CMP Associates Regulation Blog: Interest Rate Risks, Twenty Eight Million Unemployed or Underemployed, Stagnating Real Wages, United States International Trade, World Cyclical Slow Growth and Global Recession Risk: Part I

Interest Rate Risks, Twenty Eight Million Unemployed or Underemployed, Stagnating Real Wages, United States International Trade, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

Executive Summary

I Twenty Eight 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

II United States International Trade

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 Increasing Interest Rate Risk, Tapering Quantitative Easing, Duration Dumping, Steepening

Yield Curve and Global Financial and Economic Risk

ESII Twenty Nine Million Unemployed or Underemployed

ESIII Job Creation

ESIV Stagnating Real Wages

ESV United States International Trade

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

Economic risks include the following:

China’s Economic Growth. China is lowering its growth target to 7.5 percent per year. China’s GDP growth decelerated from 12.1 percent in IQ2010 and 11.2 percent in IIQ2010 to 7.7 percent in IQ2013, 7.5 percent in IIQ2013 and 7.8 percent in IIIQ2013. GDP grew 7.7 percent in IVQ2013 relative to a year earlier and 1.8 percent relative to IIIQ2013, which is equivalent to 7.4 percent per year (http://cmpassocregulationblog.blogspot.com/2014/01/capital-flows-exchange-rates-and.html and earlier http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/07/tapering-quantitative-easing-policy-and_7005.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/01/recovery-without-hiring-world-inflation.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html). There is also concern about indebtedness, move to devaluation and deep policy reforms.
United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 29.3 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.
Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
World Inflation Waves. Inflation continues in repetitive waves globally (http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/squeeze-of-economic-activity-by-carry.html). There is growing concern on capital outflows and currency depreciation of emerging markets.

A list of financial uncertainties includes:

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

What is truly important is the fixing of the overnight fed funds at 0 to ¼ percent for which there is no end in sight as evident in the FOMC statement for Mar 19, 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20140319a.htm):

“To support continued progress toward maximum employment and price stability, the Committee today reaffirmed its view that a highly accommodative stance of monetary policy remains appropriate. In determining how long to maintain the current 0 to 1/4 percent target range for the federal funds rate, the Committee will assess progress--both realized and expected--toward 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 developments. The Committee continues to anticipate, based on its assessment of these factors, that it likely will be appropriate to maintain the current target range for the federal funds rate for a considerable time after the asset purchase program ends, especially if projected inflation continues to run below the Committee's 2 percent longer-run goal, and provided that longer-term inflation expectations remain well anchored.” (emphasis added).

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

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 Apr 3, 2014. Chart SA provides the yield of the ten-year Treasury constant maturity in the same dates. Both yields increased right after the guidance of Chair Yellen. The two-year yield remain at a higher level 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).

Chart S, US, Yield of Two-Year Treasury Constant Maturity, Mar 17 to Mar 27

Source: Board of Governors of the Federal Reserve System

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

Chart SA, US, Yield of Ten-Year Treasury Constant Maturity, Mar 17 to Mar 27

Source: Board of Governors of the Federal Reserve System

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

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

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

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

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

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 $2611 billion, or $2.6 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.

Chart VIII-1, Fed Funds Rate and Yields of Ten-year Treasury Constant Maturity and Baa Seasoned Corporate Bond, Jan 2, 2001 to Mar 27, 2014

Source: Board of Governors of the Federal Reserve System

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

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

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

Source: Board of Governors of the Federal Reserve System

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

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 Dec 2013 to Feb 2014, CPI inflation for all items seasonally adjusted was 1.6 percent in annual equivalent, obtained by calculating accumulated inflation from Dec 2013 to Feb 2014 and compounding for a full year. In the 12 months ending in Feb 2014, CPI inflation of all items not seasonally adjusted was 1.1 percent. Inflation in Feb 2014 seasonally adjusted was 0.1 percent relative to Jan 2014, or 1.2 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: 1.6 percent in 12 months and 1.2 percent in annual equivalent Dec 2013-Feb 2014. 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 0.036 percent for one month, 0.036 percent for three months, 0.058 percent for six months, 0.112 percent for one year, 0.415 percent for two years, 0.866 percent for three years, 1.699 percent for five years, 2.285 percent for seven years, 2.723 percent for ten years and 3.586 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 Feb 2014 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.

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 Apr 4, 2014, Dec 31, 2013, May 1, 2013, Apr 4, 2013 and Apr 4, 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 2.73 percent on Mar 28, 2014, 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 2.74 percent as occurred on Apr 4, 2013 would jump instantaneously from yield of 2.74 percent on Apr 4, 2014 to 4.87 percent as occurred on Apr 4, 2006 when the economy was closer to full employment. The price of the hypothetical bond issued with coupon of 2.74 percent would drop from 100 to 83.2952 after an instantaneous increase of the yield to 4.87 percent. The price loss would be 16.7 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

	4/04/14	12/31/13	5/01/13	3/28/13	3/28/06
1 M	0.03	0.01	0.03	0.07	4.64
3 M	0.03	0.07	0.06	0.07	4.68
6 M	0.05	0.10	0.08	0.10	4.85
1 Y	0.11	0.13	0.11	0.13	4.85
2 Y	0.43	0.38	0.20	0.22	4.84
3 Y	0.89	0.78	0.30	0.33	4.83
5 Y	1.71	1.75	0.65	0.69	4.82
7 Y	2.30	2.45	1.07	1.15	4.84
10 Y	2.74	3.04	1.66	1.78	4.87
20 Y	3.33	3.72	2.44	2.60	5.09
30 Y	3.59	3.96	2.83	2.99	4.91

M: Months; Y: Years

Source: United States Treasury

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

Interest rate risk is increasing in the US with amplifying fluctuations. Chart VI-13 of the Board of Governors provides the conventional mortgage rate for a fixed-rate 30-year mortgage. The rate stood at 5.87 percent on Jan 8, 2004, increasing to 6.79 percent on Jul 6, 2006. The rate bottomed at 3.35 percent on May 2, 2013. Fear of duration risk in longer maturities such as mortgage-backed securities caused continuing increases in the conventional mortgage rate that rose to 4.51 percent on Jul 11, 2013, 4.58 percent on Aug 22, 2013 and 4.41 percent on Apr 3, 2014, which is the last data point in Chart VI-13. Shayndi Raice and Nick Timiraos, writing on “Banks cut as mortgage boom ends,” on Jan 9, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303754404579310940019239208), analyze the drop in mortgage applications to a 13-year low, as measured by the Mortgage Bankers Association.

Chart VI-13, US, Conventional Mortgage Rate, Jan 8, 2004 to Apr 3, 2014

Source: Board of Governors of the Federal Reserve System

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

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 extracts four rows of Table VI-1 with the Dollar/EUR (USD/EUR) 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 devalued again to USD 1.3704/EUR on Apr 3, 2014 or by 15.0 percent {[(1.3704/1.192)-1]100 = 15.0%}. 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 revalued to CNY 6.2102/USD on Fri Apr 3, 2014, or by an additional 9.0 percent, for cumulative revaluation of 25.0 percent. The final row of Table VI-2 shows: devaluation of 0.4 percent in the week of Mar 14, 2014; devaluation of 1.2 percent in the week of Mar 21, 2014; revaluation of 0.2 percent the week of Mar 28, 2013; and no change in the week of Apr 3, 2013. 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	4/4/14
Rate	1.1423	1.5914	1.192	1.3704
CNY/USD	01/03 2000	07/21 2005	7/15 2008	4/4/ 2014
Rate	8.2798	8.2765	6.8211	6.2102
Weekly Rates	3/14/2014	3/21/2014	3/28/2014	4/4/ 2014
CNY/USD	6.1496	6.2247	6.2130	6.2102
∆% from Earlier Week*	-0.4	-1.2	0.2	0.0

*Negative sign is depreciation; positive sign is appreciation

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

Professor Edward P Lazear (2013Jan7), writing on “Chinese ‘currency manipulation’ is not the problem,” on Jan 7, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887323320404578213203581231448.html), provides clear thought on the role of the yuan in trade between China and the United States and trade between China and Europe. There is conventional wisdom that Chinese exchange rate policy causes the loss of manufacturing jobs in the United States, which is shown by Lazear (2013Jan7) to be erroneous. The fact is that manipulation of the CNY/USD rate by China has only minor effects on US employment. Lazear (2013Jan7) shows that the movement of monthly exports of China to its major trading partners, United States and Europe, since 1995 cannot be explained by the fixing of the CNY/USD rate by China. The period is quite useful because it includes rapid growth before 2007, contraction until 2009 and weak subsequent expansion. Chart VI-1 of the Board of Governors of the Federal Reserve System provides the CNY/USD exchange rate from Jan 3, 1995 to Mar 28, 2014 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 6.2117/USD on Mar 28, 2014, which is the last data point in Chart VI-1. Revaluation of the CNY relative to the USD by 25.0 percent by Apr 4, 2014 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. 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-Mar 28, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

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

Chart VI-1A provides the daily CNY/USD rate from Jan 5, 1981 to Mar 28, 2014. 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 6.2117/USD on Mar 28, 2014. 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-Mar 28, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

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

Chart VI-1B provides fine details with the rate of Chinese Yuan (CNY) to the US Dollar (USD) from Oct 28, 2011 to Mar 14, 2014. There have been alternations of revaluation and devaluation. The initial data point is CNY 6.3570 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 1.7 percent. Another devaluation is from CNY 6.042/USD on Jan 4, 2014 to CNY 6.2117 on Mar 28, 2014, or devaluation of 2.8 percent.

Chart VI-1B, Chinese Yuan (CNY) per US Dollar (US), Business Days, Oct 28, 2011-Mar 28, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

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

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 Mar 28, 2014. 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 in the current flight from emerging markets is MXN 13.0880/USD on Mar 28, 2014.

Chart VI-4A, Mexican Peso (MXN) per US Dollar (USD), Nov 8, 1993 to Mar 28, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://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 current Governor of the Reserve Bank of India, which is India’s central bank (http://www.rbi.org.in/scripts/AboutusDisplay.aspx). In this interview, Rajan argues that central banks should avoid unintended consequences on emerging market economies of inflows and outflows of capital triggered by monetary policy. 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. Chart VI-4B provides the rate of the Indian rupee (INR) per US dollar (USD) from Jan 2, 1973 to Mar 28, 2014. 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 58.8900/USD on Mar 28, 2014.

Chart VI-4B, Indian Rupee (INR) per US Dollar (USD), Jan 2, 1973 to Mar 28, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

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

ChVI-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 102.9200/USD on Mar 28, 2013 for appreciation of 17.1 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. 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-Mar 28, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

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

The financial crisis and global recession were caused by interest rate and housing subsidies and affordability policies that encouraged high leverage and risks, low liquidity and unsound credit (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4). Several past comments of this blog elaborate on these arguments, among which: http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html

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 2.2627/USD on Mar 28, 2013. 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 2.2627/USD on Mar 28, 2014 for depreciation of 47.2 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 Mar 28, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://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/USD on Sep 21, 2001 relative to Mar 3, 1999.

Chart VI-7, Brazilian Real (BRL) per US Dollar (USD), Jan 2, 1995 to Mar 28, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://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).

Current focus is on tapering quantitative easing by the Federal Open Market Committee (FOMC). There is sharp distinction between the two measures of unconventional monetary policy: (1) fixing of the overnight rate of fed funds at 0 to ¼ percent; and (2) outright purchase of Treasury and agency securities and mortgage-backed securities for the balance sheet of the Federal Reserve. Market are overreacting to the so-called “paring” of outright purchases of $55 billion of securities per month for the balance sheet of the Fed

(http://www.federalreserve.gov/newsevents/press/monetary/20140319a.htm):

“The Committee currently judges that there is sufficient underlying strength in the broader economy to support ongoing improvement in labor market conditions. In light of the cumulative progress toward maximum employment and the improvement in the outlook for labor market conditions since the inception of the current asset purchase program, the Committee decided to make a further measured reduction in the pace of its asset purchases. Beginning in April, the Committee will add to its holdings of agency mortgage-backed securities at a pace of $25 billion per month rather than $30 billion per month, and will add to its holdings of longer-term Treasury securities at a pace of $30 billion per month rather than $35 billion per month. The Committee is maintaining its existing policy of reinvesting principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities and of rolling over maturing Treasury securities at auction. The Committee's sizable and still-increasing holdings of longer-term securities should maintain downward pressure on longer-term interest rates, support mortgage markets, and help to make broader financial conditions more accommodative, which in turn should promote a stronger economic recovery and help to ensure that inflation, over time, is at the rate most consistent with the Committee's dual mandate.”

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

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

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

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

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

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

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

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

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

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

W = Y/r (10

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

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

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

Friedman (1953) argues there are three lags in effects of monetary policy: (1) between the need for action and recognition of the need; (2) the recognition of the need and taking of actions; and (3) taking of action and actual effects. Friedman (1953) finds that the combination of these lags with insufficient knowledge of the current and future behavior of the economy causes discretionary economic policy to increase instability of the economy or standard deviations of real income σ_y and prices σ_p. Policy attempts to circumvent the lags by policy impulses based on forecasts. We are all naïve about forecasting. Data are available with lags and revised to maintain high standards of estimation. Policy simulation models estimate economic relations with structures prevailing before simulations of policy impulses such that parameters change as discovered by Lucas (1977). Economic agents adjust their behavior in ways that cause opposite results from those intended by optimal control policy as discovered by Kydland and Prescott (1977). Advance guidance attempts to circumvent expectations by economic agents that could reverse policy impulses but is of dubious effectiveness. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/search?q=rules+versus+authorities). Jon Hilsenrath, writing on “New view into Fed’s response to crisis,” on Feb 21, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303775504579396803024281322?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes 1865 pages of transcripts of eight formal and six emergency policy meetings at the Fed in 2008 (http://www.federalreserve.gov/monetarypolicy/fomchistorical2008.htm). If there were an infallible science of central banking, models and forecasts would provide accurate information to policymakers on the future course of the economy in advance. Such forewarning is essential to central bank science because of the long lag between the actual impulse of monetary policy and the actual full effects on income and prices many months and even years ahead (Romer and Romer 2004, Friedman 1961, 1953, Culbertson 1960, 1961, Batini and Nelson 2002). The transcripts of the Fed meetings in 2008 (http://www.federalreserve.gov/monetarypolicy/fomchistorical2008.htm) analyzed by Jon Hilsenrath demonstrate that Fed policymakers frequently did not understand the current state of the US economy in 2008 and much less the direction of income and prices. The conclusion of Friedman (1953) is that monetary impulses increase financial and economic instability because of lags in anticipating needs of policy, taking policy decisions and effects of decisions. This is a fortiori true when untested unconventional monetary policy in gargantuan doses shocks the economy and financial markets.

The key policy is maintaining fed funds rate between 0 and ¼ percent. An increase in fed funds rates could cause flight out of risk financial markets worldwide. There is no exit from this policy without major financial market repercussions. Indefinite financial repression induces carry trades with high leverage, risks and illiquidity. A competing event is the high level of valuations of risk financial assets (http://cmpassocregulationblog.blogspot.com/2013/01/peaking-valuation-of-risk-financial.html). Matt Jarzemsky, writing on “Dow industrials set record,” on Mar 5, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324156204578275560657416332.html), analyzes that the DJIA broke the closing high of 14,164.53 set on Oct 9, 2007, and subsequently also broke the intraday high of 14,198.10 reached on Oct 11, 2007. The DJIA closed at 16,412.71 on Fri Apr 4, 2014, which is higher by 15.9 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 15.6 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs.

Jon Hilsenrath, writing on “Jobs upturn isn’t enough to satisfy Fed,” on Mar 8, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324582804578348293647760204.html), finds that much stronger labor market conditions are required for the Fed to end quantitative easing. Unconventional monetary policy with zero interest rates and quantitative easing is quite difficult to unwind because of the adverse effects of raising interest rates on valuations of risk financial assets and home prices, including the very own valuation of the securities held outright in the Fed balance sheet. Gradual unwinding of 1 percent fed funds rates from Jun 2003 to Jun 2004 by seventeen consecutive increases of 25 percentage points from Jun 2004 to Jun 2006 to reach 5.25 percent caused default of subprime mortgages and adjustable-rate mortgages linked to the overnight fed funds rate. The zero interest rate has penalized liquidity and increased risks by inducing carry trades from zero interest rates to speculative positions in risk financial assets. There is no exit from zero interest rates without provoking another financial crash.

The carry trade from zero interest rates to leveraged positions in risk financial assets had proved strongest for commodity exposures but US equities have regained leadership. The DJIA has increased 69.4 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Apr 4, 2014; S&P 500 has gained 82.4 percent and DAX 71.0 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 4/4/14” 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 13.6 percent below the trough. Japan’s Nikkei Average is 70.7 percent above the trough. DJ Asia Pacific TSM is 25.4 percent above the trough. Dow Global is 47.8 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 28.6 percent above the trough. NYSE Financial Index is 49.5 percent above the trough. DJ UBS Commodities is 8.7 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 71.0 percent above the trough. Japan’s Nikkei Average is 70.7 percent above the trough on Aug 31, 2010 and 32.2 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 15,063.77 on Fri Apr 4, 2014 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 46.9 percent higher than 10,254.43 on Mar 11, 2011, on the date of the Tōhoku or Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar depreciated by 15.0 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 4/5/14” in Table VI-4 shows increase of 0.8 percent in the week for China’s Shanghai Composite. DJ Asia Pacific increased 1.8 percent. NYSE Financial increased 0.8 percent in the week. DJ UBS Commodities changed 0.0 percent. Dow Global increased 1.3 percent in the week of Apr 4, 2014. The DJIA increased 0.5 percent and S&P 500 increased 0.4 percent. DAX of Germany increased 1.1 percent. STOXX 50 increased 1.3 percent. The USD appreciated 0.3 percent. There are still high uncertainties on European sovereign risks and banking soundness, US and world growth slowdown and China’s growth tradeoffs. Sovereign problems in the “periphery” of Europe and fears of slower growth in Asia and the US cause risk aversion with trading caution instead of more aggressive risk exposures. There is a fundamental change in Table VI-4 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 4/4/14” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Apr 4, 2014. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 4/4/14” but also relative to the peak in column “∆% Peak to 4/4/14.” There are now several equity indexes above the peak in Table VI-4: DJIA 46.5 percent, S&P 500 53.2 percent, DAX 53.1 percent, Dow Global 20.6 percent, DJ Asia Pacific 9.8 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 19.1 percent, Nikkei Average 32.2 percent and STOXX 50 8.9 percent. There is only one equity index below the peak: Shanghai Composite by 34.9 percent. DJ UBS Commodities Index is now 7.1 percent below the peak. The US dollar strengthened 9.4 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010.

Alexandra Scaggs, writing on “Tepid profits, roaring stocks,” on May 16, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323398204578487460105747412.html), analyzes stabilization of earnings growth: 70 percent of 458 reporting companies in the S&P 500 stock index reported earnings above forecasts but sales fell 0.2 percent relative to forecasts of increase of 0.5 percent. Paul Vigna, writing on “Earnings are a margin story but for how long,” on May 17, 2013, published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2013/05/17/earnings-are-a-margin-story-but-for-how-long/), analyzes that corporate profits increase with stagnating sales while companies manage costs tightly. More than 90 percent of S&P components reported moderate increase of earnings of 3.7 percent in IQ2013 relative to IQ2012 with decline of sales of 0.2 percent. Earnings and sales have been in declining trend. In IVQ2009, growth of earnings reached 104 percent and sales jumped 13 percent. Net margins reached 8.92 percent in IQ2013, which is almost the same at 8.95 percent in IIIQ2006. Operating margins are 9.58 percent. There is concern by market participants that reversion of margins to the mean could exert pressure on earnings unless there is more accelerated growth of sales. Vigna (op. cit.) finds sales growth limited by weak economic growth. Kate Linebaugh, writing on “Falling revenue dings stocks,” on Oct 20, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444592704578066933466076070.html?mod=WSJPRO_hpp_LEFTTopStories), identifies a key financial vulnerability: falling revenues across markets for United States reporting companies. Global economic slowdown is reducing corporate sales and squeezing corporate strategies. Linebaugh quotes data from Thomson Reuters that 100 companies of the S&P 500 index have reported declining revenue only 1 percent higher in Jun-Sep 2012 relative to Jun-Sep 2011 but about 60 percent of the companies are reporting lower sales than expected by analysts with expectation that revenue for the S&P 500 will be lower in Jun-Sep 2012 for the entities represented in the index. Results of US companies are likely repeated worldwide. Future company cash flows derive from investment projects. In IQ1980, gross private domestic investment in the US was $951.6 billion of 2009 dollars, growing to $1,174.4 billion in IIQ1987 or 23.4 percent. Real gross private domestic investment in the US increased 1.5 percent from $2,605.2 billion of 2009 dollars in IVQ2007 to $2,643.3 billion in IVQ2013. As shown in Table IAI-2, real private fixed investment fell 2.9 percent from $2,586.3 billion of 2009 dollars in IVQ2007 to $2,511.2 billion in IVQ2013. Growth of real private investment in Table IA1-2 is mediocre for all but four quarters from IIQ2011 to IQ2012 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). The investment decision of United States corporations has been fractured in the current economic cycle in preference of cash. Corporate profits with IVA and CCA fell $26.6 billion in IQ2013 after increasing $34.9 billion in IVQ2012 and $13.9 billion in IIIQ2012. Corporate profits with IVA and CCA rebounded with $66.8 billion in IIQ2013 and $39.2 billion in IIIQ2013. Corporate profits with IVA and CCA increased $47.1 billion in IVQ2013. Profits after tax with IVA and CCA fell $1.7 billion in IQ2013 after increasing $40.8 billion in IVQ2012 and $4.5 billion in IIIQ2012. In IIQ2013, profits after tax with IVA and CCA increased $56.9 billion and $39.5 billion in IIIQ2013. In IVQ2013, profits after tax with IVA and CCA increased $33.8 billion. Anticipation of higher taxes in the “fiscal cliff” episode caused increase of $120.9 billion in net dividends in IVQ2012 followed with adjustment in the form of decrease of net dividends by $103.8 billion in IQ2013, rebounding with $273.5 billion in IIQ2013. Net dividends fell at $179.0 billion in IIIQ2013 and increased at $90.5 billion in IVQ2013. There is similar decrease of $80.1 billion in undistributed profits with IVA and CCA in IVQ2012 followed by increase of $102.1 billion in IQ2013 and decline of $216.6 billion in IIQ2013. Undistributed profits with IVA and CCA rose at $218.6 billion in IIIQ2013 and fell at $56.7 billion in IVQ2013. Undistributed profits of US corporations swelled 375.4 percent from $107.7 billion IQ2007 to $512.0 billion in IVQ2013 and changed signs from minus $55.9 billion in billion in IVQ2007 (Section IA2). In IQ2013, corporate profits with inventory valuation and capital consumption adjustment fell $26.6 billion relative to IVQ2012, from $2047.2 billion to $2020.6 billion at the quarterly rate of minus 1.3 percent. In IIQ2013, corporate profits with IVA and CCA increased $66.8 billion from $2020.6 billion in IQ2013 to $2087.4 billion at the quarterly rate of 3.3 percent. Corporate profits with IVA and CCA increased $39.2 billion from $2087.4 billion in IIQ2013 to $2126.6 billion in IIIQ2013 at the annual rate of 1.9 percent. Corporate profits with IVA and CCA increased at $47.1 billion in IVQ2013 from $2126.6 billion in IIIQ2013 to $2173.7 billion in IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp4q13_3rd.pdf).

Uncertainty originating in fiscal, regulatory and monetary policy causes wide swings in expectations and decisions by the private sector with adverse effects on investment, real economic activity and employment. The investment decision of US business is fractured. 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 4/4/ /14	∆% Week 4/4/14	∆% Trough to 4/4/ 14
DJIA	4/26/ 10	7/2/10	-13.6	46.5	0.5	69.4
S&P 500	4/23/ 10	7/20/ 10	-16.0	53.2	0.4	82.4
NYSE Finance	4/15/ 10	7/2/10	-20.3	19.1	0.8	49.5
Dow Global	4/15/ 10	7/2/10	-18.4	20.6	1.3	47.8
Asia Pacific	4/15/ 10	7/2/10	-12.5	9.8	1.8	25.4
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	32.2	2.5	70.7
China Shang.	4/15/ 10	7/02 /10	-24.7	-34.9	0.8	-13.6
STOXX 50	4/15/10	7/2/10	-15.3	8.9	1.3	28.6
DAX	4/26/ 10	5/25/ 10	-10.5	53.1	1.1	71.0
Dollar Euro	11/25 2009	6/7 2010	21.2	9.4	0.3	-15.0
DJ UBS Comm.	1/6/ 10	7/2/10	-14.5	-7.1	0.0	8.7
10-Year T Note	4/5/ 10	4/6/10	3.986	2.784	2.724

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 Twenty Eight Million Unemployed or Underemployed. 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 11.4 percent and the number of people in job stress could be around 28.2 million, which is 17.2 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 Feb 2013, Jan 2014 and Feb 2014 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 (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). Table I-4b provides the yearly labor force participation rate from 1979 to 2014. 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 Mar 2013, Feb 2014 and Mar 2014 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 63.1 percent by Mar 2013 and was 62.7 percent in Feb 2014 and 62.9 percent in Mar 2014, 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 8.058 million unemployed in Mar 2014 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 19.595 million (Total UEM) and not 10.537 million (UEM) of whom many have been unemployed long term
the rate of unemployment is 11.9 percent (Total UEM%) and not 6.8 percent, not seasonally adjusted, or 6.7 percent seasonally adjusted
the number of people in job stress is close to 28.2 million by adding the 8.053 million leaving the labor force because they believe they could not find another job.

The row “In Job Stress” in Table I-4 provides the number of people in job stress not seasonally adjusted at 28.218 million in Mar 2014, 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 17.2 percent of the labor force in Mar 2014. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 58.2 percent in Mar 2013, 58.3 percent in Feb 2014 and 58.7 percent in Mar 2014. The number employed in Mar 2014 was 145.090 million (NSA) or 2.225 million fewer people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population increased from 231.958 million in Jul 2007 to 247.258 million in Mar 2014 or by 15.300 million. The number employed fell 1.5 percent from Jul 2007 to Mar 2014 while population increased 6.6 percent. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

What really matters for labor input in production and wellbeing is the number of people with jobs or the employment/population ratio, which has declined and does not show signs of increasing. There are several million fewer people working in 2014 than in 2006 and the number employed is not increasing while population increased 15.300 million. 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/2014/03/global-financial-risks-recovery-without.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 17 million and does not show signs of increasing in an unusual recovery without hiring (http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html). 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). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth under trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,098.0 billion than actual $15,942.3 billion. There are about two trillion dollars of GDP less than under trend, explaining the 28.2 million unemployed or underemployed equivalent to actual unemployment of 17.2 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,942.3 billion in IVQ2013 or 6.3 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because 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.

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

	2006	Mar 2013	Feb 2014	Mar 2014
POP	229	244,995	247,085	247,258
LF	151	154,512	155,027	155,627
PART%	66.2	63.1	62.7	62.9
EMP	144	142,698	144,134	145,090
EMP/POP%	62.9	58.2	58.3	58.7
UEM	7	11,815	10,893	10,537
UEM/LF Rate%	4.6	7.6	7.0	6.8
NLF	77	90,483	92,058	91,630
LF PART 66.2%		162,187	163,570	163,685
∆NLF UEM		7,675	8,543	8,058
Total UEM		19,490	19,436	18,595
Total UEM%		12.0	11.9	11.4
Part Time Economic Reasons		7,734	7,397	7,455
Marginally Attached to LF		2,326	2,303	2,168
In Job Stress		29,550	29,136	28,218
People in Job Stress as % Labor Force		18.2	17.8	17.2

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 and 62.9 percent in Mar 2014. 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/2014/03/global-financial-risks-recovery-without.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, 1979-2014

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

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, 1979-2014

Source: Bureau of Labor Statistics

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

Broader perspective is provided by 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, 1948-2014

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, 1948-2014

Sources: US Bureau of Labor Statistics

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

The rate of labor force participation of the US is in Chart I-12E from 1948 to 2014. There is sudden decline during the global recession after 2007 without recovery explained by cyclic factors (Lazear and Spletzer 2012JHJul22) as many potential workers stopped their job searches disillusioned that there could be an opportunity for them in sharply contracted labor markets.

Chart I-12E, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1948-2014

Sources: US Bureau of Labor Statistics

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

ESIII 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 2013. The civilian noninstitutional population grew by 41.0 percent from 174.215 million in 1983 to 245.679 million in 2013 and labor force higher by 39.3 percent, growing from 111.550 million in 1983 to 155.389 million in 2013. Total nonfarm payroll employment seasonally adjusted (SA) increased 192,000 in Mar 2014 and private payroll employment rose 192,000. The average number of nonfarm jobs created from Mar 2012 to Mar 2013 was 168,750, using seasonally adjusted data, while the average number of nonfarm jobs created from Mar 2013 to Mar 2014 was 187,167, or increase by 10.9 percent. The average number of private jobs created in the US from Mar 2012 to Mar 2013 was 175,167, using seasonally adjusted data, while the average from Mar 2013 to Mar 2014 was 188,750, or increase by 7.8 percent. This blog calculates the effective labor force of the US at 162.187 million in Mar 2013 and 163.685 million in Mar 2014 (Table I-4), for growth of 1.498 million at average 124,833 per month. The difference between the average increase of 188,750 new private nonfarm jobs per month in the US from Mar 2013 to Mar 2014 and the 124,833 average monthly increase in the labor force from Mar 2013 to Mar 2014 is 63,917 monthly new jobs net of absorption of new entrants in the labor force. There are 28.218 million in job stress in the US currently. Creation of 63,917 new jobs per month net of absorption of new entrants in the labor force would require 441 months to provide jobs for the unemployed and underemployed (28.218 million divided by 63,917) or 37 years (502 divided by 12). The civilian labor force of the US in Mar 2014 not seasonally adjusted stood at 155.627 million with 10.537 million unemployed or effectively 18.595 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 163.685 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 1.3 years (1 million divided by product of 63,917 by 12, which is 767,004). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.781 million (0.05 times labor force of 155.627 million) for new net job creation of 2.756 million (10.537 million unemployed minus 7.781 million unemployed at rate of 5 percent) that at the current rate would take 3.6 years (2.756 million divided by 0.767004). Under the calculation in this blog, there are 18.595 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 163.685 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 11.257 million jobs net of labor force growth that at the current rate would take 13.6 years (18.595 million minus 0.05(163.685 million) = 10.411 million divided by 0.767004, 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 Mar 2014 was 145.090 million (NSA) or 2.225 million fewer people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population increased from 231.958 million in Jul 2007 to 247.258 million in Mar 2014 or by 15.300 million. The number employed fell 1.5 percent from Jul 2007 to Mar 2014 while population increased 6.6 percent. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

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/2014/02/theory-and-reality-of-cyclical-slow.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 under trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,098.0 billion than actual $15,942.3 billion. There are about two trillion dollars of GDP less than under trend, explaining the 28.2 million unemployed or underemployed equivalent to actual unemployment of 17.2 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,942.3 billion in IVQ2013 or 6.3 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because 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.

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

Month	1981	1982	1983	2008	2009	2010	Private
Jan	94	-326	224	15	-798	18	20
Feb	68	-5	-75	-86	-701	-50	-38
Mar	105	-130	172	-80	-826	156	113
Apr	73	-280	276	-214	-684	251	192
May	10	-45	277	-182	-354	516	94
Jun	197	-243	379	-172	-467	-122	110
Jul	112	-342	418	-210	-327	-61	120
Aug	-36	-158	-308	-259	-216	-42	117
Sep	-87	-181	1115	-452	-227	-57	107
Oct	-99	-277	271	-474	-198	241	199
Nov	-209	-123	353	-765	-6	137	149
Dec	-278	-14	356	-697	-283	71	94
			1984			2011	Private
Jan			446			70	72
Feb			481			168	223
Mar			275			212	231
Apr			363			322	320
May			308			102	166
Jun			379			217	186
Jul			313			106	219
Aug			242			122	125
Sep			310			183	268
Oct			286			183	177
Nov			349			164	191
Dec			128			196	222
			1985			2012	Private
Jan			266			360	364
Feb			124			226	228
Mar			346			243	246
Apr			196			96	102
May			274			110	131
Jun			146			88	75
Jul			190			160	172
Aug			193			150	136
Sep			203			161	159
Oct			188			225	255
Nov			209			203	211
Dec			167			214	215
			1986			2013	Private
Jan			125			197	219
Feb			107			280	263
Mar			94			141	164
Apr			187			203	188
May			127			199	222
Jun			-94			201	201
Jul			318			149	170
Aug			114			202	180
Sep			347			164	153
Oct			186			237	247
Nov			186			274	272
Dec			205			84	86
			1987			2014	Private
Jan			172			144	166
Feb			232			197	188
Mar			249			192	192

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Charts numbered from I-38 to I-41 from the database of the Bureau of Labor Statistics provide a comparison of payroll survey data for the contractions and expansions in the 1980s and after 2007. Chart I-38 provides total nonfarm payroll jobs from 2001 to 2013. The sharp decline in total nonfarm jobs during the contraction after 2007 has been followed by initial stagnation and then inadequate growth in 2012 and 2013-2014 while population growth continued.

Chart I-38, US, Total Nonfarm Payroll Jobs SA 2001-2014

Source: US Bureau of Labor Statistics

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

Chart I-39 provides total nonfarm jobs SA from 1979 to 1989. Recovery is strong throughout the decade with the economy growing at trend over the entire economic cycle.

Chart I-39, US, Total Nonfarm Payroll Jobs SA 1979-1989

Source: US Bureau of Labor Statistics

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

Most job creation in the US is by the private sector. Chart I-40 shows the sharp destruction of private payroll jobs during the contraction after 2007. There has been growth after 2010 but insufficient to recover higher levels of employment prevailing before the contraction. At current rates, recovery of employment may spread over several years in contrast with past expansions of the business cycle in the US.

Chart I-40, US, Total Private Payroll Jobs SA 2001-2014

Source: US Bureau of Labor Statistics

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

In contrast, growth of private payroll jobs in the US recovered vigorously during the expansion in 1983 through 1985, as shown in Chart I-41. Rapid growth of creation of private jobs continued throughout the 1980s.

Chart I-41, US, Total Private Payroll Jobs SA 1979-1989

Source: US Bureau of Labor Statistics

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

ESIV Stagnating Real Wages. Average weekly hours in Table IB-2 fell from 34.9 in Dec 2007 at the beginning of the contraction to 33.8 in Jun 2009, which was the last month of the contraction. Average weekly hours rose to 34.4 in Dec 2011 and oscillated to 34.9 in Dec 2012 and 34.7 in Dec 2013. Average weekly hours of all employees eased to 34.7 in Mar 2014.

Table IB-2, US, Average Weekly Hours of All Employees, NSA 2006-2014

Year	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
2006			34.2	34.6	34.3	34.6	34.9	34.6	34.5	34.9	34.4	34.6
2007	34.1	34.1	34.3	34.7	34.4	34.7	34.9	34.7	35.0	34.5	34.5	34.9
2008	34.1	34.2	34.7	34.4	34.4	34.9	34.5	34.6	34.4	34.4	34.6	34.1
2009	33.8	34.2	33.9	33.6	33.7	33.8	33.8	34.3	33.7	33.8	34.2	33.9
2010	33.7	33.6	33.8	34.0	34.4	34.1	34.2	34.7	34.1	34.3	34.2	34.2
2011	34.2	34.0	34.1	34.2	34.6	34.4	34.4	34.4	34.4	34.8	34.3	34.4
2012	34.5	34.2	34.2	34.6	34.2	34.4	34.8	34.5	34.9	34.3	34.3	34.9
2013	34.0	34.2	34.3	34.3	34.3	34.9	34.3	34.5	34.9	34.4	34.4	34.7
2014	34.0	34.4	34.7

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart IB-1 provides average weekly hours monthly from Mar 2006 to Mar 2014. Average weekly hours remained relatively stable in the period before the contraction and fell sharply during the contraction as business could not support lower production with the same labor input. Average weekly hours rose rapidly during the expansion but have stabilized at a level below that prevailing before the contraction.

Chart IB-1, US, Average Weekly Hours of All Employees, SA 2006-2014

Source: US Bureau of Labor Statistics

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

Calculations of inflation-adjusted average hourly earnings using BLS data are in Table IB-3. The final column of Table IB-3 (“12 Month Real ∆%”) provides inflation-adjusted average hourly earnings of all employees in the US. 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 four 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 0.6 percent in Mar 2012. There was a gain of 0.5 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 1.3 percent in Oct 2012 and gained 1.0 percent in Dec 2012 but declined 0.3 percent in Jan 2013 and stagnated at change of 0.1 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 0.6 percent in May 2013. In Jun 2013, real hourly earnings increased 1.0 percent relative to Jun 2012. Real hourly earnings fell 0.6 percent in the 12 months ending in Jul 2013 and increased 0.7 percent in the 12 months ending in Aug 2013. Real hourly earnings increased 1.2 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 0.3 percent in the 12 months ending in Jan 2014 and 1.7 percent in the 12 months ending in Feb 2014. 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/2014/03/interest-rate-risks-world-inflation.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html) originating in weak economic growth (http://cmpassocregulationblog.blogspot.com/2014/03/financial-uncertainty-mediocre-cyclical.html).

Table IB-3, US, Average Hourly Earnings Nominal and Inflation Adjusted, Dollars and % NSA

	AHE ALL	12 Month Nominal ∆%	∆% 12 Month CPI	12 Month Real ∆%
2007
Jan*	$20.69*	4.2*	2.1	2.1*
Feb*	$20.77*	4.1*	2.4	1.7*
Mar	$20.80	3.6	2.8	0.8
Apr	$21.03	3.3	2.6	0.7
May	$20.82	3.8	2.7	1.1
Jun	$20.81	3.8	2.7	1.1
Jul	$20.97	3.4	2.4	1.0
Aug	$20.83	3.5	2.0	1.5
Sep	$21.17	4.0	2.8	1.2
Oct	$21.05	2.6	3.5	-0.9
Nov	$21.12	3.3	4.3	-1.0
Dec	$21.35	3.6	4.1	-0.5
2010
Jan	$22.53	2.0	2.6	-0.6
Feb	$22.59	1.4	2.1	-0.7
Mar	$22.49	1.1	2.3	-1.2
Apr	$22.54	1.8	2.2	-0.4
May	$22.61	2.5	2.0	0.5
Jun	$22.35	1.7	1.1	0.6
Jul	$22.42	1.8	1.2	0.6
Aug	$22.55	1.7	1.1	0.6
Sep	$22.61	1.8	1.1	0.7
Oct	$22.70	1.9	1.2	0.7
Nov	$22.70	1.1	1.1	0.0
Dec	$22.77	1.7	1.5	0.2
2011
Jan	$23.17	2.8	1.6	1.2
Feb	$23.00	1.8	2.1	-0.3
Mar	$22.91	1.9	2.7	-0.8
Apr	$22.97	1.9	3.2	-1.3
May	$23.07	2.0	3.6	-1.5
Jun	$22.82	2.1	3.6	-1.4
Jul	$22.95	2.4	3.6	-1.2
Aug	$22.86	1.4	3.8	-2.3
Sep	$23.06	2.0	3.9	-1.8
Oct	$23.31	2.7	3.5	-0.8
Nov	$23.16	2.0	3.4	-1.4
Dec	$23.22	2.0	3.0	-1.0
2012
Jan	$23.57	1.7	2.9	-1.2
Feb	$23.41	1.8	2.9	-1.1
Mar	$23.40	2.1	2.7	-0.6
Apr	$23.62	2.8	2.3	0.5
May	$23.33	1.1	1.7	-0.6
Jun	$23.28	2.0	1.7	0.3
Jul	$23.49	2.4	1.4	1.0
Aug	$23.27	1.8	1.7	0.1
Sep	$23.68	2.7	2.0	0.7
Oct	$23.52	0.9	2.2	-1.3
Nov	$23.59	1.9	1.8	0.1
Dec	$23.85	2.7	1.7	1.0
2013
Jan	$23.88	1.3	1.6	-0.3
Feb	$23.91	2.1	2.0	0.1
Mar	$23.84	1.9	1.5	0.4
Apr	$23.92	1.3	1.1	0.2
May	$23.80	2.0	1.4	0.6
Jun	$23.93	2.8	1.8	1.0
Jul	$23.81	1.4	2.0	-0.6
Aug	$23.79	2.2	1.5	0.7
Sep	$24.16	2.0	1.2	0.8
Oct	$24.04	2.2	1.0	1.2
Nov	$24.11	2.2	1.2	1.0
Dec	$24.30	1.9	1.5	0.4
2014
Jan	$24.35	2.0	1.6	0.4
Feb	$24.58	2.8	1.1	1.7
Mar	$24.47	2.6

Note: AHE ALL: average hourly earnings of all employees; CPI: consumer price index; Real: adjusted by CPI inflation; NA: not available

*AHE of production and nonsupervisory employees because of unavailability of data for all employees for Jan-Feb 2006

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Average hourly 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 provided in Table IB-4. Average hourly earnings fell 0.5 percent after adjusting for inflation in the 12 months ending in Mar 2012 and gained 0.6 percent in the 12 months ending in Apr 2012 but then lost 0.6 percent in the 12 months ending in May 2012. Average hourly earnings in the US in constant dollars of 1982-1984 increased 0.3 percent in the 12 months ending in Jun 2012 and 0.9 percent in Jul 2012 followed by 0.1 percent in Aug 2012 and 0.7 percent in Sep 2012. Average hourly earnings adjusted by inflation fell 1.2 percent in the 12 months ending in Oct 2012. Average hourly earnings adjusted by inflation increased 0.1 percent in the 12 months ending in Nov 2012 and 1.0 percent in the 12 months ending in Dec 2012 but fell 0.3 percent in the 12 months ending in Jan 2013 and stagnated with gain of 0.2 percent in the 12 months ending in Feb 2013. Average hourly earnings adjusted for inflation increased 0.4 percent in the 12 months ending in Mar 2013 and increased 0.2 percent in the 12 months ending in Apr 2013. Average hourly earnings adjusted for inflation increased 0.7 percent in the 12 months ending in May 2013 and 1.1 percent in the 12 months ending in Jun 2013. Average hourly earnings of all employees adjusted for inflation fell 0.6 percent in the 12 months ending in Jul 2013 and increased 0.7 percent in the 12 months ending in Aug 2013. Average hourly earnings adjusted for inflation increased 0.9 percent in the 12 months ending in Sep 2013 and increased 1.2 percent in the 12 months ending in Oct 2013. Average hourly earnings adjusted for inflation increased 0.9 percent in the 12 months ending in Nov 2013. Average hourly earnings increased 0.4 percent in the 12 months ending in Dec 2013 and 0.4 percent in the 12 months ending in Jan 2014. Average hourly earnings adjusted for inflation increased 1.7 percent in the 12 months ending in Feb 2014. Table IB-4 confirms the trend of deterioration of purchasing power of average hourly earnings in 2011 and into 2012 with 12-month percentage declines in three of the first three months of 2012 (-1.1 percent in Jan, -1.1 percent in Feb and -0.5 percent in Mar), declines of 0.6 percent in May and 1.2 percent in Oct and increase in five (0.6 percent in Apr, 0.3 percent in Jun, 0.9 percent in Jul, 0.7 percent in Sep and 1.0 percent in Dec) and stagnation in two (0.1 percent in Aug and 0.1 percent in Nov). Average hourly earnings adjusted for inflation fell 0.3 percent in the 12 months ending in Jan 2013, virtually stagnated with gain of 0.2 percent in the 12 months ending in Feb 2013 and gained 0.4 percent in the 12 months ending Mar 2013. Real average hourly earnings increased 0.2 percent in the 12 months ending in Apr 2013 and 0.7 percent in the 12 months ending in May 2013. Average hourly earnings increased 1.1 percent in the 12 months ending in Jun 2013 and fell 0.6 percent in the 12 months ending in Jul 2013. Annual data are revealing: -0.7 percent in 2008 during carry trades into commodity futures in a global recession, 3.1 percent in 2009 with reversal of carry trades, muted change of 0.1 percent in 2010 and no change in 2012 and decline by 1.1 percent in 2011. Average hourly earnings adjusted for inflation increased 0.5 percent in 2013. Annual average hourly earnings of all employees in the United States adjusted for inflation increased 1.9 percent from 2007 to 2013 at the yearly average rate of 0.3 percent (from $10.10 in 2007 to $10.29 in 2013 in constant dollars of 1982-1984 using data in http://www.bls.gov/data/). Those who still work bring back home a paycheck that buys fewer goods than a year earlier and savings in bank deposits do not pay anything because of financial repression (http://cmpassocregulationblog.blogspot.com/2014/03/financial-uncertainty-mediocre-cyclical.html).

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

Year	Jan	Feb	Aug	Sep	Oct	Nov	Dec
2006			9.87	10.03	10.16	10.14	10.21
2007	10.22	10.21	10.02	10.15	10.07	10.05	10.16
2008	10.11	10.11	9.82	9.93	10.05	10.36	10.46
2009	10.46	10.50	10.28	10.29	10.31	10.38	10.37
2010	10.40	10.42	10.33	10.35	10.38	10.37	10.39
2011	10.52	10.39	10.09	10.16	10.29	10.24	10.29
2012	10.40	10.28	10.10	10.23	10.17	10.25	10.39
∆%12M	-1.1	-1.1	0.1	0.7	-1.2	0.1	1.0
2013	10.37	10.30	10.17	10.32	10.29	10.34	10.43
∆%12M	-0.3	0.2	0.7	0.9	1.2	0.9	0.4
2014	10.41	10.47
∆%12M	0.4	1.7

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. The economic welfare or wellbeing of United States workers deteriorated in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html), stagnating/declining real wages and 28.2 million unemployed or underemployed (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html) because of mediocre economic growth (http://cmpassocregulationblog.blogspot.com/2014/03/financial-uncertainty-mediocre-cyclical.html).

Chart IB-2, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2014

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-Feb 2014.

Chart IB-3, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2014

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 provided 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 0.4 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 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 0.3 percent in the 12 months ending in Jun and 2.1 percent 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 2.7 percent in the 12 months ending in Oct 2012 and increased 0.1 percent in the 12 months ending in Nov 2012 and 2.4 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 0.9 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 2.0 percent in the 12 months ending in Jul 2013. Real weekly earnings increased 0.7 percent in the 12 months ending in Aug 2013, 0.8 percent in the 12 months ending in Sep 2013 and 1.5 percent in the 12 months ending in Oct 2013. Average weekly earnings increased 1.2 percent in the 12 months ending in Nov 2013 and fell 0.2 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. 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/2014/03/interest-rate-risks-world-inflation.html). On an annual basis, average weekly earnings in constant 1982-1984 dollars increased from $349.34 in 2007 to $354.16 in 2013, by 1.4 percent or at the average rate of 0.2 percent per year (data in http://www.bls.gov/data/). Annual average weekly earnings in constant dollars of $353.11 in 2010 were virtually unchanged at $353.00 in 2012. 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 28.2 million unemployed or underemployed (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html) in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html).

Table IB-5, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, NSA 2007-2014

Year	Jan	Feb	Sep	Oct	Nov	Dec
2006			346.02	354.71	348.95	353.20
2007	348.55	348.04	355.39	347.58	346.68	354.76
2008	344.58	345.89	341.51	345.63	358.50	356.85
2009	353.62	358.93	346.72	348.35	355.07	351.48
2010	350.39	350.20	352.96	356.00	354.81	355.29
2011	359.82	353.35	349.62	358.27	351.14	353.95
2012	358.75	351.67	357.13	348.76	351.46	362.53
∆%12M	-0.3	-0.5	2.1	-2.7	0.1	2.4
2013	352.58	352.21	360.10	354.10	355.85	361.82
∆%12M	-1.7	0.2	0.8	1.5	1.2	-0.2
2014	353.93	360.14
∆%12M	0.4	2.3

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 and 2013.

Chart IB-4, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2014

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. There is the same pattern of contraction during the global recession in 2008 and then again trend of deterioration in the recovery without hiring and inflation waves. (http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html).

Chart IB-5, US, Average Weekly Earnings of All Employees NSA in Constant Dollars of 1982-1984 12-Month Percent Change, NSA 2007-2014

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

ESV United States International Trade. Table IIA-1 provides the trade balance of the US and monthly growth of exports and imports seasonally adjusted with the latest release and revisions (http://www.census.gov/foreign-trade/). Because of heavy dependence on imported oil, fluctuations in the US trade account originate largely in fluctuations of commodity futures prices caused by carry trades from zero interest rates into commodity futures exposures in a process similar to world inflation waves (http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html). The Census Bureau revised data for 2013. The US trade balance improved from deficits of $39,770 million in Oct 2013 and $43,434 million in Sep 2013 to deficit of $35,171 million in Nov 2013 but higher deficit of $38,975 million in Dec 2013. The trade deficit increased to $39,280 million in Jan 2014 and deficit of $42,300 million in Feb 2014. Exports fell 0.1 percent in Aug 2013 and imports increased 0.1 percent. Exports decreased 0.2 percent in Sep 2012 while imports increased 1.7 percent. Exports increased 2.0 percent in Oct 2013 while imports increased 0.1 percent. Exports increased 0.8 percent in Nov 2013 while imports fell 1.3 percent. Exports fell 1.7 percent in Dec 2013 while imports increased 0.2 percent. Exports increased 0.6 percent in Jan 2014 and imports increased 0.6 percent. In Feb 2014, exports fell 1.1 percent while imports increased 0.4 percent. The trade balance deteriorated from cumulative deficit of $499,379 million in Jan-Dec 2010 to deficit of $556,838 million in Jan-Dec 2011 and improved to marginally lower deficit of $534,656 million in Jan-Dec 2012. The trade deficit improved to $474,864 million in Jan-Dec 2013.

Table IIA-1, US, Trade Balance of Goods and Services Seasonally Adjusted Millions of Dollars and ∆%

	Trade Balance	Exports	Month ∆%	Imports	Month ∆%
Feb 2014	-42,300	190,434	-1.1	232,734	0.4
Jan	-39,280	192,459	0.6	231,740	0.6
Dec 2013	-38,975	191,290	-1.7	230,265	0.2
Nov	-35,171	194,644	0.8	229,815	-1.3
Oct	-39,770	193,112	2.0	232,882	0.1
Sep	-43,434	189,251	-0.2	232,685	1.7
Aug	-39,207	189,635	-0.1	228,842	0.1
Jul	-38,900	189,753	-0.7	228,652	1.4
Jun	-34,414	191,055	2.2	225,469	-2.2
May	-43,661	186,909	-0.2	230,571	1.7
Apr	-39,374	187,308	1.4	226,682	2.4
Mar	-36,562	184,758	-1.1	221,321	-3.8
Feb	-43,257	186,880	0.0	230,137	0.5
Jan	-42,139	186,789	-1.0	228,928	0.9
Jan-Dec 2013	-474,864	2,271,385		2,746,249
Dec 2012	-38,307	188,686	1.9	226,994	-2.0
Nov	-46,422	185,220	1.4	231,641	2.8
Oct	-42,650	182,655	-2.2	225,304	-1.4
Sep	-41,570	186,829	2.6	228,400	1.0
Aug	-44,007	182,071	-0.7	226,078	-0.3
Jul	-43,451	183,375	-1.0	226,826	-0.4
Jun	-42,430	185,218	0.5	227,648	-1.2
May	-46,247	184,217	0.0	230,464	-0.2
Apr	-46,625	184,267	-1.2	230,892	-1.5
Mar	-47,790	186,505	2.4	234,295	3.7
Feb	-43,763	182,064	1.4	225,827	-2.2
Jan	-51,393	179,477	0.2	230,871	0.2
Jan-Dec 2012	-534,656	2,210,585		2,745,240
Jan-Dec 2011	-556,838	2,112,825		2,669,663
Jan-Dec 2010	-499,379	1,844,468		2,343,847

Note: Trade Balance of Goods = Exports of Goods less Imports of Goods. Trade balance may not add exactly because of errors of rounding and seasonality. Source: US Census Bureau, Foreign Trade Division

http://www.census.gov/foreign-trade/

Table IIA-1B provides US exports, imports and the trade balance of goods. The US has not shown a trade surplus in trade of goods since 1976. The deficit of trade in goods deteriorated sharply during the boom years from 2000 to 2007. The deficit improved during the contraction in 2009 but deteriorated in the expansion after 2009. The deficit could deteriorate sharply with growth at full employment.

Table IIA-1B, US, International Trade Balance of Goods, Exports and Imports of Goods, Millions of Dollars, Census Basis

	Balance	∆%	Exports	∆%	Imports	∆%
1960	4,608	(X)	19,626	(X)	15,018	(X)
1961	5,476	18.8	20,190	2.9	14,714	-2.0
1962	4,583	-16.3	20,973	3.9	16,390	11.4
1963	5,289	15.4	22,427	6.9	17,138	4.6
1964	7,006	32.5	25,690	14.5	18,684	9.0
1965	5,333	-23.9	26,699	3.9	21,366	14.4
1966	3,837	-28.1	29,379	10.0	25,542	19.5
1967	4,122	7.4	30,934	5.3	26,812	5.0
1968	837	-79.7	34,063	10.1	33,226	23.9
1969	1,289	54.0	37,332	9.6	36,043	8.5
1970	3,224	150.1	43,176	15.7	39,952	10.8
1971	-1,476	-145.8	44,087	2.1	45,563	14.0
1972	-5,729	288.1	49,854	13.1	55,583	22.0
1973	2,389	-141.7	71,865	44.2	69,476	25.0
1974	-3,884	-262.6	99,437	38.4	103,321	48.7
1975	9,551	-345.9	108,856	9.5	99,305	-3.9
1976	-7,820	-181.9	116,794	7.3	124,614	25.5
1977	-28,352	262.6	123,182	5.5	151,534	21.6
1978	-30,205	6.5	145,847	18.4	176,052	16.2
1979	-23,922	-20.8	186,363	27.8	210,285	19.4
1980	-19,696	-17.7	225,566	21.0	245,262	16.6
1981	-22,267	13.1	238,715	5.8	260,982	6.4
1982	-27,510	23.5	216,442	-9.3	243,952	-6.5
1983	-52,409	90.5	205,639	-5.0	258,048	5.8
1984	-106,702	103.6	223,976	8.9	330,678	28.1
1985	-117,711	10.3	218,815	-2.3	336,526	1.8
1986	-138,279	17.5	227,159	3.8	365,438	8.6
1987	-152,119	10.0	254,122	11.9	406,241	11.2
1988	-118,526	-22.1	322,426	26.9	440,952	8.5
1989	-109,399	-7.7	363,812	12.8	473,211	7.3
1990	-101,719	-7.0	393,592	8.2	495,311	4.7
1991	-66,723	-34.4	421,730	7.1	488,453	-1.4
1992	-84,501	26.6	448,164	6.3	532,665	9.1
1993	-115,568	36.8	465,091	3.8	580,659	9.0
1994	-150,630	30.3	512,626	10.2	663,256	14.2
1995	-158,801	5.4	584,742	14.1	743,543	12.1
1996	-170,214	7.2	625,075	6.9	795,289	7.0
1997	-180,522	6.1	689,182	10.3	869,704	9.4
1998	-229,758	27.3	682,138	-1.0	911,896	4.9
1999	-328,821	43.1	695,797	2.0	1,024,618	12.4
2000	-436,104	32.6	781,918	12.4	1,218,022	18.9
2001	-411,899	-5.6	729,100	-6.8	1,140,999	-6.3
2002	-468,263	13.7	693,103	-4.9	1,161,366	1.8
2003	-532,350	13.7	724,771	4.6	1,257,121	8.2
2004	-654,830	23.0	814,875	12.4	1,469,704	16.9
2005	-772,373	18.0	901,082	10.6	1,673,455	13.9
2006	-827,971	7.2	1,025,967	13.9	1,853,938	10.8
2007	-808,763	-2.3	1,148,199	11.9	1,956,962	5.6
2008	-816,199	0.9	1,287,442	12.1	2,103,641	7.5
2009	-503,582	-38.3	1,056,043	-18.0	1,559,625	-25.9
2010	-635,362	26.2	1,278,495	21.1	1,913,857	22.7
2011	-727,765	14.5	1,480,290	15.8	2,208,055	15.4
2012	-729,611	0.3	1,545,709	4.4	2,275,320	3.0
2013	-688,450	-5.6	1,578,972	2.2	2,267,421	-0.3

Census Bureau, Foreign Trade Division

http://www.census.gov/foreign-trade/

Table IIA-2B provides the US international trade balance, exports and imports of goods and services on an annual basis from 1992 to 2013. The trade balance deteriorated sharply over the long term. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US decreased from $99.2 billion in IVQ2012, or 2.5 percent of GDP to $83.7 billion in IVQ2013, or 1.9 percent of GDP (http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html). The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71). The last row of Table IIA-2B shows marginal improvement of the trade deficit from $556,838 million in 2011 to lower $534,656 million in 2012 with exports growing 4.6 percent and imports 2.8 percent. The trade balance improved further to deficit of $474,864 million in 2013 with growth of exports of 2.8 percent while imports stagnated. Growth and commodity shocks under alternating inflation waves (http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html) have deteriorated the trade deficit from the low of $383,657 million in 2009.

Table IIA-2B, US, International Trade Balance of Goods and Services, Exports and Imports of Goods and Services, SA, Millions of Dollars, Balance of Payments Basis

	Balance	Exports	Imports
1960	3,508	25,940	22,432
1961	4,195	26,403	22,208
1962	3,370	27,722	24,352
1963	4,210	29,620	25,410
1964	6,022	33,341	27,319
1965	4,664	35,285	30,621
1966	2,939	38,926	35,987
1967	2,604	41,333	38,729
1968	250	45,543	45,293
1969	91	49,220	49,129
1970	2,254	56,640	54,386
1971	-1,302	59,677	60,979
1972	-5,443	67,222	72,665
1973	1,900	91,242	89,342
1974	-4,293	120,897	125,190
1975	12,404	132,585	120,181
1976	-6,082	142,716	148,798
1977	-27,246	152,301	179,547
1978	-29,763	178,428	208,191
1979	-24,565	224,131	248,696
1980	-19,407	271,834	291,241
1981	-16,172	294,398	310,570
1982	-24,156	275,236	299,391
1983	-57,767	266,106	323,874
1984	-109,072	291,094	400,166
1985	-121,880	289,070	410,950
1986	-138,538	310,033	448,572
1987	-151,684	348,869	500,552
1988	-114,566	431,149	545,715
1989	-93,141	487,003	580,144
1990	-80,864	535,233	616,097
1991	-31,135	578,344	609,479
1992	-39,212	616,882	656,094
1993	-70,311	642,863	713,174
1994	-98,493	703,254	801,747
1995	-96,384	794,387	890,771
1996	-104,065	851,602	955,667
1997	-108,273	934,453	1,042,726
1998	-166,140	933,174	1,099,314
1999	-263,755	967,008	1,230,764
2000	-377,337	1,072,782	1,450,119
2001	-362,339	1,007,725	1,370,065
2002	-418,165	980,879	1,399,044
2003	-490,545	1,023,937	1,514,482
2004	-604,897	1,163,724	1,768,622
2005	-707,914	1,288,257	1,996,171
2006	-752,399	1,460,792	2,213,191
2007	-699,065	1,652,859	2,351,925
2008	-702,302	1,840,332	2,542,634
2009	-383,657	1,578,187	1,961,844
2010	-499,379	1,844,468	2,343,847
2011	-556,838	2,112,825	2,669,663
2012	-534,656	2,210,585	2,745,240
2013	-474,864	2,271,385	2,746,249

Census Bureau, Foreign Trade Division

http://www.census.gov/foreign-trade/

Chart IIA-1 of the US Census Bureau of the Department of Commerce shows that the trade deficit (gap between exports and imports) fell during the economic contraction after 2007 but has grown again during the expansion. The low average rate of growth of GDP of 2.4 percent during the expansion beginning since IIIQ2009 does not deteriorate further the trade balance. Higher rates of growth may cause sharper deterioration.

Chart IIA-1, US, International Trade Balance, Exports and Imports of Goods and Services USD Billions

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr042.html

Chart IIA-2 of the US Census Bureau provides the US trade account in goods and services SA from Jan 1992 to Feb 2014. There is long-term trend of deterioration of the US trade deficit shown vividly by Chart IIA-2. The global recession from IVQ2007 to IIQ2009 reversed the trend of deterioration. Deterioration resumed together with incomplete recovery and was influenced significantly by the carry trade from zero interest rates to commodity futures exposures (these arguments are elaborated in 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 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). Earlier research focused on the long-term external imbalance of the US in the form of trade and current account deficits (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). US external imbalances have not been fully resolved and tend to widen together with improving world economic activity and commodity price shocks.

Chart IIA-2, US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-Feb 2014

Source: US Census Bureau

http://www.census.gov/foreign-trade/

Chart IIA-3 of the US Census Bureau provides US exports SA from Jan 1992 to Feb 2014. There was sharp acceleration from 2003 to 2007 during worldwide economic boom and increasing inflation. Exports fell sharply during the financial crisis and global recession from IVQ2007 to IIQ2009. Growth picked up again together with world trade and inflation but stalled in the final segment with less rapid global growth and inflation.

Chart IIA-3, US, Exports SA, Monthly, Millions of Dollars Jan 1992-Feb 2014

Source: US Census Bureau

http://www.census.gov/foreign-trade/

Chart IIA-4 of the US Census Bureau provides US imports SA from Jan 1992 to Feb 2014. Growth was stronger between 2003 and 2007 with worldwide economic boom and inflation. There was sharp drop during the financial crisis and global recession. There is stalling import levels in the final segment resulting from weaker world economic growth and diminishing inflation because of risk aversion and portfolio reallocations from commodity exposures to equities.

Chart IIA-4, US, Imports SA, Monthly, Millions of Dollars Jan 1992-Feb 2014

Source: US Census Bureau

http://www.census.gov/foreign-trade/

The balance of international trade in goods of the US seasonally adjusted is in Table IIA-3. The US has a dynamic surplus in services that reduces the large deficit in goods for a still very sizeable deficit in international trade of goods and services. The deficit in the balance in international trade of goods decreased from deficit of $62,130 million in Feb 2013 to $61,733 million in Feb 2014. The relative stability of the goods balance in Feb 2014 relative to Feb 2013 occurred mostly in the petroleum balance, exports less imports of petroleum goods, in the magnitude of decreasing the deficit by $1708 million, while there was deterioration in the nonpetroleum balance, exports less imports of nonpetroleum goods, in the magnitude of increasing the deficit by $1388 million. US terms of trade, export prices relative to import prices, and the US trade account fluctuate in accordance with the carry trade from zero interest rates to commodity futures exposures, especially oil futures. Exports increased 0.4 percent with nonpetroleum exports decreasing 0.5 percent. Total imports increased 0.1 percent with petroleum imports decreasing 3.6 percent and nonpetroleum imports increasing 0.5 percent. Details do not add because of seasonal adjustment and rounding.

Table IIA-3, US, International Trade in Goods Balance, Exports and Imports $ Millions and ∆% SA

	Feb 2014	Feb 2013	∆%
Total Balance	-61,733	-62,130
Petroleum	-19,945	-21,653
Non Petroleum	-39,967	-38,579
Total Exports	131,715	131,198	0.4
Petroleum	11,087	10,544	5.1
Non Petroleum	119,582	120,173	-0.5
Total Imports	193,448	193,328	0.1
Petroleum	31,032	32,197	-3.6
Non Petroleum	159,550	158,752	0.5

Details may not add because of rounding and seasonal adjustment

Source: US Census Bureau

http://www.census.gov/foreign-trade/

US exports and imports of goods not seasonally adjusted in Jan-Feb 2014 and Jan-Feb 2013 are in Table IIA-4. The rate of growth of exports was 1.8 percent and minus 0.1 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that increased 7.0 percent and of mineral fuels that increased 17.0 percent both because prices of raw materials and commodities increase and fall recurrently as a result of shocks of risk aversion and portfolio reallocations. The US exports an insignificant amount of crude oil. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports decreased 0.6 percent while manufactured imports rose 0.1 percent. Significant part of the US trade imbalance originates in imports of mineral fuels decreasing 4.5 percent and petroleum decreasing 6.5 percent with wide oscillations in oil prices. The limited hedge in exports of agricultural commodities and mineral fuels compared with substantial imports of mineral fuels and crude oil results in waves of deterioration of the terms of trade of the US, or export prices relative to import prices, originating in commodity price increases caused by carry trades from zero interest rates. These waves are similar to those in worldwide inflation (http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html).

Table IIA-4, US, Exports and Imports of Goods, Not Seasonally Adjusted Millions of Dollars and %, Census Basis

	Jan-Feb 2014 $ Millions	Jan-Feb 2014 $ Millions	∆%
Exports	251,464	246,996	1.8
Manufactured	182,745	183,780	-0.6
Agricultural Commodities	27,291	25,514	7.0
Mineral Fuels	25,109	21,460	17.0
Petroleum	20,532	17,796	15.4
Imports	354,999	355,364	-0.1
Manufactured	284,306	284,120	0.1
Agricultural Commodities	17,133	17,249	-0.7
Mineral Fuels	59,256	62,074	-4.5
Petroleum	55,124	58,983	-6.5

Source: US Census Bureau

http://www.census.gov/foreign-trade/

CMP Associates Regulation Blog

Followers

Blog Archive

About Me

Monday, April 7, 2014

Interest Rate Risks, Twenty Eight Million Unemployed or Underemployed, Stagnating Real Wages, United States International Trade, World Cyclical Slow Growth and Global Recession Risk: Part I

No comments:

Post a Comment