Sunday, January 1, 2017

Rules versus Discretionary Authorities in Monetary Policy, Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth, United States Housing, World Cyclical Slow Growth and Global Recession Risk: Part I

 

Rules versus Discretionary Authorities in Monetary Policy, Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth, United States Housing, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017

I Rules versus Discretionary Authorities in Monetary Policy

IA Monetary Policy Rules

IA1 Origins of Rules versus Discretion

IA2 Monetary Policy Rules

IA3 The Taylor Rule

IB Unconventional Monetary Policy

IC Counterfactual of Policies Causing the Financial Crisis and Global Recession

ID Appendix on the Monetary History of Brazil

II Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth

IIA United States Housing Collapse

IIA1 Sales of New Houses

IIA2 United States House Prices

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

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

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during the Debt Crisis of the 1980s

Executive Summary

Contents of Executive Summary

ESI Financial “Irrational Exuberance,” Increasing Interest Rate and Exchange Rate Risk, Duration Dumping, Competitive Devaluations, Steepening Yield Curve and Global Financial and Economic Risk

ESII Valuations of Risk Financial Assets

ESIII Rules versus Discretionary Authorities in Monetary Policy

ESIV Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth

ESV United States Housing

ESI “Financial “Irrational Exuberance,” Increasing Interest Rate and Exchange Rate Risk, Duration Dumping, Competitive Devaluations, 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 IMF provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/ns/cs.aspx?id=29), of the world financial system with its Global Financial Stability Report (GFSR) (http://www.imf.org/external/pubs/ft/gfsr/index.htm) and of fiscal affairs with the Fiscal Monitor (http://www.imf.org/external/ns/cs.aspx?id=262). 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:

  1. China’s Economic Growth. The National People’s Congress of China in Mar 2016 is reducing the GDP growth target to the range of 6.5 percent to 7.0 percent in guiding stable market expectations (http://news.xinhuanet.com/english/photo/2016-03/05/c_135157171.htm). President Xi Jinping announced on Nov 3, 2015 that “For China to double 2010 GDP and the per capita income of both urban and rural residents by 2010, annual growth for the 2016-2020 period must be at least 6.5 percent,” as quoted by Xinhuanet (http://news.xinhuanet.com/english/2015-11/03/c_134780377.htm). China lowered the growth target to approximately 7.0 percent in 2015, as analyzed by Xiang Bo, writing on “China lowers 2015 economic growth target to around 7 percent,” published on Xinhuanet on Mar 5, 2015 (http://news.xinhuanet.com/english/2015-03/05/c_134039341.htm). China had lowered its growth target to 7.5 percent per year. Lu Hui, writing on “China lowers GDP target to achieve quality economic growth, on Mar 12, 2012, published in Beijing by Xinhuanet (http://news.xinhuanet.com/english/china/2012-03/12/c_131461668.htm), informs that Premier Jiabao wrote in a government work report that the GDP growth target will be lowered to 7.5 percent to enhance the quality and level of development of China over the long term. The Third Plenary Session of the 18th Central Committee of the Communist Party of China adopted unanimously on Nov 15, 2013, a new round of reforms with 300 measures (Xinhuanet, “China details reform decision-making process,” Nov 19, 2013 http://news.xinhuanet.com/english/china/2013-11/19/c_125722517.htm). Growth rates of GDP of China in a quarter relative to the same quarter a year earlier have been declining from 2011 to 2016. China’s GDP grew 1.9 percent in IQ2012, annualizing to 7.8 percent, and 8.1 percent relative to a year earlier. The GDP of China grew at 2.2 percent in IIQ2012, which annualizes to 9.1 percent, and 7.6 percent relative to a year earlier. China grew at 1.8 percent in IIIQ2012, which annualizes at 7.4 percent, and 7.5 percent relative to a year earlier. In IVQ2012, China grew at 1.9 percent, which annualizes at 7.8 percent, and 8.1 percent in IVQ2012 relative to IVQ2011. In IQ2013, China grew at 1.9 percent, which annualizes at 7.8 percent, and 7.9 percent relative to a year earlier. In IIQ2013, China grew at 1.7 percent, which annualizes at 7.0 percent, and 7.6 percent relative to a year earlier. China grew at 2.1 percent in IIIQ2013, which annualizes at 8.7 percent, and increased 7.9 percent relative to a year earlier. China grew at 1.6 percent in IVQ2013, which annualized to 6.6 percent, and 7.7 percent relative to a year earlier. China’s GDP grew 1.7 percent in IQ2014, which annualizes to 7.0 percent, and 7.4 percent relative to a year earlier. China’s GDP grew 1.8 percent in IIQ2014, which annualizes at 7.4 percent, and 7.5 percent relative to a year earlier. China’s GDP grew 1.8 percent in IIIQ2014, which is equivalent to 7.4 percent in a year, and 7.1 percent relative to a year earlier. The GDP of China grew 1.8 percent in IVQ2014, which annualizes at 7.4 percent, and 7.2 percent relative to a year earlier. The GDP of China grew at 1.6 percent in IQ2015, which annualizes at 6.6 percent, and 7.0 percent relative to a year earlier. The GDP of China grew 1.9 percent in IIQ2015, which annualizes at 7.8 percent, and increased 7.0 percent relative to a year earlier. In IIIQ2015, China’s GDP grew at 1.7 percent, which annualizes at 7.0 percent, and increased 6.9 percent relative to a year earlier. The GDP of China grew at 1.6 percent in IVQ2015, which annualizes at 6.6 percent, and increased 6.8 percent relative to a year earlier. The GDP of China grew 1.2 percent in IQ2016, which annualizes at 4.9 percent, and increased 6.7 percent relative to a year earlier. In IIQ2016, the GDP of China increased 1.9 percent, which annualizes to 7.8 percent, and increased 6.7 percent relative to a year earlier. The GDP of China increased at 1.8 percent in IIIQ2016, which annualizes at 7.4 percent, and increased 6.7 percent relative to a year earlier. There is decennial change in leadership in China (http://www.xinhuanet.com/english/special/18cpcnc/index.htm). (http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/unresolved-us-balance-of-payments.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/imf-view-of-world-economy-and-finance.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/uncertainty-of-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/valuation-of-risk-financial-assets.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/04/imf-view-of-world-economy-and-finance.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/04/imf-view-of-economy-and-finance-united.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/competitive-currency-conflicts-world.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/financial-oscillations-world-inflation.html and earlier http://cmpassocregulationblog.blogspot.com/2014/07/financial-irrational-exuberance.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/imf-view-world-inflation-waves-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/capital-flows-exchange-rates-and.html). There is also ongoing political development in China during a decennial political reorganization with new leadership (http://www.xinhuanet.com/english/special/18cpcnc/index.htm). Xinhuanet informs that Premier Wen Jiabao considers the need for macroeconomic stimulus, arguing that “we should continue to implement proactive fiscal policy and a prudent monetary policy, while giving more priority to maintaining growth” (http://news.xinhuanet.com/english/china/2012-05/20/c_131599662.htm). Premier Wen elaborates that “the country should properly handle the relationship between maintaining growth, adjusting economic structures and managing inflationary expectations” (http://news.xinhuanet.com/english/china/2012-05/20/c_131599662.htm). Bob Davis, writing on “At China’s NPC, Proposed Changes,” on Mar 5, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304732804579420743344553328?KEYWORDS=%22china%22&mg=reno64-wsj), analyzes the wide ranging policy changes in the annual work report by Prime Minister Li Keqiang to China’s NPC (National People’s Congress of the People’s Republic of China http://www.npc.gov.cn/englishnpc/news/). There are about sixty different fiscal and regulatory measures.
  2. United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 23.6 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically low hiring and declining/stagnating real wages. Actual GDP is about two trillion dollars lower than trend GDP.
  3. Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
  4. World Inflation Waves. Inflation continues in repetitive waves globally (http://cmpassocregulationblog.blogspot.com/2016/12/of-course-economic-outlook-is-highly.html and earlier http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html). There is growing concern on capital outflows and currency depreciation of emerging markets.

A list of financial uncertainties includes:

  1. Euro Area Survival Risk. The resilience of the euro to fiscal and financial doubts on larger member countries is still an unknown risk. There are complex economic, financial and political effects of the withdrawal of the UK from the European Union or BREXIT after the referendum on Jun 23, 2016 (https://next.ft.com/eu-referendum for extensive coverage by the Financial Times).
  2. Competitive Devaluations. Exchange rate struggles continue as zero interest rates and negative interest rates in advanced economies induce devaluation of their currencies with alternating episodes of revaluation. The dollar is revaluing sharply.
  3. Valuation and Volatility of Risk Financial Assets. Valuations of risk financial assets have reached extremely high levels in markets with oscillating volumes. The President of the European Central Bank (ECB), Mario Draghi, warned on Jun 3, 2015 that (http://www.ecb.europa.eu/press/pressconf/2015/html/is150603.en.html):

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

  1. 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.
  2. Credibility and Commitment of Central Bank Policy. There is a credibility issue of the commitment of monetary policy (Sargent and Silber 2012Mar20)
  3. Carry Trades. Commodity prices driven by zero interest rates have resumed their increasing path with fluctuations caused by intermittent risk aversion mixed with reallocations of portfolios of risk financial

There are collateral effects of unconventional monetary policy. 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 by the penalty in the form of low interest rates and unsound credit decisions. 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 (http://www.federalreserve.gov/boarddocs/press/monetary/2004/20040630/default.htm) to 5.25 percent in Jun 2006 (http://www.federalreserve.gov/newsevents/press/monetary/20060629a.htm) 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 $2671 billion, or $2.7 trillion, of 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 differ from each other in their expectations. For the purposes of dynamic theory and of analysis of specific market situations, the theories of sections 2 and 3 are complementary rather than competitive. The formal apparatus of section 3 will serve just as well for a non-zero expected capital gain or loss as for a zero expected value of g. Stickiness of interest rate expectations would mean that the expected value of g is a function of the rate of interest r, going down when r goes down and rising when r goes up. In addition to the rotation of the opportunity locus due to a change in r itself, there would be a further rotation in the same direction due to the accompanying change in the expected capital gain or loss. At low interest rates expectation of capital loss may push the opportunity locus into the negative quadrant, so that the optimal position is clearly no consols, all cash. At the other extreme, expectation of capital gain at high interest rates would increase sharply the slope of the opportunity locus and the frequency of no cash, all consols positions, like that of Figure 3.3. The stickier the investor's expectations, the more sensitive his demand for cash will be to changes in the rate of interest (emphasis added).”

Tobin (1969) provides more elegant, complete analysis of portfolio allocation in a general equilibrium model. The major point is equally clear in a portfolio consisting of only cash balances and a perpetuity or consol. Let g be the capital gain, r the rate of interest on the consol and re the expected rate of interest. The rates are expressed as proportions. The price of the consol is the inverse of the interest rate, (1+re). Thus, g = [(r/re) – 1]. The critical analysis of Tobin is that at extremely low interest rates there is only expectation of interest rate increases, that is, dre>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 (Friedman 1957). 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 (1)

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.

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

Fri May 1

Mon 4

Tue 5

Wed 6

Thu 7

Fri 8

DJIA

18024.06

-0.3%

1.0%

18070.40

0.3%

0.3%

17928.20

-0.5%

-0.8%

17841.98

-1.0%

-0.5%

17924.06

-0.6%

0.5%

18191.11

0.9%

1.5%

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

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

Another hurdle of exit from zero interest rates is “competitive easing” that Professor Raghuram Rajan, governor of the Reserve Bank of India, characterizes as disguised “competitive devaluation” (http://www.centralbanking.com/central-banking-journal/interview/2358995/raghuram-rajan-on-the-dangers-of-asset-prices-policy-spillovers-and-finance-in-india). The fed has been considering increasing interest rates. The European Central Bank (ECB) announced, on Mar 5, 2015, the beginning on Mar 9, 2015 of its quantitative easing program denominated as Public Sector Purchase Program (PSPP), consisting of “combined monthly purchases of EUR 60 bn [billion] in public and private sector securities” (http://www.ecb.europa.eu/mopo/liq/html/pspp.en.html). Expectation of increasing interest rates in the US together with euro rates close to zero or negative cause revaluation of the dollar (or devaluation of the euro and of most currencies worldwide). US corporations suffer currency translation losses of their foreign transactions and investments (http://www.fasb.org/jsp/FASB/Pronouncement_C/SummaryPage&cid=900000010318) while the US becomes less competitive in world trade (Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), Government Intervention in Globalization (2008c)). The DJIA fell 1.5 percent on Mar 6, 2015 and the dollar revalued 2.2 percent from Mar 5 to Mar 6, 2015. The euro has devalued 51.2 percent relative to the dollar from the high on Jul 15, 2008 to Dec 30, 2016.

Fri 27 Feb

Mon 3/2

Tue 3/3

Wed 3/4

Thu 3/5

Fri 3/6

USD/ EUR

1.1197

1.6%

0.0%

1.1185

0.1%

0.1%

1.1176

0.2%

0.1%

1.1081

1.0%

0.9%

1.1030

1.5%

0.5%

1.0843

3.2%

1.7%

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

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

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

Fri Mar 6

Mon 9

Tue 10

Wed 11

Thu 12

Fri 13

USD/ EUR

1.0843

3.2%

1.7%

1.0853

-0.1%

-0.1%

1.0700

1.3%

1.4%

1.0548

2.7%

1.4%

1.0637

1.9%

-0.8%

1.0497

3.2%

1.3%

Fri Mar 13

Mon 16

Tue 17

Wed 18

Thu 19

Fri 20

USD/ EUR

1.0497

3.2%

1.3%

1.0570

-0.7%

-0.7%

1.0598

-1.0%

-0.3%

1.0864

-3.5%

-2.5%

1.0661

-1.6%

1.9%

1.0821

-3.1%

-1.5%

Fri Apr 24

Mon 27

Tue 28

Wed 29

Thu 30

May Fri 1

USD/ EUR

1.0874

-0.6%

-0.4%

1.0891

-0.2%

-0.2%

1.0983

-1.0%

-0.8%

1.1130

-2.4%

-1.3%

1.1223

-3.2%

-0.8%

1.1199

-3.0%

0.2%

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

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

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

Fri May 15

Mon 18

Tue 19

Wed 20

Thu 21

Fri 22

USD/ EUR

1.1449

-2.2%

-0.3%

1.1317

1.2%

1.2%

1.1150

2.6%

1.5%

1.1096

3.1%

0.5%

1.1113

2.9%

-0.2%

1.1015

3.8%

0.9%

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

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

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

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

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

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

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

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

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

Some equity markets fell on Fri Sep 18, 2015:

Fri Sep 11

Mon 14

Tue 15

Wed 16

Thu 17

Fri 18

DJIA

16433.09

2.1%

0.6%

16370.96

-0.4%

-0.4%

16599.85

1.0%

1.4%

16739.95

1.9%

0.8%

16674.74

1.5%

-0.4%

16384.58

-0.3%

-1.7%

Nikkei 225

18264.22

2.7%

-0.2%

17965.70

-1.6%

-1.6%

18026.48

-1.3%

0.3%

18171.60

-0.5%

0.8%

18432.27

0.9%

1.4%

18070.21

-1.1%

-2.0%

DAX

10123.56

0.9%

-0.9%

10131.74

0.1%

0.1%

10188.13

0.6%

0.6%

10227.21

1.0%

0.4%

10229.58

1.0%

0.0%

9916.16

-2.0%

-3.1%

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

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

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

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

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

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

Fri Oct 16

Mon 19

Tue 20

Wed 21

Thu 22

Fri 23

USD/ EUR

1.1350

0.1%

0.3%

1.1327

0.2%

0.2%

1.1348

0.0%

-0.2%

1.1340

0.1%

0.1%

1.1110

2.1%

2.0%

1.1018

2.9%

0.8%

DJIA

17215.97

0.8%

0.4%

17230.54

0.1%

0.1%

17217.11

0.0%

-0.1%

17168.61

-0.3%

-0.3%

17489.16

1.6%

1.9%

17646.70

2.5%

0.9%

Dow Global

2421.58

0.3%

0.6%

2414.33

-0.3%

-0.3%

2411.03

-0.4%

-0.1%

2411.27

-0.4%

0.0%

2434.79

0.5%

1.0%

2458.13

1.5%

1.0%

DJ Asia Pacific

1402.31

1.1%

0.3%

1398.80

-0.3%

-0.3%

1395.06

-0.5%

-0.3%

1402.68

0.0%

0.5%

1396.03

-0.4%

-0.5%

1415.50

0.9%

1.4%

Nikkei 225

18291.80

-0.8%

1.1%

18131.23

-0.9%

-0.9%

18207.15

-0.5%

0.4%

18554.28

1.4%

1.9%

18435.87

0.8%

-0.6%

18825.30

2.9%

2.1%

Shanghai

3391.35

6.5%

1.6%

3386.70

-0.1%

-0.1%

3425.33

1.0%

1.1%

3320.68

-2.1%

-3.1%

3368.74

-0.7%

1.4%

3412.43

0.6%

1.3%

DAX

10104.43

0.1%

0.4%

10164.31

0.6%

0.6%

10147.68

0.4%

-0.2%

10238.10

1.3%

0.9%

10491.97

3.8%

2.5%

10794.54

6.8%

2.9%

Ben Leubsdorf, writing on “Fed’s Yellen: December is “Live Possibility” for First Rate Increase,” on Nov 4, 2015, published in the Wall Street Journal (http://www.wsj.com/articles/feds-yellen-december-is-live-possibility-for-first-rate-increase-1446654282) quotes Chair Yellen that a rate increase in “December would be a live possibility.” The remark of Chair Yellen was during a hearing on supervision and regulation before the Committee on Financial Services, US House of Representatives (http://www.federalreserve.gov/newsevents/testimony/yellen20151104a.htm) and a day before the release of the employment situation report for Oct 2015 (Section I). The dollar revalued 2.4 percent during the week. The euro has devalued 51.2 percent relative to the dollar from the high on Jul 15, 2008 to Dec 30, 2016.

Fri Oct 30

Mon 2

Tue 3

Wed 4

Thu 5

Fri 6

USD/ EUR

1.1007

0.1%

-0.3%

1.1016

-0.1%

-0.1%

1.0965

0.4%

0.5%

1.0867

1.3%

0.9%

1.0884

1.1%

-0.2%

1.0742

2.4%

1.3%

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

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

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

Fri Nov 13

Mon 16

Tue 17

Wed 18

Thu 19

Fri 20

USD/ EUR

1.0774

-0.3%

0.4%

1.0686

0.8%

0.8%

1.0644

1.2%

0.4%

1.0660

1.1%

-0.2%

1.0735

0.4%

-0.7%

1.0647

1.2%

0.8%

DJIA

17245.24

-3.7%

-1.2%

17483.01

1.4%

1.4%

17489.50

1.4%

0.0%

17737.16

2.9%

1.4%

17732.75

2.8%

0.0%

17823.81

3.4%

0.5%

DAX

10708.40

-2.5%

-0.7%

10713.23

0.0%

0.0%

10971.04

2.5%

2.4%

10959.95

2.3%

-0.1%

11085.44

3.5%

1.1%

11119.83

3.8%

0.3%

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

Fri Nov 27

Mon 30

Tue 1

Wed 2

Thu 3

Fri 4

USD/ EUR

1.0594

0.5%

0.2%

1.0565

0.3%

0.3%

1.0634

-0.4%

-0.7%

1.0616

-0.2%

0.2%

1.0941

-3.3%

-3.1%

1.0885

-2.7%

0.5%

DJIA

17798.49

-0.1%

-0.1%

17719.92

-0.4%

-0.4%

17888.35

0.5%

1.0%

17729.68

-0.4%

-0.9%

17477.67

-1.8%

-1.4%

17847.63

0.3%

2.1%

DAX

11293.76

1.6%

-0.2%

11382.23

0.8%

0.8%

11261.24

-0.3%

-1.1%

11190.02

-0.9%

-0.6%

10789.24

-4.5%

-3.6%

10752.10

-4.8%

-0.3%

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

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

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

Fri Dec 11

Mon 14

Tue 15

Wed 16

Thu 17

Fri 18

USD/ EUR

1.0991

-1.0%

-0.4%

1.0993

0.0%

0.0%

1.0932

0.5%

0.6%

1.0913

0.7%

0.2%

1.0827

1.5%

0.8%

1.0868

1.1%

-0.4%

DJIA

17265.21

-3.3%

-1.8%

17368.50

0.6%

0.6%

17524.91

1.5%

0.9%

17749.09

2.8%

1.3%

17495.84

1.3%

-1.4%

17128.55

-0.8%

-2.1%

DAX

10340.06

-3.8%

-2.4%

10139.34

-1.9%

-1.9%

10450.38

-1.1%

3.1%

10469.26

1.2%

0.2%

10738.12

3.8%

2.6%

10608.19

2.6%

-1.2%

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

Fri 22

Mon 25

Tue 26

Wed 27

Thu 28

Fri 29

JPY/ USD

118.77

-1.5%

-0.9%

118.30

0.4%

0.4%

118.42

0.3%

-0.1%

118.68

0.1%

-0.2%

118.82

0.0%

-0.1%

121.13

-2.0%

-1.9%

DJIA

16093.51

0.7%

1.3%

15885.22

-1.3%

-1.3%

16167.23

0.5%

1.8%

15944.46

-0.9%

-1.4%

16069.64

-0.1%

0.8%

16466.30

2.3%

2.5%

Nikkei

16958.53

-1.1%

5.9%

17110.91

0.9%

0.9%

16708.90

-1.5%

-2.3%

17163.92

1.2%

2.7%

17041.45

0.5%

-0.7%

17518.30

3.3%

2.8%

Shanghai

2916.56

0.5%

1.3

2938.51

0.8%

0.8%

2749.79

-5.7%

-6.4%

2735.56

-6.2%

-0.5%

2655.66

-8.9%

-2.9%

2737.60

-6.1%

3.1%

DAX

9764.88

2.3%

2.0%

9736.15

-0.3%

-0.3%

9822.75

0.6%

0.9%

9880.82

1.2%

0.6%

9639.59

-1.3%

-2.4%

9798.11

0.3%

1.6%

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

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

Sovereign Yields 2/12/16

Japan

Germany

USA

2 Year

-0.168

-0.498

0.694

10 Year

0.076

0.262

1.744

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

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

Fri 4

Mon 7

Tue 8

Wed 9

Thu10

Fri 11

USD/ EUR

1.1006

-0.7%

-0.4%

1.1012

-0.1%

-0.1%

1.1013

-0.1%

0.0%

1.0999

0.1%

0.1%

1.1182

-1.6%

-1.7%

1.1151

-1.3%

0.3%

DJIA

17006.77

2.2%

0.4%

17073.95

0.4%

0.4%

16964.10

-0.3%

-0.6%

17000.36

0.0%

0.2%

16995.13

-0.1%

0.0%

17213.31

1.2%

1.3%

DAX

9824.17

3.3%

0.7%

9778.93

-0.5%

0.5%

9692.82

-1.3%

-0.9%

9723.09

-1.0%

0.3%

9498.15

-3.3%

-2.3%

9831.13

0.1%

3.5%

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

clip_image001

Chart VIII-1, Fed Funds Rate and Yields of  Ten-year Treasury Constant Maturity and Baa Seasoned Corporate Bond, Jan 2, 2001 to Oct 6, 2016 

Source: Board of Governors of the Federal Reserve System

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

clip_image002

Chart VIII-1A, Fed Funds Rate and Yields of Ten-year Treasury Constant Maturity, Jan 2, 2001 to Dec 29, 2016

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

0.089

2.98

5.53

11/21/2013

0.09

2.79

5.44

11/26/13

0.09

2.74

5.34 (11/26/13)

12/5/13

0.09

2.88

5.47

12/11/13

0.09

2.89

5.42

12/18/13

0.09

2.94

5.36

12/26/13

0.08

3.00

5.37

1/1/2014

0.08

3.00

5.34

1/8/2014

0.07

2.97

5.28

1/15/2014

0.07

2.86

5.18

1/22/2014

0.07

2.79

5.11

1/30/2014

0.07

2.72

5.08

2/6/2014

0.07

2.73

5.13

2/13/2014

0.06

2.73

5.12

2/20/14

0.07

2.76

5.15

2/27/14

0.07

2.65

5.01

3/6/14

0.08

2.74

5.11

3/13/14

0.08

2.66

5.05

3/20/14

0.08

2.79

5.13

3/27/14

0.08

2.69

4.95

4/3/14

0.08

2.80

5.04

4/10/14

0.08

2.65

4.89

4/17/14

0.09

2.73

4.89

4/24/14

0.10

2.70

4.84

5/1/14

0.09

2.63

4.77

5/8/14

0.08

2.61

4.79

5/15/14

0.09

2.50

4.72

5/22/14

0.09

2.56

4.81

5/29/14

0.09

2.45

4.69

6/05/14

0.09

2.59

4.83

6/12/14

0.09

2.58

4.79

6/19/14

0.10

2.64

4.83

6/26/14

0.10

2.53

4.71

7/2/14

0.10

2.64

4.84

7/10/14

0.09

2.55

4.75

7/17/14

0.09

2.47

4.69

7/24/14

0.09

2.52

4.72

7/31/14

0.08

2.58

4.75

8/7/14

0.09

2.43

4.71

8/14/14

0.09

2.40

4.69

8/21/14

0.09

2.41

4.69

8/28/14

0.09

2.34

4.57

9/04/14

0.09

2.45

4.70

9/11/14

0.09

2.54

4.79

9/18/14

0.09

2.63

4.91

9/25/14

0.09

2.52

4.79

10/02/14

0.09

2.44

4.76

10/09/14

0.08

2.34

4.68

10/16/14

0.09

2.17

4.64

10/23/14

0.09

2.29

4.71

11/13/14

0.09

2.35

4.82

11/20/14

0.10

2.34

4.86

11/26/14

0.10

2.24

4.73

12/04/14

0.12

2.25

4.78

12/11/14

0.12

2.19

4.72

12/18/14

0.13

2.22

4.78

12/23/14

0.13

2.26

4.79

12/30/14

0.06

2.20

4.69

1/8/15

0.12

2.03

4.57

1/15/15

0.12

1.77

4.42

1/22/15

0.12

1.90

4.49

1/29/15

0.11

1.77

4.35

2/05/15

0.12

1.83

4.43

2/12/15

0.12

1.99

4.53

2/19/15

0.12

2.11

4.64

2/26/15

0.11

2.03

4.47

3/5/215

0.11

2.11

4.58

3/12/15

0.11

2.10

4.56

3/19/15

0.12

1.98

4.48

3/26/15

0.11

2.01

4.56

4/03/15

0.12

1.92

4.47

4/9/15

0.12

1.97

4.50

4/16/15

0.13

1.90

4.45

4/23/15

0.13

1.96

4.50

5/1/15

0.08

2.05

4.65

5/7/15

0.13

2.18

4.82

5/14/15

0.13

2.23

4.97

5/21/15

0.12

2.19

4.94

5/28/15

0.12

2.13

4.88

6/04/15

0.13

2.31

5.03

6/11/15

0.13

2.39

5.10

6/18/15

0.14

2.35

5.17

6/25/15

0.13

2.40

5.20

7/1/15

0.13

2.43

5.26

7/9/15

0.13

2.32

5.20

7/16/15

0.14

2.36

5.24

7/23/15

0.13

2.28

5.13

7/30/15

0.14

2.28

5.16

8/06/15

0.14

2.23

5.15

8/20/15

0.15

2.09

5.13

8/27/15

0.14

2.18

5.33

9/03/15

0.14

2.18

5.35

9/10/15

0.14

2.23

5.35

9/17/15

0.14

2.21

5.39

9/25/15

0.14

2.13

5.29

10/01/15

0.13

2.05

5.36

10/08/15

0.13

2.12

5.40

10/15/15

0.13

2.04

5.33

10/22/15

0.12

2.04

5.30

10/29/15

0.12

2.19

5.40

11/05/15

0.12

2.26

5.44

11/12/15

0.12

2.32

5.51

11/19/15

0.12

2.24

5.44

11/25/15

0.12

2.23

5.44

12/03/15

0.13

2.33

5.51

12/10/15

0.14

2.24

5.43

12/17/15

0.37

2.24

5.45

12/23/15

0.36

2.27

5.53

12/30/15

0.35

2.31

5.54

1/07/2016

0.36

2.16

5.44

01/14/16

0.36

2.10

5.46

01/20/16

0.37

2.01

5.41

01/29/16

0.38

2.00

5.48

02/04/16

0.38

1.87

5.40

02/11/16

0.38

1.63

5.26

02/18/16

0.38

1.75

5.37

02/25/16

0.37

1.71

5.27

03/03/16

0.37

1.83

5.30

03/10/16

0.36

1.93

5.23

03/17/16

0.37

1.91

5.11

03/24/16

0.37

1.91

4.97

03/31/16

0.25

1.78

4.90

04/07/16

0.37

1.70

4.76

04/14/16

0.37

1.80

4.79

04/21/16

0.37

1.88

4.79

04/28/16

0.37

1.84

4.73

05/05/16

0.37

1.76

4.62

05/12/16

0.37

1.75

4.66

05/19/16

0.37

1.85

4.70

05/26/16

0.37

1.83

4.69

06/02/16

0.37

1.81

4.64

06/09/16

0.37

1.68

4.53

06/16/16

0.38

1.57

4.47

06/23/16

0.39

1.74

4.60

06/30/16

0.36

1.49

4.41

07/07/16

0.40

1.40

4.19

07/14/16

0.40

1.53

4.23

07/21/16

0.40

1.57

4.25

07/28/16

0.40

1.52

4.20

08/04/16

0.40

1.51

4.27

08/11/16

0.40

1.57

4.27

08/18/16

0.40

1.53

4.23

08/25/16

0.40

1.58

4.21

09/01/16

0.40

1.57

4.19

09/08/16

0.40

1.61

4.28

09/15/16

0.40

1.71

4.43

09/22/16

0.40

1.63

4.32

09/29/16

0.40

1.56

4.23

10/06/16

0.40

1.75

4.36

10/13/16

0.40

1.75

NA*

10/20/16

0.41

1.76

NA*

10/27/16

0.41

1.85

NA*

11/03/16

0.41

1.82

NA*

11/09/16

0.41

2.07

NA*

11/17/16

0.41

2.29

NA*

11/23/16

0.40

2.36

NA*

12/01/16

0.40

2.45

NA*

12/08/16

0.41

2.40

NA*

12/15/16

0.66

2.60

NA*

12/22/16

0.66

2.55

NA*

12/29/16

0.66

2.49

NA*

*Note: the Board of Governors of the Federal Reserve System discontinued the publication of the BAA bond yield.

Source: Board of Governors of the Federal Reserve System

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

Chart VIII-2 of the Board of Governors of the Federal Reserve System provides the rate of US dollars (USD) per euro (EUR), USD/EUR. The rate appreciated from USD 1.0955/EUR on Dec 23, 2015 to USD 1.0449/EUR on Dec 30, 2016 or 4.6 percent. The euro has devalued 51.2 percent relative to the dollar from the high on Jul 15, 2008 to Dec 30, 2016. US corporations with foreign transactions and net worth experience losses in their balance sheets in converting revenues from depreciated currencies to the dollar. Corporate profits with IVA and CCA fell at $127.9 billion in IVQ2015 with decrease of domestic industries at $149.8 billion, mostly because of decrease of nonfinancial business at $131.7 billion, and increase of profits from operations in the rest of the world at $22.0 billion. Receipts from the rest of the world fell at $19.9 billion. Corporate profits with IVA and CCA increased at $66.0 billion in IQ2016 with increase of domestic industries at $92.9 billion. Profits from operations from the rest of the world fell at $26.9 billion and payments to the rest of the world increased at $35.6 billion. Corporate profits with IVA and CCA decreased at $12.5 billion in IIQ2016. Profits from domestic industries fell at $50.5 billion and profits from nonfinancial business fell at $56.1 billion. Profits from the rest of the world increased at $38.0 billion. Corporate profits with IVA and CCA increased at $117.8 billion in IIIQ2016. Profits from domestic industries increased at $116.5 billion and profits from nonfinancial business increased at $66.4 billion. Profits from the rest of the world increased at $1.3 billion. Total corporate profits with IVA and CCA were $2138.8 billion in IIIQ2016 of which $1729.9 billion from domestic industries, or 80.9 percent of the total, and $408.9 billion, or 19.1 percent, from the rest of the world. Nonfinancial corporate profits of $1236.9 billion account for 57.8 percent of the total. 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. There is increase in corporate profits from devaluing the dollar with unconventional monetary policy of zero interest rates and decrease of corporate profits in revaluing the dollar with attempts at “normalization” or increases in interest rates. Conflicts arise while other central banks differ in their adjustment process. The current account deficit seasonally adjusted increases from 2.3 percent of GDP in IVQ2014 to 2.7 percent in IQ2015. The current account deficit increases to 2.7 percent of GDP in IQ2015 and decreases to 2.5 percent of GDP in IIQ2015. The deficit increases to 2.9 percent of GDP in IIIQ2015, easing to 2.8 percent of GDP in IVQ2015. The net international investment position decreases from minus $7.0 trillion in IVQ2014 to minus $6.8 trillion in IQ2015, decreasing at minus $6.7 trillion in IIQ2015. The net international investment position increases to minus $7.6 trillion in IQ2016 and increases to minus $8.0 trillion in IIQ2016. The BEA explains as follows (http://www.bea.gov/newsreleases/international/intinv/2016/pdf/intinv216.pdf):

The U.S. net international investment position at the end of the second quarter of 2016 was -$8,042.8 billion (preliminary), according to statistics released today by the Bureau of Economic Analysis (BEA). The net investment position at the end of the first quarter was -$7,582.0 billion (revised). The net investment position decreased $460.8 billion or 6.1 percent in the second quarter, compared with a decrease of 4.1 percent in the first quarter, and an average quarterly decrease of 6.1 percent from the first quarter of 2011 through the fourth quarter of 2015. The $460.8 billion decrease in the net position reflected a $479.9 billion decrease in the net position excluding financial derivatives that was partly offset by a $19.1 billion increase in the net position in financial derivatives.”

The BEA explains further (http://www.bea.gov/newsreleases/international/intinv/2016/pdf/intinv216.pdf): “U.S. assets increased $404.1 billion to $24,465.9 billion at the end of the second quarter, reflecting increases in both financial derivatives and assets excluding financial derivatives. Financial derivatives with a positive fair value increased $241.4 billion to $3,223.7 billion, mostly in single-currency interest rate contracts. Assets excluding financial derivatives increased $162.7 billion to $21,242.1 billion, reflecting increases in other investment, portfolio investment, and reserve assets that were partly offset by a decrease in direct investment. Increases resulting from financial transactions were partly offset by depreciation of major foreign currencies against the U.S. dollar that lowered the value of U.S. assets in dollar terms.”

clip_image003

Chart VIII-2, Exchange Rate of US Dollars (USD) per Euro (EUR), Dec 30, 2015 to Dec 30, 2016

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

Chart VIII-3 of the Board of Governors of the Federal Reserve System provides the yield of the 10-year Treasury constant maturity note from 1.60 percent on Sep 29 2016 to 2.49 percent on Dec 29, 2016. There is turbulence in financial markets originating in a combination of intentions of normalizing or increasing US policy fed funds rate, quantitative easing in Europe and Japan and increasing perception of financial/economic risks.

clip_image004

Chart VIII-3, Yield of Ten-year Constant Maturity Treasury, Sep 29, 2016 to Dec 29, 2016

Source: Board of Governors of the Federal Reserve System

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

Chart S provides the yield of the two-year Treasury constant maturity from Mar 17, 2014, two days before the guidance of Chair Yellen on Mar 19, 2014, to Dec 29, 2016. Chart SA provides the yields of the seven-, ten- and thirty-year Treasury constant maturity in the same dates. Yields increased right after the guidance of Chair Yellen. The two-year yield remain at a higher level than before while the ten-year yield fell and increased again. There could be more immediate impact on two-year yields of an increase in the fed funds rates but the effects would spread throughout the term structure of interest rates (Cox, Ingersoll and Ross 1981, 1985, Ingersoll 1987). Yields converged toward slightly lower earlier levels in the week of Apr 24, 2014 with reallocation of portfolios of risk financial assets away from equities and into bonds and commodities. There is ongoing reshuffling of portfolios to hedge against geopolitical events and world/regional economic performance.

clip_image005

Chart S, US, Yield of Two-Year Treasury Constant Maturity, Mar 17, 2014 to Dec 29, 2016 

Source: Board of Governors of the Federal Reserve System

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

clip_image006

Chart SA, US, Yield of Seven-Year, Ten-Year and Thirty-Year Treasury Constant Maturity, Mar 17, 2014 to Dec 22, 2016 

Source: Board of Governors of the Federal Reserve System

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

Chair Yellen states (http://www.federalreserve.gov/newsevents/speech/yellen20140331a.htm):

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

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

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

Inflation and unemployment in the period 1966 to 1985 is analyzed by Cochrane (2011Jan, 23) by means of a Phillips circuit joining points of inflation and unemployment. Chart VI-1B for Brazil in Pelaez (1986, 94-5) was reprinted in The Economist in the issue of Jan 17-23, 1987 as updated by the author. Cochrane (2011Jan, 23) argues that the Phillips circuit shows the weakness in Phillips curve correlation. The explanation is by a shift in aggregate supply, rise in inflation expectations or loss of anchoring. The case of Brazil in Chart VI-1B cannot be explained without taking into account the increase in the fed funds rate that reached 22.36 percent on Jul 22, 1981 (http://www.federalreserve.gov/releases/h15/data.htm) in the Volcker Fed that precipitated the stress on a foreign debt bloated by financing balance of payments deficits with bank loans in the 1970s. The loans were used in projects, many of state-owned enterprises with low present value in long gestation. The combination of the insolvency of the country because of debt higher than its ability of repayment and the huge government deficit with declining revenue as the economy contracted caused adverse expectations on inflation and the economy.  This interpretation is consistent with the case of the 24 emerging market economies analyzed by Reinhart and Rogoff (2010GTD, 4), concluding that “higher debt levels are associated with significantly higher levels of inflation in emerging markets. Median inflation more than doubles (from less than seven percent to 16 percent) as debt rises from the low (0 to 30 percent) range to above 90 percent. Fiscal dominance is a plausible interpretation of this pattern.”

The reading of the Phillips circuits of the 1970s by Cochrane (2011Jan, 25) is doubtful about the output gap and inflation expectations:

“So, inflation is caused by ‘tightness’ and deflation by ‘slack’ in the economy. This is not just a cause and forecasting variable, it is the cause, because given ‘slack’ we apparently do not have to worry about inflation from other sources, notwithstanding the weak correlation of [Phillips circuits]. These statements [by the Fed] do mention ‘stable inflation expectations. How does the Fed know expectations are ‘stable’ and would not come unglued once people look at deficit numbers? As I read Fed statements, almost all confidence in ‘stable’ or ‘anchored’ expectations comes from the fact that we have experienced a long period of low inflation (adaptive expectations). All these analyses ignore the stagflation experience in the 1970s, in which inflation was high even with ‘slack’ markets and little ‘demand, and ‘expectations’ moved quickly. They ignore the experience of hyperinflations and currency collapses, which happen in economies well below potential.”

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

Chart VI-1B provides the tortuous Phillips Circuit of Brazil from 1963 to 1987. There were no reliable consumer price index and unemployment data in Brazil for that period. Chart VI-1B used the more reliable indicator of inflation, the wholesale price index, and idle capacity of manufacturing as a proxy of unemployment in large urban centers.

clip_image008

ChVI1-B, Brazil, Phillips Circuit, 1963-1987

Source:

©Carlos Manuel Pelaez, O Cruzado e o Austral: Análise das Reformas Monetárias do Brasil e da Argentina. São Paulo: Editora Atlas, 1986, pages 94-5. Reprinted in: Brazil. Tomorrow’s Italy, The Economist, 17-23 January 1987, page 25.

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

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

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

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

There is concern at the Federal Open Market Committee (FOMC) with the world economy and financial markets (http://www.federalreserve.gov/newsevents/press/monetary/20160127a.htm): “The Committee is closely monitoring global economic and financial developments and is assessing their implications for the labor market and inflation, and for the balance of risks to the outlook” (emphasis added). This concern should include the effects on dollar revaluation of competitive easing by other central banks such as quantitative and qualitative easing with negative nominal interest rates.”

It is quite difficult to measure inflationary expectations because they tend to break abruptly from past inflation. There could still be an influence of past and current inflation in the calculation of future inflation by economic agents. Table VIII-1 provides inflation of the CPI. In the three months from Sep 2016 to Nov 2016, CPI inflation for all items seasonally adjusted was 3.7 percent in annual equivalent, obtained by calculating accumulated inflation from Sep 2016 to Nov 2016 and compounding for a full year. In the 12 months ending in Nov 2016, CPI inflation of all items not seasonally adjusted was 1.7 percent. Inflation in Nov 2016 seasonally adjusted was 0.2 percent relative to Oct 2016, or 2.4 percent annual equivalent (http://www.bls.gov/cpi/). The second row provides the same measurements for the CPI of all items excluding food and energy: 2.1 percent in 12 months, 1.6 percent in annual equivalent Sep 2016-Nov 2016 and 0.2 percent in Nov 2016 or 2.4 percent in annual equivalent. The Wall Street Journal provides the yield curve of US Treasury securities (http://professional.wsj.com/mdc/public/page/mdc_bonds.html?mod=mdc_topnav_2_3000). The shortest term is 0.416 percent for one month, 0.505 percent for three months, 0.628 percent for six months, 0.825 percent for one year, 1.206 percent for two years, 1.459 percent for three years, 1.926 percent for five years, 2.249 percent for seven years, 2.445 percent for ten years and 3.068 percent for 30 years. The Irving Fisher (1930) definition of real interest rates is approximately the difference between nominal interest rates, which are those estimated by the Wall Street Journal, and the rate of inflation expected in the term of the security, which could behave as in Table VIII-1. Inflation in Jan 2016 is low in 12 months because of the unwinding of carry trades from zero interest rates to commodity futures prices but could ignite again with subdued risk aversion. Real interest rates in the US have been negative during substantial periods in the past decade while monetary policy pursues a policy of attaining its “dual mandate” of (http://www.federalreserve.gov/aboutthefed/mission.htm):

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

Negative real rates of interest distort calculations of risk and returns from capital budgeting by firms, through lending by financial intermediaries to decisions on savings, housing and purchases of households. Inflation on near zero interest rates misallocates resources away from their most productive uses and creates uncertainty of the future path of adjustment to higher interest rates that inhibit sound decisions.

Table I-3, US, Consumer Price Index Percentage Changes 12 months NSA and Annual Equivalent ∆%

 

% RI

∆% 12 Months Nov 2016/Nov
2015 NSA

∆% Annual Equivalent Sep 2016 to Nov 2016 SA

∆% Nov 2016/Oct 2016 SA

CPI All Items

100.000

1.7

3.7

0.2

CPI ex Food and Energy

79.193

2.1

1.6

0.2

% RI: Percent Relative Importance

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

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 State, 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 and riskier asset classes resulting from the debate within and outside the Fed on increasing interest rates. Table VIII-2 provides the yield curve of Treasury securities on Dec 30, 2016, Dec 31, 2013, May 1, 2013, Dec 30, 2015 and Dec 29, 2006. There is oscillating 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 3.04 percent on Dec 31, 2013 and 2.45 percent on Dec 30, 2016, as measured by the United States Treasury. Assume that a bond with maturity in 10 years were issued on Dec 31, 2013, at par or price of 100 with coupon of 1.45 percent. The price of that bond would be 86.3778 with instantaneous increase of the yield to 3.04 percent for loss of 13.6 percent and far more with leverage. Assume that the yield of a bond with exactly ten years to maturity and coupon of 2.45 percent would jump instantaneously from yield of 2.45 percent on Dec 30, 2016 to 4.71 percent as occurred on Dec 29, 2006 when the economy was closer to full employment. The price of the hypothetical bond issued with coupon of 2.45 percent would drop from 100 to 82.1405 after an instantaneous increase of the yield to 4.71 percent. The price loss would be 17.9 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

 

12/30/16

12/31/13

5/01/13

12/30/15

12/29/06

1 M

0.44

0.00

0.03

0.08

4.75

3 M

0.51

0.01

0.06

0.21

5.02

6 M

0.62

0.07

0.08

0.47

5.09

1 Y

0.85

0.25

0.11

0.64

5.00

2 Y

1.20

0.56

0.20

1.08

4.82

3 Y

1.47

0.91

0.30

1.36

4.74

5 Y

1.93

1.43

0.65

1.80

4.70

7 Y

2.25

1.80

1.07

2.14

4.70

10 Y

2.45

3.04

1.66

2.31

4.71

20 Y

2.79

3.72

2.44

2.69

4.91

30 Y

3.06

3.96

2.83

3.04

4.81

M: Months; Y: Years

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 with amplifying fluctuations. 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 3.42 percent on Oct 6, 2016, which is the last data point in Chart VI-13. The thirty-year mortgage rate was 4.32 percent on Dec 29, 2016 (http://www.freddiemac.com/finance/ http://www.freddiemac.com/pmms/index.html). The current decline of yields is encouraging a surge in mortgage applications that could be reversed in a new increase. Shayndi Raice and Nick Timiraos, writing on “Banks cut as mortgage boom ends,” on Jan 9, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303754404579310940019239208), analyze the drop in mortgage applications to a 13-year low, as measured by the Mortgage Bankers Association. Nick Timiraos, writing on “Demand for home loans plunges,” on Apr 24, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304788404579522051733228402?mg=reno64-wsj), analyzes data in Inside Mortgage Finance that mortgage lending of $235 billion in IQ2014 is 58 percent lower than a year earlier and 23 percent below IVQ2013. Mortgage lending collapsed to the lowest level in 14 years. In testimony before the Committee on the Budget of the US Senate on May 8, 2004, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm): “One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.”

clip_image009

Chart VI-13, US, Conventional Mortgage Rate, Jan 8, 2004 to Oct 6, 2016

Source: Board of Governors of the Federal Reserve System

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

Table IIB-8, US, Fed Funds Rate, Thirty Year Treasury Bond and Conventional Mortgage Rate, Monthly, Percent per Year, Dec 2012 to Aug 2016

 

Fed Funds Rate

Yield of Thirty Year Constant Maturity

Conventional Mortgage Rate

2012-12

0.16

2.88

3.35

2013-01

0.14

3.08

3.41

2013-02

0.15

3.17

3.53

2013-03

0.14

3.16

3.57

2013-04

0.15

2.93

3.45

2013-05

0.11

3.11

3.54

2013-06

0.09

3.40

4.07

2013-07

0.09

3.61

4.37

2013-08

0.08

3.76

4.46

2013-09

0.08

3.79

4.49

2013-10

0.09

3.68

4.19

2013-11

0.08

3.80

4.26

2013-12

0.09

3.89

4.46

2014-01

0.07

3.77

4.43

2014-02

0.07

3.66

4.30

2014-03

0.08

3.62

4.34

2014-04

0.09

3.52

4.34

2014-05

0.09

3.39

4.19

2014-06

0.1

3.42

4.16

2014-07

0.09

3.33

4.13

2014-08

0.09

3.2

4.12

2014-09

0.09

3.26

4.16

2014-10

0.09

3.04

4.04

2014-11

0.09

3.04

4.00

2014-12

0.12

2.83

3.86

2015-01

0.11

2.46

3.67

2015-02

0.11

2.57

3.71

2015-03

0.11

2.63

3.77

2015-04

0.12

2.59

3.67

2015-05

0.12

2.96

3.84

2015-06

0.13

3.11

3.98

2015-07

0.13

3.07

4.05

2015-08

0.14

2.86

3.91

2015-09

0.14

2.95

3.89

2015-10

0.12

2.89

3.80

2015-11

0.12

3.03

3.94

2015-12

0.24

2.97

3.96

2016-01

0.34

2.86

3.87

2016-02

0.38

2.62

3.66

2016-03

0.36

2.68

3.69

2016-04

0.37

2.62

3.61

2016-05

0.37

2.63

3.60

2016-06

0.38

2.45

3.57

2016-07

0.39

2.23

3.44

2016-08

0.40

2.26

3.44

2016-09

0.40

2.35

3.46

2016-10

0.40

2.50

3.47

2016-11

0.41

2.86

3.77

Source: Board of Governors of the Federal Reserve System

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

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

Chart VI-14 provides the overnight fed funds rate, the yield of the 10-year Treasury constant maturity bond, the yield of the 30-year constant maturity bond and the conventional mortgage rate from Jan 1991 to Dec 1996. In Jan 1991, the fed funds rate was 6.91 percent, the 10-year Treasury yield 8.09 percent, the 30-year Treasury yield 8.27 percent and the conventional mortgage rate 9.64 percent. Before monetary policy tightening in Oct 1993, the rates and yields were 2.99 percent for the fed funds, 5.33 percent for the 10-year Treasury, 5.94 for the 30-year Treasury and 6.83 percent for the conventional mortgage rate. After tightening in Nov 1994, the rates and yields were 5.29 percent for the fed funds rate, 7.96 percent for the 10-year Treasury, 8.08 percent for the 30-year Treasury and 9.17 percent for the conventional mortgage rate.

clip_image011

Chart VI-14, US, Overnight Fed Funds Rate, 10-Year Treasury Constant Maturity, 30-Year Treasury Constant Maturity and Conventional Mortgage Rate, Monthly, Jan 1991 to Dec 1996

Source: Board of Governors of the Federal Reserve System

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

Chart VI-15 of the Bureau of Labor Statistics provides the all items consumer price index from Jan 1991 to Dec 1996. There does not appear acceleration of consumer prices requiring aggressive tightening.

clip_image012

Chart VI-15, US, Consumer Price Index All Items, Jan 1991 to Dec 1996

Source: Bureau of Labor Statistics

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

Chart IV-16 of the Bureau of Labor Statistics provides 12-month percentage changes of the all items consumer price index from Jan 1991 to Dec 1996. Inflation collapsed during the recession from Jul 1990 (III) and Mar 1991 (I) and the end of the Kuwait War on Feb 25, 1991 that stabilized world oil markets. CPI inflation remained almost the same and there is no valid counterfactual that inflation would have been higher without monetary policy tightening because of the long lag in effect of monetary policy on inflation (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). Policy tightening had adverse collateral effects in the form of emerging market crises in Mexico and Argentina and fixed income markets worldwide.

clip_image013

Chart VI-16, US, Consumer Price Index All Items, Twelve-Month Percentage Change, Jan 1991 to Dec 1996

Source: Bureau of Labor Statistics

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

Table VI-2 provides the Euro/Dollar (EUR/USD) exchange rate and Chinese Yuan/Dollar (CNY/USD) exchange rate that reveal pursuit of exchange rate policies resulting from monetary policy in the US and capital control/exchange rate policy in China. The ultimate intentions are the same: promoting internal economic activity at the expense of the rest of the world. The easy money policy of the US was deliberately or not but effectively to devalue the dollar from USD 1.1423/EUR on Jun 26, 2003 to USD 1.5914/EUR on Jul 14, 2008, or by 39.3 percent. The flight into dollar assets after the global recession caused revaluation to USD 1.192/EUR on Jun 7, 2010, or by 25.1 percent. After the temporary interruption of the sovereign risk issues in Europe from Apr to Jul, 2010, shown in Table VI-4 below, the dollar has revalued to USD 1.0520 EUR on Dec 30, 2016 or by 11.7 percent {[(1.0520/1.192)-1]100 = -11.7%}. Yellen (2011AS, 6) admits that Fed monetary policy results in dollar devaluation with the objective of increasing net exports, which was the policy that Joan Robinson (1947) labeled as “beggar-my-neighbor” remedies for unemployment. Risk aversion erodes devaluation of the dollar. China fixed the CNY to the dollar for a long period at a highly undervalued level of around CNY 8.2765/USD subsequently revaluing to CNY 6.8211/USD until Jun 7, 2010, or by 17.6 percent. After fixing again the CNY to the dollar, China devalued to CNY 6.9448/USD on Fri Dec 30, 2016, or by 1.8 percent, for cumulative revaluation of 16.1 percent. The final row of Table VI-2 shows: devaluation of 0.3 percent in the week of Dec 9, 2016; devaluation of 0.7 percent in the week of Dec 16 2016; revaluation of 0.2 percent in the week of Dec 23, 2016; and change of 0.0 percent in the week of Dec 30. There could be reversal of revaluation to devalue the Yuan.

Table VI-2, Dollar/Euro (USD/EUR) Exchange Rate and Chinese Yuan/Dollar (CNY/USD) Exchange Rate

USD/EUR

12/26/03

7/14/08

6/07/10

12/30/16

Rate

1.1423

1.5914

1.192

1.0520

CNY/USD

01/03
2000

07/21
2005

7/15
2008

12/30/16

Rate

8.2765

8.2765

6.8211

6.9448

Weekly Rates

12/09/2016

12/16/2016

12/23/2016

12/30/16

CNY/USD

6.9077

6.9593

6.9463

6.9448

∆% from Earlier Week*

-0.3

-0.7

0.2

0.0

*Negative sign is depreciation; positive sign is appreciation

Source: http://professional.wsj.com/mdc/public/page/mdc_currencies.html?mod=mdc_topnav_2_3000

Professor Edward P Lazear (2013Jan7), writing on “Chinese ‘currency manipulation’ is not the problem,” on Jan 7, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887323320404578213203581231448.html), provides clear thought on the role of the yuan in trade between China and the United States and trade between China and Europe. There is conventional wisdom that Chinese exchange rate policy causes the loss of manufacturing jobs in the United States, which is shown by Lazear (2013Jan7) to be erroneous. The fact is that manipulation of the CNY/USD rate by China has only minor effects on US employment. Lazear (2013Jan7) shows that the movement of monthly exports of China to its major trading partners, United States and Europe, since 1995 cannot be explained by the fixing of the CNY/USD rate by China. The period is quite useful because it includes rapid growth before 2007, contraction until 2009 and weak subsequent expansion. Chart VI-1 of the Board of Governors of the Federal Reserve System provides the CNY/USD exchange rate from Jan 3, 1995 to Dec 23, 2016 together with US recession dates in shaded areas. China fixed the CNY/USD rate for a long period as shown in the horizontal segment from 1995 to 2005. There was systematic revaluation of 17.6 percent from CNY 8.2765 on Jul 21, 2005 to CNY 6.8211 on Jul 15, 2008. China fixed the CNY/USD rate until Jun 7, 2010, to avoid adverse effects on its economy from the global recession, which is shown as a horizontal segment from 2009 until mid 2010. China then continued the policy of appreciation of the CNY relative to the USD with oscillations until the beginning of 2012 when the rate began to move sideways followed by a final upward slope of devaluation that is measured in Table VI-2A but virtually disappeared in the rate of CNY 6.3589/USD on Aug 17, 2012 and was nearly unchanged at CNY 6.3558/USD on Aug 24, 2012. China then appreciated 0.2 percent in the week of Dec 21, 2012, to CNY 6.2352/USD for cumulative 1.9 percent revaluation from Oct 28, 2011 and left the rate virtually unchanged at CNY 6.2316/USD on Jan 11, 2013, appreciating to CNY 6.9432/USD on Dec 23, 2016, which is the last data point in Chart VI-1. Revaluation of the CNY relative to the USD of 16.1 percent by Dec 30, 2016 has not reduced the trade surplus of China but reversal of the policy of revaluation could result in international confrontation. The interruption with upward slope in the final segment on the right of Chart VI-I is measured as virtually stability in Table VI-2A followed with decrease or revaluation and subsequent increase or devaluation. The final segment shows decline or revaluation with another upward move or devaluation. Linglin Wei, writing on “China intervenes to lower yuan,” on Feb 26, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304071004579406810684766716?KEYWORDS=china+yuan&mg=reno64-wsj), finds from informed sources that the central bank of China conducted the ongoing devaluation of the yuan with the objective of driving out arbitrageurs to widen the band of fluctuation. There is concern if the policy of revaluation is changing to devaluation.

clip_image014

Chart VI-1, Chinese Yuan (CNY) per US Dollar (USD), Business Days, Jan 3, 1995-Dec 23, 2016

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

Chart VI-1A provides the daily CNY/USD rate from Jan 5, 1981 to Dec 23, 2016. The exchange rate was CNY 1.5418/USD on Jan 5, 1981. There is sharp cumulative depreciation of 107.8 percent to CNY 3.2031 by Jul 2, 1986, continuing to CNY 5.8145/USD on Dec 29, 1993 for cumulative 277.1 percent since Jan 5, 1981. China then devalued sharply to CNY 8.7117/USD on Jan 7, 1994 for 49.8 percent relative to Dec 29, 1993 and cumulative 465.0 percent relative to Jan 5, 1981. China then fixed the rate at CNY 8.2765/USD until Jul 21, 2005 and revalued as analyzed in Chart VI-1. The final data point in Chart VI-1A is CNY 6.9432/USD on Dec 23, 2016. To be sure, China fixed the exchange rate after substantial prior devaluation. It is unlikely that the devaluation could have been effective after many years of fixing the exchange rate with high inflation and multiple changes in the world economy. The argument of Lazear (2013Jan7) is still valid in view of the lack of association between monthly exports of China to the US and Europe since 1995 and the exchange rate of China.

clip_image015

Chart VI-1A, Chinese Yuan (CNY) per US Dollar (USD), Business Days, Jan 5, 1981-Dec 23 2016

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

Chart VI-1B provides finer details with the rate of Chinese Yuan (CNY) to the US Dollar (USD) from Oct 28, 2011 to Dec 23, 2016. There have been alternations of revaluation and devaluation. The initial data point is CNY 6.5370 on Oct 28, 2011. There is an episode of devaluation from CNY 6.2790 on Apr 30, 2012 to CNY 6.3879 on Jul 25, 2012, or devaluation of 1.4 percent. Another devaluation is from CNY 6.0402/USD on Jan 21, 2014 to CNY 6.9432/USD on Dec 23, 2016, or devaluation of 14.9 percent. The United States Treasury estimates US government debt held by private investors at $11,184 billion in Sep 2016. China’s holding of US Treasury securities represent 10.0 percent of US government marketable interest-bearing debt held by private investors (http://www.fms.treas.gov/bulletin/index.html). Min Zeng, writing on “China plays a big role as US Treasury yields fall,” on Jul 16, 2014, published in the Wall Street Journal (http://online.wsj.com/articles/china-plays-a-big-role-as-u-s-treasury-yields-fall-1405545034?tesla=y&mg=reno64-wsj), finds that acceleration in purchases of US Treasury securities by China has been an important factor in the decline of Treasury yields in 2014. Japan decreased its holdings from $1149.2 billion in Oct 2015 to $1131.9 billion in Oct 2016 or 1.5 percent. The combined holdings of China and Japan in Oct 2016 add to $2247.6 billion, which is equivalent to 20.1 percent of US government marketable interest-bearing securities held by investors of $11,184 billion in Jun 2016 (http://www.fms.treas.gov/bulletin/index.html). Total foreign holdings of Treasury securities decreased from $6047.2 billion in Oct 2015 to $6038.9 billion in Oct 2016, or 0.1 percent. The US continues to finance its fiscal and balance of payments deficits with foreign savings (see Pelaez and Pelaez, The Global Recession Risk (2007)). A point of saturation of holdings of US Treasury debt may be reached as foreign holders evaluate the threat of reduction of principal by dollar devaluation and reduction of prices by increases in yield, including possibly risk premium. Shultz et al (2012) find that the Fed financed three-quarters of the US deficit in fiscal year 2011, with foreign governments financing significant part of the remainder of the US deficit while the Fed owns one in six dollars of US national debt. Concentrations of debt in few holders are perilous because of sudden exodus in fear of devaluation and yield increases and the limit of refinancing old debt and placing new debt. In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):

“Imagine that fiscal policy dominates monetary policy. The fiscal authority independently sets its budgets, announcing all current and future deficits and surpluses and thus determining the amount of revenue that must be raised through bond sales and seignorage. Under this second coordination scheme, the monetary authority faces the constraints imposed by the demand for government bonds, for it must try to finance with seignorage any discrepancy between the revenue demanded by the fiscal authority and the amount of bonds that can be sold to the public. Suppose that the demand for government bonds implies an interest rate on bonds greater than the economy’s rate of growth. Then if the fiscal authority runs deficits, the monetary authority is unable to control either the growth rate of the monetary base or inflation forever. If the principal and interest due on these additional bonds are raised by selling still more bonds, so as to continue to hold down the growth of base money, then, because the interest rate on bonds is greater than the economy’s growth rate, the real stock of bonds will growth faster than the size of the economy. This cannot go on forever, since the demand for bonds places an upper limit on the stock of bonds relative to the size of the economy. Once that limit is reached, the principal and interest due on the bonds already sold to fight inflation must be financed, at least in part, by seignorage, requiring the creation of additional base money.”

clip_image016

Chart VI-1B, Chinese Yuan (CNY) per US Dollar (US), Business Days, Oct 28, 2011-Dec 23, 2016

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

There are major ongoing and unresolved realignments of exchange rates in the international financial system as countries and regions seek parities that can optimize their productive structures. Seeking exchange rate parity or exchange rate optimizing internal economic activities is complex in a world of unconventional monetary policy of zero interest rates and even negative nominal interest rates of government obligations such as negative yields for the two-year government bond of Germany. Regulation, trade and devaluation conflicts should have been expected from a global recession (Pelaez and Pelaez (2007), The Global Recession Risk, Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008a)): “There are significant grounds for concern on the basis of this experience. International economic cooperation and the international financial framework can collapse during extreme events. It is unlikely that there will be a repetition of the disaster of the Great Depression. However, a milder contraction can trigger regulatory, trade and exchange wars” (Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008c), 181). Chart VI-2 of the Board of Governors of the Federal Reserve System provides the key exchange rate of US dollars (USD) per euro (EUR) from Jan 4, 1999 to Dec 23, 2016. US recession dates are in shaded areas. The rate on Jan 4, 1999 was USD 1.1812/EUR, declining to USD 0.8279/EUR on Oct 25, 2000, or appreciation of the USD by 29.9 percent. The rate depreciated 21.9 percent to USD 1.0098/EUR on Jul 22, 2002. There was sharp devaluation of the USD of 34.9 percent to USD 1.3625/EUR on Dec 27, 2004 largely because of the 1 percent interest rate between Jun 2003 and Jun 2004 together with a form of quantitative easing by suspension of auctions of the 30-year Treasury, which was equivalent to withdrawing supply from markets. Another depreciation of 17.5 percent took the rate to USD 1.6010/EUR on Apr 22, 2008, already inside the shaded area of the global recession. The flight to the USD and obligations of the US Treasury appreciated the dollar by 22.3 percent to USD 1.2446/EUR on Oct 27, 2008. In the return of the carry trade after stress tests showed sound US bank balance sheets, the rate depreciated 21.2 percent to USD 1.5085/EUR on Nov 25, 2009. The sovereign debt crisis of Europe in the spring of 2010 caused sharp appreciation of 20.7 percent to USD 1.1959/EUR on Jun 6, 2010. Renewed risk appetite depreciated the rate 24.4 percent to USD 1.4875/EUR on May 3, 2011. The rate appreciated 12.6 percent to USD 1.0449/EUR on Dec 23, 2016, which is the last point in Chart VI-2. The data in Table VI-6 is obtained from closing dates in New York published by the Wall Street Journal (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata).

clip_image017

Chart VI-2, US Dollars (USD) per Euro (EUR), Jan 4, 1999 to Dec 23, 2016

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

Chart VI-3 provides three indexes of the US Dollars (USD) from Jan 4, 1995 to Dec 23, 2016.

Chart VI-3A provides the overnight fed funds rate and yields of the three-month constant maturity Treasury bill, the ten-year constant maturity Treasury note and Moody’s Baa bond from Jan 4, 1995 to Jul 7, 2016. Chart VI-3B provides the overnight fed funds rate and yields of the three-month constant maturity Treasury bill and the ten-year constant maturity Treasury from Jan 5, 2001 to Dec 29, 2016. The first phase from 1995 to 2001 shows sharp trend of appreciation of the USD while interest rates remained at relatively high levels. The dollar revalued partly because of the emerging market crises that provoked inflows of financial investment into the US and partly because of a deliberate strong dollar policy. DeLong and Eichengreen (2001, 4-5) argue:

“That context was an economic and political strategy that emphasized private investment as the engine for U.S. economic growth. Both components of this term, "private" and "investment," had implications for the administration’s international economic strategy. From the point of view of investment, it was important that international events not pressure on the Federal Reserve to raise interest rates, since this would have curtailed capital formation and vitiated the effects of the administration’s signature achievement: deficit reduction. A strong dollar -- or rather a dollar that was not expected to weaken -- was a key component of a policy which aimed at keeping the Fed comfortable with low interest rates. In addition, it was important to create a demand for the goods and services generated by this additional productive capacity. To the extent that this demand resided abroad, administration officials saw it as important that the process of increasing international integration, of both trade and finance, move forward for the interest of economic development in emerging markets and therefore in support of U.S. economic growth.”

The process of integration consisted of restructuring “international financial architecture” (Pelaez and Pelaez, International Financial Architecture: G7, IMF, BIS, Debtors and Creditors (2005)). Policy concerns subsequently shifted to the external imbalances, or current account deficits, and internal imbalances, or government deficits (Pelaez and Pelaez, The Global Recession Risk: Dollar Devaluation and the World Economy (2007)). Fed policy consisted of lowering the policy rate or fed funds rate, which is close to the marginal cost of funding of banks, toward zero during the past decade. Near zero interest rates induce carry trades of selling dollar debt (borrowing), shorting the USD and investing in risk financial assets. Without risk aversion, near zero interest rates cause devaluation of the dollar. Chart VI-3 shows the weakening USD between the recession of 2001 and the contraction after IVQ2007. There was a flight to dollar assets and especially obligations of the US government after Sep 2008. Cochrane and Zingales (2009) show that flight was coincident with proposals of TARP (Troubled Asset Relief Program) to withdraw “toxic assets” in US banks (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a) and Regulation of Banks and Finance (2009b)). There are shocks to globalization in the form of regulation, trade and devaluation wars and breakdown of international cooperation (Pelaez and Pelaez, Globalization and the State: Vol. I (2008a), Globalization and the State: Vol. II (2008b) and Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008c)). As evident in Chart VI-3A, there is no exit from near zero interest rates without a financial crisis and economic contraction, verified by the increase of interest rates from 1 percent in Jun 2004 to 5.25 percent in Jun 2006. 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). 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 VI-3A. The gradual exit from the first round of unconventional monetary policy from 1.00 percent in Jun 2004 (http://www.federalreserve.gov/boarddocs/press/monetary/2004/20040630/default.htm) to 5.25 percent in Jun 2006 (http://www.federalreserve.gov/newsevents/press/monetary/20060629a.htm) caused the financial crisis and global recession. There are conflicts on exchange rate movements among central banks.

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

clip_image018

Chart VI-3, US Dollar Currency Indexes, Jan 4, 1995-Dec 23, 2016

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

clip_image019

Chart VI-3A, US, Overnight Fed Funds Rate, Yield of  Three-Month Treasury Constant Maturity, Yield of  Ten-Year Treasury Constant Maturity and Yield of Moody’s Baa Bond, Jan 4, 1995 to Jul 7, 2016

Source: Board of Governors of the Federal Reserve System

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

clip_image020

Chart VI-3B, US, Overnight Fed Funds Rate, Yield of Three-Month Treasury Constant Maturity and Yield of Ten-Year Treasury Constant Maturity, Jan 5, 2001 to Dec 29, 2016

Source: Board of Governors of the Federal Reserve System

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

Carry trades induced by zero interest rates increase capital flows into emerging markets that appreciate exchange rates. Portfolio reallocations away from emerging markets depreciate their exchange rates in reversals of capital flows. Chart VI-4A provides the exchange rate of the Mexican peso (MXN) per US dollar from Nov 8, 1993 to Dec 23, 2016. The first data point in Chart VI-4A is MXN 3.1520 on Nov 8, 1993. The rate devalued to 11.9760 on Nov 14, 1995 during emerging market crises in the 1990s and the increase of interest rates in the US in 1994 that stressed world financial markets (Pelaez and Pelaez, International Financial Architecture 2005, The Global Recession Risk 2007, 147-77). The MXN depreciated sharply to MXN 15.4060/USD on Mar 2, 2009, during the global recession. The rate moved to MXN 11.5050/USD on May 2, 2011, during the sovereign debt crisis in the euro area. The rate depreciated to 11.9760 on May 9, 2013. The final data point is MXN 20.6100/USD on Dec 23, 2016.

clip_image021

Chart VI-4A, Mexican Peso (MXN) per US Dollar (USD), Nov 8, 1993 to Dec 23, 2016

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

There are collateral effects worldwide from unconventional monetary policy. In remarkable anticipation in 2005, Professor Raghuram G. Rajan (2005) warned of low liquidity and high risks of central bank policy rates approaching the zero bound (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 218-9). Professor Rajan excelled in a distinguished career as an academic economist in finance and was chief economist of the International Monetary Fund (IMF). Shefali Anand and Jon Hilsenrath, writing on Oct 13, 2013, on “India’s central banker lobbies Fed,” published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304330904579133530766149484?KEYWORDS=Rajan), interviewed Raghuram G Rajan, who is the former Governor of the Reserve Bank of India, which is India’s central bank (http://www.rbi.org.in/scripts/AboutusDisplay.aspx). In this interview, Rajan argues that central banks should avoid unintended consequences on emerging market economies of inflows and outflows of capital triggered by monetary policy. Professor Rajan, in an interview with Kartik Goyal of Bloomberg (http://www.bloomberg.com/news/2014-01-30/rajan-warns-of-global-policy-breakdown-as-emerging-markets-slide.html), warns of breakdown of global policy coordination. Professor Willem Buiter (2014Feb4), a distinguished economist currently Global Chief Economist at Citigroup (http://www.willembuiter.com/resume.pdf), writing on “The Fed’s bad manners risk offending foreigners,” on Feb 4, 2014, published in the Financial Times (http://www.ft.com/intl/cms/s/0/fbb09572-8d8d-11e3-9dbb-00144feab7de.html#axzz2suwrwkFs), concurs with Raghuram Rajan. Buiter (2014Feb4) argues that international policy cooperation in monetary policy is both in the interest of the world and the United States. Portfolio reallocations induced by combination of zero interest rates and risk events stimulate carry trades that generate wide swings in world capital flows. In a speech at the Brookings Institution on Apr 10, 2014, Raghuram G. Rajan (2014Apr10, 1, 10) argues:

“As the world seems to be struggling back to its feet after the great financial crisis, I want to draw attention to an area we need to be concerned about: the conduct of monetary policy in this integrated world. A good way to describe the current environment is one of extreme monetary easing through unconventional policies. In a world where debt overhangs and the need for structural change constrain domestic demand, a sizeable portion of the effects of such policies spillover across borders, sometimes through a weaker exchange rate. More worryingly, it prompts a reaction. Such competitive easing occurs both simultaneously and sequentially, as I will argue, and both advanced economies and emerging economies engage in it. Aggregate world demand may be weaker and more distorted than it should be, and financial risks higher. To ensure stable and sustainable growth, the international rules of the game need to be revisited. Both advanced economies and emerging economies need to adapt, else I fear we are about to embark on the next leg of a wearisome cycle. A first step to prescribing the right medicine is to recognize the cause of the sickness. Extreme monetary easing, in my view, is more cause than medicine. The sooner we recognize that, the more sustainable world growth we will have.”

Professor Raguram G Rajan, former governor of the Reserve Bank of India, which is India’s central bank, warned about risks in high valuations of asset prices in an interview with Christopher Jeffery of Central Banking Journal on Aug 6, 2014 (http://www.centralbanking.com/central-banking-journal/interview/2358995/raghuram-rajan-on-the-dangers-of-asset-prices-policy-spillovers-and-finance-in-india). Professor Rajan demystifies in the interview “competitive easing” by major central banks as equivalent to competitive devaluation.

Chart VI-4B provides the rate of the Indian rupee (INR) per US dollar (USD) from Jan 2, 1973 to Dec 23, 2016. The first data point is INR 8.0200 on Jan 2, 1973. The rate depreciated sharply to INR 51.9600 on Mar 3, 2009, during the global recession. The rate appreciated to INR 44.0300/USD on Jul 28, 2011 in the midst of the sovereign debt event in the euro area. The rate overshot to INR 68.8000 on Aug 28, 2013. The final data point is INR 67.8400/USD on Dec 23, 2016.

clip_image022

Chart VI-4B, Indian Rupee (INR) per US Dollar (USD), Jan 2, 1973 to Dec 23, 2016

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

Chart VI-5 provides the exchange rate of JPY (Japan yen) per USD (US dollars). The first data point on the extreme left is JPY 357.7300/USD for Jan 4, 1971. The JPY has appreciated over the long term relative to the USD with fluctuations along an evident long-term appreciation. Before the global recession, the JPY stood at JPY 124.0900/USD on Jun 22, 2007. The use of the JPY as safe haven is evident by sharp appreciation during the global recession to JPY 110.48/USD on Aug 15, 2008, and to JPY 87.8000/USD on Jan 21, 2009. The final data point in Chart VI-5 is JPY 117.2200/USD on Dec 23, 2016 for appreciation of 5.5 percent relative to JPY 124.0900/USD on Jun 22, 2007 before the global recession and expansion characterized by recurring bouts of risk aversion. Takashi Nakamichi and Eleanor Warnock, writing on “Japan lashes out over dollar, euro,” on Dec 29, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887323530404578207440474874604.html?mod=WSJ_markets_liveupdate&mg=reno64-wsj), analyze the “war of words” launched by Japan’s new Prime Minister Shinzo Abe and his finance minister Taro Aso, arguing of deliberate devaluations of the USD and EUR relative to the JPY, which are hurting Japan’s economic activity. Gerard Baker and Jacob M. Shlesinger, writing on “Bank of Japan’s Kuroda signals impatience with Abe government,” on May 23, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303480304579579311491068756?KEYWORDS=bank+of+japan+kuroda&mg=reno64-wsj), analyze concerns of the Governor of the Bank of Japan Haruhiko Kuroda that the JPY has strengthened relative to the USD, partly eroding earlier depreciation. The data in Table VI-6 is obtained from closing dates in New York published by the Wall Street Journal (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata).

clip_image023

Chart VI-5, Japanese Yen JPY per US Dollars USD, Monthly, Jan 4, 1971-Dec 23, 2016

Note: US Recessions in Shaded Areas 

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

The causes of the financial crisis and global recession were 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

Zero interest rates in the United States forever tend to depreciate the dollar against every other currency if there is no risk aversion preventing portfolio rebalancing toward risk financial assets, which include the capital markets and exchange rates of emerging-market economies. The objective of unconventional monetary policy as argued by Yellen 2011AS) is to devalue the dollar to increase net exports that increase US economic growth. Increasing net exports and internal economic activity in the US is equivalent to decreasing net exports and internal economic activity in other countries.

Continental territory, rich endowment of natural resources, investment in human capital, teaching and research universities, motivated labor force and entrepreneurial initiative provide Brazil with comparative advantages in multiple economic opportunities. Exchange rate parity is critical in achieving Brazil’s potential but is difficult in a world of zero interest rates. Chart IV-6 of the Board of Governors of the Federal Reserve System provides the rate of Brazilian real (BRL) per US dollar (USD) from BRL 1.2074/USD on Jan 4, 1999 to BRL 3.2687/USD on Dec 23, 2016. The rate reached BRL 3.9450/USD on Oct 10, 2002 appreciating 60.5 percent to BRL 1.5580/USD on Aug 1, 2008. The rate depreciated 68.1 percent to BRL 2.6187/USD on Dec 5, 2008 during worldwide flight from risk. The rate appreciated again by 41.3 percent to BRL 1.5375/USD on Jul 26, 2011. The final data point in Chart VI-6 is BRL 3.2687/USD on Dec 23, 2016 for depreciation of 112.6 percent. The data in Table VI-6 is obtained from closing dates in New York published by the Wall Street Journal (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata).

clip_image024

Chart VI-6, Brazilian Real (BRL) per US Dollar (USD) Jan 4, 1999 to Dec 23, 2016

Note: US Recessions in Shaded Areas 

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

Chart VI-7 of the Board of Governors of the Federal Reserve System provides the history of the BRL beginning with the first data point of BRL 0.8440/USD on Jan 2, 1995. The rate jumped to BRL 2.0700/USD on Jan 29, 1999 after changes in exchange rate policy and then to BRL 2.2000/USD on Mar 3, 1999. The rate depreciated 26.7 percent to BRL 2.7880 on Sep 21, 2001 relative to Mar 3, 1999.

clip_image025

Chart VI-7, Brazilian Real (BRL) per US Dollar (USD), Jan 2, 1995 to Dec 23, 2016

Note: US Recessions in Shaded Areas 

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

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 in be the nominal interest rate, ir the real or inflation-adjusted interest rate and πe 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 + ir) = (1 + in)/(1 + πe) (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 πe 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 + rr) = 0.9902

That is, ir 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 πe. The result could be the same rate of unemployment with higher inflation (Kydland and Prescott 1977).

What is truly important is the fixing of the overnight fed funds at ½ to ¾ percent with gradual consideration of further rate increases (https://www.federalreserve.gov/newsevents/press/monetary/20161214a.htm): In determining the timing and size of future adjustments to the target range for the federal funds rate, the Committee will assess realized and expected economic conditions relative to its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial and international developments. In light of the current shortfall of inflation from 2 percent, the Committee will carefully monitor actual and expected progress toward its inflation goal. The Committee expects that economic conditions will evolve in a manner that will warrant only gradual increases in the federal funds rate; the federal funds rate is likely to remain, for some time, below levels that are expected to prevail in the longer run. However, the actual path of the federal funds rate will depend on the economic outlook as informed by incoming data” (emphasis added).

There is concern at the Federal Open Market Committee (FOMC) with the world economy and financial markets (http://www.federalreserve.gov/newsevents/press/monetary/20160127a.htm): “The Committee is closely monitoring global economic and financial developments and is assessing their implications for the labor market and inflation, and for the balance of risks to the outlook” (emphasis added). This concern should include the effects on dollar revaluation of competitive easing by other central banks such as quantitative and qualitative easing with negative nominal interest rates (https://www.boj.or.jp/en/announcements/release_2016/k160129a.pdf).

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

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. There are complex economic, financial and political effects of the withdrawal of the UK from the European Union or BREXIT after the referendum on Jun 23, 2016 (https://next.ft.com/eu-referendum for extensive coverage by the Financial Times). The DJIA has increased 104.0 percent since the trough of the sovereign debt crisis in Europe on Jul 16, 2010 to Dec 30, 2016; S&P 500 has gained 118.9 percent and DAX 102.5 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 12/30/16” 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 30.2 percent above the trough. Japan’s Nikkei Average is 116.6 percent above the trough. DJ Asia Pacific TSM is 24.3 percent above the trough. Dow Global is 48.7 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 31.1 percent above the trough. NYSE Financial Index is 63.7 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 102.5 percent above the trough. Japan’s Nikkei Average is 116.6 percent above the trough on Aug 31, 2010 and 67.8 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 19,114.37 on Dec 23, 2016 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 86.4 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 appreciated 11.7 percent relative to the euro. The dollar devalued before the new bout of sovereign risk issues in Europe. The column “∆% week to 12/30/16” in Table VI-4 shows

decrease of 0.2 percent in the week for China’s Shanghai Composite. The Nikkei decreased 1.6 percent. DJ Asia Pacific increased 0.5 percent. NYSE Financial decreased 0.7 percent in the week. Dow Global decreased 0.2 percent in the week of Dec 30, 2016. The DJIA decreased 0.9 percent and S&P 500 decreased 1.1 percent. DAX of Germany increased 0.3 percent. STOXX 50 increased 0.4 percent. The USD depreciated 0.6 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 12/30/16” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Dec 30, 2016. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 12/30/16” but also relative to the peak in column “∆% Peak to 12/30/16.” There are now several equity indexes above the peak in Table VI-4: DJIA 76.4 percent, S&P 500 83.9 percent, DAX 81.3 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 30.4 percent, Dow Global 21.3 percent, and Nikkei Average 67.8 percent. Shanghai Composite is 1.9 percent below the peak; STOXX 50 is 11.0 percent above the peak; and DJ Asia Pacific TSM is 8.8 percent above the peak. The Shanghai Composite increased 57.2 percent from March 12, 2014, to Dec 30, 2016. The US dollar strengthened 30.5 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. Sharp and continuing strengthening of the dollar is affecting balance sheets of US corporations with foreign operations (http://www.fasb.org/jsp/FASB/Pronouncement_C/SummaryPage&cid=900000010318). The Federal Open Market Committee (FOMC) is following “financial and international developments” as part of the process of framing interest rate policy (http://www.federalreserve.gov/newsevents/press/monetary/20150128a.htm). Kate Linebaugh, writing on “Corporate profits set to shrink for fourth consecutive quarter,” on Jul 17, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/corporate-profits-set-to-shrink-for-fourth-consecutive-quarter-1468799278), quotes forecasts of Thomson Reuters of 4.7 decline of adjusted earnings per share in the S&P 500 index in IIQ2016 relative to a year earlier. That would be the fourth consecutive quarterly decline. Theo Francis and Kate Linebaugh, writing on “US corporate profits on pace for third straight decline,” on Apr 28, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/u-s-corporate-profits-on-pace-for-third-straight-decline-1461872242), analyze three consecutive quarters of decline of corporate earnings and revenue in companies in S&P 500. They quote Thomson Reuters on expected decline of earnings of 6.1 percent in IQ2016 based on 55 percent of reporting companies. Weakness of economic activity shows in decline of revenues in IQ2016 of 1.4 percent, increasing 1.7 percent excluding energy, and contraction of profits of 0.5 percent. Justin Lahart, writing on “S&P 500 Earnings: far worse than advertised,” on Feb 24, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/s-p-500-earnings-far-worse-than-advertised-1456344483), analyzes S&P 500 earnings in 2015. Under data provided by companies, earnings increased 0.4 percent in 2015 relative to 2014 but under GAAP (Generally Accepted Accounting Principles), earnings fell 12.7 percent, which is the worst decrease since 2008. Theo Francis e Kate Linebaugh, writing on Oct 25, 2015, on “US Companies Warn of Slowing Economy, published in the Wall Street Journal (http://www.wsj.com/articles/u-s-companies-warn-of-slowing-economy-1445818298) analyze the first contraction of earnings and revenue of big US companies. Production, sales and employment are slowing in a large variety of companies with some contracting. Corporate profits also suffer from revaluation of the dollar that constrains translation of foreign profits into dollar balance sheets. Francis and Linebaugh quote Thomson Reuters that analysts expect decline of earnings per share of 2.8 percent in IIIQ2015 relative to IIIQ2014 based on reports by one third of companies in the S&P 500. Sales would decline 4.0% in a third quarter for the first joint decline of earnings per share and revenue in the same quarter since IIIQ2009. Dollar revaluation also constrains corporate results.

Inyoung Hwang, writing on “Fed optimism spurs record bets against stock volatility,” on Aug 21, 2014, published in Bloomberg.com (http://www.bloomberg.com/news/2014-08-21/fed-optimism-spurs-record-bets-against-stock-voalitlity.html), informs that the S&P 500 is trading at 16.6 times estimated earnings, which is higher than the five-year average of 14.3 Tom Lauricella, writing on Mar 31, 2014, on “Stock investors see hints of a stronger quarter,” published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304157204579473513864900656?mod=WSJ_smq0314_LeadStory&mg=reno64-wsj), finds views of stronger earnings among many money managers with positive factors for equity markets in continuing low interest rates and US economic growth. There is important information in the Quarterly Markets review of the Wall Street Journal (http://online.wsj.com/public/page/quarterly-markets-review-03312014.html) for IQ2014. 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. Future company cash flows derive from investment projects. In IQ1980, real gross private domestic investment in the US was $951.6 billion of chained 2009 dollars, growing to $1,270.0 billion in IQ1990 or 33.5 percent. Real gross private domestic investment in the US increased 7.7 percent from $2605.2 billion in IVQ2007 to $2,804.7 billion in IIIQ2016. As shown in Table IAI-2, real private fixed investment increased 7.5 percent from $2,586.3 billion of chained 2009 dollars in IVQ2007 to $2,779.3 billion in IIIQ2016. Private fixed investment fell relative to IVQ2007 in all quarters preceding IQ2014 and changed 0.0 percent in IIIQ2016, declining 0.3 percent in IIQ2016 and falling 0.2 percent in IQ2016. Growth of real private investment in Table IA1-2 is mediocre for all but four quarters from IIQ2011 to IQ2012. The investment decision of United States corporations is fractured in the current economic cycle in preference of cash. There are three aspects. First, there is fluctuation in corporate profits. Corporate profits with IVA and CCA decreased at $127.9 billion in IVQ2015 and increased at $66.0 billion in IQ2016. Corporate profits with IVA and CCA fell at $12.5 billion in IIQ2016 and increased at $117.8 billion in IIIQ2016. Profits after tax with IVA and CCA fell at $172.7 billion in IVQ2015 and increased at $113.4 billion in IQ2016. Profits after tax with IVA and CCA fell at $28.9 billion in IIQ2016 and increased at $98.3 billion in IIIQ2016. Net dividends fell at $20.8 billion in IVQ2015 and increased at $7.3 billion in IQ2016. Net dividends fell at $9.3 billion in IIQ2016. Net dividends increased at $18.5 billion in IIIQ2016. Undistributed corporate profits with IVA and CCA fell at $152.0 billion in IVQ2015. Undistributed profits with IVA and CCA increased at $106.1 billion in IQ2016. Undistributed corporate profits fell at $19.6 billion in IIQ2016. Undistributed corporate profits increased at $79.8 billion in IIIQ2016. Undistributed corporate profits swelled 238.8 percent from $107.7 billion in IQ2007 to $364.9 billion in IIIQ2016 and changed signs from minus $55.9 billion in current dollars in IVQ2007. 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. Second, sharp and continuing strengthening of the dollar is affecting balance sheets of US corporations with foreign operations (http://www.fasb.org/jsp/FASB/Pronouncement_C/SummaryPage&cid=900000010318) and the overall US economy. The bottom part of Table IA1-9 provides the breakdown of corporate profits with IVA and CCA in domestic industries and the rest of the world. Corporate profits with IVA and CCA fell at $127.9 billion in IVQ2015 with decrease of domestic industries at $149.8 billion, mostly because of decrease of nonfinancial business at $131.7 billion, and increase of profits from operations in the rest of the world at $22.0 billion. Receipts from the rest of the world fell at $19.9 billion. Corporate profits with IVA and CCA increased at $66.0 billion in IQ2016 with increase of domestic industries at $92.9 billion. Profits from operations from the rest of the world fell at $26.9 billion and payments to the rest of the world increased at $35.6 billion. Corporate profits with IVA and CCA decreased at $12.5 billion in IIQ2016. Profits from domestic industries fell at $50.5 billion and profits from nonfinancial business fell at $56.1 billion. Profits from the rest of the world increased at $38.0 billion. Corporate profits with IVA and CCA increased at $117.8 billion in IIIQ2016. Profits from domestic industries increased at $116.5 billion and profits from nonfinancial business increased at $66.4 billion. Profits from the rest of the world increased at $1.3 billion. Total corporate profits with IVA and CCA were $2138.8 billion in IIIQ2016 of which $1729.9 billion from domestic industries, or 80.9 percent of the total, and $408.9 billion, or 19.1 percent, from the rest of the world. Nonfinancial corporate profits of $1236.9 billion account for 57.8 percent of the total. Third, there is reduction in the use of corporate cash for investment. Vipal Monga, David Benoit and Theo Francis, writing on “Companies send more cash back to shareholders,” published on May 26, 2015 in the Wall Street Journal (http://www.wsj.com/articles/companies-send-more-cash-back-to-shareholders-1432693805?tesla=y), use data of a study by Capital IQ conducted for the Wall Street Journal. This study shows that companies in the S&P 500 reduced investment in plant and equipment to median 29 percent of operating cash flow in 2013 from 33 percent in 2003 while increasing dividends and buybacks to median 36 percent in 2013 from 18 percent in 2003.

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_image027

Where Rτ is expected revenue in the time horizon from τ =1 to T; Cτ 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

clip_image028

declines. Equally, decline in expected revenue from the stock or project, Rτ, 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 12/30/

/16

∆% Week 12/30/16

∆% Trough to 12/30/

16

DJIA

4/26/
10

7/2/10

-13.6

76.4

-0.9

104.0

S&P 500

4/23/
10

7/20/
10

-16.0

83.9

-1.1

118.9

NYSE Finance

4/15/
10

7/2/10

-20.3

30.4

-0.7

63.7

Dow Global

4/15/
10

7/2/10

-18.4

21.3

-0.2

48.7

Asia Pacific

4/15/
10

7/2/10

-12.5

8.8

0.5

24.3

Japan Nikkei Aver.

4/05/
10

8/31/
10

-22.5

67.8

-1.6

116.6

China Shang.

4/15/
10

7/02
/10

-24.7

-1.9

-0.2

30.2

STOXX 50

4/15/10

7/2/10

-15.3

11.0

0.4

31.1

DAX

4/26/
10

5/25/
10

-10.5

81.3

0.3

102.5

Dollar
Euro

11/25 2009

6/7
2010

21.2

30.5

-0.6

11.7

DJ UBS Comm.

1/6/
10

7/2/10

-14.5

NA

NA

NA

10-Year T Note

4/5/
10

4/6/10

3.986

2.784

2.447

 

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 Valuations of Risk Financial Assets. There are complex economic, financial and political effects of the withdrawal of the UK from the European Union or BREXIT after the referendum on Jun 23, 2016 (https://next.ft.com/eu-referendum for extensive coverage by the Financial Times).The most important source of financial turbulence is shifting toward fluctuating interest rates. The dollar/euro rate is quoted as number of US dollars USD per one euro EUR, USD 1.0456/EUR in the first row, first column in the block for currencies in Table III-1 for Fri Dec 23, appreciating to USD 1.0414/EUR on Wed Dec 28, 2016, or by 0.4 percent. The dollar appreciated because fewer dollars, 1.0414, were required on Wed Dec 28 to buy one euro than $1.0456 on Fri Dec 23. Table III-1 defines a country’s exchange rate as number of units of domestic currency per unit of foreign currency. USD/EUR would be the definition of the exchange rate of the US and the inverse [1/(USD/EUR)] is the definition in this convention of the rate of exchange of the euro zone, EUR/USD. A convention used throughout this blog is required to maintain consistency in characterizing movements of the exchange rate such as in Table III-1 as appreciation and depreciation. The first row for each of the currencies shows the exchange rate at 5 PM New York time, such as USD 1.0456/EUR on Dec 23. The second row provides the cumulative percentage appreciation or depreciation of the exchange rate from the rate on the last business day of the prior week, in this case Fri Dec 23, to the last business day of the current week, in this case Dec 30, such as depreciation of 0.6 percent to USD 1.0520/EUR by Dec 30. The third row provides the percentage change from the prior business day to the current business day. For example, the USD depreciated (denoted by negative sign) by 0.6 percent from the rate of USD 1.0456/EUR on Fri Dec 23 to the rate of USD 1.0520/EUR on Dec 30 {[(1.0520/1.0456) - 1]100 = 0.6%}. The dollar depreciated (denoted by negative sign) by 0.3 percent from the rate of USD 1.0492 on

Thu Dec 29 to USD 1.0520/EUR on Fri Dec 30 {[(1.0520/1.0492) -1]100 = 0.3%}. Other factors constant, increasing risk aversion causes appreciation of the dollar relative to the euro, with rising uncertainty on European and global sovereign risks increasing dollar-denominated assets with sales of risk financial investments. Funds move away from higher yielding risk assets to the safety of dollar-denominated assets.

There is mixed performance in equity indexes with several indexes in Table III-1 increasing in the week ending on Dec 30, 2016, after wide swings caused by reallocations of investment portfolios worldwide. Stagnating revenues, corporate cash hoarding, effects of currency oscillations on corporate earnings and declining investment are causing reevaluation of discounted net earnings with deteriorating views on the world economy and United States fiscal sustainability but investors have been driving indexes higher. There are complex economic, financial and political effects of the withdrawal of the UK from the European Union or BREXIT after the referendum on Jun 23, 2016 (https://next.ft.com/eu-referendum for extensive coverage by the Financial Times). DJIA decreased 0.3 percent on Dec 30, decreasing 0.9 percent in the week. Germany’s DAX increased 0.3 percent on Dec 30 and increased 0.3 percent in the week. Dow Global increased 0.1 percent on Dec 30 and decreased 0.2 percent in the week. Japan’s Nikkei Average decreased 0.2 percent on Dec 30 and decreased 1.6 percent in the week as the yen continues oscillating but relatively weaker and the stock market gains in expectations of success of fiscal stimulus by a new administration and monetary stimulus by a new board of the Bank of Japan. Dow Asia Pacific TSM increased 0.3 percent on Dec 30 and increased 0.5 percent in the week. Shanghai Composite that decreased 1.0 percent on Mar 8 and decreased 1.7 percent in the week of Mar 8, falling below 2000 at 1974.38 on Mar 12, 2014 but closing at 3103.64 on Dec 30, 2016, for increase of 0.2 percent and decreasing 0.2 percent in the week. The Shanghai Composite increased 57.2 percent from March 12, 2014 to Dec 30, 2016. There is deceleration with oscillations of the world economy that could affect corporate revenue and equity valuations, causing fluctuations in equity markets with increases during favorable risk appetite. The global hunt for yield induced by central bank policy rates of near zero percent motivates wide portfolio reshufflings among classes of risk financial assets.

Commodities were mixed in the week of Dec 30, 2016. Table III-1 shows that WTI increased 1.3 percent in the week of Dec 30 while Brent increased 3.0 percent in the week with turmoil in oil producing regions but oscillating action by OPEC. Gold decreased 0.6 percent on Dec 30 and increased 1.6 percent in the week.

Table III-I, Weekly Financial Risk Assets Dec 26 to Dec 30, 2016

Fri 23

Mon 26

Tue 27

Wed 28

Thu 29

Fri 30

USD/ EUR

1.0456

0.0%

-0.2%

1.0454

0.0%

0.0%

1.0458

0.0%

0.0%

1.0414

0.4%

0.4%

1.0492

-0.3%

-0.7%

1.0520

-0.6%

-0.3%

JPY/ USD

117.32

0.5%

0.2%

117.08

0.2%

0.2%

117.43

-0.1%

-0.3%

117.26

0.1%

0.1%

116.54

0.7%

0.6%

117.00

0.3%

-0.4%

CHF/ USD

1.0266

0.0%

-0.1%

1.0271

0.0%

0.0%

1.0280

-0.1%

-0.1%

1.0283

-0.2%

0.0%

1.0230

0.4%

0.5%

1.0189

0.8%

0.4%

CHF/ EUR

1.0734

-0.1%

-0.3%

1.0734

0.0%

0.0%

1.0750

-0.1%

-0.1%

1.0708

0.2%

0.4%

1.0733

0.0%

-0.2%

1.0718

0.1%

0.1%

USD/ AUD

0.7175

1.3937

-1.8%

-0.6%

0.7191

1.3906

0.2%

0.2%

0.7184

1.3920

0.1%

-0.1%

0.7178

1.3931

0.0%

-0.1%

0.7219

1.3852

0.6%

0.6%

0.7202

1.3885

0.4%

-0.2%

10Y Note

2.542

2.564

2.564

2.507

2.472

2.447

2Y Note

1.202

1.239

1.239

1.262

1.230

1.210

German Bond

2Y -0.79 10Y 0.26

2Y -0.79 10Y 0.26

2Y -0.79 10Y 0.26

2Y -0.82 10Y 0.20

2Y -0.79 10Y 0.17

2Y -0.79 10Y 0.21

DJIA

19933.81

0.5%

0.1%

19933.81

0.0%

0.0%

19945.04

0.1%

0.1%

19833.68

-0.5%

-0.6%

19819.78

-0.6%

-0.1%

19762.60

-0.9%

-0.3%

Dow Global

2536.89

-0.1%

0.0%

2536.89

0.0%

0.0%

2535.68

0.0%

0.0%

2527.82

-0.4%

-0.3%

2529.83

-0.3%

0.1%

2531.51

-0.2%

0.1%

DJ Asia Pacific

1415.42

-0.8%

-0.1%

1415.42

0.0%

0.0%

1412.15

-0.2%

-0.2%

1416.37

0.1%

0.3%

1419.05

0.3%

0.2%

1422.73

0.5%

0.3%

Nikkei

19427.67

0.1%

0.0%

19396.64

-0.2%

-0.2%

19403.06

-0.1%

0.0%

19401.72

-0.1%

0.0%

19145.14

-1.5%

-1.3%

19114.37

-1.6%

-0.2%

Shanghai

3110.15

-0.4%

-0.9%

3122.57

0.4%

0.4%

3114.66

0.1%

-0.3%

3102.24

-0.3%

-0.4%

3096.10

-0.5%

-0.2%

3103.64

-0.2%

0.2%

DAX

11449.93

0.4%

-0.1%

11449.93

0.0%

0.0%

11472.24

0.2%

0.2%

11474.99

0.2%

0.0%

11451.05

0.0%

-0.2%

11481.06

0.3%

0.3%

DJ UBS Comm.

NA

NA

NA

NA

NA

NA

WTI $/B

53.02

2.2%

0.1%

53.02

0.0%

0.0%

53.90

1.7%

1.7%

54.06

2.0%

0.3%

53.77

1.4%

-0.5%

53.72

1.3%

-0.1%

Brent $/B

55.16

-0.1%

0.2%

55.16

0.0%

0.0%

56.09

1.7%

1.7%

56.22

1.9%

0.2%

56.14

1.8%

-0.1%

56.82

3.0%

1.2%

44Gold

1131.9

-0.3%

0.3%

1131.9

0.0%

0.0%

1137.3

0.5%

0.5%

1139.4

0.7%

0.2%

1156.4

2.2%

1.5%

1150.0

1.6%

-0.6%

Note: USD: US dollar; JPY: Japanese Yen; CHF: Swiss

Franc; AUD: Australian dollar; Comm.: commodities; OZ: ounce

Sources: http://www.bloomberg.com/markets/

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

Table VI-6, updated with every blog comment, shows that exchange rate valuations affect a large variety of countries, in fact, almost the entire world, in magnitudes that cause major problems for domestic monetary policy and trade flows. The euro has devalued 51.2 percent relative to the dollar from the high on Jul 15, 2008 to Dec 30, 2016. There are complex economic, financial and political effects of the withdrawal of the UK from the European Union or BREXIT after the referendum on Jun 23, 2016 (https://next.ft.com/eu-referendum for extensive coverage by the Financial Times). The British pound (GBP) devalued 12.4 percent from the trough of ₤1.388 on Jan 2, 2009 to ₤1.2345 on Dec 30, 2016 and devalued 62.5 percent from the high of ₤2.006 on Sep 15, 2008. Such similar event actually occurred in the week of Sep 23, 2011 reversing the devaluation of the dollar in the form of sharp appreciation of the dollar relative to other currencies from all over the world including the offshore Chinese yuan market. The Bank of England reduced the Bank Rate to 0.25 percent on Aug 4, 2016, and announced new measures of quantitative easing (http://www.bankofengland.co.uk/publications/Pages/news/2016/008.aspx).

Table VI-6, Exchange Rates

 

Peak

Trough

∆% P/T

Dec 30, 2016

∆% T

Dec 30, 2016

∆% P

Dec 30,

2016

EUR USD

7/15
2008

6/7 2010

 

12/30/16

2016

   

1Rate

1.59

1.192

 

1.0520

   

∆%

   

-33.4

 

-13.3

-51.2

JPY USD

8/18
2008

9/15
2010

 

12/30/16

2016

   

Rate

110.19

83.07

 

117.00

   

∆%

   

24.6

 

-40.8

-6.2

CHF USD

11/21 2008

12/8 2009

 

12/30/16

2016

   

Rate

1.225

1.025

 

1.0189

   

∆%

   

16.3

 

0.6

16.8

USD GBP

7/15
2008

1/2/ 2009

 

12/30/16

2016

   

Rate

2.006

1.388

 

1.2345

   

∆%

   

-44.5

 

-12.4

-62.5

USD AUD

7/15 2008

10/27 2008

 

12/30/16

2016

   

Rate

1.0215

1.6639

 

0.7202

   

∆%

   

-62.9

 

16.6

-35.9

ZAR USD

10/22 2008

8/15
2010

 

12/30/16

2016

   

Rate

11.578

7.238

 

13.6932

   

∆%

   

37.5

 

-89.2

-18.3

SGD USD

3/3
2009

8/9
2010

 

12/30/16

2016

   

Rate

1.553

1.348

 

1.4473

   

∆%

   

13.2

 

-7.4

6.8

HKD USD

8/15 2008

12/14 2009

 

12/30/16

2016

   

Rate

7.813

7.752

 

7.7555

   

∆%

   

0.8

 

0.0

0.7

BRL USD

12/5 2008

4/30 2010

 

12/30/16

2016

   

Rate

2.43

1.737

 

3.2550

   

∆%

   

28.5

 

-87.4

-34.0

CZK USD

2/13 2009

8/6 2010

 

12/30/16

2016

   

Rate

22.19

18.693

 

25.686

   

∆%

   

15.7

 

-37.4

-15.8

SEK USD

3/4 2009

8/9 2010

 

12/30/16

2016

   

Rate

9.313

7.108

 

9.1071

   

∆%

   

23.7

 

-28.1

2.2

CNY USD

7/20 2005

7/15
2008

 

12/30/16

2016

   

Rate

8.2765

6.8211

 

6.9448

-1.8

16.1

∆%

   

17.6

     

Symbols: USD: US dollar; EUR: euro; JPY: Japanese yen; CHF: Swiss franc; GBP: UK pound; AUD: Australian dollar; ZAR: South African rand; SGD: Singapore dollar; HKD: Hong Kong dollar; BRL: Brazil real; CZK: Czech koruna; SEK: Swedish krona; CNY: Chinese yuan; P: peak; T: trough

Note: percentages calculated with currencies expressed in units of domestic currency per dollar; negative sign means devaluation and no sign appreciation

Source:

http://professional.wsj.com/mdc/public/page/mdc_currencies.html?mod=mdc_topnav_2_3000

ESIII Rules versus Discretionary Authorities in Monetary Policy. The objective of this section is to place the alternatives of monetary policy into two perspectives of (1) emphasis on long-term policy in contrast with (2) current emphasis on short-term impulses of unusual magnitude to respond immediately to deviations perceived with significant lags and measurement errors because of the deficiencies of the state of the art.

Unconventional monetary policy since 2003 has consisted of near zero nominal interest rates, negative real rates of interest, massive purchases of securities for the balance sheet of the Fed and intervention in allocation of credit. Professor John B. Taylor (2016Dec 7, 2016Dec20), in Testimony to the Subcommittee on Monetary Policy and Trade Committee on Financial Services, on Dec 7, 2016, analyzes the adverse effects of unconventional monetary policy:

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

Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 29 quarters from IIIQ2009 to IIIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIIQ2016 (https://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp3q16_3rd.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 $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2016 would have accumulated to 29.5 percent. GDP in IIIQ2016 would be $19,414.4 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2687.4 billion than actual $16,727.0 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html). US GDP in IIIQ2016 is 13.8 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,727.0 billion in IIIQ2016 or 11.6 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.1081 in Nov 2016. The actual index NSA in Nov 2016 is 103.0759, which is 27.5 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 130.3109 in Nov 2016. The output of manufacturing at 103.0759 in Nov 2016 is 20.9 percent below trend under this alternative calculation.

There is socio-economic stress in the combination of adverse events and cyclical performance:

IA Monetary Policy Rules considers the use of long-term rules or guidance for optimization of policy over many periods in contrast with discretion or immediate optimization of every perceived deviation from desired paths by policymakers. Section IB Unconventional Monetary Policy raises the issue if excessive short-term impulses cause instability instead of the prime objective of monetary policy of fostering stability. There are adverse effects on resource allocation that prevent an efficient dynamic path of the economy at the time when real disposable income per capita, or what is left per person after taxes and inflation, has stagnated. IC Counterfactual of Policies Causing the Financial Crisis and Global Recession identifies the critical issue of research that economic conditions would have been less unfavorable under alternative monetary policy rules. ID Appendix on the Monetary History of Brazil provides some evidence on the history of Brazil that is of relevance to monetary policy rules. The data in the appendix were part of a research project on the monetary history of Brazil using the NBER framework of Friedman and Schwartz (1963, 1970) and Cagan (1965) as well as the institutional framework of Rondo E. Cameron (1967, 1972) who inspired the research (Pelaez 1974, 1975, 1976a,b, 1977, 1979, Pelaez and Suzigan 1978, 1981). The data were also used to test the correct specification of money and income following Sims (1972; see also Williams et al. 1976) as well as another test of orthogonality of money demand and supply using covariance analysis. Sims (1972, 541) finds that: “If and only if causality runs one way from current and past values of some list of exogenous variables to a given endogenous variable, then in a regression of the endogenous variable on past, current, and future values of the exogenous variables, the future values of the exogenous variables should have zero coefficients.” The objective of research was to verify the quantity theory of money of Friedman and Schwartz (1963, 1970) for the economy of Brazil from 1862 to 1976. The Granger-Sims test postulates that causality runs from money into nominal income if and only if in a regression of nominal income on past, current and future values of money, future coefficients are zero. The results show that the Sims F coefficients are zero for the regressions of nominal income on money and 38 for the coefficients of money on income (Pelaez and Suzigan 1978, Pelaez 1979, 106). There are also covariance tests verifying orthogonality of money demand and money supply and orthogonality of base money and the money multiplier. The quantity theory of money explains money, income and prices in the historical period of Brazil 1862 to 1976. There are two important conclusions.

  • Models of Keynesian multipliers in historical Brazil are inconsistent with these findings
  • Pelaez (1979, 121) concludes following Friedman and Schwartz (1963, 1970) that for the case of Brazil “in historical perspective, it appears that a system of rules, instead of authorities, would have best promoted the interests of the Nation.”

Hill (2007, 763) develops “a simple parametric recursion for VAR coefficients that, for trivariate processes with one scalar auxiliary variable, always allows for sequential linear parametric conditions for non-causality up to horizon h ≥ 1. An empirical analysis of the money-income relationship reveals significant evidence in favor of linear causation of money to income, either directly when we control for cointegration, or indirectly after a delay of 1-3 months in models of first differences.” Shikida, Araujo Jr. e Figueiredo (2014) apply Hill (2007) to the historical experience of Brazil. They conclude that base money influences nominal output but not real output. Their results are consistent with the unpleasant monetarist arithmetic of Sargent and Wallace (1981) that uses base money instead of the stock of money. Because of restrictions on banking and finance (Summerhill 2015, Pelaez 1975), base money should have been more important in influencing nominal income in historical Brazil. It is valid to conclude that monetary policy rules instead of discretionary authorities would have best promoted national interests in historical Brazil.

IA Monetary Policy Rules. The discussion of monetary policy rules is divided into three subsections: IA1 Origins of Rules versus Discretion, IA2 Monetary Policy Rules and IA3 The Taylor Rule.

IA1 Origins of Rules versus Discretion. A classic proposal for rules instead of “authorities” in monetary policy is by Simons (1936, 29-30):

“A democratic, free-enterprise system implies, and requires for its effective functioning and survival, a stable framework of definite rules, laid down in legislation and subject to change only gradually and with careful regard for the vested interests of participants in the economic game. It is peculiarly essential economically that there should be a minimum of uncertainty for enterprisers and investors as to monetary conditions in the future and, politically, that the plausible expedient of setting up "authorities" instead of rules, with respect to matters of such fundamental importance, be avoided, or accepted only as a very temporary arrangement. The most important objective of a sound liberal policy, apart from the establishment of highly competitive conditions in industry and the narrow limitation of political control over relative prices, should be that of securing a monetary system governed by definite rule. The responsibility for carrying out the monetary rules should be lodged in a federal authority, endowed with large administrative powers but closely controlled in their exercise by a sharply defined policy. The powers of the monetary authority should have to do primarily or exclusively with fiscal arrangements with the issue and retirement of paper money (open-market operations in government securities) and perhaps with the relation between government revenues and expenditures; in other words, the monetary rules should be implemented entirely by, and in turn should largely determine, fiscal policy. A monetary rule of maintaining the constancy of some price-index, preferably an index of prices of competitively produced commodities, appears to afford the only promising escape from present monetary chaos and uncertainties.”

The working system of Simons (1936, 1948) consisted of 100 percent reserve requirements on banks (see Allen 1993, Fisher 1936, Graham 1936) to avoid fluctuations from bank runs and fixed quantity of money. Friedman (1967) finds that the monetary reforms proposed by Simons (1948) were not required and moving against desired directions by restricting financial intermediation that would raise costs of capital, inhibiting capital formation. The value in the proposals of Simons (1948) as viewed by Friedman (1967) would be in providing more flexibility for banks that were restricted in the 1960s by regulation inherited from the Great Depression. There are contemporary proposals that resemble the 100 percent reserve requirement in what is known as “narrow banking” (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 71-72).

Historical evolution of monetary policy rules is analyzed by Asso, Khan and Leeson (2007, 2010). In the United States, Irving Fisher and Milton Friedman proposed price and monetary rules (see Bordo and Rockoff 2011). An important departure for considering rules is the existence of three lags of macroeconomic policy (Friedman 1953):

  • The lag between the need for action and the recognition of the need
  • The lag between recognition of the need and taking action
  • The lag between taking action and effects on prices and income

There is not “one hundred percent” confidence in controlling inflation because of the lags in effects of monetary policy impulses and the equally important lags in realization of the need for action and taking of action in addition to the inability to forecast any economic variable. Romer and Romer (2004) find that a one-percentage point tightening of monetary policy is associated with a 4.3 percent decline in industrial production. There is no change in inflation in the first 22 months after monetary policy tightening when it begins to decline steadily, with decrease by 6 percent after 48 months (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 102). Even if there were one hundred percent confidence in reducing inflation by monetary policy, it could take a prolonged period with adverse effects on economic activity. Certainty does not occur in economic policy, in which there are costs that cannot be anticipated.

Friedman (1968) restated his proposal for fixed setting of monetary policy in terms of a fixed rate of increase of the money stock:

“My own prescription is still that the monetary authority go all the way in avoiding such swings by adopting publicly the policy of achieving a steady rate of growth in a specified monetary total. The precise rate of growth, like the precise monetary total, is less important than the adoption of some stated and known rate. I myself have argued for a rate that would on the average achieve rough stability in the level of prices of final products, which I have estimated would call for something like a 3 to 5 per cent per year rate of growth in currency plus all commercial bank deposits or a slightly lower rate of growth in currency plus demand deposits only. But it would be better to have a fixed rate that would on the average produce moderate inflation or moderate deflation, provided it was steady, than to suffer the wide and erratic perturbations we have experienced. Short of the adoption of such a publicly stated policy of a steady rate of monetary growth, it would constitute a major improvement if the monetary authority followed the self-denying ordinance of avoiding wide swings. It is a matter of record that periods of relative stability in the rate of monetary growth have also been periods of relative stability in economic activity, both in the United States and other countries. Periods of wide swings in the rate of monetary growth have also been periods of wide swings in economic activity.”

This was Friedman’s presidential address to the American Economic Association at the onset of wide swings in monetary policy, output and employment in the period of United States economic history known as “the Great Inflation.”

There are three “tactics” in monetary policy identified by Friedman (1982, 100-1):

  • Interest rates as both targets and instruments
  • Monetary targets as instruments and interest rates as targets
  • Base money as instrument and monetary aggregates as targets

The specific policy proposal of Friedman (1982, 101) consists of five ingredients:

“A monetarist policy has five points: first, the target should be growth in some monetary aggregate just which monetary aggregate is a separate question; second, monetary authorities should adopt long-run targets for monetary growth that are consistent with no inflation; third, present rates of growth of monetary aggregates should be modified to achieve the long-run target in a gradual, systematic, and preannounced fashion; fourth, monetary authorities should avoid fine-tuning; fifth, monetary authorities should avoid trying to manipulate either interest rates or exchange rates. Internationally, those countries that have broadly followed the five-point monetarist policy have succeeded in controlling inflation and have done so while achieving relatively satisfactory economic growth.”

The fourth of eight specific proposals for Fed monetary policy at the time states (Friedman, 1982, 117): “set a target path for several years ahead for a single aggregate—for example, M2 or the base. It is less important which aggregate is chosen than that a single aggregate be designated as the target.”

IA2 Monetary Policy Rules. The essence of rules versus discretion monetary policy is posed by McCallum (1999) as follows:

  1. Rules attempt to optimize by using a policy-contingent rule or formula that is implemented every period and is designed such as to apply indefinitely
  2. Discretion consist of re-optimization in every period in accordance with existing conditions assessed by monetary authorities

A rules-based policy optimizes over a long-term period while discretionary policy optimizes individually in every period in accordance with short-term information. A practical definition of monetary policy rule by McCallum (1999) is systematic policy that does not use expectations to cause temporary gains in output.

McCallum (1999) finds that Barro and Gordon (1983b) opened the inclusion of activist policy within a monetary policy rule. The rule provides a reaction function of the central bank that depends on available information. Barro and Gordon (1983b, 606) differentiate as follows: “the presence or absence of precomitment is the most important distinction between rules and discretion.” The reaction function of the central bank h(It-1) depends on information available in the past period, It-1, that would be more restrictive under rules-based policy than under discretion, would include many more variables in the argument. As McCallum (1999) argues, a rule could specify the conditions for activism instead of fixed settings for policy. For example, constant rate of growth of the money stock would be a fixed setting that the central bank would implement indefinitely. A policy in which the interest rate depends on inflation and the divergence of actual and potential output would be activist but under certain guidance.

Current distinction between rules and discretion is provided by Taylor (2012JMCB, 2). There are characteristics of both rules and discretion.

  1. Characteristics of rules

· More predictable and systematic decisions by the central bank on policy instruments

· Dynamic analysis of effects of current decisions on future outcomes

· Decisions based or guided by formulas and equations

· Use of stable relation of policy instruments to outcomes such as inflation and growth

  1. Characteristics of discretion

· Decisions on monetary policy instruments are “less predictable,” focusing on short-term events such as “fine tuning” or policy actions in response to ad hoc movements in economic and financial variables

· Little or no interest by policymakers in agreeing on alternative strategies for fixing magnitudes of instruments of policy

· Evolution of policy instruments over time cannot be captured by equations

IA3 The Taylor Rule. The definition of policy rule by Taylor (1993, 199) is: “Technically, a policy rule is a contingency plan that lasts forever unless there is an explicit cancellation clause.” “Forever” means here “a reasonably long period of time” (Taylor 1993, 1999). The departing theory of Taylor (1993, 1999) is the quantity theory of money equation:

MV = PY (1)

Where M is the money stock, V is income velocity of money, P the price level and Y real output. Velocity depends on the interest rate r and real output or income Y with functional form V(r, Y). The substitution of V(r, Y) in equation (1) yields a relation between the interest rate, r, the price level, P, and real output Y. Taylor (1999) assumes a linear relation of interest rates and the logarithms of the price level P and real output Y. Assuming no lags, deviation of output from stochastic trend and the inflation rate as the first difference of the logarithms of the price level, Taylor (1999) obtains:

r = π + gy + h(π – π*) + rr = (rfhπ*) + (1 + h)π + gy (2)

Where r is the short-term interest rate, π the inflation rate or percent change in the price level P, y the percentage difference of real output Y from trend and g, h, π* and rf are constants. The settings of monetary policy are the response coefficients g of the deviation of actual output from potential output and (1+h), the response to inflation.

Taylor (1993, 202) provides the simple formula, known as the Taylor Rule, as follows:

r = p + .5y + .5(p-2) + 2 (3)

Where r is the federal funds rate or policy rate of the Fed, p is the rate of inflation in the past four quarters and y is the percentage deviation of actual output from potential output. The fed funds rate increases if the gap between actual and potential output y increases to prevent lower growth below potential and resulting unemployment, and increases if inflation p increases above maximum tolerable inflation of 2 percent. Thus, the policy is guidance on fixing the fed funds rate in response to growth and inflation. Taylor (1993, 202) states: “if both the inflation rate and real GDP are on target, then the federal funds rate would equal 4 percent, or 2 percent in real terms.” If real economic growth is around trend, y is zero, and inflation is around the maximum desired of 2 percent, (p-2) is zero, such that the fed funds rate r is equal to 4 or 2 percent by deducting inflation of 2 percent.

IB Unconventional Monetary Policy. Taylor (1998LB, 1999, 2012JMCB) argues that economic performance has been enhanced during periods of long-term focus of monetary policy in the form of guidance under monetary policy rules. Periods of discretion such as the Great Inflation from the second half of the 1960s to the beginning of the 1980s and the past decade since 2003 have been characterized by instability and mediocre economic performance.

The objective of Levin and Taylor (2009) is to reveal the primary cause of the persistence of inflation drift during the Great Inflation by focusing on the path of inflationary expectations to model monetary policy from 1965 to 1980. They derive three stylized facts by use of measurements of inflation expectations. (1) Inflation began in the mid 1960 while it had been contained since the late 1950s at around 1 percent but inflation expectations accelerate beginning in 1965. (2) Long-term inflation expectations stabilized at a high level in the first half of the 1970s but catapulted toward the end of the decade. (3) Long-run inflation expectations only began to decline at the end of 1980. The central bank reaction function analyzed by Taylor (1993, 202, equation (1)) based on prior research is:

r = p +0.5y + 0.5(p-2) + 2 (3)

In equation (3), the federal funds rate, r, is expressed in terms of the rate of inflation over the previous four quarters, the percentage output gap, y, defined as 100(Y-Y*)/Y*, where Y is actual GDP, Y* is trend real GDP (2.2 percent from IQ1984 to IIIQ1992), and the deviation of inflation from the target of 2 percent, 0.5(p-2). The Taylor policy rule in equation (3) triggers an increase in the fed funds rate when inflation exceeds 2 percent or when GDP exceeds trend GDP. If GDP is equal to target, y = 0, and inflation is also equal to target, p = 2, then the real rate of interest as measured by prior inflation, r-p, equal 2 percent. The fed funds rate calculated with this simple policy rule fits remarkably well the actual fed funds rate in 1987-1992 (Taylor 1993, 204, Figure 1).

The simple rule is restated by Levin and Taylor (2010, 16, equation (1)) to account for discrete shifts in the intercept:

rt = ­r’ + γπt – π*) + γy(yty*t) (5)

Equation (5) expresses the short-term real interest rate, rt, in terms of an effect, γπt – π*), of the difference between actual inflation, πt, and the central’s bank objective for inflation, π*, and an effect, γy(yty*t), of the deviation of actual output, yt, from trend or steady-state output, y*t, and r’ stands for the steady-state value of the real rate of interest.

Equation (5) is shown by Levy and Taylor (2009) to provide a good fit of experience during the Great Inflation by allowing for shifts in the central bank’s inflation objective π*. Monetary policy during the Great Inflation can be interpreted by three stop-start events occurring in 1968-70, 1974-76 and 1979-80. Levy and Taylor (2009) conclude that in all three “stop and go” episodes monetary policy “fell behind the curve,” permitting rising inflation before belated tightening and abandoning tightening because of the contraction before inflation was reduced to the level before the event. Lags in effect of monetary policy have been amply discussed in the literature and may have proved important in falling behind the curve (see Culbertson 1960, Friedman 1961, Culbertson 1961, Batini and Nelson 2002 and Romer and Romer 2004).

Detailed discussion of the analysis of the Great Inflation is provided in past comments of this blog (http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html). Unconventional monetary policy played a major role in the financial crisis and global recession as discussed in the balance of this section.

IC. Counterfactual of Policies Causing the Financial Crisis and Global Recession. A counterfactual consists of theory and measurements of what would have occurred otherwise if economic policies or institutional arrangements had been different. This task is quite difficult because economic data are observed with all effects as they actually occurred while the counterfactual attempts to evaluate how data would differ had policies and institutional arrangements been different (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008b), 125, 136; Pelaez 1979, 26-8). Counterfactual data are unobserved and must be calculated using theory and measurement methods. The measurement of costs and benefits of projects or applied welfare economics (Harberger 1971, 1997) specifies and attempts to measure projects such as what would be economic welfare with or without a bridge or whether markets would be more or less competitive in the absence of antitrust and regulation laws (Winston 2006). The “new economic history” of the United States used counterfactuals to measure the economy with or without railroads (Fishlow 1965, Fogel 1964) and in analyzing slavery (Fogel and Engerman 1974). A critical counterfactual in economic history is how Britain surged ahead of France (North and Weingast 1989). There is similarly path-breaking research on railroads in Latin America by Coastworth (1981) and Summerhill (1997, 1998, 2003). Coastworth (2006, 176) argues that: “We already have so many history books that tells us so much about what really occurred in the past, that what we need now are books about what did not happen—but might have, or perhaps even should have happened: Counterfactual History, that is, history that is contrary to fact.”

The counterfactual of avoidance of deeper and more prolonged contraction by fiscal and monetary policies is not the critical issue. As Professor John B. Taylor (2012Oct25) argues, the critically important counterfactual is that the financial crisis and global recession would have not occurred in the first place if different economic policies had been followed. The counterfactual intends to verify that a combination of housing policies and discretionary monetary policies instead of rules (Taylor 1993) caused, deepened and prolonged the financial crisis (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/; see http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). The experience resembles that of the Great Inflation of the 1960s and 1970s with stop-and-go growth/inflation that coined the term stagflation (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I).

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

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

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

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

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

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

W = Y/r (1)

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

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

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

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

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

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

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

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

ESIV Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth. The valuable report on Financial Accounts of the United States formerly Flow of Funds Accounts of the United States provided by the Board of Governors of the Federal Reserve System (http://www.federalreserve.gov/releases/z1/Current/ http://www.federalreserve.gov/apps/fof/) is rich in important information and analysis. Table IIA-1, updated in this blog for every new quarterly release, shows the balance sheet of US households combined with nonprofit organizations in 2007, 2014, 2015 and IIIQ2016. The contraction caused a strong shock to US wealth. Assets fell from $80.9 trillion in 2007 to $76.9 trillion in 2011 even after nine consecutive quarters of growth beginning in IIIQ2009 (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.html), for decline of $4.0 trillion or 4.9 percent. Assets stood at $101.7 trillion in 2015 for gain of $20.8 trillion relative to $80.9 trillion in 2007 or increase by 25.7 percent. Assets increased to $105.1 trillion in IIIQ2016 by $24.2 trillion relative to 2007 or 30.0 percent. Liabilities declined from $14.4 trillion in 2007 to $13.6 trillion in 2011 or by $752.8 billion equivalent to decline by 5.2 percent. Liabilities increased $182.7 billion or 1.3 percent from 2007 to 2015. Liabilities increased from $14.4 trillion in 2007 to $14.9 trillion in IIIQ2016, by $513.8 billion or increase of 3.6 percent. Net worth shrank from $66.5 trillion in 2007 to $63.3 trillion in 2011, that is, $3.2 trillion equivalent to decline of 4.8 percent. Net worth increased from $66,464.0 billion in 2007 to $90,196.1 billion in IIIQ2016 by $23,732.1 billion or 35.7 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 241.428 in Sep 2016 (http://www.bls.gov/cpi/data.htm) or 14.9 percent. Net worth adjusted by CPI inflation increased 18.1 percent from 2007 to IIIQ2016. Nonfinancial assets increased $3890.3 billion from $28,074.5 billion in 2007 to $31,964.8 billion in IIIQ2016 or 13.9 percent. There was increase from 2007 to IIIQ2016 of $2844.8 billion in real estate assets or by 12.2 percent. Real estate assets adjusted for CPI inflation fell 2.4 percent between 2007 and IIIQ2016. The National Association of Realtors estimated that the gains in net worth in homes by Americans were about $4 trillion between 2000 and 2005 (quoted in Pelaez and Pelaez, The Global Recession Risk (2007), 224-5).

Table IIA-1, US, Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars Outstanding End of Period, NSA

 

2007

2014

2015

IIIQ2016

Assets

80,860.2

97,976.5

101,696.8

105,106.1

Nonfinancial

28,074.5

28,706.7

30,473.6

31,964.8

  Real Estate

23,265.0

23,200.5

24,766.9

26,109.8

  Durable Goods

  4,476.0

5,052.9

  5,236.8

5,373.2

Financial

52,785.7

69,269.8

71,223.2

73,141.2

  Deposits

  7,562.3

10,145.9

  10,737.7

11,126.0

  Debt Secs.

  4,080.6

3,993.1

  4,440.0

3,733.7

  Mutual Fund Shares

   4,314.9

6,726.3

   6,504.4

6,875.2

  Equities Corporate

   10,046.8

14,356.7

   14,159.8

14,748.4

  Equity Noncorporate

   8,815.5

10,097.5

   10,829.4

11,174.0

  Pension

15,073.4

20,658.6

21,247.6

22,087.5

Liabilities

14,396.1

14,232.5

14,578.8

14,909.9

  Home Mortgages

10,613.1

9,461.1

  9,547.2

9,707.5

  Consumer Credit

   2,609.9

3,318.0

   3,535.7

3,696.0

Net Worth

66,464.0

83,744.0

87,118.0

90,196.1

Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

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

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

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

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

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

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

W = Y/r (1)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

According to Pinto (2008) in testimony to Congress:

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

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

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

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

Table IIA-1 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 96.0 percent in the 10-city composite of the Case-Shiller home price index, 81.2 percent in the 20-city composite and 65.9 percent in the US national home price index between Oct 2000 and Oct 2005. Prices rose around 100 percent from Oct 2000 to Oct 2006, increasing 101.1 percent for the 10-city composite, 86.7 percent for the 20-city composite and 70.9 percent in the US national index. House prices rose 38.9 percent between Oct 2003 and Oct 2005 for the 10-city composite, 34.9 percent for the 20-city composite and 29.6 percent for the US national propelled by low fed funds rates of 1.0 percent between Oct 2003 and Oct 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Oct 2004 until Oct 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 Oct 2003 and Oct 2006, the 10-city index gained 42.5 percent; the 20-city index increased 39.0 percent; and the US national 33.4 percent. House prices have fallen from Oct 2006 to Oct 2016 by 8.5 percent for the 10-city composite and 6.6 percent for the 20-city composite, increasing 0.5 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Oct 2016, house prices increased 4.3 percent in the 10-city composite, increasing 5.1 percent in the 20-city composite and 5.6 percent in the US national. Table IIA-1 also shows that house prices increased 83.9 percent between Oct 2000 and Oct 2016 for the 10-city composite, increasing 74.3 percent for the 20-city composite and 71.8 percent for the US national. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The 10-city composite fell 9.2 percent from the peak in Jun 2006 to Oct 2016 and the 20-city composite fell 7.1 percent from the peak in Jul 2006 to Oct 2016. The US national increased 0.3 percent from the peak of the 10-city composite to Jun 2016 and 0.2 percent from the peak of the 20-city composite to Jul 2016. The final part of Table II-2 provides average annual percentage rates of growth of the house price indexes of Standard & Poor’s Case-Shiller. The average annual growth rate between Dec 1987 and Dec 2015 for the 10-city composite was 3.8 percent and 3.4 percent for the US national. Data for the 20-city composite are available only beginning in Jan 2000. House prices accelerated in the 1990s with the average rate of the 10-city composite of 5.0 percent between Dec 1992 and Dec 2000 while the average rate for the period Dec 1987 to Dec 2000 was 3.8 percent. The average rate for the US national was 3.4 percent from Dec 1987 to Dec 2015 and 3.6 percent from Dec 1987 to Dec 2000. Although the global recession affecting the US between IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly above 30 percent, the average annual growth rate of the 10-city composite between Dec 2000 and Dec 2015 was 3.7 percent while the rate of the 20-city composite was 3.3 percent and 3.2 percent for the US national.

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

 

10-City Composite

20-City Composite

US National

∆% Oct 2000 to Oct 2003

41.1

34.3

28.1

∆% Oct 2000 to Oct 2005

96.0

81.2

65.9

∆% Oct 2003 to Oct 2005

38.9

34.9

29.6

∆% Oct 2000 to Oct 2006

101.1

86.7

70.9

∆% Oct 2003 to Oct 2006

42.5

39.0

33.4

∆% Oct 2005 to Oct 2016

-6.2

-3.8

3.5

∆% Oct 2006 to Oct 2016

-8.5

-6.6

0.5

∆% Oct 2009 to Oct 2016

29.5

30.9

24.5

∆% Oct 2010 to Oct 2016

29.4

32.1

29.3

∆% Oct 2011 to Oct 2016

33.9

36.9

33.7

∆% Oct 2012 to Oct 2016

29.6

31.3

28.5

∆% Oct 2013 to Oct 2016

14.0

15.6

15.9

∆% Oct 2014 to Oct 2016

9.3

10.7

10.8

∆% Oct 2015 to Oct 2016

4.3

5.1

5.6

∆% Oct 2000 to Oct 2016

83.9

74.3

71.8

∆% Peak Jun 2006 Oct 2016

-9.2

 

0.3

∆% Peak Jul 2006 Oct 2016

 

-7.1

0.2

Average ∆% Dec 1987-Dec 2015

3.8

NA

3.4

Average ∆% Dec 1987-Dec 2000

3.8

NA

3.6

Average ∆% Dec 1992-Dec 2000

5.0

NA

4.5

Average ∆% Dec 2000-Dec 2015

3.7

3.3

3.2

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

Price increases measured by the Case-Shiller house price indices show in data for Oct 2016 that “home prices continued their rise across the country over the last 12 months” (https://www.spice-indices.com/idpfiles/spice-assets/resources/public/documents/461749_cshomeprice-release-1227.pdf?force_download=true). Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the 10- and 20-city composites, as shown in Table IIA-2. In Jan 2013, the seasonally adjusted 10-city composite increased 0.8 percent and the 20-city increased 0.9 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city changed 0.0 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. With the exception of Mar through Apr 2012, house prices seasonally adjusted declined in most months for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table IIA-2. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. Without seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Aug 2011 but fell in every month from Sep 2011 to Feb 2012. The not seasonally adjusted index registers decline in Mar 2012 of 0.1 percent for the 10-city composite and is flat for the 20-city composite. Not seasonally adjusted house prices increased 1.4 percent in Apr 2012 and at high monthly percentage rates until Sep 2012. House prices not seasonally adjusted stalled from Oct 2012 to Jan 2013 and surged from Feb to Sep 2013, decelerating in Oct 2013-Feb 2014. House prices grew at fast rates in Mar 2014. The 10-city NSA index changed 0.0 percent in Oct 2016 and the 20-city increased 0.1 percent. The 10-city SA increased 0.6 percent in Oct 2016 and the 20-city composite SA increased 0.6 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

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

 

10-City Composite SA

10-City Composite NSA

20-City Composite SA

20-City Composite NSA

Oct 2016

0.6

0.0

0.6

0.1

Sep

0.4

0.1

0.5

0.1

Aug

0.3

0.3

0.3

0.4

Jul

0.0

0.5

0.1

0.5

Jun

-0.1

0.7

0.0

0.8

May

-0.2

0.8

-0.1

0.9

Apr

-0.3

1.0

-0.3

1.1

Mar

1.1

0.9

1.1

1.0

Feb

0.5

0.2

0.6

0.2

Jan

0.6

-0.1

0.7

0.0

Dec 2015

0.5

-0.1

0.6

0.0

Nov

0.8

0.0

0.8

0.0

Oct

0.5

-0.1

0.6

0.0

Sep

0.4

0.1

0.5

0.1

Aug

0.2

0.2

0.2

0.3

Jul

0.1

0.6

0.1

0.7

Jun

0.1

0.9

0.1

1.0

May

0.1

1.0

0.1

1.1

Apr

-0.3

1.1

-0.3

1.1

Mar

1.0

0.8

1.1

0.9

Feb

0.9

0.5

0.9

0.5

Jan

0.6

-0.1

0.6

-0.1

Dec 2014

0.7

0.0

0.7

0.0

Nov

0.5

-0.3

0.6

-0.2

Oct

0.5

-0.1

0.5

-0.1

Sep

0.2

-0.1

0.3

-0.1

Aug

0.1

0.2

0.1

0.2

Jul

0.0

0.6

0.0

0.6

Jun

0.1

1.0

0.1

1.0

May

0.0

1.1

0.1

1.1

Apr

-0.2

1.1

-0.2

1.2

Mar

1.0

0.8

1.0

0.9

Feb

0.5

0.0

0.5

0.0

Jan

0.7

-0.1

0.6

-0.1

Dec 2013

0.6

-0.1

0.6

-0.1

Nov

0.8

0.0

0.8

-0.1

Oct

0.9

0.2

0.9

0.2

Sep

1.0

0.7

1.1

0.7

Aug

1.2

1.3

1.2

1.3

Jul

1.1

1.9

1.1

1.8

Jun

1.2

2.2

1.1

2.2

May

1.3

2.5

1.3

2.5

Apr

1.4

2.6

1.4

2.6

Mar

1.5

1.3

1.5

1.3

Feb

1.0

0.3

0.9

0.2

Jan

0.8

0.0

0.9

0.0

Dec 2012

0.9

0.2

0.9

0.2

Nov

0.6

-0.3

0.7

-0.2

Oct

0.6

-0.2

0.7

-0.1

Sep

0.6

0.3

0.6

0.3

Aug

0.6

0.8

0.7

0.9

Jul

0.6

1.5

0.7

1.6

Jun

1.0

2.1

1.1

2.3

May

1.0

2.2

1.1

2.4

Apr

0.3

1.4

0.4

1.4

Mar

0.2

-0.1

0.2

0.0

Feb

-0.1

-0.9

0.0

-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

-0.6

-1.3

-0.6

-1.4

Sep

-0.3

-0.6

-0.4

-0.7

Aug

-0.2

0.1

-0.2

0.1

Jul

-0.1

0.9

0.0

1.0

Jun

-0.1

1.0

-0.1

1.2

May

-0.2

1.0

-0.2

1.0

Apr

-0.3

0.6

-0.2

0.6

Mar

-0.6

-1.0

-0.7

-1.0

Feb

-0.4

-1.3

-0.4

-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-corelogic-case-shiller

Table IIA-4 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2008 and 2009. Total assets fell $10.5 trillion or 13.0 percent from 2007 to 2008 and $8.9 trillion or 11.1 percent to 2009. Net worth fell $10.4 trillion from 2007 to 2008 or 15.7 percent and $8.7 trillion to 2009 or 13.0 percent. Subsidies to housing prolonged over decades together with interest rates at 1.0 percent from Jun 2003 to Jun 2004 inflated valuations of real estate and risk financial assets such as equities. The increase of fed funds rates by 25 basis points until 5.25 percent in Jun 2006 reversed carry trades through exotic vehicles such as subprime adjustable rate mortgages (ARM) and world financial markets. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9).

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

 

2007

2008

Change to 2008

2009

Change to 2009

A

80,860.2

70,342.9

-10,517.3

71,919.9

-8,940.3

Non
FIN

28,074.5

24,388.3

-3,686.2

23,399.0

-4,675.5

RE

23,265.0

19,454.1

-3,810.9

18,442.6

-4,822.4

FIN

52,785.7

45,954.5

-6,831.2

48,520.9

-4,264.8

LIAB

14,396.1

14,296.1

-100.0

14,108.6

-287.5

NW

66,464.0

56,046.8

-10,417.2

57,811.3

-8,652.7

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

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

The apparent improvement in Table IIA-4A is mostly because of increases in valuations of risk financial assets by the carry trade from zero interest rates to leveraged exposures in risk financial assets such as stocks, high-yield bonds, emerging markets, commodities and so on. Zero interest rates also act to increase net worth by reducing debt or liabilities. The net worth of households has become an instrument of unconventional monetary policy by zero interest rates in the theory that increases in net worth increase consumption that accounts for 68.7 percent of GDP in IIIQ2016 (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IIIQ2016, real estate increased in value by $2844.8 billion and financial assets increased $20,355.5 billion for net gain of real estate and financial assets of $23,200.3 billion, explaining most of the increase in net worth of $23,732.1 billion obtained by deducting the increase in liabilities of $513.8 billion from the increase of assets of $22,245.9 billion. Net worth increased from $66,464.0 billion in 2007 to $90,196.1 billion in IIIQ2016 by $23,732.1 billion or 35.7 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 241.428 in Sep 2016 (http://www.bls.gov/cpi/data.htm) or 14.9 percent. Net worth adjusted by CPI inflation increased 18.1 percent from 2007 to IIQ2016. Real estate assets adjusted for CPI inflation fell 2.3 percent from 2007 to IIIQ2016. There are multiple complaints that unconventional monetary policy concentrates income on wealthier individuals because of their holdings of financial assets while the middle class has gained less because of fewer holdings of financial assets and higher share of real estate in family wealth. There is nothing new in these arguments. Interest rate ceilings on deposits and loans have been commonly used. The Banking Act of 1933 imposed prohibition of payment of interest on demand deposits and ceilings on interest rates on time deposits. These measures were justified by arguments that the banking panic of the 1930s was caused by competitive rates on bank deposits that led banks to engage in high-risk loans (Friedman, 1970, 18; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 74-5). The objective of policy was to prevent unsound loans in banks. Savings and loan institutions complained of unfair competition from commercial banks that led to continuing controls with the objective of directing savings toward residential construction. Friedman (1970, 15) argues that controls were passive during periods when rates implied on demand deposit were zero or lower and when Regulation Q ceilings on time deposits were above market rates on time deposits. The Great Inflation or stagflation of the 1960s and 1970s changed the relevance of Regulation Q. Friedman (1970, 26-7) predicted the future:

“The banks have been forced into costly structural readjustments, the European banking system has been given an unnecessary competitive advantage, and London has been artificially strengthened as a financial center at the expense of New York.”

In short, Depression regulation exported the US financial system to London and offshore centers. What is vividly relevant currently from this experience is the argument by Friedman (1970, 27) that the controls affected the most people with lower incomes and wealth who were forced into accepting controlled-rates on their savings that were lower than those that would be obtained under freer markets. As Friedman (1970, 27) argues:

“These are the people who have the fewest alternative ways to invest their limited assets and are least sophisticated about the alternatives.” Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 29 quarters from IIIQ2009 to IIIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIIQ2016 (https://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp3q16_3rd.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 $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2016 would have accumulated to 29.5 percent. GDP in IIIQ2016 would be $19,414.4 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2687.4 billion than actual $16,727.0 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html). US GDP in IIIQ2016 is 13.8 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,727.0 billion in IIIQ2016 or 11.6 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.1081 in Nov 2016. The actual index NSA in Nov 2016 is 103.0759, which is 27.5 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 130.3109 in Nov 2016. The output of manufacturing at 103.0759 in Nov 2016 is 20.9 percent below trend under this alternative calculation.

Table IIA-4A, US, Difference of Balance Sheet of Households and Nonprofit Organizations Billions of Dollars from 2007 to 2011, 2015 and IQ2016

 

Value 2007

Change to 2014

Change to 2015

Change to IIIQ2016

Assets

80,860.2

17,116.3

20,836.6

22,245.9

Nonfinancial

28,074.5

632.2

2,399.1

3,890.3

Real Estate

23,265.0

-64.5

1,501.9

2,844.8

Financial

52,785.7

16,484.1

18,437.5

20,355.5

Liabilities

14,396.1

-163.6

182.7

513.8

Net Worth

66,464.0

17,280.0

20,654.0

23,732.1

Net Worth = Assets – Liabilities

Source: Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and from IVQ1979) to IQ1990 and from IVQ2007 to IIIQ2016 is in Table IIA-5. The data reveal the following facts for the cycles in the 1980s:

  • IVQ1979 to IQ1990. Net worth increased 138.1 percent from IVQ1979 to IQ1990, the all items CPI index increased 67.8 percent from 76.7 in Dec 1979 to 128.7 in Mar 1990 and real net worth increased 41.9 percent.
  • IQ1980 to IVQ1985. Net worth increased 65.4 percent, the all items CPI index increased 36.5 percent from 80.1 in Mar 1980 to 109.3 in Dec 1985 and real net worth increased 21.2 percent.
  • IVQ1979 to IVQ1985. Net worth increased 68.9 percent, the all items CPI index increased 42.5 percent from 76.7 in Dec 1979 to 109.3 in Dec 1985 and real net worth increased 18.5 percent.
  • IQ1980 to IQ1989. Net worth increased 118.0 percent, the all items CPI index increased 52.7 percent from 80.1 in Mar 1980 to 122.3 in Mar 1989 and real net worth increased 42.8 percent.
  • IQ1980 to IIQ1989. Net worth increased 122.2 percent, the all items CPI index increased 54.9 percent from 80.1 in Mar 1980 to 124.1 in Jun 1989 and real net worth increased 43.4 percent.
  • IQ1980 to IIIQ1989. Net worth increased 128.1 percent, the all items CPI index increased 56.1 percent from 80.1 in Mar 1980 to 125.0 in Sep 1989 and real net worth increased 46.2 percent.
  • IQ1980 to IVQ1989. Net worth increased 132.1 percent, the all items CPI index increased 57.4 from 80.1 in Mar 1980 to 126.1 in Dec 1989 and real net worth increased 47.4 percent.
  • IQ1980 to IQ1990. Net worth increased 133.2 percent, the all items CPI indexed increased 60.7 percent from 80.1 in Mar 1980 to 128.7 in Mar 1990 and real net worth increased 45.1 percent.

There is disastrous performance in the current economic cycle:

  • IVQ2007 to IIIQ2016. Net worth increased 35.7 percent, the all items CPI increased 14.9 percent from 210.036 in Dec 2007 to 241.428 in Sep 2016 and real or inflation adjusted net worth increased 18.1 percent. Real estate assets adjusted for inflation fell 2.4 percent. Growth of real net worth at the long-term average of 3.1 percent per year from IVQ1945 to IIIQ2016 would have accumulated to 30.6 percent in the entire cycle from IVQ2007 to IIIQ2016, much higher than actual 18.1 percent.

The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 29 quarters from IIIQ2009 to IIIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIIQ2016 (https://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp3q16_3rd.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 $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2016 would have accumulated to 29.5 percent. GDP in IIIQ2016 would be $19,414.4 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2687.4 billion than actual $16,727.0 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html). US GDP in IIIQ2016 is 13.8 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,727.0 billion in IIIQ2016 or 11.6 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.1081 in Nov 2016. The actual index NSA in Nov 2016 is 103.0759, which is 27.5 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 130.3109 in Nov 2016. The output of manufacturing at 103.0759 in Nov 2016 is 20.9 percent below trend under this alternative calculation.

Table IIA-5, Net Worth of Households and Nonprofit Organizations in Billions of Dollars, IVQ1979 to IIIQ1989 and IVQ2007 to IQ2016

Period IQ1980 to IVQ1989

 

Net Worth of Households and Nonprofit Organizations USD Millions

 

IVQ1979

IQ1980

9,047.8

9,238.6

IVQ1985

IIIQ1986

IVQ1986

IQ1987

IIQ1987

IIIQ1987

IVQ1987

IQ1988

IIQ1988

IIIQ1988

IVQ1988

IQ1989

IIQ1989

IIIQ1989

IVQ1989

IQ1990

15,278.3

16,292.1

16,841.0

17,494.9

17,782.0

18,192.3

18,019.7

18,492.5

18,902.6

19,209.5

19,690.0

20,136.4

20,529.2

21,077.3

21,443.5

21,542.1

∆ USD Billions IVQ1985

IVQ1979 to IQ1990

IQ1980-IVQ1985

IQ1980-IIIQ1986

IQ1980-IVQ1986

IQ1980-IQ1987

IQ1980-IIQ1987

IQ1980-IIIQ1987

IQ1980-IVQ1987

IQ1980-IQ1988

IQ1980-IIQ1988

IQ1980-IIIQ1988

IQ1980-IVQ1988

IQ1980-IQ1989

IQ1980-IIQ1989

IQ1980-IIIQ1989

IQ1980-IVQ1989

IQ1980-IQ1990

+6,230.5  ∆%68.9 R∆%18.5

+12,494.3  ∆%138.1 R∆%41.9

+6,039.7 ∆%65.4 R∆%21.2

+7,053.5 ∆%76.3 R∆%28.2

+7,602.4 ∆%82.3 R∆%32.1

+8,256.3 ∆%89.4 R∆%35.3

+8,543.4 ∆%92.5 R∆%35.8

+8,953.7 ∆%96.9 R∆%37.2

+8781.1 ∆%95.0 R∆%35.4

+9253.9 ∆%100.2 R∆%37.6

+9664.0 ∆%104.6 R∆%38.9

+9970.9 ∆%107.9 R∆%39.0

+10451.4 ∆%113.1 R∆%41.7

+10897.8 ∆%118.0 R∆%42.8

+11,290.6 ∆%122.2 R∆% 43.4

+11,838.7 ∆%128.1 R∆% 46.2

+12,204.9 ∆%132.1 R∆%47.4

+12,303.5 ∆%133.2 R∆%45.1

Period IVQ2007 to IIIQ2016

 

Net Worth of Households and Nonprofit Organizations USD Millions

 

IVQ2007

66,464.0

IIIQ2016

90,196.1

∆ USD Billions

+23,732.1 ∆%35.7 R∆%18.1

Net Worth = Assets – Liabilities. R∆% real percentage change or adjusted for CPI percentage change.

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

Chart IIA-1 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ2007 to IIIQ2016. There is remarkable stop and go behavior in this series with two sharp declines and two standstills in the 28 quarters of expansion of the economy beginning in IIIQ2009. The increase in net worth of households and nonprofit organizations is the result of increases in valuations of risk financial assets and compressed liabilities resulting from zero interest rates. Wealth of households and nonprofits organization increased 18.1 percent from IVQ2007 to IIIQ2016 when adjusting for consumer price inflation.

clip_image029

Chart IIA-1, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ2007 to IIIQ2016

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

Chart IIA-2 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1979 to IQ1990. There are changes in the rates of growth of wealth suggested by the changing slopes but there is smooth upward trend. There was significant financial turmoil during 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 $5657.7 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.65 percent of GDP in a year. The Bureau of Economic Analysis estimates US GDP in 2015 at $18,036.6 billion, such that the bailout would be equivalent to cost to taxpayers of about $477.97 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. Money center banks were under extraordinary pressure from the default of sovereign debt by various emerging nations that represented a large share of their net worth (see Pelaez 1986). Net worth of households and nonprofit organizations increased 138.1 percent from IVQ1979 to IQ1990 and 41.9 percent when adjusting for consumer price inflation. Net worth of households and nonprofit organizations increased 133.2 percent from IQ1980 to IQ1990 and 45.1 percent when adjusting for consumer price inflation.

clip_image030

Chart IIA-2, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1979 to IQ1990

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

Chart IIA-3 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1945 at $802.4 billion to IVQ2015 at $87,118.0 billion or increase of 10,757.2 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 236.525 in Dec 2015 or increase of 1,199.6 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 70 years with inflation-adjusted increase from $44.088 in dollars of 1945 to $373.594 in IIIQ2016 or 747.4 percent. In a simple formula: {[($90196.1.7/$802.4)/(241.428/18.2)-1]100 = 747.4%}. Wealth of households and nonprofit organizations increased from $802.4 billion at year-end 1945 to $90,196.1 billion at the end of IIIQ2016 or 11,140.8 percent. The consumer price index increased from 18.2 in Dec 1945 to 241.428 in Jun 2016 or 1,226.6 percent. Net wealth of households and nonprofit organizations in dollars of 1945 increased from $44.088 in 1945 to $373.594 in IIIQ2016 or 747.4 percent at the average yearly rate of 3.1 percent. US real GDP grew at the average rate of 2.9 percent from 1945 to 2015 (http://www.bea.gov/iTable/index_nipa.cfm). The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIQ2009 caused sharp contraction of net worth of US households and nonprofit organizations. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 70 years when US GDP grew at 2.1 percent on average in the twenty-nine quarters between IIIQ2009 and IIIQ2016 (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html). US GDP was $228.2 billion in 1945 and net worth of households and nonprofit organizations $802.4 billion for ratio of wealth to GDP of 3.52. The ratio of net worth of households and nonprofits of $66,464.0 billion in 2007 to GDP of $14,477.6 billion was 4.59. The ratio of net worth of households and nonprofits of $87,118.0 billion in 2015 to GDP of 18,036.6 billion was 4.83. The final data point in Chart IIA-3 is net worth of household and nonprofit institutions at $90,196.1 billion in IIIQ2016 for increase of 11,140.8 percent relative to $802.4 billion in IVQ1945. CPI adjusted net worth of household and nonprofit institutions increased from $44.088 in IVQ1945 to $373.594 in IIIQ2016 or 747.4 percent at the annual equivalent rate of 3.1 percent.

clip_image031

Chart IIA-3, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1945 to IIIQ2016

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

Table IIA-6 provides percentage changes of nonfinancial domestic sector debt. Households increased debt by 10.5 percent in 2006 but reduced debt from 2010 to 2011. Households have increased debt moderately since 2012. Financial repression by zero fed funds rates or negative interest rates intends to increase debt and reduce savings. Business had not been as exuberant in acquiring debt and has been increasing debt benefitting from historically low costs while increasing cash holdings to around $2 trillion by swelling undistributed profits because of the uncertainty of capital budgeting. The key to growth and hiring consists in creating the incentives for business to invest and hire. States and local government were forced into increasing debt by the decline in revenues but began to contract in IQ2011, decreasing again from IQ2011 to IVQ2011, increasing at 2.1 percent in IIQ2012 and decreasing at 0.2 percent in IIIQ2012 and 2.6 percent in IVQ2012. State and local government increased debt at 1.9 percent in IQ2013 and decreased at 1.1 percent in IIQ2013. State and local government decreased debt at 3.0 percent in IIIQ2013 and at 2.8 percent in IVQ2013. State and local government reduced debt at 1.7 percent in IQ2014 and decreased at 0.4 percent in IIQ2014. State and local government reduced debt at 2.7 percent in IIIQ2014 and increased at 0.7 percent in IVQ2014. State and local government increased debt at 1.8 percent in IQ2015 and increased at 0.2 percent in IIIQ2015. State and local government decreased debt at 1.2 percent in IVQ2015. State and local government increased debt at 0.7 percent in IQ2016 and increased at 2.2 percent in IIQ2016. State and local government increased debt at 0.8 percent in IIIQ2016. Opposite behavior is for the federal government that has been rapidly accumulating debt but without success in the self-assigned goal of promoting economic growth. Financial repression constitutes seigniorage of government debt (http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-financial.html http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-monetary.html).

Table IIA-6, US, Percentage Change of Nonfinancial Domestic Sector Debt

 

Total

Households

Business

State &
Local Govern-ment

Federal

IIIQ2016

5.8

4.0

6.0

0.8

8.2

IIQ2016

4.3

4.3

4.1

2.2

5.0

IQ2016

5.4

2.7

9.4

0.7

5.6

IVQ2015

7.7

3.7

5.4

-1.2

15.4

IIIQ2015

2.7

1.4

5.4

0.2

2.1

IIQ2015

4.4

4.0

7.9

0.5

2.7

IQ2015

2.7

2.1

7.4

1.8

-0.3

IVQ2014

3.5

2.2

6.3

0.7

3.1

IIIQ2014

5.1

2.8

6.5

-2.7

7.9

2015

4.4

2.8

6.7

0.3

5.0

2014

4.3

3.1

6.1

-1.2

5.4

2013

3.8

1.8

4.7

-1.8

6.7

2012

5.0

1.9

4.7

-0.2

10.1

2011

3.5

-0.5

2.8

-1.5

10.8

2010

4.4

-0.4

-0.7

2.4

18.5

2009

3.6

0.5

-4.2

4.4

20.4

2008

5.8

0.0

6.0

1.2

21.4

2007

8.1

7.2

12.4

6.0

4.7

2006

8.4

10.5

9.8

4.4

3.9

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

Table IIA-7 provides wealth of US households and nonprofit organizations since 2005 in billions of current dollars at the end of period, NSA. Wealth fell from $66,464 billion in 2007 to $57,811 billion in 2009 or 13.0 percent and to $63,258 billion in 2011 or 4.8 percent. Wealth increased 35.7 percent from 2007 to IIIQ2016, increasing 18.1 percent after adjustment for inflation, primarily because of bloating financial assets while nonfinancial assets declined/stagnated in real terms.

Table IIA-7, US, Net Worth of Households and Nonprofit Organizations, Billions of Dollars, Amounts Outstanding at End of Period, NSA

Quarter

Net Worth

IIIQ2016

90,196

IIQ2016

88,603

IQ2016

87,765

IVQ2015

87,118

IIIQ2015

85,018

IIQ2015

86,298

IQ2015

85,678

IVQ2014

83,744

IIIQ2014

81,916

IIQ2014

81,605

IQ2014

79,995

IVQ2013

78,773

IIIQ2013

76,049

IIQ2013

73,590

IQ2013

72,088

IVQ2012

69,113

2015

87,118

2014

83,744

2013

78,773

2012

69,113

2011

63,258

2010

61,946

2009

57,811

2008

56,047

2007

66,464

2006

66,184

2005

61,867

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

ESV United States Housing. Data and other information continue to provide depressed conditions in the US housing market in a longer perspective, with recent improvement at the margin. Table IIB-1 shows sales of new houses in the US at seasonally adjusted annual equivalent rate (SAAR). House sales fell in 28 of 71 months from Jan 2011 to Nov 2016 with monthly declines of 5 in 2011, 4 in 2012, 4 in 2013, 6 in 2014, 3 in 2015 and 6 in 2016. In Jan-Apr 2012, house sales increased at the annual equivalent rate of 11.8 percent and at 22.3 percent in May-Sep 2012. There was significant strength in Sep-Dec 2011 with annual equivalent rate of 48.4 percent. Sales of new houses fell 7.0 percent in Oct 2012 with increase of 9.5 percent in Nov 2012. Sales of new houses rebounded 10.8 percent in Jan 2013 with annual equivalent rate of 51.5 percent from Oct 2012 to Jan 2013 because of the increase of 10.8 percent in Jan 2013. New house sales increased at annual equivalent 9.9 percent in Feb-Mar 2013. New house sales weakened, decreasing at 2.3 percent in annual equivalent from Apr to Dec 2013 with significant volatility illustrated by decline of 18.8 percent in Jul 2013 and increase of 11.3 percent in Oct 2013. New house sales fell 1.1 percent in Dec 2013. New house sales increased 1.4 percent in Jan 2014 and fell 5.4 percent in Feb 2014, decreasing 3.1 percent in Mar 2014. New house sales decreased 2.2 percent in Apr 2014 and increased 12.7 percent in May 2014. New house sales fell 8.0 percent in Jun 2014 and decreased 3.4 percent in Jul 2014. New house sales jumped 11.7 percent in Aug 2014 and increased 3.8 percent in Sep 2014. New House sales increased 1.7 percent in Oct 2014 and fell 5.9 percent in Nov 2014. House sales fell at the annual equivalent rate of 2.6 percent in Sep-Nov 2014. New house sales increased 10.3 percent in Dec 2014 and increased 6.5 percent in Jan 2015. Sales of new houses increased 4.8 percent in Feb 2015 and fell 10.7 percent in Mar 2015. House sales increased 2.0 percent in Apr 2015. The annual equivalent rate in Dec 2014-Apr 2015 was 31.6 percent. New house sales increased 1.4 percent in May 2015 and fell 6.9 percent in Jun 2015, increasing 5.5 percent in Jul 2015. New house sales fell at annual equivalent 1.6 percent in May-Jul 2015. New house sales increased 1.4 percent in Aug 2015 and fell 9.5 percent in Sep 2015. New house sales decreased at annual equivalent 40.3 percent in Aug-Sep 2015. New house sales increased 4.6 percent in Oct 2015 and increased 6.3 percent in Nov 2015, increasing 5.9 percent in Dec 2015. New house sales increased at the annual equivalent rate of 92.2 percent in Oct-Dec 2015. New house sales decreased 2.2 percent in Jan 2016 at the annual equivalent rate of minus 23.4 percent. New house sales decreased 0.2 percent in Feb 2016 and increased 2.3 percent in Mar 2016. New house sales jumped at 6.1 percent in Apr 2016. New house sales increased at the annual equivalent rate of 37.7 percent in Feb-Apr 2016. New house sales decreased 0.7 percent in May 2016 and decreased 1.4 percent in Jun 2016. New house sales jumped 11.5 percent in Aug 2016. New house sales increased at the annual equivalent rate of 42.0 percent in May-Jul 2016. New house sales fell 10.1 percent in Aug 2016 and increased 2.1 percent in Sep 2016, decreasing 1.4 percent in Oct 2016. New house sales fell at the annual equivalent rate of minus 32.9 percent in Aug-Oct 2016. New house sales increased at 5.2 percent in Nov 2016, which is equivalent to 83.7 percent in a year. There are with wide monthly oscillations. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), analyze how builders have provided financial assistance to home buyers, including those short of cash and with weaker credit background, explaining the rise in new home sales and the highest gap between prices of new and existing houses. The 30-year conventional mortgage rate increased from 3.40 on Apr 25, 2013 to 4.58 percent on Aug 22, 2013 (http://www.federalreserve.gov/releases/h15/data.htm), which could also be a factor in recent weakness with improvement after the rate fell to 4.26 in Nov 2013. The conventional mortgage rate rose to 4.48 percent on Dec 26, 2013 and fell to 4.32 percent on Jan 30, 2014. The conventional mortgage rate increased to 4.37 percent on Feb 26, 2014 and 4.40 percent on Mar 27, 2014. The conventional mortgage rate fell to 4.14 percent on Apr 22, 2014, stabilizing at 4.14 on Jun 26, 2014. The conventional mortgage rate stood at 3.93 percent on Aug 20, 2015 and at 3.91 percent on Sep 17, 2015. The conventional mortgage rate was at 3.79 percent on Oct 22, 2015. The conventional mortgage rate was 3.97 percent on Nov 20, 2015. The conventional mortgage rate was 3.97 percent on Dec 18, 2015, and 3.92 percent on Jan 14, 2016. The conventional mortgage rate was 3.65 percent on Feb 19, 2016. The commercial mortgage rate was 3.73 percent on Mar 17, 2016 and 3.59 percent on Apr 21, 2016. The conventional mortgage rate was 3.58 on May 19, 2016. The conventional mortgage rate was 3.54 percent on Jun 19, 2016 and 3.45 percent on Jul 21, 2016. The conventional mortgage rate was 3.43 percent on Aug 18, 2016 and 3.48 percent on Sep 22, 2016. The conventional mortgage rate was 3.94 on Nov 17, 2016 and 4.30 percent on Dec 22. The conventional mortgage rate measured in a survey by Freddie Mac (http://www.freddiemac.com/pmms/ http://www.freddiemac.com/pmms/abtpmms.htm) is the “interest rate a lender would charge to lend mortgage money to a qualified borrower.”

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

 

SA Annual Rate
Thousands

∆%

Nov 2016

592

5.2

AE ∆% Nov

 

83.7

Oct

563

-1.4

Sep

571

2.1

Aug

559

-10.1

AE ∆% Aug-Oct

 

-32.9

Jul

622

11.5

Jun

558

-1.4

May

566

-0.7

AE ∆% May-Jul

 

42.0

Apr

570

6.1

Mar

537

2.3

Feb

525

-0.2

AE ∆% Feb-Apr

 

37.7

Jan

526

-2.2

AE ∆% Jan

 

-23.4

Dec 2015

538

5.9

Nov

508

6.3

Oct

478

4.6

AE ∆% Oct-Dec

 

92.2

Sep

457

-9.5

Aug

505

1.4

AE ∆% Aug-Sep

 

-40.3

Jul

498

5.5

Jun

472

-6.9

May

507

1.4

AE ∆% May-Jul

 

-1.6

Apr

500

2.0

Mar

490

-10.7

Feb

549

4.8

Jan

524

6.5

Dec 2014

492

10.3

AE ∆% Dec-Apr

 

31.6

Nov

446

-5.9

Oct

474

1.7

Sep

466

3.8

AE ∆% Sep-Nov

 

-2.6

Aug

449

11.7

Jul

402

-3.4

Jun

416

-8.0

May

452

12.7

Apr

401

-2.2

Mar

410

-3.1

Feb

423

-5.4

Jan

447

1.4

AE ∆% Jan-Aug

 

2.6

Dec 2013

441

-1.1

Nov

446

0.5

Oct

444

11.3

Sep

399

5.0

Aug

380

1.1

Jul

376

-18.8

Jun

463

7.7

May

430

-4.7

Apr

451

0.4

AE ∆% Apr-Dec

 

-2.3

Mar

449

2.3

Feb

439

-0.7

AE ∆% Feb-Mar

 

9.9

Jan

442

10.8

Dec 2012

399

1.8

Nov

392

9.5

Oct

358

-7.0

AE ∆% Oct-Jan

 

51.5

Sep

385

2.7

Aug

375

1.6

Jul

369

2.5

Jun

360

-2.7

May

370

4.5

AE ∆% May-Sep

 

22.3

Apr

354

0.0

Mar

354

-3.3

Feb

366

9.3

Jan

335

-1.8

AE ∆% Jan-Apr

 

11.8

Dec 2011

341

4.0

Nov

328

3.8

Oct

316

3.9

Sep

304

1.7

AE ∆% Sep-Dec

 

48.4

Aug

299

1.0

Jul

296

-1.7

Jun

301

-1.3

May

305

-1.6

AE ∆% May-Aug

 

-10.3

Apr

310

3.3

Mar

300

11.1

Feb

270

-12.1

Jan

307

-5.8

AE ∆% Jan-Apr

 

-14.2

Dec 2010

326

13.6

AE: Annual Equivalent

Source: US Census Bureau

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

The depressed level of residential construction and new house sales in the US is evident in Table IIB-3 providing new house sales not seasonally adjusted in Jan-Nov of various years. Sales of new houses are higher in Jan-Nov 2016 relative to Jan-Nov 2015 with increase of 12.7 percent. Sales of new houses are higher in Jan-Nov 2016 relative to Jan-Nov 2014 with increase of 29.2 percent. Sales of new houses in Jan-Nov 2016 are substantially lower than in many years between 1971 and 2016 with the exception of the years from 2008 to 2015. There are only six other increases of 31.2 percent relative to Jan-Nov 2013, 53.1 percent relative to Jan-Nov 2012, 85.8 percent relative to Jan-Nov 2011, 74.6 percent relative to Jan-Nov 2010, 49.1 percent relative to Jan-Nov 2009 and 13.7 percent relative to Jan-Nov 2008. Sales of new houses in Jan-Nov 2016 are lower by 28.7 percent relative to Jan-Nov 2007, 46.8 percent relative to 2006, 56.4 percent relative to 2005 and 53.4 percent relative to 2004. The housing boom peaked in 2005 and 2006 when increases in fed funds rates to 5.25 percent in Jun 2006 from 1.0 percent in Jun 2004 affected subprime mortgages that were programmed for refinancing in two or three years on the expectation that price increases forever would raise home equity. Higher home equity would permit refinancing under feasible mortgages incorporating full payment of principal and interest (Gorton 2009EFM; see other references in http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Sales of new houses in Jan-Jul 2016 relative to the same period in 2003 fell 48.5 percent and 42.1 percent relative to the same period in 2002. Similar percentage declines are also for 2016 relative to years from 2000 to 2004. Sales of new houses in Jan-Nov 2016 fell 15.8 per cent relative to the same period in 1995. The population of the US was 179.3 million in 1960 and 281.4 million in 2000 (Hobbs and Stoops 2002, 16). Detailed historical census reports are available from the US Census Bureau at (http://www.census.gov/population/www/censusdata/hiscendata.html). The estimate of the US population is 418.8 million in 2015. The US population increased by 133.6 percent from 1960 to 2015. The final row of Table IIB-3 reveals catastrophic data: sales of new houses in Jan-Nov 2016 of 522 thousand units are lower by 3.0 percent relative to 538 thousand units of houses sold in Jan-Nov 1965, which is two years after data become available. The civilian noninstitutional population increased from 122.416 million in 1963 to 250.801 million in 2015, or 104.9 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

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

 

Not Seasonally Adjusted Thousands

Jan-Nov 2016

522

Jan-Nov 2015

463

∆% Jan-Nov 2016/Jan-Nov 2015

12.7

Jan-Nov 2014

404

∆% Jan-Nov 2016/Jan-Nov 2014

29.2

Jan-Nov 2013

398

∆% Jan-Nov 2016/Jan-Nov 2013

31.2

Jan-Nov 2012

341

∆% Jan-Nov 2016/Jan-Nov 2012

53.1

Jan-Nov 2011

281

∆% Jan-Nov 2016/Jan-Nov 2011

85.8

Jan-Nov 2010

299

∆% Jan-Nov 2016/ 
Jan-Nov 2010

74.6

Jan-Nov 2009

350

∆% Jan-Nov 2016/ 
Jan-Nov 2009

49.1

Jan-Nov 2008

459

∆% Jan-Nov 2016/ 
Jan-Nov 2008

13.7

Jan-Nov 2007

732

∆% Jan-Nov 2016/
Jan-Nov 2007

-28.7

Jan-Nov 2006

981

∆% Jan-Nov 2016/Jan-Nov 2006

-46.8

Jan-Nov 2005

1196

∆% Jan-Nov 2016/Jan-Nov 2005

-56.4

Jan-Nov 2004

1120

∆% Jan-Nov 2016/Jan-Nov 2004

-53.4

Jan-Nov 2003

1013

∆% Jan-Nov 2016/
Jan-Nov  2003

-48.5

Jan-Nov 2002

902

∆% Jan-Nov 2016/
Jan-Nov 2002

-42.1

Jan-Nov 2001

843

∆% Jan-Nov 2016/
Jan-Nov 2001

-38.1

Jan-Nov 2000

812

∆% Jan-Nov 2016/
Jan-Nov 2000

-35.7

Jan-Nov 1995

620

∆% Jan-Nov 2016/
Jan-Nov 1995

-15.8

Jan-Nov 1965

538

∆% Jan-Nov 2016/
Jan-Nov 1965

-3.0

*Computed using unrounded data

Source: US Census Bureau

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

Chart IIB-2 of the US Bureau of the Census provides the entire monthly sample of new houses sold in the US between Jan 1963 and Nov 2016 without seasonal adjustment. The series is almost stationary until the 1990s. There is sharp upward trend from the early 1990s to 2005-2006 after which new single-family houses sold collapse to levels below those in the beginning of the series.

clip_image032

Chart IIB-2, US, New Single-family Houses Sold, NSA, 1963-2016

Source: US Census Bureau

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

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017.

No comments:

Post a Comment