Rising Yields and Dollar Revaluation, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Private Fixed Investment, Swelling Undistributed Corporate Profits, Stagnating Real Disposable Income per Capita, Financial Repression, Twenty Four Million Unemployed or Underemployed, Insufficient Job Creation, Stagnating Real Wages, World Cyclical Slow Growth and Global Recession Risk: Part I

 

Rising Yields and Dollar Revaluation, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Private Fixed Investment, Swelling Undistributed Corporate Profits, Stagnating Real Disposable Income per Capita, Financial Repression, Twenty Four Million Unemployed or Underemployed, Insufficient Job Creation, Stagnating Real Wages, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

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

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

IA Mediocre Cyclical United States Economic Growth

IA1 Stagnating Real Private Fixed Investment

IA2 Swelling Undistributed Corporate Profits

II Stagnating Real Disposable Income and Consumption Expenditures

IB1 Stagnating Real Disposable Income and Consumption Expenditures

IB2 Financial Repression

I Twenty Four Million Unemployed or Underemployed

IA1 Summary of the Employment Situation

IA2 Number of People in Job Stress

IA3 Long-term and Cyclical Comparison of Employment

IA4 Job Creation

IB Stagnating Real Wages

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

ESIV Stagnating Real Private Fixed Investment

ESV Swelling Undistributed Corporate Profits

ESVI Twenty-four Million Unemployed or Underemployed

ESVII Job Creation

ESVIII Stagnating Real Wages

ESVIII Stagnating Real Disposable Income

ESIX Financial Repression

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 18^th 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/2016/11/dollar-revaluation-and-valuations-of.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/dollar-revaluation-world-inflation.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.
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 r^e the expected rate of interest. The rates are expressed as proportions. The price of the consol is the inverse of the interest rate, (1+r^e). Thus, g = [(r/r^e) – 1]. The critical analysis of Tobin is that at extremely low interest rates there is only expectation of interest rate increases, that is, dr^e>0, such that there is expectation of capital losses on the consol, dg<0. Investors move into positions combining only cash and no consols. Valuations of risk financial assets would collapse in reversal of long positions in carry trades with short exposures in a flight to cash. There is no exit from a central bank created liquidity trap without risks of financial crash and another global recession. The net worth of the economy depends on interest rates. In theory, “income is generally defined as the amount a consumer unit could consume (or believe that it could) while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is a flow that is obtained by applying a rate of return, r, to a stock of wealth, W, or Y = rW (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 49.1 percent relative to the dollar from the high on Jul 15, 2008 to Dec 2, 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 49.1 percent relative to the dollar from the high on Jul 15, 2008 to Dec 2, 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?

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/

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

*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 1.0616/EUR on Nov 25, 2015 to USD 1.0595/EUR on Nov 25, 2016 or 0.2 percent. The euro has devalued 49.1 percent relative to the dollar from the high on Jul 15, 2008 to Dec 2, 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 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 $133.8 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 $112.7 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 $18.8 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 $93.9 billion in IIIQ2016. Undistributed corporate profits swelled 246.2 percent from $107.7 billion in IQ2007 to $372.9 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. 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.”

Chart VIII-2, Exchange Rate of US Dollars (USD) per Euro (EUR), Nov 25, 2015 to Nov 25, 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 1, 2016 to 2.45 percent on Dec 1, 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.

Chart VIII-3, Yield of Ten-year Constant Maturity Treasury, Sep 1, 2016 to Dec 1, 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 1, 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.

Chart S, US, Yield of Two-Year Treasury Constant Maturity, Mar 17, 2014 to Dec 1, 2016 

Source: Board of Governors of the Federal Reserve System

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

Chart SA, US, Yield of Seven-Year, Ten-Year and Thirty-Year Treasury Constant Maturity, Mar 17, 2014 to Dec 1, 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.

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 Aug 2016 to Oct 2016, CPI inflation for all items seasonally adjusted was 3.7 percent in annual equivalent, obtained by calculating accumulated inflation from Aug 2016 to Oct 2016 and compounding for a full year. In the 12 months ending in Oct 2016, CPI inflation of all items not seasonally adjusted was 1.6 percent. Inflation in Oct 2016 seasonally adjusted was 0.4 percent relative to Oct 2016, or 4.9 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, 2.0 percent in annual equivalent Aug 2016-Oct 2016 and 0.1 percent in Oct 2016 or 1.2 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 0.330 percent for one month, 0.477 percent for three months, 0.608 percent for six months, 0.768 percent for one year, 1.100 percent for two years, 1.378 percent for three years, 1.824 percent for five years, 2.178 percent for seven years, 2.387 percent for ten years and 3.065 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 VIII-1, US, Consumer Price Index Percentage Changes 12 months NSA and Annual Equivalent ∆%

	% RI	∆% 12 Months Oct 2016/Oct 2015 NSA	∆% Annual Equivalent Aug 2016 to Oct 2016 SA	∆% Oct 2016/Sep 2016 SA
CPI All Items	100.000	1.6	3.7	0.4
CPI ex Food and Energy	79.137	2.1	2.0	0.1

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 tapering quantitative easing. Table VIII-2 provides the yield curve of Treasury securities on Dec 2, 2016, Dec 31, 2013, May 1, 2013, Dec 2, 2015 and Dec 1, 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 2.40 percent on Dec 2, 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 2.40 percent would jump instantaneously from yield of 2.40 percent on Dec 2, 2016 to 4.43 percent as occurred on Dec 1, 2006 when the economy was closer to full employment. The price of the hypothetical bond issued with coupon of 2.40 percent would drop from 100 to 83.7426 after an instantaneous increase of the yield to 4.43 percent. The price loss would be 16.3 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

	1202/16	12/31/13	5/01/13	12/02/15	12/01/06
1 M	0.34	0.00	0.03	0.19	5.21
3 M	0.49	0.01	0.06	0.21	5.03
6 M	0.61	0.07	0.08	0.42	5.05
1 Y	0.80	0.25	0.11	0.52	4.87
2 Y	1.11	0.56	0.20	0.94	4.52
3 Y	1.40	0.91	0.30	1.23	4.43
5 Y	1.84	1.43	0.65	1.63	4.39
7 Y	2.20	1.80	1.07	1.97	4.39
10 Y	2.40	3.04	1.66	2.18	4.43
20 Y	2.78	3.72	2.44	2.55	4.64
30 Y	3.08	3.96	2.83	2.91	4.54

M: Months; Y: Years

Source: United States Treasury

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

There is a false impression of the existence of a monetary policy “science,” measurements and forecasting with which to steer the economy into “prosperity without inflation.” Market participants are remembering the Great Bond Crash of 1994 shown in Table VI-7G when monetary policy pursued nonexistent inflation, causing trillions of dollars of losses in fixed income worldwide while increasing the fed funds rate from 3 percent in Jan 1994 to 6 percent in Dec. The exercise in Table VI-7G shows a drop of the price of the 30-year bond by 18.1 percent and of the 10-year bond by 14.1 percent. 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). The pursuit of nonexistent deflation during the past ten years has resulted in the largest monetary policy accommodation in history that created the 2007 financial market crash and global recession and is currently preventing smoother recovery while creating another financial crash in the future. The issue is not whether there should be a central bank and monetary policy but rather whether policy accommodation in doses from zero interest rates to trillions of dollars in the fed balance sheet endangers economic stability.

Table VI-7G, Fed Funds Rates, Thirty and Ten Year Treasury Yields and Prices, 30-Year Mortgage Rates and 12-month CPI Inflation 1994

1994	FF	30Y	30P	10Y	10P	MOR	CPI
Jan	3.00	6.29	100	5.75	100	7.06	2.52
Feb	3.25	6.49	97.37	5.97	98.36	7.15	2.51
Mar	3.50	6.91	92.19	6.48	94.69	7.68	2.51
Apr	3.75	7.27	88.10	6.97	91.32	8.32	2.36
May	4.25	7.41	86.59	7.18	88.93	8.60	2.29
Jun	4.25	7.40	86.69	7.10	90.45	8.40	2.49
Jul	4.25	7.58	84.81	7.30	89.14	8.61	2.77
Aug	4.75	7.49	85.74	7.24	89.53	8.51	2.69
Sep	4.75	7.71	83.49	7.46	88.10	8.64	2.96
Oct	4.75	7.94	81.23	7.74	86.33	8.93	2.61
Nov	5.50	8.08	79.90	7.96	84.96	9.17	2.67
Dec	6.00	7.87	81.91	7.81	85.89	9.20	2.67

Notes: FF: fed funds rate; 30Y: yield of 30-year Treasury; 30P: price of 30-year Treasury assuming coupon equal to 6.29 percent and maturity in exactly 30 years; 10Y: yield of 10-year Treasury; 10P: price of 10-year Treasury assuming coupon equal to 5.75 percent and maturity in exactly 10 years; MOR: 30-year mortgage; CPI: percent change of CPI in 12 months

Sources: yields and mortgage rates http://www.federalreserve.gov/releases/h15/data.htm CPI ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.t

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.

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.

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.

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 1.0668 EUR on Dec 2, 2016 or by 10.5 percent {[(1.0668/1.192)-1]100 = -10.5%}. 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 6.8865/USD on Fri Dec 2, 2016, or by 1.0 percent, for cumulative revaluation of 16.8 percent. The final row of Table VI-2 shows: devaluation of 0.9 percent in the week of Nov 11, 2016; devaluation of 1.1 percent in the week of Nov 18, 2016; devaluation of 0.5 percent in the week of Nov 25, 2016; and revaluation of 0.5 percent in the week of Dec 2. 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	12/02/16
Rate	1.1423	1.5914	1.192	1.0668
CNY/USD	01/03 2000	07/21 2005	7/15 2008	12/02/16
Rate	8.2765	8.2765	6.8211	6.8865
Weekly Rates	11/11/2016	11/18/2016	11/25/2016	12/02/16
CNY/USD	6.8151	6.8883	6.9236	6.8865
∆% from Earlier Week*	-0.9	-1.1	-0.5	0.5

*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 Nov 25, 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 6.9176/USD on Nov 25, 2016, which is the last data point in Chart VI-1. Revaluation of the CNY relative to the USD by 16.8 percent by Dec 2, 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.

Chart VI-1, Chinese Yuan (CNY) per US Dollar (USD), Business Days, Jan 3, 1995-Nov 25, 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 Nov 25, 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 6.9176/USD on Nov 25, 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.

Chart VI-1A, Chinese Yuan (CNY) per US Dollar (USD), Business Days, Jan 5, 1981-Nov 25 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 Nov 25, 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 6.9176/USD on Nov 25, 2016, or devaluation of 14.5 percent. The United States Treasury estimates US government debt held by private investors at $10,955 billion in Jun 2016. China’s holding of US Treasury securities represent 10.6 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 $1177.1 billion in Sep 2015 to $1136.4 billion in Sep 2016 or 3.5 percent. The combined holdings of China and Japan in Sep 2016 add to $2293.4 billion, which is equivalent to 20.9 percent of US government marketable interest-bearing securities held by investors of $10,955 billion in Jun 2016 (http://www.fms.treas.gov/bulletin/index.html). Total foreign holdings of Treasury securities increased from $6105.9 billion in Sep 2015 to $6154.7 billion in Sep 2016, or 0.8 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.”

Chart VI-1B, Chinese Yuan (CNY) per US Dollar (US), Business Days, Oct 28, 2011-Nov 25, 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 Nov 18, 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 11.4 percent to USD 1.0595/EUR on Nov 25, 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).

Chart VI-2, US Dollars (USD) per Euro (EUR), Jan 4, 1999 to Nov 25, 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 Nov 25, 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 1, 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. There is concern of declining inflation in the euro area and appreciation of the euro.

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?

Chart VI-3, US Dollar Currency Indexes, Jan 4, 1995-Nov 25, 2016

Source: Board of Governors of the Federal Reserve System

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

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/

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 1, 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 Nov 25, 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 20.6505/USD on Nov 25, 2016.

Chart VI-4A, Mexican Peso (MXN) per US Dollar (USD), Nov 8, 1993 to Nov 25, 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 Nov 25, 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 68.5900/USD on Nov 25, 2016.

Chart VI-4B, Indian Rupee (INR) per US Dollar (USD), Jan 2, 1973 to Nov 25, 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 113.1700/USD on Nov 25, 2016 for appreciation of 8.8 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).

Chart VI-5, Japanese Yen JPY per US Dollars USD, Monthly, Jan 4, 1971-Nov 25, 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 3.4229USD on Nov 25, 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 3.4229/USD on Nov 25, 2016 for depreciation of 122.6 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).

Chart VI-6, Brazilian Real (BRL) per US Dollar (USD) Jan 4, 1999 to Nov 25, 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.

Chart VI-7, Brazilian Real (BRL) per US Dollar (USD), Jan 2, 1995 to Nov 25, 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 i_n be the nominal interest rate, i_r the real or inflation-adjusted interest rate and π^e the expectation of inflation in the time term of the interest rate, which are all expressed as proportions. The following expression provides the relation of real and nominal interest rates and the expectation of inflation:

(1 + i_r) = (1 + i_n)/(1 + π^e) (1)

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

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

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

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

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

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

Focus is shifting from tapering quantitative easing by the Federal Open Market Committee (FOMC). There is sharp distinction between the two measures of unconventional monetary policy: (1) fixing of the overnight rate of fed funds at 0 to ¼ percent; and (2) outright purchase of Treasury and agency securities and mortgage-backed securities for the balance sheet of the Federal Reserve. Markets overreacted to the so-called “paring” of outright purchases to $15 billion of securities per month for the balance sheet of the Fed.

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

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

What is truly important is the fixing of the overnight fed funds at ¼ to ½ percent with gradual consideration of further rate increases (https://www.federalreserve.gov/newsevents/press/monetary/20161102a.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 97.9 percent since the trough of the sovereign debt crisis in Europe on Jul 16, 2010 to Dec 2, 2016; S&P 500 has gained 114.4 percent and DAX 85.4 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 12/02/16” 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 36.1 percent above the trough. Japan’s Nikkei Average is 108.8 percent above the trough. DJ Asia Pacific TSM is 24.6 percent above the trough. Dow Global is 44.4 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 22.4 percent above the trough. NYSE Financial Index is 58.9 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 85.4 percent above the trough. Japan’s Nikkei Average is 108.8 percent above the trough on Aug 31, 2010 and 61.7 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 18,426.08 on Dec 2, 2016 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 79.7 percent higher than 10,254.43 on Mar 11, 2011, on the date of the Tōhoku or Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar appreciated 10.5 percent relative to the euro. The dollar devalued before the new bout of sovereign risk issues in Europe. The column “∆% week to 12/02/16” in Table VI-4 shows

decrease of 0.6 percent in the week for China’s Shanghai Composite. The Nikkei increased 0.2 percent. DJ Asia Pacific changed 0.0 percent. NYSE Financial increased 0.2 percent in the week. Dow Global decreased 0.3 percent in the week of Dec 2, 2016. The DJIA increased 0.1 percent and S&P 500 decreased 1.0 percent. DAX of Germany decreased 1.7 percent. STOXX 50 decreased 0.9 percent. The USD revalued 0.7 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 12/02/16” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Dec 2, 2016. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 12/02/16” but also relative to the peak in column “∆% Peak to 12/02/16.” There are now several equity indexes above the peak in Table VI-4: DJIA 71.1 percent, S&P 500 80.1 percent, DAX 66.0 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 26.6 percent, Dow Global 17.8 percent, and Nikkei Average 61.7 percent. Shanghai Composite is 2.5 percent above the peak; STOXX 50 is 3.6 percent above the peak; and DJ Asia Pacific TSM is 9.1 percent above the peak. The Shanghai Composite increased 64.3 percent from March 12, 2014, to Dec 2, 2016. The US dollar strengthened 29.5 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 7.4 percent from $2605.2 billion in IVQ2007 to $2,798.1 billion in IIIQ2016. As shown in Table IAI-2, real private fixed investment increased 7.2 percent from $2,586.3 billion of chained 2009 dollars in IVQ2007 to $2,772.4 billion in IIIQ2016. Private fixed investment fell relative to IVQ2007 in all quarters preceding IIQ2014 and fell 0.2 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 $133.8 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 $112.7 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 $18.8 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 $93.9 billion in IIIQ2016. Undistributed corporate profits swelled 246.2 percent from $107.7 billion in IQ2007 to $372.9 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 $133.8 billion in IIIQ2016. Profits from domestic industries increased at $127.4 billion and profits from nonfinancial business increased at $76.5 billion. Profits from the rest of the world increased at $6.4 billion. Total corporate profits with IVA and CCA were $2154.8 billion in IIIQ2016 of which $1740.7 billion from domestic industries, or 80.8 percent of the total, and $414.0 billion, or 19.2 percent, from the rest of the world. Nonfinancial corporate profits of $1247.0 billion account for 57.9 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:

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

declines. Equally, decline in expected revenue from the stock or project, R_τ, causes decline in valuation.

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

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

	Peak	Trough	∆% to Trough	∆% Peak to 12/02/ /16	∆% Week 12/02/16	∆% Trough to 12/02/ 16
DJIA	4/26/ 10	7/2/10	-13.6	71.1	0.1	97.9
S&P 500	4/23/ 10	7/20/ 10	-16.0	80.1	-1.0	114.4
NYSE Finance	4/15/ 10	7/2/10	-20.3	26.6	0.2	58.9
Dow Global	4/15/ 10	7/2/10	-18.4	17.8	-0.3	44.4
Asia Pacific	4/15/ 10	7/2/10	-12.5	9.1	0.0	24.6
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	61.7	0.2	108.8
China Shang.	4/15/ 10	7/02 /10	-24.7	2.5	-0.6	36.1
STOXX 50	4/15/10	7/2/10	-15.3	3.6	-0.9	22.4
DAX	4/26/ 10	5/25/ 10	-10.5	66.0	-1.7	85.4
Dollar Euro	11/25 2009	6/7 2010	21.2	29.5	-0.7	10.5
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	2.389

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 1.0591/EUR in the first row, first column in the block for currencies in Table III-1 for Fri Nov 25, depreciating to USD 1.0613/EUR on Mon Nov 28, 2016, or by 0.2 percent. The dollar depreciated because more dollars, 1.0613, were required on Mon Nov 28 to buy one euro than $1.0591 on Fri Nov 25. 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 1.0591/EUR on Nov 25. 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 Nov 25, to the last business day of the current week, in this case Dec 2, such as depreciation of 0.7 percent to USD 1.0668/EUR by Dec 2. 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 0.7 percent from the rate of USD 1.0591/EUR on Fri Nov 25 to the rate of USD 1.0668/EUR on Dec 2 {[(1.0668/1.0591) - 1]100 = 0.7%}. The dollar depreciated (denoted by negative sign) by 0.1 percent from the rate of USD 1.0662 on

Thu Dec 1 to USD 1.0668/EUR on Fri Dec 2 {[(1.0668/1.0662) -1]100 = 0.1%}. 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 decreasing in the week ending on Dec 2, 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 0.1 percent on Dec 2, increasing 0.1 percent in the week. Germany’s DAX decreased 0.2 percent on Dec 2 and decreased 1.7 percent in the week. Dow Global decreased 0.1 percent on Dec 2 and decreased 0.3 percent in the week. Japan’s Nikkei Average decreased 0.5 percent on Dec 2 and increased 0.2 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 decreased 0.4 percent on Dec 2 and changed 0.0 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 3243.84 on Dec 2, 2016, for decrease of 0.9 percent and decreasing 0.6 percent in the week. The Shanghai Composite increased 64.3 percent from March 12, 2014 to Dec 2, 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 2, 2016. Table III-1 shows that WTI increased 12.2 percent in the week of Dec 2 while Brent increased 15.3 percent in the week with turmoil in oil producing regions but oscillating action by OPEC. Gold increased 0.7 percent on Dec 2 and decreased 0.3 percent in the week.

Table III-I, Weekly Financial Risk Assets Nov 28 to Dec 2, 2016

Fri 25	Mon 28	Tue 29	Wed 30	Thu 1	Fri 2
USD/ EUR 1.0591 0.0% -0.4%	1.0613 -0.2% -0.2%	1.0651 -0.6% -0.4%	1.0590 0.0% 0.6%	1.0662 -0.7% -0.7%	1.0668 -0.7% -0.1%
JPY/ USD 113.22 -2.1% 0.1%	111.94 1.1% 1.1%	112.38 0.7% -0.4%	114.46 -1.1% -1.9%	114.09 -0.8% 0.3%	113.50 -0.3% 0.5%
CHF/ USD 1.0141 -0.4% 0.2%	1.0131 0.1% 0.1%	1.0116 0.2% 0.1%	1.0174 -0.3% -0.6%	1.0108 0.3% 0.6%	1.0106 0.3% 0.0%
CHF/ EUR 1.0740 -0.4% -0.1%	1.0752 -0.1% -0.1%	1.0774 -0.3% -0.2%	1.0774 -0.3% 0.0%	1.0777 -0.3% 0.0%	1.0781 -0.4% 0.0%
USD/ AUD 0.7444 1.3434 1.5% 0.5%	0.7483 1.3364 0.5% 0.5%	0.7485 1.3360 0.6% 0.0%	0.7385 1.3541 -0.8% -1.4%	0.7415 1.3486 -0.4% 0.4%	0.7452 1.3419 0.1% 0.5%
10Y Note 2.358	2.315	2.302	2.368	2.441	2.389
2Y Note 1.115	1.123	1.107	1.123	1.147	1.120
German Bond 2Y -0.74 10Y 0.24	2Y -0.75 10Y 0.21	2Y -0.75 10Y 0.22	2Y -0.72 10Y 0.28	2Y -0.74 10Y 0.37	2Y -0.73 10Y 0.28
DJIA 19152.14 1.5% 0.4%	19097.90 -0.3% -0.3%	19121.60 -0.2% 0.1%	19123.58 -0.1% 0.0%	19191.93 0.2% 0.4%	19170.42 0.1% -0.1%
Dow Global 2466.74 1.6% 0.7%	2456.34 -0.4% -0.4%	2456.41 -0.4% 0.0%	2455.59 -0.5% 0.0%	2460.87 -0.2% 0.2%	2459.09 -0.3% -0.1%
DJ Asia Pacific 1426.75 1.0% 0.6%	1435.88 0.6% 0.6%	1431.47 0.3% -0.3%	1426.43 0.0% -0.4%	1431.49 0.3% 0.4%	1426.14 0.0% -0.4%
Nikkei 18381.22 2.3% 0.3%	18356.89 -0.1% -0.1%	18307.04 -0.4% -0.3%	18308.48 -0.4% 0.0%	18513.12 0.7% 1.1%	18426.08 0.2% -0.5%
Shanghai 3261.94 2.2% 0.6%	3277.00 0.5% 0.5%	3282.92 0.6% 0.2%	3250.03 -0.4% -1.0%	3273.31 0.3% 0.7%	3243.84 -0.6% -0.9%
DAX 10699.27 0.3% 0.1%	10582.67 -1.1% -1.1%	10620.49 -0.7% 0.4%	10640.30 -0.6% 0.2%	10534.05 -1.5% -1.0%	10513.35 -1.7% -0.2%
DJ UBS Comm. NA	NA	NA	NA	NA	NA
WTI $/B 46.06 0.8% -4.0%	47.08 2.2% 2.2%	45.23 -1.8% -3.9%	49.44 7.3% 9.3%	51.06 10.9% 3.3%	51.68 12.2% 1.2%
Brent $/B 47.24 0.8% -3.5%	48.24 2.1% 2.1%	46.38 -1.8% -3.9%	50.47 6.8% 8.8%	53.94 14.2% 6.9%	54.46 15.3% 1.0%
44Gold 1178.2 -2.5% -0.9%	1190.6 1.1% 1.1%	1187.9 0.8% -0.2%	1170.8 -0.6% -1.4%	1166.9 -1.0% -0.3%	1175.1 -0.3% 0.7%

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

The euro has devalued 49.1 percent relative to the dollar from the high on Jul 15, 2008 to Dec 2, 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 9.1 percent from the trough of ₤1.388 on Jan 2, 2009 to ₤1.2727 on Dec 2, 2016 and devalued 57.6 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). Column “Peak” in Table VI-6 shows exchange rates during the crisis year of 2008. There was a flight to safety in dollar-denominated government assets because of the arguments in favor of TARP (Cochrane and Zingales 2009).

Table VI-6, Exchange Rates

	Peak	Trough	∆% P/T	Dec 2, 2016	∆% T Dec 2, 2016	∆% P Dec 2, 2016
EUR USD	7/15 2008	6/7 2010		12/02/16 2016
Rate	1.59	1.192		1.0668
∆%			-33.4		-11.7	-49.1
JPY USD	8/18 2008	9/15 2010		12/02/16 2016
Rate	110.19	83.07		113.50
∆%			24.6		-36.6	-3.0
CHF USD	11/21 2008	12/8 2009		12/02/16 2016
Rate	1.225	1.025		1.0106
∆%			16.3		1.4	17.5
USD GBP	7/15 2008	1/2/ 2009		12/02/16 2016
Rate	2.006	1.388		1.2727
∆%			-44.5		-9.1	-57.6
USD AUD	7/15 2008	10/27 2008		12/02/16 2016
Rate	1.0215	1.6639		0.7452
∆%			-62.9		19.4	-31.4
ZAR USD	10/22 2008	8/15 2010		12/02/16 2016
Rate	11.578	7.238		13.8075
∆%			37.5		-90.8	-19.3
SGD USD	3/3 2009	8/9 2010		12/02/16 2016
Rate	1.553	1.348		1.4193
∆%			13.2		-5.3	8.6
HKD USD	8/15 2008	12/14 2009		12/02/16 2016
Rate	7.813	7.752		7.7558
∆%			0.8		0.0	0.7
BRL USD	12/5 2008	4/30 2010		12/02/16 2016
Rate	2.43	1.737		3.4762
∆%			28.5		-100.1	-43.1
CZK USD	2/13 2009	8/6 2010		12/02/16 2016
Rate	22.19	18.693		25.362
∆%			15.7		-35.7	-14.3
SEK USD	3/4 2009	8/9 2010		12/02/16 2016
Rate	9.313	7.108		9.2119
∆%			23.7		-29.6	1.1
CNY USD	7/20 2005	7/15 2008		12/02/16 2016
Rate	8.2765	6.8211		6.8865	-1.0	16.8
∆%			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 Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend. 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 second estimate of GDP for IIIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp3q16_2nd.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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.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 $2702.3 billion than actual $16,712.1 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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 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 Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 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 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 percent below trend under this alternative calculation.

The economy of the US can be summarized in growth of economic activity or GDP as fluctuating from mediocre growth of 2.5 percent on an annual basis in 2010 to 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014 and 2.6 percent in 2015. The following calculations show that actual growth is around 2.1 percent per year. The rate of growth of 1.2 percent in the entire cycle from 2007 to 2015 is well below 3 percent per year in trend from 1870 to 2010, which the economy of the US always attained for entire cycles in expansions after events such as wars and recessions (Lucas 2011May). Revisions and enhancements of United States GDP and personal income accounts by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) provide important information on long-term growth and cyclical behavior. Table Summary provides relevant data.

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

	GDP
Long-Term
1929-2015	3.2
1947-2015	3.2
Whole Cycles
1980-1989	3.5
2006-2015	1.3
2007-2015	1.2
Cyclical Contractions ∆%
IQ1980 to IIIQ1980, IIIQ1981 to IVQ1982	-4.7
IVQ2007 to IIQ2009	-4.2
Cyclical Expansions Average Annual Equivalent ∆%
IQ1983 to IVQ1985 IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987 IQ1983-IIQ1987 IQ1983-IIIQ1987 IQ1983 to IVQ1987 IQ1983 to IQ1988 IQ1983 to IIQ1988 IQ1983 to IIIQ1988 IQ1983 to IVQ1988 IQ1983 to IQ1989 IQ1983 to IIQ1989 IQ1983 to IIIQ1989 IQ1983 to IVQ1989 IQ1983 to IQ1990	5.9 5.7 5.4 5.2 5.0 5.0 4.9 5.0 4.9 4.9 4.8 4.8 4.8 4.7 4.7 4.5 4.5
First Four Quarters IQ1983 to IVQ1983	7.8
IIIQ2009 to IIIQ2016	2.1
First Four Quarters IIIQ2009 to IIQ2010	2.7
	Real Disposable Income	Real Disposable Income per Capita
Long-Term
1929-2015	3.2	2.0
1947-1999	3.7	2.3
Whole Cycles
1980-1989	3.5	2.6
2006-2015	1.7	0.9

Source: Bureau of Economic Analysis

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

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

1. Average Annual Growth in the Past Nineteen Quarters. GDP growth in the four quarters of 2012, the four quarters of 2013, the four quarters of 2014, the four quarters of Q2015 and the three quarters of 2016 accumulated to 10.0 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IIIQ2016 of $16,712.5 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/19: {[($16,712.5/$15,190.3)^4/19 -1]100 = 2.0 percent}.

2. Average Annual Growth in the Past Four Quarters. GDP growth in the four quarters of IIQ2015 to IIIQ2016 accumulated to 1.6 percent that is equivalent to 1.6 percent in a year. This is obtained by dividing GDP in IIIQ2016 of $16,712.5 billion by GDP in IIIQ2015 of $16,454.9 billion and compounding by 4/4: {[($16,712.5/$16,454.9)^4/4 -1]100 = 1.6%}. The US economy grew 1.6 percent in IIIQ2016 relative to the same quarter a year earlier in IIIQ2015. Growth was at annual equivalent 4.0 percent in IIQ2014 and 5.0 percent IIIQ2014 and only at 2.3 percent in IVQ2014. GDP grew at annual equivalent 2.0 percent in IQ2015, 2.6 percent in IIQ2015, 2.0 percent in IIIQ2015 and 0.9 percent in IVQ2015. GDP grew at annual equivalent 0.8 percent in IQ2016 and at 1.4 percent annual equivalent in IIQ2016. GDP increased at 3.2 percent annual equivalent in IIIQ2016. Another important revelation of the revisions and enhancements is that GDP was flat in IVQ2012, which is in the borderline of contraction, and negative in IQ2014. US GDP fell 0.3 percent in IQ2014. The rate of growth of GDP in the revision of IIIQ2013 is 3.1 percent in seasonally adjusted annual rate (SAAR).

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

	Real GDP, Billions Chained 2009 Dollars	∆% Relative to IVQ2007	∆% Relative to Prior Quarter	∆% over Year Earlier
IVQ2007	14,991.8	NA	0.4	1.9
IVQ2011	15,190.3	1.3	1.1	1.7
IQ2012	15,291.0	2.0	0.7	2.8
IIQ2012	15,362.4	2.5	0.5	2.5
IIIQ2012	15,380.8	2.6	0.1	2.4
IVQ2012	15,384.3	2.6	0.0	1.3
IQ2013	15,491.9	3.3	0.7	1.3
IIQ2013	15,521.6	3.5	0.2	1.0
IIIQ2013	15,641.3	4.3	0.8	1.7
IVQ2013	15,793.9	5.4	1.0	2.7
IQ2014	15,747.0	5.0	-0.3	1.6
IIQ2014	15,900.8	6.1	1.0	2.4
IIIQ2014	16,094.5	7.4	1.2	2.9
IVQ2014	16,186.7	8.0	0.6	2.5
IQ2015	16,269.0	8.5	0.5	3.3
IIQ2015	16,374.2	9.2	0.6	3.0
IIIQ2015	16,454.9	9.8	0.5	2.2
IVQ2015	16,490.7	10.0	0.2	1.9
IQ2016	16,525.0	10.2	0.2	1.6
IIQ2016	16,583.1	10.6	0.4	1.3
IIIQ2016	16,712.5	11.5	0.8	1.6
Cumulative ∆% IQ2012 to IIIQ2016	10.0		10.1
Annual Equivalent ∆%	2.0		2.1

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

Chart GDP of the US Bureau of Economic Analysis provides the rates of growth of GDP at SAAR (seasonally adjusted annual rate) in the 16 quarters from IVQ2012 to IIIQ2016. Growth has been fluctuating.

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

Source: US Bureau of Economic Analysis

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

Characteristics of the four cyclical contractions are in Table I-4 with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.7 percent, which is almost equal to the decline of 4.2 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

Table I-4, US, Number of Quarters, GDP Cumulative Percentage Contraction and Average Percentage Annual Equivalent Rate in Cyclical Contractions   

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	3	-2.4	-0.8
IIIQ1957 to IIQ1958	3	-3.0	-1.0
IVQ1973 to IQ1975	5	-3.1	-0.6
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.5	-0.64
IVQ2007 to IIQ2009	6	-4.2	-0.72

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

Table I-5 shows the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the twenty-nine quarters of the current cyclical expansion from IIIQ2009 to IIIQ2016. In sharp contrast, the average growth rate of GDP was:

• 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986
• 5.4 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986
• 5.2 percent in the first sixteen quarters of expansion from IQ1983 to IVQ1986
• 5.0 percent in the first seventeen quarters of expansion from IQ1983 to IQ1987
• 5.0 percent in the first eighteen quarters of expansion from IQ1983 to IIQ1987
• 4.9 percent in the first nineteen quarters of expansion from IQ1983 to IIIQ1987
• 5.0 percent in the first twenty quarters of expansion from IQ1983 to IVQ1987
• 4.9 percent in the first twenty-first quarters of expansion from IQ1983 to IQ1988
• 4.9 percent in the first twenty-two quarters of expansion from IQ1983 to IIQ1988
• 4.8 percent in the first twenty-three quarters of expansion from IQ1983 to IIIQ1988
• 4.8 percent in the first twenty-four quarters of expansion from IQ1983 to IVQ1988
• 4.8 percent in the first twenty-five quarters of expansion from IQ1983 to IQ1989
• 4.7 percent in the first twenty-six quarters of expansion from IQ1983 to IIQ1989
• 4.7 percent in the first twenty-seven quarters of expansion from IQ1983 to IIIQ1989
• 4.5 percent in the first twenty-eight quarters of expansion from IQ1983 to IVQ1989
• 4.5 percent in the first twenty-nine quarters of expansion from IQ1983 to IQ1990

The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill with annual growth of 2.5 percent in 2010 decelerating to 1.6 percent annual growth in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014 and 2.6 percent in 2015 (http://www.bea.gov/iTable/index_nipa.cfm). The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988, 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. GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the four quarters of 2012, the four quarters of 2013, the four quarters of 2014, the four quarters of Q2015, IQ2016, IIQ2016 and IIIQ2016 accumulated to 10.0 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IIIQ2016 of $16,712.5 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/19: {[($16,712.5/$15,190.3)^4/19 -1]100 = 2.0 percent}.

Table I-5 shows that GDP grew 16.4 percent in the first twenty-nine quarters of expansion from IIIQ2009 to IIIQ2016 at the annual equivalent rate of 2.1 percent.

Table I-5, US, Number of Quarters, Cumulative Growth and Average Annual Equivalent Growth Rate in Cyclical Expansions

	Number of Quarters	Cumulative Growth ∆%	Average Annual Equivalent Growth Rate
IIIQ 1954 to IQ1957	11	12.8	4.5
First Four Quarters IIIQ1954 to IIQ1955	4	7.8
IIQ1958 to IIQ1959	5	10.0	7.9
First Four Quarters IIIQ1958 to IIQ1959	4	9.2
IIQ1975 to IVQ1976	8	8.3	4.1
First Four Quarters IIIQ1975 to IIQ1976	4	6.1
IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987 IQ1983-IIQ1987 IQ1983 to IIIQ1987 IQ1983 to IVQ1987 IQ1983 to IQ1988 IQ1983 to IIQ1988 IQ1983 to IIIQ1988 IQ1983 to IVQ1988 IQ1983 to IQ1989 IQ1983 to IIQ1989 IQ1983 to IIIQ1989 IQ1983 to IVQ1989 IQ1983 to IQ1990	13 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29	19.9 21.6 22.3 23.1 24.5 25.6 27.7 28.4 30.1 30.9 32.6 34.0 35.0 36.0 36.3 37.8	5.7 5.4 5.2 5.0 5.0 4.9 5.0 4.9 4.9 4.8 4.8 4.8 4.7 4.7 4.5 4.5
First Four Quarters IQ1983 to IVQ1983	4	7.8
Average First Four Quarters in Four Expansions*		7.7
IIIQ2009 to IIIQ2016	29	16.4	2.1
First Four Quarters IIIQ2009 to IIQ2010		2.7

*First Four Quarters: 7.8% IIIQ1954-IIQ1955; 9.2% IIIQ1958-IIQ1959; 6.1% IIIQ1975-IQ1976; 7.8% IQ1983-IVQ1983

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

As shown in Tables I-4 and I-5 above the loss of real GDP in the US during the contraction was 4.2 percent but the gain in the cyclical expansion has been only 16.4 percent (first to the last row in Table I-5), using all latest revisions. As a result, the level of real GDP in IIIQ2016 with the second estimate and revisions is higher by only 11.5 percent than the level of real GDP in IVQ2007.

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 $2702.3 billion than actual $16,712.1 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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 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 Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 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 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 percent below trend under this alternative calculation.

Table I-6 shows that the contraction actually concentrated in two quarters: decline of 2.1 percent in IVQ2008 relative to the prior quarter and decline of 1.4 percent in IQ2009 relative to IVQ2008. The combined fall of GDP in IVQ2008 and IQ2009 was 3.5 percent {[(1-0.021) x (1-0.014) -1]100 = -3.5%}, or {[(IQ2009 $14,375.0)/(IIIQ2008 $14,891.6) – 1]100 = -3.5%} except for rounding. Those two quarters coincided with the worst effects of the financial crisis (Cochrane and Zingales 2009). GDP fell 0.1 percent in IIQ2009 but grew 0.3 percent in IIIQ2009, which is the beginning of recovery in the cyclical dates of the NBER. Most of the recovery occurred in five successive quarters from IVQ2009 to IVQ2010 of growth of 1.0 percent in IVQ2009, 0.4 percent in IQ2010, 1.0 percent in IIQ2010 and nearly equal growth at 0.7 percent in IIIQ2010 and 0.6 percent in IVQ2010 for cumulative growth in those five quarters of 3.8 percent, obtained by accumulating the quarterly rates {[(1.01 x 1.004 x 1.01 x 1.007 x 1.006) – 1]100 = 3.8%} or {[(IVQ2010 $14,939.0)/(IIIQ2009 $14,402.5) – 1]100 = 3.7%} with minor rounding difference. The economy then stalled during the first half of 2011 with decline of 0.4 percent in IQ2011 and growth of 0.7 percent in IIQ2011 for combined annual equivalent rate of 0.6 percent {(0.996 x 1.007)²}. The economy grew 0.2 percent in IIIQ2011 for annual equivalent growth of 0.7 percent in the first three quarters {[(0.996 x 1.007 x 1.002)^4/3 -1]100 = 0.7%}. Growth picked up in IVQ2011 with 1.1 percent relative to IIIQ2011. Growth in a quarter relative to a year earlier in Table I-6 slows from over 2.7 percent during three consecutive quarters from IIQ2010 to IVQ2010 to 1.9 percent in IQ2011, 1.7 percent in IIQ2011, 1.2 percent in IIIQ2011 and 1.7 percent in IVQ2011. As shown below, growth of 1.1 percent in IVQ2011 was partly driven by inventory accumulation. In IQ2012, GDP grew 0.7 percent relative to IVQ2011 and 2.8 percent relative to IQ2011, decelerating to 0.5 percent in IIQ2012 and 2.5 percent relative to IIQ2011 and 0.1 percent in IIIQ2012 and 2.4 percent relative to IIIQ2011. Growth was 0.0 percent in IVQ2012 with 1.3 percent relative to a year earlier but mostly because of deduction of 1.54 percentage points of inventory divestment and 0.42 percentage points of reduction of one-time national defense expenditures. Growth was 0.7 percent in IQ2013 and 1.3 percent relative to IQ2012 in large part because of burning savings to consume caused by financial repression of zero interest rates. There is similar growth of 0.2 percent in IIQ2013 and 1.0 percent relative to a year earlier. In IIIQ2013, GDP grew 0.8 percent relative to the prior quarter and 1.7 percent relative to the same quarter a year earlier with inventory accumulation contributing 1.60 percentage points to growth at 3.1 percent SAAR in IIIQ2013. GDP increased 1.0 percent in IVQ2013 and 2.7 percent relative to a year earlier. GDP fell 0.3 percent in IQ2014 and grew 1.6 percent relative to a year earlier. Inventory divestment deducted 1.89 percentage points from GDP growth in IQ2014. GDP grew 1.0 percent in IIQ2014, 2.4 percent relative to a year earlier and at 4.0 SAAR with inventory change contributing 0.67 percentage points. GDP grew 1.2 percent in IIIQ2014 and 2.9 percent relative to a year earlier. GDP grew 0.6 percent in IVQ2014 and 2.5 percent relative to a year earlier. GDP increased 0.5 percent in IQ2015 and increased 3.3 percent relative to a year earlier partly because of low level during contraction of 0.3 percent in IQ2014. GDP grew 0.6 percent in IIQ2015 and 3.0 percent relative to a year earlier. GDP grew 0.5 percent in IIIQ2015 and 2.2 percent relative to a year earlier. GDP grew 0.2 percent in IVQ2015 and increased 1.9 percent relative to a year earlier. GDP grew 0.2 percent in IQ2016 and increased 1.6 percent relative to a year earlier. GDP grew 0.4 percent in IIQ2016 and increased 1.3 percent relative to a year earlier. GDP grew 0.8 percent in IIIQ2016 and increased 1.6 percent relative to a year earlier. Rates of a quarter relative to the prior quarter capture better deceleration of the economy than rates on a quarter relative to the same quarter a year earlier. The critical question for which there is not yet definitive solution is whether what lies ahead is continuing growth recession with the economy crawling and unemployment/underemployment at extremely high levels or another contraction or conventional recession. Forecasts of various sources continued to maintain high growth in 2011 without taking into consideration the continuous slowing of the economy in late 2010 and the first half of 2011. The sovereign debt crisis in the euro area and growth in China are common sources of doubts on the rate and direction of economic growth in the US. There is weak internal demand in the US with almost no investment and spikes of consumption driven by burning saving because of financial repression in the form of zero interest rates and bloated balance sheet of the Fed.

Table I-6, US, Real GDP and Percentage Change Relative to IVQ2007 and Prior Quarter, Billions Chained 2009 Dollars and ∆%

	Real GDP, Billions Chained 2009 Dollars	∆% Relative to IVQ2007	∆% Relative to Prior Quarter	∆% over Year Earlier
IVQ2007	14,991.8	NA	0.4	1.9
IQ2008	14,889.5	-0.7	-0.7	1.1
IIQ2008	14,963.4	-0.2	0.5	0.8
IIIQ2008	14,891.6	-0.7	-0.5	-0.3
IVQ2008	14,577.0	-2.8	-2.1	-2.8
IQ2009	14,375.0	-4.1	-1.4	-3.5
IIQ2009	14,355.6	-4.2	-0.1	-4.1
IIIQ2009	14,402.5	-3.9	0.3	-3.3
IV2009	14,541.9	-3.0	1.0	-0.2
IQ2010	14,604.8	-2.6	0.4	1.6
IIQ2010	14,745.9	-1.6	1.0	2.7
IIIQ2010	14,845.5	-1.0	0.7	3.1
IVQ2010	14,939.0	-0.4	0.6	2.7
IQ2011	14,881.3	-0.7	-0.4	1.9
IIQ2011	14,989.6	0.0	0.7	1.7
IIIQ2011	15,021.1	0.2	0.2	1.2
IVQ2011	15,190.3	1.3	1.1	1.7
IQ2012	15,291.0	2.0	0.7	2.8
IIQ2012	15,362.4	2.5	0.5	2.5
IIIQ2012	15,380.8	2.6	0.1	2.4
IVQ2012	15,384.3	2.6	0.0	1.3
IQ2013	15,491.9	3.3	0.7	1.3
IIQ2013	15,521.6	3.5	0.2	1.0
IIIQ2013	15,641.3	4.3	0.8	1.7
IVQ2013	15,793.9	5.4	1.0	2.7
IQ2014	15,747.0	5.0	-0.3	1.6
IIQ2014	15,900.8	6.1	1.0	2.4
IIIQ2014	16,094.5	7.4	1.2	2.9
IVQ2014	16,186.7	8.0	0.6	2.5
IQ2015	16,269.0	8.5	0.5	3.3
IIQ2015	16,374.2	9.2	0.6	3.0
IIIQ2015	16,454.9	9.8	0.5	2.2
IVQ2015	16,490.7	10.0	0.2	1.9
IQ2016	16,525.0	10.2	0.2	1.6
IIQ2016	16,583.1	10.6	0.4	1.3
IIIQ2016	16,712.5	11.5	0.8	1.6

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

Manufacturing jobs not seasonally adjusted decreased 44,000 from Nov 2015 to
Nov 2016 or at the average monthly rate of minus 3667. There are effects of the weaker economy and international trade together with the yearly adjustment of labor statistics. Industrial production changed 0.0 percent in Oct 2016 and decreased 0.2 percent in Sep 2016 after decreasing 0.1 percent in Aug 2016, with all data seasonally adjusted, as shown in Table I-1. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Apr 1, 2016 (http://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] Total IP is now reported to have increased about 2 1/2 percent per year, on average, from 2011 through 2014 before falling 1 1/2 percent in 2015.[2] Relative to earlier reports, the current rates of change are lower, especially for 2014 and 2015. Total IP is now estimated to have returned to its pre-recession peak in November 2014, six months later than previously estimated. Capacity for total industry is now reported to have increased about 2 percent in 2014 and 2015 after having increased only 1 percent in 2013. Compared with the previously reported estimates, the gain in 2015 is 1/2 percentage point higher, and the gain in 2013 is 1/2 percentage point lower. Industrial capacity is expected to increase 1/2 percent in 2016.” 

Manufacturing fell 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increased 16.0 percent from the trough in Apr 2009 to Dec 2015. Manufacturing grew 19.6 percent from the trough in Apr 2009 to Oct 2016. Manufacturing in Oct 2016 is lower by 7.1 percent relative to the peak in Jun 2007. 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 $2702.3 billion than actual $16,712.1 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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 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 Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 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 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 percent below trend under this alternative calculation.

Table I-13 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 87.0 percent in IIQ2016. Most of US national income is in the form of services. In Nov 2016, there were 146.399 million nonfarm jobs NSA in the US, according to estimates of the establishment survey of the Bureau of Labor Statistics (BLS) (http://www.bls.gov/news.release/empsit.nr0.htm Table B-1). Total private jobs of 123.657 million NSA in Nov 2016 accounted for 84.5 percent of total nonfarm jobs of 146.399 million, of which 12.273 million, or 9.9 percent of total private jobs and 8.4 percent of total nonfarm jobs, were in manufacturing. Private service-providing jobs were 103.879 million NSA in Nov 2016, or 71.0 percent of total nonfarm jobs and 84.0 percent of total private-sector jobs. Manufacturing has share of 10.4 percent in US national income in IIQ2016 and durable goods 6.1 percent, as shown in Table I-13. Most income in the US originates in services. Subsidies and similar measures designed to increase manufacturing jobs will not increase economic growth and employment and may actually reduce growth by diverting resources away from currently employment-creating activities because of the drain of taxation.

Table I-13, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total

	SAAR IIQ2016	% Total	SAAR IIIQ2016	% Total
National Income WCCA	15,905.5	100.0	16,184.5	100.0
Domestic Industries	15,697.6	98.7	15,975.6	98.7
Private Industries	13,843.4	87.0	14,101.4	87.1
Agriculture	123.9	0.8
Mining	187.7	1.2
Utilities	164.9	1.0
Construction	765.2	4.8
Manufacturing	1658.4	10.4
Durable Goods	972.8	6.1
Nondurable Goods	685.6	4.3
Wholesale Trade	920.7	5.8
Retail Trade	1118.6	7.0
Transportation & WH	495.7	3.1
Information	578.8	3.6
Finance, Insurance, RE	2807.8	17.7
Professional & Business Services	2246.5	14.1
Education, Health Care	1633.0	10.3
Arts, Entertainment	675.1	4.2
Other Services	467.1	2.9
Government	1854.3	11.7	1874.3	11.6
Rest of the World	207.8	1.3	208.8	1.3

Notes: SSAR: Seasonally-Adjusted Annual Rate; WCCA: Without Capital Consumption Adjustment by Industry; WH: Warehousing; RE, includes rental and leasing: Real Estate; Art, Entertainment includes recreation, accommodation and food services; BS: business services

Source: US Bureau of Economic Analysis

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

ESIV Stagnating Real Private Fixed Investment. The United States economy has grown at the average yearly rate of 3 percent per year and 2 percent per year in per capita terms from 1870 to 2010, as measured by Lucas (2011May). An important characteristic of the economic cycle in the US has been rapid growth in the initial phase of expansion after recessions. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design. 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 second estimate of GDP for IIIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp3q16_2nd.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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.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 $2702.3 billion than actual $16,712.1 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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 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 Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 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 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 percent below trend under this alternative calculation.

Table IA1-1 provides quarterly seasonally adjusted annual rates (SAAR) of growth of private fixed investment for the recessions of the 1980s and the current economic cycle. In the cyclical expansion beginning in IQ1983 (http://www.nber.org/cycles.html), real private fixed investment in the United States grew at the average annual rate of 14.7 percent in the first eight quarters from IQ1983 to IVQ1984. Growth rates fell to an average of 2.2 percent in the following eight quarters from IQ1985 to IVQ1986 and to an average of 1.9 percent in the 12 quarters of 1985, 1986 and 1987. The average rate of growth in the four quarters of 1988 was 3.7 percent. There were only four quarters of contraction of private fixed investment from IQ1983 to IVQ1987. The National Bureau of Economic Research dates another cycle from Jul 1990 (IIIQ1981) to Mar 1991 (IQ1991) (http://www.nber.org/cycles.html), showing in Table III-1 with contractions of fixed investment in the final three quarters of 1990. There is quite different behavior of private fixed investment in the twenty-nine quarters of cyclical expansion from IIIQ2009 to IIIQ2016. The average annual growth rate in the first eight quarters of expansion from IIIQ2009 to IIQ2011 was 3.2 percent, which is significantly lower than 14.7 percent in the first eight quarters of expansion from IQ1983 to IVQ1984. There is only strong growth of private fixed investment in the four quarters of expansion from IIQ2011 to IQ2012 at the average annual rate of 12.5 percent. Growth has fallen from the SAAR of 17.3 percent in IIIQ2011 to 0.1 percent in IIIQ2012, recovering to 6.9 percent in IVQ2012 and increasing to 7.0 percent in IQ2013. The SAAR of fixed investment fell to 2.9 percent in IIIQ2013 and to 6.6 percent in IVQ2013. The SAAR of fixed investment decreased to 5.3 percent in IQ2014. Fixed investment grew at the SAAR of 7.2 percent in IIQ2014 and at 7.4 percent in IIIQ2014. Fixed investment grew at 1.3 percent in IVQ2014, 3.7 percent in IQ2015 and 4.3 percent in IIQ2015. Fixed investment grew at 5.7 percent in IIIQ2015 and fell at 0.2 percent in IVQ2015. Fixed investment contracted at 0.9 percent in IQ2016 and fell at 1.1 percent in IIQ2016. Fixed investment contracted at 0.9 percent in IIIQ2016. Sudeep Reddy and Scott Thurm, writing on “Investment falls off a cliff,” on Nov 18, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324595904578123593211825394.html?mod=WSJPRO_hpp_LEFTTopStories) analyze the decline of private investment in the US and inform that a review by the Wall Street Journal of filing and conference calls finds that 40 of the largest publicly traded corporations in the US have announced intentions to reduce capital expenditures in 2012.

Table IA1-1, US, Quarterly Growth Rates of Real Private Fixed Investment, % Annual Equivalent SA

Q	1981	1982	1983	1984	2008	2009	2010
I	3.8	-12.2	9.4	13.1	-7.1	-27.4	0.8
II	3.2	-12.1	16.0	16.6	-5.5	-14.2	13.6
III	0.1	-9.3	24.4	8.2	-12.1	-0.5	-0.4
IV	-1.5	0.2	24.3	7.3	-23.9	-2.8	8.5
				1985			2011
I				3.7			-0.9
II				5.2			8.2
III				-1.6			17.3
IV				7.8			9.9
				1986			2012
I				1.1			14.7
II				0.1			6.9
III				-1.8			0.1
IV				3.1			6.9
				1987			2013
I				-6.7			7.0
II				6.3			4.3
III				7.1			2.9
IV				-0.2			6.6
				1988			2014
I				0.2			5.3
II				8.1			7.2
III				1.9			7.4
IV				4.8			1.3
				1989			2015
IQ				3.6			3.7
IIQ				0.5			4.3
IIIQ				7.2			5.7
IVQ				-5.0			-0.2
				1990			2016
IQ				4.8			-0.9
IIQ				-7.7			-1.1
IIIQ				-3.3			-0.9
IVQ				-9.8

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

Chart IA1-1 of the US Bureau of Economic Analysis (BEA) provides seasonally adjusted annual rates of growth of real private fixed investment from 1981 to 1989. Growth rates recovered sharply during the first eight quarters, which was essential in returning the economy to trend growth and eliminating unemployment and most underemployment accumulated during the contractions.

Chart IA1-1, US, Real Private Fixed Investment, Seasonally-Adjusted Annual Rates Percent Change from Prior Quarter, 1980-1989

Source: US Bureau of Economic Analysis

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

Weak behavior of real private fixed investment from 2007 to 2016 is in Chart IA1-2. Growth rates of real private fixed investment were much lower during the initial phase of the current economic cycle and have entered sharp trend of decline.

Chart IA1-2, US, Real Private Fixed Investment, Seasonally-Adjusted Annual Rates Percent Change from Prior Quarter, 2007-2016

Source: US Bureau of Economic Analysis

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

Table IA1-2 provides real private fixed investment at seasonally adjusted annual rates from IVQ2007 to IIQ2016 or for the complete economic cycle. The first column provides the quarter, the second column percentage change relative to IVQ2007, the third column the quarter percentage change in the quarter relative to the prior quarter and the final column percentage change in a quarter relative to the same quarter a year earlier. 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 7.4 percent from $2605.2 billion in IVQ2007 to $2,798.1 billion in IIIQ2016. As shown in Table IAI-2, real private fixed investment increased 7.2 percent from $2,586.3 billion of chained 2009 dollars in IVQ2007 to $2,772.4 billion in IIIQ2016. Private fixed investment fell relative to IVQ2007 in all quarters preceding IIQ2014 and fell 0.2 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.

Table IA1-2, US, Real Private Fixed Investment and Percentage Change Relative to IVQ2007 and Prior Quarter, Billions of Chained 2009 Dollars and ∆%

	Real PFI, Billions Chained 2009 Dollars	∆% Relative to IVQ2007	∆% Relative to Prior Quarter	∆% over Year Earlier
IVQ2007	2586.3	NA	-0.9	-1.4
IQ2008	2539.1	-1.8	-1.8	-3.0
IIQ2008	2503.4	-3.2	-1.4	-4.6
IIIQ2008	2424.1	-6.3	-3.2	-7.1
IV2008	2263.8	-12.5	-6.6	-12.5
IQ2009	2089.3	-19.2	-7.7	-17.7
IIQ2009	2011.0	-22.2	-3.7	-19.7
IIIQ2009	2008.4	-22.3	-0.1	-17.1
IVQ2009	1994.1	-22.9	-0.7	-11.9
IQ2010	1997.9	-22.8	0.2	-4.4
IIQ2010	2062.8	-20.2	3.2	2.6
IIIQ2010	2060.8	-20.3	-0.1	2.6
IVQ2010	2103.1	-18.7	2.1	5.5
IQ2011	2098.4	-18.9	-0.2	5.0
IIQ2011	2140.2	-17.2	2.0	3.8
IIIQ2011	2227.5	-13.9	4.1	8.1
IVQ2011	2280.6	-11.8	2.4	8.4
IQ2012	2360.4	-8.7	3.5	12.5
IIQ2012	2399.8	-7.2	1.7	12.1
IIIQ2012	2400.4	-7.2	0.0	7.8
IVQ2012	2441.0	-5.6	1.7	7.0
IQ2013	2482.7	-4.0	1.7	5.2
IIQ2013	2508.8	-3.0	1.1	4.5
IIIQ2013	2526.7	-2.3	0.7	5.3
IVQ2013	2567.2	-0.7	1.6	5.2
IQ2014	2600.5	0.5	1.3	4.7
IIQ2014	2646.1	2.3	1.8	5.5
IIIQ2014	2693.4	4.1	1.8	6.6
IVQ2014	2702.3	4.5	0.3	5.3
IQ2015	2727.2	5.4	0.9	4.9
IIQ2015	2756.0	6.6	1.1	4.2
IIIQ2015	2794.5	8.1	1.4	3.8
IVQ2015	2793.3	8.0	0.0	3.4
IQ2016	2786.7	7.7	-0.2	2.2
IIQ2016	2778.8	7.4	-0.3	0.8
IIIQ2016	2772.4	7.2	-0.2	-0.8

PFI: Private Fixed Investment

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

Chart IA1-3 provides real private fixed investment in chained dollars of 2009 from 2007 to 2016. Real private fixed investment increased 7.2 percent from $2,586.3 billion of chained 2009 dollars in IVQ2007 to $2,772.4 billion in IIIQ2016.

Chart IA1-3, US, Real Private Fixed Investment, Billions of Chained 2009 Dollars, IQ2007 to IIIQ2016

Source: US Bureau of Economic Analysis

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

Chart IA1-4 provides real gross private domestic investment in chained dollars of 2009 from 1980 to 1989. Real gross private domestic investment climbed 33.5 percent to $1,270.0 billion of 2009 dollars in IQ1990 above the level of $951.6 billion in IQ1980.

Chart IA1-4, US, Real Gross Private Domestic Investment, Billions of Chained 2009 Dollars at Seasonally Adjusted Annual Rate, 1980-1989

Source: US Bureau of Economic Analysis

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

Chart IA1-5 provides real gross private domestic investment in the United States in billions of chained dollars of 2009 from 2006 to 2016. Real gross private domestic investment reached a level of $2,798.1 billion in IIIQ2016, which was only 7.4 percent higher than the level of $2605.2 billion in IVQ2007 (http://www.bea.gov/iTable/index_nipa.cfm).

Chart IA1-5, US, Real Gross Private Domestic Investment, Billions of Chained 2009 Dollars at Seasonally Adjusted Annual Rate, 2007-2016

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

ESV Swelling Undistributed Corporate Profits. Table IA1-5 provides value added of corporate business, dividends and corporate profits in billions of current dollars at seasonally adjusted annual rates (SAAR) in IVQ2007 and IIIQ2016 together with percentage changes. The last three rows of Table IA1-5 provide gross value added of nonfinancial corporate business, consumption of fixed capital and net value added in billions of chained 2009 dollars at SAARs. Deductions from gross value added of corporate profits down the rows of Table IA1-5 end with undistributed corporate profits. Profits after taxes with inventory valuation adjustment (IVA) and capital consumption adjustment (CCA) increased 67.1 percent in nominal terms from IVQ2007 to IIIQ2016 while net dividends increased 16.5 percent and undistributed corporate profits swelled 246.2 percent from $107.7 billion in IQ2007 to $372.9 billion in IIIQ2016 and changed signs from minus $55.9 billion in current dollars in IVQ2007. The investment decision of United States corporations has been fractured in the current economic cycle in preference of cash. Gross value added of nonfinancial corporate business adjusted for inflation increased 17.3 percent from IVQ2007 to IIIQ2016, which is much lower than nominal increase of 31.2 percent in the same period for gross value added of total corporate business.

Table IA1-5, US, Value Added of Corporate Business, Corporate Profits and Dividends, IVQ2007-IIIQ2016

	IVQ2007	IIIQ2016	∆%
Current Billions of Dollars Seasonally Adjusted Annual Rates (SAAR)
Gross Value Added of Corporate Business	8,165.9	10,714.2	31.2
Consumption of Fixed Capital	1,216.5	1,567.1	28.8
Net Value Added	6,949.4	9,147.1	31.6
Compensation of Employees	4,945.8	6,244.8	26.3
Taxes on Production and Imports Less Subsidies	688.5	837.4	21.6
Net Operating Surplus	1,315.1	2,065.0	57.0
Net Interest and Misc	204.2	197.6	-3.2
Business Current Transfer Payment Net	68.9	126.7	83.9
Corporate Profits with IVA and CCA Adjustments	1,042.0	1,740.7	67.1
Taxes on Corporate Income	408.8	564.9	38.2
Profits after Tax with IVA and CCA Adjustment	633.2	1,175.8	85.7
Net Dividends	689.1	803.0	16.5
Undistributed Profits with IVA and CCA Adjustment	-55.9	372.9	NA ∆% 246.2 relative to 107.7 in IQ2007
Billions of Chained USD 2009 SAAR
Gross Value Added of Nonfinancial Corporate Business	7,519.3	8,817.0	17.3
Consumption of Fixed Capital	1,066.0	1,293.0	21.3
Net Value Added	6,453.4	7,524.0	16.6

IVA: Inventory Valuation Adjustment; CCA: Capital Consumption Adjustment

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

Table IA1-6 provides comparable United States value added of corporate business, corporate profits and dividends from IQ1980 to IQ1990. There is significant difference both in nominal and inflation-adjusted data. Between IQ1980 and IQ1990, profits after tax with IVA and CCA increased 72.5 percent with dividends growing 256.5 percent and undistributed profits decreasing 7.4 percent. There was much higher inflation in the 1980s than in the current cycle. For example, the consumer price index increased 60.7 percent from Mar 1980 to Mar 1990 but only 14.9 percent between Dec 2007 and Sep 2016 (http://www.bls.gov/cpi/data.htm). The comparison is still valid in terms of inflation-adjusted data: gross value added of nonfinancial corporate business adjusted for inflation increased 42.4 percent between IQ1980 and IQ1990 but only 17.3 percent between IVQ2007 and IIIQ2016 while net value added adjusted for inflation increased 41.1 percent between IQ1980 and IQ1990 but only 16.6 percent between IVQ2007 and IIIQ2016.

Table IA1-6, US, Value Added of Corporate Business, Corporate Profits and Dividends, IQ1980-IVQ1989

	IQ1980	IQ1990	∆%
Current Billions of Dollars Seasonally Adjusted Annual Rates (SAAR)
Gross Value Added of Corporate Business	1,654.1	3,427.5	107.2
Consumption of Fixed Capital	200.5	444.6	121.7
Net Value Added	1,453.6	2,982.9	105.2
Compensation of Employees	1,072.9	2,195.8	104.7
Taxes on Production and Imports Less Subsidies	121.5	276.0	127.2
Net Operating Surplus	259.2	511.0	97.1
Net Interest and Misc.	50.4	136.5	170.8
Business Current Transfer Payment Net	11.5	34.5	200.0
Corporate Profits with IVA and CCA Adjustments	197.2	340.1	72.5
Taxes on Corporate Income	97.0	139.3	43.6
Profits after Tax with IVA and CCA Adjustment	100.2	200.8	100.4
Net Dividends	40.9	145.8	256.5
Undistributed Profits with IVA and CCA Adjustment	59.3	54.9	-7.4
Billions of Chained USD 2009 SAAR
Gross Value Added of Nonfinancial Corporate Business	2,952.3	4,203.0	42.4
Consumption of Fixed Capital	315.6	481.6	52.6
Net Value Added	2,636.7	3,721.3	41.1

IVA: Inventory Valuation Adjustment; CCA: Capital Consumption Adjustment

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

Chart IA1-14 of the US Bureau of Economic Analysis provides quarterly corporate profits after tax and undistributed profits with IVA and CCA from 1979 to 2016. There is tightness between the series of quarterly corporate profits and undistributed profits in the 1980s with significant gap developing from 1988 and to the present with the closest approximation peaking in IVQ2005 and surrounding quarters. These gaps widened during all recessions including in 1991 and 2001 and recovered in expansions with exceptionally weak performance in the current expansion.

Chart IA1-14, US, Corporate Profits after Tax and Undistributed Profits with Inventory Valuation Adjustment and Capital Consumption Adjustment, Quarterly, 1979-2016

Source: US Bureau of Economic Analysis

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

Table IA1-7 provides price, costs and profit per unit of gross value added of nonfinancial domestic corporate income for IVQ2007 and IIIQ2016 in the upper block and for IQ1980 and IQ1990 in the lower block. Compensation of employees or labor costs per unit of gross value added of nonfinancial domestic corporate income hardly changed from 0.577 in IVQ2007 to 0.624 in IIIQ2016 in a fractured labor market but increased from 0.340 in IQ1980 to 0.476 in IQ1990 in a more vibrant labor market. Unit nonlabor costs increased mildly from 0.270 per unit of gross value added in IVQ2007 to 0.288 in IIIQ2016 but increased from 0.124 in IQ1980 to 0.201 in IQ1990 in an economy closer to full employment of resources. Profits after tax with IVA and CCA per unit of gross value added of nonfinancial domestic corporate income increased from 0.076 in IVQ2007 to 0.104 in IIIQ2016 and from 0.029 in IQ1980 to 0.041 in IQ1990.

Table IA1-7, US, Price, Costs and Profit per Unit of Gross Value Added of Nonfinancial Domestic Corporate Income

	IVQ2007	IIIQ2016
Price per Unit of Real Gross Value Added of Nonfinancial Corporate Business	0.961	1.054
Compensation of Employees (Unit Labor Cost)	0.577	0.624
Unit Nonlabor Cost	0.270	0.288
Consumption of Fixed Capital	0.140	0.156
Taxes on Production and Imports less Subsidies plus Business Current Transfer Payments (net)	0.093	0.097
Net Interest and Misc. Payments	0.037	0.036
Corporate Profits with IVA and CCA Adjustment (Unit Profits from Current Production)	0.114	0.141
Taxes on Corporate Income	0.038	0.038
Profits after Tax with IVA and CCA Adjustment	0.076	0.104
	IQ1980	IQ1990
Price per Unit of Real Gross Value Added of Nonfinancial Corporate Business	0.518	0.740
Compensation of Employees (Unit Labor Cost)	0.340	0.476
Unit Nonlabor Cost	0.124	0.201
Consumption of Fixed Capital	0.064	0.094
Taxes on Production and Imports less Subsidies plus Business Current Transfer Payments (net)	0.042	0.067
Net Interest and Misc. Payments	0.018	0.040
Corporate Profits with IVA and CCA Adjustment (Unit Profits from Current Production)	0.055	0.063
Taxes on Corporate Income	0.026	0.022
Profits after Tax with IVA and CCA Adjustment	0.029	0.041

IVA: Inventory Valuation Adjustment; CCA: Capital Consumption Adjustment

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

Chart IA1-15 provides quarterly profits after tax with IVA and CCA per unit of gross value added of nonfinancial domestic corporate income from 1980 to 2016. In an environment of idle labor and other productive resources nonfinancial corporate income increased after tax profits with IVA and CCA per unit of gross value added at a faster pace in the weak economy from IVQ2007 to IVQ2015 than in the vibrant expansion following the cyclical contractions of the 1980s. Part of the profits was distributed as dividends and significant part was retained as undistributed profits in the current economic cycle with frustrated investment decision.

Chart IA1-15, US, Profits after Tax with Inventory Valuation Adjustment and Capital Consumption Adjustment per Unit of Gross Value Added of Nonfinancial Domestic Corporate Income, 1980-2016

Source: US Bureau of Economic Analysis

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

Corporate profits with IVA and CCA decreased at 0.6 percent in IIQ2016 and decreased at 1.9 percent after taxes. Corporate profits with IVA and CCA increased at 6.6 percent in IIIQ2016 and increased at 7.6 percent after taxes. Corporate profits with IVA and CCA increased 2.8 percent in IIIQ2016 relative to IIIQ2015 and profits after tax with IVA and CCA increased 1.6 percent in IIIQ2016 relative to IIIQ2015. Net dividends fell at 2.1 percent in IVQ2015 and increased at 0.8 percent in IQ2016. Net dividends fell at 1.0 percent in IIQ2016 and increased at 2.0 percent in IIIQ2016. Net dividends decreased 0.4 percent in IIIQ2016 relative to a year earlier. Undistributed profits fell at 25.8 percent in IVQ2015 and increased at 24.3 percent in IQ2016. Undistributed profits fell at 3.6 percent in IIQ2016 and increased at 18.0 percent in IIIQ2016. Undistributed profits increased at 4.8 percent in IIIQ2016 relative to IIIQ2015.

Table IA1-8, Quarterly Seasonally Adjusted Annual Equivalent Percentage Rates of Change of Corporate Profits, ∆%

	2014	2015	IVQ 2015	IQ 2016	IIQ 2016	IIIQ 2016	IIIQ16/ IIIQ15
Corporate Profits with IVA and CCA	5.9	-3.0	-6.1	3.4	-0.6	6.6	2.8
Corporate Income Taxes	13.9	4.0	8.5	-8.3	3.1	3.9	6.6
After Tax Profits with IVA and CCA	3.5	-5.3	-11.0	8.1	-1.9	7.6	1.6
Net Dividends	4.4	0.1	-2.1	0.8	-1.0	2.0	-0.4
Und Profits with IVA and CCA	2.0	-13.2	-25.8	24.3	-3.6	18.0	4.8

Source: US Bureau of Economic Analysis

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

Table IA1-9 provides change from prior quarter of the level of seasonally adjusted annual rates of US corporate profits. 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 $133.8 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 $112.7 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 $18.8 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 $93.9 billion in IIIQ2016. Undistributed corporate profits swelled 246.2 percent from $107.7 billion in IQ2007 to $372.9 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 $133.8 billion in IIIQ2016. Profits from domestic industries increased at $127.4 billion and profits from nonfinancial business increased at $76.5 billion. Profits from the rest of the world increased at $6.4 billion. Total corporate profits with IVA and CCA were $2154.8 billion in IIIQ2016 of which $1740.7 billion from domestic industries, or 80.8 percent of the total, and $414.0 billion, or 19.2 percent, from the rest of the world. Nonfinancial corporate profits of $1247.0 billion account for 57.9 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.

Table IA1-9, Change from Prior Quarter of Level of Seasonally Adjusted Annual Equivalent Rates of Corporate Profits, Billions of Dollars

	2014	2015	IVQ 2015	IQ 2016	IIQ 2016	IIIQ       2016
Corporate Profits with IVA and CCA	119.2	-64.0	-127.9	66.0	-12.5	133.8
Corporate Income Taxes	65.0	21.1	44.9	-47.4	16.4	21.0
After Tax Profits with IVA and CCA	54.1	-85.0	-172.7	113.4	-28.9	112.7
Net Dividends	41.2	0.8	-20.8	7.3	-9.3	18.8
Und Profits with IVA and CCA	12.9	-85.8	-152.0	106.1	-19.6	93.9
Corporate Profits with IVA and CCA	119.2	-64.0	-127.9	66.0	-12.5	133.8
Domestic Industries	120.1	-38.8	-149.8	92.9	-50.5	127.4
Financial	52.7	8.5	-18.2	8.1	5.6	50.9
Nonfinancial	67.4	-47.3	-131.7	84.8	-56.1	76.5
Rest of the World	-0.9	-25.2	22.0	-26.9	38.0	6.4
Receipts from Rest of the World	23.7	-40.0	-19.9	8.7	37.5	-0.2
Payments to the Rest of the World	24.5	-14.8	-41.9	35.6	-0.5	-6.6

Source: Bureau of Economic Analysis

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

ESVI Twenty-four Million Unemployed or Underemployed. The balance of this section considers the second approach. Charts I-1 to I-12 explain the reasons for considering another approach to calculating job stress in the US. Chart I-1 of the Bureau of Labor Statistics provides the level of employment in the US from 2001 to 2016. There was a big drop of the number of people employed from 147.315 million at the peak in Jul 2007 (NSA) to 136.809 million at the trough in Jan 2010 (NSA) with 10.506 million fewer people employed. Recovery has been anemic compared with the shallow recession of 2001 that was followed by nearly vertical growth in jobs. The number employed in Nov 2016 was 152.385 million (NSA) or 5.070 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 254.540 million in Nov 2016 or by 22.582 million. The number employed increased 3.4 percent from Jul 2007 to Nov 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.7 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Nov 2016 would result in 161.633 million jobs (0.635 multiplied by noninstitutional civilian population of 254.540 million). There are effectively 9.248 million fewer jobs in Nov 2016 than in Jul 2007, or 161.633 million minus 152.385 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

Chart I-1, US, Employed, Thousands, SA, 2001-2016

Source: Bureau of Labor Statistics

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

Chart I-2 of the Bureau of Labor Statistics provides 12-month percentage changes of the number of people employed in the US from 2001 to 2016. There was recovery since 2010 but not sufficient to recover lost jobs. Many people in the US who had jobs before the global recession are not working now and many who entered the labor force cannot find employment.

Chart I-2, US, Employed, 12-Month Percentage Change NSA, 2001-2016

Source: Bureau of Labor Statistics

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

The foundation of the second approach derives from Chart I-3 of the Bureau of Labor Statistics providing the level of the civilian labor force in the US. The civilian labor force consists of people who are available and willing to work and who have searched for employment recently. The labor force of the US NSA grew 9.4 percent from 142.828 million in Jan 2001 to 156.255 million in Jul 2009. The civilian labor force is 2.0 percent higher at 159.451 million in Nov 2016 than in Jul 2009, all numbers not seasonally adjusted. Chart I-3 shows the flattening of the curve of expansion of the labor force and its decline in 2010 and 2011. The ratio of the labor force of 154.871 million in Jul 2007 to the noninstitutional population of 231.958 million in Jul 2007 was 66.8 percent while the ratio of the labor force of 159.451 million in Nov 2016 to the noninstitutional population of 254.540 million in Nov 2016 was 62.6 percent. The labor force of the US in Nov 2016 corresponding to 66.8 percent of participation in the population would be 170.033 million (0.668 x 254.540). The difference between the measured labor force in Nov 2016 of 159.451 million and the labor force in Nov 2016 with participation rate of 66.8 percent (as in Jul 2007) of 170.033 million is 10.582 million. The level of the labor force in the US has stagnated and is 10.582 million lower than what it would have been had the same participation rate been maintained. Millions of people have abandoned their search for employment because they believe there are no jobs available for them. The key issue is whether the decline in participation of the population in the labor force is the result of people giving up on finding another job.

Chart I-3, US, Civilian Labor Force, Thousands, SA, 2001-2016

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

Chart I-4 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of the labor force in the US. The rate of growth fell almost instantaneously with the global recession and became negative from 2009 to 2011. The labor force of the US collapsed and did not recover. Growth in the beginning of the summer originates in younger people looking for jobs in the summer after graduation or during school recess.

Chart I-4, US, Civilian Labor Force, Thousands, NSA, 12-month Percentage Change, 2001-2016

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

Chart I-5 of the Bureau of Labor Statistics provides the labor force participation rate in the US or labor force as percent of the population. The labor force participation rate of the US fell from 66.8 percent in Jan 2001 to 62.6 percent NSA in Nov 2016, all numbers not seasonally adjusted. The annual labor force participation rate for 1979 was 63.7 percent and also 63.7 percent in Nov 1980 during sharp economic contraction. This comparison is further elaborated below. Chart I-5 shows an evident downward trend beginning with the global recession that has continued throughout the recovery beginning in IIIQ2009. The critical issue is whether people left the workforce of the US because they believe there is no longer a job for them.

Chart I-5, Civilian Labor Force Participation Rate, Percent of Population in Labor Force SA, 2001-2016

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

Chart I-6 of the Bureau of Labor Statistics provides the level of unemployed in the US. The number unemployed rose from the trough of 6.272 million NSA in Oct 2006 to the peak of 16.147 million in Jan 2010, declining to 13.400 million in Jul 2012, 12.696 million in Aug 2012 and 11.741 million in Sep 2012. The level unemployed fell to 11.741 million in Oct 2012, 11.404 million in Nov 2012, 11.844 million in Dec 2012, 13.181 million in Jan 2013, 12.500 million in Feb 2013 and 9.984 million in Dec 2013. The level of unemployment reached 7.006 million in Nov 2016, all numbers not seasonally adjusted.

Chart I-6, US, Unemployed, Thousands, SA, 2001-2016

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

Chart I-7 of the Bureau of Labor Statistics provides the rate of unemployment in the US or unemployed as percent of the labor force. The rate of unemployment of the US rose from 4.7 percent in Jan 2001 to 6.5 percent in Jun 2003, declining to 4.1 percent in Oct 2006. The rate of unemployment jumped to 10.6 percent in Jan 2010 and declined to 7.6 percent in Dec 2012 but increased to 8.5 percent in Jan 2013 and 8.1 percent in Feb 2013, falling back to 7.3 percent in May 2013 and 7.8 percent in Jun 2013, all numbers not seasonally adjusted. The rate of unemployment not seasonally adjusted stabilized at 7.7 percent in Jul 2013 and fell to 6.5 percent in Dec 2013 and 5.4 percent in Dec 2014. The rate of unemployment NSA decreased to 4.8 percent in Dec 2015 and 4.4 percent in Nov 2016.

Chart I-7, US, Unemployment Rate, SA, 2001-2016

Source: Bureau of Labor Statistics

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

Chart I-8 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of unemployed. There was a jump of 81.8 percent in Apr 2009 with subsequent decline and negative rates since 2010. On an annual basis, the level of unemployed rose 59.8 percent in 2009 and 26.1 percent in 2008 with increase of 3.9 percent in 2010, decline of 7.3 percent in 2011 and decrease of 9.0 percent in 2012. The annual level of unemployment decreased 8.4 percent in 2013 and fell 16.1 percent in 2014. The annual level of unemployment fell 13.7 percent in 2015. The level of unemployment decreased 6.7 percent in Nov 2016 relative to a year earlier.

Chart I-8, US, Unemployed, 12-month Percentage Change, NSA, 2001-2016

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

Chart I-9 of the Bureau of Labor Statistics provides the number of people in part-time occupations because of economic reasons, that is, because they cannot find full-time employment. The number underemployed in part-time occupations not seasonally adjusted rose from 3.732 million in Jan 2001 to 5.270 million in Jan 2004, falling to 3.787 million in Apr 2006. The number underemployed seasonally adjusted jumped to 9.114 million in Nov 2009, falling to 8.171 million in Dec 2011 but increasing to 8.267 million in Jan 2012 and 8.214 million in Feb 2012 but then falling to 7.922 million in Dec 2012 and increasing to 8.093 million in Jul 2013. The number employed part-time for economic reasons seasonally adjusted reached 7.763 million in Dec 2013 and 6.786 million in Dec 2014. The number employed part-time for economic reasons seasonally adjusted reached 5.669 million in Nov 2016. Without seasonal adjustment, the number employed part-time for economic reasons reached 9.354 million in Dec 2009, declining to 8.918 million in Jan 2012 and 8.166 million in Dec 2012 but increasing to 8.324 million in Jul 2013. The number employed part-time for economic reasons NSA stood at 7.990 million in Dec 2013, 6.970 million in Dec 2014 and 6.179 million in Dec 2015. The number employed part-time for economic reasons NSA stood at 5.518 million in Nov 2016. The longer the period in part-time jobs the lower are the chances of finding another full-time job.

Chart I-9, US, Part-Time for Economic Reasons, Thousands, SA, 2001-2016

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

Chart I-10 of the Bureau of Labor Statistics repeats the behavior of unemployment. The 12-month percentage change of the level of people at work part-time for economic reasons jumped 84.7 percent in Mar 2009 and declined subsequently. The declines have been insufficient to reduce significantly the number of people who cannot shift from part-time to full-time employment. On an annual basis, the number of part-time for economic reasons increased 33.5 percent in 2008 and 51.7 percent in 2009, declining 0.4 percent in 2010, 3.5 percent in 2011 and 5.1 percent in 2012. The annual number of part-time for economic reasons decreased 2.3 percent in 2013 and fell 9.1 percent in 2014. The annual number of part-time for economic reasons fell 11.7 percent in 2015. The number of part-time for economic reasons decreased 7.5 percent in Nov 2016 relative to a year earlier.

Chart I-10, US, Part-Time for Economic Reasons NSA 12-Month Percentage Change, 2001-2016

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

Chart I-11 of the Bureau of Labor Statistics provides the same pattern of the number marginally attached to the labor force jumping to significantly higher levels during the global recession and remaining at historically high levels. The number marginally attached to the labor force not seasonally adjusted increased from 1.295 million in Jan 2001 to 1.691 million in Feb 2004. The number of marginally attached to the labor force fell to 1.299 million in Sep 2006 and increased to 2.609 million in Dec 2010 and 2.800 million in Jan 2011. The number marginally attached to the labor force was 2.540 million in Dec 2011, increasing to 2.809 million in Jan 2012, falling to 2.608 million in Feb 2012. The number marginally attached to the labor force fell to 2.352 million in Mar 2012, 2.363 million in Apr 2012, 2.423 million in May 2012, 2.483 million in Jun 2012, 2.529 million in Jul 2012 and 2.561 million in Aug 2012. The number marginally attached to the labor force fell to 2.517 million in Sep 2012, 2.433 million in Oct 2012, 2.505 million in Nov 2012 and 2.427 million in in Dec 2013. The number marginally attached to the labor force reached 2.260 million in Dec 2014 and 1.833 million in Dec 2015. The number marginally attached to the labor force stood at 1.932 million in Nov 2016.

Chart I-11, US, Marginally Attached to the Labor Force, Thousands, NSA, 2001-2016

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

Chart I-12 provides 12-month percentage changes of the marginally attached to the labor force from 2001 to 2016. There was a jump of 56.1 percent in May 2009 during the global recession followed by declines in percentage changes but insufficient negative changes. On an annual basis, the number of marginally attached to the labor force increased in four consecutive years: 15.7 percent in 2008, 37.9 percent in 2009, 11.7 percent in 2010 and 3.5 percent in 2011. The number marginally attached to the labor force fell 2.2 percent on annual basis in 2012 but increased 2.9 percent in the 12 months ending in Dec 2012, fell 13.0 percent in the 12 months ending in Jan 2013, falling 10.7 percent in the 12 months ending in May 2013. The number marginally attached to the labor force increased 4.0 percent in the 12 months ending in Jun 2013 and fell 4.5 percent in the 12 months ending in Jul 2013 and 8.6 percent in the 12 months ending in Aug 2013. The annual number of marginally attached to the labor force fell 6.2 percent in 2013 and fell 6.5 percent in 2014. The annual number of marginally attached to the labor force fell 11.4 percent in 2015. The number marginally attached to the labor force fell 7.2 percent in the 12 months ending in Dec 2013 and fell 6.9 percent in the 12 months ending in Dec 2014. The number marginally attached to the labor force fell 18.9 percent in the 12 months ending in Dec 2015 and increased 12.5 percent in the 12 months ending in Nov 2016.

Chart I-12, US, Marginally Attached to the Labor Force 12-Month Percentage Change, NSA, 2001-2016

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

Table I-4 consists of data and additional calculations using the BLS household survey, illustrating the possibility that the actual rate of unemployment could be 9.6 percent and the number of people in job stress could be around 23.6 million, which is 14.0 percent of the effective labor force. The first column provides for 2006 the yearly average population (POP), labor force (LF), participation rate or labor force as percent of population (PART %), employment (EMP), employment population ratio (EMP/POP %), unemployment (UEM), the unemployment rate as percent of labor force (UEM/LF Rate %) and the number of people not in the labor force (NLF). All data are unadjusted or not-seasonally-adjusted (NSA). The numbers in column 2006 are averages in millions while the monthly numbers for Nov 2015, Oct 2016 and Nov 2016 are in thousands, not seasonally adjusted. The average yearly participation rate of the population in the labor force was in the range of 66.0 percent minimum to 67.1 percent maximum between 2000 and 2006 with the average of 66.4 percent (http://www.bls.gov/data/). Table I-4b provides the yearly labor force participation rate from 1979 to 2016. The objective of Table I-4 is to assess how many people could have left the labor force because they do not think they can find another job. Row “LF PART 66.2 %” applies the participation rate of 2006, almost equal to the rates for 2000 to 2006, to the noninstitutional civilian population in Nov 2015, Oct 2016 and Nov 2016 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 62.5 percent by Nov 2015 and was 62.8 percent in Oct 2016 and 62.6 percent in Nov 2016, suggesting that many people simply gave up on finding another job. Row “∆ NLF UEM” calculates the number of people not counted in the labor force because they could have given up on finding another job by subtracting from the labor force with participation rate of 66.2 percent (row “LF PART 66.2%”) the labor force estimated in the household survey (row “LF”). Total unemployed (row “Total UEM”) is obtained by adding unemployed in row “∆NLF UEM” to the unemployed of the household survey in row “UEM.” The row “Total UEM%” is the effective total unemployed “Total UEM” as percent of the effective labor force in row “LF PART 66.2%.” The results are that:

• there are an estimated 9.054 million unemployed in Nov 2016 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM), that is, they dropped out of their job searches
• the total number of unemployed is effectively 16.120 million (Total UEM) and not 7.006 million (UEM) of whom many have been unemployed long term
• the rate of unemployment is 9.6 percent (Total UEM%) and not 4.4 percent, not seasonally adjusted, or 4.6 percent seasonally adjusted
• the number of people in job stress is close to 23.6 million by adding the 9.054 million leaving the labor force because they believe they could not find another job, corresponding to 14.0 percent of the effective labor force.

The row “In Job Stress” in Table I-4 provides the number of people in job stress not seasonally adjusted at 23.373 million in Oct 2016, adding the total number of unemployed (“Total UEM”), plus those involuntarily in part-time jobs because they cannot find anything else (“Part Time Economic Reasons”) and the marginally attached to the labor force (“Marginally attached to LF”). The final row of Table I-4 shows that the number of people in job stress is equivalent to 14.0 percent of the labor force in Nov 2016. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 59.5 percent in Nov 2015, 59.9 percent in Oct 2016 and 59.9 percent in Nov 2016. The number employed in Nov 2016 was 152.385 million (NSA) or 5.070 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 254.540 million in Nov 2016 or by 22.582 million. The number employed increased 3.4 percent from Jul 2007 to Nov 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.7 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Nov 2016 would result in 161.633 million jobs (0.635 multiplied by noninstitutional civilian population of 254.540 million). There are effectively 9.248 million fewer jobs in Nov 2016 than in Jul 2007, or 161.633 million minus 152.385 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html). This is merely another case of theory without reality with dubious policy proposals. The number of hiring relative to the number unemployed measures the chances of becoming employed. The number of hiring in the US economy has declined by 10 million and does not show signs of increasing in an unusual recovery without hiring. 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 second estimate of GDP for IIIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp3q16_2nd.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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.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 $2702.3 billion than actual $16,712.1 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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 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 Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 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 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 percent below trend under this alternative calculation.

Table I-4, US, Population, Labor Force and Unemployment, NSA

	2006	Nov 2015	Oct 2016	Nov 2016
POP	229	251,747	254,321	254,540
LF	151	157,340	159,783	159,451
PART%	66.2	62.5	62.8	62.6
EMP	144	149,766	152,335	152,385
EMP/POP%	62.9	59.5	59.9	59.9
UEM	7	7,573	7,447	7,066
UEM/LF Rate%	4.6	4.8	4.7	4.4
NLF	77	94,407	94,539	95,089
LF PART 66.2%		166,657	168,361	168,505
∆NLF UEM		9,317	8,578	9,054
Total UEM		16,890	16,025	16,120
Total UEM%		10.1	9.5	9.6
Part Time Economic Reasons		5,967	5,648	5,518
Marginally Attached to LF		1,717	1,700	1,932
In Job Stress		24,574	23,373	23,570
People in Job Stress as % Labor Force		14.7	13.9	14.0

Pop: population; LF: labor force; PART: participation; EMP: employed; UEM: unemployed; NLF: not in labor force; ∆NLF UEM: additional unemployed; Total UEM is UEM + ∆NLF UEM; Total UEM% is Total UEM as percent of LF PART 66.2%; In Job Stress = Total UEM + Part Time Economic Reasons + Marginally Attached to LF

Note: the first column for 2006 is in average millions; the remaining columns are in thousands; NSA: not seasonally adjusted

The labor force participation rate of 66.2% in 2006 is applied to current population to obtain LF PART 66.2%; ∆NLF UEM is obtained by subtracting the labor force with participation of 66.2 percent from the household survey labor force LF; Total UEM is household data unemployment plus ∆NLF UEM; and total UEM% is total UEM divided by LF PART 66.2%

Source: US Bureau of Labor Statistics

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

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

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

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

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

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

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

Y = ∑_is_iy_i (1)

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

∆Y = ∑_i∆s_iy*_i + ∑_i∆y_is*_i (2)

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

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

Table I-4b and Chart I-12-b provide the US labor force participation rate or percentage of the labor force in population. It is not likely that simple demographic trends caused the sharp decline during the global recession and failure to recover earlier levels. The civilian labor force participation rate dropped from the peak of 66.9 percent in Jul 2006 to 62.6 percent in Dec 2013, 62.5 percent in Dec 2014 and 62.4 percent in Dec 2015. The civilian labor force participation rate was 62.6 percent in Nov 2016. The civilian labor force participation rate was 63.7 percent on an annual basis in 1979 and 63.4 percent in Dec 1980 and Dec 1981, reaching even 62.9 percent in both Apr and May 1979. The civilian labor force participation rate jumped with the recovery to 64.8 percent on an annual basis in 1985 and 65.9 percent in Jul 1985. Structural factors cannot explain these sudden changes vividly shown visually in the final segment of Chart I-12b. Seniors would like to delay their retiring especially because of the adversities of financial repression on their savings. Labor force statistics are capturing the disillusion of potential workers with their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors. The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html). “Secular stagnation” would be a process over many years and not from one year to another. This is merely another case of theory without reality with dubious policy proposals.

Table I-4b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2016

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

Source: US Bureau of Labor Statistics

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

Chart I-12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2016

Source: Bureau of Labor Statistics

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

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

Chart I-12c, US, Civilian Noninstitutional Population, Thousands, NSA, 1948-2016

Sources: US Bureau of Labor Statistics

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

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

Chart I-12d, US, Labor Force, Thousands, NSA, 1948-2016

Sources: US Bureau of Labor Statistics

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

The rate of labor force participation in the US is in Chart I-12E from 1948 to 2016. There is sudden decline during the global recession after 2007 without recovery explained by cyclical factors (Lazear and Spletzer2012JHJul22) as may many potential workers stopped their searches disillusioned that there could be an opportunity for them in sharply contracted markets.

Chart I-12E, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1948-2016

Sources: US Bureau of Labor Statistics

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

ESVII Job Creation. What is striking about the data in Table I-8 is that the numbers of monthly increases in jobs in 1983 and 1984 are several times higher than in 2010 to 2015. The civilian noninstitutional population grew by 44.0 percent from 174.215 million in 1983 to 250.801 million in 2015 and labor force higher by 40.9 percent, growing from 111.550 million in 1983 to 157.130 million in 2015. Total nonfarm payroll employment seasonally adjusted (SA) increased 178,000 in Nov 2016 and private payroll employment increased 156,000. The average monthly number of nonfarm jobs created from Nov 2014 to Nov 2015 was 230,417 using seasonally adjusted data, while the average number of nonfarm jobs created from Nov 2015 to Nov 2016 was 187,750, or decrease by 18.5 percent. The average number of private jobs created in the US from Nov 2014 to Nov 2015 was 222,583, using seasonally adjusted data, while the average from Nov 2015 to Nov 2016 was 169,667, or decrease by 23.8 percent. This blog calculates the effective labor force of the US at 168,505 million in Nov 2015 and 166,657 million in Nov 2016 (Table I-4), for growth of 1.848 million at average 154,000 per month. The difference between the average increase of 169,667 new private nonfarm jobs per month in the US from Nov 2015 to Nov 2016 and the 154,000 average monthly increase in the labor force from Nov 2015 to Nov 2016 is 15,667 monthly new jobs net of absorption of new entrants in the labor force. There are 23.570 million in job stress in the US currently. Creation of 15,667 new jobs per month net of absorption of new entrants in the labor force would require 1,504 months to provide jobs for the unemployed and underemployed (23.570 million divided by 15,667) or 125 years (1,504 divided by 12). The civilian labor force of the US in Nov 2016 not seasonally adjusted stood at 159.451 million with 7.066 million unemployed or effectively 16.120 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 168.505 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 5.3 years (1 million divided by product of 15,667 by 12, which is 188,004). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.973 million (0.05 times labor force of 159.451 million). New net job creation would be minus 0.967 million (7.006 million unemployed minus 7.973 million unemployed at rate of 5 percent) that at the current rate would take 0.0 years (0.967 million divided by 188,004). Under the calculation in this blog, there are 16.120 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 168.505 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 7.695 million jobs net of labor force growth that at the current rate would take 40.9 years (16.120 million minus 0.05(168.505 million) = 7.695 million divided by 188,004 using LF PART 66.2% and Total UEM in Table I-4). These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply. The number employed in Nov 2016 was 152.385 million (NSA) or 5.070 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 254.540 million in Nov 2016 or by 22.582 million. The number employed increased 3.4 percent from Jul 2007 to Nov 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.7 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Nov 2016 would result in 161.633 million jobs (0.635 multiplied by noninstitutional civilian population of 254.540 million). There are effectively 9.248 million fewer jobs in Nov 2016 than in Jul 2007, or 161.633 million minus 152.385 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

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

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

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html). The proper explanation is not in secular stagnation but in cyclically slow growth. 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 $2702.3 billion than actual $16,712.1 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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 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 Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 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 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 percent below trend under this alternative calculation.

Table I-8, US, Monthly Change in Jobs, Number SA

Month	1981	1982	1983	2008	2009	2010	Private
Jan	94	-326	224	19	-791	28	19
Feb	68	-5	-75	-86	-703	-69	-54
Mar	105	-130	172	-78	-823	163	121
Apr	73	-280	276	-210	-686	243	192
May	10	-45	277	-185	-351	522	95
Jun	197	-243	379	-165	-470	-133	123
Jul	112	-342	418	-209	-329	-70	101
Aug	-36	-158	-308	-266	-212	-34	115
Sep	-87	-181	1115	-452	-219	-52	121
Oct	-99	-277	271	-473	-200	257	207
Nov	-209	-123	353	-769	-7	123	133
Dec	-278	-14	356	-695	-279	88	109
			1984			2011	Private
Jan			446			42	50
Feb			481			188	231
Mar			275			225	248
Apr			363			346	354
May			308			73	128
Jun			379			235	200
Jul			313			70	185
Aug			242			107	139
Sep			310			246	280
Oct			286			202	187
Nov			349			146	173
Dec			128			207	224
			1985			2012	Private
Jan			266			338	347
Feb			124			257	261
Mar			346			239	237
Apr			196			75	90
May			274			115	130
Jun			146			87	72
Jul			190			143	160
Aug			193			190	174
Sep			203			181	180
Oct			188			132	164
Nov			209			149	171
Dec			167			243	233
			1986			2013	Private
Jan			125			190	203
Feb			107			311	297
Mar			94			135	150
Apr			187			192	193
May			127			218	225
Jun			-94			146	173
Jul			318			140	162
Aug			114			269	242
Sep			347			185	179
Oct			186			189	203
Nov			186			291	280
Dec			205			45	71
			1987			2014	Private
Jan			172			187	197
Feb			232			168	158
Mar			249			272	261
Apr			338			310	282
May			226			213	215
Jun			172			306	267
Jul			347			232	244
Aug			171			218	231
Sep			228			286	237
Oct			492			200	190
Nov			232			331	324
Dec			294			292	279
			1988			2015	Private
Jan			94			221	214
Feb			453			265	252
Mar			276			84	90
Apr			245			251	241
May			229			273	256
Jun			363			228	226
Jul			222			277	245
Aug			124			150	123
Sep			339			149	162
Oct			268			295	304
Nov			339			280	279
Dec			290			271	259
			1989			2016	Private
Jan			262			168	155
Feb			258			233	222
Mar			193			186	167
Apr			173			144	147
May			118			24	-1
Jun			116			271	238
Jul			40			252	221
Aug			49			176	132
Sep			250			208	205
Oct			111			142	132
Nov			277			178	156
Dec			96

Source: US Bureau of Labor Statistics

http://www.bls.gov/

The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). Table I-12 provides total annual level nonfarm employment in the US for the 1980s and the 2000s, which is different from 12-month comparisons. Nonfarm jobs rose by 4.859 million from 1982 to 1984, or 5.4 percent, and continued rapid growth in the rest of the decade. In contrast, nonfarm jobs are down by 7.638 million in 2010 relative to 2007 and fell by 952,000 in 2010 relative to 2009 even after six quarters of GDP growth. Monetary and fiscal stimuli have failed in increasing growth to rates required for mitigating job stress. The initial growth impulse reflects a flatter growth curve in the current expansion. Nonfarm jobs declined from 137.999 million in 2007 to 136.381 million in 2013, by 1.618 million or 1.2 percent. Nonfarm jobs increased from 137.999 million in 2007 to 141,865 million in 2015, by 3.866 million or 2.8 percent. The US noninstitutional population or in condition to work increased from 231.867 million in 2007 to 250,801 million in 2015, by 18.934 million or 8.2 percent. The ratio of nonfarm jobs of 137.999 million in 2007 to the noninstitutional population of 231.867 was 59.5. Nonfarm jobs in 2015 corresponding to the ratio of 59.5 of nonfarm jobs/noninstitutional population would be 149.227 million (0.595x250.801). The difference between actual nonfarm jobs of 141.865 million in 2015 and nonfarm jobs of 149.227 million that are equivalent to 59.5 percent of the noninstitutional population as in 2007 is 7.362 million fewer jobs. The proper explanation for this loss of work opportunities is not in secular stagnation but in cyclically slow growth. The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). Table I-12 provides total annual level nonfarm employment in the US for the 1980s and the 2000s, which is different from 12-month comparisons. Nonfarm jobs rose by 4.859 million from 1982 to 1984, or 5.4 percent, and continued rapid growth in the rest of the decade. In contrast, nonfarm jobs are down by 7.638 million in 2010 relative to 2007 and fell by 952,000 in 2010 relative to 2009 even after six quarters of GDP growth. Monetary and fiscal stimuli have failed in increasing growth to rates required for mitigating job stress. The initial growth impulse reflects a flatter growth curve in the current expansion. Nonfarm jobs declined from 137.999 million in 2007 to 136.381 million in 2013, by 1.618 million or 1.2 percent. Nonfarm jobs increased from 137.999 million in 2007 to 141,865 million in 2015, by 3.866 million or 2.8 percent. The US noninstitutional population or in condition to work increased from 231.867 million in 2007 to 250,801 million in 2015, by 18.934 million or 8.2 percent. The ratio of nonfarm jobs of 137.999 million in 2007 to the noninstitutional population of 231.867 was 59.5. Nonfarm jobs in 2015 corresponding to the ratio of 59.5 of nonfarm jobs/noninstitutional population would be 149.227 million (0.595x250.801). The difference between actual nonfarm jobs of 141.865 million in 2015 and nonfarm jobs of 149.227 million that are equivalent to 59.5 percent of the noninstitutional population as in 2007 is 7.362 million fewer jobs. The proper explanation for this loss of work opportunities is not in secular stagnation but in cyclically slow growth. 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 $2702.3 billion than actual $16,712.1 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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 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 Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 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 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 percent below trend under this alternative calculation.

Table I-12, US, Total Nonfarm Employment in Thousands

Year	Total Nonfarm	Year	Total Nonfarm
1980	90,533	2000	132,024
1981	91,297	2001	132,087
1982	89,689	2002	130,649
1983	90,295	2003	130,347
1984	94,548	2004	131,787
1985	97,532	2005	134,051
1986	99,500	2006	136,453
1987	102,116	2007	137,999
1988	105,378	2008	137,242
1989	108,051	2009	131,313
1990	109,527	2010	130,361
1991	108,427	2011	131,932
1992	108,802	2012	134,175
1993	110,935	2013	136,381
1994	114,398	2014	139,958
1995	117,407	2015	141,865

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

Chart I-43 provides annual nonfarm jobs from 2000 to 2015. Cyclically slow growth in the expansion since IIIQ2009 has not been sufficient to recover nonfarm jobs. Because of population growth, there are 7.362 million fewer nonfarm jobs in the US in 2015 than in 2007.

Chart I-43, US, Annual Nonfarm Jobs, NSA, Thousands, 2000-2015

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

Chart I-44 provides annual nonfarm jobs in the US from 1980 to 1995. Much more rapid cyclical growth as in other expansions historically allowed steady and rapid growth of nonfarm job opportunities even with similarly dynamic population growth.

Chart I-44, US, Annual Nonfarm Jobs, NSA, Thousands, 1980-1995

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

ESVIII Stagnating Real Wages. Calculations of inflation-adjusted average hourly earnings by the BLS are in Table IB-4. Average hourly earnings rose above inflation throughout the first nine months of 2007 just before the global recession that began in the final quarter of 2007 when average hourly earnings began to lose to inflation. In contrast, average hourly earnings of all US workers have risen less than inflation in five months in 2010 and in all but the first month in 2011 and the loss accelerated at 1.8 percent in Sep 2011, declining to a real loss of 1.1 percent in Feb 2012 and 0.5 percent in Mar 2012. There was a gain of 0.6 percent in Apr 2012 in inflation-adjusted average hourly earnings but another fall of 0.6 percent in May 2012 followed by increases of 0.3 percent in Jun and 1.0 percent in Jul 2012. Real hourly earnings stagnated in the 12 months ending in Aug 2012 with increase of only 0.1 percent, and increased 0.7 percent in the 12 months ending in Sep 2012. Real hourly earnings fell 1.2 percent in Oct 2012 and gained 1.0 percent in Dec 2012 but declined 0.2 percent in Jan 2013 and stagnated at change of 0.2 percent in Feb 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Mar 2013 and 0.2 percent in Apr 2013, increasing 0.7 percent in May 2013. In Jun 2013, real hourly earnings increased 1.1 percent relative to Jun 2012. Real hourly earnings fell 0.6 percent in the 12 months ending in Jul 2013 and increased 0.8 percent in the 12 months ending in Aug 2013. Real hourly earnings increased 1.3 percent in the 12 months ending in Oct 2013 and 1.0 percent in Nov 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Dec 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Jan 2014 and 1.7 percent in the 12 months ending in Feb 2014. Real hourly earnings increased 1.3 percent in the 12 months ending in Mar 2014. Real hourly changed 0.0 percent in the 12 months ending in Apr 2014. Real hourly changed 0.0 percent in the 12 months ending in May 2014. Real hourly earnings changed 0.0 percent in the 12 months ending in Jun 2014. Real hourly earnings increased 0.1 percent in the 12 months ending in Jul 2014 and increased 0.5 percent in the 12 months ending in Aug 2014. Real hourly earnings fell 0.3 percent in the 12 months ending in Sep 2014 and increased 0.3 percent in the 12 months ending in Oct 2014. Real hourly earnings increased 1.4 percent in the 12 months ending in Nov 2014 and 0.4 percent in the 12 months ending in Dec 2014. Real hourly earnings increased 2.3 percent in the 12 months ending in Jan 2015 and increased 2.0 percent in the 12 months ending in Feb 2015. Real hourly earnings increased 2.3 percent in the 12 months ending in Mar 2015 and increased 2.5 percent in the 12 months ending in Apr 2015. Real hourly earnings increased 2.4 percent in the 12 months ending in May 2015 and 1.3 percent in the 12 months ending in Jun 2015. Real hourly earnings increased 2.1 percent in the 12 months ending in Jul 2015 and increased 2.7 percent in the 12 months ending in Aug 2015. Real hourly earnings increased 2.4 percent in the 12 months ending in Sep 2015. Real hourly earnings increased 2.4 percent in the 12 months ending in Oct 2015 and increased 1.9 percent in the 12 months ending in Nov 2015. Average hourly earnings increased 1.8 percent in the 12 months ending in Dec 2015 and increased 1.1 percent in the 12 months ending in Jan 2016. Real hourly earnings increased 0.7 percent in the 12 months ending in Feb 2016 and increased 0.8 percent in the 12 months ending in Mar 2016. Real hourly earnings increased 1.4 percent in the 12 months ending in Apr 2016 and increased 2.1 percent in the 12 months ending in May 2016. Real hourly earnings increased 1.6 percent in the 12 months ending in Jun 2016 and increased 1.9 percent in the 12 months ending in Jul 2016. Real hourly earnings increased 0.9 percent in the 12 months ending in Aug 2016 and increased 1.1 percent in the 12 months ending in Sep 2016. Real hourly earnings increased 1.9 percent in the 12 months ending in Oct 2016. Real hourly earnings are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html) originating in weak economic growth (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available in the release for Jan 2016 and subsequent releases.

Table IB-4, US, Average Hourly Earnings of All Employees NSA in Constant Dollars of 1982-1984

Year	May	Jun	Jul	Aug	Sep	Oct	Dec
2006	9.91	9.88	9.97	9.87	10.03	10.16	10.21
2007	9.99	9.97	10.05	10.00	10.13	10.06	10.15
2008	9.88	9.82	9.75	9.81	9.91	10.03	10.45
2009	10.31	10.18	10.22	10.27	10.28	10.30	10.36
2010	10.36	10.25	10.28	10.33	10.35	10.38	10.38
2011	10.21	10.11	10.15	10.09	10.16	10.29	10.29
2012	10.15	10.14	10.25	10.10	10.23	10.17	10.39
∆%12M	-0.6	0.3	1.0	0.1	0.7	-1.2	1.0
2013	10.22	10.25	10.19	10.18	10.32	10.30	10.43
∆%12M	0.7	1.1	-0.6	0.8	0.9	1.3	0.4
2014	10.22	10.25	10.20	10.23	10.29	10.33	10.47
∆%12M	0.0	0.0	0.1	0.5	-0.3	0.3	0.4
2015	10.47	10.38	10.41	10.51	10.54	10.58	10.66
∆%12M	2.4	1.3	2.1	2.7	2.4	2.4	1.8
2016	10.69	10.55	10.61	10.60	10.66	10.78
∆%12M	2.1	1.6	1.9	0.9	1.1	1.9

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart IB-2 of the US Bureau of Labor Statistics plots average hourly earnings of all US employees in constant 1982-1984 dollars with evident decline from annual earnings of $10.34 in 2009 and $10.35 in 2010 to $10.24 in 2011 and $10.24 again in 2012 or loss of 1.1 percent (data in http://www.bls.gov/data/). Annual real hourly earnings increased 0.5 percent in 2013 relative to 2012 and increased 0.5 percent in 2014 relative to 2013. Annual real hourly earnings increased 2.1 percent in 2015 relative to 2014. Annual real hourly earnings increased 4.7 percent from 2007 to 2015 at the rate of 0.6 percent per year. Annual real hourly earnings increased 2.1 percent from 2009 to 2015 at the rate of 0.4 percent per year. Real hourly earnings of US workers are crawling in a fractured labor market. The economic welfare or wellbeing of United States workers deteriorated in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html), stagnating/declining real wages and 23.6 million unemployed or underemployed (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html) because of mediocre economic growth (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available for the release of Jan 2016 and subsequent releases.

Chart IB-2, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2016

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

Chart IB-3 provides 12-month percentage changes of average hourly earnings of all employees in constant dollars of 1982-1984, that is, adjusted for inflation. There was sharp contraction of inflation-adjusted average hourly earnings of US employees during parts of 2007 and 2008. Rates of change in 12 months became positive in parts of 2009 and 2010 but then became negative again in 2011 and into 2012 with temporary increase in Apr 2012 that was reversed in May with another gain in Jun and Jul 2012 followed by stagnation in Aug 2012. There was marginal gain in Sep 2012 with sharp decline in Oct 2012, stagnation in Nov 2012, increase in Dec 2012 and renewed decrease in Jan 2013 with near stagnation in Feb 2013 followed by mild increase in Mar-Apr 2013. Hourly earnings adjusted for inflation increased in Jun 2013 and fell in Jul 2013, increasing in Aug-Dec 2013 and Jan-Mar 2014. Average hourly earnings stagnated in Apr-May 2014 and rebounded mildly in Jul 2014, increasing in Aug 2014 and Sep 2014. Average hourly earnings adjusted for inflation increased in Oct-Dec 2014, Jan-Dec 2015 and Jan-Oct 2016.

Chart IB-3, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2016

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

Average weekly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are in Table IB-5. Average weekly earnings fell 3.2 percent after adjusting for inflation in the 12 months ending in Aug 2011, decreased 0.9 percent in the 12 months ending in Sep 2011 and increased 0.6 percent in the 12 months ending in Oct 2011. Average weekly earnings fell 1.0 percent in the 12 months ending in Nov 2011 and fell 0.3 percent in the 12 months ending in Dec 2011. Average weekly earnings declined 0.3 percent in the 12 months ending in Jan 2012 and fell 0.5 percent in the 12 months ending in Feb 2012. Average weekly earnings in constant dollars were virtually flat in Mar 2012 relative to Mar 2011, decreasing 0.2 percent. Average weekly earnings in constant dollars increased 1.7 percent in Apr 2012 relative to Apr 2011 but fell 1.7 percent in May 2012 relative to May 2011, increasing 0.6 percent in the 12 months ending in Jun 2012 and 1.8 percent in the 12 months ending in Jul 2012. Real weekly earnings increased 0.4 percent in the 12 months ending in Aug 2012 and 2.1 percent in the 12 months ending in Sep 2012. Real weekly earnings fell 2.6 percent in the 12 months ending in Oct 2012 and increased 0.1 percent in the 12 months ending in Nov 2012 and 2.1 percent in the 12 months ending in Dec 2012. Real weekly earnings fell 1.7 percent in the 12 months ending in Jan 2013 and virtually stagnated with gain of 0.2 percent in the 12 months ending in Feb 2013, increasing 0.7 percent in the 12 months ending in Mar 2013. Real weekly earnings fell 0.7 percent in the 12 months ending in Apr 2013 and increased 1.0 percent in the 12 months ending in May 2013. Average weekly earnings increased 2.5 percent in the 12 months ending in Jun 2013 and fell 1.4 percent in the 12 months ending in Jul 2013. Real weekly earnings increased 0.8 percent in the 12 months ending in Aug 2013, 0.9 percent in the 12 months ending in Sep 2013 and 1.6 percent in the 12 months ending in Oct 2013. Average weekly earnings increased 1.3 percent in the 12 months ending in Nov 2013 and increased 0.1 percent in the 12 months ending in Dec 2013. Average weekly earnings increased 0.4 percent in the 12 months ending in Jan 2014 and 2.3 percent in the 12 months ending in Feb 2014. Average weekly earnings increased 2.4 percent in the 12 months ending in Mar 2014 and 0.3 percent in the 12 months ending in Apr 2014. Average weekly earnings in constant dollars increased 0.3 percent in the 12 months ending in May 2014 and changed 0.0 percent in the 12 months ending in Jun 2014. Real average weekly earnings increased 0.4 percent in the 12 months ending in Jul 2014 and 0.8 percent in the 12 months ending in Aug 2014. Real weekly earnings decreased 1.4 percent in the 12 months ending in Sep 2014 and increased 0.6 percent in the 12 months ending in Oct 2014. Average weekly earnings increased 2.9 percent in the 12 months ending in Nov 2014 and increased 0.1 percent in the 12 months ending in Dec 2014. Average weekly earnings increased 2.9 percent in the 12 months ending in Jan 2015 and increased 2.6 percent in the 12 months ending in Feb 2015. Average weekly earnings adjusted for inflation increased 2.3 percent in the 12 months ending in Mar 2015 and increased 2.5 percent in the 12 months ending in Apr 2015. Average weekly earnings adjusted for inflation increased 2.4 percent in the 12 months ending in May 2015 and increased 0.2 percent in the 12 months ending in Jun 2015. Average weekly earnings increased 2.0 percent in the 12 months ending in Jul 2015 and 4.2 percent in the 12 months ending in Aug 2015. Average weekly earnings adjusted for inflation increased 1.8 percent in the 12 months ending in Sep 2015 and increased 2.4 percent in the 12 months ending in Oct 2015. Average weekly earnings adjusted for inflation increased 1.6 percent in the 12 months ending in Nov 2015 and increased 1.5 percent in the 12 months ending in Dec 2015. Average weekly earnings increased 1.2 percent in the 12 months ending in Jan 2016. Average weekly earnings contracted 0.7 percent in the 12 months ending in Feb 2015 and contracted 0.6 percent in the 12 months ending in Mar 2016. Average weekly earnings increased 1.2 percent in the 12 months ending in Apr 2016 and increased 2.7 percent in the 12 months ending in May 2016. Average weekly earnings increased 1.3 percent in the 12 months ending in Jun 2016 and increased 1.6 percent in the 12 months ending in Jul 2016. Average weekly earnings decreased 1.2 percent in the 12 months ending in Aug 2016 and increased 1.5 percent in the 12 months ending in Sep 2016. Average weekly earnings increased 2.8 percent in the 12 months ending in Oct 2008. Table I-5 confirms the trend of deterioration of purchasing power of average weekly earnings in 2011 and into 2013 with oscillations according to carry trades causing world inflation waves (http://cmpassocregulationblog.blogspot.com/2016/07/oscillating-valuations-of-risk.html). On an annual basis, average weekly earnings in constant 1982-1984 dollars increased from $347.19 in 2007 to $354.30 in 2013, by 2.0 percent or at the average rate of 0.3 percent per year (data in http://www.bls.gov/data/). Annual average weekly earnings in constant dollars of $352.96 in 2010 fell 0.4 percent to $351.68 in 2012. Annual average weekly earnings increased from $347.19 in 2007 to $356.94 in 2014 or by 2.8 at the average rate of 0.4 percent. Annual average weekly earnings in constant increased from $347.19 in 2007 to $364.78 in 2015 by 5.1 percent at the average rate of 0.6 percent per year. Those who still work bring back home a paycheck that buys fewer high-quality goods than a year earlier. The fractured US job market does not provide an opportunity for advancement as in past booms following recessions because of poor job creation with 23.6 million unemployed or underemployed (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html) in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html) because of mediocre economic growth (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) available in the release for Jan 2016 and subsequent releases.

Table IB-5, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, NSA 2007-2016

Year	May	Jun	Jul	Aug	Sep	Oct
2006	337.97	340.92	345.81	340.60	344.02	352.68
2007	342.59	343.92	349.84	345.14	352.69	344.91
2008	337.84	341.61	334.32	338.41	338.90	342.99
2009	346.28	343.10	345.45	352.16	346.57	348.20
2010	356.33	349.50	351.55	358.43	352.80	356.00
2011	353.10	346.61	349.30	346.97	349.47	358.11
2012	347.04	348.83	355.63	348.33	356.98	348.76
∆%12M	-1.7	0.6	1.8	0.4	2.1	-2.6
2013	350.44	357.66	350.63	351.08	360.25	354.24
∆%12M	1.0	2.5	-1.4	0.8	0.9	1.6
2014	351.52	357.58	352.03	353.93	355.10	356.29
∆%12M	0.3	0.0	0.4	0.8	-1.4	0.6
2015	360.05	358.25	359.09	368.95	361.39	364.96
∆%12M	2.4	0.2	2.0	4.2	1.8	2.4
2016	369.87	362.82	364.97	364.50	366.76	375.02
∆%12M	2.7	1.3	1.6	-1.2	1.5	2.8

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

Chart IB-4 provides average weekly earnings of all employees in constant dollars of 1982-1984. The same pattern emerges of sharp decline during the contraction, followed by recovery in the expansion and continuing fall with oscillations caused by carry trades from zero interest rates into commodity futures from 2010 to 2011 and into 2012-2016. The increase in the final segment is mostly because of collapse of commodity prices in reversals of carry trade exposures. The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) available for the release of Jan 2016 and subsequent releases.

Chart IB-4, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2016

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

Chart IB-5 provides 12-month percentage changes of average weekly earnings of all employees in the US in constant dollars of 1982-1984. The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) available for the release of Jan 2016 and subsequent releases. There is the same pattern of contraction during the global recession in 2008 and then again weakness in the recovery without hiring and inflation waves. (http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html).

Chart IB-5, US, Average Weekly Earnings of All Employees NSA in Constant Dollars of 1982-1984 12-Month Percent Change, NSA 2007-2016

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

ESVIII Stagnating Real Disposable Income. The Bureau of Economic Analysis (BEA) provides a wealth of revisions and enhancements of US personal income and outlays since 1929 (http://www.bea.gov/iTable/index_nipa.cfm). Table IB-4 provides growth rates of real disposable income and real disposable income per capita in the long-term and selected periods. Real disposable income consists of after-tax income adjusted for inflation. Real disposable income per capita is income per person after taxes and inflation. There is remarkable long-term trend of growth of real disposable income of 3.2 percent per year on average from 1929 to 2015 and 2.0 percent in real disposable income per capita. Real disposable income increased at the average yearly rate of 3.7 percent from 1947 to 1999 and real disposable income per capita at 2.3 percent. These rates of increase broadly accompany rates of growth of GDP. Institutional arrangements in the United States provided the environment for growth of output and income after taxes, inflation and population growth. There is significant break of growth by much lower 2.4 percent for real disposable income on average from 1999 to 2015 and 1.5 percent in real disposable per capita income. Real disposable income grew at 3.5 percent from 1980 to 1989 and real disposable per capita income at 2.6 percent. In contrast, real disposable income grew at only 1.7 percent on average from 2006 to 2015 and real disposable income per capita at 0.9 percent. Real disposable income grew at 1.7 percent from 2007 to 2015 and real disposable income per capita at 0.8 percent. The United States has interrupted its long-term and cyclical dynamism of output, income and employment growth. Recovery of this dynamism could prove to be a major challenge. Cyclical uncommonly slow growth explains weakness in the current whole cycle instead of the allegation of secular stagnation.

Table IB-4, Average Annual Growth Rates of Real Disposable Income (RDPI) and Real Disposable Income per Capita (RDPIPC), Percent per Year 

RDPI Average ∆%
1929-2015	3.2
1947-1999	3.7
1999-2015	2.4
1999-2006	3.2
1980-1989	3.5
2006-2015	1.7
2007-2015	1.7
RDPIPC Average ∆%
1929-2015	2.0
1947-1999	2.3
1999-2015	1.5
1999-2006	2.2
1980-1989	2.6
2006-2015	0.9
2007-2015	0.8

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

Table IB-5 provides the comparison between the cycle of the 1980s and the current cycle. Real per capita disposable income (RDPI-PC) increased 27.0 percent from Dec 1979 to Apr 1990. In the comparable period in the current cycle from Dec 2007 to Oct 2016, real per capita disposable income increased 9.7 percent.

Table IB-5, Percentage Changes of Real Disposable Personal Income Per Capita

Month	RDPI-PC ∆% 12/79	RDPI-PC ∆% YOY	Month	RDPI-PC ∆% 12/07	RDPI-PC ∆% YOY
11/1982	2.4	0.7	6/2009	-0.6	-2.4
12/1982	2.9	1.3	9/2009	-1.3	-0.6
12/1983	7.8	4.8	6/2010	-0.4	0.2
12/1987	20.4	2.7	6/2014	4.2	2.6
1/1988	20.6	2.6	7/2014	4.3	2.8
2/1988	21.2	2.6	8/2014	4.7	3.0
3/1988	21.6	2.9	9/2014	4.8	2.9
4/1988	21.9	7.4	10/2014	5.2	3.6
5/1988	22.0	3.3	11/2014	5.5	3.7
6/1988	22.3	3.9	12/2014	5.8	3.9
7/1988	22.7	4.0	1/2015	5.8	3.6
8/1988	23.0	3.8	2/2015	5.9	3.2
9/1988	23.1	4.0	3/2015	5.8	2.5
10/1988	23.6	3.9	4/2015	6.4	2.9
11/1988	23.6	3.5	5/2015	6.7	2.8
12/1988	24.2	3.2	6/2015	6.9	2.6
1/1989	24.7	3.4	7/2015	7.1	2.6
2/1989	25.0	3.2	8/2015	7.3	2.5
3/1989	25.6	3.3	9/2015	7.5	2.5
4/1989	24.8	2.4	10/2015	7.7	2.4
5/1989	24.1	1.8	11/2015	7.8	2.1
6/1989	24.4	1.6	12/2015	8.2	2.3
7/1989	24.7	1.6	1/2016	8.2	2.3
8/1989	24.9	1.6	2/2016	8.2	2.1
9/1989	25.1	1.7	3/2016	8.4	2.4
10/1989	25.6	1.6	4/2016	8.7	2.1
11/1989	25.6	1.6	5/2016	8.8	2.0
12/1989	25.6	1.1	6/2016	9.0	2.0
1/1990	26.3	1.3	7/2016	9.3	2.1
2/1990	26.5	1.2	8/2016	9.3	1.8
3/1990	26.4	0.6	9/2016	9.4	1.8
4/1990	27.0	1.7	10/216	9.7	1.9

RDPI: Real Disposable Personal Income; RDPI-PC, Real Disposable Personal Income Per Capita

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

National Bureau of Economic Research

http://www.nber.org/cycles.html

Table IB-6 provides data for analysis of the current cycle. Real disposable income (RDPI) increased 17.6 percent from Dec 2007 to Oct 2016 (column RDPI ∆% 12/07). In the same period, real disposable income per capita increased 9.7 percent (column RDPI-PC ∆% 12/07). The annual equivalent rate of increase of real disposable income per capita is 1.1 percent, only a fraction of 2.0 percent on average from 1929 to 2015, and 1.9 percent for real disposable income, much lower than 3.2 percent on average from 1929 to 2015.

Table IB-6, Percentage Changes of Real Disposable Personal Income and Real Disposable Personal Income Per Capita

Month	RDPI ∆% 12/07	RDPI ∆% Month	RDPI ∆% YOY	RDPI-PC ∆% 12/07	RDPI-PC ∆% Month	RDPI-PC ∆% YOY
6/09	0.8	-1.7	-1.5	-0.6	-1.8	-2.4
9/09	0.3	0.1	0.3	-1.3	0.1	-0.6
6/10	1.8	0.0	1.0	-0.4	0.0	0.2
12/10	3.3	0.7	2.9	0.7	0.6	2.1
6/11	4.1	0.4	2.3	1.2	0.4	1.5
12/11	5.0	0.8	1.6	1.6	0.7	0.8
6/12	7.2	0.2	2.9	3.4	0.2	2.2
10/12	7.9	0.6	3.4	3.7	0.5	2.7
11/12	9.3	1.3	4.9	5.0	1.3	4.1
12/12	12.1	2.6	6.8	7.7	2.5	6.0
6/13	6.2	0.2	-1.0	1.6	0.2	-1.7
12/13	6.8	0.1	-4.8	1.8	0.0	-5.5
1/14	7.2	0.4	1.9	2.1	0.3	1.2
2/14	7.8	0.6	2.5	2.6	0.5	1.8
3/14	8.5	0.6	3.0	3.2	0.5	2.3
4/14	8.8	0.3	3.3	3.4	0.2	2.5
5/14	9.2	0.4	3.1	3.8	0.4	2.3
6/14	9.7	0.5	3.3	4.2	0.4	2.6
7/14	9.9	0.2	3.6	4.3	0.1	2.8
8/14	10.4	0.5	3.8	4.7	0.4	3.0
9/14	10.6	0.1	3.7	4.8	0.1	2.9
10/14	11.1	0.4	4.4	5.2	0.4	3.6
11/14	11.5	0.4	4.5	5.5	0.3	3.7
12/14	11.8	0.3	4.7	5.8	0.2	3.9
1/15	11.9	0.1	4.4	5.8	0.0	3.6
2/15	12.1	0.2	4.0	5.9	0.1	3.2
3/15	12.1	0.0	3.3	5.8	-0.1	2.5
4/15	12.7	0.6	3.7	6.4	0.5	2.9
5/15	13.1	0.4	3.6	6.7	0.3	2.8
6/15	13.4	0.3	3.4	6.9	0.2	2.6
7/15	13.7	0.2	3.4	7.1	0.2	2.6
8/15	14.1	0.3	3.3	7.3	0.2	2.5
9/15	14.3	0.2	3.3	7.5	0.1	2.5
10/15	14.6	0.3	3.2	7.7	0.2	2.4
11/15	14.7	0.1	2.9	7.8	0.1	2.1
12/15	15.3	0.5	3.0	8.2	0.4	2.3
1/16	15.4	0.1	3.1	8.2	0.0	2.3
2/16	15.4	0.0	2.9	8.2	0.0	2.1
3/16	15.6	0.2	3.2	8.4	0.2	2.4
4/16	16.0	0.3	2.9	8.7	0.3	2.1
5/16	16.3	0.2	2.8	8.8	0.2	2.0
6/16	16.6	0.2	2.8	9.0	0.2	2.0
7/16	17.0	0.3	2.9	9.3	0.3	2.1
8/16	17.0	0.1	2.6	9.3	0.0	1.8
9/16	17.2	0.2	2.6	9.4	0.1	1.8
10/16	17.6	0.4	2.7	9.7	0.3	1.9

RDPI: Real Disposable Personal Income; RDPI-PC, Real Disposable Personal Income Per Capita

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

National Bureau of Economic Research

http://www.nber.org/cycles.html

ESIX Financial Repression. McKinnon (1973) and Shaw (1974) argue that legal restrictions on financial institutions can be detrimental to economic development. “Financial repression” is the term used in the economic literature for these restrictions (see Pelaez and Pelaez, Globalization and the State, Vol. II (2008b), 81-6; for historical analysis see the landmark exhaustive research by Summerhill (2015) and earlier research by Pelaez (1975)). Theory and evidence support the role of financial institutions in efficiency and growth (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 22-6, Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 37-44). Excessive official regulation frustrates financial development required for growth (Haber 2011). Emphasis on disclosure can reduce bank fragility and corruption, empowering investors to enforce sound governance (Barth, Caprio and Levine 2006). Banking was important in facilitating economic growth in historical periods (Cameron 1961, 1967, 1972; Cameron et al. 1992). Banking is also important currently because small- and medium-size business may have no other form of financing than banks in contrast with many options for larger and more mature companies that have access to capital markets. Calomiris and Haber (2014) find that broad voting rights and institutions restricting coalitions of bankers and populists ensure stable banking systems and access to credit. Summerhill (2015) contributes momentous solid facts and analysis with an ideal method combining economic theory, econometrics, international comparisons, data reconstruction and exhaustive archival research. Summerhill (2015) finds that Brazil committed to service of sovereign foreign and internal debt. Contrary to conventional wisdom, Brazil generated primary fiscal surpluses during most of the Empire until 1889 (Summerhill 2015, 37-8, Figure 2.1). Econometric tests by Summerhill (2015, 19-44) show that Brazil’s sovereign debt was sustainable. Sovereign credibility in the North-Weingast (1989) sense spread to financial development that provided the capital for modernization in England and parts of Europe (see Cameron 1961, 1967). Summerhill (2015, 3, 194-6, Figure 7.1) finds that “Brazil’s annual cost of capital in London fell from a peak of 13.9 percent in 1829 to only 5.12 percent in 1889. Average rates on secured loans in the private sector in Rio, however, remained well above 12 percent through 1850.” Financial development would have financed diversification of economic activities, increasing productivity and wages and ensuring economic growth. Brazil restricted creation of limited liability enterprises (Summerhill 2015, 151-82) that prevented raising capital with issue of stocks and corporate bonds. Cameron (1961) analyzed how the industrial revolution in England spread to France and then to the rest of Europe. The Société Générale de Crédit Mobilier of Émile and Isaac Péreire provided the “mobilization of credit” for the new economic activities (Cameron 1961). Summerhill (2015, 151-9) provides facts and analysis demonstrating that regulation prevented the creation of a similar vehicle for financing modernization by Irineu Evangelista de Souza, the legendary Visconde de Mauá. Regulation also prevented the use of negotiable bearing notes of the Caisse Générale of Jacques Lafitte (Cameron 1961, 118-9). The government also restricted establishment and independent operation of banks (Summerhill 2015, 183-214). Summerhill (2005, 198-9) measures concentration in banking that provided economic rents or a social loss. The facts and analysis of Summerhill (2015) provide convincing evidence in support of the economic theory of regulation, which postulates that regulated entities capture the process of regulation to promote their self-interest. There appears to be a case that excessively centralized government can result in regulation favoring private instead of public interests with adverse effects on economic activity. The contribution of Summerhill (2015) explains why Brazil did not benefit from trade as an engine of growth—as did regions of recent settlement in the vision of nineteenth-century trade and development of Ragnar Nurkse (1959)—partly because of restrictions on financing and incorporation. 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.

Most regulatory actions trigger compensatory measures by the private sector that result in outcomes that are different from those intended by regulation (Kydland and Prescott 1977). Banks offered services to their customers and loans at rates lower than market rates to compensate for the prohibition to pay interest on demand deposits (Friedman 1970, 24). The prohibition of interest on demand deposits was eventually lifted in recent times. In the second half of the 1960s, already in the beginning of the Great Inflation (DeLong 1997), market rates rose above the ceilings of Regulation Q because of higher inflation. Nobody desires savings allocated to time or savings deposits that pay less than expected inflation. This is a fact currently with near zero interest rates, ¼ to ½ percent, and consumer price inflation of 1.6 percent in the 12 months ending in Oct 2016 (http://www.bls.gov/cpi/) but rising during waves of carry trades from zero interest rates to commodity futures exposures (http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/dollar-revaluation-world-inflation.html). Funding problems motivated compensatory measures by banks. Money-center banks developed the large certificate of deposit (CD) to accommodate increasing volumes of loan demand by customers. As Friedman (1970, 25) finds:

“Large negotiable CD’s were particularly hard hit by the interest rate ceiling because they are deposits of financially sophisticated individuals and institutions who have many alternatives. As already noted, they declined from a peak of $24 billion in mid-December, 1968, to less than $12 billion in early October, 1969.”

Banks created different liabilities to compensate for the decline in CDs. As Friedman (1970, 25; 1969) explains:

“The most important single replacement was almost surely ‘liabilities of US banks to foreign branches.’ Prevented from paying a market interest rate on liabilities of home offices in the United States (except to foreign official institutions that are exempt from Regulation Q), the major US banks discovered that they could do so by using the Euro-dollar market. Their European branches could accept time deposits, either on book account or as negotiable CD’s at whatever rate was required to attract them and match them on the asset side of their balance sheet with ‘due from head office.’ The head office could substitute the liability ‘due to foreign branches’ for the liability ‘due on CDs.”

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.”

Chart IB-14 of the Bureau of Economic Analysis (BEA) provides quarterly savings as percent of disposable income or the US savings rate from 1980 to 2016. There was a long-term downward sloping trend from 12 percent in the early 1980s to 1.9 percent in Jul 2005. The savings rate then rose during the contraction and in the expansion. In 2011 and into 2012 the savings rate declined as consumption is financed with savings in part because of the disincentive or frustration of receiving a few pennies for every $10,000 of deposits in a bank. The savings rate increased in the final segment of Chart IB-14 in 2012 because of the “fiscal cliff” episode followed by another decline because of the pain of the opportunity cost of zero remuneration for hard-earned savings. There are multiple recent oscillations during expectations of increase or “liftoff” of the fed funds rate in the United States followed by “shallow” monetary policy.

Chart IB-14, US, Personal Savings as a Percentage of Disposable Personal Income, Quarterly, 1980-2016

Source: US Bureau of Economic Analysis

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

Chart IB-14A provides the US personal savings rate, or personal savings as percent of disposable personal income, on an annual basis from 1929 to 2015. The US savings rate shows decline from around 10 percent in the 1960s to around 5 percent currently.

Chart IB-14A, US, Personal Savings as a Percentage of Disposable Personal Income, Annual, 1929-2015

Source: US Bureau of Economic Analysis

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

Table IB-7 provides personal savings as percent of disposable income and annual change of real disposable personal income in selected years since 1930. Savings fell from 4.4 percent of disposable personal income in 1930 to minus 0.8 percent in 1933 while real disposable income contracted 6.3 percent in 1930 and 2.9 percent in 1933. Savings as percent of disposable personal income swelled during World War II to 27.9 percent in 1944 with increase of real disposable income of 3.1 percent. Savings as percent of personal disposable income fell steadily over decades from 11.5 percent in 1982 to 2.6 percent in 2005. Savings as percent of disposable personal income was 5.0 percent in 2013 while real disposable income fell 1.4 percent. The savings rate was 5.6 percent of GDP in 2014 with growth of real disposable income of 3.5 percent. The savings rate was 5.8 percent in 2015 with growth of real disposable income of 3.5 percent. The average ratio of savings as percent of disposable income fell from 9.3 percent in 1980 to 1989 to 5.5 percent on average from 2007 to 2015. Real disposable income grew on average at 3.5 percent from 1980 to 1989 and at 1.7 percent on average from 2007 to 2015.

Table IB-7, US, Personal Savings as Percent of Disposable Personal Income, Annual, Selected Years 1929-1915

	Personal Savings as Percent of Disposable Personal Income	Annual Change of Real Disposable Personal Income
1930	4.4	-6.3
1933	-0.8	-2.9
1944	27.9	3.1
1947	6.3	-4.1
1954	10.3	1.4
1958	11.4	1.1
1960	10.0	2.6
1970	12.6	4.6
1975	13.0	2.5
1982	11.5	2.1
1989	7.8	3.0
1992	8.9	4.3
2002	5.0	3.1
2003	4.8	2.7
2004	4.5	3.6
2005	2.6	1.5
2006	3.3	4.0
2007	2.9	2.1
2008	4.9	1.5
2009	6.1	-0.4
2010	5.6	1.0
2011	6.0	2.5
2012	7.6	3.2
2013	5.0	-1.4
2014	5.6	3.5
2015	5.8	3.5
Average Savings Ratio
1980-1989	9.3
2007-2015	5.5
Average Yearly ∆% Real Disposable Income
1980-1989		3.5
2007-2015		1.7

Source: US Bureau of Economic Analysis

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

Chart IB-15 of the US Bureau of Economic Analysis provides personal savings as percent of personal disposable income, or savings ratio, from Jan 2007 to Oct 2016.

Chart IB-15, US, Personal Savings as a Percentage of Disposable Income, Monthly 2007-2016

Source: US Bureau of Economic Analysis

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

Table IB-8 provides the savings ratio and changes in real disposable income in selected years. The uncertainties caused by the global recession resulted in sharp increase in the savings ratio that peaked at 7.9 percent in May 2008 (http://www.bea.gov/iTable/index_nipa.cfm). The second peak occurred at 8.1 percent in May 2009. There was another rising trend until 5.9 percent in Jun 2010 and then steady downward trend until 5.6 percent in Nov 2011. This was followed by an upward trend with 7.6 percent in Jun 2012 but decline to 7.1 percent in Aug 2012 followed by jump to 11.0 percent in Dec 2012. Swelling realization of income in Oct-Dec 2012 in anticipation of tax increases in Jan 2013 caused the jump of the savings rate to 11.0 percent in Dec 2012. The BEA explains as “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf). There was a reverse effect in Jan 2013 with decline of the savings rate to 4.9 percent. Real disposable personal income fell 6.2 percent and real disposable per capita income fell from $38,639 in Dec 2012 to $36,216 in Jan 2013 or by 6.3 percent (http://www.bea.gov/iTable/index_nipa.cfm), which is explained by the Bureau of Economic Analysis as follows (page 3 http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf):

“Contributions for government social insurance -- a subtraction in calculating personal income --increased $6.4 billion in February, compared with an increase of $126.8 billion in January. The

January estimate reflected increases in both employer and employee contributions for government social insurance. The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base; together, these changes added $12.9 billion to January. Employer contributions were boosted $5.9 billion in January, which reflected increases in the social security taxable wage base (from $110,100 to $113,700), in the tax rates paid by employers to state unemployment insurance, and in employer contributions for the federal unemployment tax and for pension guaranty. The total contribution of special factors to the January change in contributions for government social insurance was $132.9 billion.”

Table IB-8, US, Savings Ratio and Real Disposable Income, % and ∆%

	Personal Saving as % Disposable Income	RDPI ∆% 12/07	RDPI ∆% Month	RDPI ∆% YOY
May 2008	7.9	5.1	4.8	5.7
May 2009	8.1	2.5	1.6	-2.5
Jun 2010	5.9	1.8	0.0	1.0
Nov 2011	5.6	4.2	-0.1	1.5
Jun 2012	7.6	7.2	0.2	2.9
Aug 2012	7.1	6.7	-0.2	2.1
Dec 2012	11.0	12.1	2.6	6.8
Jan 2013	4.9	5.2	-6.2	-0.5
Feb 2013	4.7	5.1	0.0	-1.1
Mar 2013	4.8	5.2	0.1	-1.2
Apr 2013	4.9	5.3	0.0	-1.5
May 2013	5.3	5.9	0.6	-1.0
Jun 2013	5.4	6.2	0.2	-1.0
Jul 2013	5.2	6.1	-0.1	-0.8
Aug 2013	5.4	6.4	0.3	-0.3
Sep 2013	5.3	6.7	0.3	-0.5
Oct 2013	4.8	6.4	-0.3	-1.3
Nov 2013	4.6	6.7	0.3	-2.4
Dec 2013	4.7	6.8	0.1	-4.8
Jan 2014	5.3	7.2	0.4	1.9
Feb 2014	5.3	7.8	0.6	2.5
Mar 2014	5.4	8.5	0.6	3.0
Apr 2014	5.5	8.8	0.3	3.3
May 2014	5.7	9.2	0.4	3.1
Jun 2014	5.8	9.7	0.5	3.3
Jul 2014	5.9	9.9	0.2	3.6
Aug 2014	5.6	10.4	0.5	3.8
Sep 2014	5.7	10.6	0.1	3.7
Oct 2014	5.6	11.1	0.4	4.4
Nov 2014	5.5	11.5	0.4	4.5
Dec 2014	5.7	11.8	0.3	4.7
Jan 2015	5.6	11.9	0.1	4.4
Feb 2015	5.7	12.1	0.2	4.0
Mar 2015	5.3	12.1	0.0	3.3
Apr 2015	5.7	12.7	0.6	3.7
May 2015	5.7	13.1	0.4	3.6
Jun 2015	5.8	13.4	0.3	3.4
Jul 2015	5.8	13.7	0.2	3.4
Aug 2015	5.9	14.1	0.3	3.3
Sep 2015	5.9	14.3	0.2	3.3
Oct 2015	6.1	14.6	0.3	3.2
Nov 2015	6.0	14.7	0.1	2.9
Dec 2015	6.1	15.3	0.5	3.0
Jan 2016	6.2	15.4	0.1	3.1
Feb 2016	6.0	15.4	0.0	2.9
Mar 2016	6.2	15.6	0.2	3.2
Apr 2016	5.9	16.0	0.3	2.9
May 2016	6.0	16.3	0.2	2.8
Jun 2016	5.8	16.6	0.2	2.8
Jul 2016	5.8	17.0	0.3	2.9
Aug 2016	6.0	17.0	0.1	2.6
Sep 2016	5.7	17.2	0.2	2.6
Oct 2016	6.0	17.6	0.4	2.7

Source: US Bureau of Economic Analysis

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

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