www.federalreserve.gov/newsevents/testimony/yellen20151203a.htm), Chair Yellen reiterated that the FOMC (Federal Open Market Committee) “anticipates that even after employment and inflation are near mandate-consistent levels, economic condition may, for some time, warrant keeping the target federal funds rate below the Committee views as normal in the longer run.” Todd Buell and Katy Burne, writing on “Draghi says ECB could step up stimulus efforts if necessary,” on Dec 4, 2015, published in the Wall Street Journal (http://www.wsj.com/articles/draghi-says-ecb-could-step-up-stimulus-efforts-if-necessary-1449252934), analyze that the President of the European Central Bank (ECB), Mario Draghi, reassured financial markets that the ECB will increase stimulus if required to raise inflation the euro area to targets. The USD depreciated 3.1 percent on Thu Dec 3, 2015 after weaker than expected measures by the European Central Bank. DJIA fell 1.4 percent on Dec 3 and increased 2.1 percent on Dec 4. DAX fell 3.6 percent on Dec 3.

Fri Nov 27

Mon 30

Tue 1

Wed 2

Thu 3

Fri 4

USD/ EUR

1.0594

0.5%

0.2%

1.0565

0.3%

1.0634

-0.4%

-0.7%

1.0616

-0.2%

0.2%

1.0941

-3.3%

-3.1%

1.0885

-2.7%

0.5%

DJIA

17798.49

-0.1%

17719.92

-0.4%

17888.35

0.5%

1.0%

17729.68

-0.4%

-0.9%

17477.67

-1.8%

-1.4%

17847.63

0.3%

2.1%

DAX

11293.76

1.6%

-0.2%

11382.23

0.8%

11261.24

-0.3%

-1.1%

11190.02

-0.9%

-0.6%

10789.24

-4.5%

-3.6%

10752.10

-4.8%

-0.3%

At the press conference following the meeting of the FOMC on Dec 16, 2015, Chair Yellen states (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20151216.pdf page 8):

“And we recognize that monetary policy operates with lags. We would like to be able to move in a prudent, and as we've emphasized, gradual manner. It's been a long time since the Federal Reserve has raised interest rates, and I think it's prudent to be able to watch what the impact is on financial conditions and spending in the economy and moving in a timely fashion enables us to do this.”

The implication of this statement is that the state of the art is not accurate in analyzing the effects of monetary policy on financial markets and economic activity. The US dollar appreciated and equities fluctuated:

Fri Dec 11

Mon 14

Tue 15

Wed 16

Thu 17

Fri 18

USD/ EUR

1.0991

-1.0%

-0.4%

1.0993

0.0%

1.0932

0.5%

0.6%

1.0913

0.7%

0.2%

1.0827

1.5%

0.8%

1.0868

1.1%

-0.4%

DJIA

17265.21

-3.3%

-1.8%

17368.50

0.6%

17524.91

1.5%

0.9%

17749.09

2.8%

1.3%

17495.84

1.3%

-1.4%

17128.55

-0.8%

-2.1%

DAX

10340.06

-3.8%

-2.4%

10139.34

-1.9%

10450.38

-1.1%

3.1%

10469.26

1.2%

0.2%

10738.12

3.8%

2.6%

10608.19

2.6%

-1.2%

On January 29, 2016, the Policy Board of the Bank of Japan introduced a new policy to attain the “price stability target of 2 percent at the earliest possible time” (https://www.boj.or.jp/en/announcements/release_2016/k160129a.pdf). The new framework consists of three dimensions: quantity, quality and interest rate. The interest rate dimension consists of rates paid to current accounts that financial institutions hold at the Bank of Japan of three tiers zero, positive and minus 0.1 percent. The quantitative dimension consists of increasing the monetary base at the annual rate of 80 trillion yen. The qualitative dimension consists of purchases by the Bank of Japan of Japanese government bonds (JGBs), exchange traded funds (ETFs) and Japan real estate investment trusts (J-REITS). The yen devalued sharply relative to the dollar and world equity markets soared after the new policy announced on Jan 29, 2016:

Fri 22

Mon 25

Tue 26

Wed 27

Thu 28

Fri 29

JPY/ USD

118.77

-1.5%

-0.9%

118.30

0.4%

118.42

0.3%

-0.1%

118.68

0.1%

-0.2%

118.82

0.0%

-0.1%

121.13

-2.0%

-1.9%

DJIA

16093.51

0.7%

1.3%

15885.22

-1.3%

16167.23

0.5%

1.8%

15944.46

-0.9%

-1.4%

16069.64

-0.1%

0.8%

16466.30

2.3%

2.5%

Nikkei

16958.53

-1.1%

5.9%

17110.91

0.9%

16708.90

-1.5%

-2.3%

17163.92

1.2%

2.7%

17041.45

0.5%

-0.7%

17518.30

3.3%

2.8%

Shanghai

2916.56

0.5%

1.3

2938.51

0.8%

2749.79

-5.7%

-6.4%

2735.56

-6.2%

-0.5%

2655.66

-8.9%

-2.9%

2737.60

-6.1%

3.1%

DAX

9764.88

2.3%

2.0%

9736.15

-0.3%

9822.75

0.6%

0.9%

9880.82

1.2%

0.6%

9639.59

-1.3%

-2.4%

9798.11

0.3%

1.6%

In testimony on the Semiannual Monetary Policy Report to the Congress on Feb 10-11, 2016, Chair Yellen (http://www.federalreserve.gov/newsevents/testimony/yellen20160210a.htm) states: “U.S. real gross domestic product is estimated to have increased about 1-3/4 percent in 2015. Over the course of the year, subdued foreign growth and the appreciation of the dollar restrained net exports. In the fourth quarter of last year, growth in the gross domestic product is reported to have slowed more sharply, to an annual rate of just 3/4 percent; again, growth was held back by weak net exports as well as by a negative contribution from inventory investment.”

Jon Hilsenrath, writing on “Yellen Says Fed Should Be Prepared to Use Negative Rates if Needed,” on Feb 11, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/yellen-reiterates-concerns-about-risks-to-economy-in-senate-testimony-1455203865), analyzes the statement of Chair Yellen in Congress that the FOMC (Federal Open Market Committee) is considering negative interest rates on bank reserves. The Wall Street Journal provides yields of two and ten-year sovereign bonds with negative interest rates on shorter maturities where central banks pay negative interest rates on excess bank reserves:

Sovereign Yields 2/12/16	Japan	Germany	USA
2 Year	-0.168	-0.498	0.694
10 Year	0.076	0.262	1.744

On Mar 10, 2016, the European Central Bank (ECB) announced (1) reduction of the refinancing rate by 5 basis points to 0.00 percent; decrease the marginal lending rate to 0.25 percent; reduction of the deposit facility rate to 0,40 percent; increase of the monthly purchase of assets to €80 billion; include nonbank corporate bonds in assets eligible for purchases; and new long-term refinancing operations (https://www.ecb.europa.eu/press/pr/date/2016/html/pr160310.en.html). The President of the ECB, Mario Draghi, stated in the press conference (https://www.ecb.europa.eu/press/pressconf/2016/html/is160310.en.html): “How low can we go? Let me say that rates will stay low, very low, for a long period of time, and well past the horizon of our purchases…We don’t anticipate that it will be necessary to reduce rates further. Of course, new facts can change the situation and the outlook.”

The dollar devalued relative to the euro and open stock markets traded lower after the announcement on Mar 10, 2016, but stocks rebounded on Mar 11:

Fri 4

Mon 7

Tue 8

Wed 9

Thu10

Fri 11

USD/ EUR

1.1006

-0.7%

-0.4%

1.1012

-0.1%

1.1013

-0.1%

0.0%

1.0999

0.1%

1.1182

-1.6%

-1.7%

1.1151

-1.3%

0.3%

DJIA

17006.77

2.2%

0.4%

17073.95

0.4%

16964.10

-0.3%

-0.6%

17000.36

0.0%

0.2%

16995.13

-0.1%

0.0%

17213.31

1.2%

1.3%

DAX

9824.17

3.3%

0.7%

9778.93

-0.5%

0.5%

9692.82

-1.3%

-0.9%

9723.09

-1.0%

0.3%

9498.15

-3.3%

-2.3%

9831.13

0.1%

3.5%

At the press conference after the FOMC meeting on Sep 21, 2016, Chair Yellen states (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20160921.pdf ): “However, the economic outlook is inherently uncertain.” In the address to the Jackson Hole symposium on Aug 26, 2016, Chair Yellen states: “I believe the case for an increase in in federal funds rate has strengthened in recent months…And, as ever, the economic outlook is uncertain, and so monetary policy is not on a preset course” (http://www.federalreserve.gov/newsevents/speech/yellen20160826a.htm). In a speech at the World Affairs Council of Philadelphia, on Jun 6, 2016 (http://www.federalreserve.gov/newsevents/speech/yellen20160606a.htm), Chair Yellen finds that “there is considerable uncertainty about the economic outlook.” There are fifteen references to this uncertainty in the text of 18 pages double-spaced. In the Semiannual Monetary Policy Report to the Congress on Jun 21, 2016, Chair Yellen states (http://www.federalreserve.gov/newsevents/testimony/yellen20160621a.htm), “Of course, considerable uncertainty about the economic outlook remains.” Frank H. Knight (1963, 233), in Risk, uncertainty and profit, distinguishes between measurable risk and unmeasurable uncertainty. Is there a “science” or even “art” of central banking under this extreme uncertainty in which policy does not generate higher volatility of money, income, prices and values of financial assets?

What is truly important is the fixing of the overnight fed funds at 1 to 1 ¼ percent with gradual consideration of further rate increases with all measures depending on “incoming data” (https://www.federalreserve.gov/newsevents/pressreleases/monetary20170920a.htm): “In determining the timing and size of future adjustments to the target range for the federal funds rate, the Committee will assess realized and expected economic conditions relative to its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial and international developments. The Committee will carefully monitor actual and expected inflation developments relative to its symmetric inflation goal. The Committee expects that economic conditions will evolve in a manner that will warrant gradual increases in the federal funds rate; the federal funds rate is likely to remain, for some time, below levels that are expected to prevail in the longer run. However, the actual path of the federal funds rate will depend on the economic outlook as informed by incoming data” (emphasis added). The FOMC advised the intention to begin the “normalization” or reduction of the balance sheet in Oct 2017.

The decisions of the FOMC (Federal Open Market Committee) depend on incoming data. There are unexpected swings in valuations of risk financial assets by “carry trades” from interest rates below inflation to exposures in stocks, commodities and their derivatives. Another issue is the unexpected “data surprises” such as the sharp decline in 12 months rates of increase of real disposable income, or what is left after taxes and inflation, and the price indicator of the FOMC, prices of personal consumption expenditures (PCE) excluding food and energy. There is no science or art of monetary policy that can deal with this uncertainty.

Real Disposable Personal Income	Real Personal Consumption Expenditures	Prices of Personal Consumption Expenditures	PCE Prices Excluding Food and Energy
∆%12M	∆%12M	∆%12M	∆%12M
6/2017	6/2017	6/2017	6/2017
1.2	2.4	1.4	1.5

Professor Ronald I. McKinnon (2013Oct27), writing on “Tapering without tears—how to end QE3,” on Oct 27, 2013, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304799404579153693500945608?KEYWORDS=Ronald+I+McKinnon), finds that the major central banks of the world have fallen into a “near-zero-interest-rate trap.” World economic conditions are weak such that exit from the zero interest rate trap could have adverse effects on production, investment and employment. The maintenance of interest rates near zero creates long-term near stagnation. The proposal of Professor McKinnon is credible, coordinated increase of policy interest rates toward 2 percent. Professor John B. Taylor at Stanford University, writing on “Economic failures cause political polarization,” on Oct 28, 2013, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303442004579121010753999086?KEYWORDS=John+B+Taylor), analyzes that excessive risks induced by near zero interest rates in 2003-2004 caused the financial crash. Monetary policy continued in similar paths during and after the global recession with resulting political polarization worldwide.

It may be quite painful to exit QE∞ or use of the balance sheet of the central bank together with zero interest rates forever. The basic valuation equation that is also used in capital budgeting postulates that the value of stocks or of an investment project is given by:

Where R_τ is expected revenue in the time horizon from τ =1 to T; C_τ denotes costs; and ρ is an appropriate rate of discount. In words, the value today of a stock or investment project is the net revenue, or revenue less costs, in the investment period from τ =1 to T discounted to the present by an appropriate rate of discount. In the current weak economy, revenues have been increasing more slowly than anticipated in investment plans. An increase in interest rates would affect discount rates used in calculations of present value, resulting in frustration of investment decisions. If V represents value of the stock or investment project, as ρ → ∞, meaning that discount rates increase without bound, then V → 0, or

declines.

IB Functions of Banks. Modern banking theory analyzes three important functions provided by banks: monitoring of borrowers, provision of liquidity services and transformation of illiquid assets into immediately liquid assets (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 51-60). These functions require valuation of alternative investment projects that may be distorted by zero interest rates of monetary policy and artificially low long-term interest rates. The QE∞ trap frustrates essential banking functions.

Monitoring. Banks monitor projects to ensure that funds are allocated to their intended projects (Diamond 1984, 1996). Banks issue deposits, which are secondary assets, to acquire loans, which are primary assets. Monitoring reduces costs of participating in business projects. Acting as delegated monitor, banks obtain information on the borrower, allowing less costly participation through the issue of unmonitored deposits. Monitoring of borrowers provides enhanced less costly participation by investors through the issue of deposits. There is significant reduction of monitoring costs by delegating to a bank. If there are many potential investors, monitoring by the bank of a credit name is less costly than the sum of individual monitoring of the same credit name by all potential investors. Banks permit borrowers to reach many investors for their projects while affording investors less costly participation in the returns of projects of bank borrowers.
Transformation of Illiquid Loans into Liquid Deposits. Diamond and Dybvig (1986) analyze bank services through bank balance sheets.

i. Assets. Banks provide loans to borrowers. The evaluation of borrowers prevents “adverse selection,” which consists of banks choosing unsound projects and failing to finance sound projects. Monitoring of loans prevents “moral hazard,” which consists of borrowers using the funds of the loan for purposes other than the project for which they were lent, as for example, using borrowed bank funds for speculative real estate instead of for the intended industrial project. Relationship banking improves the information on borrowers and the monitoring function.

ii. Liabilities. Banks provide numerous services to their clients such as holding deposits, clearing transactions, currency inventory and payments for goods, services and obligations.

iii. Assets and Liabilities: Transformation Function. The transformation function operates through both sides of the balance sheet: banks convert illiquid loans in the asset side into liquid deposits in the liability side. There is rich theory of banking (Diamond and Rajan 2000, 2001a,b). Securitized banking provides the same transformation function by bundling mortgage and other consumer loans into securities that are then sold to investors who finance them in short-dated sale and repurchase agreements (Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 61-6).

Banking was important in facilitating economic growth in historical periods (Cameron 1961, 1967, 1972; Cameron et al. 1992). Banking is also important currently because small- and medium-size business may have no other form of financing than banks in contrast with many options for larger and more mature companies that have access to capital markets. Calomiris and Haber (2014) find that broad voting rights and institutions restricting coalitions of bankers and populists ensure stable banking systems and access to credit. Summerhill (2015) provides convincing evidence that commitment to sovereign credibility is not sufficient to promote financial development in the presence of inadequate regulatory organization. Personal consumptions expenditures have share of 68.9 percent of GDP in IIQ2016 (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.html). Most consumers rely on their banks for real estate loans, credit cards and personal consumer loans. Thus, it should be expected that success of monetary policy in stimulating the economy would be processed through bank balance sheets.

IA Appendix: Transmission of Unconventional Monetary Policy. Janet L. Yellen, Vice Chair of the Board of Governors of the Federal Reserve System, provides analysis of the policy of purchasing large amounts of long-term securities for the Fed’s balance sheet. The new analysis provides three channels of transmission of quantitative easing to the ultimate objectives of increasing growth and employment and increasing inflation to “levels of 2 percent or a bit less that most Committee participants judge to be consistent, over the long run, with the FOMC’s dual mandate” (Yellen 2011AS, 4, 7):

“There are several distinct channels through which these purchases tend to influence aggregate demand, including a reduced cost of credit to consumers and businesses, a rise in asset prices that boost household wealth and spending, and a moderate change in the foreign exchange value of the dollar that provides support to net exports.”

The new analysis by Yellen (2011AS) is considered below in four separate subsections: IA1 Theory; IA2 Policy; IA3 Evidence; and IA4 Unwinding Strategy.

IA1 Theory. The transmission mechanism of quantitative easing can be analyzed in three different forms. (1) Portfolio choice theory. General equilibrium value theory was proposed by Hicks (1935) in analyzing the balance sheets of individuals and institutions with assets in the capital segment consisting of money, debts, stocks and productive equipment. Net worth or wealth would be comparable to income in value theory. Expected yield and risk would be the constraint comparable to income in value theory. Markowitz (1952) considers a portfolio of individual securities with mean μ_p and variance σ_p. The Markowitz (1952, 82) rule states that “investors would (or should” want to choose a portfolio of combinations of (μ_p, σ_p) that are efficient, which are those with minimum variance or risk for given expected return μ_p or more and maximum expected μ_p for given variance or risk or less. The more complete model of Tobin (1958) consists of portfolio choice of monetary assets by maximizing a utility function subject to a budget constraint. Tobin (1961, 28) proposes general equilibrium analysis of the capital account to derive choices of capital assets in balance sheets of economic units with the determination of yields in markets for capital assets with the constraint of net worth. A general equilibrium model of choice of portfolios was developed simultaneously by various authors (Hicks 1962; Treynor 1962; Sharpe 1964; Lintner 1965; Mossin 1966). If shocks such as by quantitative easing displace investors from the efficient frontier, there would be reallocations of portfolios among assets until another efficient point is reached. Investors would bid up the prices or lower the returns (interest plus capital gains) of long-term assets targeted by quantitative easing, causing the desired effect of lowering long-term costs of investment and consumption.

(2) General Equilibrium Theory. Bernanke and Reinhart (2004, 88) argue that “the possibility monetary policy works through portfolio substitution effects, even in normal times, has a long intellectual history, having been espoused by both Keynesians (James Tobin 1969) and monetarists (Karl Brunner and Allan Meltzer 1973).” Andres et al. (2004) explain the Tobin (1969) contribution by optimizing agents in a general-equilibrium model. Both Tobin (1969) and Brunner and Meltzer (1973) consider capital assets to be gross instead of perfect substitutes with positive partial derivatives of own rates of return and negative partial derivatives of cross rates in the vector of asset returns (interest plus principal gain or loss) as argument in portfolio balancing equations (see Pelaez and Suzigan 1978, 113-23). Tobin (1969, 26) explains portfolio substitution after monetary policy:

“When the supply of any asset is increased, the structure of rates of return, on this and other assets, must change in a way that induces the public to hold the new supply. When the asset’s own rate can rise, a large part of the necessary adjustment can occur in this way. But if the rate is fixed, the whole adjustment must take place through reductions in other rates or increases in prices of other assets. This is the secret of the special role of money; it is a secret that would be shared by any other asset with a fixed interest rate.”

Andrés et al. (2004, 682) find that in their multiple-channels model “base money expansion now matters for the deviations of long rates from the expected path of short rates. Monetary policy operates by both the expectations channel (the path of current and expected future short rates) and this additional channel. As in Tobin’s framework, interest rates spreads (specifically, the deviations from the pure expectations theory of the term structure) are an endogenous function of the relative quantities of assets supplied.”

The interrelation among yields of default-free securities is measured by the term structure of interest rates. This schedule of interest rates along time incorporates expectations of investors. (Cox, Ingersoll and Ross 1985). The expectations hypothesis postulates that the expectations of investors about the level of future spot rates influence the level of current long-term rates. The normal channel of transmission of monetary policy in a recession is to lower the target of the fed funds rate that will lower future spot rates through the term structure and also the yields of long-term securities. The expectations hypothesis is consistent with term premiums (Cox, Ingersoll and Ross 1981, 774-7) such as liquidity to compensate for risk or uncertainty about future events that can cause changes in prices or yields of long-term securities (Hicks 1935; see Cox, Ingersoll and Ross 1981, 784; Chung et al. 2011, 22).

(3) Preferred Habitat. Another approach is by the preferred-habitat models proposed by Culbertson (1957, 1963) and Modigliani and Sutch (1966). This approach is formalized by Vayanos and Vila (2009). The model considers investors or “clientele” who do not abandon their segment of operations unless there are extremely high potential returns and arbitrageurs who take positions to profit from discrepancies. Pension funds matching benefit liabilities would operate in segments above 15 years; life insurance companies operate around 15 years or more; and asset managers and bank treasury managers are active in maturities of less than 10 years (Ibid, 1). Hedge funds, proprietary trading desks and bank maturity transformation activities are examples of potential arbitrageurs. The role of arbitrageurs is to incorporate “information about current and future short rates into bond prices” (Ibid, 12). Suppose monetary policy raises the short-term rate above a certain level. Clientele would not trade on this information, but arbitrageurs would engage in carry trade, shorting bonds and investing at the short-term rate, in a “roll-up” trade, resulting in decline of bond prices or equivalently increases in yields. This is a situation of an upward-sloping yield curve. If the short-term rate were lowered, arbitrageurs would engage in carry trade borrowing at the short-term rate and going long bonds, resulting in an increase in bond prices or equivalently decline in yields, or “roll-down” trade. The carry trade is the mechanism by which bond yields adjust to changes in current and expected short-term interest rates. The risk premiums of bonds are positively associated with the slope of the term structure (Ibid, 13). Fama and Bliss (1987, 689) find with data for 1964-85 that “1-year expected returns for US Treasury maturities to 5 years, measured net of the interest rate on a 1-year bond, vary through time. Expected term premiums are mostly positive during good times but mostly negative during recessions.” Vayanos and Vila (2009) develop a model with two-factors, the short-term rate and demand or quantity. The term structure moves because of shocks of short-term rates and demand. An important finding is that demand or quantity shocks are largest for intermediate and long maturities while short-rate shocks are largest for short-term maturities.

IA2 Policy. A simplified analysis could consider the portfolio balance equations A_ij = f(r, x) where A_ij is the demand for i = 1,2,∙∙∙n assets from j = 1,2, ∙∙∙m sectors, r the 1xn vector of rates of return, r_i, of n assets and x a vector of other relevant variables. Tobin (1969) and Brunner and Meltzer (1973) assume imperfect substitution among capital assets such that the own first derivatives of A_ij are positive, demand for an asset increases if its rate of return (interest plus capital gains) is higher; and cross first derivatives are negative, demand for an asset decreases if the rate of return of alternative assets increases. Theoretical purity would require the estimation of the complete model with all rates of return. In practice, it may be impossible to observe all rates of return such as in the critique of Roll (1976). Policy proposals by the Fed have been focused on the likely impact of withdrawals of stocks of securities in specific segments, that is, of effects of one or several specific rates of return among the n possible rates. There have been at least seven approaches on the role of monetary policy in purchasing long-term securities that have increased the classes of rates of return targeted by the Fed:

(1) Suspension of Auctions of 30-year Treasury Bonds. Auctions of 30-year Treasury bonds were suspended between 2001 and 2005. This was Treasury policy not Fed policy. The effects were similar to those of quantitative easing: withdrawal of supply from the segment of 30-year bonds would result in higher prices or lower yields for close-substitute mortgage-backed securities with resulting lower mortgage rates. The objective was to encourage refinancing of house loans that would increase family income and consumption by freeing income from reducing monthly mortgage payments.

(2) Purchase of Long-term Securities by the Fed. Between Nov 2008 and Mar 2009 the Fed announced the intention of purchasing $1750 billion of long-term securities: $600 billion of agency mortgage-backed securities and agency debt announced on Nov 25 and $850 billion of agency mortgaged-backed securities and agency debt plus $300 billion of Treasury securities announced on Mar 18, 2009 (Yellen 2011AS, 5-6). The objective of buying mortgage-backed securities was to lower mortgage rates that would “support the housing sector” (Bernanke 2009SL). The FOMC statement on Dec 16, 2008 informs that: “over the next few quarters the Federal Reserve will purchase large quantities of agency debt and mortgage-backed securities to provide support to the mortgage and housing markets, and its stands ready to expand its purchases of agency debt and mortgage-backed securities as conditions warrant” (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm). The Mar 18, 2009, statement of the FOMC explained that: “to provide greater support to mortgage lending and housing markets, the Committee decided today to increase the size of the Federal Reserve’s balance sheet further by purchasing up to an additional $750 billion of agency mortgage-backed securities, bringing its total purchases of these securities up to $1.25 trillion this year, and to increase its purchase of agency debt this year by up to $100 billion to a total of up to $200 billion. Moreover, to help improve conditions in private credit markets, the Committee decided to purchase up to $300 billion of longer-term Treasury securities over the next six months” (http://www.federalreserve.gov/newsevents/press/monetary/20090318a.htm). Policy changed to increase prices or reduce yields of mortgage-backed securities and Treasury securities with the objective of supporting housing markets and private credit markets by lowering costs of housing and long-term private credit.

(3) Portfolio Reinvestment. On Aug 10, 2010, the FOMC statement explains the reinvestment policy: “to help support the economic recovery in a context of price stability, the Committee will keep constant the Federal Reserve’s holdings of securities at their current level by reinvesting principal payments from agency debt and agency mortgage-backed securities in long-term Treasury securities. The Committee will continue to roll over the Federal Reserve’s holdings of Treasury securities as they mature” (http://www.federalreserve.gov/newsevents/press/monetary/20100810a.htm). The objective of policy appears to be supporting conditions in housing and mortgage markets with slow transfer of the portfolio to Treasury securities that would support private-sector markets.

(4) Increasing Portfolio. As widely anticipated, the FOMC decided on Dec 3, 2010: “to promote a stronger pace of economic recovery and to help ensure that inflation, over time, is at levels consistent with its mandate, the Committee decided today to expand its holdings of securities. The Committee will maintain its existing policy of reinvesting principal payments from its securities holdings. In addition, the Committee intends to purchase a further $600 billion of longer-term Treasury securities by the end of the second quarter of 2011, a pace of about $75 billion per month” (http://www.federalreserve.gov/newsevents/press/monetary/20101103a.htm). The emphasis appears to shift from housing markets and private-sector credit markets to the general economy, employment and preventing deflation.

(5) Increasing Stock Market Valuations. Chairman Bernanke (2010WP) explained on Nov 4 the objectives of purchasing an additional $600 billion of long-term Treasury securities and reinvesting maturing principal and interest in the Fed portfolio. Long-term interest rates fell and stock prices rose when investors anticipated the new round of quantitative easing. Growth would be promoted by easier lending such as for refinancing of home mortgages and more investment by lower corporate bond yields. Consumers would experience higher confidence as their wealth in stocks rose, increasing outlays. Income and profits would rise and, in a “virtuous circle,” support higher economic growth. Bernanke (2000) analyzes the role of stock markets in central bank policy (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 99-100). Fed policy in 1929 increased interest rates to avert a gold outflow and failed to prevent the deepening of the banking crisis without which the Great Depression may not have occurred. In the crisis of Oct 19, 1987, Fed policy supported stock and futures markets by persuading banks to extend credit to brokerages. Collapse of stock markets would slow consumer spending.

(6) Devaluing the Dollar. Yellen (2011AS, 6) broadens the effects of quantitative easing by adding dollar devaluation: “there are several distinct channels through which these purchases tend to influence aggregate demand, including a reduced cost of credit to consumers and businesses, a rise in asset prices that boosts household wealth and spending, and a moderate change in the foreign exchange value of the dollar that provides support to net exports.”

(7) Let’s Twist Again Monetary Policy. The term “operation twist” grew out of the dance “twist” popularized by successful musical performer Chubby Chekker (http://www.youtube.com/watch?v=aWaJ0s0-E1o). Meulendyke (1998, 39) describes the coordination of policy by Treasury and the FOMC in the beginning of the Kennedy administration in 1961 (see Modigliani and Sutch 1966, 1967; http://cmpassocregulationblog.blogspot.com/2011/09/imf-view-of-world-economy-and-finance.html http://cmpassocregulationblog.blogspot.com/2011/09/collapse-of-household-income-and-wealth.html):

“In 1961, several developments led the FOMC to abandon its “bills only” restrictions. The new Kennedy administration was concerned about gold outflows and balance of payments deficits and, at the same time, it wanted to encourage a rapid recovery from the recent recession. Higher rates seemed desirable to limit the gold outflows and help the balance of payments, while lower rates were wanted to speed up economic growth.

To deal with these problems simultaneously, the Treasury and the FOMC attempted to encourage lower long-term rates without pushing down short-term rates. The policy was referred to in internal Federal Reserve documents as “operation nudge” and elsewhere as “operation twist.” For a few months, the Treasury engaged in maturity exchanges with trust accounts and concentrated its cash offerings in shorter maturities.

The Federal Reserve participated with some reluctance and skepticism, but it did not see any great danger in experimenting with the new procedure.

It attempted to flatten the yield curve by purchasing Treasury notes and bonds while selling short-term Treasury securities. The domestic portfolio grew by $1.7 billion over the course of 1961. Note and bond holdings increased by a substantial $8.8 billion, while certificate of indebtedness holdings fell by almost $7.4 billion (Table 2). The extent to which these actions changed the yield curve or modified investment decisions is a source of dispute, although the predominant view is that the impact on yields was minimal. The Federal Reserve continued to buy coupon issues thereafter, but its efforts were not very aggressive. Reference to the efforts disappeared once short-term rates rose in 1963. The Treasury did not press for continued Fed purchases of long-term debt. Indeed, in the second half of the decade, the Treasury faced an unwanted shortening of its portfolio. Bonds could not carry a coupon with a rate above 4 1/4 percent, and market rates persistently exceeded that level. Notes—which were not subject to interest rate restrictions—had a maximum maturity of five years; it was extended to seven years in 1967.”

As widely anticipated by markets, perhaps intentionally, the Federal Open Market Committee (FOMC) decided at its meeting on Sep 21 that it was again “twisting time” (http://www.federalreserve.gov/newsevents/press/monetary/20110921a.htm):

“Information received since the Federal Open Market Committee met in August indicates that economic growth remains slow. Recent indicators point to continuing weakness in overall labor market conditions, and the unemployment rate remains elevated. Household spending has been increasing at only a modest pace in recent months despite some recovery in sales of motor vehicles as supply-chain disruptions eased. Investment in nonresidential structures is still weak, and the housing sector remains depressed. However, business investment in equipment and software continues to expand. Inflation appears to have moderated since earlier in the year as prices of energy and some commodities have declined from their peaks. Longer-term inflation expectations have remained stable.

Consistent with its statutory mandate, the Committee seeks to foster maximum employment and price stability. The Committee continues to expect some pickup in the pace of recovery over coming quarters but anticipates that the unemployment rate will decline only gradually toward levels that the Committee judges to be consistent with its dual mandate. Moreover, there are significant downside risks to the economic outlook, including strains in global financial markets. The Committee also anticipates that inflation will settle, over coming quarters, at levels at or below those consistent with the Committee's dual mandate as the effects of past energy and other commodity price increases dissipate further. However, the Committee will continue to pay close attention to the evolution of inflation and inflation expectations.

To support a stronger economic recovery and to help ensure that inflation, over time, is at levels consistent with the dual mandate, the Committee decided today to extend the average maturity of its holdings of securities. The Committee intends to purchase, by the end of June 2012, $400 billion of Treasury securities with remaining maturities of 6 years to 30 years and to sell an equal amount of Treasury securities with remaining maturities of 3 years or less. This program should put downward pressure on longer-term interest rates and help make broader financial conditions more accommodative. The Committee will regularly review the size and composition of its securities holdings and is prepared to adjust those holdings as appropriate.

To help support conditions in mortgage markets, the Committee will now reinvest principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities. In addition, the Committee will maintain its existing policy of rolling over maturing Treasury securities at auction.

The Committee also decided to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that economic conditions--including low rates of resource utilization and a subdued outlook for inflation over the medium run--are likely to warrant exceptionally low levels for the federal funds rate at least through mid-2013.

The Committee discussed the range of policy tools available to promote a stronger economic recovery in a context of price stability. It will continue to assess the economic outlook in light of incoming information and is prepared to employ its tools as appropriate.”

The FOMC decided at its meeting on Jun 20, 2012, to continue “Let’s Twist Again” monetary policy until the end of 2012 (http://www.federalreserve.gov/newsevents/press/monetary/20120620a.htm http://www.newyorkfed.org/markets/opolicy/operating_policy_120620.html):

“The Committee also decided to continue through the end of the year its program to extend the average maturity of its holdings of securities. Specifically, the Committee intends to purchase Treasury securities with remaining maturities of 6 years to 30 years at the current pace and to sell or redeem an equal amount of Treasury securities with remaining maturities of approximately 3 years or less. This continuation of the maturity extension program should put downward pressure on longer-term interest rates and help to make broader financial conditions more accommodative. The Committee is maintaining its existing policy of reinvesting principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities. The Committee is prepared to take further action as appropriate to promote a stronger economic recovery and sustained improvement in labor market conditions in a context of price stability.”

IA3 Evidence. There are multiple empirical studies on the effectiveness of quantitative easing that have been covered in past posts such as (Andrés et al. 2004, D’Amico and King 2010, Doh 2010, Gagnon et al. 2010, Hamilton and Wu 2010). On the basis of simulations of quantitative easing with the FRB/US econometric model, Chung et al (2011, 28-9) find that:

”Lower long-term interest rates, coupled with higher stock market valuations and a lower foreign exchange value of the dollar, provide a considerable stimulus to real activity over time. Phase 1 of the program by itself is estimated to boost the level of real GDP almost 2 percent above baseline by early 2012, while the full program raises the level of real GDP almost 3 percent by the second half of 2012. This boost to real output in turn helps to keep labor market conditions noticeably better than they would have been without large scale asset purchases. In particular, the model simulations suggest that private payroll employment is currently 1.8 million higher, and the unemployment rate ¾ percentage point lower, that would otherwise be the case. These benefits are predicted to grow further over time; by 2012, the incremental contribution of the full program is estimated to be 3 million jobs, with an additional 700,000 jobs provided by the most recent phase of the program alone.”

An additional conclusion of these simulations is that quantitative easing may have prevented actual deflation. Empirical research is continuing.

IA4 Unwinding Strategy. Fed Vice-Chair Yellen (2011AS) considers four concerns on quantitative easing discussed below in turn. First, Excessive Inflation. Yellen (2011AS, 9-12) considers concerns that quantitative easing could result in excessive inflation because fast increases in aggregate demand from quantitative easing could raise the rate of inflation, posing another problem of adjustment with tighter monetary policy or higher interest rates. The Fed estimates significant slack of resources in the economy as measured by the difference of four percentage points between the high current rate of unemployment above 9 percent and the NAIRU (non-accelerating rate of unemployment) of 5.75 percent (Ibid, 2). Thus, faster economic growth resulting from quantitative easing would not likely result in upward trend of costs as resources are bid up competitively. The Fed monitors frequently slack indicators and is committed to maintaining inflation at a “level of 2 percent or a bit less than that” (Ibid, 13), say, in the narrow open interval (1.9, 2.1).

Second, Inflation and Bank Reserves. On Jan 12, 2012, the line “Reserve Bank credit” in the Fed balance sheet stood at $2450.6 billion, or $2.5 trillion, with the portfolio of long-term securities of $2175.7 billion, or $2.2 trillion, composed of $987.6 billion of notes and bonds, $49.7 billion of inflation-adjusted notes and bonds, $146.3 billion of Federal agency debt securities, and $992.1 billion of mortgage-backed securities; reserves balances with Federal Reserve Banks stood at $1095.5 billion, or $1.1 trillion (http://federalreserve.gov/releases/h41/current/h41.htm#h41tab1). The concern addressed by Yellen (2011AS, 12-4) is that this high level of reserves could eventually result in demand growth that could accelerate inflation. Reserves would be excessively high relative to the levels before the recession. Reserves of depository institutions at the Federal Reserve Banks rose from $45.6 billion in Aug 2008 to $1084.8 billion in Aug 2010, not seasonally adjusted, multiplying by 23.8 times, or to $1038.2 billion in Nov 2010, multiplying by 22.8 times. The monetary base consists of the monetary liabilities of the government, composed largely of currency held by the public plus reserves of depository institutions at the Federal Reserve Banks. The monetary base not seasonally adjusted, or issue of money by the government, rose from $841.1 billion in Aug 2008 to $1991.1 billion or by 136.7 percent and to $1968.1 billion in Nov 2010 or by 133.9 percent (http://federalreserve.gov/releases/h3/hist/h3hist1.pdf). Policy can be viewed as creating government monetary liabilities that ended mostly in reserves of banks deposited at the Fed to purchase $2.1 trillion of long-term securities or assets, which in nontechnical language would be “printing money” (http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html). The marketable debt of the US government in Treasury securities held by the public stood at $8.7 trillion on Nov 30, 2010 (http://www.treasurydirect.gov/govt/reports/pd/mspd/2010/opds112010.pdf). The current holdings of long-term securities by the Fed of $2.1 trillion, in the process of converting fully into Treasury securities, are equivalent to 24 percent of US government debt held by the public, and would represent 29.9 percent with the new round of quantitative easing if all the portfolio of the Fed, as intended, were in Treasury securities. Debt in Treasury securities held by the public on Dec 31, 2009, stood at $7.2 trillion (http://www.treasurydirect.gov/govt/reports/pd/mspd/2009/opds122009.pdf), growing on Nov 30, 2010, to $1.5 trillion or by 20.8 percent. In spite of this growth of bank reserves, “the 12-month change in core PCE [personal consumption expenditures] prices dropped from about 2 ½ percent in mid-2008 to around 1 ½ percent in 2009 and declined further to less than 1 percent by late 2010” (Yellen 2011AS, 3). The PCE price index, excluding food and energy, is around 0.8 percent in the past 12 months, which could be, in the Fed’s view, too close for comfort to negative inflation or deflation. Yellen (2011AS, 12) agrees “that an accommodative monetary policy left in place too long can cause inflation to rise to undesirable levels” that would be true whether policy was constrained or not by “the zero bound on interest rates.” The FOMC is monitoring and reviewing the “asset purchase program regularly in light of incoming information” and will “adjust the program as needed to meet its objectives” (Ibid, 12). That is, the FOMC would withdraw the stimulus once the economy is closer to full capacity to maintain inflation around 2 percent. In testimony at the Senate Committee on the Budget, Chairman Bernanke stated that “the Federal Reserve has all the tools its needs to ensure that it will be able to smoothly and effectively exit from this program at the appropriate time” (http://federalreserve.gov/newsevents/testimony/bernanke20110107a.htm). The large quantity of reserves would not be an obstacle in attaining the 2 percent inflation level. Yellen (2011A, 13-4) enumerates Fed tools that would be deployed to withdraw reserves as desired: (1) increasing the interest rate paid on reserves deposited at the Fed currently at 0.25 percent per year; (2) withdrawing reserves with reverse sale and repurchase agreement in addition to those with primary dealers by using mortgage-backed securities; (3) offering a Term Deposit Facility similar to term certificates of deposit for member institutions; and (4) sale or redemption of all or parts of the portfolio of long-term securities. The Fed would be able to increase interest rates and withdraw reserves as required to attain its mandates of maximum employment and price stability.

Third, Financial Imbalances. Fed policy intends to lower costs to business and households with the objective of stimulating investment and consumption generating higher growth and employment. Yellen (2011A, 14-7) considers a possible consequence of excessively reducing interest rates: “a reasonable fear is that this process could go too far, encouraging potential borrowers to employ excessive leverage to take advantage of low financing costs and leading investors to accept less compensation for bearing risks as they seek to enhance their rates of return in an environment of very low yields. This concern deserves to be taken seriously, and the Federal Reserve is carefully monitoring financial indicators for signs of potential threats to financial stability.” Regulation and supervision would be the “first line of defense” against imbalances threatening financial stability but the Fed would also use monetary policy to check imbalances (Yellen 2011AS, 17).

Fourth, Adverse Effects on Foreign Economies. The issue is whether the now recognized dollar devaluation would promote higher growth and employment in the US at the expense of lower growth and employment in other countries.

IC United States Commercial Banks Assets and Liabilities. Selected assets and liabilities of US commercial banks, not seasonally adjusted, in billions of dollars, from Report H.8 of the Board of Governors of the Federal Reserve System are in Table I-1. Data are not seasonally adjusted to permit comparison between Sep 2016 and Sep 2017. Total assets of US commercial banks grew 2.8 percent from $16,063.1 billion in Sep 2016 to $16,508.2 billion in Sep 2017. The Bureau of Economic Analysis (BEA) estimates US GDP in 2016 at $18,624.5 billion (http://www.bea.gov/iTable/index_nipa.cfm). Thus, total assets of US commercial banks are equivalent to over 80 percent of US GDP. Bank credit grew 3.3 percent from $12,364.3 billion in Sep 2016 to $12,766.5 billion in Sep 2017. Securities in bank credit increased 2.9 percent from $3293 billion in Sep 2016 to $3387 billion in Sep 2017. A large part of securities in banking credit consists of US Treasury and agency securities, increasing 4.2 percent from $2377 billion in Sep 2016 to $2477 billion in Sep 2017. Credit to the government that issues or backs Treasury and agency securities of $2477 billion in Sep 2017 is about 19.4 percent of total bank credit of US commercial banks of $12,766.5 billion. Mortgage-backed securities, providing financing of home loans, increased 8.0 percent, from $1656 billion in Sep 2016 to $1788 billion in Sep 2017. Loans and leases are relatively dynamic, growing 3.4 percent from $9071 billion in Sep 2016 to $9380 billion in Sep 2017. A dynamic class historically, currently slowing, is commercial and industrial loans, growing 2.0 percent from $2070 billion in Sep 2016 and providing $2112 billion or 22.5 percent of total loans and leases of $9380 billion in Sep 2017. Real estate loans increased 4.0 percent, providing $4240 billion in Sep 2017 or 45.2 percent of total loans and leases. Consumer loans increased 4.2 percent, providing $1396 billion in Sep 2017 or 14.9 percent of total loans. Cash assets are measured to “include vault cash, cash items in process of collection, balances due from depository institutions and balances due from Federal Reserve Banks” (https://www.federalreserve.gov/releases/h8/current/default.htm). Cash assets in US commercial banks increased 1.0 percent from $2366 billion in Sep 2016 to $2390 billion in Sep 2017 but a single year of the series masks exploding cash in banks because of unconventional monetary policy, which is discussed below. Bank deposits increased 4.5 percent from $11,354 billion in Sep 2016 to $11,860 billion in Sep 2017. The difference between bank deposits and total loans and leases in banks increased from $2283 billion in Sep 2016 to $2480 billion in Sep 2017 or by $197 billion. Securities in bank credit increased $94 billion from $3293 billion in Sep 2016 to $3383 billion in Sep 2017 and Treasury and agency securities increased $100 billion from $2377 billion in Sep 2016 to $2477 billion in Sep 2017. Loans and leases increased $309 billion from $9071 billion in Sep 2016 to $9380 billion in Sep 2017. Banks expanded both lending and investment in lower risk securities partly because of the weak economy and credit disappointments during the global recession that has resulted in an environment of fewer sound lending opportunities. Investing in securities with high duration, or price elasticity of yields, is riskier because of the increase in yields that can cause loss of principal as investors shift away from bond funds into money market funds invested in short-term assets. Lower interest rates resulting from monetary policy may not necessarily encourage higher borrowing in the current loss of dynamism of the US economy. Real disposable income per capita in IIQ2017 is higher by only 9.7 percent than in IVQ2007 (Table IB-2 IX Conclusion and extended analysis in IB Collapse of United States Dynamism of Income Growth and Employment Creation), which is significantly lower than 20.7 percent higher if the economy had performed in long-term growth of per capita income in the United States at 2 percent per year from 1870 to 2010 (Lucas 2011May). In contrast, real disposable income per capita grew cumulatively 25.1 percent in the cycle from IQ1980 to IVQ1990 that was close to trend growth of 25.0 percent. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm).

Table I-1, US, Assets and Liabilities of Commercial Banks, NSA, Billions of Dollars

	Sep 2016	Sep 2017	∆%
Total Assets	16,063.1	16,508.2	2.8
Bank Credit	12,364.3	12,766.5	3.3
Securities in Bank Credit	3293	3387	2.9
Treasury & Agency Securities	2377	2477	4.2
Mortgage-Backed Securities	1656	1788	8.0
Loans & Leases	9071	9380	3.4
Real Estate Loans	4077	4240	4.0
Commercial Real Estate Loans	1926	2055	6.7
Consumer Loans	1340	1396	4.2
Commercial & Industrial Loans	2070	2112	2.0
Other Loans & Leases	1584	1631	3.0
Cash Assets*	2366	2390	1.0
Total Liabilities	14,308	14,672	2.5
Deposits	11,354	11,860	4.5
Residual (Assets less Liabilities)	1756	1837	NA

Note: balancing item of residual assets less liabilities not included

*”Includes vault cash, cash items in process of collection, balances due from depository institutions and balances due from Federal Reserve Banks.”

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Seasonally adjusted annual equivalent rates (SAAR) of change of selected assets and liabilities of US commercial banks from the report H.8 of the Board of Governors of the Federal Reserve System are in Table I-2 annually from 2011 to 2016 and for Aug 2017 and Aug 2017. The global recession had strong impact on bank assets as shown by declines of total assets of 6.0 percent in 2009 and 2.6 percent in 2010. Loans and leases fell 10.2 percent in 2009 and 5.7 percent in 2010. Commercial and industrial loans fell 18.7 percent in 2009 and 9.2 percent in 2010. Unconventional monetary policy caused an increase of cash assets of banks of 159.2 percent in 2008, 49.5 percent in 2009 and 48.1 percent in 2011 followed by decline by 2.2 percent in 2012. Cash assets of banks increased 54.5 percent in 2013 and 12.3 percent in 2014, decreasing 7.8 percent in 2015. Cash assets of banks decreased 14.4 percent in 2016. Cash assets of banks increased at the SAAR of 22.5 percent in Aug 2012 but contraction by 49.6 percent in Sep 2012 and 6.3 percent in Oct 2012. Cash assets of banks increased at 56.0 percent in Nov 2012, minus 7.8 percent in Dec 2012, 38.8 percent in Jan 2013, 66.2 percent in Feb 2013, 66.0 percent in Mar 2013 and 14.5 percent in Apr 2013. Cash assets of banks increased at the SAAR of 63.2 percent in May 2013, 42.4 percent in Jun 2013, 28.6 percent in Jul 2013, 71.5 percent in Aug 2013, 57.5 percent in Sep 2013 and 50.2 percent in Oct 2013. Cash assets of banks increased at the rate of 29.0 percent in Nov 2013 and fell at 1.5 percent in Dec 2013. Cash assets of banks increased at 20.1 percent in Jan 2014 and at 20.5 percent in Feb 2014. Cash assets of banks increased at 24.4 percent in Mar 2014 and at 8.1 percent in Apr 2014. Cash assets of banks increased at 3.5 percent in May 2014 and 29.8 percent in Jun 2014. Cash assets of banks increased at 8.4 percent in Jul 2014 and 16.0 percent in Aug 2014. Cash assets of banks increased at 16.8 percent in Sep 2014. Cash assets of banks increased at 2.9 percent in Oct 2014 and fell at 1.0 percent in Nov 2014. Cash assets of banks fell at 32.1 percent in Dec 2014. Cash assets of banks increased at 5.0 percent in Jan 2015, declining at 14.1 percent in Feb 2015 and increasing at 5.3 percent in Mar 2015. Cash assets of banks fell at 1.9 percent in Apr 2015 and at 31.4 percent in May 2015. Cash assets of banks fell at 29.0 percent in Jun 2015 and increased at 8.8 percent in Jul 2015. Cash assets of banks increased at 11.8 percent in Aug 2015 and fell at 29.2 percent in Sep 2015. Cash assets of banks increased at 51.2 percent in Oct 2015 and fell at 33.0 percent in Nov 2015. Cash assets of banks fell at 37.7 percent in Dec 2015 and fell at 14.0 percent in Jan 2016. Cash assets of banks increased at 9.0 percent in Feb 2016 and fell at 4.6 percent in Mar 2016. Cash assets of banks increased at 12.7 percent in Apr 2016 and fell at 4.4 percent in May 2016. Cash assets of banks fell at 23.6 percent in Jun 2016 and fell at 13.1 percent in Jul 2016. Cash assets of banks decreased at 0.6 percent in Aug 2016 and decreased at 34.4 percent in Sep 2016. Cash assets of banks decreased at 59.5 percent in Oct 2016, increasing at 0.5 percent in Nov 2016. Cash assets of banks increased at 18.2 percent in Dec 2016 and increased at 12.6 percent in Jan 2017. Cash assets of banks increased at 38.9 percent in Feb 2017 and increased at 31.2 percent in Mar 2017. Cash assets of banks decreased at 28.3 percent in Apr 2017 and decreased at 31.7 percent in May 2017. Cash assets of banks increased at 5.3 percent in Jun 2017 and increased at 18.1 percent in Jul 2017. Cash assets of banks increased at 35.9 percent in Aug 2017 and decreased at 9.9 percent in Sep 2017. Acquisitions of securities for the portfolio of the central bank injected reserves in depository institutions that banks held as cash and reserves at the central bank because of the lack of sound lending opportunities and the adverse expectations in the private sector on doing business. The truly dynamic investment of banks has been in securities in bank credit: growing at the SAAR of 15.4 percent in Jul 2012, 2.6 percent in Aug 2012, 5.3 percent in Sep 2012, 4.7 percent in Oct 2012, 1.7 percent in Nov 2012 and 20.5 percent in Dec 2012. There were declines of securities in bank credit at 1.1 percent in Jan 2013, 3.2 percent in Feb 2013 and 2.7 percent in Mar 2013 but growth of 1.5 percent in Apr 2013. Securities in bank credit fell at the SAAR of 2.6 percent in May 2013 and 5.7 percent in Jun 2013. Securities in bank credit fell at the SAAR of 11.9 percent in Jul 2013 and at 8.3 percent in Aug 2013. Securities in bank credit fell at the SAAR of 6.8 percent in Sep 2013 and increased at 3.0 percent in Oct 2013. Securities in bank credit increased at 5.2 percent in Nov 2013 and at 10.5 percent in Dec 2013. Securities in bank credit increased at 4.1 percent in Jan 2014 and at 8.3 percent in Feb 2014. Securities in bank credit increased at 7.8 percent in Mar 2014 and at 4.4 percent in Apr 2014. Securities in bank credit increased at 10.1 percent in May 2014 and at 7.9 percent in Jun 2014. Securities in bank credit increased at 10.1 percent in Jul 2014, at 0.3 percent in Aug 2014 and at 7.6 percent in Sep 2014. Securities in bank credit increased at 2.8 percent in Oct 2014 and at 5.3 percent in Nov 2014. Securities in bank credit jumped at 19.1 percent in Dec 2014. Securities in bank credit increased at 11.2 percent in Jan 2015 and at 7.8 percent in Feb 2015. Securities in bank credit increased at 0.5 percent in Mar 2015 and increased at 7.9 percent in Apr 2015. Securities in bank credit increased at 11.3 percent in May 2015 and at 0.8 percent in Jun 2015. Securities in bank credit fell at 1.9 percent in Jul 2015. Securities in bank credit increased at 5.2 percent in Aug 2015 and fell at 3.5 percent in Sep 2015. Securities in bank credit increased at 5.8 percent in Oct 2015 and increased at 6.5 percent in Nov 2015, increasing at 9.0 percent in Dec 2015. Securities in bank credit increased at 10.7 percent in Jan 2016 and changed at 0.0 percent in Feb 2016. Securities in bank credit increased at 0.8 percent in Mar 2016 and increased at 10.1 percent in Apr 2016. Securities in bank credit increased at 9.0 percent in May 2016 and increased at 7.1 percent in Jun 2016. Securities in bank credit increased at 15.8 percent in Jul 2016 and increased at 7.2 percent in Aug 2016. Securities in bank credit increased at 10.9 percent in Sep 2016 and increased at 10.6 percent in Oct 2016. Securities in bank credit increased at 0.9 percent in Nov 2016, decreasing at 2.3 percent in Dec 2016. Securities in bank credit increased at 5.5 percent in Jan 2017 and increased at 1.2 percent in Feb 2017. Securities in bank credit increased at 1.3 percent in Mar 2017. Securities in bank credit increased at 1.3 percent in Apr 2017 and increased at 6.2 percent in May 2017. Securities in bank credit increased at 0.2 percent in Jun 2017 and increased at 2.5 percent in Jul 2017. Securities in bank credit increased at 1.2 percent in Aug 2017 and increased at 0.2 percent in Sep 2017. Fear of loss of principal in securities with high duration or price elasticity of yield is shifting investments away from bonds into cash and other assets with less price risk. Positions marked to market in balance sheets experience sharp declines. Throughout the crisis, banks allocated increasing part of their assets to the safety of Treasury and agency securities, or credit to the US government and government-backed credit: with growth of 13.5 percent in 2009 and 15.4 percent in 2010. Treasury and agency securities in bank credit increased at the rate of 16.3 percent in Jul 2012, declining to the rate of 3.4 percent in Aug 2012, 2.1 percent in Sep 2012 and 0.7 percent in Oct 2012. Treasury and agency securities in bank credit fell at the rate of 0.8 percent in Nov 2012, increasing at 17.2 percent in Dec 2012. Treasury and agency securities in bank credit fell at 5.9 percent in Jan 2013, 3.1 percent in Feb 2013, 7.0 percent in Mar 2013 and 5.4 percent in Apr 2013 and 8.3 percent in May 2013. Treasury and agency securities in US commercial banks fell at the SAAR of 6.8 percent in Jun 2013, 19.7 percent in Jul 2013 and 15.7 percent in Aug 2013. Treasury and agency securities fell at the SAAR of 5.6 percent in Sep 2013 and increased at 1.3 percent in Oct 2013. Treasury and agency securities increased at 5.6 percent in Nov 2013 and at 8.9 percent in Dec 2013. Treasury and agency securities increased at 4.2 percent in Jan 2014 and at 8.1 percent in Feb 2014. Treasury and agency securities increased at 9.3 percent in Mar 2014 and at 7.9 percent in Apr 2014. Treasury and agency securities increased at 17.4 percent in May 2014 and 10.1 percent in Jun 2014. Treasury and agency securities increased at 14.6 percent in Jul 2014, at 6.4 percent in Aug 2014 and at 19.5 percent in Sep 2014. Treasury and agency securities increased at 9.3 percent in Oct 2014 and at 6.5 percent in Nov 2014. Treasury and agency securities jumped at 24.0 percent in Dec 2014, 15.3 percent in Jan 2015 and 9.9 percent in Feb 2015, decreasing at 0.5 percent in Mar 2015. Treasury and agency securities increased at 8.1 percent in Apr 2015, at 18.3 percent in May 2015 and at 1.2 percent in Jun 2015. Treasury and agency securities fell at 0.4 percent in Jul 2015, increasing at 8.2 percent in Aug 2015 and decreasing at 0.2 percent in Sep 2015. Treasury and agency securities increased at 9.7 percent in Oct 2015 and increased at 9.0 percent in Nov 2015, increasing at 12.0 percent in Dec 2015. Treasury and agency securities increased at 12.3 percent in Jan 2016 and fell at 0.9 percent in Feb 2016. Treasury and agency securities fell at 1.4 percent in Mar 2016 and increased at 13.4 percent in Apr 2016. Treasury and agency securities increased at 11.5 percent in May 2016 and increased at 4.6 percent in Jun 2016. Treasury and agency securities increased at 19.9 percent in Jul 2016 and increased at 10.5 percent in Aug 2016. Treasury and agency securities increased at 13.9 percent in Sep 2016 and increased at 16.8 percent in Oct 2016. Treasury and agency securities increased at 4.1 percent in Nov 2016 and decreased at 2.7 percent in Dec 2016. Treasury and agency securities increased at 7.4 percent in Jan 2017 and decreased at 1.0 percent in Feb 2017. Treasury and agency securities decreased at 2.2 percent in Mar 2017. Treasury and agency securities increased at 2.7 percent in Apr 2017 and increased at 7.3 percent in May 2017. Treasury and agency secure ties increased at 0.8 percent in Jun 2017 and increased at 5.7 percent in Jul 2017. Treasury and agency securities increased at 1.6 percent in Aug 2017 and increased at 1.6 percent in Sep 2017. Increases in yield result in capital losses that may explain less interest in holding securities with higher duration. Deposits grew at the rate of 10.5 percent in Jul 2012, with the rate declining as for most assets of commercial banks to the rate of 6.2 percent in Aug 2012 but increasing to 7.2 percent in Sep 2012, 8.4 percent in Oct 2012, 5.7 percent in Nov 2012, 18.7 percent in Dec 2012, 2.7 percent in Jan 2013. Deposits grew at the rate of 4.4 percent in Feb 2013, 7.7 percent in Mar 2013, 3.5 percent in Apr 2013 and 2.4 percent in May 2013. Deposits increased at the SAAR of 6.3 percent in Jun 2013, 8.0 percent in Jul 2013 and 3.5 percent in Aug 2013. Deposits grew at the rate of 7.2 percent in Sep 2013 and at 9.0 percent in Oct 2013. Deposits grew at 9.1 percent in Nov 2013 and at 9.1 percent in Dec 2013. Deposits increased at 8.7 percent in Jan 2014 and at 9.6 percent in Feb 2014. Deposits grew at 6.7 percent in Mar 2014 and at 8.4 percent in Apr 2014. Deposits grew at 7.9 percent in May and 3.4 percent in Jun 2014. Deposits increased at 7.2 percent in Jul 2014, at 1.5 percent in Aug 2014 and at 9.9 percent in Sep 2014. Deposits fell at 4.4 percent in Oct 2014 and increased at 9.8 percent in Nov 2014. Deposits increased at 8.2 percent in Dec 2014, 7.0 percent in Jan 2015, 11.3 percent in Feb 2015 and 5.7 percent in Mar 2015. Deposits fell at 1.1 percent in Apr 2015 and increased at 4.8 percent in May 2015 and at 5.6 percent in Jun 2015. Deposits increased at 5.5 percent in Jul 2015, increasing at 7.3 percent in Aug 2015 and increasing at 0.6 percent in Sep 2015. Deposits increased at 6.0 percent in Oct 2015 and increased at 2.4 percent in Nov 2015. Deposits fell at 4.0 percent in Dec 2015 and increased at 5.4 percent in Jan 2016. Deposits increased at 6.2 percent in Feb 2016 and increased at 7.9 percent in Mar 2016. Deposits increased at 5.2 percent in Apr 2016 and increased at 4.3 percent in May 2016, increasing at 7.2 percent in Jun 2016. Deposits increased at 4.0 percent in Jul 2016 and increased at 8.9 percent in Aug 2016. Deposits fell at 1.0 percent in Sep 2016 and increased at 0.5 percent in Oct 2016. Deposits increased at 5.0 percent in Nov 2016 and increased at 4.6 percent in Dec 2016. Deposits increased at 8.5 percent in Jan 2017 and increased at 2.3 percent in Feb 2017. Deposits increased at 6.5 percent in Mar 2017. Deposits increased at 3.5 percent in Apr 2017 and increased at 8.1 percent in May 2017. Deposits increased at 1.0 percent in Jun 2017 and increased at 6.9 percent in Jul 2017. Deposits increased at 3.4 percent in Aug 2017 and increased at 2.5 percent in Sep 2017. The credit intermediation function of banks is broken because of adverse expectations on future business and cannot be fixed by monetary and fiscal policy. Incentives to business and consumers are more likely to be effective in this environment in recovering willingness to assume risk on the part of the private sector, which is the driver of growth and job creation.

Table I-2, US, Selected Assets and Liabilities of Commercial Banks, at Break Adjusted, Seasonally Adjusted Annual Rate, ∆%

	2011	2012	2013	2014	2015	2016	Aug 2017	Sep 2017
Total Assets	5.2	2.6	7.1	7.4	3.5	2.8	8.5	1.1
Bank Credit	1.6	4.1	1.2	6.9	7.3	6.8	3.0	3.1
Securities in Bank Credit	1.9	7.6	-1.5	7.1	5.9	7.8	1.2	0.2
Treasury & Agency Securities	3.2	8.4	-5.2	11.8	8.8	10.0	1.6	1.6
Other Securities	-0.9	5.8	6.9	-2.3	-0.6	2.4	0.1	-3.7
Loans & Leases	1.5	2.9	2.3	6.8	7.8	6.4	3.6	4.2
Real Estate Loans	-3.7	-1.1	-1.0	2.4	5.2	6.5	2.4	1.2
Commercial Real Estate Loans	-6.3	-1.3	4.5	6.7	10.3	10.3	3.9	-1.0
Consumer Loans	-1.7	0.5	3.2	5.3	5.9	6.9	3.4	8.3
Commercial & Industrial Loans	8.6	11.6	6.9	12.0	10.6	6.7	3.5	6.4
Other Loans & Leases	18.6	8.1	5.9	14.6	13.0	5.5	7.1	5.9
Cash Assets	48.1	-2.2	54.5	12.3	-7.8	-14.4	35.9	-9.9
Total Liabilities	5.5	2.4	8.2	7.6	3.2	2.8	9.3	0.4
Deposits	6.7	7.2	6.5	6.4	4.9	4.4	3.4	2.5

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-1 of the Board of Governors of the Federal Reserve System provides quarterly seasonally adjusted annual rates (SAAR) of cash assets in US commercial banks from 1973 to 2017. Unconventional monetary policy caused an increase in cash assets in late 2008 of close to 500 percent at SAAR and in following policy impulses. Such aggressive policies were not required for growth of GDP at the average rate of 4.0 percent in 32 quarters of cyclical expansion from IQ1983 to IVQ1990. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). In contrast, the average rate in 32 quarters of cyclical expansion from IIIQ2009 to IIQ2017 has been at the rate of 2.2 percent (https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/mediocre-cyclical-united-states.html). The difference in magnitude of the recessions is not sufficient to explain weakness of the current cyclical expansion. Bordo (2012Sep27) and Bordo and Haubrich (2012DR) find that growth is higher after deeper contractions and contractions with financial crises. There were two consecutive contractions in the 1980s with decline of 2.2 percent in two quarters from IQ1980 to IIIQ1980 and 2.5 percent from IIIQ1981 to IVQ1982 that are almost identical to the contraction of 4.2 percent from IVQ2007 to IIIQ2009. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). There was also a decade-long financial and banking crisis during the 1980s. The debt crisis of 1982 (Pelaez 1986) wiped out a large part of the capital of large US money-center banks. Benston and Kaufman (1997, 139) find that there was failure of 1150 US commercial and savings banks between 1983 and 1990, or about 8 percent of the industry in 1980, which is nearly twice more than between the establishment of the Federal Deposit Insurance Corporation in 1934 through 1983. More than 900 savings and loans associations, representing 25 percent of the industry, were closed, merged or placed in conservatorships (see Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 74-7). The Financial Institutions Reform, Recovery and Enforcement Act of 1989 (FIRREA) created the Resolution Trust Corporation (RTC) and the Savings Association Insurance Fund (SAIF) that received $150 billion of taxpayer funds to resolve insolvent savings and loans. The GDP of the US in 1989 was $5657.7 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.65 percent of GDP in a year. The US Bureau of Economic Analysis estimates GDP of $18,624.5 billion in 2016, such that the bailout would be equivalent to cost to taxpayers of about $493.5 billion in current GDP terms. A major difference with the Troubled Asset Relief Program (TARP) for private-sector banks is that most of the costs were recovered with interest gains whereas in the case of savings and loans there was no recovery.

Chart I-1, US, Cash Assets, Commercial Banks, Seasonally Adjusted Annual Rate, Monthly, 1973-2017, ∆%

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-2 of the Board of Governors of the Federal Reserve System provides quarterly SAARs of bank credit at US commercial banks from 1947 to 2017. Rates collapsed sharply during the global recession as during the recessions of the 1980s and then rebounded. In both episodes, rates of growth of bank credit did not return to earlier magnitudes.

Chart I-2, US, Bank Credit, Commercial Banks, Seasonally Adjusted Annual Rate, Monthly, 1947-2017, ∆%

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-3 of the Board of Governors of the Federal Reserve System provides deposits at US commercial banks from 1973 to 2017. Deposits fell sharply during and after the global recession but then rebounded in the cyclical expansion.

Chart I-3, US, Deposits, Commercial Banks, Seasonally Adjusted Annual Rate, Monthly, 1973-2017, ∆%

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

There is similar behavior in the 1980s and in the current cyclical expansion of SAARs holdings of Treasury and agency securities in US commercial banks provided in Chart I-4 of the Board of Governors of the Federal Reserve System for the period 1947 to 2017. Sharp reductions of holdings during the contraction were followed by sharp increases.

Chart I-4, US, Treasury and Agency Securities in Bank Credit, Commercial Banks, Seasonally Adjusted Annual Rate, Monthly, 1947-2017,

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-5 of the Board of Governors of the Federal Reserve System provides SAARs of change of total loans and leases in US commercial banks from 1947 to 2017. The decline of SAARs in the current cycle was much sharper and the rebound did not recover earlier growth rates. Part of the explanation originates in demand for loans that was high during rapid economic growth at 4.5 percent per year on average in the cyclical expansion of the 1980s in contrast with lower demand during tepid economic growth at 2.1 percent per year on average in the current weak expansion.

Chart I-5, US, Loans and Leases in Bank Credit, Commercial Banks, Seasonally Adjusted Annual Rate, Monthly, 1947-2017, ∆%

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

There is significant difference in the two cycles of the 1980s and the current one in quarterly SAARs of real estate loans in US commercial banks provided in Chart I-6 of the Board of Governors of the Federal Reserve System. The difference is explained by the debacle in real estate after 2006 compared to expansion during the 1980s even during the crisis of savings and loans and real estate credit. In both cases, government policy tried to influence recovery and avoid market clearing.

Chart I-6, US, Real Estate Loans in Bank Credit, Commercial Banks, Seasonally Adjusted Annual Rate, Monthly, 1947-2017, ∆%

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

There is significant difference in quarterly SAARs of change of consumer loans in US commercial banks in the 1980s and during the current cycle as shown in Chart I-7 of the Board of Governors of the Federal Reserve System. Quarterly SAARs of consumer loans in US commercial banks fell sharply during the contraction of 1980 and oscillated with upward trend during the contraction of 1983-1984 but increased sharply in the cyclical expansion. In contrast, SAARs of consumer loans in US commercial banks collapsed to high negative magnitudes during the contraction, increased at very low magnitudes during the current cyclical expansion with recent higher rates.

Chart I-7, US, Consumer Loans in Bank Credit, Commercial Banks, Seasonally Adjusted Annual Rate, Monthly, 1958-2017, ∆%

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

The departing theoretical framework of Bordo and Haubrich (2012DR) is the plucking model of Friedman (1964, 1988). Friedman (1988, 1) recalls, “I was led to the model in the course of investigating the direction of influence between money and income. Did the common cyclical fluctuation in money and income reflect primarily the influence of money on income or of income on money?” Friedman (1964, 1988) finds useful for this purpose to analyze the relation between expansions and contractions. Analyzing the business cycle in the United States between 1870 and 1961, Friedman (1964, 15) found that “a large contraction in output tends to be followed on the average by a large business expansion; a mild contraction, by a mild expansion.” The depth of the contraction opens up more room in the movement toward full employment (Friedman 1964, 17):

“Output is viewed as bumping along the ceiling of maximum feasible output except that every now and then it is plucked down by a cyclical contraction. Given institutional rigidities and prices, the contraction takes in considerable measure the form of a decline in output. Since there is no physical limit to the decline short of zero output, the size of the decline in output can vary widely. When subsequent recovery sets in, it tends to return output to the ceiling; it cannot go beyond, so there is an upper limit to output and the amplitude of the expansion tends to be correlated with the amplitude of the contraction.”

Kim and Nelson (1999) test the asymmetric plucking model of Friedman (1964, 1988) relative to a symmetric model using reference cycles of the NBER and find evidence supporting the Friedman model. Bordo and Haubrich (2012DR) analyze 27 cycles beginning in 1872, using various measures of financial crises while considering different regulatory and monetary regimes. The revealing conclusion of Bordo and Haubrich (2012DR, 2) is that:

“Our analysis of the data shows that steep expansions tend to follow deep contractions, though this depends heavily on when the recovery is measured. In contrast to much conventional wisdom, the stylized fact that deep contractions breed strong recoveries is particularly true when there is a financial crisis. In fact, on average, it is cycles without a financial crisis that show the weakest relation between contraction depth and recovery strength. For many configurations, the evidence for a robust bounce-back is stronger for cycles with financial crises than those without.”

The average rate of growth of real GDP in expansions after recessions with financial crises was 8 percent but only 6.9 percent on average for recessions without financial crises (Bordo 2012Sep27). Real GDP declined 12 percent in the Panic of 1907 and increased 13 percent in the recovery, consistent with the plucking model of Friedman (Bordo 2012Sep27). Bordo (2012Sep27) finds two probable explanations for the weak recovery during the current economic cycle: (1) collapse of United States housing; and (2) uncertainty originating in fiscal policy, regulation and structural changes. There are serious doubts if monetary policy is adequate to recover the economy under these conditions.

Lucas (2011May) estimates US economic growth in the long-term at 3 percent per year and about 2 percent per year in per capita terms. There are displacements from this trend caused by events such as wars and recessions but the economy grows much faster during the expansion, compensating for the contraction and maintaining trend growth over the entire cycle. Historical US GDP data exhibit remarkable growth: Lucas (2011May) estimates an increase of US real income per person by a factor of 12 in the period from 1870 to 2010. The explanation by Lucas (2011May) of this remarkable growth experience is that government provided stability and education while elements of “free-market capitalism” were an important driver of long-term growth and prosperity. Lucas sharpens this analysis by comparison with the long-term growth experience of G7 countries (US, UK, France, Germany, Canada, Italy and Japan) and Spain from 1870 to 2010. Countries benefitted from “common civilization” and “technology” to “catch up” with the early growth leaders of the US and UK, eventually growing at a faster rate. Significant part of this catch up occurred after World War II. Lucas (2011May) finds that the catch up stalled in the 1970s. The analysis of Lucas (2011May) is that the 20-40 percent gap that developed originated in differences in relative taxation and regulation that discouraged savings and work incentives in comparison with the US. A larger welfare and regulatory state, according to Lucas (2011May), could be the cause of the 20-40 percent gap. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. The key indicator of growth of real income per capita, which is what a person earns after inflation, measures long-term economic growth and prosperity. A refined concept would include real disposable income per capita, which is what a person earns after inflation and taxes.

Table IB-1 provides the data required for broader comparison of long-term and cyclical performance of the United States economy. Revisions and enhancements of United States GDP and personal income accounts by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) provide valuable information on long-term growth and cyclical behavior. First, Long-term performance. Using annual data, US GDP grew at the average rate of 3.2 percent per year from 1929 to 2016 and at 3.2 percent per year from 1947 to 2016. Real disposable income grew at the average yearly rate of 3.2 percent from 1929 to 2016 and at 3.7 percent from 1947 to 1999. Real disposable income per capita grew at the average yearly rate of 2.0 percent from 1929 to 2016 and at 2.3 percent from 1947 to 1999. US economic growth was much faster during expansions, compensating contractions in maintaining trend growth for whole cycles. Using annual data, US real disposable income grew at the average yearly rate of 3.5 percent from 1980 to 1989 and real disposable income per capita at 2.6 percent. The US economy has lost its dynamism in the current cycle: real disposable income grew at the yearly average rate of 1.8 percent from 2006 to 2016 and real disposable income per capita at 1.0 percent. Real disposable income grew at the average rate of 1.7 percent from 2007 to 2016 and real disposable income per capita at 0.9 percent. Table IB-1 illustrates the contradiction of long-term growth with the proposition of secular stagnation (Hansen 1938, 1938, 1941 with early critique by Simons (1942). Secular stagnation would occur over long periods. Table IB-1 also provides the corresponding rates of population growth that is only marginally lower at 0.8 to 0.9 percent recently from 1.1 percent over the long-term. GDP growth fell abruptly from 2.6 percent on average from 2000 to 2006 to 1.4 percent from 2006 to 2016 and 1.3 percent from 2007 to 2017 and real disposable income growth fell from 2.9 percent on average from 2000 to 2006 to 1.8 percent from 2006 to 2016. The decline of growth of real per capita disposable income is even sharper from average 2.0 percent from 2000 to 2006 to 1.0 percent from 2006 to 2016 and 0.9 percent from 2007 to 2016 while population growth was 0.8 percent on average. Lazear and Spletzer (2012JHJul122) provide theory and measurements showing that cyclic factors explain currently depressed labor markets. This is also the case of the overall economy. Second, first four quarters of expansion. Growth in the first four quarters of expansion is critical in recovering loss of output and employment occurring during the contraction. In the first four quarters of expansion from IQ1983 to IVQ1983: GDP increased 7.8 percent, real disposable personal income 5.3 percent and real disposable income per capita 4.4 percent. In the first four quarters of expansion from IIIQ2009 to IIQ2010: GDP increased 2.7 percent, real disposable personal income 0.2 percent and real disposable income per capita decreased 0.7 percent. Third, first 32 quarters of expansion. In the expansion from IQ1983 to IVQ1990: GDP grew 37.2 percent at the annual equivalent rate of 4.0 percent; real disposable income grew 31.5 percent at the annual equivalent rate of 3.5 percent; and real disposable income per capita grew 21.9 percent at the annual equivalent rate of 2.5 percent. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm).

In the expansion from IIIQ2009 to IIQ2017: GDP grew 18.6 percent at the annual equivalent rate of 2.2 percent; real disposable income grew 15.9 percent at the annual equivalent rate of 1.9 percent; and real disposable personal income per capita grew 9.4 percent at the annual equivalent rate of 1.1 percent. Fourth, entire quarterly cycle. In the entire cycle combining contraction and expansion from IQ1980 to IVQ1990: GDP grew 37.0 percent at the annual equivalent rate of 2.8 percent; real disposable personal income grew 39.2 percent at the annual equivalent rate of 3.0 percent; and real disposable personal income per capita 25.1 percent at the annual equivalent rate of 2.0 percent. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). In the entire cycle combining contraction and expansion from IVQ2007 to IIQ2017: GDP grew 13.6 percent at the annual equivalent rate of 1.4 percent; real disposable personal income increased 17.8 percent at the annual equivalent rate of 1.7 percent; and real disposable personal income per capita grew 9.7 percent at the annual equivalent rate of 1.0 percent. The United States grew during its history at high rates of per capita income that made its economy the largest in the world. That dynamism is disappearing. Bordo (2012 Sep27) and Bordo and Haubrich (2012DR) provide convincing evidence that recoveries have been faster after deeper recessions and recessions with financial crises, casting serious doubts on the conventional explanation of weak growth during the current expansion allegedly because of the depth of the contraction of 4.2 percent from IVQ2007 to IIQ2009 and the financial crisis. The proposition of secular stagnation should explain a long-term process of decay and not the actual abrupt collapse of the economy and labor markets currently.

Chart I-8 of the Board of Governors of the Federal Reserve System provides cash assets in commercial banks not seasonally adjusted in billions of dollars from 1973 to 2017. Increases in bank cash reserves processed acquisitions of securities for the portfolio of the central bank. There is no comparable experience in US economic history and such flood of money was never required to return US economic growth to trend of 3 percent per year and 2 percent per year in per capita income after events such as recessions and wars (Lucas 2011May). It is difficult to argue that higher magnitudes of monetary and fiscal policy impulses would have been more successful. Discovery of such painless and fast adjustment by gigantic impulses of monetary policy of zero interest rates and trillions of dollars of bond buying would have occurred earlier with prior cases of successful implementation. Selective incentives to the private sector of a long-term nature could have been more effective.

Chart I-8, US, Cash Assets in Commercial Banks, Not Seasonally Adjusted, Monthly, 1973-2017, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-9 of the Board of Governors of the Federal Reserve System provides total assets of Federal Reserve Banks in millions of dollars on Wednesdays from Dec 18, 2002 to Oct 25, 2017. This is what is referred as the leverage of the central bank balance sheet in monetary policy (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-62, Regulation of Banks and Finance (2009b) 224-27). Consecutive rounds of unconventional monetary policy increased total assets by purchase of mortgage-backed securities, agency securities and Treasury securities. Bank reserves in cash and deposited at the central bank swelled as shown in Chart I-8. The central bank created assets in the form of securities financed with creation of liabilities in the form of reserves of depository institutions.

Chart I-9, US, Total Assets of Federal Reserve Banks, Wednesday Level, Millions of Dollars, Dec 18, 2002 to Oct 25, 2017

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h41/current/h41.htm#h41tab1

Chart I-10 of the Board of Governors of the Federal Reserve System provides deposits in US commercial banks not seasonally adjusted in billions of dollars from 1973 to 2017. Deposit growth clearly accelerated after 2001 and continued during the current cyclical expansion after bumps during the global recession.

Chart I-10, US, Deposits in Commercial Banks, Not Seasonally Adjusted, Monthly, 1973-2017, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-11 of the Board of Governors of the Federal Reserve System provides Treasury and agency securities in US commercial banks, not seasonally adjusted, in billions of dollars from 1947 to 2017. Holdings stabilized between the recessions of 2001 and after IVQ2007. There was rapid growth during the global contraction especially after unconventional monetary policy in 2008 and nearly vertical increase without prior similar historical experience during the various bouts of unconventional monetary policy. Banks hoard cash and less risky Treasury and agency securities instead of risky lending because of the weakness of the economy and the lack of demand for financing sound business projects. Banks and investors in general are avoiding exposures to high-duration fixed-income securities because of possible price losses during increases in yields. There is decline of bank holdings of Treasury and agency securities in the final segment with subsequent sharp recovery.

Chart I-11, US, Treasury and Agency Securities in Bank Credit, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1947-2017, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-12 of the Board of Governors of the Federal Reserve System provides total loans and leases in US commercial banks not seasonally adjusted in billions of dollars from 1947 to 2017. Total loans and leases of US commercial banks contracted sharply, stalled during the cyclical expansion and resumed growth.

Chart I-12, US, Loans and Leases in Bank Credit, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1947-2017, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-13 of the Board of Governors of the Federal Reserve System provides real estate loans in US commercial banks not seasonally adjusted in billions of dollars from 1947 to 2017. Housing subsidies and low interest rates caused a point of inflexion to higher, nearly vertical growth until 2007. Real estate loans have contracted in downward trend partly because of adverse effects of uncertainty on the impact on balance sheets of the various mechanisms of resolution imposed by policy. Nick Timiraos, writing on “Push for cheaper credit hits wall,” on Dec 24, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324660404578197782701079650.html), provides important information and analysis on housing finance. Quantitative easing consists of withdrawing supply of mortgage-backed securities by acquiring them as assets in the Fed balance sheet. Lending banks obtain funds for mortgages by bundling them according to risk and other characteristics and selling them to investors, using the proceeds from the sale to provide the loans to homebuyers or refinancing homeowners. Banks earn net revenue to remunerate capital required for operations from the spread between the rate received from mortgage debtors and the rate implicit in the yield of the mortgage-backed securities. Nick Timiraos (Ibid) finds that the spread was around 0.5 percentage points before the financial crisis of 2007, widening to 1 percentage point after the crisis but jumping to 1.6 percentage points after the Fed engaged in another program of buying mortgage-backed securities, oscillating currently around 1.3 percentage points. The spread has widened because banks have higher costs originating in regulation, litigation on repurchasing defaulted mortgages, loss in case of default and more prudent but more costly scrutiny of property appraisals and income verification. As a result, even if quantitative easing had lowered yields of mortgage-backed securities there would not be proportionate reduction in mortgage rates and even less likely construction and sales of houses. There is sharp recovery in the final segment.

Chart I-13, US, Real Estate Loans in Bank Credit, Not Seasonally Adjusted, Monthly, 1947-2017, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-14 of the Board of Governors of the Federal Reserve System provides consumer loans in US commercial banks not seasonally adjusted in billions of dollars from 1947 to 2017. Consumer loans even increased during the contraction then declined and increased vertically to decline again. There is renewed growth. There was high demand for reposition of durable goods that exhausted and limited consumption again with increase in savings rates in recent periods. Shayndi Raice and Nick Timiraos, writing on “Banks cut as mortgage boom ends,” on Jan 9, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303754404579310940019239208), analyze the drop in mortgage applications to a 13-year low, as measured by the Mortgage Bankers Association. Nick Timiraos, writing on “Demand for home loans plunges,” on Apr 24, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304788404579522051733228402?mg=reno64-wsj), analyzes data in Inside Mortgage Finance that mortgage lending of $235 billion in IQ2014 is 58 percent lower than a year earlier and 23 percent below IVQ2013. Mortgage lending collapsed to the lowest level in 14 years. In testimony before the Committee on the Budget of the US Senate on May 8, 2014, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm): “One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.”

Chart I-14, US, Consumer Loans in Bank Credit, Not Seasonally Adjusted, US Commercial Banks, Monthly, 1947-2017, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-15 of the Board of Governors of the Federal Reserve System provides commercial and industrial loans not seasonally adjusted in billions of dollars from 1947 to 2017. Commercial and industrial loans fell sharply during both contractions in 2001 and after IVQ2007 and then rebounded with accelerated growth. Commercial and industrial loans have not reached again the trend extrapolated from the peak during the global recession and appear to vacillate in the final segment.

Chart I-15, US, Commercial and Industrial Loans in Bank Credit, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1947-2017, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-16 and Chart I-16A are quite revealing in analyzing the state of bank credit in the US economy. The upper curves are (1) deposits and (2) loans and leases in bank credit. Historically since 1973, the level and rate of change of deposits and loans and leases in bank credit were almost identical. The lower two curves are Treasury and agency securities in bank credit and cash assets with treasury and agency securities moving closely with cash assets until the 1990s when Treasury and agency securities exceeded cash assets. There is convergence in the final segment after cash assets exceeded treasury and agency securities. The shaded area of the recession from IV2007 to IIQ2009 shows a break in the level and rate of movement of the series. Deposits continued to expand rapidly through the recession and the following expansion period. Loans and leases fell and barely recovered the level of trend before the recession while deposits moved nearly vertically well above the level before the recession. While Treasury and agency securities in bank credit continued to expand at a higher rate, reaching a level well above that before the recession, cash assets jumped as the counterpart of excess reserves in banks that financed quantitative easing or massive outright purchases of securities for the balance sheet of the Fed. Unconventional monetary policy of zero interest rates and outright purchases of securities caused sharp increases of deposits, cash assets and Treasury and agency securities in bank credit but not in loans and leases. There is much discussion about the almost impossible task of evaluating monetary policy in terms of costs and benefits. Before the financial crisis, Chairman Greenspan (2004) analyzes monetary policy and its limitations (see Pelaez and Pelaez, The Global Recession Risk (2007), 13-4, 212-13) that do not differ from those of private financial institutions:

“The Federal Reserve’s experiences over the past two decades make it clear that uncertainty is not just a pervasive feature of the monetary policy landscape; it is the defining characteristic of that landscape. The term “uncertainty” is meant here to encompass both “Knightian uncertainty,” in which the probability distribution of outcomes is unknown, and “risk,” in which uncertainty of outcomes is delimited by a known probability distribution. In practice, one is never quite sure what type of uncertainty one is dealing with in real time, and it may be best to think of a continuum ranging from well-defined risks to the truly unknown.

As a consequence, the conduct of monetary policy in the United States has come to involve, at its core, crucial elements of risk management. This conceptual framework emphasizes understanding as much as possible the many sources of risk and uncertainty that policymakers face, quantifying those risks when possible, and assessing the costs associated with each of the risks. In essence, the risk management approach to monetary policymaking is an application of Bayesian decision making.

This framework also entails devising, in light of those risks, a strategy for policy directed at maximizing the probabilities of achieving over time our goals of price stability and the ma

ximum sustainable economic growth that we associate with it. In designing strategies to meet our policy objectives, we have drawn on the work of analysts, both inside and outside the Fed, who over the past half century have devoted much effort to improving our understanding of the economy and its monetary transmission mechanism. A critical result has been the identification of a relatively small set of key relationships that, taken together, provide a useful approximation of our economy’s dynamics. Such an approximation underlies the statistical models that we at the Federal Reserve employ to assess the likely influence of our policy decisions.

However, despite extensive efforts to capture and quantify what we perceive as the key macroeconomic relationships, our knowledge about many of the important linkages is far from complete and, in all likelihood, will always remain so. Every model, no matter how detailed or how well designed, conceptually and empirically, is a vastly simplified representation of the world that we experience with all its intricacies on a day-to-day basis.

Given our inevitably incomplete knowledge about key structural aspects of an ever-changing economy and the sometimes asymmetric costs or benefits of particular outcomes, a central bank needs to consider not only the most likely future path for the economy but also the distribution of possible outcomes about that path. The decision makers then need to reach a judgment about the probabilities, costs, and benefits of the various possible outcomes under alternative choices for policy.”

Risk management tools are as likely to fail in private financial institutions as in central banks because of the difficulty of modeling risk during uncertainty. There is no such thing as riskless financial management. “Whale” trades at official institutions causing wide swings of financial and economic variables do not receive the same attention as those in large private banking institutions such as the teapot storm over JP Morgan Chase.

The post of this blog on Nov 8, 2009 is currently relevant (https://cmpassocregulationblog.blogspot.com/2009/11/how-big-bank-carlos-manuel-pelaezs.html):

Sunday, November 8, 2009

How Big a Bank
Carlos Manuel Peláez's Latest Blog Posts
How Big a Bank
5:56 PM PST, November 8, 2009
Agendas of financial regulation in parliaments, international official institutions and monetary authorities include limits on the size of banks or how big a bank should be. These proposals imply that regulators would decide the total value of assets held by banks. Assets would have to be weighted by risk, which is the best practice applied in the Basel capital accords. Regulators would decide not only the total value of assets but also the structure or percentage share of assets by risk class and credit rating such as how much in consumer credit, real estate lending, securities holding, corporate lending and so on. If the regulators decide on the total value of assets and their risk, they effectively micro manage bank decisions on risk and return. Managers would only implement regulatory criteria with little decision power on how best to reward shareholder capital. Regulators would mandate maximum assets and their risk distribution by leverage, credit and liquidity regulation. There are two concerns on the regulation of how big a bank should be. First, there is the issue of best practice in bank management and its consequences for financing prosperity. Banking is characterized by declining costs because of bulky fixed investments required for initiation of lines of business (Pelaez and Pelaez, Regulation of Banks and Finance, 82-9, Financial Regulation after the Global Recession, 63-9). There has been a new industrial/technological revolution in the past three decades centered on information technology (IT). Banking is highly intensive in the creation, processing, transmission and decision use of information. The first transaction of a $100 million IT facility costs $100 million but the hundred millionth costs only one dollar. Competitive banking requires a large volume of transactions to reach the minimum cost of operations. At the time of the call report for the implementation of Basel II in 2006, 11 banking organizations had total assets of $4.6 trillion, equivalent to 44 percent of total US banking assets of $10.5 trillion, and about $978 billion in foreign assets, equivalent to 96 percent of US foreign banking assets of $1 trillion (Pelaez and Pelaez, Globalization and the State: Vol. II, 147). Concentration likely increased during the credit/dollar crisis and its reversal by regulation could cause another confidence shock. The regulation of how big a bank should be would disrupt investment in the best practice of using technology and delivery of products at lowest cost by US banking organizations. It would also undermine the competitiveness of US banks in international business, violating the essential principle of the Basel capital accords of maintaining fair competitive international banking. Second, the regulation of how big a bank should be is based on an inadequate interpretation of the credit crisis/global recession. The panic of confidence in financial markets is commonly attributed to the failure of Lehman Bros. in September 2008. Cochrane and Zingales have shown that the crisis of confidence originated in the proposal of the Troubled Asset Relief Program (TARP) of $700 billion two weeks after the failure of Lehman Bros. TARP was proposed in negative terms of: withdraw "toxic" assets from bank balance sheets of banks or there would be an economic catastrophe similar to the Great Depression. Counterparty risk perception rose sharply because of fear of banking panics, paralyzing sale and repurchase transactions and causing illiquidity of multiple market segments. The "toxin" was introduced by zero interest rates in 2003-4 that induced high leverage and risk, low liquidity and imprudent credit together with the purchase or guarantee of $1.6 trillion of nonprime mortgages by Fannie and Freddie on the good faith and credit of the US. Regulatory micro management of the volume and structure of risk of banks and financial markets will weaken banks, reducing the volume of credit required for steering the world economy from currently low levels of activity. It will also restructure markets with arbitrary concession of monopolistic power to less efficient banks, creating vulnerabilities to new crises. There is need for less intrusive regulation that induces a sustainable path of prosperity, using effectively the staff, expertise and resources of existing regulatory agencies.

Chart I-16, US, Deposits, Loans and Leases in Bank Credit, Cash Assets and Treasury and Agency Securities in Bank Credit, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1973-2016, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

Chart I-16A, Deposits, Loans and Leases in Bank Credit, Cash Assets and Treasury and Agency Securities in Bank Credit, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1995-2017, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h8/current/default.htm

IID Theory and Reality of Economic History, Cyclical Slow Growth Not Secular Stagnation and Monetary Policy Based on Fear of Deflation. Fear of deflation as had occurred during the Great Depression and in Japan was used as an argument for the first round of unconventional monetary policy with 1 percent interest rates from Jun 2003 to Jun 2004 and quantitative easing in the form of withdrawal of supply of 30-year securities by suspension of the auction of 30-year Treasury bonds with the intention of reducing mortgage rates (for fear of deflation see Pelaez and Pelaez, International Financial Architecture (2005), 18-28, and Pelaez and Pelaez, The Global Recession Risk (2007), 83-95). The financial crisis and global recession were caused by interest rate and housing subsidies and affordability policies that encouraged high leverage and risks, low liquidity and unsound credit (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4). Several past comments of this blog elaborate on these arguments, among which: http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html

If the forecast of the central bank is of recession and low inflation with controlled inflationary expectations, monetary policy should consist of lowering the short-term policy rate of the central bank, which in the US is the fed funds rate. The intended effect is to lower the real rate of interest (Svensson 2003LT, 146-7). The real rate of interest, r, is defined as the nominal rate, i, adjusted by expectations of inflation, π*, with all variables defined as proportions: (1+r) = (1+i)/(1+π*) (Fisher 1930). If i, the fed funds rate, is lowered by the Fed, the numerator of the right-hand side is lower such that if inflationary expectations, π*, remain unchanged, the left-hand (1+r) decreases, that is, the real rate of interest, r, declines. Expectations of lowering short-term real rates of interest by policy of the Federal Open Market Committee (FOMC) fixing a lower fed funds rate would lower long-term real rates of interest, inducing with a lag investment and consumption, or aggregate demand, that can lift the economy out of recession. Inflation also increases with a lag by higher aggregate demand and inflation expectations (Fisher 1933). This reasoning explains why the FOMC lowered the fed funds rate in Dec 2008 to 0 to 0.25 percent and left it unchanged.

The fear of the Fed is expected deflation or negative π*. In that case, (1+ π*) < 1, and (1+r) would increase because the right-hand side of the equation would be divided by a fraction. A simple numerical example explains the effect of deflation on the real rate of interest. Suppose that the nominal rate of interest or fed funds rate, i, is 0.25 percent, or in proportion 0.25/100 = 0.0025, such that (1+i) = 1.0025. Assume now that economic agents believe that inflation will remain at 1 percent for a long period, which means that π* = 1 percent, or in proportion 1/100 =0.01. The real rate of interest, using the equation, is (1+0.0025)/(1+0.01) = (1+r) = 0.99257, such that r = 0.99257 - 1 = -0.00743, which is a proportion equivalent to –(0.00743)100 = -0.743 percent. That is, Fed policy has created a negative real rate of interest of 0.743 percent with the objective of inducing aggregate demand by higher investment and consumption. This is true if expected inflation, π*, remains at 1 percent. Suppose now that expectations of deflation become generalized such that π* becomes -1 percent, that is, the public believes prices will fall at the rate of 1 percent in the foreseeable future. Then the real rate of interest becomes (1+0.0025) divided by (1-0.01) equal to (1.0025)/(0.99) = (1+r) = 1.01263, or r = (1.01263-1) = 0.01263, which results in positive real rate of interest of (0.01263)100 = 1.263 percent.

Irving Fisher also identified the impact of deflation on debts as an important cause of deepening contraction of income and employment during the Great Depression illustrated by an actual example (Fisher 1933, 346):

“By March, 1933, liquidation had reduced the debts about 20 percent, but had increased the dollar about 75 percent, so that the real debt, that is the debt measured in terms of commodities, was increased about 40 percent [100%-20%)X(100%+75%) =140%]. Unless some counteracting cause comes along to prevent the fall in the price level, such a depression as that of 1929-1933 (namely when the more the debtors pay the more they owe) tends to continue, going deeper, in a vicious spiral, for many years. There is then no tendency of the boat to stop tipping until it has capsized”

The nominal rate of interest must always be nonnegative, that is, i ≥ 0 (Hick 1937, 154-5):

“If the costs of holding money can be neglected, it will always be profitable to hold money rather than lend it out, if the rate of interest is not greater than zero. Consequently the rate of interest must always be positive. In an extreme case, the shortest short-term rate may perhaps be nearly zero. But if so, the long-term rate must lie above it, for the long rate has to allow for the risk that the short rate may rise during the currency of the loan, and it should be observed that the short rate can only rise, it cannot fall”

The interpretation by Hicks of the General Theory of Keynes is the special case in which at interest rates close to zero liquidity preference is infinitely or perfectly elastic, that is, the public holds infinitely large cash balances at that near zero interest rate because there is no opportunity cost of foregone interest. Increases in the money supply by the central bank would not decrease interest rates below their near zero level, which is called the liquidity trap. The only alternative public policy would consist of fiscal policy that would act similarly to an increase in investment, increasing employment without raising the interest rate.

An influential view on the policy required to steer the economy away from the liquidity trap is provided by Paul Krugman (1998). Suppose the central bank faces an increase in inflation. An important ingredient of the control of inflation is the central bank communicating to the public that it will maintain a sustained effort by all available policy measures and required doses until inflation is subdued and price stability is attained. If the public believes that the central bank will control inflation only until it declines to a more benign level but not sufficiently low level, current expectations will develop that inflation will be higher once the central bank abandons harsh measures. During deflation and recession the central bank has to convince the public that it will maintain zero interest rates and other required measures until the rate of inflation returns convincingly to a level consistent with expansion of the economy and stable prices. Krugman (1998, 161) summarizes the argument as:

“The ineffectuality of monetary policy in a liquidity trap is really the result of a looking-glass version of the standard credibility problem: monetary policy does not work because the public expects that whatever the central bank may do now, given the chance, it will revert to type and stabilize prices near their current level. If the central bank can credibly promise to be irresponsible—that is, convince the market that it will in fact allow prices to rise sufficiently—it can bootstrap the economy out of the trap”

This view is consistent with results of research by Christina Romer that “the rapid rates of growth of real output in the mid- and late 1930s were largely due to conventional aggregate demand stimulus, primarily in the form of monetary expansion. My calculations suggest that in the absence of these stimuli the economy would have remained depressed far longer and far more deeply than it actually did” (Romer 1992, 757-8, cited in Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 210-2). The average growth rate of the money supply in 1933-1937 was 10 percent per year and increased in the early 1940s. Romer calculates that GDP would have been much lower without this monetary expansion. The growth of “the money supply was primarily due to a gold inflow, which was in turn due to the devaluation in 1933 and to capital flight from Europe because of political instability after 1934” (Romer 1992, 759). Gold inflow coincided with the decline in real interest rates in 1933 that remained negative through the latter part of the 1930s, suggesting that they could have caused increases in spending that was sensitive to declines in interest rates. Bernanke finds dollar devaluation against gold to have been important in preventing further deflation in the 1930s (Bernanke 2002):

“There have been times when exchange rate policy has been an effective weapon against deflation. A striking example from US history is Franklin Roosevelt’s 40 percent devaluation of the dollar against gold in 1933-34, enforced by a program of gold purchases and domestic money creation. The devaluation and the rapid increase in money supply it permitted ended the US deflation remarkably quickly. Indeed, consumer price inflation in the United States, year on year, went from -10.3 percent in 1932 to -5.1 percent in 1933 to 3.4 percent in 1934. The economy grew strongly, and by the way, 1934 was one of the best years of the century for the stock market”

Fed policy is seeking what Irving Fisher proposed “that great depressions are curable and preventable through reflation and stabilization” (Fisher 1933, 350).

The President of the Federal Reserve Bank of Chicago argues that (Charles Evans 2010):

“I believe the US economy is best described as being in a bona fide liquidity trap. Highly plausible projections are 1 percent for core Personal Consumption Expenditures (PCE) inflation at the end of 2012 and 8 percent for the unemployment rate. For me, the Fed’s dual mandate misses are too large to shrug off, and there is currently no policy conflict between improving employment and inflation outcomes”

There are two types of monetary policies that could be used in this situation. First, the Fed could announce a price-level target to be attained within a reasonable time frame (Evans 2010):

“For example, if the slope of the price path is 2 percent and inflation has been underunning the path for some time, monetary policy would strive to catch up to the path. Inflation would be higher than 2 percent for a time until the path was reattained”

Optimum monetary policy with interest rates near zero could consist of “bringing the price level back up to a level even higher than would have prevailed had the disturbance never occurred” (Gauti Eggertsson and Michael Woodford 2003, 207). Bernanke (2003JPY) explains as follows:

“Failure by the central bank to meet its target in a given period leads to expectations of (and public demands for) increased effort in subsequent periods—greater quantities of assets purchased on the open market for example. So even if the central bank is reluctant to provide a time frame for meetings its objective, the structure of the price-level objective provides a means for the bank to commit to increasing its anti-deflationary efforts when its earlier efforts prove unsuccessful. As Eggertsson and Woodford show, the expectations that an increasing price level gap will give rise to intensified effort by the central bank should lead the public to believe that ultimately inflation will replace deflation, a belief that supports the central bank’s own objectives by lowering the current real rate of interest”

Second, the Fed could use its balance sheet to increase purchases of long-term securities together with credible commitment to maintain the policy until the dual mandates of maximum employment and price stability are attained.

In the restatement of the liquidity trap and large-scale policies of monetary/fiscal stimulus, Krugman (1998, 162) finds:

“In the traditional open economy IS-LM model developed by Robert Mundell [1963] and Marcus Fleming [1962], and also in large-scale econometric models, monetary expansion unambiguously leads to currency depreciation. But there are two offsetting effects on the current account balance. On one side, the currency depreciation tends to increase net exports; on the other side, the expansion of the domestic economy tends to increase imports. For what it is worth, policy experiments on such models seem to suggest that these effects very nearly cancel each other out.”

Krugman (1998) uses a different dynamic model with expectations that leads to similar conclusions.

The central bank could also be pursuing competitive devaluation of the national currency in the belief that it could increase inflation to a higher level and promote domestic growth and employment at the expense of growth and unemployment in the rest of the world. An essay by Chairman Bernanke in 1999 on Japanese monetary policy received attention in the press, stating that (Bernanke 2000, 165):

“Roosevelt’s specific policy actions were, I think, less important than his willingness to be aggressive and experiment—in short, to do whatever it took to get the country moving again. Many of his policies did not work as intended, but in the end FDR deserves great credit for having the courage to abandon failed paradigms and to do what needed to be done”

Quantitative easing has never been proposed by Chairman Bernanke or other economists as certain science without adverse effects. What has not been mentioned in the press is another suggestion to the Bank of Japan (BOJ) by Chairman Bernanke in the same essay that is very relevant to current events and the contentious issue of ongoing devaluation wars (Bernanke 2000, 161):

“Because the BOJ has a legal mandate to pursue price stability, it certainly could make a good argument that, with interest rates at zero, depreciation of the yen is the best available tool for achieving its mandated objective. The economic validity of the beggar-thy-neighbor thesis is doubtful, as depreciation creates trade—by raising home country income—as well as diverting it. Perhaps not all those who cite the beggar-thy-neighbor thesis are aware that it had its origins in the Great Depression, when it was used as an argument against the very devaluations that ultimately proved crucial to world economic recovery. A yen trading at 100 to the dollar is in no one’s interest”

Chairman Bernanke is referring to the argument by Joan Robinson based on the experience of the Great Depression that: “in times of general unemployment a game of beggar-my-neighbour is played between the nations, each one endeavouring to throw a larger share of the burden upon the others” (Robinson 1947, 156). Devaluation is one of the tools used in these policies (Robinson 1947, 157). Banking crises dominated the experience of the United States, but countries that recovered were those devaluing early such that competitive devaluations rescued many countries from a recession as strong as that in the US (see references to Ehsan Choudhri, Levis Kochin and Barry Eichengreen in Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 205-9; for the case of Brazil that devalued early in the Great Depression recovering with an increasing trade balance see Pelaez, 1968, 1968b, 1972; Brazil devalued and abandoned the gold standard during crises in the historical period as shown by Pelaez 1976, Pelaez and Suzigan 1981). Beggar-my-neighbor policies did work for individual countries but the criticism of Joan Robinson was that it was not optimal for the world as a whole.

Chairman Bernanke (2013Mar 25) reinterprets devaluation and recovery from the Great Depression:

“The uncoordinated abandonment of the gold standard in the early 1930s gave rise to the idea of "beggar-thy-neighbor" policies. According to this analysis, as put forth by important contemporary economists like Joan Robinson, exchange rate depreciations helped the economy whose currency had weakened by making the country more competitive internationally. Indeed, the decline in the value of the pound after 1931 was associated with a relatively early recovery from the Depression by the United Kingdom, in part because of some rebound in exports. However, according to this view, the gains to the depreciating country were equaled or exceeded by the losses to its trading partners, which became less internationally competitive--hence, ‘beggar thy neighbor.’ Economists still agree that Smoot-Hawley and the ensuing tariff wars were highly counterproductive and contributed to the depth and length of the global Depression. However, modern research on the Depression, beginning with the seminal 1985 paper by Barry Eichengreen and Jeffrey Sachs, has changed our view of the effects of the abandonment of the gold standard. Although it is true that leaving the gold standard and the resulting currency depreciation conferred a temporary competitive advantage in some cases, modern research shows that the primary benefit of leaving gold was that it freed countries to use appropriately expansionary monetary policies. By 1935 or 1936, when essentially all major countries had left the gold standard and exchange rates were market-determined, the net trade effects of the changes in currency values were certainly small. Yet the global economy as a whole was much stronger than it had been in 1931. The reason was that, in shedding the strait jacket of the gold standard, each country became free to use monetary policy in a way that was more commensurate with achieving full employment at home.”

Nurkse (1944) raised concern on the contraction of trade by competitive devaluations during the 1930s. Haberler (1937) dwelled on the issue of flexible exchange rates. Bordo and James (2001) provide perceptive exegesis of the views of Haberler (1937) and Nurkse (1944) together with the evolution of thought by Haberler. Policy coordination among sovereigns may be quite difficult in practice even if there were sufficient knowledge and sound forecasts. Friedman (1953) provided compelling case in favor of a system of flexible exchange rates.

Eichengreen and Sachs (1985) argue theoretically with measurements using a two-sector model that it is possible for series of devaluations to improve the welfare of all countries. There were adverse effects of depreciation on other countries but depreciation by many countries could be beneficial for all. The important counterfactual is if depreciations by many countries would have promoted faster recovery from the Great Depression. Depreciation in the model of Eichengreen and Sachs (1985) affected domestic and foreign economies through real wages, profitability, international competitiveness and world interest rates. Depreciation causes increase in the money supply that lowers world interest rates, promoting growth of world output. Lower world interest rates could compensate contraction of output from the shift of demand away from home goods originating in neighbor’s exchange depreciation. Eichengreen and Sachs (1985, 946) conclude:

“This much, however, is clear. We do not present a blanket endorsement of the competitive devaluations of the 1930s. Though it is indisputable that currency depreciation conferred macroeconomic benefits on the initiating country, because of accompanying policies the depreciations of the 1930s had beggar-thy-neighbor effects. Though it is likely that currency depreciation (had it been even more widely adopted) would have worked to the benefit of the world as a whole, the sporadic and uncoordinated approach taken to exchange-rate policy in the 1930s tended, other things being equal, to reduce the magnitude of the benefits.”

There could major difference in the current world economy. The initiating impulse for depreciation originates in zero interest rates on the fed funds rate. The dollar is the world’s reserve currency. Risk aversion intermittently channels capital flight to the safe haven of the dollar and US Treasury securities. In the absence of risk aversion, zero interest rates induce carry trades of short positions in dollars and US debt (borrowing) together with long leveraged exposures in risk financial assets such as stocks, emerging stocks, commodities and high-yield bonds. Without risk aversion, the dollar depreciates against every currency in the world. The dollar depreciated against the euro by 39.3 percent from USD 1.1423/EUR con Jun 26, 2003 to USD 1.5914/EUR on Jun 14, 2008 during unconventional monetary policy before the global recession (Table VI-1). Unconventional monetary policy causes devaluation of the dollar relative to other currencies, which can increase net exports of the US that increase aggregate economic activity (Yellen 2011AS). The country issuing the world’s reserve currency appropriates the advantage from initiating devaluation that in policy intends to generate net exports that increase domestic output.

Pelaez and Pelaez (Regulation of Banks and Finance (2009b), 208-209) summarize the experience of Brazil as follows:

“During 1927–9, Brazil accumulated ￡30 million of foreign exchange of which ￡20 million were deposited at its stabilization fund (Pelaez 1968, 43–4). After the decline in coffee prices and the first impact of the Great Depression in Brazil a hot money movement wiped out foreign exchange reserves. In addition, capital inflows stopped entirely. The deterioration of the terms of trade further complicated matters, as the value of exports in foreign currency declined abruptly. Because of this exchange crisis, the service of the foreign debt of Brazil became impossible. In August 1931, the federal government was forced to cancel the payment of principal on certain foreign loans. The balance of trade in 1931 was expected to yield ￡20 million whereas the service of the foreign debt alone amounted to ￡22.6 million. Part of the solution given to these problems was typical of the 1930s. In September 1931, the government of Brazil required that all foreign transactions were to be conducted through the Bank of Brazil. This monopoly of foreign exchange was exercised by the Bank of Brazil for the following three years. Export permits were granted only after the exchange derived from sales abroad was officially sold to the Bank, which in turn allocated it in accordance with the needs of the economy. An active black market in foreign exchange developed. Brazil was in the first group of countries that abandoned early the gold standard, in 1931, and suffered comparatively less from the Great Depression. The Brazilian federal government, advised by the BOE, increased taxes and reduced expenditures in 1931 to compensate a decline in custom receipts (Pelaez 1968, 40). Expenditures caused by a revolution in 1932 in the state of Sao Paulo and a drought in the northeast explain the deficit. During 1932–6, the federal government engaged in strong efforts to stabilize the budget. Apart from the deliberate efforts to balance the budget during the 1930s, the recovery in economic activity itself may have induced a large part of the reduction of the deficit (Ibid, 41). Brazil’s experience is similar to that of the United States in that fiscal policy did not promote recovery from the Great Depression.”

Is depreciation of the dollar the best available tool currently for achieving the dual mandate of higher inflation and lower unemployment? Bernanke (2002) finds dollar devaluation against gold to have been important in preventing further deflation in the 1930s (http://www.federalreserve.gov/boarddocs/speeches/2002/20021121/default.htm):

“Although a policy of intervening to affect the exchange value of the dollar is nowhere on the horizon today, it's worth noting that there have been times when exchange rate policy has been an effective weapon against deflation. A striking example from U.S. history is Franklin Roosevelt's 40 percent devaluation of the dollar against gold in 1933-34, enforced by a program of gold purchases and domestic money creation. The devaluation and the rapid increase in money supply it permitted ended the U.S. deflation remarkably quickly. Indeed, consumer price inflation in the United States, year on year, went from -10.3 percent in 1932 to -5.1 percent in 1933 to 3.4 percent in 1934.¹⁷ The economy grew strongly, and by the way, 1934 was one of the best years of the century for the stock market. If nothing else, the episode illustrates that monetary actions can have powerful effects on the economy, even when the nominal interest rate is at or near zero, as was the case at the time of Roosevelt's devaluation.”

Should the US devalue following Roosevelt? Alternatively, has monetary policy intended devaluation? Fed policy is seeking, deliberately or as a side effect, what Irving Fisher proposed “that great depressions are curable and preventable through reflation and stabilization” (Fisher, 1933, 350). The Fed has created not only high volatility of assets but also what many countries are regarding as a competitive devaluation similar to those criticized by Nurkse (1944). Yellen (2011AS, 6) admits that Fed monetary policy results in dollar devaluation with the objective of increasing net exports, which was the policy that Joan Robinson (1947) labeled as “beggar-my-neighbor” remedies for unemployment.

Friedman (1969) finds that the optimal rule for the quantity of money is deflation at a rate that results in a zero nominal interest rate (see Ireland 2003 and Cole and Kocherlakota 1998). Atkeson and Kehoe (2004) argue that central bankers are not inclined to implement policies that could result in deflation because of the interpretation of the Great Depression as closely related to deflation. They use panel data on inflation and growth of real output for 17 countries over more than 100 years. The time-series data for each individual country are broken into five-year events with deflation measured as average negative inflation and depression as average negative growth rate of real output. Atkeson and Kehoe (2004) find that the Great Depression from 1929 to 1934 is the only case of association between deflation and depression without any evidence whatsoever of such relation in any other period. Their conclusion is (Atkeson and Kehoe 2004, 99): “Our finding thus suggests that policymakers’ fear of anticipated policy-induced deflation that would result from following, say, the Friedman rule is greatly overblown.” Their conclusion on the experience of Japan is (Atkeson and Kehoe 2004, 99):

“Since 1960, Japan’s average growth rates have basically fallen monotonically, and since 1970, its average inflation rates have too. Attributing this 40-year slowdown to monetary forces is a stretch. More reasonable, we think, is that much of the slowdown is the natural pattern for a country that was far behind the world leaders and had begun to catch up.”

In the sample of Atkeson and Kehoe (2004), there are only eight five-year periods besides the Great Depression with both inflation and depression. Deflation and depression is shown in 65 cases with 21 of depression without deflation. There is no depression in 65 of 73 five-year periods and there is no deflation in 29 episodes of depression. There is a remarkable result of no depression in 90 percent of deflation episodes. Excluding the Great Depression, there is virtually no relation of deflation and depression. Atkeson and Kehoe (2004, 102) find that the average growth rate of Japan of 1.41 percent in the 1990s is “dismal” when compared with 3.20 percent in the United States but is not “dismal” when compared with 1.61 percent for Italy and 1.84 percent for France, which are also catch-up countries in modern economic growth (see Atkeson and Kehoe 1998). The conclusion of Atkeson and Kehoe (2004), without use of controls, is that there is no association of deflation and depression in their dataset.

Benhabib and Spiegel (2009) use a dataset similar to that of Atkeson and Kehoe (2004) but allowing for nonlinearity and inflation volatility. They conclude that in cases of low and negative inflation an increase of average inflation of 1 percent is associated with an increase of 0.31 percent of average annual growth. The analysis of Benhabib and Spiegel (2009) leads to the significantly different conclusion that inflation and economic performance are strongly associated for low and negative inflation. There is no claim of causality by Atkeson and Kehoe (2004) and Benhabib and Spiegel (2009).

Delfim Netto (1959) partly reprinted in Pelaez (1973) conducted two classical nonparametric tests (Mann 1945, Wallis and Moore 1941; see Kendall and Stuart 1968) with coffee-price data in the period of free markets from 1857 to 1906 with the following conclusions (Pelaez, 1976a, 280):

“First, the null hypothesis of no trend was accepted with high confidence; secondly, the null hypothesis of no oscillation was rejected also with high confidence. Consequently, in the nineteenth century international prices of coffee fluctuated but without long-run trend. This statistical fact refutes the extreme argument of structural weakness of the coffee trade.”

In his classic work on the theory of international trade, Jacob Viner (1937, 563) analyzed the “index of total gains from trade,” or “amount of gain per unit of trade,” denoted as T:

T= (∆P^e/∆Pⁱ)∆Q

Where ∆P^e is the change in export prices, ∆Pⁱ is the change in import prices and ∆Q is the change in export volume. Dorrance (1948, 52) restates “Viner’s index of total gain from trade” as:

“What should be done is to calculate an index of the value (quantity multiplied by price) of exports and the price of imports for any country whose foreign accounts are to be analysed. Then the export value index should be divided by the import price index. The result would be an index which would reflect, for the country concerned, changes in the volume of imports obtainable from its export income (i.e. changes in its "real" export income, measured in import terms). The present writer would suggest that this index be referred to as the ‘income terms of trade’ index to differentiate it from the other indexes at present used by economists.”

What really matters for an export activity especially during modernization is the purchasing value of goods that it exports in terms of prices of imports. For a primary producing country, the purchasing power of exports in acquiring new technology from the country providing imports is the critical measurement. The barter terms of trade of Brazil improved from 1857 to 1906 because international coffee prices oscillated without trend (Delfim Netto 1959) while import prices from the United Kingdom declined at the rate of 0.5 percent per year (Imlah 1958). The accurate measurement of the opportunity afforded by the coffee exporting economy was incomparably greater when considering the purchasing power in British prices of the value of coffee exports, or Dorrance’s (1948) income terms of trade.

The conventional theory that the terms of trade of Brazil deteriorated over the long term is without reality (Pelaez 1976a, 280-281):

“Moreover, physical exports of coffee by Brazil increased at the high average rate of 3.5 per cent per year. Brazil's exchange receipts from coffee-exporting in sterling increased at the average rate of 3.5 per cent per year and receipts in domestic currency at 4.5 per cent per year. Great Britain supplied nearly all the imports of the coffee economy. In the period of the free coffee market, British export prices declined at the rate of 0.5 per cent per year. Thus, the income terms of trade of the coffee economy improved at the relatively satisfactory average rate of 4.0 per cent per year. This is only a lower bound of the rate of improvement of the terms of trade. While the quality of coffee remained relatively constant, the quality of manufactured products improved significantly during the fifty-year period considered. The trade data and the non-parametric tests refute conclusively the long-run hypothesis. The valid historical fact is that the tropical export economy of Brazil experienced an opportunity of absorbing rapidly increasing quantities of manufactures from the "workshop" countries. Therefore, the coffee trade constituted a golden opportunity for modernization in nineteenth-century Brazil.”

Imlah (1958) provides decline of British export prices at 0.5 percent in the nineteenth century and there were no lost decades, depressions or unconventional monetary policies in the highly dynamic economy of England that drove the world’s growth impulse. Inflation in the United Kingdom between 1857 and 1906 is measured by the composite price index of O’Donoghue and Goulding (2004) at minus 7.0 percent or average rate of decline of 0.2 percent per year.

Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:

“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated.Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”

Cameron (1961) analyzes the mechanism by which the Industrial Revolution in Great Britain spread throughout Europe and Cameron (1967) analyzes the financing by banks of the Industrial Revolution in Great Britain. O’Donoghue and Goulding (2004) provide consumer price inflation in England since 1750 and MacFarlane and Mortimer-Lee (1994) analyze inflation in England over 300 years. Lucas (2004) estimates world population and production since the year 1000 with sustained growth of per capita incomes beginning to accelerate for the first time in English-speaking countries and in particular in the Industrial Revolution in Great Britain. The conventional theory is unequal distribution of the gains from trade and technical progress between the industrialized countries and developing economies (Singer 1950, 478):

“Dismissing, then, changes in productivity as a governing factor in changing terms of trade, the following explanation presents itself: the fruits of technical progress may be distributed either to producers (in the form of rising incomes) or to consumers (in the form of lower prices). In the case of manufactured commodities produced in more developed countries, the former method, i.e., distribution to producers through higher incomes, was much more important relatively to the second method, while the second method prevailed more in the case of food and raw material production in the underdeveloped countries. Generalizing, we may say -that technical progress in manufacturing industries showed in a rise in incomes while technical progress in the production of food and raw materials in underdeveloped countries showed in a fall in prices”

Temin (1997, 79) uses a Ricardian trade model to discriminate between two views on the Industrial Revolution with an older view arguing broad-based increases in productivity and a new view concentration of productivity gains in cotton manufactures and iron:

“Productivity advances in British manufacturing should have lowered their prices relative to imports. They did. Albert Imlah [1958] correctly recognized this ‘severe deterioration’ in the net barter terms of trade as a signal of British success, not distress. It is no surprise that the price of cotton manufactures fell rapidly in response to productivity growth. But even the price of woolen manufactures, which were declining as a share of British exports, fell almost as rapidly as the price of exports as a whole. It follows, therefore, that the traditional ‘old-hat’ view of the Industrial Revolution is more accurate than the new, restricted image. Other British manufactures were not inefficient and stagnant, or at least, they were not all so backward. The spirit that motivated cotton manufactures extended also to activities as varied as hardware and haberdashery, arms, and apparel.”

Phyllis Deane (1968, 96) estimates growth of United Kingdom gross national product (GNP) at around 2 percent per year for several decades in the nineteenth century. The facts that the terms of trade of Great Britain deteriorated during the period of epochal innovation and high rates of economic growth while the income terms of trade of the coffee economy of nineteenth-century Brazil improved at the average yearly rate of 4.0 percent from 1857 to 1906 disprove the hypothesis of weakness of trade as an explanation of relatively lower income and wealth. As Temin (1997) concludes, Britain did pass on lower prices and higher quality the benefits of technical innovation. Explanation of late modernization must focus on laborious historical research on institutions and economic regimes together with economic theory, data gathering and measurement instead of grand generalizations of weakness of trade and alleged neocolonial dependence (Stein and Stein 1970, 134-5):

“Great Britain, technologically and industrially advanced, became as important to the Latin American economy as to the cotton-exporting southern United States. [After Independence in the nineteenth century] Latin America fell back upon traditional export activities, utilizing the cheapest available factor of production, the land, and the dependent labor force.”

Summerhill (2015) contributes momentous solid facts and analysis with an ideal method combining economic theory, econometrics, international comparisons, data reconstruction and exhaustive archival research. Summerhill (2015) finds that Brazil committed to service of sovereign foreign and internal debt. Contrary to conventional wisdom, Brazil generated primary fiscal surpluses during most of the Empire until 1889 (Summerhill 2015, 37-8, Figure 2.1). Econometric tests by Summerhill (2015, 19-44) show that Brazil’s sovereign debt was sustainable. Sovereign credibility in the North-Weingast (1989) sense spread to financial development that provided the capital for modernization in England and parts of Europe (see Cameron 1961, 1967). Summerhill (2015, 3, 194-6, Figure 7.1) finds that “Brazil’s annual cost of capital in London fell from a peak of 13.9 percent in 1829 to only 5.12 percent in 1889. Average rates on secured loans in the private sector in Rio, however, remained well above 12 percent through 1850.” Financial development would have financed diversification of economic activities, increasing productivity and wages and ensuring economic growth. Brazil restricted creation of limited liability enterprises (Summerhill 2015, 151-82) that prevented raising capital with issue of stocks and corporate bonds. Cameron (1961) analyzed how the industrial revolution in England spread to France and then to the rest of Europe. The Société Générale de Crédit Mobilier of Émile and Isaac Péreire provided the “mobilization of credit” for the new economic activities (Cameron 1961). Summerhill (2015, 151-9) provides facts and analysis demonstrating that regulation prevented the creation of a similar vehicle for financing modernization by Irineu Evangelista de Souza, the legendary Visconde de Mauá. Regulation also prevented the use of negotiable bearing notes of the Caisse Générale of Jacques Lafitte (Cameron 1961, 118-9). The government also restricted establishment and independent operation of banks (Summerhill 2015, 183-214). Summerhill (2005, 198-9) measures concentration in banking that provided economic rents or a social loss. The facts and analysis of Summerhill (2015) provide convincing evidence in support of the economic theory of regulation, which postulates that regulated entities capture the process of regulation to promote their self-interest. There appears to be a case that excessively centralized government can result in regulation favoring private instead of public interests with adverse effects on economic activity. The contribution of Summerhill (2015) explains why Brazil did not benefit fully from trade as an engine of growth—as did regions of recent settlement in the vision of nineteenth-century trade and development of Ragnar Nurkse (1959)—partly because of restrictions on financing and incorporation. Professor Rondo E. Cameron, in his memorable A Concise Economic History of the World (Cameron 1989, 307-8), finds that “from a broad spectrum of possible forms of interaction between the financial sector and other sectors of the economy that requires its services, one can isolate three type-cases: (1) that in which the financial sector plays a positive, growth-inducing role; (2) that in which the financial sector is essentially neutral or merely permissive; and (3) that in which inadequate finance restricts or hinders industrial and commercial development.” Summerhill (1985) proves exhaustively that Brazil failed to modernize earlier because of the restrictions of an inadequate institutional financial arrangement plagued by regulatory capture for self-interest.

The experience of the United Kingdom with deflation and economic growth is relevant and rich. Table IE-1 uses yearly percentage changes of the composite index of prices of the United Kingdom of O’Donoghue and Goulding (2004). There are 73 declines of inflation in the 145 years from 1751 to 1896. Prices declined in 50.3 percent of 145 years. Some price declines were quite sharp and many occurred over several years. Table IE-1 also provides yearly percentage changes of the UK composite price index of O’Donoghue and Goulding (2004) from 1929 to 1934. Deflation was much sharper in continuous years in earlier periods than during the Great Depression. The United Kingdom could not have led the world in modern economic growth if there were meaningful causality from deflation to depression.

Table IE-1, United Kingdom, Negative Percentage Changes of Composite Price Index, 1751-1896, 1929-1934, Yearly ∆%

Year	∆%	Year	∆%	Year	∆%	Year	∆%
1751	-2.7	1797	-10.0	1834	-7.8	1877	-0.7
1753	-2.7	1798	-2.2	1841	-2.3	1878	-2.2
1755	-6.0	1802	-23.0	1842	-7.6	1879	-4.4
1758	-0.3	1803	-5.9	1843	-11.3	1881	-1.1
1759	-7.9	1806	-4.4	1844	-0.1	1883	-0.5
1760	-4.5	1807	-1.9	1848	-12.1	1884	-2.7
1761	-4.5	1811	-2.9	1849	-6.3	1885	-3.0
1768	-1.1	1814	-12.7	1850	-6.4	1886	-1.6
1769	-8.2	1815	-10.7	1851	-3.0	1887	-0.5
1770	-0.4	1816	-8.4	1857	-5.6	1893	-0.7
1773	-0.3	1819	-2.5	1858	-8.4	1894	-2.0
1775	-5.6	1820	-9.3	1859	-1.8	1895	-1.0
1776	-2.2	1821	-12.0	1862	-2.6	1896	-0.3
1777	-0.4	1822	-13.5	1863	-3.6	1929	-0.9
1779	-8.5	1826	-5.5	1864	-0.9	1930	-2.8
1780	-3.4	1827	-6.5	1868	-1.7	1931	-4.3
1785	-4.0	1828	-2.9	1869	-5.0	1932	-2.6
1787	-0.6	1830	-6.1	1874	-3.3	1933	-2.1
1789	-1.3	1832	-7.4	1875	-1.9	1934	0.0
1791	-0.1	1833	-6.1	1876	-0.3

Source:

O’Donoghue, Jim and Louise Goulding, 2004. Consumer Price Inflation since 1750. UK Office for National Statistics Economic Trends 604, Mar 2004, 38-46.

There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

“Not until the problem of full employment of our productive resources from the long-run, secular standpoint was upon us, were we compelled to give serious consideration to those factors and forces in our economy which tend to make business recoveries weak and anaemic (sic) and which tend to prolong and deepen the course of depressions. This is the essence of secular stagnation-sick recoveries which die in their infancy and depressions which feed on themselves and leave a hard and seemingly immovable core of unemployment. Now the rate of population growth must necessarily play an important role in determining the character of the output; in other words, the composition of the flow of final goods. Thus a rapidly growing population will demand a much larger per capita volume of new residential building construction than will a stationary population. A stationary population with its larger proportion of old people may perhaps demand more personal services; and the composition of consumer demand will have an important influence on the quantity of capital required. The demand for housing calls for large capital outlays, while the demand for personal services can be met without making large investment expenditures. It is therefore not unlikely that a shift from a rapidly growing population to a stationary or declining one may so alter the composition of the final flow of consumption goods that the ratio of capital to output as a whole will tend to decline.”

In the analysis of Hansen (1939, 3) of secular stagnation, economic progress consists of growth of real income per person driven by growth of productivity. The “constituent elements” of economic progress are “(a) inventions, (b) the discovery and development of new territory and new resources, and (c) the growth of population” (Hansen 1939, 3). Secular stagnation originates in decline of population growth and discouragement of inventions. According to Hansen (1939, 2), US population grew by 16 million in the 1920s but grew by one half or about 8 million in the 1930s with forecasts at the time of Hansen’s writing in 1938 of growth of around 5.3 million in the 1940s. Hansen (1939, 2) characterized demography in the US as “a drastic decline in the rate of population growth. Hansen’s plea was to adapt economic policy to stagnation of population in ensuring full employment. In the analysis of Hansen (1939, 8), population caused half of the growth of US GDP per year. Growth of output per person in the US and Europe was caused by “changes in techniques and to the exploitation of new natural resources.” In this analysis, population caused 60 percent of the growth of capital formation in the US. Declining population growth would reduce growth of capital formation. Residential construction provided an important share of growth of capital formation. Hansen (1939, 12) argues that market power of imperfect competition discourages innovation with prolonged use of obsolete capital equipment. Trade unions would oppose labor-savings innovations. The combination of stagnating and aging population with reduced innovation caused secular stagnation. Hansen (1939, 12) concludes that there is role for public investments to compensate for lack of dynamism of private investment but with tough tax/debt issues.

Table SE1 provides contributions to growth of GDP in the 1930s. These data were not available until much more recently. Residential investment (RSI) contributed 1.03 percentage points to growth of GDP of 8.0 percent in 1939, which is a high percentage of the contribution of gross private domestic investment of 2.39 percentage points. Residential investment contributed 0.42 percentage points to GDP growth of 8.8 percent in 1940 with gross private domestic investment contributing 3.99 percentage points.

Table SE1, US, Contributions to Growth of GDP

	GDP ∆%	PCE PP	GDI PP	NRI PP	RSI PP	Net Trade PP	GOVT PP
1930	-8.5	-3.96	-5.18	-1.84	-1.50	-0.31	0.94
1931	-6.4	-2.37	-4.28	-3.32	-0.40	-0.22	0.48
1932	-12.9	-7.00	-5.28	-2.78	-1.02	-0.20	-0.42
1933	-1.3	-1.79	1.16	-0.44	-0.24	-0.11	-0.52
1934	10.8	5.71	2.83	1.31	0.38	0.33	1.91
1935	8.9	4.69	4.54	1.41	0.56	-0.83	0.50
1936	12.9	7.68	2.58	2.10	0.47	0.24	2.44
1937	5.1	2.72	2.57	1.42	0.17	0.45	-0.64
1938	-3.3	-1.15	-4.13	-2.13	0.01	0.88	1.09
1939	8.0	4.11	2.39	0.71	1.03	0.07	1.41
1940	8.8	3.72	3.99	1.60	0.42	0.52	0.57

GDP ∆%: Annual Growth of GDP; PCE PP: Percentage Points Contributed by Personal Consumption Expenditures (PCE); GDI PP: Percentage Points Contributed by Gross Private Domestic Investment (GDI); NRI PP: Percentage Points Contributed by Nonresidential Investment (NRI); RSI: Percentage Points Contributed by Residential Investment; Net Trade PP: Percentage Points Contributed by Net Exports less Imports of Goods and Services; GOVT PP: Percentage Points Contributed by Government Consumption and Gross Investment

Source: Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

Table ES2 provides percentage shares of GDP in 1929, 1939, 1940, 2006 and 2015. The share of residential investment was 3.9 percent in 1929, 3.4 percent in 1939 and 6.0 percent in 2006 at the peak of the real estate boom. The share of residential investment in GDP has not been very high historically.

Table ES2, Percentage Shares in GDP

	1929	1939	1940	2006	2015
GDP	100.00	100.00	100.00	100.00	100.00
PCE	74.0	71.9	69.2	67.1	68.4
GDI	16.4	10.9	14.2	19.3	16.8
NRI	11.1	7.3	8.3	12.8	12.8
RSI	3.9	3.4	3.5	6.0	3.4
Net Trade	0.4	0.9	1.4	-5.6	-3.0
GOVT	9.2	16.3	15.2	19.1	17.8

PCE: Personal Consumption Expenditures; GDI: Gross Domestic Investment; NRI: Nonresidential Investment; RSI: Residential Investment; Net Trade: Net Exports less Imports of Goods and Services; GOVT: Government Consumption and Gross Investment

Source: Bureau of Economic Analysis

PCE: Personal Consumption Expenditures; GDI: Gross Private Domestic Investment; NRI: Nonresidential Investment; RSI: Residential Investment; Net Trade: Net Exports less Imports of Goods and Services; GOVT: Government Consumption and Gross Investment

Source: Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

An interpretation of the New Deal is that fiscal stimulus must be massive in recovering growth and employment and that it should not be withdrawn prematurely to avoid a sharp second contraction as it occurred in 1937 (Christina Romer 2009). Proposals for another higher dose of stimulus explain the current weakness by insufficient fiscal expansion and warn that failure to spend more can cause another contraction as in 1937. According to a different interpretation, private hours worked declined by 25 percent by 1939 compared with the level in 1929, suggesting that the economy fell to a lower path of expansion than in 1929 (works by Harold Cole and Lee Ohanian (1999) (cited in Pelaez and Pelaez, Regulation of Banks and Finance, 215-7). Major real variables of output and employment were below trend by 1939: -26.8 percent for GNP, -25.4 percent for consumption, -51 percent for investment and -25.6 percent for hours worked. Surprisingly, total factor productivity increased by 3.1 percent and real wages by 21.8 percent (Cole and Ohanian 1999). The policies of the Roosevelt administration encouraged increasing unionization to maintain high wages with lower hours worked and high prices by lax enforcement of antitrust law to encourage cartels or collusive agreements among producers. The encouragement by the government of labor bargaining by unions and higher prices by collusion depressed output and employment throughout the 1930s until Roosevelt abandoned the policies during World War II after which the economy recovered full employment (Cole and Ohanian 1999). The fortunate ones who worked during the New Deal received higher real wages at the expense of many who never worked again. In a way, the administration behaved like the father of the unionized workers and the uncle of the collusive rich, neglecting the majority in the middle. Inflation-adjusted GDP increased by 10.8 percent in 1934, 8.9 percent in 1935, 12.9 percent in 1936 but only 5.1 percent in 1937, contracting by -3.3 percent in 1938 (US Bureau of Economic Analysis cited in Pelaez and Pelaez, Financial Regulation after the Global Recession, 151, Globalization and the State, Vol. II, 206). The competing explanation is that the economy did not decline from 1937 to 1938 because of lower government spending in 1937 but rather because of the expansion of unions promoted by the New Deal and increases in tax rates (Thomas Cooley and Lee Ohanian 2010). Government spending adjusted for inflation fell only 0.7 percent in 1936 and 1937 and could not explain the decline of GDP by 3.4 percent in 1938. In 1936, the administration imposed a tax on retained profits not distributed to shareholders according to a sliding scale of 7 percent for retaining 1 percent of total net income up to 27 percent for retaining 70 percent of total net income, increasing costs of investment that were mostly financed in that period with retained earnings (Cooley and Ohanian 2010). The tax rate on dividends jumped from 10.1 percent in 1929 to 15.9 percent in 1932 and doubled by 1936. A recent study finds that “tax rates on dividends rose dramatically during the 1930s and imply significant declines in investment and equity values and nontrivial declines in GDP and hours of work” (Ellen McGrattan 2010), explaining a significant part of the decline of 26 percent in business fixed investment in 1937-1938. The National Labor Relations Act of 1935 caused an increase in union membership from 12 percent in 1934 to 25 percent in 1938. The alternative lesson from the 1930s is that capital income taxes and higher unionization caused increases in business costs that perpetuated job losses of the recession with current risks of repeating the 1930s (Cooley and Ohanian 1999).

The current application of Hansen’s (1938, 1939, 1941) proposition argues that secular stagnation occurs because full employment equilibrium can be attained only with negative real interest rates between minus 2 and minus 3 percent. Professor Lawrence H. Summers (2013Nov8) finds that “a set of older ideas that went under the phrase secular stagnation are not profoundly important in understanding Japan’s experience in the 1990s and may not be without relevance to America’s experience today” (emphasis added). Summers (2013Nov8) argues there could be an explanation in “that the short-term real interest rate that was consistent with full employment had fallen to -2% or -3% sometime in the middle of the last decade. Then, even with artificial stimulus to demand coming from all this financial imprudence, you wouldn’t see any excess demand. And even with a relative resumption of normal credit conditions, you’d have a lot of difficulty getting back to full employment.” The US economy could be in a situation where negative real rates of interest with fed funds rates close to zero as determined by the Federal Open Market Committee (FOMC) do not move the economy to full employment or full utilization of productive resources. Summers (2013Oct8) finds need of new thinking on “how we manage an economy in which the zero nominal interest rates is a chronic and systemic inhibitor of economy activity holding our economies back to their potential.”

Former US Treasury Secretary Robert Rubin (2014Jan8) finds three major risks in prolonged unconventional monetary policy of zero interest rates and quantitative easing: (1) incentive of delaying action by political leaders; (2) “financial moral hazard” in inducing excessive exposures pursuing higher yields of risker credit classes; and (3) major risks in exiting unconventional policy. Rubin (2014Jan8) proposes reduction of deficits by structural reforms that could promote recovery by improving confidence of business attained with sound fiscal discipline.

Professor John B. Taylor (2014Jan01, 2014Jan3) provides clear thought on the lack of relevance of Hansen’s contention of secular stagnation to current economic conditions. The application of secular stagnation argues that the economy of the US has attained full-employment equilibrium since around 2000 only with negative real rates of interest of minus 2 to minus 3 percent. At low levels of inflation, the so-called full-employment equilibrium of negative interest rates of minus 2 to minus 3 percent cannot be attained and the economy stagnates. Taylor (2014Jan01) analyzes multiple contradictions with current reality in this application of the theory of secular stagnation:

Secular stagnation would predict idle capacity, in particular in residential investment when fed fund rates were fixed at 1 percent from Jun 2003 to Jun 2004. Taylor (2014Jan01) finds unemployment at 4.4 percent with house prices jumping 7 percent from 2002 to 2003 and 14 percent from 2004 to 2005 before dropping from 2006 to 2007. GDP prices doubled from 1.7 percent to 3.4 percent when interest rates were low from 2003 to 2005.
Taylor (2014Jan01, 2014Jan3) finds another contradiction in the application of secular stagnation based on low interest rates because of savings glut and lack of investment opportunities. Taylor (2009) shows that there was no savings glut. The savings rate of the US in the past decade is significantly lower than in the 1980s.
Taylor (2014Jan01, 2014Jan3) finds another contradiction in the low ratio of investment to GDP currently and reduced investment and hiring by US business firms.
Taylor (2014Jan01, 2014Jan3) argues that the financial crisis and global recession were caused by weak implementation of existing regulation and departure from rules-based policies.
Taylor (2014Jan01, 2014Jan3) argues that the recovery from the global recession was constrained by a change in the regime of regulation and fiscal/monetary policies.

In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share s_i of a demographic group in an industry i and unemployment rate y_i of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):

Y = ∑_is_iy_i (1)

This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):

∆Y = ∑_i∆s_iy*_i+ ∑_i∆y_is*_i (2)

The first term in (2) captures changes in the demographic and industrial composition of the economy ∆s_i multiplied by the average rate of unemployment y*_i, or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆y_i, multiplied by the average share of the group s*_i,or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:

“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”

Table I-4b and Chart I-12-b provide the US labor force participation rate or percentage of the labor force in population. It is not likely that simple demographic trends caused the sharp decline during the global recession and failure to recover earlier levels. The civilian labor force participation rate dropped from the peak of 66.9 percent in Jul 2006 to 62.6 percent in Dec 2013, 62.5 percent in Dec 2014, 62.4 percent in Dec 2015 and 62.4 in Dec 2016. The civilian labor force participation rate reached 63.0 in Sep 2017. The civilian labor force participation rate was 63.7 percent on an annual basis in 1979 and 63.4 percent in Dec 1980 and Dec 1981, reaching even 62.9 percent in both Apr and May 1979. The civilian labor force participation rate jumped with the recovery to 64.8 percent on an annual basis in 1985 and 65.9 percent in Jul 1985. Structural factors cannot explain these sudden changes vividly shown visually in the final segment of Chart I-12b. Seniors would like to delay their retiring especially because of the adversities of financial repression on their savings. Labor force statistics are capturing the disillusion of potential workers with their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors. The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (https://cmpassocregulationblog.blogspot.com/2017/09/dollar-devaluation-world-inflation.html). “Secular stagnation” would be a process over many years and not from one year to another. This is merely another case of theory without reality with dubious policy proposals.

Table I-4b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2017

Year	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Dec	Annual
1979	63.0	63.2	62.9	62.9	64.5	64.9	64.5	63.8	63.8	63.7
1980	63.2	63.2	63.2	63.5	64.6	65.1	64.5	63.6	63.4	63.8
1981	63.2	63.5	63.6	63.9	64.6	65.0	64.6	63.5	63.4	63.9
1982	63.2	63.4	63.3	63.9	64.8	65.3	64.9	64.0	63.8	64.0
1983	63.2	63.3	63.2	63.4	65.1	65.4	65.1	64.3	63.8	64.0
1984	63.4	63.6	63.7	64.3	65.5	65.9	65.2	64.4	64.3	64.4
1985	64.0	64.4	64.3	64.6	65.5	65.9	65.4	64.9	64.6	64.8
1986	64.4	64.6	64.6	65.0	66.3	66.6	66.1	65.3	65.0	65.3
1987	64.8	65.0	64.9	65.6	66.3	66.8	66.5	65.5	65.5	65.6
1988	65.2	65.2	65.3	65.5	66.7	67.1	66.8	65.9	65.9	65.9
1989	65.6	65.7	65.9	66.2	67.4	67.7	67.2	66.3	66.3	66.5
1990	66.0	66.2	66.1	66.5	67.4	67.7	67.1	66.4	66.1	66.5
1991	65.7	65.9	66.0	66.0	67.2	67.3	66.6	66.1	65.8	66.2
1992	65.8	66.0	66.0	66.4	67.6	67.9	67.2	66.3	66.1	66.4
1993	65.8	65.8	65.6	66.3	67.3	67.5	67.0	66.1	66.2	66.3
1994	66.2	66.1	66.0	66.5	67.2	67.5	67.2	66.5	66.5	66.6
1995	66.2	66.4	66.4	66.4	67.2	67.7	67.1	66.5	66.2	66.6
1996	66.1	66.4	66.2	66.7	67.4	67.9	67.2	66.8	66.7	66.8
1997	66.5	66.9	66.7	67.0	67.8	68.1	67.6	67.0	67.0	67.1
1998	66.7	67.0	66.6	67.0	67.7	67.9	67.3	67.0	67.0	67.1
1999	66.8	66.9	66.7	67.0	67.7	67.9	67.3	66.8	67.0	67.1
2000	67.0	67.1	67.0	67.0	67.7	67.6	67.2	66.7	67.0	67.1
2001	66.8	67.0	66.7	66.6	67.2	67.4	66.8	66.6	66.6	66.8
2002	66.6	66.6	66.4	66.5	67.1	67.2	66.8	66.6	66.2	66.6
2003	66.2	66.2	66.2	66.2	67.0	66.8	66.3	65.9	65.8	66.2
2004	65.7	65.8	65.7	65.8	66.5	66.8	66.2	65.7	65.8	66.0
2005	65.6	65.6	65.8	66.0	66.5	66.8	66.5	66.1	65.9	66.0
2006	65.7	65.8	65.8	66.0	66.7	66.9	66.5	66.1	66.3	66.2
2007	65.8	65.9	65.7	65.8	66.6	66.8	66.1	66.0	65.9	66.0
2008	65.5	65.7	65.7	66.0	66.6	66.8	66.4	65.9	65.7	66.0
2009	65.5	65.4	65.4	65.5	66.2	66.2	65.6	65.0	64.4	65.4
2010	64.6	64.8	64.9	64.8	65.1	65.3	65.0	64.6	64.1	64.7
2011	63.9	64.0	63.9	64.1	64.5	64.6	64.3	64.2	63.8	64.1
2012	63.6	63.6	63.4	63.8	64.3	64.3	63.7	63.6	63.4	63.7
2013	63.2	63.1	63.1	63.5	64.0	64.0	63.4	63.2	62.6	63.2
2014	62.7	62.9	62.6	62.9	63.4	63.5	63.0	62.8	62.5	62.9
2015	62.5	62.5	62.6	63.0	63.1	63.2	62.7	62.3	62.4	62.7
2016	62.7	62.8	62.7	62.7	63.2	63.4	62.9	62.8	62.4	62.8
2017	62.7	62.9	62.8	62.8	63.3	63.5	63.0	63.0

Source: US Bureau of Labor Statistics

http://www.bls.gov/cps/

Chart I-12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2017

Source: Bureau of Labor Statistics

http://www.bls.gov/cps/

Broader perspective is in Chart I-12c of the US Bureau of Labor Statistics. The United States civilian noninstitutional population has increased along a consistent trend since 1948 that continued through earlier recessions and the global recession from IVQ2007 to IIQ2009 and the cyclical expansion after IIIQ2009.

Chart I-12c, US, Civilian Noninstitutional Population, Thousands, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

The labor force of the United States in Chart I-12d has increased along a trend similar to that of the civilian noninstitutional population in Chart I-12c. There is an evident stagnation of the civilian labor force in the final segment of Chart I-12d during the current economic cycle. This stagnation is explained by cyclical factors similar to those analyzed by Lazear and Spletzer (2012JHJul22) that motivated an increasing population to drop out of the labor force instead of structural factors. Large segments of the potential labor force are not observed, constituting unobserved unemployment and of more permanent nature because those afflicted have been seriously discouraged from working by the lack of opportunities.

Chart I-12d, US, Labor Force, Thousands, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

The rate of labor force participation in the US is in Chart I-12E from 1948 to 2017. There is sudden decline during the global recession after 2007 without recovery explained by cyclical factors (Lazear and Spletzer2012JHJul22) as may many potential workers stopped their searches disillusioned that there could be an opportunity for them in sharply contracted markets.

Chart I-12E, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Chart I-20 provides the level of full-time jobs from 2001 to 2017. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 255.562 million in Sep 2017 or by 23.604 million (http://www.bls.gov/data/). The number with full-time jobs in Sep 2017 is 127.235 million, which is higher by 4.016 million relative to the peak of 123.219 million in Jul 2007. The ratio of full-time jobs of 123.219 million in Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 135.703 million full-time jobs with population of 255.562 million in Sep 2017 (0.531 x 255.562) or 8.468 million fewer full-time jobs relative to actual 127.235 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 20 million. Mediocre GDP growth is the main culprit of the fractured US labor market.

There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

Inferior performance of the US economy and labor markets, during cyclical slow growth not secular stagnation, is the critical current issue of analysis and policy design.

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2017. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Chart I-20B provides number of full-time jobs in the US from 1968 to 2017. There were multiple recessions followed by expansions without contraction of full-time jobs and without recovery as during the period after 2008. The problem is specific of the current cycle and not secular.

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2017. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

Chart I-20C, US, Noninstitutional Civilian Population, Thousands, 1968-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Table EMP provides the comparison between the labor market in the current whole cycle from 2007 to 2016 and the whole cycle from 1979 to 1989. In the entire cycle from 2007 to 2016, the number employed increased 5.389 million, full-time employed increased 2.670 million, part-time for economic reasons increased 1.542 million and population increased 21.491 million. The number employed increased 3.7 percent, full-time employed increased 2.2 percent, part-time for economic reasons increased 35.0 percent and population increased 9.3 percent. There is sharp contrast with the contractions of the 1980s and with most economic history of the United States. In the whole cycle from 1979 to 1989, the number employed increased 18.518 million, full-time employed increased 14.715 million, part-time for economic reasons increased 1.317 million and population increased 21.530 million. In the entire cycle from 1979 to 1989, the number employed increased 18.7 percent, full-time employed increased 17.8 percent, part-time for economic reasons increased 36.8 percent and population increased 13.1 percent. The difference between the 1980s and the current cycle after 2007 is in the high rate of growth after the contraction that maintained trend growth around 3.0 percent for the entire cycle and per capital growth at 2.0 percent. The evident fact is that current weakness in labor markets originates in cyclical slow growth and not in imaginary secular stagnation.

Table EMP, US, Annual Level of Employed, Full-Time Employed, Employed Part-Time for Economic Reasons and Noninstitutional Civilian Population, Millions

	Employed	Full-Time Employed	Part Time Economic Reasons	Noninstitutional Civilian Population
2000s
2000	136.891	113.846	3.227	212.577
2001	136.933	113.573	3.715	215.092
2002	136.485	112.700	4.213	217.570
2003	137.736	113.324	4.701	221.168
2004	139.252	114.518	4.567	223.357
2005	141.730	117.016	4.350	226.082
2006	144.427	119.688	4.162	228.815
2007	146.047	121.091	4.401	231.867
2008	145.362	120.030	5.875	233.788
2009	139.877	112.634	8.913	235.801
2010	139.064	111.714	8.874	237.830
2011	139.869	112.556	8.560	239.618
2012	142.469	114.809	8.122	243.284
2013	143.929	116.314	7.935	245.679
2014	146.305	118.718	7.213	247.947
2015	148.834	121.492	6.371	250.801
2016	151.436	123.761	5.943	253.538
∆2007-2016	5.389	2.670	1.542	21.671
∆% 2007-2016	3.7	2.2	35.0	9.3
1980s
1979	98.824	82.654	3.577	164.863
1980	99.303	82.562	4.321	167.745
1981	100.397	83.243	4.768	170.130
1982	99.526	81.421	6.170	172.271
1983	100.834	82.322	6.266	174.215
1984	105.005	86.544	5.744	176.383
1985	107.150	88.534	5.590	178.206
1986	109.597	90.529	5.588	180.587
1987	112.440	92.957	5.401	182.753
1988	114.968	95.214	5.206	184.613
1989	117.342	97.369	4.894	186.393
∆1979-1989	18.518	14.715	1.317	21.530
∆% 1979-1989	18.7	17.8	36.8	13.1

Source: Bureau of Labor Statistics

http://www.bls.gov/

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. There are accentuated cyclic factors for both the entire population and the young population of ages 16 to 24 years. Table Summary Total provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment level (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would spread over long periods instead of immediately. All indicators of the labor market weakened sharply during the contraction and did not recover. Population continued to grow but all other variables collapsed and did not recover. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-16). Hansen (1938, 1939) finds secular stagnation in lower growth of an aging population. In the current US economy, Table Summary shows that population is dynamic while the labor market is fractured. There is key explanation in the behavior of the civilian labor force participation rate (CLFP) and the employment population ratio (EPOP) that collapsed during the global recession with inadequate recovery. Abandoning job searches are difficult to capture in labor statistics but likely explain the decline in the participation of the population in the labor force. Allowing for abandoning job searches, the total number of people unemployed or underemployed is 21.1 million or 12.5 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/10/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/twenty-two-million-unemployed-or.html).

Table Summary Total, US, Total Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Millions and Percent

	ICP	FTE	EMP	CLF	CLFP	EPOP	UNE
2006	228.8	119.7	144.4	151.4	66.2	63.1	7.0
2009	235.8	112.6	139.9	154.1	65.4	59.3	14.3
2012	243.3	114.8	142.5	155.0	63.7	58.6	12.5
2013	245.7	116.3	143.9	155.4	63.2	58.6	11.5
2014	247.9	118.7	146.3	155.9	62.9	59.0	9.6
2015	250.8	121.5	148.8	157.1	62.7	59.3	8.3
2016	253.5	123.8	151.4	159.2	62.8	59.7	7.8
12/07	233.2	121.0	146.3	153.7	65.9	62.8	7.4
9/09	236.3	112.0	139.1	153.6	65.0	58.9	14.5
9/17	255.6	127.2	154.5	161.0	63.0	60.5	6.6

ICP: Total Noninstitutional Civilian Population; FT: Full-time Employment Level, EMP: Total Employment Level; CLF: Civilian Labor Force; CLFP: Civilian Labor Force Participation Rate; EPOP: Employment Population Ratio; UNE: Unemployment

Source: Bureau of Labor Statistics

http://www.bls.gov/

The eminent economist and historian Professor Rondo E. Cameron (1989, 3) searches for the answer of “why are some nations rich and others poor?” by analyzing economic history since Paleolithic times. Cameron (1989, 4) argues that:

“Policymakers and their staffs of experts, faced with the responsibility of proposing and implementing policies for development, frequently shrug off the potential contributions of historical analysis to the solution of their problems with the observation that the contemporary situation is unique and therefore history is irrelevant to their concerns. Such an attitude contains a double fallacy. In the first place, those who are ignorant of the past are not qualified to generalize about it. Second, it implicitly denies the uniformity of nature, including human behavior and the behavior of social institutions—an assumption on which all scientific inquiry is founded. Such attitudes reveal how easy it is, without historical perspective, to mistake the symptoms of a problem for its causes.”

Scholars detached from practical issues of economic policy are more likely to discover sound knowledge (Cohen and Nagel 1934). There is troublesome sacrifice of rigorous scientific objectivity in cutting the economic past by a procrustean bed fitting favored current economic policies.

Nicholas Georgescu-Rogen (1960, 1) reprinted in Pelaez (1973) argues that “the agrarian economy has to this day remained a reality without theory.” The economic history of Latin America shares with the relation of deflation and unconventional monetary policy and secular stagnation when the event is cyclical slow growth a more frustrating intellectual misfortune: theory without reality. MacFarlane and Mortimer-Lee (1994, 159) quote in a different context a phrase by Thomas Henry Huxley in the President’s Address to the British Association for the Advancement of Science on Sep 14, 1870 that is appropriate to these issues: “The great tragedy of science—the slaying of a beautiful hypothesis by an ugly fact.” There may be current relevance in another quote from Thomas Henry Huxley: “The deepest sin against the human mind is to believe things without evidence.”

I United States Housing Collapse. Data and other information continue to provide depressed conditions in the US housing market in a longer perspective, with recent improvement at the margin. Table IIB-1 shows sales of new houses in the US at seasonally adjusted annual equivalent rate (SAAR). House sales fell in 30 of 81 months from Jan 2011 to Sep 2017 with monthly declines of 5 in 2011, 4 in 2012, 4 in 2013, 6 in 2014, 3 in 2015, 5 in 2016 and 3 in 2017. In Jan-Apr 2012, house sales increased at the annual equivalent rate of 11.8 percent and at 22.3 percent in May-Sep 2012. There was significant strength in Sep-Dec 2011 with annual equivalent rate of 48.4 percent. Sales of new houses fell 7.0 percent in Oct 2012 with increase of 9.5 percent in Nov 2012. Sales of new houses rebounded 10.8 percent in Jan 2013 with annual equivalent rate of 51.5 percent from Oct 2012 to Jan 2013 because of the increase of 10.8 percent in Jan 2013. New house sales increased at annual equivalent 9.9 percent in Feb-Mar 2013. New house sales weakened, decreasing at 2.3 percent in annual equivalent from Apr to Dec 2013 with significant volatility illustrated by decline of 18.8 percent in Jul 2013 and increase of 11.3 percent in Oct 2013. New house sales fell 1.1 percent in Dec 2013. New house sales increased 1.4 percent in Jan 2014 and fell 5.4 percent in Feb 2014, decreasing 3.1 percent in Mar 2014. New house sales decreased 2.2 percent in Apr 2014 and increased 12.7 percent in May 2014. New house sales fell 8.0 percent in Jun 2014 and decreased 3.4 percent in Jul 2014. New house sales jumped 11.7 percent in Aug 2014 and increased 3.8 percent in Sep 2014. New House sales increased 1.7 percent in Oct 2014 and fell 5.9 percent in Nov 2014. House sales fell at the annual equivalent rate of 2.6 percent in Sep-Nov 2014. New house sales increased 10.3 percent in Dec 2014 and increased 6.3 percent in Jan 2015. Sales of new houses increased 5.0 percent in Feb

2015 and fell 12.4 percent in Mar 2015. House sales increased 4.0 percent in Apr 2015. The annual equivalent rate in Dec 2014-Apr 2015 was 31.7 percent. New house sales increased 0.8 percent in May 2015 and fell 5.6 percent in Jun 2015, increasing 4.6 percent in Jul 2015. New house sales fell at annual equivalent 1.9 percent in May-Jul 2015. New house sales increased 3.0 percent in Aug 2015 and fell 10.1 percent in Sep 2015. New house sales decreased at annual equivalent 37.0 percent in Aug-Sep 2015. New house sales increased 4.6 percent in Oct 2015 and increased 5.4 percent in Nov 2015, increasing 5.5 percent in Dec 2015. New house sales increased at the annual equivalent rate of 83.0 percent in Oct-Dec 2015. New house sales decreased 3.0 percent in Jan 2016 at the annual equivalent rate of minus 30.6 percent. New house sales increased 1.0 percent in Feb 2016 and increased 1.5 percent in Mar 2016. New house sales jumped at 6.2 percent in Apr 2016. New house sales increased at the annual equivalent rate of 40.5 percent in Feb-Apr 2016. New house sales decreased 1.1 percent in May 2016 and decreased 0.2 percent in Jun 2016. New house sales jumped 12.2 percent in Aug 2016. New house sales increased at the annual equivalent rate of 50.4 percent in May-Jul 2016. New house sales fell 9.6 percent in Aug 2016 and increased 0.5 percent in Sep 2016, increasing 1.2 percent in Oct 2016. New house sales fell at the annual equivalent rate of minus 28.5 percent in Aug-Oct 2016. New house sales increased at 0.3 percent in Nov 2016 and fell at 5.4 percent in Dec 2016. New house sales fell at 27.0 percent annual equivalent in Nov-Dec 2016. New house sales increased at 9.3 percent in Jan 2017 and increased at 2.7 percent in Feb 2017. New house sales increased at 100.1 percent in Jan-Feb 2017. New house sales increased at 3.7 percent in Mar 2017 and fell at 7.5 percent in Apr 2017. New house sales decreased at annual equivalent 22.1 percent in Mar-Apr 2017. New house sales increased at 2.7 percent in May 2017 and increased at 2.1 percent in Jun 2017. New house sales increased at annual equivalent 32.9 percent in May-Jun 2017. New house sales decreased at 6.0 percent in Jul 2017 and decreased at 3.6 percent in Aug 2017, increasing at 18.9 percent in Sep 2017. New house sales increased at annual equivalent 34.8 percent in Jul-Sep 2017. There are wide monthly oscillations. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), analyze how builders have provided financial assistance to home buyers, including those short of cash and with weaker credit background, explaining the rise in new home sales and the highest gap between prices of new and existing houses. The 30-year conventional mortgage rate increased from 3.40 on Apr 25, 2013 to 4.58 percent on Aug 22, 2013 (http://www.federalreserve.gov/releases/h15/data.htm), which could also be a factor in recent weakness with improvement after the rate fell to 4.26 in Nov 2013. The conventional mortgage rate rose to 4.48 percent on Dec 26, 2013 and fell to 4.32 percent on Jan 30, 2014. The conventional mortgage rate increased to 4.37 percent on Feb 26, 2014 and 4.40 percent on Mar 27, 2014. The conventional mortgage rate fell to 4.14 percent on Apr 22, 2014, stabilizing at 4.14 on Jun 26, 2014. The conventional mortgage rate stood at 3.93 percent on Aug 20, 2015 and at 3.91 percent on Sep 17, 2015. The conventional mortgage rate was at 3.79 percent on Oct 22, 2015. The conventional mortgage rate was 3.97 percent on Nov 20, 2015. The conventional mortgage rate was 3.97 percent on Dec 18, 2015, and 3.92 percent on Jan 14, 2016. The conventional mortgage rate was 3.65 percent on Feb 19, 2016. The commercial mortgage rate was 3.73 percent on Mar 17, 2016 and 3.59 percent on Apr 21, 2016. The conventional mortgage rate was 3.58 on May 19, 2016. The conventional mortgage rate was 3.54 percent on Jun 19, 2016 and 3.45 percent on Jul 21, 2016. The conventional mortgage rate was 3.43 percent on Aug 18, 2016 and 3.48 percent on Sep 22, 2016. The conventional mortgage rate was 3.94 on Nov 17, 2016 and 4.30 percent on Dec 22. The conventional mortgage rate was 4.19 percent on Jan 26, 2017 and 4.15 percent on Feb 17, 2017. The conventional mortgage rate was 4.1 percent on Mar 16, 2017. The conventional mortgage rate was 3.97 percent on Apr 20, 2017. The conventional mortgage rate was 4.05 percent on May 18, 2017. The conventional mortgage rate was 3.90 percent on Jun 22, 2017. The conventional mortgage rate was 3.96 percent on Jul 20, 2017. The conventional mortgage rate was 3.90 percent on Aug 18, 2017. The conventional mortgage rate was 3.83 percent on Sep 21, 2017. The conventional mortgage rate was 3.88 percent on Oct 20, 2017. The conventional mortgage rate measured in a survey by Freddie Mac (http://www.freddiemac.com/pmms/ http://www.freddiemac.com/pmms/abtpmms.htm) is the “interest rate a lender would charge to lend mortgage money to a qualified borrower.”

Table IIB-1, US, Sales of New Houses at Seasonally-Adjusted (SA) Annual Equivalent Rate, Thousands and %

	SA Annual Rate Thousands	∆%
Sep 2017	667	18.9
Aug	561	-3.6
Jul	582	-6.0
AE ∆% Jul-Sep		34.8
Jun	619	2.1
May	606	2.7
AE ∆% May -Jun		32.9
Apr	590	-7.5
Mar	638	3.7
AE ∆% Mar-Apr		-22.1
Feb	615	2.7
Jan	599	9.3
AE ∆% Jan-Feb		100.1
Dec 2016	548	-5.4
Nov	579	0.3
AE ∆% Nov-Dec		-27.0
Oct	577	1.2
Sep	570	0.5
Aug	567	-9.6
AE ∆% Aug-Oct		-28.5
Jul	627	12.2
Jun	559	-0.2
May	560	-1.1
AE ∆% May-Jul		50.4
Apr	566	6.2
Mar	533	1.5
Feb	525	1.0
AE ∆% Feb-Apr		40.5
Jan	520	-3.0
AE ∆% Jan		-30.6
Dec 2015	536	5.5
Nov	508	5.4
Oct	482	4.6
AE ∆% Oct-Dec		83.0
Sep	461	-10.1
Aug	513	3.0
AE ∆% Aug-Sep		-37.0
Jul	498	4.6
Jun	476	-5.6
May	504	0.8
AE ∆% May-Jul		-1.9
Apr	500	4.0
Mar	481	-12.4
Feb	549	5.0
Jan	523	6.3
Dec 2014	492	10.3
AE ∆% Dec-Apr		31.7
Nov	446	-5.9
Oct	474	1.7
Sep	466	3.8
AE ∆% Sep-Nov		-2.6
Aug	449	11.7
Jul	402	-3.4
Jun	416	-8.0
May	452	12.7
Apr	401	-2.2
Mar	410	-3.1
Feb	423	-5.4
Jan	447	1.4
AE ∆% Jan-Aug		2.6
Dec 2013	441	-1.1
Nov	446	0.5
Oct	444	11.3
Sep	399	5.0
Aug	380	1.1
Jul	376	-18.8
Jun	463	7.7
May	430	-4.7
Apr	451	0.4
AE ∆% Apr-Dec		-2.3
Mar	449	2.3
Feb	439	-0.7
AE ∆% Feb-Mar		9.9
Jan	442	10.8
Dec 2012	399	1.8
Nov	392	9.5
Oct	358	-7.0
AE ∆% Oct-Jan		51.5
Sep	385	2.7
Aug	375	1.6
Jul	369	2.5
Jun	360	-2.7
May	370	4.5
AE ∆% May-Sep		22.3
Apr	354	0.0
Mar	354	-3.3
Feb	366	9.3
Jan	335	-1.8
AE ∆% Jan-Apr		11.8
Dec 2011	341	4.0
Nov	328	3.8
Oct	316	3.9
Sep	304	1.7
AE ∆% Sep-Dec		48.4
Aug	299	1.0
Jul	296	-1.7
Jun	301	-1.3
May	305	-1.6
AE ∆% May-Aug		-10.3
Apr	310	3.3
Mar	300	11.1
Feb	270	-12.1
Jan	307	-5.8
AE ∆% Jan-Apr		-14.2
Dec 2010	326	13.6

AE: Annual Equivalent

Source: US Census Bureau

http://www.census.gov/construction/nrs/

There is additional information of the report of new house sales in Table IIB-2. The stock of unsold houses fell from rates of 6 to 8 percent of sales in 2011 to 4 to 5 percent in 2013 and 5.0 percent in Sep 2017. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), find that inventories of houses have declined as investors acquire distressed houses of higher quality. Median and average house prices oscillate. In Sep 2017, median prices of new houses sold not seasonally adjusted (NSA) increased 5.2 percent after decreasing 6.1 percent in

Aug 2017. Average prices increased 5.7 percent in Sep 2017 and decreased 2.8 percent in Aug 2017. Between Dec 2010 and Sep 2017, median prices increased 32.5 percent, with increases of 6.0 percent in Feb 2016, 4.9 percent in Nov 2015, 2.2 percent in Sep 2015, 13.6 percent in Oct 2014, 4.0 percent in Aug 2014, 4.0 percent in May 2014 and 5.2 percent in Mar 2014. Average prices increased 32.1 percent between Dec 2010 and Sep 2017, with increases of 5.1 percent in Mar 2016, 4.0 percent in Sep 2015, 4.4 percent in Jul 2015 and 18.3 percent in Oct 2014. Between Dec 2010 and Dec 2012, median prices increased 7.1 percent and average prices increased 2.6 percent. Price increases concentrated in 2012 with increase of median prices of 18.2 percent from Dec 2011 to Dec 2012 and of average prices of 13.8 percent. Median prices increased 16.7 percent from Dec 2012 to Dec 2014, with increase of 13.6 percent in Oct 2014, while average prices increased 24.7 percent, with increase of 18.3 percent in Oct 2014. Median prices decreased 1.5 percent from Dec 2014 to Dec 2015 while average prices fell 5.5 percent. Median prices increased 10.1 percent from Dec 2015 to Dec 2016 while average prices increased 8.5 percent. Median prices increased 1.6 percent from Sep 2016 to Sep 2017 while average prices increased 5.2 percent. Robbie Whelan, writing on “New homes hit record as builders cap supply,” on May 24, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323475304578500973445311276.html?mod=WSJ_economy_LeftTopHighlights), finds that homebuilders are continuing to restrict the number of new homes for sale. Restriction of available new homes for sale increases prices paid by buyers.

Table IIB-2, US, New House Stocks and Median and Average New Homes Sales Price

	Unsold* Stocks in Equiv. Months of Sales SA %	Median New House Sales Price USD NSA	Month ∆%	Average New House Sales Price USD NSA	Month ∆%
Sep 2017	5.0	319,700	5.2	385,200	5.7
Aug	6.0	303,800	-6.1	364,300	-2.8
Jul	5.6	323,600	2.7	374,700	1.1
Jun	5.3	315,200	-2.6	370,600	-2.1
May	5.4	323,600	4.0	378,400	3.4
Apr	5.4	311,100	-3.3	365,800	-4.8
Mar	5.0	321,700	8.0	384,400	3.8
Feb	5.1	298,000	-5.5	370,500	3.6
Jan	5.2	315,200	-3.6	357,700	-6.5
Dec 2016	5.6	327,000	3.8	382,500	5.3
Nov	5.1	315,000	4.0	363,400	3.2
Oct	5.2	302,800	-3.8	352,200	-3.8
Sep	5.1	314,800	8.6	366,100	3.1
Aug	5.1	289,900	-2.5	355,100	0.6
Jul	4.5	297,400	-4.4	353,000	-1.3
Jun	5.2	311,200	5.4	357,800	2.3
May	5.2	295,200	-7.3	349,700	-5.3
Apr	5.1	318,300	5.0	369,300	2.9
Mar	5.5	303,200	-0.9	359,000	5.1
Feb	5.5	305,800	6.0	341,700	-5.4
Jan	5.5	288,400	-2.9	361,200	2.5
Dec 2015	5.2	297,100	-5.0	352,500	-5.5
Nov	5.4	312,600	4.9	373,200	1.2
Oct	5.6	298,000	-0.5	368,900	3.3
Sep	5.8	299,500	2.2	357,200	4.0
Aug	5.1	293,000	0.2	343,300	0.6
Jul	5.2	292,300	2.5	341,200	4.4
Jun	5.4	285,100	-0.8	326,900	-2.8
May	5.0	287,500	-2.4	336,200	-1.2
Apr	4.9	294,500	2.8	340,400	-2.5
Mar	5.1	286,600	0.0	349,300	0.9
Feb	4.5	286,600	-1.8	346,300	-0.6
Jan	4.7	292,000	-3.2	348,300	-6.7
Dec 2014	5.1	301,500	1.1	373,200	7.0
Nov	5.7	298,300	0.4	348,900	-7.6
Oct	5.3	297,000	13.6	377,500	18.3
Sep	5.3	261,500	-10.4	319,100	-10.4
Aug	5.5	291,700	4.0	356,200	3.2
Jul	6.1	280,400	-2.3	345,200	2.1
Jun	5.7	287,000	0.5	338,100	4.5
May	5.1	285,600	4.0	323,500	-0.5
Apr	5.7	274,500	-2.8	325,100	-1.9
Mar	5.6	282,300	5.2	331,500	1.7
Feb	5.3	268,400	-0.5	325,900	-3.4
Jan	5.1	269,800	-2.1	337,300	5.0
Dec 2013	5.1	275,500	-0.6	321,200	-4.3
Nov	5.0	277,100	4.8	335,600	0.0
Oct	4.9	264,300	-2.0	335,700	4.4
Sep	5.5	269,800	5.7	321,400	3.4
Aug	5.5	255,300	-2.6	310,800	-5.8
Jul	5.4	262,200	0.9	329,900	7.8
Jun	4.1	259,800	-1.5	306,100	-2.5
May	4.5	263,700	-5.6	314,000	-6.8
Apr	4.3	279,300	8.5	337,000	12.3
Mar	4.1	257,500	-2.9	300,200	-3.9
Feb	4.2	265,100	5.4	312,500	1.8
Jan	4.0	251,500	-2.6	306,900	2.6
Dec 2012	4.5	258,300	5.4	299,200	2.9
Nov	4.6	245,000	-0.9	290,700	1.9
Oct	4.9	247,200	-2.9	285,400	-4.1
Sep	4.5	254,600	0.6	297,700	-2.6
Aug	4.6	253,200	6.7	305,500	8.2
Jul	4.6	237,400	2.1	282,300	3.9
Jun	4.8	232,600	-2.8	271,800	-3.2
May	4.7	239,200	1.2	280,900	-2.4
Apr	4.9	236,400	-1.4	287,900	1.5
Mar	4.9	239,800	0.0	283,600	3.5
Feb	4.8	239,900	8.2	274,000	3.1
Jan	5.3	221,700	1.4	265,700	1.1
Dec 2011	5.3	218,600	2.0	262,900	5.2
Nov	5.7	214,300	-4.7	250,000	-3.2
Oct	6.0	224,800	3.6	258,300	1.1
Sep	6.3	217,000	-1.2	255,400	-1.5
Aug	6.5	219,600	-4.5	259,300	-4.1
Jul	6.7	229,900	-4.3	270,300	-1.0
Jun	6.6	240,200	8.2	273,100	4.0
May	6.6	222,000	-1.2	262,700	-2.3
Apr	6.7	224,700	1.9	268,900	3.1
Mar	7.2	220,500	0.2	260,800	-0.8
Feb	8.1	220,100	-8.3	262,800	-4.7
Jan	7.3	240,100	-0.5	275,700	-5.5
Dec 2010	7.0	241,200	9.8	291,700	3.5

*Percent of new houses for sale relative to houses sold

Source: US Census Bureau

http://www.census.gov/construction/nrs/

The depressed level of residential construction and new house sales in the US is evident in Table IIB-3 providing new house sales not seasonally adjusted in Jan-Sep of various years. New house sales increased 8.5 percent from Jan-Sep 2016 to Jan-Sep 2017. Sales of new houses are higher in Jan-Sep 2017 relative to Jan-Sep 2015 with increase of 21.9 percent. Sales of new houses are higher in Jan-Sep 2017 relative to Jan-Sep 2014 with increase of 41.2 percent. Sales of new houses in Jan-Sep 2017 are substantially lower than in many years between 1971 and 2017 except for the years from 2008 to 2017. There are only six other increases of 43.3 percent relative to Jan-Sep 2013, 66.5 percent relative to Jan-Sep 2012, 103.0 percent relative to Jan-Sep 2011, 84.8 percent relative to Jan-Sep 2010 and 62.5 percent relative to Jan-Sep 2009. New house sales in Jan-Sep 2017 are 15.3 percent higher than in Jan-Sep 2008. Sales of new houses in Jan-Sep 2017 are lower by 24.9 percent relative to Jan-Sep 2007, 43.4 percent relative to 2006, 52.9 percent relative to 2005 and 49.4 percent relative to 2004. The housing boom peaked in 2005 and 2006 when increases in fed funds rates to 5.25 percent in Jun 2006 from 1.0 percent in Jun 2004 affected subprime mortgages that were programmed for refinancing in two or three years on the expectation that price increases forever would raise home equity. Higher home equity would permit refinancing under feasible mortgages incorporating full payment of principal and interest (Gorton 2009EFM; see other references in http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Sales of new houses in Jan 2017 relative to the same period in 2003 fell 44.3 percent and 37.1 percent relative to the same period in 2002. Similar percentage declines are also for 2017 relative to years from 2000 to 2004. Sales of new houses in Jan-Sep 2017 fell 9.0 per cent relative to the same period in 1995. The population of the US was 179.3 million in 1960 and 281.4 million in 2000 (Hobbs and Stoops 2002, 16). Detailed historical census reports are available from the US Census Bureau at (http://www.census.gov/population/www/censusdata/hiscendata.html). The estimate of the US population is 418.8 million in 2015. The US population increased by 133.6 percent from 1960 to 2015. The final row of Table IIB-3 reveals catastrophic data: sales of new houses in Jan-Sep 2017 of 473 thousand units are lower by 7.4 percent relative to 511 thousand units of houses sold in Jan-Sep 1971, which is the ninth year when data become available in 1963. The civilian noninstitutional population increased from 122.416 million in 1963 to 253.538 million in 2016, or 107.1 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

Table IIB-3, US, Sales of New Houses Not Seasonally Adjusted, Thousands and %

Jan-Sep 2017	473
Jan-Sep 2016	436
Jan-Sep 2017/Jan-Sep 2016	8.5
Jan-Sep 2015	388
∆% Jan-Sep 2017/Jan-Sep 2015	21.9
Jan-Sep 2014	335
∆% Jan-Sep 2017/Jan-Sep 2014	41.2
Jan-Sep 2013	330
∆% Jan-Sep 2017/Jan-Sep 2013	43.3
Jan-Sep 2012	284
∆% Jan-Sep 2017/Jan-Sep 2012	66.5
Jan-Sep 2011	233
∆% Jan-Sep 2017/Jan-Sep 2011	103.0
Jan-Sep 2010	256
∆% Jan-Sep 2017/ Jan-Sep 2010	84.8
Jan-Sep 2009	291
∆% Jan-Sep 2017/ Jan-Sep 2009	62.5
Jan-Sep 2008	400
∆% Jan-Sep 2017/ Jan-Sep 2008	18.3
Jan-Sep 2007	630
∆% Jan-Sep 2017/ Jan-Sep 2007	-24.9
Jan-Sep 2006	836
∆% Jan-Sep 2017/Jan-Sep 2006	-43.4
Jan-Sep 2005	1005
∆% Jan-Sep 2017/Jan-Sep 2005	-52.9
Jan-Sep 2004	935
∆% Jan-Sep 2017/Jan-Sep 2004	-49.4
Jan-Sep 2003	849
∆% Jan-Sep 2017/ Jan-Sep 2003	-44.3
Jan-Sep 2002	752
∆% Jan-Sep 2017/ Jan-Sep 2002	-37.1
Jan-Sep 2001	710
∆% Jan-Sep 2017/ Jan-Sep 2001	-33.4
Jan-Sep 2000	678
∆% Jan-Sep 2017/ Jan-Sep 2000	-30.2
Jan-Sep 1995	520
∆% Jan-Sep 2017/ Jan-Sep 1995	-9.0
Jan-Sep 1971	511
∆% Jan-Sep 2017/ Jan-Sep 1971	-7.4

*Computed using unrounded data

Source: US Census Bureau

http://www.census.gov/construction/nrs/

The revised level of 306 thousand new houses sold in 2011 is the lowest since 560 thousand in 1963 in the 53 years of available data while the level of 368 thousand in 2012 is only higher than 323 thousand in 2010. The level of sales of new houses of 437 thousand in 2014 is the lowest from 1963 to 2009 with exception of 412 thousand in 1982 and 436 thousand in 1981. The population of the US increased 129.4 million from 179.3 million in 1960 to 308.7 million in 2010, or 72.2 percent. The estimate of the US population is 418.8 million in 2015. The US population increased 133.6 percent from 1960 to 2015. The civilian noninstitutional population increased from 122.416 million in 1963 to 253.538 million in 2016, or 107.1 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

The civilian noninstitutional population is the universe of the labor force. In fact, there is no year from 1963 to 2013 in Table IIA-4 with sales of new houses below 400 thousand except for the immediately preceding years of 2009, 2010, 2011 and 2012.

Table IIB-4, US, New Houses Sold, NSA Thousands

Period	Sold during Period
1963	560
1964	565
1965	575
1966	461
1967	487
1968	490
1969	448
1970	485
1971	656
1972	718
1973	634
1974	519
1975	549
1976	646
1977	819
1978	817
1979	709
1980	545
1981	436
1982	412
1983	623
1984	639
1985	688
1986	750
1987	671
1988	676
1989	650
1990	534
1991	509
1992	610
1993	666
1994	670
1995	667
1996	757
1997	804
1998	886
1999	880
2000	877
2001	908
2002	973
2003	1,086
2004	1,203
2005	1,283
2006	1,051
2007	776
2008	485
2009	375
2010	323
2011	306
2012	368
2013	429
2014	437
2015	501
2016	561

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-1 of the US Bureau of the Census shows the sharp decline of sales of new houses in the US. Sales rose temporarily until about mid 2010 but then declined to a lower plateau followed by increase, stability and new oscillating increase.

Chart IIB-1, US, New One-Family Houses Sold in the US, SAAR (Seasonally Adjusted Annual Rate)

Source: US Census Bureau

https://www.census.gov/construction/nrs/img/c25_curr.gif

Between 1991 and 2001, sales of new houses rose 78.4 percent at the average yearly rate of 6.0 percent, as shown in Table IB-5. Between 1995 and 2005 sales of new houses increased 92.4 percent at the yearly rate of 6.8 percent. There are similar rates in all years from 2000 to 2005. The boom in housing construction and sales began in the 1980s and 1990s. The collapse of real estate culminated several decades of housing subsidies and policies to lower mortgage rates and borrowing terms (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 42-8). Sales of new houses sold in 2016 fell 16.0 percent relative to the same period in 1995 and 56.4 percent relative to 2005.

Table IIB-5, US, Percentage Change and Average Yearly Rate of Growth of Sales of New One-Family Houses

	∆%	Average Yearly % Rate
1963-2016	0.0	NA
1991-2001	78.4	6.0
1995-2005	92.4	6.8
2000-2005	46.3	7.9
1995-2016	-16.0	NA
2000-2016	-36.1	NA
2005-2016	-56.4	NA

NA: Not Applicable

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-2 of the US Bureau of the Census provides the entire monthly sample of new houses sold in the US between Jan 1963 and Jul 2017 without seasonal adjustment. The series is almost stationary until the 1990s. There is sharp upward trend from the early 1990s to 2005-2006 after which new single-family houses sold collapse to levels below those in the beginning of the series.

Chart IIB-2, US, New Single-family Houses Sold, NSA, 1963-2017

Source: US Census Bureau

http://www.census.gov/construction/nrs/

The available historical annual data of median and average prices of new houses sold in the US between 1963 and 2016 is in Table IIB-6. On a yearly basis, median and average prices reached a peak in 2007 and then fell substantially. There is recovery in 2012-2016.

Table IIB-6, US, Median and Average Prices of New Houses Sold, Annual Data

Period	Median	Average
1963	$18,000	$19,300
1964	$18,900	$20,500
1965	$20,000	$21,500
1966	$21,400	$23,300
1967	$22,700	$24,600
1968	$24,700	$26,600
1969	$25,600	$27,900
1970	$23,400	$26,600
1971	$25,200	$28,300
1972	$27,600	$30,500
1973	$32,500	$35,500
1974	$35,900	$38,900
1975	$39,300	$42,600
1976	$44,200	$48,000
1977	$48,800	$54,200
1978	$55,700	$62,500
1979	$62,900	$71,800
1980	$64,600	$76,400
1981	$68,900	$83,000
1982	$69,300	$83,900
1983	$75,300	$89,800
1984	$79,900	$97,600
1985	$84,300	$100,800
1986	$92,000	$111,900
1987	$104,500	$127,200
1988	$112,500	$138,300
1989	$120,000	$148,800
1990	$122,900	$149,800
1991	$120,000	$147,200
1992	$121,500	$144,100
1993	$126,500	$147,700
1994	$130,000	$154,500
1995	$133,900	$158,700
1996	$140,000	$166,400
1997	$146,000	$176,200
1998	$152,500	$181,900
1999	$161,000	$195,600
2000	$169,000	$207,000
2001	$175,200	$213,200
2002	$187,600	$228,700
2003	$195,000	$246,300
2004	$221,000	$274,500
2005	$240,900	$297,000
2006	$246,500	$305,900
2007	$247,900	$313,600
2008	$232,100	$292,600
2009	$216,700	$270,900
2010	$221,800	$272,900
2011	$227,200	$267,900
2012	$245,200	$292,200
2013	$268,900	$324,500
2014	$288,500	$347,700
2015	$294,200	$352,700
2016	$307,800	$360,900

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Table IIB-7. Prices rose sharply between 2000 and 2005. In fact, prices in 2016 are higher than in 2000. Between 2006 and 2016, median prices of new houses sold increased 24.9 percent and average prices increased 18.0 percent. Between 2015 and 2016, median prices increased 4.6 percent and average prices increased 2.3 percent.

Table IIB-7, US, Percentage Change of New Houses Median and Average Prices, NSA, ∆%

	Median New Home Sales Prices ∆%	Average New Home Sales Prices ∆%
∆% 2000 to 2003	15.4	19.0
∆% 2000 to 2005	42.5	43.5
∆% 2000 to 2016	82.1	74.3
∆% 2005 to 2016	27.8	21.5
∆% 2000 to 2006	45.9	47.8
∆% 2006 to 2016	24.9	18.0
∆% 2009 to 2016	42.0	33.2
∆% 2010 to 2016	38.8	32.2
∆% 2011 to 2016	35.5	34.7
∆% 2012 to 2016	25.5	23.5
∆% 2013 to 2016	14.5	11.2
∆% 2014 to 2016	6.7	3.8
∆% 2015 to 2016	4.6	2.3

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-3 of the US Census Bureau provides the entire series of new single-family sales median prices from Jan 1963 to Jul 2017. There is long-term sharp upward trend with few declines until the current collapse. Median prices increased sharply during the Great Inflation of the 1960s and 1970s and paused during the savings and loans crisis of the late 1980s and the recession of 1991. Housing subsidies throughout the 1990s caused sharp upward trend of median new house prices that accelerated after the fed funds rate of 1 percent from 2003 to 2004. There was sharp reduction of prices after 2006 with recovery recently above earlier prices.

Chart IIB-3, US, Median Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1963-2017

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-4 of the US Census Bureau provides average prices of new houses sold from the mid-1970s to Jul 2017. There is similar behavior as with median prices of new houses sold in Chart IIB-3. The only stress occurred in price pauses during the savings and loans crisis of the late 1980s and the collapse after 2006 with recent recovery.

Chart IIB-4, US, Average Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1975-2017

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-5 of the Board of Governors of the Federal Reserve System provides the rate for the 30-year conventional mortgage, the yield of the 30-year Treasury bond and the rate of the overnight federal funds rate, monthly, from 1954 to 2016. All rates decline throughout the period from the Great Inflation of the 1970s through the following Great Moderation and until currently. In Apr 1971, the fed funds rate was 4.15 percent and the conventional mortgage rate 7.31 percent. In November 2012, the fed funds rate was 0.16 percent, the yield of the 30-year Treasury 2.80 percent and the conventional mortgage rate 3.35. The final segment shows an increase in the yield of the 30-year Treasury to 3.61 percent in July 2013 with the fed funds rate at 0.09 percent and the conventional mortgage at 4.37 percent. The final data point shows marginal decrease of the conventional mortgage rate to 3.60 percent in May 2016 with the yield of the 30-year Treasury bond at 2.63 percent and overnight rate on fed funds at 0.37 percent. The recent increase in interest rates if sustained could affect the US real estate market. Shayndi Raice and Nick Timiraos, writing on “Banks cut as mortgage boom ends,” on Jan 9, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303754404579310940019239208), analyze the drop in mortgage applications to a 13-year low, as measured by the Mortgage Bankers Association. Nick Timiraos, writing on “Demand for home loans plunges,” on Apr 24, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304788404579522051733228402?mg=reno64-wsj), analyzes data in Inside Mortgage Finance that mortgage lending of $235 billion in IQ2014 is 58 percent lower than a year earlier and 23 percent below IVQ2013. Mortgage lending collapsed to the lowest level in 14 years. In testimony before the Committee on the Budget of the US Senate on May 8, 2004, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm): “One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.”

Chart IIB-5, US, Thirty-year Conventional Mortgage, Thirty-year Treasury Bond and Overnight Federal Funds Rate, Monthly, 1954-2016

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

Chart IIB-5A of the Board of Governors of the Federal Reserve System provides the yield of the 30-year Treasury bond and the rate of the overnight federal funds rate, monthly, from 2001 to 2017. The Board of Governors of the Federal Reserve System discontinued the conventional mortgage rate in its data bank. The final data point is 1.16 percent for the fed funds rate in Aug 2017 and 2.80 percent for the thirty-year Treasury bond. The conventional mortgage rate stood at 3.88 percent in Aug 2017.

Chart IIB-5A, US, Thirty-year Treasury Bond and Overnight Federal Funds Rate, Monthly, 2001-2017

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

Table IIB-8, US, Fed Funds Rate, Thirty Year Treasury Bond and Conventional Mortgage Rate, Monthly, Percent per Year, Dec 2012 to Jul 2017

	Fed Funds Rate	Yield of Thirty Year Constant Maturity	Conventional Mortgage Rate
2012-12	0.16	2.88	3.35
2013-01	0.14	3.08	3.41
2013-02	0.15	3.17	3.53
2013-03	0.14	3.16	3.57
2013-04	0.15	2.93	3.45
2013-05	0.11	3.11	3.54
2013-06	0.09	3.40	4.07
2013-07	0.09	3.61	4.37
2013-08	0.08	3.76	4.46
2013-09	0.08	3.79	4.49
2013-10	0.09	3.68	4.19
2013-11	0.08	3.80	4.26
2013-12	0.09	3.89	4.46
2014-01	0.07	3.77	4.43
2014-02	0.07	3.66	4.30
2014-03	0.08	3.62	4.34
2014-04	0.09	3.52	4.34
2014-05	0.09	3.39	4.19
2014-06	0.10	3.42	4.16
2014-07	0.09	3.33	4.13
2014-08	0.09	3.2	4.12
2014-09	0.09	3.26	4.16
2014-10	0.09	3.04	4.04
2014-11	0.09	3.04	4.00
2014-12	0.12	2.83	3.86
2015-01	0.11	2.46	3.67
2015-02	0.11	2.57	3.71
2015-03	0.11	2.63	3.77
2015-04	0.12	2.59	3.67
2015-05	0.12	2.96	3.84
2015-06	0.13	3.11	3.98
2015-07	0.13	3.07	4.05
2015-08	0.14	2.86	3.91
2015-09	0.14	2.95	3.89
2015-10	0.12	2.89	3.80
2015-11	0.12	3.03	3.94
2015-12	0.24	2.97	3.96
2016-01	0.34	2.86	3.87
2016-02	0.38	2.62	3.66
2016-03	0.36	2.68	3.69
2016-04	0.37	2.62	3.61
2016-05	0.37	2.63	3.60
2016-06	0.38	2.45	3.57
2016-07	0.39	2.23	3.44
2016-08	0.40	2.26	3.44
2016-09	0.40	2.35	3.46
2016-10	0.40	2.50	3.47
2016-11	0.41	2.86	3.77
2016-12	0.54	3.11	4.20
2017-01	0.65	3.02	4.15
2017-02	0.66	3.03	4.17
2017-03	0.79	3.08	4.20
2017-04	0.90	2.94	4.05
2017-05	0.91	2.96	4.01
2017-06	1.04	2.80	3.90
2017-07	1.15	2.88	3.97
2017-08	1.16	2.80	3.88
2017-09	1.15	2.78	3.81

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

http://www.freddiemac.com/pmms/pmms30.htm

IIB2 United States House Prices. The Federal Housing Finance Agency (FHFA), which regulates Fannie Mae and Freddie Mac, provides the FHFA House Price Index (HPI) that “is calculated using home sales price information from Fannie Mae and Freddie Mac-acquired mortgages” (http://fhfa.gov/webfiles/24216/q22012hpi.pdf 1). The Federal Housing Finance Agency (FHFA), which regulates Fannie Mae and Freddie Mac, provides the FHFA House Price Index (HPI) that “is calculated using home sales price information from Fannie Mae and Freddie Mac-acquired mortgages” (http://fhfa.gov/webfiles/24216/q22012hpi.pdf 1). Table IIA2-1 provides the FHFA HPI for purchases only, which shows behavior similar to that of the Case-Shiller index but with lower magnitudes. House prices catapulted from 2000 to 2003, 2005 and 2006. From IVQ2000 to IVQ2006, the index for the US as a whole rose 55.0 percent, with 62.1 percent for New England, 72.0 percent for Middle Atlantic, 71.2 percent for South Atlantic but only by 33.1 percent for East South Central. Prices fell relative to 2014 for the US and all regions from 2006 with exception of increase of 2.6 percent for East South Central. Prices for the US increased 4.9 percent in IVQ2014 relative to IVQ2013 and 12.9 percent from IVQ2012 to IVQ2014. From IVQ2000 to IVQ2014, prices rose for the US and the four regions in Table IIA2-1.

Table IIA2-1, US, FHFA House Price Index Purchases Only NSA ∆%

	United States	New England	Middle Atlantic	South Atlantic	East South Central
IVQ2000 to IVQ2003	24.0	40.6	35.8	25.9	11.0
IVQ2000 to IVQ2005	50.5	65.0	67.6	62.9	25.4
IVQ2000 to IVQ2006	55.0	62.1	72.0	71.2	33.1
IVQ2005 to IVQ2014	-1.5	-8.7	-2.3	-7.4	8.9
IVQ2006 to IVQ2014	-4.4	-7.1	-4.8	-11.9	2.6
IVQ2007 to IVQ2014	-1.9	-5.1	-5.0	-8.6	0.7
IVQ2011 to IVQ2014	18.9	7.3	6.9	19.9	11.8
IVQ2012 to IVQ2014	12.9	6.8	5.7	13.8	8.6
IVQ2013 to IVQ2014	4.9	2.5	2.2	5.1	4.2
IVQ2000 to IVQ2014	48.3 144.27	50.6 138.40	63.7 127.30	50.9 140.28	36.6 146.07

Source: Federal Housing Finance Agency

http://www.fhfa.gov/KeyTopics/Pages/House-Price-Index.aspx

Data of the FHFA HPI for the remaining US regions are in Table IIA2-2. Behavior is not very different from that in Table IIA2-1 with the exception of East North Central. House prices in the Pacific region doubled between 2000 and 2006. Although prices of houses declined sharply from 2005 and 2006 to 2014 with exception of West South Central and West North Central, there was still appreciation relative to 2000.

Table IIA2-2, US, FHFA House Price Index Purchases Only NSA ∆%

	West South Central	West North Central	East North Central	Mountain	Pacific
IVQ2000 to IVQ2003	11.1	18.3	14.7	18.9	44.6
IVQ2000 to IVQ2005	23.9	31.0	23.8	58.0	107.7
IVQ2000 to IVQ2006	31.6	33.7	23.7	68.6	108.7
IVQ2005 to IVQ2014	26.6	4.7	-5.4	-2.6	-14.7
IVQ2006 to IVQ2014	19.1	2.6	-5.4	-8.7	-15.1
IVQ2007 to IVQ2014	15.2	3.2	-2.1	-5.6	-6.0
IVQ2011 to IVQ2014	18.1	13.5	14.2	32.9	37.6
IVQ2012 to IVQ2014	12.1	8.9	11.1	17.9	24.4
IVQ2013 to IVQ2014	5.9	4.0	4.6	5.5	7.3
IVQ2000 to IVQ2014	56.8 145.53	37.1 158.59	17.1 155.13	53.9 172.46	77.1 132.21

Source: Federal Housing Finance Agency

http://www.fhfa.gov/KeyTopics/Pages/House-Price-Index.aspx

Monthly and 12-month percentage changes of the FHFA House Price Index are in Table IIA2-3. Percentage monthly increases of the FHFA index were positive from Apr to Jul 2011 with exception of declines in May and Aug 2011 while 12-month percentage changes improved steadily from around minus 6.0 percent in Mar to May 2011 to minus 4.5 percent in Jun 2011. The FHFA house price index fell 0.6 percent in Oct 2011 and fell 3.2 percent in the 12 months ending in Oct 2011. There was significant recovery in Nov 2011 with increase in the house price index of 0.5 percent and reduction of the 12-month rate of decline to 2.3 percent. The house price index rose 0.4 percent in Dec 2011 and the 12-month percentage change improved to minus 1.3 percent. There was further improvement with revised change of minus 0.3 percent in Jan 2012 and decline of the 12-month percentage change to minus 1.3 percent. The index improved to positive change of 0.2 percent in Feb 2012 and change of 0.0 percent in the 12 months ending in Feb 2012. There was strong improvement in Mar 2012 with gain in prices of 0.9 percent and 2.0 percent in 12 months. The house price index of FHFA increased 0.6 percent in Apr 2012 and 2.4 percent in 12 months and improvement continued with increase of 0.6 percent in May 2012 and 3.3 percent in the 12 months ending in May 2012. Improvement consolidated with increase of 0.4 percent in Jun 2012 and 3.4 percent in 12 months. In Jul 2012, the house price index increased 0.2 percent and 3.3 percent in 12 months. Strong increase of 0.6 percent in Aug 2012 pulled the 12-month change to 4.1 percent. There was another increase of 0.6 percent in Oct 2012 and 5.1 percent in 12 months followed by increase of 0.5 percent in Nov 2012 and 5.1 percent in 12 months. The FHFA house price index increased 0.7 percent in Jan 2013 and 6.4 percent in 12 months. Improvement continued with increase of 0.5 percent in Apr 2013 and 7.1 percent in 12 months. In May 2013, the house price indexed increased 0.9 percent and 7.3 percent in 12 months. The FHFA house price index increased 0.6 percent in Jun 2013 and 7.5 percent in 12 months. In Jul 2013, the FHFA house price index increased 0.6 percent and 8.0 percent in 12 months. Improvement continued with increase of 0.3 percent in Aug 2013 and 7.7 percent in 12 months. In Sep 2013, the house price index increased 0.5 percent and 7.8 percent in 12 months. The house price index increased 0.4 percent in Oct 2013 and 7.5 percent in 12 months. In Nov 2013, the house price index increased 0.1 percent and increased 7.1 percent in 12 months. The house price index rose 0.5 percent in Dec 2013 and 7.1 percent in 12 months. Improvement continued with increase of 0.5 percent in Jan 2014 and 6.9 percent in 12 months. In Feb 2014, the house price index increased 0.4 percent and 6.7 percent in 12 months. The house price index increased 0.4 percent in Mar 2014 and 6.0 percent in 12 months. In Apr 2014, the house price index increased 0.2 percent and increased 5.7 percent in 12 months. The house price index increased 0.2 percent in May 2014 and 5.0 percent in 12 months. In Jun 2014, the house price index increased 0.5 percent and 4.8 percent in 12 months. The house price index increased 0.4 percent in Jul 2014 and 4.6 percent in 12 months. In Sep 2014, the house price index increased 0.2 percent and increased 4.4 percent in 12 months. The house price index increased 0.5 percent in Oct 2014 and 4.5 percent in 12 months. In Nov 2014, the house price index increased 0.4 percent and 4.8 percent in 12 months. The house price index increased 0.9 percent in Dec 2014 and increased 5.3 percent in 12 months. In Mar 2015, the house price index increased 0.4 percent and increased 5.3 percent in 12 months. The house price index increased 0.4 percent in Mar 2015 and 5.3 percent in 12 months. In Apr 2015, the house price index increased 0.4 percent and 5.4 percent in 12 months. The house price index increased 0.6 percent in May 2015 and 5.7 percent in 12 months. House prices increased 0.4 percent in Jun 2015 and 5.6 percent in 12 months. The house price index increased 0.4 percent in Jul 2015 and increased 5.6 percent in 12 months. House prices increased 0.2 percent in Aug 2015 and increased 5.4 percent in 12 months. In Sep 2015, the house price index increased 0.7 percent and increased 5.9 percent in 12 months. The house price index increased 0.5 percent in Oct 2015 and increased 5.9 percent in 12 months. House prices increased 0.6 percent in Nov 2015 and increased 6.1 percent in 12 months. The house price index increased 0.5 percent in Dec 2015 and increased 5.7 percent in 12 months. House prices increased 0.6 percent in Jan 2016 and increased 6.2 percent in 12 months. The house price index increased 0.3 percent in Feb 2016 and increased 5.8 percent in 12 months. House prices increased 0.7 percent in Mar 2016 and increased 6.2 percent in 12 months. The house price index increased 0.4 percent in Apr 2016 and increased 6.1 percent in 12 months. House prices increased 0.4 percent in May 2016 and increased 5.9 percent in 12 months. The house price index increased 0.5 percent in Jun 2016 and increased 5.9 percent in 12 months. House prices increased 0.5 percent in Jul 2016 and increased 6.0 percent in 12 months. The house price index increased 0.6 percent in Aug 2016 and increased 6.5 percent in 12 months. House prices increased 0.8 percent in Sep 2016 and increased 6.5 percent in 12 months. The house price index increased 0.4 percent in Oct 2016 and increased 6.4 percent in 12 months. House prices increased 0.7 percent in Nov 2016 and increased 6.5 percent in 12 months. The house price index increased 0.4 percent in Dec 2016 and increased 6.5 percent in 12 months. House prices increased 0.2 percent in Jan 2017 and increased 6.1 percent in 12 months. In Feb 2017, the house price index increased 0.9 percent and increased 6.7 percent in 12 months. House prices increased 0.8 percent in Mar 2017 and increased 6.8 percent in 12 months. In Apr 2017, the house price index increased 0.6 percent and increased 7.1 percent in 12 months. House prices increased 0.4 percent in May 2017 and increased 7.0 percent in 12 months. The house price index increased 0.1 percent in Jun 2017 and increased 6.6 percent in 12 months. House prices increased 0.4 percent in Jul 2017 and increased 6.5 percent in 12 months. The house price index increased 0.7 percent in Oct 2017 and increased 6.6 percent in 12 months.

Table IIA2-3, US, FHFA House Price Index Purchases Only SA. Month and NSA 12-Month ∆%

	Month ∆% SA	12 Month ∆% NSA
8/1/2017	0.7	6.6
7/1/2017	0.4	6.5
6/1/2017	0.1	6.6
5/1/2017	0.4	7.0
4/1/2017	0.6	7.1
3/1/2017	0.8	6.8
2/1/2017	0.9	6.7
1/1/2017	0.2	6.1
12/1/2016	0.4	6.5
11/1/2016	0.7	6.5
10/1/2016	0.4	6.4
9/1/2016	0.8	6.5
8/1/2016	0.6	6.5
7/1/2016	0.5	6.0
6/1/2016	0.5	5.9
5/1/2016	0.4	5.9
4/1/2016	0.4	6.1
3/1/2016	0.7	6.2
2/1/2016	0.3	5.8
1/1/2016	0.6	6.2
12/1/2015	0.5	5.7
11/1/2015	0.6	6.1
10/1/2015	0.5	5.9
9/1/2015	0.7	5.9
8/1/2015	0.2	5.4
7/1/2015	0.4	5.6
6/1/2015	0.4	5.6
5/1/2015	0.6	5.7
4/1/2015	0.4	5.4
3/1/2015	0.4	5.3
2/1/2015	0.7	5.2
1/1/2015	0.2	4.9
12/1/2014	0.9	5.3
11/1/2014	0.4	4.8
10/1/2014	0.5	4.5
9/1/2014	0.2	4.4
8/1/2014	0.5	4.7
7/1/2014	0.4	4.6
6/1/2014	0.5	4.8
5/1/2014	0.2	5.0
4/1/2014	0.2	5.7
3/1/2014	0.4	6.0
2/1/2014	0.4	6.7
1/1/2014	0.5	6.9
12/1/2013	0.5	7.1
11/1/2013	0.1	7.1
10/1/2013	0.4	7.5
9/1/2013	0.5	7.8
8/1/2013	0.3	7.7
7/1/2013	0.6	8.0
6/1/2013	0.6	7.5
5/1/2013	0.9	7.3
4/1/2013	0.5	7.1
3/1/2013	1.1	7.2
2/1/2013	0.6	6.8
1/1/2013	0.7	6.4
12/1/2012	0.5	5.3
11/1/2012	0.5	5.1
10/1/2012	0.6	5.1
9/1/2012	0.4	3.9
8/1/2012	0.6	4.1
7/1/2012	0.2	3.3
6/1/2012	0.4	3.4
5/1/2012	0.6	3.3
4/1/2012	0.6	2.4
3/1/2012	0.9	2.0
2/1/2012	0.2	0.0
1/1/2012	-0.3	-1.3
12/1/2011	0.4	-1.3
11/1/2011	0.5	-2.3
10/1/2011	-0.6	-3.2
9/1/2011	0.6	-2.4
8/1/2011	-0.3	-3.8
7/1/2011	0.3	-3.5
6/1/2011	0.4	-4.5
5/1/2011	-0.2	-5.9
4/1/2011	0.2	-5.7
3/1/2011	-0.9	-5.9
2/1/2011	-1.1	-5.1
1/1/2011	-0.4	-4.5
12/1/2010	-0.7	-3.9
12/1/2009	-1.0	-2.0
12/1/2008	-0.3	-10.4
12/1/2007	-0.5	-3.3
12/1/2006	0.1	2.4
12/1/2005	0.6	9.8
12/1/2004	0.8	10.2
12/1/2003	0.9	8.0
12/1/2002	0.7	7.8
12/1/2001	0.7	6.7
12/1/2000	0.6	7.1
12/1/1999	0.5	6.1
12/1/1998	0.5	5.9
12/1/1997	0.3	3.4
12/1/1996	0.3	2.8
12/1/1995	0.4	3.0
12/1/1994	0.0	2.5
12/1/1993	0.5	3.1
12/1/1992	-0.1	2.4

Source: Federal Housing Finance Agency

http://www.fhfa.gov/DataTools

The bottom part of Table IIA2-3 provides 12-month percentage changes of the FHFA house price index since 1992 when data become available for 1991. Table IIA2-4 provides percentage changes and average rates of percent change per year for various periods. Between 1992 and 2016, the FHFA house price index increased 130.7 percent at the yearly average rate of 3.5 percent. In the period 1992-2000, the FHFA house price index increased 39.3 percent at the average yearly rate of 4.2 percent. The average yearly rate of price increase accelerated to 7.5 percent in the period 2000-2003, 8.5 percent in 2000-2005 and 7.5 percent in 2000-2006. At the margin, the average rate jumped to 10.0 percent in 2003-2005 and 7.4 percent in 2003-2006. House prices measured by the FHFA house price index increased 7.6 percent at the average yearly rate of 0.7 percent between 2006 and 2016 and 10.3 percent between 2005 and 2016 at the average yearly rate of 0.9 percent.

Table IIA2-4, US, FHFA House Price Index, Percentage Change and Average Rate of Percentage Change per Year, Selected Dates 1992-2016

Dec	∆%	Average ∆% per Year
1992-2016	130.7	3.5
1992-2000	39.3	4.2
2000-2003	24.2	7.5
2000-2005	50.3	8.5
2003-2005	21.0	10.0
2005-2016	10.2	0.9
2000-2006	53.9	7.5
2003-2006	23.9	7.4
2006-2016	7.6	0.7

Source: Federal Housing Finance Agency

http://www.fhfa.gov/DataTools

The explanation of the sharp contraction of household wealth can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:

“On the maturity date T, the firm must either pay the promised payment of B to the debtholders or else the current equity will be valueless. Clearly, if at time T, V(T) > B, the firm should pay the bondholders because the value of equity will be V(T) – B > 0 whereas if they do not, the value of equity would be zero. If V(T) ≤ B, then the firm will not make the payment and default the firm to the bondholders because otherwise the equity holders would have to pay in additional money and the (formal) value of equity prior to such payments would be (V(T)- B) < 0.”

Pelaez and Pelaez (The Global Recession Risk (2007), 208-9) apply this analysis to the US housing market in 2005-2006 concluding:

“The house market [in 2006] is probably operating with low historical levels of individual equity. There is an application of structural models [Duffie and Singleton 2003] to the individual decisions on whether or not to continue paying a mortgage. The costs of sale would include realtor and legal fees. There could be a point where the expected net sale value of the real estate may be just lower than the value of the mortgage. At that point, there would be an incentive to default. The default vulnerability of securitization is unknown.”

There are multiple important determinants of the interest rate: “aggregate wealth, the distribution of wealth among investors, expected rate of return on physical investment, taxes, government policy and inflation” (Ingersoll 1987, 405). Aggregate wealth is a major driver of interest rates (Ibid, 406). Unconventional monetary policy, with zero fed funds rates and flattening of long-term yields by quantitative easing, causes uncontrollable effects on risk taking that can have profound undesirable effects on financial stability. Excessively aggressive and exotic monetary policy is the main culprit and not the inadequacy of financial management and risk controls.

The net worth of the economy depends on interest rates. In theory, “income is generally defined as the amount a consumer unit could consume (or believe that it could) while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is a flow that is obtained by applying a rate of return, r, to a stock of wealth, W, or Y = rW (Ibid). According to a subsequent restatement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption decisions is the long-run expected yield from wealth r*W. This yield was named permanent income: Y* = r*W” (Darby 1974, 229), where * denotes permanent. The simplified relation of income and wealth can be restated as:

W = Y/r (1)

Equation (1) shows that as r goes to zero, r →0, W grows without bound, W→∞.

Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment but the exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at close to zero interest rates, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).

The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4).

There are significant elements of the theory of bank financial fragility of Diamond and Dybvig (1983) and Diamond and Rajan (2000, 2001a, 2001b) that help to explain the financial fragility of banks during the credit/dollar crisis (see also Diamond 2007). The theory of Diamond and Dybvig (1983) as exposed by Diamond (2007) is that banks funding with demand deposits have a mismatch of liquidity (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 58-66). A run occurs when too many depositors attempt to withdraw cash at the same time. All that is needed is an expectation of failure of the bank. Three important functions of banks are providing evaluation, monitoring and liquidity transformation. Banks invest in human capital to evaluate projects of borrowers in deciding if they merit credit. The evaluation function reduces adverse selection or financing projects with low present value. Banks also provide important monitoring services of following the implementation of projects, avoiding moral hazard that funds be used for, say, real estate speculation instead of the original project of factory construction. The transformation function of banks involves both assets and liabilities of bank balance sheets. Banks convert an illiquid asset or loan for a project with cash flows in the distant future into a liquid liability in the form of demand deposits that can be withdrawn immediately.

In the theory of banking of Diamond and Rajan (2000, 2001a, 2001b), the bank creates liquidity by tying human assets to capital. The collection skills of the relationship banker convert an illiquid project of an entrepreneur into liquid demand deposits that are immediately available for withdrawal. The deposit/capital structure is fragile because of the threat of bank runs. In these days of online banking, the run on Washington Mutual was through withdrawals online. A bank run can be triggered by the decline of the value of bank assets below the value of demand deposits.

Pelaez and Pelaez (Regulation of Banks and Finance 2009b, 60, 64-5) find immediate application of the theories of banking of Diamond, Dybvig and Rajan to the credit/dollar crisis after 2007. It is a credit crisis because the main issue was the deterioration of the credit portfolios of securitized banks as a result of default of subprime mortgages. It is a dollar crisis because of the weakening dollar resulting from relatively low interest rate policies of the US. It caused systemic effects that converted into a global recession not only because of the huge weight of the US economy in the world economy but also because the credit crisis transferred to the UK and Europe. Management skills or human capital of banks are illustrated by the financial engineering of complex products. The increasing importance of human relative to inanimate capital (Rajan and Zingales 2000) is revolutionizing the theory of the firm (Zingales 2000) and corporate governance (Rajan and Zingales 2001). Finance is one of the most important examples of this transformation. Profits were derived from the charter in the original banking institution. Pricing and structuring financial instruments was revolutionized with option pricing formulas developed by Black and Scholes (1973) and Merton (1973, 1974, 1998) that permitted the development of complex products with fair pricing. The successful financial company must attract and retain finance professionals who have invested in human capital, which is a sunk cost to them and not of the institution where they work.

The complex financial products created for securitized banking with high investments in human capital are based on houses, which are as illiquid as the projects of entrepreneurs in the theory of banking. The liquidity fragility of the securitized bank is equivalent to that of the commercial bank in the theory of banking (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65). Banks created off-balance sheet structured investment vehicles (SIV) that issued commercial paper receiving AAA rating because of letters of liquidity guarantee by the banks. The commercial paper was converted into liquidity by its use as collateral in SRPs at the lowest rates and minimal haircuts because of the AAA rating of the guarantor bank. In the theory of banking, default can be triggered when the value of assets is perceived as lower than the value of the deposits. Commercial paper issued by SIVs, securitized mortgages and derivatives all obtained SRP liquidity on the basis of illiquid home mortgage loans at the bottom of the pyramid. The run on the securitized bank had a clear origin (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65):

“The increasing default of mortgages resulted in an increase in counterparty risk. Banks were hit by the liquidity demands of their counterparties. The liquidity shock extended to many segments of the financial markets—interbank loans, asset-backed commercial paper (ABCP), high-yield bonds and many others—when counterparties preferred lower returns of highly liquid safe havens, such as Treasury securities, than the risk of having to sell the collateral in SRPs at deep discounts or holding an illiquid asset. The price of an illiquid asset is near zero.”

Gorton and Metrick (2010H, 507) provide a revealing quote to the work in 1908 of Edwin R. A. Seligman, professor of political economy at Columbia University, founding member of the American Economic Association and one of its presidents and successful advocate of progressive income taxation. The intention of the quote is to bring forth the important argument that financial crises are explained in terms of “confidence” but as Professor Seligman states in reference to historical banking crises in the US, the important task is to explain what caused the lack of confidence. It is instructive to repeat the more extended quote of Seligman (1908, xi) on the explanations of banking crises:

“The current explanations may be divided into two categories. Of these the first includes what might be termed the superficial theories. Thus it is commonly stated that the outbreak of a crisis is due to lack of confidence,--as if the lack of confidence was not in itself the very thing which needs to be explained. Of still slighter value is the attempt to associate a crisis with some particular governmental policy, or with some action of a country’s executive. Such puerile interpretations have commonly been confined to countries like the United States, where the political passions of democracy have had the fullest way. Thus the crisis of 1893 was ascribed by the Republicans to the impending Democratic tariff of 1894; and the crisis of 1907 has by some been termed the ‘[Theodore] Roosevelt panic,” utterly oblivious of the fact that from the time of President Jackson, who was held responsible for the troubles of 1837, every successive crisis had had its presidential scapegoat, and has been followed by a political revulsion. Opposed to these popular, but wholly unfounded interpretations, is the second class of explanations, which seek to burrow beneath the surface and to discover the more occult and fundamental causes of the periodicity of crises.”

Scholars ignore superficial explanations in the effort to seek good and truth. The problem of economic analysis of the credit/dollar crisis is the lack of a structural model with which to attempt empirical determination of causes (Gorton and Metrick 2010SB). There would still be doubts even with a well-specified structural model because samples of economic events do not typically permit separating causes and effects. There is also confusion is separating the why of the crisis and how it started and propagated, all of which are extremely important.

In true heritage of the principles of Seligman (1908), Gorton (2009EFM) discovers a prime causal driver of the credit/dollar crisis. The objective of subprime and Alt-A mortgages was to facilitate loans to populations with modest means so that they could acquire a home. These borrowers would not receive credit because of (1) lack of funds for down payments; (2) low credit rating and information; (3) lack of information on income; and (4) errors or lack of other information. Subprime mortgage “engineering” was based on the belief that both lender and borrower could benefit from increases in house prices over the short run. The initial mortgage would be refinanced in two or three years depending on the increase of the price of the house. According to Gorton (2009EFM, 13, 16):

“The outstanding amounts of Subprime and Alt-A [mortgages] combined amounted to about one quarter of the $6 trillion mortgage market in 2004-2007Q1. Over the period 2000-2007, the outstanding amount of agency mortgages doubled, but subprime grew 800%! Issuance in 2005 and 2006 of Subprime and Alt-A mortgages was almost 30% of the mortgage market. Since 2000 the Subprime and Alt-A segments of the market grew at the expense of the Agency (i.e., the government sponsored entities of Fannie Mae and Freddie Mac) share, which fell from almost 80% (by outstanding or issuance) to about half by issuance and 67% by outstanding amount. The lender’s option to rollover the mortgage after an initial period is implicit in the subprime mortgage. The key design features of a subprime mortgage are: (1) it is short term, making refinancing important; (2) there is a step-up mortgage rate that applies at the end of the first period, creating a strong incentive to refinance; and (3) there is a prepayment penalty, creating an incentive not to refinance early.”

The prime objective of successive administrations in the US during the past 20 years and actually since the times of Roosevelt in the 1930s has been to provide “affordable” financing for the “American dream” of home ownership. The US housing finance system is mixed with public, public/private and purely private entities. The Federal Home Loan Bank (FHLB) system was established by Congress in 1932 that also created the Federal Housing Administration in 1934 with the objective of insuring homes against default. In 1938, the government created the Federal National Mortgage Association, or Fannie Mae, to foster a market for FHA-insured mortgages. Government-insured mortgages were transferred from Fannie Mae to the Government National Mortgage Association, or Ginnie Mae, to permit Fannie Mae to become a publicly-owned company. Securitization of mortgages began in 1970 with the government charter to the Federal Home Loan Mortgage Corporation, or Freddie Mac, with the objective of bundling mortgages created by thrift institutions that would be marketed as bonds with guarantees by Freddie Mac (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 42-8). In the third quarter of 2008, total mortgages in the US were $12,057 billion of which 43.5 percent, or $5423 billion, were retained or guaranteed by Fannie Mae and Freddie Mac (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 45). In 1990, Fannie Mae and Freddie Mac had a share of only 25.4 percent of total mortgages in the US. Mortgages in the US increased from $6922 billion in 2002 to $12,088 billion in 2007, or by 74.6 percent, while the retained or guaranteed portfolio of Fannie and Freddie rose from $3180 billion in 2002 to $4934 billion in 2007, or by 55.2 percent.

According to Pinto (2008) in testimony to Congress:

“There are approximately 25 million subprime and Alt-A loans outstanding, with an unpaid principal amount of over $4.5 trillion, about half of them held or guaranteed by Fannie and Freddie. Their high risk activities were allowed to operate at 75:1 leverage ratio. While they may deny it, there can be no doubt that Fannie and Freddie now own or guarantee $1.6 trillion in subprime, Alt-A and other default prone loans and securities. This comprises over 1/3 of their risk portfolios and amounts to 34% of all the subprime loans and 60% of all Alt-A loans outstanding. These 10.5 million unsustainable, nonprime loans are experiencing a default rate 8 times the level of the GSEs’ 20 million traditional quality loans. The GSEs will be responsible for a large percentage of an estimated 8.8 million foreclosures expected over the next 4 years, accounting for the failure of about 1 in 6 home mortgages. Fannie and Freddie have subprimed America.”

In perceptive analysis of growth and macroeconomics in the past six decades, Rajan (2012FA) argues that “the West can’t borrow and spend its way to recovery.” The Keynesian paradigm is not applicable in current conditions. Advanced economies in the West could be divided into those that reformed regulatory structures to encourage productivity and others that retained older structures. In the period from 1950 to 2000, Cobet and Wilson (2002) find that US productivity, measured as output/hour, grew at the average yearly rate of 2.9 percent while Japan grew at 6.3 percent and Germany at 4.7 percent (see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). In the period from 1995 to 2000, output/hour grew at the average yearly rate of 4.6 percent in the US but at lower rates of 3.9 percent in Japan and 2.6 percent in the US. Rajan (2012FA) argues that the differential in productivity growth was accomplished by deregulation in the US at the end of the 1970s and during the 1980s. In contrast, Europe did not engage in reform with the exception of Germany in the early 2000s that empowered the German economy with significant productivity advantage. At the same time, technology and globalization increased relative remunerations in highly-skilled, educated workers relative to those without skills for the new economy. It was then politically appealing to improve the fortunes of those left behind by the technological revolution by means of increasing cheap credit. As Rajan (2012FA) argues:

“In 1992, Congress passed the Federal Housing Enterprises Financial Safety and Soundness Act, partly to gain more control over Fannie Mae and Freddie Mac, the giant private mortgage agencies, and partly to promote affordable homeownership for low-income groups. Such policies helped money flow to lower-middle-class households and raised their spending—so much so that consumption inequality rose much less than income inequality in the years before the crisis. These policies were also politically popular. Unlike when it came to an expansion in government welfare transfers, few groups opposed expanding credit to the lower-middle class—not the politicians who wanted more growth and happy constituents, not the bankers and brokers who profited from the mortgage fees, not the borrowers who could now buy their dream houses with virtually no money down, and not the laissez-faire bank regulators who thought they could pick up the pieces if the housing market collapsed. The Federal Reserve abetted these shortsighted policies. In 2001, in response to the dot-com bust, the Fed cut short-term interest rates to the bone. Even though the overstretched corporations that were meant to be stimulated were not interested in investing, artificially low interest rates acted as a tremendous subsidy to the parts of the economy that relied on debt, such as housing and finance. This led to an expansion in housing construction (and related services, such as real estate brokerage and mortgage lending), which created jobs, especially for the unskilled. Progressive economists applauded this process, arguing that the housing boom would lift the economy out of the doldrums. But the Fed-supported bubble proved unsustainable. Many construction workers have lost their jobs and are now in deeper trouble than before, having also borrowed to buy unaffordable houses. Bankers obviously deserve a large share of the blame for the crisis. Some of the financial sector’s activities were clearly predatory, if not outright criminal. But the role that the politically induced expansion of credit played cannot be ignored; it is the main reason the usual checks and balances on financial risk taking broke down.”

In fact, Raghuram G. Rajan (2005) anticipated low liquidity in financial markets resulting from low interest rates before the financial crisis that caused distortions of risk/return decisions provoking the credit/dollar crisis and global recession from IVQ2007 to IIQ2009. Near zero interest rates of unconventional monetary policy induced excessive risks and low liquidity in financial decisions that were critical as a cause of the credit/dollar crisis after 2007. Rajan (2012FA) argues that it is not feasible to return to the employment and income levels before the credit/dollar crisis because of the bloated construction sector, financial system and government budgets.

Table IIA-1 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 94.1 percent in the 10-city composite of the Case-Shiller home price index, 78.8 percent in the 20-city composite and 64.7 percent in the US national home price index between Jul 2000 and Jul 2005. Prices rose around 100 percent from Jul 2000 to Jul 2006, increasing 107.5 percent for the 10-city composite, 91.6 percent for the 20-city composite and 74.6 percent in the US national index. House prices rose 39.6 percent between Jul 2003 and Jul 2005 for the 10-city composite, 34.7 percent for the 20-city composite and 29.3 percent for the US national propelled by low fed funds rates of 1.0 percent between Dec 2003 and Jun 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Julket Committee (FOMC) from Jun 2004 until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Jul 2003 and Jul 2006, the 10-city index gained 49.1 percent; the 20-city index increased 44.4 percent; and the US national 37.1 percent. House prices have fallen from Jul 2006 to Jul 2017 by 4.7 percent for the 10-city composite and 2.2 percent for the 20-city composite, increasing 5.1 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Jul 2017, house prices increased 5.2 percent in the 10-city composite, increasing 5.8 percent in the 20-city composite and 5.9 percent in the US national. Table IIA-1 also shows that house prices increased 97.7 percent between Jul 2000 and Jul 2017 for the 10-city composite, increasing 87.4 percent for the 20-city composite and 83.6 percent for the US national. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The 10-city composite fell 4.8 percent from the peak in Jun 2006 to Jul 2017 and the 20-city composite fell 2.2 percent from the peak in Jul 2006 to Jul 2017. The US national increased 5.2 percent in Jul 2017 from the peak of the 10-city composite in Jun 2006 and increased 5.1 percent from the peak of the 20-city composite in Jul 2016. The final part of Table II-2 provides average annual percentage rates of growth of the house price indexes of Standard & Poor’s Case-Shiller. The average annual growth rate between Dec 1987 and Dec 2016 for the 10-city composite was 3.8 percent and 3.5 percent for the US national. Data for the 20-city composite are available only beginning in Jan 2000. House prices accelerated in the 1990s with the average rate of the 10-city composite of 5.0 percent between Dec 1992 and Dec 2000 while the average rate for the period Dec 1987 to Dec 2000 was 3.8 percent. The average rate for the US national was 3.5 percent from Dec 1987 to Dec 2016 and 3.6 percent from Dec 1987 to Dec 2000. Although the global recession affecting the US between IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly above 30 percent, the average annual growth rate of the 10-city composite between Dec 2000 and Dec 2016 was 3.8 percent while the rate of the 20-city composite was 3.5 percent and 3.4 percent for the US national.

Table IIA-1, US, Percentage Changes of Standard & Poor’s Case-Shiller Home Price Indices, Not Seasonally Adjusted, ∆%

	10-City Composite	20-City Composite	US National
∆% Jul 2000 to Jul 2003	39.1	32.7	27.4
∆% Jul 2000 to Jul 2005	94.1	78.8	64.7
∆% Jul 2003 to Jul 2005	39.6	34.7	29.3
∆% Jul 2000 to Jul 2006	107.5	91.6	74.6
∆% Jul 2003 to Jul 2006	49.1	44.4	37.1
∆% Jul 2005 to Jul 2017	1.8	4.8	11.5
∆% Jul 2006 to Jul 2017	-4.7	-2.2	5.1
∆% Jul 2009 to Jul 2017	38.2	40.0	28.7
∆% Jul 2010 to Jul 2017	32.8	35.7	31.6
∆% Jul 2011 to Jul 2017	37.9	41.4	36.4
∆% Jul 2012 to Jul 2017	37.1	39.7	34.5
∆% Jul 2013 to Jul 2017	22.2	24.4	22.6
∆% Jul 2014 to Jul 2017	14.5	16.6	16.1
∆% Jul 2015 to Jul 2017	9.6	11.1	11.2
∆% Jul 2016 to Jul 2017	5.2	5.8	5.9
∆% Jul 2000 to Jul 2017	97.7	87.4	83.6
∆% Peak Jun 2006 Jul 2017	-4.8		5.2
∆% Peak Jul 2006 to Jul 2017		-2.2	5.1
Average ∆% Dec 1987-Dec 2016	3.8	NA	3.5
Average ∆% Dec 1987-Dec 2000	3.8	NA	3.6
Average ∆% Dec 1992-Dec 2000	5.0	NA	4.5
Average ∆% Dec 2000-Dec 2016	3.8	3.5	3.4

Source: http://us.spindices.com/index-family/real-estate/sp-corelogic-case-shiller

Price increases measured by the Case-Shiller house price indices show in data for Jul 2017 that “home prices continued their rise across the country over the last 12 months” (https://www.spice-indices.com/idpfiles/spice-assets/resources/public/documents/589149_cshomeprice-release-0926.pdf?force_download=true). Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the 10- and 20-city composites, as shown in Table IIA-2. In Jan 2013, the seasonally adjusted 10-city composite increased 0.8 percent and the 20-city increased 0.8 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city changed 0.0 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. Except for Mar through Apr 2012, house prices seasonally adjusted declined in most months for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table IIA-2. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. Without seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Aug 2011 but fell in every month from Sep 2011 to Feb 2012. The not seasonally adjusted index registers decline in Mar 2012 of 0.1 percent for the 10-city composite and is flat for the 20-city composite. Not seasonally adjusted house prices increased 1.4 percent in Apr 2012 and at high monthly percentage rates until Sep 2012. House prices not seasonally adjusted stalled from Oct 2012 to Jan 2013 and surged from Feb to Sep 2013, decelerating in Oct 2013-Feb 2014. House prices grew at fast rates in Mar 2014. The 10-city NSA index increased 0.8 percent in Jul 2017 and the 20-city increased 0.7 percent. The 10-city SA increased 0.4 percent in Jul 2017 and the 20-city composite SA increased 0.3 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

Table IIA-2, US, Monthly Percentage Change of S&P Case-Shiller Home Price Indices, Seasonally Adjusted and Not Seasonally Adjusted, ∆%

	10-City Composite SA	10-City Composite NSA	20-City Composite SA	20-City Composite NSA
July 2017	0.4	0.8	0.3	0.7
June 2017	0.0	0.6	0.1	0.7
May 2017	0.0	0.8	0.1	0.9
April 2017	-0.1	0.8	0.2	1.0
March 2017	0.6	0.9	0.6	1.0
February 2017	0.5	0.3	0.7	0.4
January 2017	0.8	0.3	0.9	0.2
December 2016	0.8	0.2	0.8	0.2
November 2016	0.8	0.2	0.8	0.2
October 2016	0.5	-0.1	0.9	0.0
September 2016	0.4	0.0	0.5	0.1
August 2016	0.3	0.3	0.0	0.3
July 2016	0.1	0.5	0.2	0.6
June 2016	0.1	0.8	0.1	0.8
May 2016	0.0	0.8	0.1	0.9
April 2016	0.2	1.0	0.3	1.1
March 2016	0.6	0.9	0.5	0.9
February 2016	0.5	0.2	0.6	0.2
January 2016	0.5	-0.1	0.6	0.0
December 2015	0.4	-0.1	0.5	0.0
November 2015	0.6	0.0	0.7	0.0
October 2015	0.6	-0.1	0.9	0.0
September 2015	0.5	0.1	0.5	0.1
August 2015	0.2	0.2	0.0	0.3
July 2015	0.1	0.6	0.2	0.7
June 2015	0.2	0.9	0.2	1.0
May 2015	0.2	1.0	0.2	1.1
April 2015	0.2	1.1	0.3	1.1
March 2015	0.4	0.8	0.5	0.9
February 2015	0.8	0.5	0.9	0.5
January 2015	0.5	-0.1	0.6	-0.1
December 2014	0.6	0.0	0.6	0.0
November 2014	0.4	-0.3	0.5	-0.2
October 2014	0.5	-0.1	0.8	-0.1
September 2014	0.3	-0.1	0.3	-0.1
August 2014	0.1	0.2	0.0	0.2
July 2014	0.0	0.6	0.0	0.6
June 2014	0.1	1.0	0.1	1.0
May 2014	0.1	1.1	0.1	1.1
April 2014	0.3	1.1	0.2	1.2
March 2014	0.5	0.8	0.6	0.9
February 2014	0.5	0.0	0.5	0.0
January 2014	0.6	-0.1	0.6	-0.1
December 2013	0.6	-0.1	0.6	-0.1
November 2013	0.8	0.0	0.7	-0.1
October 2013	0.9	0.2	1.1	0.2
September 2013	1.1	0.7	1.1	0.7
August 2013	1.2	1.3	1.1	1.3
July 2013	1.1	1.9	1.1	1.8
June 2013	1.2	2.2	1.1	2.2
May 2013	1.4	2.5	1.4	2.5
April 2013	1.9	2.6	1.7	2.6
March 2013	1.0	1.3	1.2	1.3
February 2013	0.9	0.3	0.9	0.2
January 2013	0.8	0.0	0.8	0.0
December 2012	0.9	0.2	0.9	0.2
November 2012	0.6	-0.3	0.7	-0.2
October 2012	0.6	-0.2	0.7	-0.1
September 2012	0.6	0.3	0.6	0.3
August 2012	0.6	0.8	0.6	0.9
July 2012	0.6	1.5	0.7	1.6
June 2012	1.0	2.1	1.1	2.3
May 2012	1.0	2.2	1.1	2.4
April 2012	0.8	1.4	0.6	1.4
March 2012	-0.3	-0.1	0.0	0.0
February 2012	-0.2	-0.9	-0.1	-0.8
January 2012	-0.3	-1.1	-0.2	-1.0
December 2011	-0.5	-1.2	-0.4	-1.1
November 2011	-0.6	-1.4	-0.5	-1.3
October 2011	-0.5	-1.3	-0.5	-1.4
September 2011	-0.3	-0.6	-0.4	-0.7
August 2011	-0.2	0.1	-0.2	0.1
July 2011	0.0	0.9	0.0	1.0
June 2011	-0.1	1.0	-0.1	1.2
May 2011	-0.2	1.0	-0.2	1.0
April 2011	0.1	0.6	-0.1	0.6
March 2011	-0.9	-1.0	-0.8	-1.0
February 2011	-0.4	-1.3	-0.4	-1.2
January 2011	-0.3	-1.1	-0.3	-1.1
December 2010	-0.2	-0.9	-0.2	-1.0

Source: http://us.spindices.com/index-family/real-estate/sp-corelogic-case-shiller

Table IIA-4A summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2008 and 2009. Total assets fell $10.4 trillion or 12.8 percent from 2007 to 2008 and $8.8 trillion or 10.8 percent to 2009. Net worth fell $10.3 trillion from 2007 to 2008 or 15.5 percent and $8.5 trillion to 2009 or 12.7 percent. Subsidies to housing prolonged over decades together with interest rates at 1.0 percent from Jun 2003 to Jun 2004 inflated valuations of real estate and risk financial assets such as equities. The increase of fed funds rates by 25 basis points until 5.25 percent in Jun 2006 reversed carry trades through exotic vehicles such as subprime adjustable rate mortgages (ARM) and world financial markets. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9).

Table IIA-4, Difference of Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars from 2007 to 2008 and 2009

	2007	2008	Change to 2008	2009	Change to 2009
A	81,175.4	70,757.5	-10,417.9	72,398.4	-8,777.0
Non FIN	28,089.7	24,408.8	-3,680.9	23,502.5	-4,587.2
RE	23,280.2	19,474.6	-3,805.6	18,546.1	-4,734.1
FIN	53,085.7	46,348.7	-6,737.0	48,895.9	-4,189.8
LIAB	14,437.2	14,339.1	-98.1	14,138.8	-298.4
NW	66,738.2	56,418.3	-10,319.9	58,259.6	-8,478.6

A: Assets; Non FIN: Nonfinancial Assets; RE: Real Estate; FIN: Financial Assets; LIAB: Liabilities; NW: Net Worth

Source: Board of Governors of the Federal Reserve System. 2017. Flow of funds, balance sheets and integrated macroeconomic accounts: second quarter 2017. Washington, DC, Federal Reserve System, Sep 21. https://www.federalreserve.gov/releases/z1/current/default.htm

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