CMP Associates Regulation Blog: Twenty Nine Million Unemployed or Underemployed, Stagnating Real Wages, United States International Trade, Collapse of United States Dynamism of Income Growth and Employment Creation, Theory and Reality of Secular Stagnation, World Economic Slowdown and Global Recession Risk: Part 1

Twenty Nine Million Unemployed or Underemployed, Stagnating Real Wages, United States International Trade, Collapse of United States Dynamism of Income Growth and Employment Creation, Theory and Reality of Secular Stagnation, World Economic Slowdown and Global Recession Risk

Carlos M. Pelaez

Executive Summary

I Twenty Nine 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

IC Collapse of United States Dynamism of Income Growth and Employment Creation

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 Theory and Reality of Secular Stagnation

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

Economic risks include the following:

China’s Economic Growth. China is lowering its growth target to 7.5 percent per year. China’s GDP growth decelerated significantly from annual equivalent 10.8 percent in IIQ2011 to 7.4 percent in IVQ2011 and 5.7 percent in IQ2012, rebounding to 9.1 percent in IIQ2012, 8.2 percent in IIIQ2012 and 7.8 percent in IVQ2012. Annual equivalent growth in IQ2013 fell to 6.1 percent and to 7.8 percent in IIQ2013, rebounding to 9.1 percent in IIIQ2013 (http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/07/tapering-quantitative-easing-policy-and_7005.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/01/recovery-without-hiring-world-inflation.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html).
United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 28.1 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically low hiring and declining/stagnating real wages.
Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
World Inflation Waves. Inflation continues in repetitive waves globally (http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html).

A list of financial uncertainties includes:

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

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

The Federal Open Market Committee (FOMC) lowered the target of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85). Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment. The exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV). The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever-increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity 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 $2490 billion, or $2.5 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 (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 (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 Jan 9, 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
11/27/13	0.09	2.74	5.34 (11/26/13)
12/6/13	0.09	2.88	5.47
12/12/13	0.09	2.89	5.42
12/19/13	0.09	2.94	5.36
12/26/13	0.08	3.00	5.37
1/2/2014	0.08	3.00	5.34
1/9/2014	0.07	2.97	5.28

Source: Board of Governors of the Federal Reserve System

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

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

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

Analysis of these methods is in Pelaez and Pelaez (International Financial Architecture (2005), 101-162) and Pelaez and Pelaez, Globalization and the 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 resulting from the debate within and outside the Fed on tapering quantitative easing. Table VIII-2 provides the yield curve of Treasury securities on Jan 10, 2014, Dec 31, 2013, May 1, 2013, Jan 10, 2013 and Jan 10, 2006. There is ongoing steepening of the yield curve for longer maturities, which are also the ones with highest duration. The 10-year yield increased from 1.45 percent on Jul 26, 2012 to 3.04 percent on Dec 31, 2013 and 2.88 percent on Jan 10, 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 2.88 percent as occurred on Jan 10, 2013 would jump instantaneously from yield of 2.99 percent on Jan 10, 2014 to 4.43 percent as occurred on Jan 10, 2006 when the economy was closer to full employment. The price of the hypothetical bond issued with coupon of 2.88 percent would drop from 100 to 87.5867 after an instantaneous increase of the yield to 4.43 percent. The price loss would be 12.4 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

	1/10/14	12/31/13	5/01/13	1/10/13	1/10/06
1 M	0.01	0.01	0.03	0.05	4.15
3 M	0.05	0.07	0.06	0.06	4.29
6 M	0.06	0.10	0.08	0.10	4.42
1 Y	0.12	0.13	0.11	0.14	4.42
2 Y	0.39	0.38	0.20	0.26	4.41
3 Y	0.77	0.78	0.30	0.37	4.36
5 Y	1.64	1.75	0.65	0.80	4.36
7 Y	2.29	2.45	1.07	1.30	4.38
10 Y	2.88	3.04	1.66	1.91	4.43
20 Y	3.54	3.72	2.44	2.68	4.68
30 Y	3.980	3.96	2.83	3.08	NA

Source: United States Treasury

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

Interest rate risk is increasing in the US. Chart VI-13 of the Board of Governors provides the conventional mortgage rate for a fixed-rate 30-year mortgage. The rate stood at 5.87 percent on Jan 8, 2004, increasing to 6.79 percent on Jul 6, 2006. The rate bottomed at 3.35 percent on May 2, 2013. Fear of duration risk in longer maturities such as mortgage-backed securities caused continuing increases in the conventional mortgage rate that rose to 4.51 percent on Jul 11, 2013, 4.58 percent on Aug 22, 2013 and 4.51 percent on Jan 9, 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 Jan 9, 2014

Source: Board of Governors of the Federal Reserve System

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

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

(1 + i_r) = (1 + i_n)/(1 + π^e) (1)

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

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

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

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

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

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

Current focus is on tapering quantitative easing by the Federal Open Market Committee (FOMC). There is sharp distinction between the two measures of unconventional monetary policy: (1) fixing of the overnight rate of fed funds at 0 to ¼ percent; and (2) outright purchase of Treasury and agency securities and mortgage-backed securities for the balance sheet of the Federal Reserve. Market are overreacting to the so-called “paring” of outright purchases of $85 billion of securities per month for the balance sheet of the Fed (http://www.federalreserve.gov/newsevents/press/monetary/20131218a.htm):

“In light of the cumulative progress toward maximum employment and the improvement in the outlook for labor market conditions, the Committee decided to modestly reduce the pace of its asset purchases. Beginning in January, the Committee will add to its holdings of agency mortgage-backed securities at a pace of $35 billion per month rather than $40 billion per month, and will add to its holdings of longer-term Treasury securities at a pace of $40 billion per month rather than $45 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.”

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 Dec 18, 2013 (http://www.federalreserve.gov/newsevents/press/monetary/20131218a.htm):

“To support continued progress toward maximum employment and price stability, the Committee today reaffirmed its view that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the asset purchase program ends and the economic recovery strengthens. The Committee also reaffirmed its expectation that the current exceptionally low target range for the federal funds rate of 0 to 1/4 percent will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee's 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored (emphasis added).

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.”

“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).”

W = Y/r (10

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

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

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

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

The key policy is maintaining fed funds rate between 0 and ¼ percent. An increase in fed funds rates could cause flight out of risk financial markets worldwide. There is no exit from this policy without major financial market repercussions. Indefinite financial repression induces carry trades with high leverage, risks and illiquidity. A competing event is the high level of valuations of risk financial assets (http://cmpassocregulationblog.blogspot.com/2013/01/peaking-valuation-of-risk-financial.html). Matt Jarzemsky, writing on “Dow industrials set record,” on Mar 5, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324156204578275560657416332.html), analyzes that the DJIA broke the closing high of 14,164.53 set on Oct 9, 2007, and subsequently also broke the intraday high of 14,198.10 reached on Oct 11, 2007. The DJIA closed at 16,437.05 on Fri Jan 10, 2014, which is higher by 16.0 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 15.8 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 69.7 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Jan 10, 2014; S&P 500 has gained 80.2 percent and DAX 67.1 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 1/10/14” 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 15.5 percent below the trough. Japan’s Nikkei Average is 80.3 percent above the trough. DJ Asia Pacific TSM is 25.5 percent above the trough. Dow Global is 45.4 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 27.3 percent above the trough. NYSE Financial Index is 50.2 percent above the trough. DJ UBS Commodities is 0.3 percent below the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 67.1 percent above the trough. Japan’s Nikkei Average is 80.3 percent above the trough on Aug 31, 2010 and 39.7 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 15,912.06 on Fri Jan 10, 2014 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 55.2 percent higher than 10,254.43 on Mar 11, 2011, on the date of the Tōhoku or Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar depreciated by 14.7 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 1/10/14” in Table VI-4 shows decrease of 3.4 percent in the week for China’s Shanghai Composite. DJ Asia Pacific decreased 0.2 percent. NYSE Financial increased 1.1 percent in the week. DJ UBS Commodities decreased 1.0 percent. Dow Global increased 0.6 percent in the week of Jan 10, 2014. The DJIA decreased 0.2 percent and S&P 500 increased 0.6 percent. DAX of Germany increased 0.4 percent. STOXX 50 increased 0.5 percent. The USD depreciated 0.6 percent. There are still high uncertainties on European sovereign risks and banking soundness, US and world growth slowdown and China’s growth tradeoffs. Sovereign problems in the “periphery” of Europe and fears of slower growth in Asia and the US cause risk aversion with trading caution instead of more aggressive risk exposures. There is a fundamental change in Table VI-4 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 1/10/14” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Jan 10, 2014. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 1/10/14” but also relative to the peak in column “∆% Peak to 1/10/14.” There are now several equity indexes above the peak in Table VI-4: DJIA 46.7 percent, S&P 500 51.3 percent, DAX 49.6 percent, Dow Global 18.6 percent, DJ Asia Pacific 9.9 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 19.6 percent, Nikkei Average 39.7 percent and STOXX 50 7.8 percent. There is only one equity index below the peak: Shanghai Composite by 36.4 percent. DJ UBS Commodities Index is now 14.7 percent below the peak. The US dollar strengthened 9.6 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010. Alexandra Scaggs, writing on “Tepid profits, roaring stocks,” on May 16, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323398204578487460105747412.html), analyzes stabilization of earnings growth: 70 percent of 458 reporting companies in the S&P 500 stock index reported earnings above forecasts but sales fell 0.2 percent relative to forecasts of increase of 0.5 percent. Paul Vigna, writing on “Earnings are a margin story but for how long,” on May 17, 2013, published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2013/05/17/earnings-are-a-margin-story-but-for-how-long/), analyzes that corporate profits increase with stagnating sales while companies manage costs tightly. More than 90 percent of S&P components reported moderate increase of earnings of 3.7 percent in IQ2013 relative to IQ2012 with decline of sales of 0.2 percent. Earnings and sales have been in declining trend. In IVQ2009, growth of earnings reached 104 percent and sales jumped 13 percent. Net margins reached 8.92 percent in IQ2013, which is almost the same at 8.95 percent in IIIQ2006. Operating margins are 9.58 percent. There is concern by market participants that reversion of margins to the mean could exert pressure on earnings unless there is more accelerated growth of sales. Vigna (op. cit.) finds sales growth limited by weak economic growth. Kate Linebaugh, writing on “Falling revenue dings stocks,” on Oct 20, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444592704578066933466076070.html?mod=WSJPRO_hpp_LEFTTopStories), identifies a key financial vulnerability: falling revenues across markets for United States reporting companies. Global economic slowdown is reducing corporate sales and squeezing corporate strategies. Linebaugh quotes data from Thomson Reuters that 100 companies of the S&P 500 index have reported declining revenue only 1 percent higher in Jun-Sep 2012 relative to Jun-Sep 2011 but about 60 percent of the companies are reporting lower sales than expected by analysts with expectation that revenue for the S&P 500 will be lower in Jun-Sep 2012 for the entities represented in the index. Results of US companies are likely repeated worldwide. Future company cash flows derive from investment projects. In IQ1980, gross private domestic investment in the US was $951.6 billion of 2009 dollars, growing to $1,143.0 billion in IVQ1986 or 20.1 percent. Real gross private domestic investment in the US increased 0.8 percent from $2,605.2 billion of 2009 dollars in IVQ2007 to $2,627.2 billion in IIIQ2013. As shown in Table IAI-2, real private fixed investment fell 3.6 percent from $2,586.3 billion of 2009 dollars in IVQ2007 to $2,494.0 billion in IIIQ2013. Growth of real private investment is mediocre for all but four quarters from IIQ2011 to IQ2012 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-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. 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. 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. 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. Undistributed profits of US corporations swelled 382.4 percent from $107.7 billion IQ2007 to $519.5 billion in IIIQ2013 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 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_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. 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:

clip_image003

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

clip_image003

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 1/10/ /14	∆% Week 1/10/14	∆% Trough to 1/10/ 14
DJIA	4/26/ 10	7/2/10	-13.6	46.7	-0.2	69.7
S&P 500	4/23/ 10	7/20/ 10	-16.0	51.3	0.6	80.2
NYSE Finance	4/15/ 10	7/2/10	-20.3	19.6	1.1	50.2
Dow Global	4/15/ 10	7/2/10	-18.4	18.6	0.6	45.4
Asia Pacific	4/15/ 10	7/2/10	-12.5	9.9	-0.2	25.5
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	39.7	-2.3	80.3
China Shang.	4/15/ 10	7/02 /10	-24.7	-36.4	-3.4	-15.5
STOXX 50	4/15/10	7/2/10	-15.3	7.8	0.5	27.3
DAX	4/26/ 10	5/25/ 10	-10.5	49.6	0.4	67.1
Dollar Euro	11/25 2009	6/7 2010	21.2	9.6	-0.6	-14.7
DJ UBS Comm.	1/6/ 10	7/2/10	-14.5	-14.7	-1.0	-0.3
10-Year T Note	4/5/ 10	4/6/10	3.986	2.784	2.858

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 Nine 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 11.6 percent and the number of people in job stress could be around 29.3 million, which is 18.0 percent of the effective labor force. The first column provides for 2006 the yearly average population (POP), labor force (LF), participation rate or labor force as percent of population (PART %), employment (EMP), employment population ratio (EMP/POP %), unemployment (UEM), the unemployment rate as percent of labor force (UEM/LF Rate %) and the number of people not in the labor force (NLF). All data are unadjusted or not-seasonally-adjusted (NSA). The numbers in column 2006 are averages in millions while the monthly numbers for Dec 2012, Nov 2013 and Dec 2013 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 2013. 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 Dec 2012, Nov 2013 and Dec 2013 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 63.4 percent by Dec 2012 and was 62.9 percent in Nov 2013 and 62.6 percent in Dec 2013, 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 8.937 million unemployed in Dec 2013 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 18.921 million (Total UEM) and not 9.984 million (UEM) of whom many have been unemployed long term
the rate of unemployment is 11.6 percent (Total UEM%) and not 6.5 percent, not seasonally adjusted, or 6.7 percent seasonally adjusted
the number of people in job stress is close to 29.3 million by adding the 8.937 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 29.338 million in Dec 2013, 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 18.0 percent of the labor force in Dec 2013. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 58.5 percent in Dec 2012, 58.7 percent in Nov 2013 and 58.5 percent in Dec 2013. The number employed in Dec 2013 was 144.423 million (NSA) or 2.892 million fewer people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population increased from 231.958 million in Jul 2007 to 246.745 million in Dec 2013 or by 14.787 million. The number employed fell 2.0 percent from Jul 2007 to Dec 2013 while population increased 6.4 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 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 2013 than in 2006 and the number employed is not increasing while population increased 14.787 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/2013/12/theory-and-reality-of-secular.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/2013/12/theory-and-reality-of-secular.html).

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

	2006	Dec 2012	Nov 2013	Dec 2013
POP	229	244.350	246,567	246,745
LF	151	154,904	155,046	154,408
PART%	66.2	63.4	62.9	62.6
EMP	144	143,060	144,775	144,423
EMP/POP%	62.9	58.5	58.7	58.5
UEM	7	11,844	10,271	9,984
UEM/LF Rate%	4.6	7.6	6.6	6.5
NLF	77	89,445	91,521	92,338
LF PART 66.2%		161,760	163,227	163,345
∆NLF UEM		6,856	8,181	8,937
Total UEM		18,700	18,452	18,921
Total UEM%		11.6	11.3	11.6
Part Time Economic Reasons		8,166	7,563	7,990
Marginally Attached to LF		2,614	2,096	2,427
In Job Stress		29,480	28,111	29,338
People in Job Stress as % Labor Force		18.2	17.2	18.0

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

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

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/home.htm

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. 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/2013/12/theory-and-reality-of-secular.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, 1979-2013

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/home.htm

Chart I-12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2013

Source: Bureau of Labor Statistics

Month	1981	1982	1983	2008	2009	2010	Private
Jan	95	-327	225	14	-794	-13	-17
Feb	67	-6	-78	-85	-695	-40	-26
Mar	104	-129	173	-79	-830	154	111
Apr	74	-281	276	-215	-704	229	170
May	10	-45	277	-186	-352	521	102
Jun	196	-243	378	-169	-472	-130	94
Jul	112	-343	418	-216	-351	-86	103
Aug	-36	-158	-308	-270	-210	-37	129
Sep	-87	-181	1114	-459	-233	-43	113
Oct	-100	-277	271	-472	-170	228	188
Nov	-209	-124	352	-775	-21	144	154
Dec	-278	-14	356	-705	-220	95	114
			1984			2011	Private
Jan			447			69	80
Feb			479			196	243
Mar			275			205	223
Apr			363			304	303
May			308			115	183
Jun			379			209	177
Jul			312			78	206
Aug			241			132	129
Sep			311			225	256
Oct			286			166	174
Nov			349			174	197
Dec			127			230	249
			1985			2012	Private
Jan			266			311	323
Feb			124			271	265
Mar			346			205	208
Apr			195			112	120
May			274			125	152
Jun			145			87	78
Jul			189			153	177
Aug			193			165	131
Sep			204			138	118
Oct			187			160	217
Nov			209			247	256
Dec			168			219	224
			1985			2013	Private
Jan			123			148	164
Feb			107			332	319
Mar			93			142	154
Apr			188			199	188
May			125			176	187
Jun			-93			172	194
Jul			318			89	100
Aug			113			238	207
Sep			346			175	168
Oct			187			200	217
Nov			186			241	226
Dec			204			74	87

Earnings per Hour	Dec 2012	Oct 2013	Nov 2013	Dec 2013
Total Private	$23.75	$24.11	$24.15	$24.17
Goods Producing	$24.89	$25.34	$25.39	$25.45
Service Providing	$23.47	$23.82	$23.85	$23.87
Average Weekly Earnings
Total Private	$819.38	$829.38	$833.18	$831.45
Goods Producing	$1,005.56	$1,023.74	$1,030.83	$1,030.73
Service Providing	$781.55	$793.21	$794.21	$792.48
Average Weekly Hours
Total Private	34.5	34.4	34.5	34.4
Goods Producing	40.4	40.4	40.6	40.5
Service Providing	33.3	33.3	33.3	33.2

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	34.2	34.3	34.7	34.4	34.7	34.9	34.7	35.0	34.5	34.5	35.0
2008	34.2	34.2	34.8	34.4	34.4	34.9	34.5	34.6	34.4	34.4	34.6	34.1
2009	33.8	34.3	34.0	33.6	33.7	33.8	33.8	34.3	33.7	33.8	34.3	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	34.3	34.6	34.4	34.4	34.4	34.4	34.9	34.3	34.4
2012	34.5	34.2	34.3	34.7	34.3	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	34.4	34.6	34.9	34.4	34.4	34.8

	AHE ALL	12 Month Nominal ∆%	∆% 12 Month CPI	12 Month Real ∆%
2007
Jan*	$20.70*	4.2*	2.1	2.1*
Feb*	$20.79*	4.1*	2.4	1.7*
Mar	$20.82	3.7	2.8	0.9
Apr	$21.05	3.3	2.6	0.7
May	$20.83	3.7	2.7	1.0
Jun	$20.82	3.8	2.7	1.1
Jul	$20.99	3.4	2.4	1.0
Aug	$20.85	3.5	2.0	1.5
Sep	$21.19	4.1	2.8	1.3
Oct	$21.07	2.7	3.5	-0.8
Nov	$21.13	3.3	4.3	-0.9
Dec	$21.37	3.7	4.1	-0.4
2010
Jan	$22.55	1.9	2.6	-0.7
Feb	$22.61	1.4	2.1	-0.7
Mar	$22.52	1.2	2.3	-1.1
Apr	$22.57	1.8	2.2	-0.4
May	$22.64	2.5	2.0	0.5
Jun	$22.38	1.8	1.1	0.7
Jul	$22.44	1.8	1.2	0.6
Aug	$22.58	1.7	1.1	0.6
Sep	$22.63	1.8	1.1	0.7
Oct	$22.73	1.9	1.2	0.7
Nov	$22.72	1.0	1.1	-0.1
Dec	$22.79	1.7	1.5	0.2
2011
Jan	$23.20	2.9	1.6	1.3
Feb	$23.03	1.9	2.1	-0.2
Mar	$22.93	1.8	2.7	-0.9
Apr	$22.99	1.9	3.2	-1.3
May	$23.09	2.0	3.6	-1.5
Jun	$22.84	2.1	3.6	-1.4
Jul	$22.97	2.4	3.6	-1.2
Aug	$22.88	1.3	3.8	-2.4
Sep	$23.08	2.0	3.9	-1.8
Oct	$23.33	2.6	3.5	-0.9
Nov	$23.18	2.0	3.4	-1.4
Dec	$23.25	2.0	3.0	-1.0
2012
Jan	$23.59	1.7	2.9	-1.2
Feb	$23.44	1.8	2.9	-1.1
Mar	$23.42	2.1	2.7	-0.6
Apr	$23.65	2.9	2.3	0.6
May	$23.36	1.2	1.7	-0.5
Jun	$23.30	2.0	1.7	0.3
Jul	$23.52	2.4	1.4	1.0
Aug	$23.30	1.8	1.7	0.1
Sep	$23.70	2.7	2.0	0.7
Oct	$23.55	0.9	2.2	-1.3
Nov	$23.62	1.9	1.8	0.1
Dec	$23.89	2.8	1.7	1.1
2013
Jan	$23.92	1.4	1.6	-0.2
Feb	$23.94	2.1	2.0	0.1
Mar	$23.86	1.9	1.5	0.4
Apr	$23.94	1.2	1.1	0.1
May	$23.81	1.9	1.4	0.5
Jun	$23.95	2.8	1.8	1.0
Jul	$23.83	1.3	2.0	-0.7
Aug	$23.81	2.2	1.5	0.7
Sep	$24.18	2.0	1.2	0.8
Oct	$24.06	2.2	1.0	1.2
Nov	$24.10	2.0	1.2	0.8
Dec	$24.31	1.8

Year	Jun	Jul	Aug	Sep	Oct	Nov
2006	9.89	9.97	9.88	10.03	10.17	10.15
2007	9.99	10.08	10.03	10.16	10.08	10.05
2008	9.84	9.77	9.83	9.94	10.06	10.37
2009	10.20	10.23	10.29	10.30	10.32	10.40
2010	10.27	10.29	10.34	10.36	10.39	10.38
2011	10.12	10.17	10.10	10.17	10.30	10.25
2012	10.15	10.27	10.11	10.24	10.18	10.26
∆%12M	0.3	1.0	0.1	0.7	-1.2	0.1
2013	10.26	10.20	10.18	10.33	10.30	10.34
∆%12M	1.1	-0.7	0.7	0.9	1.2	0.8

Year	Jul	Aug	Sep	Oct	Nov
2006	347.97	341.76	346.19	354.88	349.12
2007	351.68	347.98	355.72	347.92	346.85
2008	337.06	340.18	341.83	345.95	358.83
2009	345.92	352.80	347.04	348.83	356.59
2010	352.02	358.90	353.27	356.47	355.12
2011	349.75	347.42	349.93	359.60	351.44
2012	357.26	348.93	357.44	349.20	351.91
∆%12M	2.1	0.4	2.1	-2.9	0.1
2013	350.93	352.25	360.40	354.39	355.71
∆%12M	-1.8	1.0	0.8	1.5	1.1

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

	1929	1939	1940	2006	2012
GDP	100.00	100.00	100.00	100.00	100.00
PCE	74.0	71.9	69.2	67.1	68.6
GDI	16.4	10.9	14.2	19.3	15.2
NRI	11.1	7.3	8.3	12.8	12.1
RSI	3.9	3.4	3.5	6.0	2.7
Net Trade	0.4	0.9	1.4	-5.5	-3.4
GOVT	9.2	16.3	15.2	19.1	19.5

	ICP	FTE	EMP	CLF	CLFP	EPOP	UNE
2006	288.8	119.7	144.4	151.4	66.2	63.1	7.0
2009	235.8	112.6	139.9	154.1	65.4	59.3	14.3
2012	243.3	114.8	142.5	155.0	63.7	58.6	12.5
12/07	233.2	121.0	146.3	153.7	65.9	62.8	7.4
9/09	236.3	112.0	139.1	153.6	65.0	58.9	14.5
11/13	246.6	116.9	144.8	155.0	62.9	58.7	10.3

	ICP	EMP	CLF	CLFP	EPOP	UNE	UNER
2006	36.9	20.0	22.4	60.6	54.2	2.4	10.5
2009	37.6	17.6	21.4	56.9	46.9	3.8	17.6
2012	38.8	17.8	21.3	54.9	46.0	3.5	16.2
12/07	37.5	19.4	21.7	57.8	51.6	2.3	10.7
9/09	37.6	17.0	20.7	55.2	45.1	3.8	18.2
11/13	38.8	18.1	20.8	53.7	46.7	2.7	13.1

2013	Dec 2013	Nov 2013	Oct 2013
Labor Force Millions	154.937	155.284	154.625
Unemployed Millions	10.351	10.841	11.140
Unemployment Rate (unemployed as % labor force)	6.7	7.0	7.2
Unemployed ≥27 weeks Millions	3.878	4.044	4.047
Unemployed ≥27 weeks %	37.5	37.3	36.3
Part Time for Economic Reasons Millions	7.771	7.723	8.016
Marginally Attached to Labor Force Millions	2.427	2.096	2.283
Job Stress Millions	20.549	20.660	21.439
In Job Stress as % Labor Force	13.3	13.3	13.9

	Dec 2013	Nov 2013	Oct 2013	Sep 2013
Labor Force	154.937	155.284	154.625	155.473
Unemployed	10.351	10.841	11.140	11.203
UNE Rate %	6.7	7.0	7.2	7.2
Part Time Economic Reasons	7.771	7.723	8.016	7.914
Marginally Attached to Labor Force	2.427	2.096	2.283	2.302
In Job Stress	20.549	20.722	21,605	21.419
In Job Stress % Labor Force	13.3	13.3	13.9	13.8
Employed	144.586	144.443	143.485	144.270
Employment % Population	58.6	58.6	58.2	58.6

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	3	-2.4	-0.8
IIIQ1957 to IIQ1958	3	-3.0	-1.0
IVQ1973 to IQ1975	5	-3.1	-0.6
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.5	-0.64
IVQ2007 to IIQ2009	6	-4.3	-0.72

	Number of Quarters	Cumulative Growth ∆%	Average Annual Equivalent Growth Rate
IIIQ 1954 to IQ1957	11	12.8	4.5
First Four Quarters IIIQ1954 to IIQ1955	4	7.8
IIQ1958 to IIQ1959	5	10.0	7.9
First Four Quarters IIIQ1958 to IIQ1959	4	9.2
IIQ1975 to IVQ1976	8	8.3	4.1
First Four Quarters IIIQ1975 to IIQ1976	4	6.1
IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987	13 15 16 17	19.9 21.6 22.3 23.1	5.7 5.4 5.2 5.0
First Four Quarters IQ1983 to IVQ1983	4	7.8
Average First Four Quarters in Four Expansions*		7.7
IIIQ2009 to IIIQ2013	17	10.3	2.3
First Four Quarters IIIQ2009 to IIQ2010		2.7

Long-term Average ∆% per Year	GDP	Population
1929-2012	3.3	1.1
1947-2012	3.2	1.2
1947-1999	3.6	1.3
2000-2012	1.7	0.9
2000-2006	2.6	0.9
2006-2012	0.9	0.8
Long-term Average ∆% per Year	Real Disposable Income	Real Disposable Income per Capita	Population
1929-2012	3.2	2.0	1.1
1947-1999	3.7	2.3	1.3
2000-2012	2.2	1.3	0.9
2000-2006	2.9	2.0	0.9
Whole Cycles Average ∆% per Year
1980-1989	3.5	2.6	0.9
2006-2012	1.4	0.6	0.8
Comparison of Cycles	# Quarters	∆%	∆% Annual Equivalent
GDP
I83 to IV83 IQ83 to IQ87	4 17
I83 to IV83 I83 to IQ87	4 17	7.8 23.1	7.8 5.0
RDPI
I83 to IV83 I83 to I87	4 17	5.3 19.5	5.3 4.3
RDPI Per Capita
I83 to IV83 I83 to I87	4 17	4.4 15.1	4.4 3.4
Whole Cycle IQ1980 to IQ1987
GDP	30	22.9	2.8
RDPI	30	26.4	3.2
RDPI per Capita	30	18.1	2.2
Population	30	7.0	0.9
GDP
III09 to II10 III09 to III13	4 17	2.7 10.3	2.7 2.3
RDPI
III09 to II10 III09 to III13	4 17	0.3 6.3	0.3 1.4
RDPI per Capita
III09 to II10 II09 to IIIQ13	4 17	-0.5 2.9	-0.5 0.7
Population
II09 to II010 II09 to III13	4 17	0.9 3.2	0.8 0.8
IVQ2007 to IIIQ2013	23
GDP	24	5.6	0.9
RDPI	24	7.9	1.3
RDPI per Capita	24	3.1	0.5
Population	24	4.6	0.8

	Dec 2013	Nov 2013
New Nonfarm Payroll Jobs	74,000	241,000
New Private Payroll Jobs	87,000	226,000
Average Hourly Earnings	Dec 13 $24.17 SA ∆% Dec 13/ Dec 12 NSA: 1.8 ∆% Dec 13/Nov 13 SA: 0.1	Nov 13 $24.15 SA ∆% Nov 13/Nov 12 NSA: 2.0 ∆% Nov 13/Oct 13 SA: 0.2
Average Hourly Earnings in Constant Dollars		∆% Nov 2013/Nov 2012: 0.8
Average Weekly Hours	34.4 SA 34.8 NSA	34.5 SA 34.4 NSA
Unemployment Rate Household Survey % of Labor Force SA	6.7	7.0
Number in Job Stress Unemployed and Underemployed Blog Calculation	29.3 million NSA	28.1 million NSA
In Job Stress as % Labor Force	18.0 NSA	17.2 NSA

	Dec 2012	Dec 2013	Change
A Total Nonfarm	135,560	137,753	2,193
B Total Private	113,321	115,542	2,221
B1 Goods Producing	18,416	18,659	243
B1a Manufacturing	11,939	12,028	89
B2 Private service providing	94,905	96,883	1,978
B2a Wholesale Trade	5,724	5,821	97
B2b Retail Trade	15,538	15,945	407
B2c Transportation & Warehousing	4,609	4,673	64
B2d Financial Activities	7,846	7,925	79
B2e Professional and Business Services	18,237	18,858	621
B2e1 Temporary help services	2,651	2,889	238
B2f Health Care & Social Assistance	17,210	17,491	281
B2g Leisure & Hospitality	13,591	13,963	372
C Government	22,239	22,211	-28
C1 Federal	2,798	2,727	-71
C2 State	5,150	5,160	10
C3 Local	14,291	14,324	33

	Nov 2013 SA	Dec 2013 SA	∆	Nov 2013 NSA	Dec 2013 NSA	∆
A Total Nonfarm	136,803	136,877	74	137,999	137,753	-246
B Total Private	114,941	115,028	87	115,662	115,542	-120
B1 Goods Producing	18,755	18,752	-3	18,871	18,659	-212
B1a Constr.	5,849	5,833	-16	5,961	5,745	-216
B Mfg	12,019	12,028	9	12,024	12,028	4
B2 Private Service Providing	96,186	96,276	90	96,791	96,883	92
B2a Wholesale Trade	5,795	5,810	15	5,804	5,821	17
B2b Retail Trade	15,330	15,385	55	15,769	15,945	176
B2c Couriers & Mess.	554	548	-6	579	652	73
B2d Health-care & Social Assistance	17,435	17,434	-1	17,482	17,491	9
B2De Profess. & Business Services	18,770	18,789	19	18,902	18,858	-44
B2De1 Temp Help Services	2,776	2,816	40	2,872	2,889	17
B2f Leisure & Hospit.	14,282	14,291	9	14,016	13,963	-53

	SAAR IIQ2013	% Total	SAAR IQ2013	% Total
National Income WCCA	14,495.5	100.0	14,643.3	100.0
Domestic Industries	14,248.7	98.3	14,380.3	98.2
Private Industries	12,568.6	86.7	12,705.2	86.8
Agriculture	220.3	1.5	225.2	1.5
Mining	254.3	1.8	256.4	1.8
Utilities	216.5	1.5	221.2	1.5
Construction	629.0	4.3	639.1	4.4
Manufacturing	1558.9	10.8	1577.7	10.8
Durable Goods	888.1	6.1	910.1	6.2
Nondurable Goods	670.1	4.6	667.6	4.6
Wholesale Trade	874.4	6.0	884.0	6.0
Retail Trade	995.8	6.9	1000.2	6.8
Transportation & WH	436.3	3.0	443.6	3.0
Information	507.2	3.5	497.5	3.4
Finance, Insurance, RE	2448.1	16.9	2521.0	17.2
Professional, BS	2004.7	13.8	2004.0	13.7
Education, Health Care	1438.9	9.9	1439.2	9.8
Arts, Entertainment	577.1	4.0	585.2	4.0
Other Services	409.7	2.8	410.8	2.8
Government	1680.1	11.6	1675.1	11.4
Rest of the World	246.8	1.7	262.9	1.8

Year	Total Nonfarm	Year	Total Nonfarm
1980	90,528	2000	131,881
1981	91,289	2001	131,919
1982	89,677	2002	130,450
1983	90,280	2003	130,100
1984	94,530	2004	131,509
1985	97,511	2005	133,747
1986	99,474	2006	136,125
1987	102,088	2007	137,645
1988	105,345	2008	136,852
1989	108,014	2009	130,876
1990	109,487	2010	129,917
1991	108,377	2011	131,497
1992	108,745	2012	133,739

	Total Nonfarm Jobs	Total Private Jobs
06/1981 #	92,288	75,969
11/1982 #	89,482	73,260
Change #	-2,806	-2,709
Change ∆%	-3.0	-3.6
12/1982 #	89,383	73,185
05/1984 #	94,471	78,049
Change #	5,088	4,864
Change ∆%	5.7	6.6
11/2007 #	139,090	116,291
05/2009 #	131,626	108,601
Change %	-7,464	-7,690
Change ∆%	-5.4	-6.6
12/2009 #	130,178	107,338
05/2011 #	131,753	108,494
Change #	1,575	1,156
Change ∆%	1.2	1.1
05/1983 #	90,005	73,667
05/1984 #	94,471	78,049
Change #	4,466	4,382
Change ∆%	4.9	5.9
05/2010 #	130,801	107,405
05/2011 #	131,753	109,203
Change #	952	1,798
Change ∆%	0.7	1.7
Change # by ∆% as in 05/1984 to 05/1985	6,409*	6,337**
Difference in Jobs that Would Have Been Created	5,457 = 6,409-952	4,539 = 6,337-1,798

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Sunday, January 12, 2014

Twenty Nine Million Unemployed or Underemployed, Stagnating Real Wages, United States International Trade, Collapse of United States Dynamism of Income Growth and Employment Creation, Theory and Reality of Secular Stagnation, World Economic Slowdown and Global Recession Risk: Part 1

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