CMP Associates Regulation Blog: Exit Risks of Zero Interest Rates, World Trade Restricting Economic Growth, United States Commercial Banks Assets and Liabilities, United States Housing, World Economic Slowdown and Global Recession Risk: Part I

Exit Risks of Zero Interest Rates, World Trade Restricting Economic Growth, United States Commercial Banks Assets and Liabilities, United States Housing, World Economic Slowdown and Global Recession Risk

Carlos M. Pelaez

Executive Summary

I United States Commercial Banks Assets and Liabilities

IA Transmission of Monetary Policy

IB Functions of Banks

IC United States Commercial Banks Assets and Liabilities

ID Theory and Reality of Economic History and Monetary Policy Based on Fear of Deflation

II United States Housing

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

Executive Summary

Contents of Executive Summary

ESI Increasing Interest Rate Risk, Tapering Quantitative Easing, Duration Dumping, Steepening Yield Curve and Global Financial and Economic Risk

ESII World Trade Restricting Economic Growth

ESIII United States Commercial Banks Assets and Liabilities

ESIV United States Housing

ESI Increasing Interest Rate Risk, Tapering Quantitative Easing, Duration Dumping, Steepening Yield Curve and Global Financial and Economic Risk. The International Monetary Fund (IMF) provides an international safety net for prevention and resolution of international financial crises. The IMF’s Financial Sector Assessment Program (FSAP) provides analysis of the economic and financial sectors of countries (see Pelaez and Pelaez, International Financial Architecture (2005), 101-62, Globalization and the State, Vol. II (2008), 114-23). Relating economic and financial sectors is a challenging task for both theory and measurement. The International Monetary Fund (IMF) provides an international safety net for prevention and resolution of international financial crises. The IMF’s Financial Sector Assessment Program (FSAP) provides analysis of the economic and financial sectors of countries (see Pelaez and Pelaez, International Financial Architecture (2005), 101-62, Globalization and the State, Vol. II (2008), 114-23). Relating economic and financial sectors is a challenging task for both theory and measurement. The IMF (2013WEOOct) provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/pubs/ft/weo/2013/02/), of the world financial system with its Global Financial Stability Report (GFSR) (IMF 2013GFSROct) (http://www.imf.org/External/Pubs/FT/GFSR/2013/02/index.htm) and of fiscal affairs with the Fiscal Monitor (IMF 2013FMOct) (http://www.imf.org/external/pubs/ft/fm/2013/02/fmindex.htm). There appears to be a moment of transition in global economic and financial variables that may prove of difficult analysis and measurement. It is useful to consider a summary of global economic and financial risks, which are analyzed in detail in the comments of this blog in Section VI Valuation of Risk Financial Assets, Table VI-4.

Economic risks include the following:

China’s Economic Growth. China is lowering its growth target to 7.5 percent per year. China’s GDP growth decelerated significantly from annual equivalent 10.8 percent in IIQ2011 to 7.4 percent in IVQ2011 and 5.7 percent in IQ2012, rebounding to 9.1 percent in IIQ2012, 8.2 percent in IIIQ2012 and 7.8 percent in IVQ2012. Annual equivalent growth in IQ2013 fell to 6.1 percent and to 7.8 percent in IIQ2013, rebounding to 9.1 percent in IIIQ2013 (http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/07/tapering-quantitative-easing-policy-and_7005.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/01/recovery-without-hiring-world-inflation.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html).
United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 28.9 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically low hiring and declining/stagnating real wages.
Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
World Inflation Waves. Inflation continues in repetitive waves globally (http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-zero-interest-rates-world.html and earlier http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-world-inflation.htm).

A list of financial uncertainties includes:

Euro Area Survival Risk. The resilience of the euro to fiscal and financial doubts on larger member countries is still an unknown risk.
Foreign Exchange Wars. Exchange rate struggles continue as zero interest rates in advanced economies induce devaluation of their currencies.
Valuation of Risk Financial Assets. Valuations of risk financial assets have reached extremely high levels in markets with lower volumes.
Duration Trap of the Zero Bound. The yield of the US 10-year Treasury rose from 2.031 percent on Mar 9, 2012, to 2.294 percent on Mar 16, 2012. Considering a 10-year Treasury with coupon of 2.625 percent and maturity in exactly 10 years, the price would fall from 105.3512 corresponding to yield of 2.031 percent to 102.9428 corresponding to yield of 2.294 percent, for loss in a week of 2.3 percent but far more in a position with leverage of 10:1. Min Zeng, writing on “Treasurys fall, ending brutal quarter,” published on Mar 30, 2012, in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702303816504577313400029412564.html?mod=WSJ_hps_sections_markets), informs that Treasury bonds maturing in more than 20 years lost 5.52 percent in the first quarter of 2012.
Credibility and Commitment of Central Bank Policy. There is a credibility issue of the commitment of monetary policy (Sargent and Silber 2012Mar20).
Carry Trades. Commodity prices driven by zero interest rates have resumed their increasing path with fluctuations caused by intermittent risk aversion

Chart VIII-1 of the Board of Governors of the Federal Reserve System provides the rate on the overnight fed funds rate and the yields of the 10-year constant maturity Treasury and the Baa seasoned corporate bond. Table VIII-3 provides the data for selected points in Chart VIII-1. There are two important economic and financial events, illustrating the ease of inducing carry trade with extremely low interest rates and the resulting financial crash and recession of abandoning extremely low interest rates.

The Federal Open Market Committee (FOMC) lowered the target of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85). Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. 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. 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 interest rates close to zero, 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 with the objective of purchasing 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). The FOMC implemented increments of 25 basis points of the fed funds target from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006, as shown in Chart VIII-1. The gradual exit from the first round of unconventional monetary policy from 1.00 percent in Jun 2004 to 5.25 percent in Jun 2006 caused the financial crisis and global recession.
On Dec 16, 2008, the policy determining committee of the Fed decided (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm): “The Federal Open Market Committee decided today to establish a target range for the federal funds rate of 0 to 1/4 percent.” Policymakers emphasize frequently that there are tools to exit unconventional monetary policy at the right time. 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 that: “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.” Perception of withdrawal of $2488 billion, or $2.5 trillion bank reserves (http://www.federalreserve.gov/releases/h41/current/h41.htm#h41tab1), would cause Himalayan increase in interest rates that would provoke another recession. There is no painless gradual or sudden exit from zero interest rates because reversal of exposures created on the commitment of zero interest rates forever.

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 differfrom 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

Chart VIII-1, Fed Funds Rate and Yields of Ten-year Treasury Constant Maturity and Baa Seasoned Corporate Bond, Jan 2, 2001 to Nov 21, 2013

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/h15/

Table VIII-3, Selected Data Points in Chart VIII-1, % per Year

	Fed Funds Overnight Rate	10-Year Treasury Constant Maturity	Seasoned Baa Corporate Bond
1/2/2001	6.67	4.92	7.91
10/1/2002	1.85	3.72	7.46
7/3/2003	0.96	3.67	6.39
6/22/2004	1.00	4.72	6.77
6/28/2006	5.06	5.25	6.94
9/17/2008	2.80	3.41	7.25
10/26/2008	0.09	2.16	8.00
10/31/2008	0.22	4.01	9.54
4/6/2009	0.14	2.95	8.63
4/5/2010	0.20	4.01	6.44
2/4/2011	0.17	3.68	6.25
7/25/2012	0.15	1.43	4.73
5/1/13	0.14	1.66	4.48
9/5/13	0.08	2.98	5.53
11/21/2013	0.09	2.79	5.44
11/27/13	0.09	2.74	5.34 (11/26/13)

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/h15/

Professionals use a variety of techniques in measuring interest rate risk (Fabozzi, Buestow and Johnson, 2006, Chapter Nine, 183-226):

Full valuation approach in which securities and portfolios are shocked by 50, 100, 200 and 300 basis points to measure their impact on asset values
Stress tests requiring more complex analysis and translation of possible events with high impact even if with low probability of occurrence into effects on actual positions and capital
Value at Risk (VaR) analysis of maximum losses that are likely in a time horizon
Duration and convexity that are short-hand convenient measurement of changes in prices resulting from changes in yield captured by duration and convexity
Yield volatility

Analysis of these methods is in Pelaez and Pelaez (International Financial Architecture (2005), 101-162) and Pelaez and Pelaez, Globalization and the States, Vol. (I) (2008a), 78-100). Frederick R. Macaulay (1938) introduced the concept of duration in contrast with maturity for analyzing bonds. Duration is the sensitivity of bond prices to changes in yields. In economic jargon, duration is the yield elasticity of bond price to changes in yield, or the percentage change in price after a percentage change in yield, typically expressed as the change in price resulting from change of 100 basis points in yield. The mathematical formula is the negative of the yield elasticity of the bond price or –[dB/d(1+y)]((1+y)/B), where d is the derivative operator of calculus, B the bond price, y the yield and the elasticity does not have dimension (Hallerbach 2001). The duration trap of unconventional monetary policy is that duration is higher the lower the coupon and higher the lower the yield, other things being constant. Coupons and yields are historically low because of unconventional monetary policy. Duration dumping during a rate increase may trigger the same crossfire selling of high duration positions that magnified the credit crisis. Traders reduced positions because capital losses in one segment, such as mortgage-backed securities, triggered haircuts and margin increases that reduced capital available for positioning in all segments, causing fire sales in multiple segments (Brunnermeier and Pedersen 2009; see Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 217-24). Financial markets are currently experiencing fear of duration resulting from the debate within and outside the Fed on tapering quantitative easing. Table VIII-2 provides the yield curve of Treasury securities on Nov 29, 2013, Sep 5, 2013, May 1, 2013, Nov 29, 2012 and Nov 29, 2006. There is ongoing steepening of the yield curve for longer maturities, which are also the ones with highest duration. The 10-year yield increased from 1.45 percent on Jul 26, 2012 to 2.98 percent on Sep 5, 2013, as measured by the United States Treasury. Assume that a bond with maturity in 10 years were issued on Sep 5, 2013 at par or price of 100 with coupon of 1.45 percent. The price of that bond would be 86.8530 with instantaneous increase of the yield to 2.98 percent for loss of 13.1 percent and far more with leverage. Assume that the yield of a bond with exactly ten years to maturity and coupon of 2.75 percent as occurred on Nov 29, 2013 would jump instantaneously from yield of 2.75 percent on Nov 29, 2013 to 4.52 percent as occurred on Nov 29, 2006 when the economy was closer to full employment. The price of the hypothetical bond issued with coupon of 2.75 percent would drop from 100 to 85.8856 after an instantaneous increase of the yield to 4.52 percent. The price loss would be 14.1 percent. Losses absorb capital available for positioning, triggering crossfire sales in multiple asset classes (Brunnermeier and Pedersen 2009). What is the path of adjustment of zero interest rates on fed funds and artificially low bond yields? There is no painless exit from unconventional monetary policy. Chris Dieterich, writing on “Bond investors turn to cash,” on Jul 25, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323971204578625900935618178.html), uses data of the Investment Company Institute (http://www.ici.org/) in showing withdrawals of $43 billion in taxable mutual funds in Jun, which is the largest in history, with flows into cash investments such as $8.5 billion in the week of Jul 17 into money-market funds.

Table VIII-2, United States, Treasury Yields

	11/29/13	9/05/13	5/01/13	11/29/12	11/29/06
1 M	0.05	0.03	0.03	0.16	5.26
3 M	0.06	0.02	0.06	0.09	5.04
6 M	0.11	0.06	0.08	0.15	5.13
1 Y	0.13	0.16	0.11	0.18	4.98
2 Y	0.28	0.52	0.20	0.25	4.69
3 Y	0.56	0.97	0.30	0.35	4.58
5 Y	1.37	1.85	0.65	0.63	4.51
7 Y	2.10	2.45	1.07	1.04	4.51
10 Y	2.75	2.98	1.66	1.62	4.52
20 Y	3.54	3.64	2.44	2.37	4.72
30 Y	3.82	3.88	2.83	2.79	4.61

Source: United States Treasury

http://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yield

Interest rate risk is increasing in the US. Chart VI-13 of the Board of Governors provides the conventional mortgage rate for a fixed-rate 30-year mortgage. The rate stood at 5.87 percent on Jan 8, 2004, increasing to 6.79 percent on Jul 6, 2006. The rate bottomed at 3.35 percent on May 2, 2013. Fear of duration risk in longer maturities such as mortgage-backed securities caused continuing increases in the conventional mortgage rate that rose to 4.51 percent on Jul 11, 2013, 4.58 percent on Aug 22, 2013 and 4.22 percent on Nov 21, 2013, which is the last data point in Chart VI-13.

Chart VI-13, US, Conventional Mortgage Rate, Jan 8, 2004 to Nov 21, 2013

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/h15/update/

The major reason and channel of transmission of unconventional monetary policy is through expectations of inflation. Fisher (1930) provided theoretical and historical relation of interest rates and inflation. Let i_n be the nominal interest rate, i_r the real or inflation-adjusted interest rate and π^e the expectation of inflation in the time term of the interest rate, which are all expressed as proportions. The following expression provides the relation of real and nominal interest rates and the expectation of inflation:

(1 + i_r) = (1 + i_n)/(1 + π^e) (1)

That is, the real interest rate equals the nominal interest rate discounted by the expectation of inflation in time term of the interest rate. Fisher (1933) analyzed the devastating effect of deflation on debts. Nominal debt contracts remained at original principal interest but net worth and income of debtors contracted during deflation. Real interest rates increase during declining inflation. For example, if the interest rate is 3 percent and prices decline 0.2 percent, equation (1) calculates the real interest rate as:

(1 +0.03)/(1 – 0.02) = 1.03/(0.998) = 1.032

That is, the real rate of interest is (1.032 – 1) 100 or 3.2 percent. If inflation were 2 percent, the real rate of interest would be 0.98 percent, or about 1.0 percent {[(1.03/1.02) -1]100 = 0.98%}.

The yield of the one-year Treasury security was quoted in the Wall Street Journal at 0.114 percent on Fri May 17, 2013 (http://online.wsj.com/mdc/page/marketsdata.html?mod=WSJ_topnav_marketdata_main). The expected rate of inflation π^e in the next twelve months is not observed. Assume that it would be equal to the rate of inflation in the past twelve months estimated by the Bureau of Economic Analysis (BLS) at 1.1 percent (http://www.bls.gov/cpi/). The real rate of interest would be obtained as follows:

(1 + 0.00114)/(1 + 0.011) = (1 + r_r) = 0.9902

That is, i_r is equal to 1 – 0.9902 or minus 0.98 percent. Investing in a one-year Treasury security results in a loss of 0.98 percent relative to inflation. The objective of unconventional monetary policy of zero interest rates is to induce consumption and investment because of the loss to inflation of riskless financial assets. Policy would be truly irresponsible if it intended to increase inflationary expectations or π^e. The result could be the same rate of unemployment with higher inflation (Kydland and Prescott 1977).

Current focus is on 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 at 0 to ¼ percent; and (2) outright purchase of Treasury and agency securities and mortgage-backed securities for the balance sheet of the Federal Reserve. Market are overreacting to the so-called “paring” of outright purchases of $85 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 0 to ¼ percent for which there is no end in sight as evident in the FOMC statement for Oct 30, 2013 (http://www.federalreserve.gov/newsevents/press/monetary/20131030a.htm):

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?

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.”

W = Y/r (10

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/search?q=rules+versus+authorities).

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. Indefinite financial repression induces carry trades with high leverage, risks and illiquidity. A competing event is the high level of valuations of risk financial assets (http://cmpassocregulationblog.blogspot.com/2013/01/peaking-valuation-of-risk-financial.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 16,086.41 on Fri Nov 29, 2013, which is higher by 13.6 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 13.3 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs.

The DJIA closed at 16,064.77 on Fri Nov 22, 2013, which is higher by 13.4 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 13.1 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs.

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.

The carry trade from zero interest rates to leveraged positions in risk financial assets had proved strongest for commodity exposures but US equities have regained leadership. The DJIA has increased 66.1 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Nov 29, 2013; S&P 500 has gained 76.6 percent and DAX 65.9 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 11/29/13” had double digit gains relative to the trough around Jul 2, 2010 followed by negative performance but now some valuations of equity indexes show varying behavior. China’s Shanghai Composite is 6.8 percent below the trough. Japan’s Nikkei Average is 77.5 percent above the trough. DJ Asia Pacific TSM is 26.7 percent above the trough. Dow Global is 44.0 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 26.3 percent above the trough. NYSE Financial Index is 48.3 percent above the trough. DJ UBS Commodities is 0.2 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 65.9 percent above the trough. Japan’s Nikkei Average is 77.5 percent above the trough on Aug 31, 2010 and 37.5 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 15,661.87 on Fri Nov 29, 2013 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 52.7 percent higher than 10,254.43 on Mar 11, 2011, on the date of the Tōhoku or Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar depreciated by 14.0 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 11/29/13” in Table VI-4 shows increase of 1.1 percent in the week for China’s Shanghai Composite. DJ Asia Pacific increased 0.5 percent. NYSE Financial increased 0.2 percent in the week. DJ UBS Commodities increased 0.3 percent. Dow Global increased 0.5 percent in the week of Nov 29, 2013. The DJIA increased 0.1 percent and S&P 500 increased 0.1 percent. DAX of Germany increased 2.0 percent. STOXX 50 increased 0.4 percent. The USD depreciated 0.3 percent. There are still high uncertainties on European sovereign risks and banking soundness, US and world growth slowdown and China’s growth tradeoffs. Sovereign problems in the “periphery” of Europe and fears of slower growth in Asia and the US cause risk aversion with trading caution instead of more aggressive risk exposures. There is a fundamental change in Table VI-4 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 11/29/13” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Nov 29, 2013. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 11/29/13” but also relative to the peak in column “∆% Peak to 11/29/13.” There are now several equity indexes above the peak in Table VI-4: DJIA 43.6 percent, S&P 500 48.3 percent, DAX 48.5 percent, Dow Global 17.5 percent, DJ Asia Pacific 11.0 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 18.1 percent, Nikkei Average 37.5 percent and STOXX 50 7.0 percent. There is only one equity index below the peak: Shanghai Composite by 29.8 percent. DJ UBS Commodities Index is now 14.4 percent below the peak. The US dollar strengthened 10.2 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010. Alexandra Scaggs, writing on “Tepid profits, roaring stocks,” on May 16, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323398204578487460105747412.html), analyzes stabilization of earnings growth: 70 percent of 458 reporting companies in the S&P 500 stock index reported earnings above forecasts but sales fell 0.2 percent relative to forecasts of increase of 0.5 percent. Paul Vigna, writing on “Earnings are a margin story but for how long,” on May 17, 2013, published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2013/05/17/earnings-are-a-margin-story-but-for-how-long/), analyzes that corporate profits increase with stagnating sales while companies manage costs tightly. More than 90 percent of S&P components reported moderate increase of earnings of 3.7 percent in IQ2013 relative to IQ2012 with decline of sales of 0.2 percent. Earnings and sales have been in declining trend. In IVQ2009, growth of earnings reached 104 percent and sales jumped 13 percent. Net margins reached 8.92 percent in IQ2013, which is almost the same at 8.95 percent in IIIQ2006. Operating margins are 9.58 percent. There is concern by market participants that reversion of margins to the mean could exert pressure on earnings unless there is more accelerated growth of sales. Vigna (op. cit.) finds sales growth limited by weak economic growth. Kate Linebaugh, writing on “Falling revenue dings stocks,” on Oct 20, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444592704578066933466076070.html?mod=WSJPRO_hpp_LEFTTopStories), identifies a key financial vulnerability: falling revenues across markets for United States reporting companies. Global economic slowdown is reducing corporate sales and squeezing corporate strategies. Linebaugh quotes data from Thomson Reuters that 100 companies of the S&P 500 index have reported declining revenue only 1 percent higher in Jun-Sep 2012 relative to Jun-Sep 2011 but about 60 percent of the companies are reporting lower sales than expected by analysts with expectation that revenue for the S&P 500 will be lower in Jun-Sep 2012 for the entities represented in the index. Results of US companies are likely repeated worldwide. Future company cash flows derive from investment projects. In IQ1980, gross private domestic investment in the US was $951.6 billion of 2009 dollars, growing to $1,143.0 billion in IVQ1986 or 20.1 percent. Real gross private domestic investment in the US decreased 3.1 percent from $2,605.2 billion of 2009 dollars in IVQ2007 to $2,524.9 billion in IIQ2013. Real private fixed investment fell 4.9 percent from $2,586.3 billion of 2009 dollars in IVQ2007 to $2,458.4 billion in IIQ2013. Growth of real private investment in is mediocre for all but four quarters from IIQ2011 to IQ2012 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/09/increasing-interest-rate-risk.html). The investment decision of United States corporations has been fractured in the current economic cycle in preference of cash. Corporate profits with IVA and CCA fell $26.6 billion in IQ2013 after increasing $34.9 billion in IVQ2012 and $13.9 billion in IIIQ2012. Corporate profits with IVA and CCA rebounded with $66.8 billion in IIQ2013. Profits after tax with IVA and CCA fell $1.7 billion in IQ2013 after increasing $40.8 billion in IVQ2012 and $4.5 billion in IIIQ2012. In IIQ2013, profits after tax with IVA and CCA increased $56.9 billion. Anticipation of higher taxes in the “fiscal cliff” episode caused increase of $120.9 billion in net dividends in IVQ2012 followed with adjustment in the form of decrease of net dividends by $103.8 billion in IQ2013, rebounding with $273.5 billion in IIQ2013. There is similar decrease of $80.1 billion in undistributed profits with IVA and CCA in IVQ2012 followed by increase of $102.1 billion in IQ2013 and decline of $216.6 billion in IIQ2013. Undistributed profits of US corporations swelled 263.4 percent from $107.7 billion IQ2007 to $391.4 billion in IIQ2013 and changed signs from minus $55.9 billion in billion in IVQ2007 (Section IA2). In IQ2013, corporate profits with inventory valuation and capital consumption adjustment fell $26.6 billion relative to IVQ2012, from $2047.2 billion to $2020.6 billion at the quarterly rate of minus 1.3 percent. In IIQ2013, corporate profits with IVA and CCA increased $66.8 billion from $2020.6 billion in IQ2013 to $2087.4 billion at the quarterly rate of 3.3 percent (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_3rd.pdf). Uncertainty originating in fiscal, regulatory and monetary policy causes wide swings in expectations and decisions by the private sector with adverse effects on investment, real economic activity and employment. The investment decision of US business is fractured.

It may be quite painful to exit QE→∞ or use of the balance sheet of the central 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 interest rates increase without bound, then V → 0, or

declines. Equally, decline in expected revenue from the stock or project, R_τ, causes decline in valuation. An intriguing issue is the difference in performance of valuations of risk financial assets and economic growth and employment. Paul A. Samuelson (http://www.nobelprize.org/nobel_prizes/economics/laureates/1970/samuelson-bio.html) popularized the view of the elusive relation between stock markets and economic activity in an often-quoted phrase “the stock market has predicted nine of the last five recessions.” In the presence of zero interest rates forever, valuations of risk financial assets are likely to differ from the performance of the overall economy. The interrelations of financial and economic variables prove difficult to analyze and measure.

Table VI-4, Stock Indexes, Commodities, Dollar and 10-Year Treasury

	Peak	Trough	∆% to Trough	∆% Peak to 11/29/ /13	∆% Week 11/29/13	∆% Trough to 11/29/ 13
DJIA	4/26/ 10	7/2/10	-13.6	43.6	0.1	66.1
S&P 500	4/23/ 10	7/20/ 10	-16.0	48.3	0.1	76.6
NYSE Finance	4/15/ 10	7/2/10	-20.3	18.1	0.2	48.3
Dow Global	4/15/ 10	7/2/10	-18.4	17.5	0.5	44.0
Asia Pacific	4/15/ 10	7/2/10	-12.5	11.0	0.5	26.7
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	37.5	1.8	77.5
China Shang.	4/15/ 10	7/02 /10	-24.7	-29.8	1.1	-6.8
STOXX 50	4/15/10	7/2/10	-15.3	7.0	0.4	26.3
DAX	4/26/ 10	5/25/ 10	-10.5	48.5	2.0	65.9
Dollar Euro	11/25 2009	6/7 2010	21.2	10.2	-0.3	-14.0
DJ UBS Comm.	1/6/ 10	7/2/10	-14.5	-14.4	0.3	0.2
10-Year T Note	4/5/ 10	4/6/10	3.986	2.784	2.743

T: trough; Dollar: positive sign appreciation relative to euro (less dollars paid per euro), negative sign depreciation relative to euro (more dollars paid per euro)

Source: http://professional.wsj.com/mdc/page/marketsdata.html?mod=WSJ_hps_marketdata

ESII World Trade Restricting Economic Growth. GDP estimates for major advanced economies for IIIQ2013 are showing deductions of net trade (exports less imports) from GDP growth. It is still too early to assess if this restriction of trade on economic growth is temporary or indicative of trend (for long-term trade and growth see Pelaez 1976a, 1979). This special section provides first the GDP reports of the United States, Japan, Germany, France and the United Kingdom showing deductions of net trade from growth followed by trade and effects of net trade for multiple countries.

United States. Aggregate demand, personal consumption expenditures (PCE) and gross private domestic investment (GDI) were much stronger during the expansion phase in IQ1983 to IVQ1986 than in IIIQ2009 to IIQ2013, as shown in Table I-8. GDI provided the impulse of growth in 1983 and 1984, which has not been the case from 2009 to 2013. The investment decision in the US economy has been frustrated in the current cyclical expansion. Growth of GDP in IIIQ2013 at seasonally adjusted annual rate of 2.8 percent consisted of positive contribution of 1.04 percentage points of personal consumption expenditures (PCE) plus positive contribution of 1.45 percentage points of gross private domestic investment (GDI) of which 0.83 percentage points of inventory investment (∆PI), contribution of net exports (trade or exports less imports) of 0.31 percentage points and 0.04 percentage points of government consumption expenditures and gross investment (GOV) partly because of one-time reduction of national defense expenditures of 0.03 percentage points. The economy of the United States has lost the dynamic growth impulse of earlier cyclical expansions with mediocre growth resulting from consumption forced by one-time effects of financial repression, national defense expenditures and inventory accumulation. While net trade added 0.31 percentage points to the growth of GDP in IIIQ2013 in the advance estimates, net trade deducted 0.28 percentage points in IQ2013 and 0.07 percentage points in IIQ2013.

Table I-8, US, Contributions to the Rate of Growth of GDP in Percentage Points

	GDP	PCE	GDI	∆ PI	Trade	GOV
2013
I	1.1	1.54	0.71	0.93	-0.28	-0.82
II	2.5	1.24	1.38	0.41	-0.07	-0.07
III	2.8	1.04	1.45	0.83	0.31	0.04
2012
I	3.7	1.98	1.57	0.36	0.44	-0.28
II	1.2	1.28	-0.23	-0.91	0.10	0.05
III	2.8	1.15	0.99	0.60	-0.03	0.67
IV	0.1	1.13	-0.36	-2.00	0.68	-1.31
2011
I	-1.3	1.42	-1.11	-1.06	0.01	-1.61
II	3.2	1.03	1.88	0.72	0.53	-0.25
III	1.4	1.42	0.36	-1.60	0.10	-0.52
IV	4.9	1.65	4.13	2.73	-0.60	-0.31
2010
I	1.6	1.42	1.77	1.66	-0.96	-0.63
II	3.9	2.21	2.86	1.09	-1.77	0.61
III	2.8	1.87	1.86	1.90	-0.88	-0.07
IV	2.8	2.86	-0.51	-1.64	1.32	-0.87
2009
I	-5.4	-0.83	-7.02	-2.26	2.25	0.15
II	-0.4	-1.13	-3.25	-1.12	2.40	1.56
III	1.3	1.73	-0.40	-0.38	-0.53	0.48
IV	3.9	0.05	4.05	4.40	-0.05	-0.17
1982
I	-6.5	1.61	-7.60	-5.34	-0.49	-0.05
II	2.2	0.89	-0.06	2.26	0.81	0.56
III	-1.4	1.88	-0.62	1.11	-3.22	0.53
IV	0.4	4.51	-5.37	-5.33	-0.10	1.35
1983
I	5.3	2.45	2.36	0.92	-0.29	0.82
II	9.4	5.06	5.96	3.43	-2.46	0.89
III	8.1	4.50	4.40	0.57	-2.25	1.42
IV	8.5	4.06	6.94	3.01	-1.13	-1.36
1984
I	8.2	2.26	7.23	4.94	-2.31	1.01
II	7.2	3.64	2.57	-0.29	-0.87	1.87
III	4.0	1.95	1.69	0.21	-0.35	0.70
IV	3.2	3.29	-1.08	-2.44	-0.56	1.58
1985
I	4.0	4.23	-2.14	-2.86	0.94	1.01
II	3.7	2.35	1.34	0.35	-1.90	1.93
III	6.4	4.82	-0.43	-0.15	-0.01	1.98
IV	3.0	0.62	2.80	1.40	-0.66	0.27
1986
I	3.8	2.10	0.04	-0.17	0.92	0.70
II	1.9	2.77	-1.30	-1.30	-1.33	1.70
III	4.1	4.55	-1.97	-1.62	-0.45	1.95
IV	2.1	1.62	0.24	-0.29	0.71	-0.48

Note: PCE: personal consumption expenditures; GDI: gross private domestic investment; ∆ PI: change in private inventories; Trade: net exports of goods and services; GOV: government consumption expenditures and gross investment; – is negative and no sign positive

GDP: percent change at annual rate; percentage points at annual rates

Source: US Bureau of Economic Analysis

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

Japan. The economy of Japan grew 0.5 percent in IIIQ2013 after 0.9 percent in IIQ2013 and 1.1 percent in IQ2013, seasonally adjusted, as shown in Table VB-1, incorporating the latest estimates and revisions. Japan’s GDP increased 0.1 percent in IVQ2012 relative to IIIQ2012. IQ2012 GDP growth was revised to 1.2 percent; IIQGDP growth was revised to -0.2 percent; and IIIQ2012 growth was revised to -0.9 percent. The economy of Japan had already weakened in IVQ2010 when GDP fell revised 0.3 percent. As in other advanced economies, Japan’s recovery from the global recession has not been robust. GDP fell 2.0 percent in IQ2011 and fell again 0.8 percent in IIQ2011 as a result of the disruption of the tragic Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011. Recovery was robust in the first two quarters of 2010 but GDP grew at 1.5 percent in IIIQ2010 and fell 0.4 percent in IVQ2010. The deepest quarterly contractions in the recession were 3.3 percent in IVQ2008 and 4.0 percent in IQ2009.

Table VB-2, Japan, Contributions to Changes in Real GDP, Seasonally Adjusted Annual Rates (SAAR), %

	GDP	PC	GFCF	Trade	PINV	GOVC
2013
I	4.3	2.1	0.8	1.6	-0.1	0.0
II	3.8	1.4	1.6	0.6	-0.5	0.6
III	1.9	0.2	1.8	-1.8	1.4	0.2
2012
I	5.1	2.2	-0.1	0.3	1.3	1.3
II	-0.8	0.2	1.1	-1.3	-0.8	0.1
III	-3.7	-0.7	-1.4	-2.1	0.1	0.3
IV	0.6	1.0	0.4	-0.6	-0.7	0.5
2011
I	-7.7	-3.7	-0.3	-1.2	-2.6	0.1
II	-3.0	2.2	-0.3	-4.3	-0.9	0.2
III	10.7	3.8	1.1	3.9	1.6	0.2
IV	1.0	1.4	3.8	-3.1	-1.2	0.2
2010
I	5.7	1.3	0.2	2.1	2.4	-0.5
II	4.0	0.1	0.8	0.1	2.0	1.1
III	6.1	3.3	0.8	0.5	1.3	0.2
IV	-1.6	-0.6	-0.7	-0.5	-0.2	0.3
2009
I	-15.2	-2.1	-1.9	-4.5	-7.5	0.8
II	6.9	4.1	-3.2	7.5	-2.0	0.6
III	0.5	0.2	-1.5	2.2	-1.4	1.0
IV	7.3	3.6	0.3	2.7	0.4	0.3
2008
I	2.6	1.4	0.5	1.1	-0.4	0.0
II	-4.7	-3.2	-2.3	0.5	1.1	-0.8
III	-3.9	-0.3	-1.0	0.0	-2.6	0.0
IV	-12.5	-2.8	-4.5	-11.5	5.7	0.3
2007
I	4.0	0.8	0.6	1.1	1.2	0.4
II	0.5	0.5	-1.6	0.8	0.1	0.5
III	-1.3	-0.8	-1.7	2.0	-0.6	-0.2
IV	3.4	0.3	0.3	1.4	0.9	0.6

Note: PC: Private Consumption; GFCF: Gross Fixed Capital Formation; PINV: Private Inventory; Trade: Net Exports; GOVC: Government Consumption

Source: Japan Economic and Social Research Institute, Cabinet Office

http://www.esri.cao.go.jp/index-e.html http://www.esri.cao.go.jp/en/sna/sokuhou/sokuhou_top.html

Long-term economic growth in Japan significantly improved by increasing competitiveness in world markets. Net trade of exports and imports is an important component of the GDP accounts of Japan. Table VB-3 provides quarterly data for net trade, exports and imports of Japan. Net trade had strong positive contributions to GDP growth in Japan in all quarters from IQ2007 to IIQ2009 with exception of IVQ2008, IIIQ2008 and IQ2009. The US recession is dated by the National Bureau of Economic Research (NBER) as beginning in IVQ2007 (Dec) and ending in IIQ2009 (Jun) (http://www.nber.org/cycles/cyclesmain.html). Net trade contributions helped to cushion the economy of Japan from the global recession. Net trade deducted from GDP growth in seven of the nine quarters from IVQ2010 IQ2012. The only strong contribution of net trade was 3.9 percent in IIIQ2011. Net trade added 1.6 percentage points to GDP growth in IQ2013 and 0.6 percentage points in IIQ2013 but deducted 1.8 percentage points in IIIQ2013. Private consumption assumed the role of driver of Japan’s economic growth but should moderate as in most mature economies.

Table VB-3, Japan, Contributions to Changes in Real GDP, Seasonally Adjusted Annual Rates (SAAR), %

	Net Trade	Exports	Imports
2013
I	1.6	2.2	-0.7
II	0.6	1.7	-1.1
III	-1.8	-0.4	-1.5
2012
I	0.3	1.6	-1.3
II	-1.3	-0.3	-0.9
III	-2.1	-2.3	0.2
IV	-0.6	-1.8	1.2
2011
I	-1.2	-0.5	-0.7
II	-4.3	-4.7	0.4
III	3.9	5.8	-1.9
IV	-3.1	-1.9	-1.2
2010
I	2.1	3.4	-1.3
II	0.1	2.7	-2.6
III	0.5	1.4	-0.9
IV	-0.5	0.1	-0.6
2009
I	-4.5	-16.4	12.0
II	7.5	4.7	2.8
III	2.2	5.2	-3.1
IV	2.7	4.1	-1.4
2008
I	1.1	2.1	-1.0
II	0.5	-1.6	2.1
III	0.0	0.2	-0.1
IV	-11.5	-10.2	-1.3
2007
I	1.1	1.7	-0.5
II	0.8	1.6	-0.8
III	2.0	1.4	0.6
IV	1.4	2.1	-0.7

Source: Japan Economic and Social Research Institute, Cabinet Office

http://www.esri.cao.go.jp/index-e.html http://www.esri.cao.go.jp/en/sna/sokuhou/sokuhou_top.html

Germany. The Statistisches Bundesamt (Federal Statistical Office of Germany) provides the analysis of percentage point contributions to GDP on growth from a quarter a year earlier, shown in Table VE-5. The original data are adjusted for price but not for seasonality. There is strong internal demand, or consumption and investment, which is uncommon in advanced economies. Consumption provided 0.4 percentage points in IVQ2012 with growth of 0.5 percent; deducted 0.1 percentage points in IQ2013 with growth of minus 0.2 percent; added 0.8 percentage points in IIQ2013with growth of 1.1 percent; and added 1.0 percentage points in IIIQ2013 with growth of 1.2 percent. Growth of fixed capital formation (GFCF) deducted 0.8 percentage points to growth of GDP in IVQ2012 and decreased 4.0 percent; deducted 1.2 percentage points in IQ2013 and declined 7.7 percent relative to a year earlier; added 0.1 percentage points in IIQ2013 and grew 0.4 percent; and added 0.4 percentage points in IIIQ2013 with growth of 1.9 percent. Domestic uses added 1.6 percentage points in IIIQ2013 and grew 1.7 percent. Net exports contributed 0.8 percentage points in IVQ2012; deducted 0.5 percentage points in IQ2013; added 0.1 percentage points in IIQ2013; and deducted 0.5 percentage points in IIIQ2013. The rates of growth of exports and imports fell from over 10 percent to single digits and negative changes in IVQ2012 and IQ2013, rebounding with growth of exports of 1.1 percent in IIQ2013 and of imports of 1.2 percent. Exports grew 0.7 percent in IIIQ2013 and imports 1.9 percent. GDP per person in employment grew minus 0.3 percent in IIQ2013 and 0.5 percent in IIIQ2013.

Table VE-5, Germany, Percentage Point Contributions of Use of Gross Domestic Product on Growth from Same Quarter of Prior Year, Price Adjusted

	IVQ 12 PP	∆% IVQ 12	IQ13 PP	∆% IQ 13	IIQ 13 PP	∆% IIQ 13	IIIQ 13 PP	∆% IIIQ 13
Consumption Total	0.4	0.5	-0.1	-0.2	0.8	1.1	1.0	1.2
Households Consumption	0.3	0.5	-0.2	-0.4	0.7	1.2	0.9	1.5
Government Consumption	0.1	0.6	0.1	0.3	0.1	0.6	0.1	0.4
Gross Capital Formation	-1.1	-6.6	-0.9	-4.7	0.0	0.2	0.6	3.5
Gross Fixed Capital Formation (GFCF)	-0.8	-4.0	-1.2	-7.7	0.1	0.4	0.4	1.9
GFCF in Machinery & Equipment	-0.5	-6.2	-0.6	-8.9	0.0	-0.4	0.1	1.0
GFCF in Construction	-0.3	-3.1	-0.7	-8.0	0.1	0.5	0.2	2.2
Change in Inventories	-0.3		0.3		-0.1		0.2
Domestic Uses	-0.7	-0.7	-1.0	-1.1	0.9	0.9	1.6	1.7
Net Exports	0.8		-0.5		0.1		-0.5
Exports		0.5		-2.9		1.1		0.7
Imports		-1.0		-2.2		1.2		1.9
GDP		0.0		-1.6		0.9		1.1
GDP per Person in Employment		-0.8		-2.2		0.3		0.5
GDP per Hour Worked		0.5		0.5		-0.3		-0.1

PP: Percentage Points

Source: Statistisches Bundesamt Deutschland (Destatis

https://www.destatis.de/EN/PressServices/Press/pr/2013/11/PE13_394_811.html

https://www.destatis.de/EN/FactsFigures/Indicators/ShortTermIndicators/ShortTermIndicators.html

United Kingdom. Table VH-9 provides contributions to value added by expenditure components in a quarter relative to the prior quarter. In IQ2013, household final consumption expenditure contributed 0.4 percentage points to growth, 0.2 percentage points in IIQ2013 and 0.5 percentage points in IIIQ2013. Net trade deducted 0.3 percentage points in IVQ2012 but added 0.3 percentage points in IQ2013 and 0.0 percentage points in IIQ2013. In IIIQ2013, net trade deducted 0.9 percentage points. Gross fixed capital formation (GFCF) deducted 0.4 percentage points in IIIQ2012, 0.6 percentage points IVQ2012 and 0.0 percentage points in IQ2013, adding 0.1 percentage points in IIQ2013 and 0.2 percentage points in IIIQ2013.

Table VH-9, UK, Contribution to Quarter on Prior Quarter of Growth of Value Added by Expenditure Components, %

Component	2012 Q1	2012 Q2	2012 Q3	2012 Q4	2013 Q1	2013 Q2	2013 Q3
Household final consumption expenditure	0.2	0.1	0.1	0.5	0.4	0.2	0.5
NPISH final consumption expenditure	0.0	0.1	-0.1	-0.1	0.0	0.0	0.0
General government final consumption expenditure	0.5	-0.3	0.1	0.1	0.0	0.1	0.1
Gross capital formation	0.2	0.2	0.1	-0.5	-0.3	0.3	1.1
- of which GFCF	0.5	-0.1	-0.4	-0.6	0.0	0.1	0.2
- of which Business investment	0.5	-0.2	-0.1	-0.5	0.1	-0.2	0.1
Exports	-0.6	-0.1	0.6	-0.5	0.0	0.9	-0.8
less Imports	0.2	0.5	0.3	-0.3	-0.3	0.9	0.1
Net trade	-0.8	-0.6	0.4	-0.2	0.3	0.0	-0.9

Source: UK Office for National Statistics

http://www.ons.gov.uk/ons/rel/naa2/second-estimate-of-gdp/q3-2013/index.html

France. Percentage changes and contributions of segments of GDP in France are provided in Table VF-3. Internal demand deducted 0.1 percentage points from GDP growth in IQ2013 and added 0.4 percentage points in IIQ2013. Internal demand did not contribute to growth in IIIQ2013. Net foreign trade deducted 0.1 percentage from growth in IQ2013, did not contribute growth in IIQ2013 and subtracted 0.7 percentage points from growth in IIIQ2013.

Table VF-3, France, Contributions to GDP Growth, Calendar and Seasonally Adjusted, %

∆% from Prior Period	IVQ 2012	IQ 2013	IIQ 2013	IIIQ 2013	2012	2013 OVHG
GDP	-0.2	-0.1	0.5	-0.1	0.0	0.1
Imports	-1.1	0.1	1.6	1.0	-0.9	0.9
Household Consump.	0.1	-0.1	0.4	0.2	-0.4	0.3
Govt. Consump.	0.4	0.4	0.7	0.2	1.4	1.6
GFCF	-0.6	-0.8	-0.4	-0.6	-1.2	-2.3
Exports	-0.6	-0.4	1.9	-1.5	2.5	0.1
% Point Contribs.
Internal Demand ex Inventory Changes	0.0	-0.1	0.4	0.0	-0.1	0.2
Inventory Changes	-0.4	0.2	0.1	0.5	-0.8	0.2
Net Foreign Trade	0.2	-0.1	0.0	-0.7	1.0	-0.3

Notes: Consump.: Consumption; Gvt.: Government; GFCF: Gross Fixed Capital Formation; Contribus.: Contributions; OVHG: “annual growth rate carried over at the mid-year point.

Source: Institut National de la Statistique et des Études Économiques

http://www.insee.fr/en/themes/info-rapide.asp?id=26&date=20131114

There is evidence of deceleration of growth of world trade and even contraction in recent data. Table V-4 provides two types of data: growth of exports and imports in the latest available months and in the past 12 months; and contributions of net trade (exports less imports) to growth of real GDP. Japan provides the most worrisome data (Section VB and earlier http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-world-inflation.html http://cmpassocregulationblog.blogspot.com/2013/09/duration-dumping-and-peaking-valuations_8763.html http://cmpass ocregulationblog.blogspot.com/2013/08/interest-rate-risks-duration-dumping.html and earlier http://cmpassocregulationblog.blogspot.com/2013/07/duration-dumping-steepening-yield-curve.html and earlier http://cmpassocregulationblog.blogspot.com/2013/06/paring-quantitative-easing-policy-and_4699.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/05/united-states-commercial-banks-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2013/04/world-inflation-waves-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2013/03/united-states-commercial-banks-assets.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/02/world-inflation-waves-united-states.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html and earlier http://cmpassocregulationblog.blogspot.com/2012/11/contraction-of-united-states-real_25.html and for GDP http://cmpassocregulationblog.blogspot.com/2013/09/recovery-without-hiring-ten-million.html and earlier http://cmpassocregulationblog.blogspot.com/2013/08/duration-dumping-and-peaking-valuations.html and earlier http://cmpassocreulationblog.blogspot.com/2013/02/recovery-without-hiring-united-states.html). In Oct 2013, Japan’s exports grew 18.6 percent in 12 months while imports increased 26.1 percent. The second part of Table V-4 shows that net trade deducted 1.3 percentage points from Japan’s growth of GDP in IIQ2012, deducted 2.1 percentage points from GDP growth in IIIQ2012 and deducted 0.6 percentage points from GDP growth in IVQ2012. Net trade added 0.3 percentage points to GDP growth in IQ2012, 1.6 percentage points in IQ2013 and 0.6 percentage points in IIQ2013. In IIIQ2013, net trade deducted 1.8 percentage points from GDP growth in Japan. In Oct 2013, China exports increased 5.6 percent relative to a year earlier and imports increased 7.6 percent. Germany’s exports increased 1.7 percent in the month of Aug 2013 and fell 5.4 percent in the 12 months ending in Aug 2013. Germany’s imports increased 1.7 percent in the month of Sep and increased 3.6 percent in the 12 months ending in Sep. Net trade contributed 0.8 percentage points to growth of GDP in IQ2012, contributed 0.4 percentage points in IIQ2012, contributed 0.3 percentage points in IIIQ2012, deducted 0.5 percentage points in IVQ2012, deducted 0.2 percentage points in IQ2012 and added 0.3 percentage points in IIQ2013. Net traded deducted 0.4 percentage points from Germany’s GDP growth in IIIQ2013. Net trade deducted 0.8 percentage points from UK value added in IQ2012, deducted 0.6 percentage points in IIQ2012, added 0.4 percentage points in IIIQ2012 and subtracted 0.2 percentage points in IVQ2012. In IQ2013, net trade added 0.3 percentage points to UK’s growth of value added and contributed 0.0 percentage points in IIQ2013. In IIIQ2013, net trade deducted 0.9 percentage points from UK GDP growth. France’s exports increased 1.8 percent in Sep 2013 while imports increased 3.4. Net traded added 0.1 percentage points from France’s GDP in IIIQ2012 and 0.2 percentage points in IVQ2012. Net trade deducted 0.1 percentage points from France’s GDP growth in IQ2013 and was neutral in IIQ2013, deducting 0.7 percentage points in IIIQ2013. US exports decreased 0.2 percent in Sep 2013 and goods exports increased 1.6 percent in Jan-Sep 2013 relative to a year earlier but net trade deducted 0.03 percentage points from GDP growth in IIIQ2012 and added 0.68 percentage points in IVQ2012. Net trade deducted 0.28 percentage points from US GDP growth in IQ2013 and deducted 0.07 percentage points in IIQ2013. Net traded added 0.31 percentage points to US GDP growth in IIIQ2013. US imports increased 1.2 percent in Sep 2013 and goods imports decreased 0.9 percent in Jan-Sep 2013 relative to a year earlier. Industrial production decreased 0.1 percent in Oct 2013 after increasing 0.7 percent in Sep 2013 and increasing 0.5 percent in Aug 2013, as shown in Table I-1, with all data seasonally adjusted. The report of the Board of Governors of the Federal Reserve System states (http://www.federalreserve.gov/releases/g17/Current/default.htm):

“Industrial production edged down 0.1 percent in October after having increased 0.7 percent in September. Manufacturing production rose 0.3 percent in October for its third consecutive monthly gain. The index for mining fell 1.6 percent after having risen for six consecutive months, and the output of utilities dropped 1.1 percent after having jumped 4.5 percent in September. The level of the index for total industrial production in October was equal to its 2007 average and was 3.2 percent above its year-earlier level. Capacity utilization for the industrial sector declined 0.2 percentage point in October to 78.1 percent, a rate 1.1 percentage points above its level of a year earlier and 2.1 percentage points below its long-run (1972-2012) average.“

In the six months ending in Oct 2013, United States national industrial production accumulated increase of 1.3 percent at the annual equivalent rate of 2.6 percent, which is lower than growth of 3.2 percent in the 12 months ending in Oct 2013. Excluding growth of 0.7 percent in Sep 2013, growth in the remaining five months from May 2012 to Oct 2013 accumulated to 0.6 percent or 1.2 percent annual equivalent. Industrial production fell in two of the past six months. Business equipment accumulated growth of 1.7 percent in the six months from May to Oct 2013 at the annual equivalent rate of 3.4 percent, which is much lower than growth of 5.1 percent in the 12 months ending in Oct 2013. Growth of business equipment accumulated 0.1 percent from Apr to Aug 2013 at the annual equivalent rate of minus 0.2 percent. The Fed analyzes capacity utilization of total industry in its report (http://www.federalreserve.gov/releases/g17/Current/default.htm): “Capacity utilization for the industrial sector declined 0.2 percentage point in October to 78.1 percent, a rate 1.1 percentage points above its level of a year earlier and 2.1 percentage points below its long-run (1972-2012) average.” United States industry apparently decelerated to a lower growth rate. Manufacturing increased 0.3 percent in Oct 2013 after increasing 0.1 percent in Sep 2013 and increasing 0.7 percent in Aug 2013 seasonally adjusted, increasing 3.4 percent not seasonally adjusted in 12 months ending in Oct 2013, as shown in Table I-2. Manufacturing grew cumulatively 1.2 percent in the six months ending in Oct 2013 or at the annual equivalent rate of 2.4 percent. Excluding the increase of 0.7 percent in Aug 2013, manufacturing accumulated growth of 0.5 percent from May 2013 to Oct 2013 or at the annual equivalent rate of 1.0 percent. Manufacturing fell 21.9 from the peak in Jun 2007 to the trough in Apr 2009 and increased 16.8 percent from the trough in Apr 2009 to Dec 2012. Manufacturing grew 21.2 percent from the trough in Apr 2009 to Oct 2013. Manufacturing output in Oct 2013 is 5.3 percent below the peak in Jun 2007.

Table V-4, Growth of Trade and Contributions of Net Trade to GDP Growth, ∆% and % Points

	Exports M ∆%	Exports 12 M ∆%	Imports M ∆%	Imports 12 M ∆%
USA	-0.2 Sep	1.6 Jan-Sep	1.2 Sep	-0.9 Jan-Sep
Japan		Oct 2013 18.6 Sep 2013 11.5 Aug 2013 14.7 Jul 2013 12.2 Jun 2013 7.4 May 2013 10.1 Apr 2013 3.8 Mar 2013 1.1 Feb 2013 -2.9 Jan 2013 6.4 Dec -5.8 Nov -4.1 Oct -6.5 Sep -10.3 Aug -5.8 Jul -8.1		Oct 2013 26.1 Sep 2013 16.5 Aug 2013 16.0 Jul 2013 19.6 Jun 2013 11.8 May 2013 10.0 Apr 2013 9.4 Mar 2013 5.5 Feb 2013 7.3 Jan 2013 7.3 Dec 1.9 Nov 0.8 Oct -1.6 Sep 4.1 Aug -5.4 Jul 2.1
China		5.6 Oct -0.3 Sep 7.2 Aug 5.1 Jul -3.1 Jun 1.0 May 14.7 Apr 10.0 Mar 21.8 Feb		7.6 Oct 7.4 Sep 10.9 Jul -0.7 Jun -0.3 May 16.8 Apr 14.1 Mar -15.2 Feb
Euro Area	2.7 12-M Sep	0.9 Jan-Sep	-0.2 12-M Sep	-3.5 Jan-Sep
Germany	1.7 Sep CSA	3.6 Sep	-1.9 Sep CSA	-0.3 Sep
France Sep	1.8	-1.3	3.4	0.7
Italy Sep	0.6	2.0	1.9	-0.1
UK	0.1 Sep	0.1 Jul-Sep 13 /Jul-Sep 12	0.2 Sep	1.8 Jul-Sep 13/Jul-Sep 12
Net Trade % Points GDP Growth	% Points
USA	IIIQ2013 0.31 IIQ2013 -0.07 IQ2013 -0.28 IVQ2012 +0.68 IIIQ2012 -0.03 IIQ2012 +0.10 IQ2012 +0.44
Japan	0.3 IQ2012 -1.3 IIQ2012 -2.1 IIIQ2012 -0.6 IVQ2012 1.6 IQ2013 0.6 IIQ2013 -1.8 IIIQ2013
Germany	IQ2012 0.8 IIQ2012 0.4 IIIQ2012 0.3 IVQ2012 -0.5 IQ2013 -0.2 IIQ2013 0.3 IIIQ2013 -0.4
France	0.1 IIIQ2012 0.2 IVQ2012 -0.1 IQ2013 0.0 IIQ2013 -0.7 IIIQ2013
UK	-0.8 IQ2012 -0.6 IIQ2012 +0.4 IIIQ2012 -0.2 IVQ2012 0.3 IQ2013 0.0 IIQ2013 -0.9 IIIQ2013

Sources: Country Statistical Agencies http://www.census.gov/foreign-trade/ http://www.bea.gov/iTable/index_nipa.cfm

ESIII 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 Oct 2012 and Oct 2013. Total assets of US commercial banks grew 7.6 percent from $12,861.3 billion in Oct 2012 to $13,832.9 billion in Oct 2013. US GDP in IIIQ2013 is estimated at $16,857.6 billion (http://www.bea.gov/iTable/index_nipa.cfm). Thus, total assets of US commercial banks are equivalent to around 82 percent of US GDP. Bank credit grew 1.9 percent from $9852.7 billion in Oct 2012 to $10,036.9 billion in Oct 2013. Securities in bank credit declined 0.1 percent from $2682.7 billion in Oct 2012 to $2679.4 billion in Oct 2013. A large part of securities in banking credit consists of US Treasury and agency securities, falling 3.6 percent from $1840.8 billion in Oct 2012 to $1774.2 billion in Oct 2013. Credit to the government that issues or backs Treasury and agency securities of $1774.2 billion in Oct 2013 is about 17.7 percent of total bank credit of US commercial banks of $10,036.9 billion. Mortgage-backed securities, providing financing of home loans, fell 1.4 percent, from $1330.3 billion in Oct 2012 to $1312.1 billion in Oct 2013. Loans and leases are relatively more dynamic, growing 2.6 percent from $7170.0 billion in Oct 2012 to $7357.5 billion in Oct 2013. The only dynamic class is commercial and industrial loans, growing 8.0 percent from Oct 2012 to Oct 2013 and providing $1589.5 billion or 21.6 percent of total loans and leases of $7357.5 billion in Oct 2013. Real estate loans decreased 0.3 percent, providing $3514.8 billion in Oct 2013 or 47.8 percent of total loans and leases. Consumer loans increased 3.3 percent, providing $1146.7 billion in Oct 2013 or 15.6 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” (http://www.federalreserve.gov/releases/h8/current/default.htm). Cash assets in US commercial banks increased 57.5 percent from $1581.2 billion in Oct 2012 to $2490.9 billion in Oct 2013 but a single year of the series masks exploding cash in banks because of unconventional monetary policy, which is discussed below. Bank deposits increased 7.4 percent from $8988.4 billion to $9656.5 billion. The difference between bank deposits and total loans and leases in banks increased from $1818.4 billion in Oct 2012 to $2299.0 billion in Oct 2013 or by $480.6 billion. Securities in bank credit decreased by -$3.3 billion from $2682.7 billion in Oct 2012 to $2679.4 billion in Oct 2013 and Treasury and agency securities decreased by $66.6 billion from $1840.8 billion in Oct 2012 to $1774.2 billion in Oct 2013. Loans and leases increased $187.5 billion from $7170.0 billion in Oct 2012 to $7357.5 billion in Oct 2013. 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 with real disposable income per capita in IIQ2013 higher by only 2.4 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) in contrast with 12.1 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, growth of real disposable income grew cumulatively 16.4 percent in the cycle from IQ1980 to IIIQ1986 that was higher than trend growth of 14.9 percent.

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

	Oct 2012	Oct 2013	∆%
Total Assets	12,861.3	13,832.9	7.6
Bank Credit	9852.7	10,036.9	1.9
Securities in Bank Credit	2682.7	2679.4	-0.1
Treasury & Agency Securities	1840.8	1774.2	-3.6
Mortgage-Backed Securities	1330.3	1312.1	-1.4
Loans & Leases	7170.0	7357.5	2.6
Real Estate Loans	3524.9	3514.8	-0.3
Consumer Loans	1109.7	1146.7	3.3
Commercial & Industrial Loans	1472.4	1589.5	8.0
Other Loans & Leases	1063.0	1106.4	4.1
Cash Assets*	1581.2	2490.9	57.5
Total Liabilities	11,362.2	12,327.1	8.5
Deposits	8988.4	9656.5	7.4

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

http://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 2008 to 2012 and for Sep 2013 and Oct 2013. The global recession had strong impact on bank assets as shown by declines of total assets of 6.0 percent in 2009 and 2.7 percent in 2010. Loans and leases fell 10.2 percent in 2009 and 5.8 percent in 2010. Commercial and industrial loans fell 18.5 percent in 2009 and 9.0 percent in 2010. Unconventional monetary policy caused an increase of cash assets of banks of 160.2 percent in 2008, 49.0 percent in 2009 and 48.3 percent in 2011 followed by decline by 2.1 percent in 2012. 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, 60.3 percent in Aug 2013, 59.9 percent in Sep 2013 and 59.9 percent in Oct 2013. 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 9.1 percent in Aug 2013. Securities in bank credit fell at the SAAR of 8.7 percent in Sep 2013 and increased at 2.8 percent in Oct 2013. 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 15.2 percent in 2010 and 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 17.2 percent in Aug 2013. Treasury and agency securities fell at the SAAR of 7.2 percent in Sep 2013 and increased at 1.0 percent in Oct 2013. 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 2.5 percent in Aug 2013. Deposits grew at the rate of 8.0 percent in Sep 2013 and at 9.2 percent in Oct 2013. 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, Seasonally Adjusted Annual Rate, ∆%

	2008	2009	2010	2011	2012	Sep 2013	Oct 2013
Total Assets	7.9	-6.0	-2.7	5.4	2.5	7.7	10.2
Bank Credit	2.1	-6.6	-2.7	1.8	4.0	-1.3	3.3
Securities in Bank Credit	-1.8	6.6	6.9	1.8	7.5	-8.7	2.8
Treasury & Agency Securities	2.6	13.5	15.2	3.1	8.6	-7.2	1.0
Other Securities	-7.5	-3.2	-7.1	-0.7	5.1	-11.6	6.3
Loans & Leases	3.2	-10.2	-5.8	1.8	2.7	1.4	3.4
Real Estate Loans	-0.2	-5.7	-5.5	-3.8	-1.1	-0.9	-2.7
Consumer Loans	5.1	-3.3	-7.1	-0.7	1.2	2.4	5.2
Commercial & Industrial Loans	12.8	-18.5	-9.0	9.0	11.3	3.3	11.7
Other Loans & Leases	1.7	-23.1	0.4	19.8	6.6	5.0	9.5
Cash Assets	160.2	49.0	-7.8	48.3	-2.1	59.9	59.9
Total Liabilities	10.6	-7.1	-3.4	5.5	2.3	8.7	6.8
Deposits	5.4	5.2	2.4	6.7	7.2	8.0	9.2

Source: Board of Governors of the Federal Reserve System

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

Chart I-16 is 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. 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 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 maximum 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.”

Chart I-16, US, Deposits, Treasury and Government Securities in Bank Credit, Loans and Leases in Bank Credit and Cash Assets, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1973-2013, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

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

ESIV United States Housing. Seasonally adjusted annual rates (SAAR) of housing starts and permits are shown in Table II-1. Data for starts are only available until Aug 2013 while data for permits are available until Oct 2013. Housing starts decreased 0.9 percent in Aug 2013 after increasing 6.7 percent in Jul 2013 and decreasing 9.1 percent in Jun 2013. Housing permits, indicating future activity, increased 6.2 percent in Oct 2013 after increasing 5.2 percent in Sep 2013 and decreasing 2.9 percent in Aug 2013. While single unit houses starts increased 5.6 percent in Aug 2013, seasonally adjusted, structures with five units or more decreased 11.9 percent. Multifamily residential construction is increasing at a faster rate than single-family construction. Monthly rates in starts and permits fluctuate significantly as shown in Table II-1.

Table II-1, US, Housing Starts and Permits SSAR Month ∆%

	Housing Starts SAAR	Month ∆%	Housing Permits SAAR	Month ∆%
Oct 2013	NA	NA	1034	6.2
Sep	NA	NA	974	5.2
Aug	883	-0.9	926	-2.9
Jul	891	6.7	954	3.9
Jun	835	-9.1	918	-6.8
May	919	7.9	985	-2.0
Apr	852	-15.2	1005	12.9
Mar	1005	3.7	890	-6.5
Feb	969	7.9	952	4.0
Jan	898	-8.6	915	-3.0
Dec 2012	983	16.7	943	1.1
Nov	842	-2.5	933	2.8
Oct	864	1.2	908	-1.4
Sep	854	14.0	921	11.4
Aug	749	1.1	827	-1.4
Jul	741	-2.1	839	6.9
Jun	757	6.5	785	-2.6
May	711	-5.7	806	7.6
Apr	754	6.6	749	-4.6
Mar	707	-0.8	785	6.2
Feb	713	-1.4	739	3.5
Jan	723	4.2	714	2.4
Dec 2011	694	-2.4	697	-1.3
Nov	711	16.6	706	5.2
Oct	610	-6.2	671	10.0
Sep	650	11.1	610	-5.7
Aug	585	-6.1	647	4.2
Jul	623	2.5	621	-2.4
Jun	608	8.4	636	2.9
May	561	1.3	618	6.4
Apr	554	-7.7	581	-0.3
Mar	600	16.1	583	7.6
Feb	517	-17.9	542	-5.9
Jan	630	16.9	576	-8.9
Dec 2010	539	-1.1	632	12.9
Nov	545	0.4	560	0.4
Oct	543	-8.6	558	-0.9
Sep	594	-0.8	563	-2.9

SAAR: Seasonally Adjusted Annual Rate

Source: US Census Bureau

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

Housing starts in Jan-Aug not-seasonally adjusted and housing permits in Jan-Oct are provided in Table II-2. Housing starts increased 22.8 percent in Jan-Aug 2013 relative to Jan-Aug 2012 and new permits in Jan-Oct 2013 increased 21.2 percent relative to Jan-Oct 2012. Construction of new houses in the US remains at very depressed levels. Housing starts fell 52.3 percent in Jan-Aug 2013 relative to Jan-Aug 2006 and fell 56.1 percent relative to Jan-Aug 2005. Housing permits fell 49.0 percent in Jan-Oct 2013 relative to Jan-Oct 2006 and fell 55.3 percent in Jan-Oct 2013 from Jan-Oct 2005.

Table II-2, US, Housing Starts and New Permits, Thousands of Units, NSA, and %

	Housing Starts*	New Permits
Jan-Oct 2013	616.7	823.4
Jan-Oct 2012	502.4	685.8
∆% Jan-Oct 2013/Jan-Oct 2012	22.8	20.1
Jan-Oct 2006	1,292.5	1,616.0
∆% Jan-Oct 2013/Jan-Oct 2006	-52.3	-49.0
Jan-Oct 2005	1,403.2	1,841.7
∆% Jan-Oct 2013/Jan-Oct 2005	-56.1	-55.3

*Jan-Aug

Source: US Census Bureau http://www.census.gov/construction/nrc/

Chart II-1 of the US Census Bureau shows the sharp increase in construction of new houses from 2000 to 2006. Housing construction fell sharply through the recession, recovering from the trough around IIQ2009. The right-hand side of Chart II-1 shows a mild downward trend or stagnation from mid-2010 to the present in single-family houses with a recent mild upward trend in recent months in the category of two or more units but marginal decline in recent months. While single unit houses starts increased 19.4 percent in Jan-Aug 2013 relative to a year earlier, not seasonally adjusted, structures with two to four units increased 43.2 percent and with five units or more increased 30.7 percent.

Chart II-1, US, Total and Single-Family New Housing Units Started in the US, SAAR (Seasonally Adjusted Annual Rate)

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr020.html

Table II-4 provides new housing units that started in the US at seasonally adjusted annual rates (SAAR) from Jan to Aug of the year from 2000 to 2013. SAARs have dropped from high levels around 2 million in 2005-2006 to the range of 707,000 in Mar 2012 to 983,000 in Dec 2012 and 1,005,000 in Mar 2013, which is an improvement over the range of 517,000 in Feb 2011 to 711,000 in Nov 2011. There is improvement in Jul 2013 with SAAR of 891,000 relative to 741,000 in Jul 2012 and in Aug 2013 with 883,000 relative to 749,000 in Aug 2012.

Table II-4, US, New Housing United Started at Seasonally Adjusted Rates, Thousand Units

	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug
2000	1,636	1,737	1,604	1,626	1,575	1,559	1,463	1,541
2001	1,600	1,625	1,590	1,649	1,605	1,636	1,670	1,567
2002	1,698	1,829	1,642	1,592	1,764	1,717	1,655	1,633
2003	1,853	1,629	1,726	1,643	1,751	1,867	1,897	1,833
2004	1,911	1,846	1,998	2,003	1,981	1,828	2,002	2,024
2005	2,144	2,207	1,864	2,061	2,025	2,068	2,054	2,095
2006	2,273	2,119	1,969	1,821	1,942	1,802	1,737	1,650
2007	1,409	1,480	1,495	1,490	1,415	1,448	1,354	1,330
2008	1,084	1,103	1,005	1,013	973	1,046	923	844
2009	490	582	505	478	540	585	594	586
2010	614	604	636	687	583	536	546	599
2011	630	517	600	554	561	608	623	585
2012	723	713	707	754	711	757	741	749
2013	898	969	1,005	852	919	835	891	883

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr020.html

Chart II-2 of the US Census Bureau provides construction of new housing units started in the US at seasonally adjusted annual rate (SAAR) from Jan 1959 to Aug 2013 that help to analyze in historical perspective the debacle of US new house construction. There are three periods in the series. (1) There is stationary behavior with wide fluctuations from 1959 to the beginning of the decade of the 1970s. (2) There is sharp upward trend from the 1990s to 2006 propelled by the US housing subsidy, politics of Fannie Mae and Freddie Mac and unconventional monetary policy of near zero interest rates from Jun 2003 to Jun 2004 and suspension of the auction of 30-year Treasury bonds intended to lower mortgage rates. 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 . (3) Housing construction dropped vertically during the global recession. There was initial stability followed by some recovery in recent months.

Chart II-2, US, New Housing Units Started in the US, SAAR (Seasonally Adjusted Annual Rate), Thousands of Units, Jan 1959-Aug 2013

Source: US Census Bureau http://www.census.gov/construction/nrc/

Table II-5 provides actual new housing units started in the US, not seasonally adjusted, from Jan to Aug in the years from 2000 to 2013. The number of housing units started fell from the peak of 197.9 thousand in May 2005 to 80.4 thousand in Aug 2013 or decline of 59.4 percent. The number of housing units started jumped from 69.0 thousand in Aug 2011 to 80.4 thousand in Aug 2013 or by 16.5 percent and increase of 42.8 percent from 56.3 thousand in Aug 2010.

Table II-5, New Housing Units Started in the US, Not Seasonally Adjusted, Thousands of Units

	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug
2000	104.0	119.7	133.4	149.5	152.9	146.3	135.0	141.4
2001	106.4	108.2	133.2	151.3	154.0	155.2	154.6	141.5
2002	110.4	120.4	138.2	148.8	165.5	160.3	155.9	147.0
2003	117.8	109.7	147.2	151.2	165.0	174.5	175.8	163.8
2004	124.5	126.4	173.8	179.5	187.6	172.3	182.0	185.9
2005	142.9	149.1	156.2	184.6	197.9	192.8	187.6	192.0
2006	153.0	145.1	165.9	160.5	190.2	170.2	160.9	146.8
2007	95.0	103.1	123.8	135.6	136.5	137.8	127.9	121.2
2008	70.8	78.4	82.2	89.5	91.7	102.5	86.7	76.4
2009	31.9	39.8	42.7	42.5	52.2	59.1	56.8	52.9
2010	38.9	40.7	54.7	62.0	56.2	53.8	51.5	56.3
2011	40.2	35.4	49.9	49.0	54.0	60.5	57.6	54.5
2012	47.2	49.7	58.0	66.8	67.8	74.7	69.2	69.0
2013	58.7	66.1	83.3	76.3	87.2	80.7	84.0	80.4

Source: US Census Bureau http://www.census.gov/construction/nrc/

Chart II-3 of the US Census Bureau provides new housing units started in the US not seasonally adjusted (NSA) from Jan 1959 to Aug 2013. There is the same behavior as in Chart II-2 SA but with sharper fluctuations in the original series without seasonal adjustment. There are the same three periods. (1) The series is virtually stationary with wide fluctuations from 1959 to the late 1980s. (2) There is downward trend during the savings and loans crisis of the 1980s. 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 $4346.7 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 3.45 percent of GDP in a year. US GDP in 2012 is estimated at $16,244.6 billion, such that the bailout would be equivalent to cost to taxpayers of about $560.4 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. (3) There is vertical drop of new housing construction in the US during the global recession from (Dec) IVQ2007 to (Jun) IIQ2009 (http://www.nber.org/cycles/cyclesmain.html). The final segment shows upward trend but it could be simply part of yet another fluctuation. Marginal improvement in housing in the US should not obscure the current depressed levels relative to earlier periods.

Chart II-3, US, New Housing Units Started in the US, Not Seasonally Adjusted, Thousands of Units, Jan 1959-Aug 2013

Source: US Census Bureau http://www.census.gov/construction/nrc/

Chart II-4 of the US Census Bureau provides single-family houses started without seasonal adjustment. There was sharp increase from 1992 to 2007 followed by sharp decline. The recovery is sluggish.

Chart II-4, US, Single-family Houses Started, Thousands of Units, NSA

Source: US Census Bureau http://www.census.gov/construction/nrc

Chart II-5 of the US Census Bureau provides housing units started with five units or more. Construction was stagnant before the drop in the global recession. Recovery is stronger than in the case of single-family units.

Chart II-5, US, Housing Units Stated in Buildings with Five Units or More, Thousands of Units

Source: US Census Bureau http://www.census.gov/construction/nrc/

A longer perspective on residential construction in the US is provided by Table II-6 with annual data from 1960 to 2012. Housing starts fell 62.3 percent from 2005 to 2012, 50.2 percent from 2000 to 2012 and 45.4 percent relative to the average from 1959 to 1963. Housing permits fell 61.5 percent from 2005 to 2012, 47.9 percent from 2000 to 2012 and 28.4 percent from the average of 1969-1963 to 2012. Housing starts rose 31.8 from 2000 to 2005 while housing permits grew 35.4 percent. From 1990 to 2000, housing starts increased 31.5 percent while permits increased 43.3 percent.

Table II-6, US, Annual New Privately Owned Housing Units Authorized by Building Permits in Permit-Issuing Places and New Privately Owned Housing Units Started, Thousands

	Starts	Permits
2012	780.6	829.7
∆% 2012/2011	28.2	32.9
∆% 2012/2010	33.0	37.2
∆% 2012/2005	-62.3	-61.5
∆% 2012/2000	-50.2	-47.9
∆% 2012/Av 1959-1963	-45.4	-28.4
2011	608.8	624.1
∆% 2011/2005	-70.6	-71.0
∆% 2011/2000	-61.2	-60.8
∆% 2011/Av 1959-1963	-57.4	-46.1
2010	586.9	604.6
2009	554.0	583.0
2008	905.5	905.4
2007	1,355,0	1,398.4
2006	1,800.9	1,838.9
2005	2,068.3	2,155.3
∆% 2005/2000	31.8	35.4
2004	1,955.8	2,070.1
2003	1,847.7	1,889.2
2002	1,704.9	1,747.7
2001	1,602.7	1,636.7
2000	1,568.7	1,592.3
∆% 2000/1990	31.5	43.3
1990	1,192,7	1,110.8
1980	1,292.2	1,190.6
1970	1,433.6	1,351.5
Average 1959-63	1,429.7	1,158.2

Source: US Census Bureau http://www.census.gov/construction/nrc/

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 months percentage changes improved steadily from around minus 6 percent in Mar to May 2011 to minus 4.4 percent in Jun 2011. The FHFA house price index fell 0.6 percent in Oct 2011 and fell 3.1 percent in the 12 months ending in Oct. There was significant recovery in Nov 2012 with increase in the house price index of 0.5 percent and reduction of the 12-month rate of decline to 2.2 percent. The house price index rose 0.4 percent in Dec 2011 and the 12-month percentage change improved to minus 1.2 percent. There was further improvement with revised decline of 0.3 percent in Jan 2012 and decline of the 12-month percentage change to minus 1.0 percent. The index improved to positive change of 0.5 percent in Feb 2012 and increase of 0.4 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 2.3 percent in 12 months. The house price index of FHFA increased 0.8 percent in Apr 2012 and 3.0 percent in 12 months and improvement continued with increase of 0.6 percent in May 2012 and 3.8 percent in the 12 months ending in May 2012. Improvement consolidated with increase of 0.5 percent in Jun 2012 and 3.9 percent in 12 months. In Jul 2012, the house price index increased 0.1 percent and 3.8 percent in 12 months. Strong increase of 0.5 percent in Aug 2012 pulled the 12-month change to 4.5 percent. There was another increase of 0.7 percent in Oct and 5.6 percent in 12 months followed by increase of 0.6 percent in Nov 2012 and 5.7 percent in 12 months. The FHFA house price index increased 0.6 percent in Jan 2013 and 6.6 percent in 12 months. Improvement continued with increase of 0.5 percent in Apr 2013 and 7.3 percent in 12 months. In May 2013, the house price indexed increased 0.9 percent and 7.7 percent in 12 months. The FHFA house price index increased 0.7 percent in Jun 2013 and 8.0 percent in 12 months. In Jul 2013, the FHFA house price index increased 0.7 percent and 8.7 percent in 12 months. Improvement continued with increase of 0.4 percent in Aug 2013 and 8.5 percent in 12 months. In Sep 2013, the house price index increased 0.3 percent and 8.5 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
Sep 2013	0.3	8.5
Aug	0.4	8.5
Jul	0.7	8.7
Jun	0.7	8.0
May	0.9	7.7
Apr	0.5	7.3
Mar	1.4	7.6
Feb	0.9	7.0
Jan	0.6	6.6
Dec 2012	0.5	5.7
Nov	0.6	5.7
Oct	0.7	5.6
Sep	0.3	4.3
Aug	0.5	4.5
Jul	0.1	3.8
Jun	0.5	3.9
May	0.6	3.8
Apr	0.8	3.0
Mar	0.9	2.3
Feb	0.5	0.4
Jan	-0.3	-1.0
Dec 2011	0.4	-1.2
Nov 2011	0.5	-2.2
Oct 2011	-0.6	-3.1
Sep 2011	0.4	-2.3
Aug 2011	-0.2	-3.7
Jul 2011	0.2	-3.5
Jun 2011	0.4	-4.4
May 2011	-0.1	-5.9
Apr 2011	0.2	-5.8
Mar 2011	-0.9	-5.9
Feb 2011	-1.0	-5.1
Jan 2011	-0.5	-4.6
Dec 2010		-3.8
Dec 2009		-2.0
Dec 2008		-9.9
Dec 2007		-3.1
Dec 2006		2.5
Dec 2005		9.8
Dec 2004		10.2
Dec 2003		8.0
Dec 2002		7.8
Dec 2001		6.7
Dec 2000		7.2
Dec 1999		6.2
Dec 1998		5.9
Dec 1997		3.4
Dec 1996		2.8
Dec 1995		3.0
Dec 1994		2.6
Dec 1993		3.1
Dec 1992		2.4

Source: Federal Housing Finance Agency

http://fhfa.gov/Default.aspx?Page=14

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 2012, the FHFA house price index increased 84.5 percent at the yearly average rate of 3.1 percent. In the period 1992-2000, the FHFA house price index increased 39.4 percent at the average yearly rate of 4.2 percent. The rate of price increase accelerated to 7.5 percent in the period 2000-2003 and to 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 7.5 percent in 2003-2006. House prices measured by the FHFA house price index declined 14.2 percent between 2006 and 2012 and 12.0 percent between 2005 and 2012.

Table IIA2-4, US, FHFA House Price Index, Percentage Change and Average Rate of Percentage Change per Year, Selected Dates 1992-2012

Dec	∆%	Average ∆% per Year
1992-2012	84.5	3.1
1992-2000	39.4	4.2
2000-2003	24.2	7.5
2000-2005	50.4	8.5
2003-2005	21.1	10.0
2005-2012	-12.0	NA
2000-2006	54.2	7.5
2003-2006	24.1	7.5
2006-2012	-14.2	NA

Source: Source: Federal Housing Finance Agency

http://fhfa.gov/Default.aspx?Page=14

Table VA-5 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 95.5 percent in the 10-city composite of the Case-Shiller home price index and 80.5 percent in the 20-city composite between Sep 2000 and Sep 2005. Prices rose around 100 percent from Sep 2000 to Sep 2006, increasing 103.0 percent for the 10-city composite and 88.2 percent for the 20-city composite. House prices rose 39.2 percent between Sep 2003 and Sep 2005 for the 10-city composite and 34.9 percent for the 20-city composite propelled by low fed funds rates of 1.0 percent between Jun 2003 and Jun 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) 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 Sep 2003 and Sep 2006, the 10-city index gained 44.5 percent and the 20-city index increased 40.7 percent. House prices have fallen from Sep 2006 to Sep 2013 by 20.0 percent for the 10-city composite and 19.5 percent for the 20-city composite. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Sep 2013, house prices increased 13.3 percent in the 10-city composite and increased 13.3 percent in the 20-city composite. Table VA-5 also shows that house prices increased 62.3 percent between Sep 2000 and Sep 2013 for the 10-city composite and increased 51.5 percent for the 20-city composite. 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 20.4 percent from the peak in Jun 2006 to Sep 2013 and the 20-city composite fell 19.8 percent from the peak in Jul 2006 to Sep 2013. The final part of Table IIA2-5 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 2012 for the 10-city composite was 3.3 percent. 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. 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 2012 was 2.8 percent while the rate of the 20-city composite was 2.3 percent.

Table VA-5, US, Percentage Changes of Standard & Poor’s Case-Shiller Home Price Indices, Not Seasonally Adjusted, ∆%

	10-City Composite	20-City Composite
∆% Sep 2000 to Sep 2003	40.5	33.8
∆% Sep 2000 to Sep 2005	95.5	80.5
∆% Sep 2003 to Sep 2005	39.2	34.9
∆% Sep 2000 to Sep 2006	103.0	88.2
∆% Sep 2003 to Sep 2006	44.5	40.7
∆% Sep 2005 to Sep 2013	-16.9	-16.1
∆% Sep 2006 to Sep 2013	-20.0	-19.5
∆% Sep 2009 to Sep 2013	-8.1	-14.5
∆% Sep 2010 to Sep 2013	11.8	12.5
∆% Sep 2011 to Sep 2013	15.7	16.7
∆% Sep 2012 to Sep 2013	13.3	13.3
∆% Sep 2000 to Sep 2013	62.3	51.5
∆% Peak Jun 2006 Sep 2013	-20.4
∆% Peak Jul 2006 Sep 2013		-19.8
Average ∆% Dec 1987-Dec 2012	3.3	NA
Average ∆% Dec 1987-Dec 2000	3.8	NA
Average ∆% Dec 1992-Dec 2000	5.0	NA
Average ∆% Dec 2000-Dec 2012	2.8	2.3

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

Monthly house prices increased sharply from Feb to Sep 2013 for both the 10- and 20-city composites. In Sep 2013, the seasonally adjusted 10-city composite increased 0.9 percent and the 20-city 1.0 percent while the 10-city not seasonally adjusted increased 0.7 percent and the 20-city 0.7 percent. House prices increased at high monthly percentage rates from Feb to Sep 2013. With the exception of Feb through Apr 2012, house prices seasonally adjusted declined in every month for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table VA-6. 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. 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 VA-6, 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
Sep 2013	0.9	0.7	1.0	0.7
Aug	0.9	1.3	0.9	1.3
Jul	0.7	1.9	0.6	1.8
Jun	1.0	2.2	0.9	2.2
May	1.0	2.5	1.0	2.5
Apr	1.8	2.6	1.7	2.6
Mar	1.9	1.3	1.9	1.3
Feb	1.3	0.3	1.2	0.2
Jan	0.8	0.0	0.9	0.0
Dec 2012	1.0	0.2	1.0	0.2
Nov	0.6	-0.3	0.7	-0.2
Oct	0.7	-0.2	0.7	-0.1
Sep	0.4	0.3	0.6	0.3
Aug	0.4	0.8	0.4	0.9
Jul	0.3	1.5	0.3	1.6
Jun	0.9	2.1	1.0	2.3
May	0.8	2.2	0.9	2.4
Apr	0.6	1.4	0.6	1.4
Mar	0.5	-0.1	0.6	0.0
Feb	0.1	-0.9	0.1	-0.8
Jan	-0.3	-1.1	-0.2	-1.0
Dec 2011	-0.5	-1.2	-0.4	-1.1
Nov	-0.6	-1.4	-0.5	-1.3
Oct	-0.5	-1.3	-0.5	-1.3
Sep	-0.4	-0.6	-0.4	-0.7
Aug	-0.3	0.1	-0.4	0.1
Jul	-0.2	0.9	-0.2	1.0
Jun	-0.1	1.0	-0.1	1.2
May	-0.3	1.0	-0.3	1.0
Apr	-0.1	0.6	-0.2	0.6
Mar	-0.3	-1.0	-0.4	-1.0
Feb	-0.3	-1.3	-0.3	-1.2
Jan	-0.3	-1.1	-0.3	-1.1
Dec 2010	-0.2	-0.9	-0.2	-1.0

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

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 bank 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 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). 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.

Symmetric inflation targets are of secondary priority in favor of a self-imposed single jobs mandate of easing monetary policy even with the economy growing at or close to potential output. Monetary easing by unconventional measures, including zero interest rates and outright purchases of securities for the portfolio of the central bank, is now open ended in perpetuity, or QE→∞, as provided in the statement of the meeting of the Federal Open Market Committee (FOMC) on Sep 13, 2012 (http://www.federalreserve.gov/newsevents/press/monetary/20120913a.htm):

“To support a stronger economic recovery and to help ensure that inflation, over time, is at the rate most consistent with its dual mandate, the Committee agreed today to increase policy accommodation by purchasing additional agency mortgage-backed securities at a pace of $40 billion per month. The Committee also will continue through the end of the year its program to extend the average maturity of its holdings of securities as announced in June, and it 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. These actions, which together will increase the Committee’s holdings of longer-term securities by about $85 billion each month through the end of the year, should put downward pressure on longer-term interest rates, support mortgage markets, and help to make broader financial conditions more accommodative.

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 economic recovery strengthens.”

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.”

Unconventional monetary policy will remain in perpetuity, or QE→∞, changing to a “growth mandate.” 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 1.8 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 US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 17 quarters from IIIQ2009 to IIIQ2013. 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 http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf

http://bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_adv.pdf http://bea.gov/newsreleases/national/pi/2013/pdf/pi0613.pdf) and the first estimate of GDP for IIIQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_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 diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html). As a result, there are 28.9 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html). The US missed the opportunity of fast growth in the first four quarters of cyclical expansion when unemployment and underemployment are reduced. Zero interest rates and quantitative easing have not provided the impulse for growth and were not required in past successful cyclical expansions.

First, total nonfarm payroll employment seasonally adjusted (SA) increased 204,000 in Oct 2013 and private payroll employment rose 212,000. The average number of nonfarm jobs created in Jan-Oct 2012 was 172,700 while the average number of nonfarm jobs created in Jan-Sep 2013 was 186,300, or increase by 7.9 percent. The average number of private jobs created in the US in Jan-Oct 2012 was 178,900 while the average in Jan-Sep 2013 was 187,500, or increase by 4.8 percent. The US labor force increased from 153.617 million in 2011 to 154.975 million in 2012 by 1.358 million or 113,167 per month. The average increase of nonfarm jobs in the ten months from Jan to Oct 2013 was 186,300, which is a rate of job creation inadequate to reduce significantly unemployment and underemployment in the United States because of 113,167 new entrants in the labor force per month with 28.9 million unemployed or underemployed. The difference between the average increase of 186,300 new private nonfarm jobs per month in the US from Jan to Oct 2013 and the 113,167 average monthly increase in the labor force from 2011 to 2012 is 73,133 monthly new jobs net of absorption of new entrants in the labor force. There are 28.9 million in job stress in the US currently. Creation of 73,133 new jobs per month net of absorption of new entrants in the labor force would require 396 months to provide jobs for the unemployed and underemployed (28.942 million divided by 73,133) or 33 years (396 divided by 12). The civilian labor force of the US in Oct 2013 not seasonally adjusted stood at 155.918 million with 10.773 million unemployed or effectively 18.959 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 163.104 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 1.1 years (1 million divided by product of 73.133 by 12, which is 877,596). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.746 million (0.05 times labor force of 154.918 million) for new net job creation of 3.027 million (10.773 million unemployed minus 7.746 million unemployed at rate of 5 percent) that at the current rate would take 3.4 years (3.027 million divided by 0.877596). Under the calculation in this blog, there are 18.959 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 163.104 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 10.164 million jobs net of labor force growth that at the current rate would take 12.3 years (18.959 million minus 0.05(163.104 million) = 10.804 million divided by 0.877596, 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 Oct 2013 was 144.144 million (NSA) or 3.171 million fewer people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population increased from 231.958 million in Jul 2007 to 246.381 million in Oct 2013 or by 14.423 million. The number employed fell 2.2 percent from Jul 2007 to Oct 2013 while population increased 6.2 percent. 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. The United States economy has grown at the average yearly rate of 3 percent per year and 2 percent per year in per capita terms from 1870 to 2010, as measured by Lucas (2011May). An important characteristic of the economic cycle in the US has been rapid growth in the initial phase of expansion after recessions. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design.

Second, 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 http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf

The economy of the US can be summarized in growth of economic activity or GDP as decelerating from mediocre growth of 2.5 percent on an annual basis in 2010 to 1.8 percent in 2011 to 2.8 percent in 2012. The following calculations show that actual growth is around 2.0 to 2.2 percent per year. This rate 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 http://bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_adv.pdf http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_2nd.pdf http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_3rd.pdf http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0713.pdf http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0813.pdf http://bea.gov/newsreleases/national/pi/2013/pdf/pi0613.pdf http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf) provide important information on long-term growth and cyclical behavior. Table Summary provides relevant data.

Long-term. US GDP grew at the average yearly rate of 3.3 percent from 1929 to 2012 and at 3.2 percent from 1947 to 2012. There were periodic contractions or recessions in this period but the economy grew at faster rates in the subsequent expansions, maintaining long-term economic growth at trend.
Cycles. The combined contraction of GDP in the two almost consecutive recessions in the early 1980s is 4.7 percent. The contraction of US GDP from IVQ2007 to IIQ2009 during the global recession was 4.3 percent. The critical difference in the expansion is growth at average 7.8 percent in annual equivalent in the first four quarters of recovery from IQ1983 to IVQ1983. The average rate of growth of GDP in four cyclical expansions in the postwar period is 7.7 percent. In contrast, the rate of growth in the first four quarters from IIIQ2009 to IIQ2010 was only 2.7 percent. Average annual equivalent growth in the expansion from IQ1983 to IQ1986 was 5.7 percent. In contrast, average annual equivalent growth in the expansion from IIIQ2009 to IIIQ2013 was only 2.3 percent. The US appears to have lost its dynamism of income growth and employment creation.

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

	GDP
Long-Term
1929-2012	3.3
1947-2012	3.2
Cyclical Contractions ∆%
IQ1980 to IIIQ1980, IIIQ1981 to IVQ1982	-4.7
IVQ2007 to IIQ2009	-4.3
Cyclical Expansions Average Annual Equivalent ∆%
IQ1983 to IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987	5.7 5.4 5.2 5.0
First Four Quarters IQ1983 to IVQ1983	7.8
IIIQ2009 to IIIQ2013	2.3
First Four Quarters IIIQ2009 to IIQ2010	2.7
	Real Disposable Income	Real Disposable Income per Capita
Long-Term
1929-2012	3.2	2.0
1947-1999	3.7	2.3
Whole Cycles
1980-1989	3.5	2.6
2006-2012	1.4	0.6

Source: Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_3rd.pdf http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0813.pdf

http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf

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 http://bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_adv.pdf http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_2nd.pdf http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_3rd.pdf http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0713.pdf http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0813.pdf http://bea.gov/newsreleases/national/pi/2013/pdf/pi0613.pdf http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf) also provide critical information in assessing the current rhythm of US economic growth. The economy appears to be moving at a pace from 2.0 to 2.2 percent per year. Table Summary GDP provides the data.

1. Average Annual Growth in the Past Six Quarters. GDP growth in the four quarters of 2012 and the first three quarters of 2013 accumulated to 3.6 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IIIQ2013 of $15,790.1 by GDP in IVQ2011 of $15,242.1 and compounding by 4/7: {[($15,790.1/$15,242.1)^4/6 -1]100 = 2.0.

2. Average Annual Growth in the First Three Quarters of 2013. GDP growth in the first three quarters of 2013 accumulated to 1.6 percent that is equivalent to 2.2 percent in a year. This is obtained by dividing GDP in IIIQ2013 of $15,790.1 by GDP in IVQ2012 of $15,539.6 and compounding by 4/3: {[($15,790.1/$15,539.6)^4/3 -1]100 = 2.2%}. The US economy grew 1.6 percent in IIIQ2013 relative to the same quarter a year earlier in IIIQ2012. Another important revelation of the revisions and enhancements is that GDP was flat in IVQ2012, which is just at the borderline of contraction.

Table Summary GDP, US, Real GDP and Percentage Change Relative to IVQ2007 and Prior Quarter, Billions Chained 2005 Dollars and ∆%

	Real GDP, Billions Chained 2009 Dollars	∆% Relative to IVQ2007	∆% Relative to Prior Quarter	∆% over Year Earlier
IVQ2007	14,996.1	NA	NA	1.9
IVQ2011	15,242.1	1.6	1.2	2.0
IQ2012	15,381.6	2.6	0.9	3.3
IIQ2012	15,427.7	2.9	0.3	2.8
IIIQ2012	15,534.0	3.6	0.7	3.1
IVQ2012	15,539.6	3.6	0.0	2.0
IQ2013	15,583.9	3.9	0.3	1.3
IIQ2013	15,679.7	4.6	0.6	1.6
IIIQ2013	15,790.1	5.3	0.7	1.6
Cumulative ∆% IQ2012 to IIIQ2013	2.9		3.6
Annual Equivalent ∆%	1.9		2.0

Source: US Bureau of Economic Analysis

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

http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf

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→∞ cannot be abandoned because of the fear of rising interest rates. 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.

(1 + i_r) = (1 + i_n)/(1 + π^e) (1)

That is, the nominal interest rate equals the real interest rate discounted by the expectation of inflation in time term of the interest rate. Fisher (1933) analyzed the devastating effect of deflation on debts. Nominal debt contracts remained at original principal interest but net worth and income of debtors contracted during deflation. Real interest rates increase during declining inflation. For example, if the interest rate is 3 percent and prices decline 0.2 percent, equation (1) calculates the real interest rate as:

(1 +0.03)/(1 – 0.02) = 1.03/(0.998) = 1.032

(1 + 0.00114)/(1 + 0.011) = (1 + r_r) = 0.9902

Friedman (1953) analyzed the effects of full-employment economic policy on economic stability. There are two critical issues. First, there are lags in effect of monetary policy on aggregate income and prices (Friedman 1961, Culbertson 1960, 1961, Batini and Nelson 2002, Romer and Romer 2004). 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. Second, concrete knowledge on the functioning of the economy is inadequate. The result of shocking the economy with policies at the wrong time could be an increase in instability. 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/search?q=rules+versus+authorities).

Carry trades from zero interest rates to highly leveraged exposures in risk financial assets characterize the current environment. Some analytical aspects of the carry trade are instructive (Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 101-5, Pelaez and Pelaez, Globalization and the State, Vol. II (2008b), 202-4), Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008c), 70-4). Consider the following symbols: R_t is the exchange rate of a country receiving carry trade denoted in units of domestic currency per dollars at time t of initiation of the carry trade; R_t₊_τ is the exchange of the country receiving carry trade denoted in units of domestic currency per dollars at time t+τ when the carry trade is unwound; i_f is the domestic interest rate of the high-yielding country where investment will be made; i_usd is the interest rate on short-term dollar debt assumed to be 0.5 percent per year; i_f >i_usd, which expresses the fact that the interest rate on the foreign country is much higher than that in short-term USD (US dollars); S_t is the dollar value of the investment principal; and π is the dollar profit from the carry trade. The investment of the principal S_t in the local currency debt of the foreign country provides a profit of:

π = (1 + i_f)(R_tS_t)(1/R_t₊_τ) – (1 + i_usd)S_t (2)

The profit from the carry trade, π, is nonnegative when:

(1 + i_f)/ (1 + i_usd) ≥ R_t₊_τ/R_t (3)

In words, the difference in interest rate differentials, left-hand side of inequality (3), must exceed the percentage devaluation of the currency of the host country of the carry trade, right hand side of inequality (3). The carry trade must earn enough in the host-country interest rate to compensate for depreciation of the host-country at the time of return to USD. A simple example explains the vulnerability of the carry trade in fixed-income. Let i_f be 0.10 (10 percent), i_usd 0.005 (0.5 percent), S_t USD100 and R_t CUR 1.00/USD. Adopt the fixed-income rule of months of 30 days and years of 360 days. Consider a strategy of investing USD 100 at 10 percent for 30 days with borrowing of USD 100 at 0.5 percent for 30 days. At time t, the USD 100 are converted into CUR 100 and invested at [(30/360)10] equal to 0.833 percent for thirty days. At the end of the 30 days, assume that the rate R_t₊₃₀ is still CUR 1/USD such that the return amount from the carry trade is USD 0.833. There is still a loan to be paid [(0.005)(30/360)USD100] equal to USD 0.042. The investor receives the net amount of USD 0.833 minus USD 0.042 or US 0.791. The rate of return on the investment of the USD 100 is 0.791 percent, which is equivalent to the annual rate of return of 9.49 percent {(0.791)(360/30)}. This is incomparably better than earning 0.5 percent. There are alternatives of hedging by buying forward the exchange for conversion back into USD.

What really matters in the statement of the Federal Open Market Committee (FOMC) on Oct 30, 2013, is interest rates of fed funds at 0 to ¼ percent for the foreseeable future, even with paring of purchases of longer term bonds for the portfolio of the Fed (http://www.federalreserve.gov/newsevents/press/monetary/20131030a.htm):

“To support continued progress toward maximum employment and price stability, the Committee today reaffirmed its view 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. In determining how long to maintain a highly accommodative stance of monetary policy, the Committee will also consider other information, including additional measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial developments. When the Committee decides to begin to remove policy accommodation, it will take a balanced approach consistent with its longer-run goals of maximum employment and inflation of 2 percent.”

Another critical concern in an earlier statement of the FOMC on Sep 18, 2013, is on the effects of tapering expectations on interest rates (http://www.federalreserve.gov/newsevents/press/monetary/20130918a.htm):

“Household spending and business fixed investment advanced, and the housing sector has been strengthening, but mortgage rates have risen further and fiscal policy is restraining economic growth” (emphasis added).

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:

clip_image004[1]

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

clip_image004[1]

declines.

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. Monetary policy is constrained in a QE∞ trap with all adverse effects of financial repression and resource misallocation because an increase in interest rates causes contraction of wealth, which in the United States is concentrated in home ownership and stocks in own investment portfolios and pension funds that decline during interest rate increases.

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. Personal consumptions expenditures have share of 68.6 percent of GDP in IIQ2013 (Table I-10 http://cmpassocregulationblog.blogspot.com/2013/09/increasing-interest-rate-risk.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.

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 Oct 2012 and Oct 2013. Total assets of US commercial banks grew 7.6 percent from $12,861.3 billion in Oct 2012 to $13,832.9 billion in Oct 2013. US GDP in IIIQ2013 is estimated at $16,857.6 billion (http://www.bea.gov/iTable/index_nipa.cfm). Thus, total assets of US commercial banks are equivalent to around 82 percent of US GDP. Bank credit grew 1.9 percent from $9852.7 billion in Oct 2012 to $10,036.9 billion in Oct 2013. Securities in bank credit declined 0.1 percent from $2682.7 billion in Oct 2012 to $2679.4 billion in Oct 2013. A large part of securities in banking credit consists of US Treasury and agency securities, falling 3.6 percent from $1840.8 billion in Oct 2012 to $1774.2 billion in Oct 2013. Credit to the government that issues or backs Treasury and agency securities of $1774.2 billion in Oct 2013 is about 17.7 percent of total bank credit of US commercial banks of $10,036.9 billion. Mortgage-backed securities, providing financing of home loans, fell 1.4 percent, from $1330.3 billion in Oct 2012 to $1312.1 billion in Oct 2013. Loans and leases are relatively more dynamic, growing 2.6 percent from $7170.0 billion in Oct 2012 to $7357.5 billion in Oct 2013. The only dynamic class is commercial and industrial loans, growing 8.0 percent from Oct 2012 to Oct 2013 and providing $1589.5 billion or 21.6 percent of total loans and leases of $7357.5 billion in Oct 2013. Real estate loans decreased 0.3 percent, providing $3514.8 billion in Oct 2013 or 47.8 percent of total loans and leases. Consumer loans increased 3.3 percent, providing $1146.7 billion in Oct 2013 or 15.6 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” (http://www.federalreserve.gov/releases/h8/current/default.htm). Cash assets in US commercial banks increased 57.5 percent from $1581.2 billion in Oct 2012 to $2490.9 billion in Oct 2013 but a single year of the series masks exploding cash in banks because of unconventional monetary policy, which is discussed below. Bank deposits increased 7.4 percent from $8988.4 billion to $9656.5 billion. The difference between bank deposits and total loans and leases in banks increased from $1818.4 billion in Oct 2012 to $2299.0 billion in Oct 2013 or by $480.6 billion. Securities in bank credit decreased by -$3.3 billion from $2682.7 billion in Oct 2012 to $2679.4 billion in Oct 2013 and Treasury and agency securities decreased by $66.6 billion from $1840.8 billion in Oct 2012 to $1774.2 billion in Oct 2013. Loans and leases increased $187.5 billion from $7170.0 billion in Oct 2012 to $7357.5 billion in Oct 2013. 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 with real disposable income per capita in IIQ2013 higher by only 2.4 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) in contrast with 12.1 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, growth of real disposable income grew cumulatively 16.4 percent in the cycle from IQ1980 to IIIQ1986 that was higher than trend growth of 14.9 percent.

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

	Oct 2012	Oct 2013	∆%
Total Assets	12,861.3	13,832.9	7.6
Bank Credit	9852.7	10,036.9	1.9
Securities in Bank Credit	2682.7	2679.4	-0.1
Treasury & Agency Securities	1840.8	1774.2	-3.6
Mortgage-Backed Securities	1330.3	1312.1	-1.4
Loans & Leases	7170.0	7357.5	2.6
Real Estate Loans	3524.9	3514.8	-0.3
Consumer Loans	1109.7	1146.7	3.3
Commercial & Industrial Loans	1472.4	1589.5	8.0
Other Loans & Leases	1063.0	1106.4	4.1
Cash Assets*	1581.2	2490.9	57.5
Total Liabilities	11,362.2	12,327.1	8.5
Deposits	8988.4	9656.5	7.4

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

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

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

	2008	2009	2010	2011	2012	Sep 2013	Oct 2013
Total Assets	7.9	-6.0	-2.7	5.4	2.5	7.7	10.2
Bank Credit	2.1	-6.6	-2.7	1.8	4.0	-1.3	3.3
Securities in Bank Credit	-1.8	6.6	6.9	1.8	7.5	-8.7	2.8
Treasury & Agency Securities	2.6	13.5	15.2	3.1	8.6	-7.2	1.0
Other Securities	-7.5	-3.2	-7.1	-0.7	5.1	-11.6	6.3
Loans & Leases	3.2	-10.2	-5.8	1.8	2.7	1.4	3.4
Real Estate Loans	-0.2	-5.7	-5.5	-3.8	-1.1	-0.9	-2.7
Consumer Loans	5.1	-3.3	-7.1	-0.7	1.2	2.4	5.2
Commercial & Industrial Loans	12.8	-18.5	-9.0	9.0	11.3	3.3	11.7
Other Loans & Leases	1.7	-23.1	0.4	19.8	6.6	5.0	9.5
Cash Assets	160.2	49.0	-7.8	48.3	-2.1	59.9	59.9
Total Liabilities	10.6	-7.1	-3.4	5.5	2.3	8.7	6.8
Deposits	5.4	5.2	2.4	6.7	7.2	8.0	9.2

Source: Board of Governors of the Federal Reserve System

http://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 2013. Unconventional monetary policy caused an increase in cash assets in late 2008 of close to 500 percent at SAAR and also in following policy impulses. Such aggressive policies were not required for growth of GDP at the average rate of 5.2 percent in 16 quarters of cyclical expansion from IQ1983 to IIIQ1986 while the average rate in 16 quarters of cyclical expansion from IIIQ2009 to IIIQ2013 has been at the rate of 2.3 percent (http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.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 4.3 percent from IVQ2007 to IIQ2009. 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. US GDP in 2012 is estimated at $16,244.6 billion, such that the bailout would be equivalent to cost to taxpayers of about $430.5 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, 1973-2013, ∆%

Source: Board of Governors of the Federal Reserve System

http://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 1973 to 2013. 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, 1947-2013, ∆%

Source: Board of Governors of the Federal Reserve System

http://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 2013. Deposits fell sharp 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, 1973-2013, ∆%

Source: Board of Governors of the Federal Reserve System

http://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 1973 to 2013. 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, 1947-2013, ∆%

Source: Board of Governors of the Federal Reserve System

http://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 1973 to 2013. 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 5.2 percent per year on average in the cyclical expansion of the 1980s in contrast with lower demand during tepid economic growth at 2.3 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, 1947-2013, ∆%

Source: Board of Governors of the Federal Reserve System

http://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 in the midst of 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, 1947-2013, ∆%

Source: Board of Governors of the Federal Reserve System

http://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 and have increased at very low magnitudes during the current cyclical expansion.

Chart I-7, US, Consumer Loans in Bank Credit, Commercial Banks, Seasonally Adjusted Annual Rate, Monthly, 1958-2013, ∆%

Source: Board of Governors of the Federal Reserve System

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

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 then returns to trend. 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 or what is earned per person 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 I-3 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 http://bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_adv.pdf http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_2^nd.pdf http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_3^rd.pdf http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0713.pdf http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0813.pdf http://bea.gov/newsreleases/national/pi/2013/pdf/pi0613.pdf) provide important information on long-term growth and cyclical behavior. First, Long-term performance. Using annual data, US GDP grew at the average rate of 3.3 percent per year from 1929 to 2012 and at 3.2 percent per year from 1947 to 2012. Real disposable income grew at the average yearly rate of 3.2 percent from 1929 to 2013 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 2012 and at 2.3 percent from 1947 to 1999. US economic growth was much faster during expansions, compensating for the contraction 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 1980 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 1.4 percent from 2006 to 2012 and real disposable income per capita at 0.6 percent. 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 1.4 percent and real disposable income per capita 0.8 percent. Third, first 16 quarters of expansion. In the expansion from IQ1983 to IIIQ1986: GDP grew 22.3 percent at the annual equivalent rate of 5.2 percent; real disposable income grew 17.3 percent at the annual equivalent rate of 4.1 percent; and real disposable income per capita grew 13.7 percent at the annual equivalent rate of 3.3 percent. In the expansion from IIIQ2009 to IIQ2013: GDP grew 9.0 percent at the annual equivalent rate of 2.2 percent; real disposable income grew 6.4 percent at the annual equivalent rate of 1.6 percent; and real disposable personal income per capita grew 3.5 percent at the annual equivalent rate of 0.9 percent. Fourth, entire quarterly cycle. In the entire cycle combining contraction and expansion from IQ1980 to IIIQ1986: GDP grew 21.1 percent at the annual equivalent rate of 2.8 percent; real disposable personal income 24.7 percent at the annual equivalent rate of 3.2 percent; and real disposable personal income per capita 17.4 percent at the annual equivalent rate of 2.3 percent. In the entire cycle combining contraction and expansion from IVQ2007 to IIQ2013: GDP grew 4.4 percent at the annual equivalent rate of 0.7 percent; real disposable personal income 6.9 percent at the annual equivalent rate of 1.2 percent; and real disposable personal income per capita 2.4 percent at the annual equivalent rate of 0.4 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 strong 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 4.3 percent from IVQ2007 to IIQ2009 and the financial crisis.

Table I-3, US, GDP, Real Disposable Personal Income, Real Disposable Income per Capita and Population in 1983-85 and 2007-2013, %

Long-term GDP	Average ∆% per Year
1929-2012	3.3
1947-2012	3.2
Long-term Average ∆% per Year	Real Disposable Income	Real Disposable Income per Capita
1929-2012	3.2	2.0
1947-1999	3.7	2.3
Whole Cycles Average ∆% per Year
1980-1989	3.5	2.6
2006-2012	1.4	0.6
Comparison of Cycles	# Quarters	∆%	∆% Annual Equivalent
IQ1983 to IVQ1986 IQ1983 to IIIQ1986	4 16
GDP IQ1983 to IVQ1983 IQ1983 to IIIQ1986	4 16	7.8 22.3	7.8 5.2
RDPI IQ1983 to IVQ1983 IQ1983 to IIIQ1986	4 16	5.3 17.3	5.3 4.1
RDPI Per Capita IQ1983 to IVQ1983 IQ1983 to IIIQ1986	4 16	4.4 13.7	4.4 3.3
Whole Cycle IQ1980 to IIIQ1986
GDP	28	21.1	2.8
RDPI	28	24.7	3.2
RDPI per Capita	28	17.4	2.3
Population	28	6.3	0.9
GDP First Four Quarters IIIQ2009 to IIQ2010 IIIQ2009 to IIQ2013	4 16	2.7 9.0	2.7 2.2
RDPI IIIQ2009 to IIQ2010 IIIQ2009 to IIQ2013	4 16	1.4 6.4	1.4 1.6
RDPI per Capita IIIQ2009 to IIQ2010 IIIQ2009 to IIQ2013	4 16	0.8 3.5	0.8 0.9
Population IIIQ2009 to IIQ2010 IIIQ2009 to IIQ2013	4 16	0.6 2.8	0.6 0.7
IVQ2007 to IIQ2013	23
GDP	23	4.4	0.7
RDPI	23	6.9	1.2
RDPI per Capita	23	2.4	0.4
Population	23	4.4	0.8

RDPI: Real Disposable Personal Income

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

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 2013. 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, 1973-2013, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

http://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 Nov 20, 2013. 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 IIC-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 Nov 27, 2013

Source: Board of Governors of the Federal Reserve System

http://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 2013. 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, 1973-2013, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

http://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 2013. 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.

Chart I-11, US, Treasury and Agency Securities in Bank Credit, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1947-2013, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

http://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 2013. Total loans and leases of US commercial banks contracted sharply and have stalled during the cyclical expansion.

Chart I-12, US, Loans and Leases in Bank Credit, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1947-2013, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

http://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 2013. 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 does lower yields of mortgage-backed securities there would not be proportionate reduction in mortgage rates and even less likely construction and sales of houses.

Chart I-13, US, Real Estate Loans in Bank Credit, Not Seasonally Adjusted, Monthly, 1947-2013, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

http://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 2013. Consumer loans even increased during the contraction then declined and increased vertically to decline again. There was high demand for reposition of durable goods that exhausted and limited consumption again with increase in savings rates in recent periods.

Chart I-14, US, Consumer Loans in Bank Credit, Not Seasonally Adjusted, US Commercial Banks, Monthly, 1947-2013, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

http://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 2013. 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 peak during the global recession.

Chart I-15, US, Commercial and Industrial Loans in Bank Credit, US Commercial Banks, Not Seasonally Adjusted, Monthly, 1947-2013, Billions of Dollars

Source: Board of Governors of the Federal Reserve System

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

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 media attention as those in large private banking institutions such as the teapot storm over JP Morgan Chase.

Source: Board of Governors of the Federal Reserve System

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

ID Theory and Reality of Economic History 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 strong 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 increases 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? Or 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.

The producer price index of the US from 1947 to 2013 in Chart I-17 shows various periods of more rapid or less rapid inflation but no bumps. The major event is the decline in 2008 when risk aversion because of the global recession caused the collapse of oil prices from $148/barrel to less than $80/barrel with most other commodity prices also collapsing. The event had nothing in common with explanations of deflation but rather with the concentration of risk exposures in commodities after the decline of stock market indexes. Eventually, there was a flight to government securities because of the fears of insolvency of banks caused by statements supporting proposals for withdrawal of toxic assets from bank balance sheets in the Troubled Asset Relief Program (TARP), as explained by Cochrane and Zingales (2009). The bump in 2008 with decline in 2009 is consistent with the view that zero interest rates with subdued risk aversion induce carry trades into commodity futures.

Chart I-17, US, Producer Price Index, Finished Goods, NSA, 1947-2013

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Chart I-18 provides 12-month percentage changes of the producer price index from 1948 to 2013. The distinguishing event in Chart I-7 is the Great Inflation of the 1970s. The shape of the two-hump Bactrian camel of the 1970s resembles the double hump from 2007 to 2013.

Chart I-18, US, Producer Price Index, Finished Goods, 12-Month Percentage Change, NSA, 1948-2013

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Annual percentage changes of the producer price index from 1948 to 2012 are shown in Table I-4. The producer price index fell 2.8 percent in 1949 following the adjustment to World War II and fell 0.6 percent in 1952 and 1.0 percent in 1953 around the Korean War. There are two other mild decline of 0.3 percent in 1959 and 0.3 percent in 1963. There are only few subsequent and isolated declines of the producer price index of 1.4 percent in 1986, 0.8 percent in 1998, 1.3 percent in 2002 and 2.6 percent in 2009. The decline of 2009 was caused by unwinding of carry trades in 2008 that had lifted oil prices to $140/barrel during deep global recession because of the panic of probable toxic assets in banks that would be removed with the Troubled Asset Relief Program (TARP) (Cochrane and Zingales 2009). There is no evidence in this history of 65 years of the US producer price index suggesting that there is frequent and persistent deflation shock requiring aggressive unconventional monetary policy. The design of such anti-deflation policy could provoke price and financial instability because of lags in effect of monetary policy, model errors, inaccurate forecasts and misleading analysis of current economic conditions.

Table I-4, US, Annual PPI Inflation ∆% 1948-2012

Year	Annual ∆%
1948	8.0
1949	-2.8
1950	1.8
1951	9.2
1952	-0.6
1953	-1.0
1954	0.3
1955	0.3
1956	2.6
1957	3.8
1958	2.2
1959	-0.3
1960	0.9
1961	0.0
1962	0.3
1963	-0.3
1964	0.3
1965	1.8
1966	3.2
1967	1.1
1968	2.8
1969	3.8
1970	3.4
1971	3.1
1972	3.2
1973	9.1
1974	15.4
1975	10.6
1976	4.5
1977	6.4
1978	7.9
1979	11.2
1980	13.4
1981	9.2
1982	4.1
1983	1.6
1984	2.1
1985	1.0
1986	-1.4
1987	2.1
1988	2.5
1989	5.2
1990	4.9
1991	2.1
1992	1.2
1993	1.2
1994	0.6
1995	1.9
1996	2.7
1997	0.4
1998	-0.8
1999	1.8
2000	3.8
2001	2.0
2002	-1.3
2003	3.2
2004	3.6
2005	4.8
2006	3.0
2007	3.9
2008	6.3
2009	-2.6
2010	4.2
2011	6.0
2012	1.9

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Chart I-19 provides the consumer price index NSA from 1914 to 2013. The dominating characteristic is the increase in slope during the Great Inflation from the middle of the 1960s through the 1970s. There is long-term inflation in the US and no evidence of deflation risks.

Chart I-19, US, Consumer Price Index, NSA, 1914-2013

Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Chart I-20 provides 12-month percentage changes of the consumer price index from 1914 to 2013. The only episode of deflation after 1950 is in 2009, which is explained by the reversal of speculative commodity futures carry trades that were induced by interest rates driven to zero in a shock of monetary policy in 2008. The only persistent case of deflation is from 1930 to 1933, which has little if any relevance to the contemporary United States economy. There are actually three waves of inflation in the second half of the 1960s, in the mid-1970s and again in the late 1970s. Inflation rates then stabilized in a range with only two episodes above 5 percent.

Chart I-20, US, Consumer Price Index, All Items, 12- Month Percentage Change 1914-2013

Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Table I-5 provides annual percentage changes of United States consumer price inflation from 1914 to 2013. There have been only cases of annual declines of the CPI after wars: (1) World War I minus 10.5 percent in 1921 and minus 6.1 percent in 1922 following cumulative increases of 83.5 percent in four years from 1917 to 1920 at the average of 16.4 percent per year; (2) World War II: minus 1.2 percent in 1949 following cumulative 33.9 percent in three years from 1946 to 1948 at average 10.2 percent per year (3) minus 0.4 percent in 1955 two years after the end of the Korean War; and (4) minus 0.4 percent in 2009. The decline of 0.4 percent in 2009 followed increase of 3.8 percent in 2008 and is explained by the reversal of speculative carry trades into commodity futures that were created in 2008 as monetary policy rates were driven to zero. The reversal occurred after misleading statement on toxic assets in banks in the proposal for TARP (Cochrane and Zingales 2009). There were declines of 1.7 percent in both 1927 and 1928 during the episode of revival of rules of the gold standard. The only persistent deflationary period since 1914 was during the Great Depression in the years from 1930 to 1933 and again in 1938-1939. Fear of deflation on the basis of that experience does not justify unconventional monetary policy of zero interest rates that has failed to stop deflation in Japan. Financial repression causes far more adverse effects on allocation of resources by distorting the calculus of risk/returns than alleged employment-creating effects or there would not be current recovery without jobs and hiring after zero interest rates since Dec 2008 and intended now forever in a self-imposed forecast growth and employment mandate of monetary policy.

Table I-5, US, Annual CPI Inflation ∆% 1914-2012

Year	Annual ∆%
1914	1.0
1915	1.0
1916	7.9
1917	17.4
1918	18.0
1919	14.6
1920	15.6
1921	-10.5
1922	-6.1
1923	1.8
1924	0.0
1925	2.3
1926	1.1
1927	-1.7
1928	-1.7
1929	0.0
1930	-2.3
1931	-9.0
1932	-9.9
1933	-5.1
1934	3.1
1935	2.2
1936	1.5
1937	3.6
1938	-2.1
1939	-1.4
1940	0.7
1941	5.0
1942	10.9
1943	6.1
1944	1.7
1945	2.3
1946	8.3
1947	14.4
1948	8.1
1949	-1.2
1950	1.3
1951	7.9
1952	1.9
1953	0.8
1954	0.7
1955	-0.4
1956	1.5
1957	3.3
1958	2.8
1959	0.7
1960	1.7
1961	1.0
1962	1.0
1963	1.3
1964	1.3
1965	1.6
1966	2.9
1967	3.1
1968	4.2
1969	5.5
1970	5.7
1971	4.4
1972	3.2
1973	6.2
1974	11.0
1975	9.1
1976	5.8
1977	6.5
1978	7.6
1979	11.3
1980	13.5
1981	10.3
1982	6.2
1983	3.2
1984	4.3
1985	3.6
1986	1.9
1987	3.6
1988	4.1
1989	4.8
1990	5.4
1991	4.2
1992	3.0
1993	3.0
1994	2.6
1995	2.8
1996	3.0
1997	2.3
1998	1.6
1999	2.2
2000	3.4
2001	2.8
2002	1.6
2003	2.3
2004	2.7
2005	3.4
2006	3.2
2007	2.8
2008	3.8
2009	-0.4
2010	1.6
2011	3.2
2012	2.1

Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

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.”

The experience of the United Kingdom with deflation and economic growth is relevant and rich. Table I-6 provides 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 I-6 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 I-6, 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.

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 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.”

Seasonally adjusted annual rates (SAAR) of housing starts and permits are shown in Table II-1. Data for starts are only available until Aug 2013 while data for permits are available until Oct 2013. Housing starts decreased 0.9 percent in Aug 2013 after increasing 6.7 percent in Jul 2013 and decreasing 9.1 percent in Jun 2013. Housing permits, indicating future activity, increased 6.2 percent in Oct 2013 after increasing 5.2 percent in Sep 2013 and decreasing 2.9 percent in Aug 2013. While single unit houses starts increased 5.6 percent in Aug 2013, seasonally adjusted, structures with five units or more decreased 11.9 percent. Multifamily residential construction is increasing at a faster rate than single-family construction. Monthly rates in starts and permits fluctuate significantly as shown in Table II-1.

Table II-1, US, Housing Starts and Permits SSAR Month ∆%

	Housing Starts SAAR	Month ∆%	Housing Permits SAAR	Month ∆%
Oct 2013	NA	NA	1034	6.2
Sep	NA	NA	974	5.2
Aug	883	-0.9	926	-2.9
Jul	891	6.7	954	3.9
Jun	835	-9.1	918	-6.8
May	919	7.9	985	-2.0
Apr	852	-15.2	1005	12.9
Mar	1005	3.7	890	-6.5
Feb	969	7.9	952	4.0
Jan	898	-8.6	915	-3.0
Dec 2012	983	16.7	943	1.1
Nov	842	-2.5	933	2.8
Oct	864	1.2	908	-1.4
Sep	854	14.0	921	11.4
Aug	749	1.1	827	-1.4
Jul	741	-2.1	839	6.9
Jun	757	6.5	785	-2.6
May	711	-5.7	806	7.6
Apr	754	6.6	749	-4.6
Mar	707	-0.8	785	6.2
Feb	713	-1.4	739	3.5
Jan	723	4.2	714	2.4
Dec 2011	694	-2.4	697	-1.3
Nov	711	16.6	706	5.2
Oct	610	-6.2	671	10.0
Sep	650	11.1	610	-5.7
Aug	585	-6.1	647	4.2
Jul	623	2.5	621	-2.4
Jun	608	8.4	636	2.9
May	561	1.3	618	6.4
Apr	554	-7.7	581	-0.3
Mar	600	16.1	583	7.6
Feb	517	-17.9	542	-5.9
Jan	630	16.9	576	-8.9
Dec 2010	539	-1.1	632	12.9
Nov	545	0.4	560	0.4
Oct	543	-8.6	558	-0.9
Sep	594	-0.8	563	-2.9

SAAR: Seasonally Adjusted Annual Rate

Source: US Census Bureau

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

Table II-2, US, Housing Starts and New Permits, Thousands of Units, NSA, and %

	Housing Starts*	New Permits
Jan-Oct 2013	616.7	823.4
Jan-Oct 2012	502.4	685.8
∆% Jan-Oct 2013/Jan-Oct 2012	22.8	20.1
Jan-Oct 2006	1,292.5	1,616.0
∆% Jan-Oct 2013/Jan-Oct 2006	-52.3	-49.0
Jan-Oct 2005	1,403.2	1,841.7
∆% Jan-Oct 2013/Jan-Oct 2005	-56.1	-55.3

*Jan-Aug

Source: US Census Bureau http://www.census.gov/construction/nrc/

Chart II-1, US, Total and Single-Family New Housing Units Started in the US, SAAR (Seasonally Adjusted Annual Rate)

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr020.html

Table II-4, US, New Housing United Started at Seasonally Adjusted Rates, Thousand Units

	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug
2000	1,636	1,737	1,604	1,626	1,575	1,559	1,463	1,541
2001	1,600	1,625	1,590	1,649	1,605	1,636	1,670	1,567
2002	1,698	1,829	1,642	1,592	1,764	1,717	1,655	1,633
2003	1,853	1,629	1,726	1,643	1,751	1,867	1,897	1,833
2004	1,911	1,846	1,998	2,003	1,981	1,828	2,002	2,024
2005	2,144	2,207	1,864	2,061	2,025	2,068	2,054	2,095
2006	2,273	2,119	1,969	1,821	1,942	1,802	1,737	1,650
2007	1,409	1,480	1,495	1,490	1,415	1,448	1,354	1,330
2008	1,084	1,103	1,005	1,013	973	1,046	923	844
2009	490	582	505	478	540	585	594	586
2010	614	604	636	687	583	536	546	599
2011	630	517	600	554	561	608	623	585
2012	723	713	707	754	711	757	741	749
2013	898	969	1,005	852	919	835	891	883

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr020.html

Chart II-2, US, New Housing Units Started in the US, SAAR (Seasonally Adjusted Annual Rate), Thousands of Units, Jan 1959-Aug 2013

Source: US Census Bureau http://www.census.gov/construction/nrc/

Table II-5, New Housing Units Started in the US, Not Seasonally Adjusted, Thousands of Units

	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug
2000	104.0	119.7	133.4	149.5	152.9	146.3	135.0	141.4
2001	106.4	108.2	133.2	151.3	154.0	155.2	154.6	141.5
2002	110.4	120.4	138.2	148.8	165.5	160.3	155.9	147.0
2003	117.8	109.7	147.2	151.2	165.0	174.5	175.8	163.8
2004	124.5	126.4	173.8	179.5	187.6	172.3	182.0	185.9
2005	142.9	149.1	156.2	184.6	197.9	192.8	187.6	192.0
2006	153.0	145.1	165.9	160.5	190.2	170.2	160.9	146.8
2007	95.0	103.1	123.8	135.6	136.5	137.8	127.9	121.2
2008	70.8	78.4	82.2	89.5	91.7	102.5	86.7	76.4
2009	31.9	39.8	42.7	42.5	52.2	59.1	56.8	52.9
2010	38.9	40.7	54.7	62.0	56.2	53.8	51.5	56.3
2011	40.2	35.4	49.9	49.0	54.0	60.5	57.6	54.5
2012	47.2	49.7	58.0	66.8	67.8	74.7	69.2	69.0
2013	58.7	66.1	83.3	76.3	87.2	80.7	84.0	80.4

Source: US Census Bureau http://www.census.gov/construction/nrc/

Chart II-3, US, New Housing Units Started in the US, Not Seasonally Adjusted, Thousands of Units, Jan 1959-Aug 2013

Source: US Census Bureau http://www.census.gov/construction/nrc/

Chart II-4 of the US Census Bureau provides single-family houses started without seasonal adjustment. There was sharp increase from 1992 to 2007 followed by sharp decline. The recovery is sluggish.

Chart II-4, US, Single-family Houses Started, Thousands of Units, NSA

Source: US Census Bureau http://www.census.gov/construction/nrc

Chart II-5, US, Housing Units Stated in Buildings with Five Units or More, Thousands of Units

Source: US Census Bureau http://www.census.gov/construction/nrc/

Table II-6, US, Annual New Privately Owned Housing Units Authorized by Building Permits in Permit-Issuing Places and New Privately Owned Housing Units Started, Thousands

	Starts	Permits
2012	780.6	829.7
∆% 2012/2011	28.2	32.9
∆% 2012/2010	33.0	37.2
∆% 2012/2005	-62.3	-61.5
∆% 2012/2000	-50.2	-47.9
∆% 2012/Av 1959-1963	-45.4	-28.4
2011	608.8	624.1
∆% 2011/2005	-70.6	-71.0
∆% 2011/2000	-61.2	-60.8
∆% 2011/Av 1959-1963	-57.4	-46.1
2010	586.9	604.6
2009	554.0	583.0
2008	905.5	905.4
2007	1,355,0	1,398.4
2006	1,800.9	1,838.9
2005	2,068.3	2,155.3
∆% 2005/2000	31.8	35.4
2004	1,955.8	2,070.1
2003	1,847.7	1,889.2
2002	1,704.9	1,747.7
2001	1,602.7	1,636.7
2000	1,568.7	1,592.3
∆% 2000/1990	31.5	43.3
1990	1,192,7	1,110.8
1980	1,292.2	1,190.6
1970	1,433.6	1,351.5
Average 1959-63	1,429.7	1,158.2

Source: US Census Bureau http://www.census.gov/construction/nrc/

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 IIIQ2000 to IIIQ2006, the index for the US as a whole rose 57.4 percent, with 68.4 percent for New England, 75.5 percent for Middle Atlantic, 72.1 percent for South Atlantic but only by 32.6 percent for East South Central. Prices fell relative to 2013 for all years from 2005 and from 2006. Prices for the US increased 8.5 percent in IIIQ2013 relative to IIIQ2012 and 12.9 percent from IIIQ2011 to IIIQ2013. From IIIQ2000 to IIIQ2013, 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
IIIQ2000 to IIIQ2003	23.5	40.4	35.3	25.1	10.7
IIIQ2000 to IIIQ2005	50.2	69.5	68.7	60.8	23.7
IIIQ2000 to IIIQ2006	57.4	68.4	75.5	72.1	32.5
IIIQ2005 t0 IIIQ2013	-3.9	-9.7	-1.9	-9.0	7.2
IIIQ2006 to IIIQ2013	-8.3	-9.2	-5.8	-15.0	0.1
IIIQ2007 to IIIQ2013	-8.1	-7.6	-6.6	-14.8	-3.1
IIIQ2011 to IIIQ2013	12.9	5.0	3.5	13.9	6.9
IIIQ2012 to IIIQ2013	8.5	5.0	3.8	8.7	4.8
IIIQ2000 to IIIQ2013	44.3	53.0	65.4	46.3	32.6

Source: Federal Housing Finance Agency

http://fhfa.gov/Default.aspx?Page=14

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 2013 with exception of South 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
IIIQ2000 to IIIQ2003	11.6	18.4	14.5	18.4	42.5
IIIQ2000 to IIIQ2005	22.9	31.3	24.4	55.3	109.5
IIIQ2000 to IIIQ2006	31.4	35.8	26.0	69.3	118.0
IIIQ2005 to IIIQ2013	21.7	3.0	-7.8	-5.3	-19.3
IIIQ2006 to IIIQ2013	13.8	-0.4	-8.9	-13.1	-22.5
IIIQ2007 to IIIQ2013	8.6	-1.3	-7.1	-14.1	-18
IIIQ2011 to IIIQ2013	11.5	9.5	9.2	24.0	26.7
IIIQ2012 to IIIQ2013	6.0	6.1	6.3	12.3	19.2
IIIQ2000 to IIIQ2013	49.5	35.2	14.6	47.0	69.2

Source: Federal Housing Finance Agency

http://fhfa.gov/Default.aspx?Page=14

Chart IIA2-1 of the Federal Housing Finance Agency shows the Housing Price Index four-quarter price change from IIIQ2003 to IIIQ2013. House prices appreciated sharply from 1998 to 2005 and then fell rapidly. Recovery began already after IIQ2008 but there was another decline after IIIQ2010. The rate of decline improved in the second half of 2011 and into 2012 with movement into positive territory in successive quarter from IIQ2012 to IIIQ2013.

Chart IIA2-1, US, Federal Housing Finance Agency House Price Index Four Quarter Price Change

Source: Federal Housing Finance Agency

http://fhfa.gov/Default.aspx?Page=14

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

	Month ∆% SA	12 Month ∆% NSA
Sep 2013	0.3	8.5
Aug	0.4	8.5
Jul	0.7	8.7
Jun	0.7	8.0
May	0.9	7.7
Apr	0.5	7.3
Mar	1.4	7.6
Feb	0.9	7.0
Jan	0.6	6.6
Dec 2012	0.5	5.7
Nov	0.6	5.7
Oct	0.7	5.6
Sep	0.3	4.3
Aug	0.5	4.5
Jul	0.1	3.8
Jun	0.5	3.9
May	0.6	3.8
Apr	0.8	3.0
Mar	0.9	2.3
Feb	0.5	0.4
Jan	-0.3	-1.0
Dec 2011	0.4	-1.2
Nov 2011	0.5	-2.2
Oct 2011	-0.6	-3.1
Sep 2011	0.4	-2.3
Aug 2011	-0.2	-3.7
Jul 2011	0.2	-3.5
Jun 2011	0.4	-4.4
May 2011	-0.1	-5.9
Apr 2011	0.2	-5.8
Mar 2011	-0.9	-5.9
Feb 2011	-1.0	-5.1
Jan 2011	-0.5	-4.6
Dec 2010		-3.8
Dec 2009		-2.0
Dec 2008		-9.9
Dec 2007		-3.1
Dec 2006		2.5
Dec 2005		9.8
Dec 2004		10.2
Dec 2003		8.0
Dec 2002		7.8
Dec 2001		6.7
Dec 2000		7.2
Dec 1999		6.2
Dec 1998		5.9
Dec 1997		3.4
Dec 1996		2.8
Dec 1995		3.0
Dec 1994		2.6
Dec 1993		3.1
Dec 1992		2.4

Source: Federal Housing Finance Agency

http://fhfa.gov/Default.aspx?Page=14

Table IIA2-4, US, FHFA House Price Index, Percentage Change and Average Rate of Percentage Change per Year, Selected Dates 1992-2012

Dec	∆%	Average ∆% per Year
1992-2012	84.5	3.1
1992-2000	39.4	4.2
2000-2003	24.2	7.5
2000-2005	50.4	8.5
2003-2005	21.1	10.0
2005-2012	-12.0	NA
2000-2006	54.2	7.5
2003-2006	24.1	7.5
2006-2012	-14.2	NA

Source: Source: Federal Housing Finance Agency

http://fhfa.gov/Default.aspx?Page=14

Table VA-5, US, Percentage Changes of Standard & Poor’s Case-Shiller Home Price Indices, Not Seasonally Adjusted, ∆%

	10-City Composite	20-City Composite
∆% Sep 2000 to Sep 2003	40.5	33.8
∆% Sep 2000 to Sep 2005	95.5	80.5
∆% Sep 2003 to Sep 2005	39.2	34.9
∆% Sep 2000 to Sep 2006	103.0	88.2
∆% Sep 2003 to Sep 2006	44.5	40.7
∆% Sep 2005 to Sep 2013	-16.9	-16.1
∆% Sep 2006 to Sep 2013	-20.0	-19.5
∆% Sep 2009 to Sep 2013	-8.1	-14.5
∆% Sep 2010 to Sep 2013	11.8	12.5
∆% Sep 2011 to Sep 2013	15.7	16.7
∆% Sep 2012 to Sep 2013	13.3	13.3
∆% Sep 2000 to Sep 2013	62.3	51.5
∆% Peak Jun 2006 Sep 2013	-20.4
∆% Peak Jul 2006 Sep 2013		-19.8
Average ∆% Dec 1987-Dec 2012	3.3	NA
Average ∆% Dec 1987-Dec 2000	3.8	NA
Average ∆% Dec 1992-Dec 2000	5.0	NA
Average ∆% Dec 2000-Dec 2012	2.8	2.3

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

Table VA-6, 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
Sep 2013	0.9	0.7	1.0	0.7
Aug	0.9	1.3	0.9	1.3
Jul	0.7	1.9	0.6	1.8
Jun	1.0	2.2	0.9	2.2
May	1.0	2.5	1.0	2.5
Apr	1.8	2.6	1.7	2.6
Mar	1.9	1.3	1.9	1.3
Feb	1.3	0.3	1.2	0.2
Jan	0.8	0.0	0.9	0.0
Dec 2012	1.0	0.2	1.0	0.2
Nov	0.6	-0.3	0.7	-0.2
Oct	0.7	-0.2	0.7	-0.1
Sep	0.4	0.3	0.6	0.3
Aug	0.4	0.8	0.4	0.9
Jul	0.3	1.5	0.3	1.6
Jun	0.9	2.1	1.0	2.3
May	0.8	2.2	0.9	2.4
Apr	0.6	1.4	0.6	1.4
Mar	0.5	-0.1	0.6	0.0
Feb	0.1	-0.9	0.1	-0.8
Jan	-0.3	-1.1	-0.2	-1.0
Dec 2011	-0.5	-1.2	-0.4	-1.1
Nov	-0.6	-1.4	-0.5	-1.3
Oct	-0.5	-1.3	-0.5	-1.3
Sep	-0.4	-0.6	-0.4	-0.7
Aug	-0.3	0.1	-0.4	0.1
Jul	-0.2	0.9	-0.2	1.0
Jun	-0.1	1.0	-0.1	1.2
May	-0.3	1.0	-0.3	1.0
Apr	-0.1	0.6	-0.2	0.6
Mar	-0.3	-1.0	-0.4	-1.0
Feb	-0.3	-1.3	-0.3	-1.2
Jan	-0.3	-1.1	-0.3	-1.1
Dec 2010	-0.2	-0.9	-0.2	-1.0

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

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Exit Risks of Zero Interest Rates, World Trade Restricting Economic Growth, United States Commercial Banks Assets and Liabilities, United States Housing, World Economic Slowdown and Global Recession Risk: Part I

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