Theory and Reality of Cyclical Slow Growth Not Secular Stagnation, Recovery without Hiring, United States Budget Quagmire, United States Industrial Production, World Cyclical Slow Growth and Global Recession Risk: Part I

 

Theory and Reality of Cyclical Slow Growth Not Secular Stagnation, Recovery without Hiring, United States Budget Quagmire, United States Industrial Production, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

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

Executive Summary

I Recovery without Hiring

IA1 Hiring Collapse

IA2 Labor Underutilization

ICA3 Ten Million Fewer Full-time Jobs

IA4 Theory and Reality of Cyclical Slow Growth Not Secular Stagnation: Youth and Middle-Age Unemployment

IIA United States Budget Quagmire

IIB United States Industrial Production

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 Recovery without Hiring

ESIII Ten Million Fewer Full-time Jobs

ESIV Theory and Reality of Secular Stagnation: Youth and Middle-Age Unemployment

ESV United States Budget Quagmire

ESVI United States Industrial Production

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:

1. 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.
2. 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.
3. Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
4. World Inflation Waves. Inflation continues in repetitive waves globally (http://cmpassocregulationblog.blogspot.com/2014/01/world-inflation-waves-interest-rate.htmland earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). There is growing concern on capital outflows and currency depreciation of emerging markets.

A list of financial uncertainties includes:

1. Euro Area Survival Risk. The resilience of the euro to fiscal and financial doubts on larger member countries is still an unknown risk.
2. Foreign Exchange Wars. Exchange rate struggles continue as zero interest rates in advanced economies induce devaluation of their currencies with alternating episodes of revaluation.
3. Valuation of Risk Financial Assets. Valuations of risk financial assets have reached extremely high levels in markets with lower volumes.
4. 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.
5. Credibility and Commitment of Central Bank Policy. There is a credibility issue of the commitment of monetary policy (Sargent and Silber 2012Mar20).
6. 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 $2602 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 Feb 13, 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
1/16/2014	0.07	2.86	5.18
1/23/2014	0.07	2.79	5.11
1/31/2014	0.07	2.72	5.08
2/7/2014	0.07	2.73	5.13
2/14/2014	0.06	2.73	5.12

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 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 Feb 14, 2014, Dec 31, 2013, May 1, 2013, Feb 14, 2013 and Feb 14, 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 2.75 percent on Feb 14, 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 2.75 percent as occurred on Feb 14, 2013 would jump instantaneously from yield of 2.75 percent on Feb 14, 2014 to 4.62 percent as occurred on Feb 14, 2006 when the economy was closer to full employment. The price of the hypothetical bond issued with coupon of 2.75 percent would drop from 100 to 85.1591 after an instantaneous increase of the yield to 4.62 percent. The price loss would be 14.8 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

	2/14/14	12/31/13	5/01/13	2/14/13	2/14/06
1 M	0.01	0.01	0.03	0.10	4.42
3 M	0.02	0.07	0.06	0.11	4.55
6 M	0.07	0.10	0.08	0.13	4.72
1 Y	0.11	0.13	0.11	0.16	4.71
2 Y	0.32	0.38	0.20	0.27	4.69
3 Y	0.71	0.78	0.30	0.42	4.68
5 Y	1.53	1.75	0.65	0.86	4.61
7 Y	2.17	2.45	1.07	1.37	4.61
10 Y	2.75	3.04	1.66	2.00	4.62
20 Y	3.41	3.72	2.44	2.79	4.80
30 Y	3.69	3.96	2.83	3.17	4.60

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 4.28 percent on Feb 13, 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 Feb 13, 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

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 Feb 7, 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 13.3305/USD on Feb 7, 2014.

Chart VI-4A, Mexican Peso (MXN) per US Dollar (USD), Nov 8, 1993 to Feb 7, 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 Feb 7, 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 if INR 62.0900/USD on Feb 7, 2014.

Chart VI-4B, Indian Rupee (INR) per US Dollar (USD), Jan 2, 1973 to Feb 7, 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 102.3200/USD on Feb 7, 2013 for appreciation of 17.5 percent relative to JPY 124.0900/USD on Jun 22, 2007 before the global recession and expansion characterized by recurring bouts of risk aversion. Takashi Nakamichi and Eleanor Warnock, writing on “Japan lashes out over dollar, euro,” on Dec 29, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887323530404578207440474874604.html?mod=WSJ_markets_liveupdate&mg=reno64-wsj), analyze the “war of words” launched by Japan’s new Prime Minister Shinzo Abe and his finance minister Taro Aso, arguing of deliberate devaluations of the USD and EUR relative to the JPY, which are hurting Japan’s economic activity. 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-Feb 7, 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 2.3820/USD on Feb 7, 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 2.3820/USD on Feb 7, 2014 for depreciation of 54.9 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 Feb 7, 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 Feb 7, 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 $85 billion of securities per month for the balance sheet of the Fed

(http://www.federalreserve.gov/newsevents/press/monetary/20140129a.htm):

“Taking into account the extent of federal fiscal retrenchment since the inception of its current asset progress toward maximum employment and the improvement in the outlook for labor market conditions, the Committee decided to make a further measured reduction in the pace of its asset purchases. Beginning in February, the Committee will add to its holdings of agency mortgage-backed securities at a pace of $30 billion per month rather than $35 billion per month, and will add to its holdings of longer-term Treasury securities at a pace of $35 billion per month rather than $40 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 Jan 29, 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20140129a.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. In determining how long to maintain a highly accommodative stance of monetary policy, the Committee will also consider other information, including additional measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial developments. 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 well past the time that the unemployment rate declines below 6-1/2 percent, especially if projected inflation continues to run below the Committee's 2 percent longer-run goal (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.”

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).”

In his classic restatement of the Keynesian demand function in terms of “liquidity preference as behavior toward risk,” James Tobin (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/1981/tobin-bio.html) identifies the risks of low interest rates in terms of portfolio allocation (Tobin 1958, 86):

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

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

W = Y/r (10

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.

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/2014/01/capital-flows-exchange-rates-and.htm and earlier 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 current reality is cyclical slow growth.

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). 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 16,154.39 Fri Feb 14, 2014, which is higher by 14.0 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 13.8 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 66.8 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Feb 14, 2014; S&P 500 has gained 79.8 percent and DAX 70.4 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 2/14/14” 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 11.2 percent below the trough. Japan’s Nikkei Average is 62.2 percent above the trough. DJ Asia Pacific TSM is 21.9 percent above the trough. Dow Global is 44.3 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 27.5 percent above the trough. NYSE Financial Index is 47.0 percent above the trough. DJ UBS Commodities is 5.4 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 70.4 percent above the trough. Japan’s Nikkei Average is 62.2 percent above the trough on Aug 31, 2010 and 25.6 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 14,313.03 on Fri Feb 14, 2014 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 39.6 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 14.9 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 2/14/14” in Table VI-4 shows increase of 3.5 percent in the week for China’s Shanghai Composite. DJ Asia Pacific increased 1.5 percent. NYSE Financial increased 1.7 percent in the week. DJ UBS Commodities increased 1.7 percent. Dow Global increased 2.2 percent in the week of Feb 14, 2014. The DJIA increased 2.3 percent and S&P 500 increased 2.3 percent. DAX of Germany increased 3.9 percent. STOXX 50 increased 2.4 percent. The USD depreciated 0.4 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 2/14/14” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Feb 14, 2014. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 2/14/14” but also relative to the peak in column “∆% Peak to 2/14/14.” There are now several equity indexes above the peak in Table VI-4: DJIA 44.2 percent, S&P 500 51.0 percent, DAX 52.6 percent, Dow Global 17.7 percent, DJ Asia Pacific 6.7 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 17.1 percent, Nikkei Average 25.6 percent and STOXX 8.0 percent. There is only one equity index below the peak: Shanghai Composite by 33.1 percent. DJ UBS Commodities Index is now 9.9 percent below the peak. The US dollar strengthened 9.5 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010. 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/2013/12/tapering-quantitative-easing-mediocre.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:

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 2/14/ /14	∆% Week 2/14/14	∆% Trough to 2/14/ 14
DJIA	4/26/ 10	7/2/10	-13.6	44.2	2.3	66.8
S&P 500	4/23/ 10	7/20/ 10	-16.0	51.0	2.3	79.8
NYSE Finance	4/15/ 10	7/2/10	-20.3	17.1	1.7	47.0
Dow Global	4/15/ 10	7/2/10	-18.4	17.7	2.2	44.3
Asia Pacific	4/15/ 10	7/2/10	-12.5	6.7	1.5	21.9
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	25.6	-1.0	62.2
China Shang.	4/15/ 10	7/02 /10	-24.7	-33.1	3.5	-11.2
STOXX 50	4/15/10	7/2/10	-15.3	8.0	2.4	27.5
DAX	4/26/ 10	5/25/ 10	-10.5	52.6	3.9	70.4
Dollar Euro	11/25 2009	6/7 2010	21.2	9.5	-0.4	-14.9
DJ UBS Comm.	1/6/ 10	7/2/10	-14.5	-9.9	1.7	5.4
10-Year T Note	4/5/ 10	4/6/10	3.986	2.784	2.743

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

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

ESII Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels have increased by only 4 percent since Jan 2009. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job currently is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn, there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/01/capital-flows-exchange-rates-and.htm). Lazear and Spletzer (2012Mar, 1) argue that reductions of churn reduce the operational effectiveness of labor markets. Churn is part of the allocation of resources or in this case labor to occupations of higher marginal returns. The decline in churn can harm static and dynamic economic efficiency. Losses from decline of churn during recessions can affect an economy over the long-term by preventing optimal growth trajectories because resources are not used in the occupations where they provide highest marginal returns. Lazear and Spletzer (2012Mar 7-8) conclude that: “under a number of assumptions, we estimate that the loss in output during the recession [of 2007 to 2009] and its aftermath resulting from reduced churn equaled $208 billion. On an annual basis, this amounts to about .4% of GDP for a period of 3½ years.”

There are two additional facts discussed below: (1) there are about ten million fewer full-time jobs currently than before the recession of 2008 and 2009; and (2) the extremely high and rigid rate of youth unemployment is denying an early start to young people ages 16 to 24 years while unemployment of ages 45 years or over has swelled. There are four subsections. IA1 Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IA2 Labor Underutilization provides the measures of labor underutilization of the Bureau of Labor Statistics (BLS). Statistics on the decline of full-time employment are in IA3 Ten Million Fewer Full-time Jobs. IA4 Theory and Reality of Cyclical Slow Growth Not Secular Stagnation: Youth and Middle-Age Unemployment provides the data on high unemployment of ages 16 to 24 years and of ages 45 years or over.

IA1 Hiring Collapse. An important characteristic of the current fractured labor market of the US is the closing of the avenue for exiting unemployment and underemployment normally available through dynamic hiring. Another avenue that is closed is the opportunity for advancement in moving to new jobs that pay better salaries and benefits again because of the collapse of hiring in the United States. Those who are unemployed or underemployed cannot find a new job even accepting lower wages and no benefits. The employed cannot escape declining inflation-adjusted earnings because there is no hiring. The objective of this section is to analyze hiring and labor underutilization in the United States.

Blanchard and Katz (1997, 53 consider an appropriate measure of job stress:

“The right measure of the state of the labor market is the exit rate from unemployment, defined as the number of hires divided by the number unemployed, rather than the unemployment rate itself. What matters to the unemployed is not how many of them there are, but how many of them there are in relation to the number of hires by firms.”

The natural rate of unemployment and the similar NAIRU are quite difficult to estimate in practice (Ibid; see Ball and Mankiw 2002).

The Bureau of Labor Statistics (BLS) created the Job Openings and Labor Turnover Survey (JOLTS) with the purpose that (http://www.bls.gov/jlt/jltover.htm#purpose):

“These data serve as demand-side indicators of labor shortages at the national level. Prior to JOLTS, there was no economic indicator of the unmet demand for labor with which to assess the presence or extent of labor shortages in the United States. The availability of unfilled jobs—the jobs opening rate—is an important measure of tightness of job markets, parallel to existing measures of unemployment.”

The BLS collects data from about 16,000 US business establishments in nonagricultural industries through the 50 states and DC. The data are released monthly and constitute an important complement to other data provided by the BLS (see also Lazear and Spletzer 2012Mar, 6-7).

Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 52.0 million in 2012 or by 11.8 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 48.5 million in 2012 or by 11.0 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.2 in 2005 to 38.9 in 2012 and in the private sector (RHP) from 53.1 in 2005 to 43.4 in 2012. Hiring has not recovered as in previous cyclical expansions because of the low rate of economic growth in the current cyclical expansion. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.4 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the first estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). As a result, there are 30.3 million unemployed or underemployed in the United States for an effective underutilization rate of 18.5 percent (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.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). US GDP grew 6.5 percent from $14,996.1 billion in IVQ2007 in constant dollars to $15,965.6 billion in IVQ2013 or 6.5 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US GDP grew 6.5 percent from $14,996.1 billion in IVQ2007 in constant dollars to $15,965.6 billion in IVQ2013 or 6.5 percent. 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 $2,074.7 billion than actual $15,965.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 30.3 million unemployed or underemployed equivalent to actual unemployment of 18.5 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.html). 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. 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-1, US, Annual Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US in Thousands and Percentage of Total Employment

	HNF	Rate RNF	HP	Rate HP
2001	62,948	47.8	58,825	53.1
2002	58,583	44.9	54,759	50.3
2003	56,451	43.4	53,056	48.9
2004	60,367	45.9	56,617	51.6
2005	63,150	47.2	59,372	53.1
2006	63,773	46.9	59,494	52.1
2007	62,421	45.4	58,035	50.3
2008	55,128	40.3	51,591	45.1
2009	46,357	35.4	43,031	39.8
2010	48,607	37.4	44,788	41.7
2011	49,675	37.8	46,552	42.5
2012	51,991	38.9	48,493	43.4

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-1 shows the annual level of total nonfarm hiring (HNF) that collapsed during the global recession after 2007 in contrast with milder decline in the shallow recession of 2001. Nonfarm hiring has not recovered, remaining at a depressed level.

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2012

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-2 shows the ratio or rate of nonfarm hiring to employment (RNF) that also fell much more in the recession of 2007 to 2009 than in the shallow recession of 2001. Recovery is weak in the current environment of cyclical slow growth.

Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2012

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table I-2. There were much milder declines in 2002 of 6.9 percent and 3.6 percent in 2003 followed by strong rebounds of 6.9 percent in 2004 and 4.6 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.1 in 2007, 11.7 in 2008 and 15.9 percent in 2009. On a yearly basis, nonfarm hiring grew 4.9 percent in 2010 relative to 2009, 2.2 percent in 2011 and 4.7 percent in 2012.

Table I-2, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2002-2012

Year	Annual ∆%
2002	-6.9
2003	-3.6
2004	6.9
2005	4.6
2006	1.0
2007	-2.1
2008	-11.7
2009	-15.9
2010	4.9
2011	2.2
2012	4.7

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Total private hiring (HP) yearly data are provided in Chart I-4. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2012.

Chart I-4, US, Total Nonfarm Hiring Level, Annual, 12-Month ∆%, 2001-2012

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-5 plots the rate of total private hiring relative to employment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.

Chart I-5, US, Total Private Hiring, Annual, 2001-2013

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-5A plots the rate of total private hiring relative to employment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.

Chart I-5A, US, Rate Total Private Hiring Level, Annual, 2001-2012

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Dec in the years from 2001 to 2013 in Table I-3. Hiring numbers are in thousands. There is moderate recovery in HNF from 2744 thousand (or 2.7 million) in Dec 2009 to 2948 thousand in Dec 2010, 2990 thousand in Dec 2011, 3013 thousand in Dec 2012 and 4169 thousand in Dec 2013 for cumulative gain of 15.5 percent. HP rose from 2600 thousand in Dec 2009 to 2782 thousand in Dec 2010, 2809 thousand in Dec 2011, 2842 thousand in Dec 2012 and 3005 thousand in Dec 2013 for cumulative gain of 15.6 percent. HNF has fallen from 3835 thousand in Dec 2006 to 3169 thousand in Dec 2013 or by 17.4 percent. HP has fallen from 3635 thousand in Dec 2006 to 3005 thousand in Dec 2013 or by 17.3 percent. The civilian noninstitutional population of the US, or individuals in condition to work, rose from 228.815 million in 2006 to 245.679 million in 2013 or by 16.864 million and the civilian labor force from 151.428 million in 2006 to 155.389 million in 2013 or by 3.961 million (http://www.bls.gov/data/). The number of nonfarm hires in the US fell from 63.773 million in 2006 to 51.991 million in 2012 or by 11.782 million and the number of private hires fell from 59.494 million in 2006 to 48.493 million in 2012 or by 11 million (http://www.bls.gov/jlt/). Private hiring of 63,773 million in 2006 was equivalent to 27.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 48.493 million in 2012 or 19.9 percent of the civilian noninstitutional population of 243.284 million in 2012. The percentage of hiring in civilian noninstitutional population of 27.9 percent in 2006 would correspond to 67.876 million of hiring in 2012, which would be 19.383 million higher than actual 48.493 million in 2012. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html) explains the fact that there are many million fewer hires in the US than before the global recession. The labor market continues to be fractured, failing to provide an opportunity to exit from unemployment/underemployment or to find an opportunity for advancement away from declining inflation-adjusted earnings.

Table I-3, US, Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US in

Thousands and in Percentage of Total Employment Not Seasonally Adjusted

	HNF	Rate RNF	HP	Rate HP
2001 Dec	3541	2.7	3317	3.0
2002 Dec	3698	2.8	3493	3.2
2003 Dec	3697	2.8	3490	3.2
2004 Dec	3859	2.9	3643	3.3
2005 Dec	3777	2.8	3568	3.1
2006 Dec	3835	2.8	3635	3.2
2007 Dec	3610	2.6	3393	2.9
2008 Dec	2997	2.2	2836	2.5
2009 Dec	2744	2.1	2600	2.4
2010 Dec	2948	2.2	2782	2.6
2011 Dec	2990	2.2	2809	2.5
2012 Dec	3013	2.2	2842	2.5
2013 Dec	3169	2.3	3005	2.6

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

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2013. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4774 in May 2010 until it surpassed it with 4883 in Jun 2011 but declined to 3013 in Dec 2012. Nonfarm hiring fell to 2990 in Dec 2011 from 3827 in Nov and to revised 3683 in Feb 2012, increasing to 4210 in Mar 2012, 3013 in Dec 2012 and 4128 in Jan 2013 and declining to 3661 in Feb 2013. Nonfarm hires not seasonally adjusted increased to 4137 in Nov 2013 and 3169 in Dec 2013. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Oct 2011 was 4159 thousand, increasing to revised 4489 thousand in Feb 2012, or 7.9 percent, moving to 4195 in Dec 2012 for cumulative increase of 0.5 percent from 4174 in Dec 2011 and 4437 in Dec 2013 for increase of 5.8 percent relative to 4195 in Dec 2012. The number of hires not seasonally adjusted was 4883 in Jun 2011, falling to 2990 in Dec 2011 but increasing to 4013 in Jan 2012 and declining to 3013 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 38.8 percent from 4883 in Jun 2011 to 2990 in Dec 2011 and fell 41.3 percent from 5130 in Jun 2012 to 3013 in Dec 2012 in a yearly-repeated seasonal pattern. The number of nonfarm hires not seasonally adjusted fell from 5087 in Jun 2013 to 3169 in Dec 2013, or decline of 37.7 percent, showing strong seasonality.

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2013 Month SA

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Similar behavior occurs in the rate of nonfarm hiring in Chart I-7. Recovery in early 2010 was followed by decline and stabilization at a lower level but with stability in monthly SA estimates of 3.2 in Aug 2011 to 3.2 in Jan 2012, increasing to 3.4 in May 2012 and falling to 3.3 in Jun 2012. The rate fell to 3.1 in Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.1 in Dec 2012 and 3.2 in Dec 2013. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.2 in Dec 2011, climbing to 3.8 in Jun 2012 but falling to 2.2 in Dec 2012. The rate of nonfarm hires not seasonally adjusted fell from 3.7 in Jun 2013 to 2.3 in Dec 2013. Rates of nonfarm hiring NSA were in the range of 2.8 (Dec) to 4.5 (Jun) in 2006.

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2013

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

There is only milder improvement in total private hiring shown in Chart I-8. Hiring private (HP) rose in 2010 with stability and renewed increase in 2011 followed by almost stationary series in 2012. The number of private hiring seasonally adjusted fell from 4026 thousand in Sep 2011 to 3876 in Dec 2011 or by 3.7 percent, decreasing to 3915 in Jan 2012 or decline by 2.8 percent relative to the level in Sep 2011. The rate fell to 3934 in Sep 2012 or lower by 2.3 percent relative to Sep 2011, decreasing to 3915 in Dec 2012 for change of 0.0 percent relative to 3915 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4504 in Jun 2011 to 2809 in Dec 2011 or by 37.6 percent, reaching 3749 in Jan 2012 or decline of 16.8 percent relative to Jun 2011 and moving to 2842 in Dec 2012 or 39.8 percent lower relative to 4724 in Jun 2012. Hires fell from 4692 in Jun 2013 to 3005 in Dec 2013. Companies do not hire in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5661 in Jun 2006 to 3635 in Dec 2006 or by 35.8 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Jul 2006, private hiring NSA was 5555, declining to 4245 in Jul 2011 or by 23.6 percent and to 4277 in Jul 2012 or lower by 23.0 percent relative to Jul 2006. Private hiring NSA fell from 3635 in Dec 2006 to 2842 in Dec 2012 or 21.8 percent and declined to 3005 in Dec 2013 or lower by 17.3 percent relative to Dec 2006. Private hiring fell from 5555 in Jul 2006 to 4633 in Jun 2013 or 16.6 percent. The conclusion is that private hiring in the US is around 20 percent below the hiring before the global recession while the noninstitutional population of the United States has grown from 228.815 million in 2006 to 245.679 million in 2013, by 16.864 million or 7.4 percent. The main problem in recovery of the US labor market has been the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-8, US, Total Private Hiring Month SA 2001-2013

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data did not rise significantly above the peak in 2010. The rate seasonally adjusted fell from 3.7 in Sep 2011 to 3.5 in Dec 2011 and reached 3.5 in Dec 2012 and 3.6 in Dec 2013. The rate not seasonally adjusted (NSA) fell from 3.7 in Sep 2011 to 2.5 in Dec 2011, increasing to 3.8 in Oct 2012 but falling to 2.5 in Dec 2012 and 3.4 in Mar 2013. The NSA rate of private hiring fell from 4.8 in Jul 2006 to 3.4 in Aug 2009 but recovery was insufficient to only 3.8 in Aug 2012, 2.5 in Dec 2012 and 2.6 in Dec 2013. The rate of private hires fell from 4.8 in Jul 2006 to 4.0 in Jul 2013. US economic growth has been at only 2.4 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the first estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). As a result, there are 30.3 million unemployed or underemployed in the United States for an effective underutilization rate of 18.5 percent (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.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). US GDP grew 6.5 percent from $14,996.1 billion in IVQ2007 in constant dollars to $15,965.6 billion in IVQ2013 or 6.5 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US GDP grew 6.5 percent from $14,996.1 billion in IVQ2007 in constant dollars to $15,965.6 billion in IVQ2013 or 6.5 percent. 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 $2,074.7 billion than actual $15,965.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 30.3 million unemployed or underemployed equivalent to actual unemployment of 18.5 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.html). 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. 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.

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2013

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

ESIII Ten Million Fewer Full-time Jobs. There is strong seasonality in US labor markets around the end of the year. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.068 million in Sep 2011 to 7.780 million in Mar 2012, seasonally adjusted, or decline of 1.288 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.572 million in Sep 2012 for increase of 527,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.231 million in Oct 2012 or by 341,000 again in one month, further declining to 8.164 million in Nov 2012 for another major one-month decline of 67,000 and 7.929 million in Dec 2012 or fewer 235,000 in just one month. The number employed part-time for economic reasons increased to 7.983 million in Jan 2013 or 54,000 more than in Dec 2012 and to 7,991 million in Feb 2013, declining to 7.917 million in May 2013 but increasing to 8.194 million in Jun 2013. The number employed part-time for economic reasons fell to 7.898 million in Aug 2013 for decline of 282,000 in one month from 8.180 million in Jul 2013. The number employed part-time for economic reasons increased 16,000 from 7.898 million in Aug 2013 to 7.914 million in Sep 2013. The number part-time for economic reasons rose to 8.016 million in Oct 2013, falling by 293,000 to 7.723 million in Nov 2013. The number part-time for economic reasons increased to 7.771 million in Dec 2013, decreasing to 7.257 million in Jan 2014. There is an increase of 186,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 119,000 from Aug 2012 to Nov 2012. The number employed full-time increased from 112.906 million in Oct 2011 to 115.114 million in Mar 2012 or 2.208 million but then fell to 114.279 million in May 2012 or 0.835 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.626 million in Aug 2012 to 115.531 million in Oct 2012 or increase of 0.905 million full-time jobs in two months and further to 115.821 million in Jan 2013 or increase of 1.195 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.785 million in Feb 2013, increasing to 116.288 million in May 2013 and 116.087 million in Jun 2013. Then number of full-time jobs increased to 116.156 million in Jul 2013, 116.301 million in Aug 2013 and 116.883 million in Sep 2013. The number of full-time jobs fell to 116.306 million in Oct 2013 and increased to 116.951 in Nov 2013. The level of full-time jobs fell to 117.278 million in Dec 2013, increasing to 117.656 million in Jan 2014. Benchmark and seasonality-factors adjustments at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.051 million and to 7.694 million in Apr 2012 or 1.224 million fewer relative to Jan 2012. In Aug 2012, the number employed part-time for economic reasons reached 7.842 million NSA or 148,000 more than in Apr 2012. The number employed part-time for economic reasons increased from 7.842 million in Aug 2012 to 8.110 million in Sep 2012 or by 3.4 percent. The number part-time for economic reasons fell from 8.110 million in Sep 2012 to 7.870 million in Oct 2012 or by 240.000 in one month. The number employed part-time for economic reasons NSA increased to 8.628 million in Jan 2013 or 758,000 more than in Oct 2012. The number employed part-time for economic reasons fell to 8.298 million in Feb 2013, which is lower by 330,000 relative to 8.628 million in Jan 2013 but higher by 428,000 relative to 7.870 million in Oct 2012. The number employed part time for economic reasons fell to 7.734 million in Mar 2013 or 564,000 less than in Feb 2013 and fell to 7.709 million in Apr 2013. The number employed part-time for economic reasons reached 7.618 million in May 2013. The number employed part-time for economic reasons jumped from 7.618 million in May 2013 to 8.440 million in Jun 2013 or 822,000 in one month. The number employed part-time for economic reasons fell to 8.324 million in Jul 2013 and 7.690 million in Aug 2013. The number employed part-time for economic reasons NSA fell to 7.522 million in Sep 2013, increasing to 7.700 million in Oct 2013. The number employed part-time for economic reasons fell to 7.563 million in Nov 2013 and increased to 7.990 million in Dec 2013. The number employed part-time for economic reasons fell to 7.771 million in Jan 2014. The number employed full time without seasonal adjustment fell from 113.138 million in Nov 2011 to 113.050 million in Dec 2011 or by 88,000 and fell further to 111.879 in Jan 2012 for cumulative decrease of 1.259 million. The number employed full-time not seasonally adjusted fell from 113.138 million in Nov 2011 to 112.587 million in Feb 2012 or by 551.000 but increased to 116.214 million in Aug 2012 or 3.076 million more full-time jobs than in Nov 2011. The number employed full-time not seasonally adjusted decreased from 116.214 million in Aug 2012 to 115.678 million in Sep 2012 for loss of 536,000 full-time jobs and rose to 116.045 million in Oct 2012 or by 367,000 full-time jobs in one month relative to Sep 2012. The number employed full-time NSA fell from 116.045 million in Oct 2012 to 115.515 million in Nov 2012 or decline of 530.000 in one month. The number employed full-time fell from 115.515 in Nov 2012 to 115.079 million in Dec 2012 or decline by 436,000 in one month. The number employed full time fell from 115.079 million in Dec 2012 to 113.868 million in Jan 2013 or decline of 1.211 million in one month. The number of full time jobs increased to 114.191 in Feb 2012 or by 323,000 in one month and increased to 114.796 million in Mar 2013 for cumulative increase from Jan by 928,000 full-time jobs but decrease of 283,000 from Dec 2012. The number employed full time reached 117.400 million in Jun 2013 and increased to 117.688 in Jul 2013 or by 288,000. The number employed full-time reached 117.868 million in Aug 2013 for increase of 180,000 in one month relative to Jul 2013. The number employed full-time fell to 117.308 million in Sep 2013 or by 560,000. The number employed full-time fell to 116.798 million in Oct 2013 or decline of 510.000 in one month. The number employed full-time rose to 116.875 million in Nov 2013, falling to 116.661 million in Dec 2013. The number employed full-time fell to 115.744 million in Jan 2014. Comparisons over long periods require use of NSA data. The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in Jan 2014 is 115.774 million, which is lower by 7.475 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 246.915 million in Jan 2014 or by 14.957 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 7.475 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 131.112 million full-time jobs with population of 246.915 million in Jan 2014 or 15.368 million fewer full-time jobs relative to actual 115.744 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 14 million. Mediocre GDP growth is the main culprit of the fractured US labor market. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.4 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the first estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). As a result, there are 30.3 million unemployed or underemployed in the United States for an effective underutilization rate of 18.5 percent (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.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). US GDP grew 6.5 percent from $14,996.1 billion in IVQ2007 in constant dollars to $15,965.6 billion in IVQ2013 or 6.5 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US GDP grew 6.5 percent from $14,996.1 billion in IVQ2007 in constant dollars to $15,965.6 billion in IVQ2013 or 6.5 percent. 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 $2,074.7 billion than actual $15,965.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 30.3 million unemployed or underemployed equivalent to actual unemployment of 18.5 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.html). 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. 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-9, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Jan 2014	7,257	117,656
Dec 2013	7,771	117.278
Nov 2013	7,723	116.951
Oct 2013	8,016	116.306
Sep 2013	7,914	116.883
Aug 2013	7,898	116.301
Jul 2013	8,180	116.156
Jun 2013	8,194	116.087
May 2013	7,917	116.288
Apr 2013	7,929	116.062
Mar 2013	7,663	115.901
Feb 2013	7,991	115.785
Jan 2013	7,983	115.821
Dec 2012	7,929	115.735
Nov 2012	8,164	115.581
Oct 2012	8,231	115.531
Sep 2012	8,572	115.229
Aug 2012	8,045	114.626
Jul 2012	8,163	114.589
Jun 2012	8,154	114.728
May 2012	8,138	114.279
Apr 2012	7,913	114.398
Mar 2012	7,780	115.114
Feb 2012	8,133	114.210
Jan 2012	8,228	113.790
Dec 2011	8,177	113.740
Nov 2011	8,457	113.158
Oct 2011	8,675	112.906
Sep 2011	9,068	112.523
Aug 2011	8,820	112.643
Jul 2011	8,342	112.209
Not Seasonally Adjusted
Jan 2014	7,771	115.744
Dec 2013	7,990	116.661
Nov 2013	7,563	116.875
Oct 2013	7,700	116.798
Sep 2013	7,522	117.308
Aug 2013	7,690	117.868
Jul 2013	8,324	117.688
Jun 2013	8,440	117.400
May 2013	7,618	116.643
Apr 2013	7,709	115.674
Mar 2013	7,734	114.796
Feb 2013	8,298	114.191
Jan 2013	8,628	113.868
Dec 2012	8,166	115.079
Nov 2012	7,994	115.515
Oct 2012	7,870	116.045
Sep 2012	8,110	115.678
Aug 2012	7,842	116.214
Jul 2012	8,316	116.131
Jun 2012	8,394	116.024
May 2012	7,837	114.634
Apr 2012	7,694	113.999
Mar 2012	7,867	113.916
Feb 2012	8,455	112.587
Jan 2012	8,918	111.879
Dec 2011	8,428	113.050
Nov 2011	8,271	113.138
Oct 2011	8,258	113.456
Sep 2011	8,541	112.980
Aug 2011	8,604	114.286
Jul 2011	8,514	113.759
Jun 2011	8,738	113.255
May 2011	8,270	112.618
Apr 2011	8,425	111.844
Mar 2011	8,737	111.186
Feb 2011	8,749	110.731
Jan 2011	9,187	110.373
Dec 2010	9,205	111.207
Nov 2010	8,670	111.348
Oct 2010	8,408	112.342
Sep 2010	8,628	112.385
Aug 2010	8,628	113.508
Jul 2010	8,737	113.974
Jun 2010	8,867	113.856
May 2010	8,513	112.809
Apr 2010	8,921	111.391
Mar 2010	9,343	109.877
Feb 2010	9,282	109.100
Jan 2010	9,290	108.777 (low)
Dec 2009	9,354 (high)	109.875
Nov 2009	8,894	111.274
Oct 2009	8,474	111.599
Sep 2009	8,255	111.991
Aug 2009	8,835	113.863
Jul 2009	9,103	114.184
Jun 2009	9,301	114.014
May 2009	8,785	113.083
Apr 2009	8,648	112.746
Mar 2009	9,305	112.215
Feb 2009	9,170	112.947
Jan 2009	8,829	113.815
Dec 2008	8,250	116.422
Nov 2008	7,135	118.432
Oct 2008	6,267	120.020
Sep 2008	5,701	120.213
Aug 2008	5,736	121.556
Jul 2008	6,054	122.378
Jun 2008	5,697	121.845
May 2008	5,096	120.809
Apr 2008	5,071	120.027
Mar 2008	5,038	119.875
Feb 2008	5,114	119.452
Jan 2008	5,340	119.332
Dec 2007	4,750	121.042
Nov 2007	4,374	121.846
Oct 2007	4,028	122.006
Sep 2007	4,137	121.728
Aug 2007	4,494	122.870
Jul 2007	4,516	123.219 (high)
Jun 2007	4,469	122.150
May 2007	4,315	120.846
Apr 2007	4,205	119.609
Mar 2007	4,384	119.640
Feb 2007	4,417	119.041
Jan 2007	4,726	119.094
Dec 2006	4,281	120.371
Nov 2006	4,054	120.507
Oct 2006	4,010	121.199
Sep 2006	3,735 (low)	120.780
Aug 2006	4,104	121.979
Jul 2006	4,450	121.951
Jun 2006	4,456	121.070
May 2006	3,968	118.925
Apr 2006	3,787	118.559
Mar 2006	4,097	117.693
Feb 2006	4,403	116.823
Jan 2006	4,597	116.395

Source: US Bureau of Labor Statistics

http://www.bls.gov/

People lose their marketable job skills after prolonged unemployment and face increasing difficulty in finding another job. Chart I-18 shows the sharp rise in unemployed over 27 weeks and stabilization at an extremely high level.

Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2014

Sources: US Bureau of Labor Statistics

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

Another segment of U6 consists of people marginally attached to the labor force who continue to seek employment but less frequently on the frustration there may not be a job for them. Chart I-19 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.

Chart I-19, US, Marginally Attached to the Labor Force, NSA Month, Thousands, 2001-2014

Sources: US Bureau of Labor Statistics

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

The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession, as shown in Chart I-20. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 246.915 million in Jan 2014 or by 14.957 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 7.475 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 131.112 million full-time jobs with population of 246.915 million in Jan 2014 or 15.368 million fewer full-time jobs relative to actual 115.744 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 14 million. 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). This is merely another case of theory without reality with dubious policy proposals.

Inferior performance of the US economy and labor markets, during cyclical slow growth not secular stagnation, is the critical current issue of analysis and policy design.

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2014

Sources: US Bureau of Labor Statistics

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

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2013. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2014

Sources: US Bureau of Labor Statistics

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

Chart I-20B provides number of full-time jobs in the US from 1968 to 2013. There were multiple recessions followed by expansions without contraction of full-time jobs and without recovery as during the period after 2008.

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2014

Sources: US Bureau of Labor Statistics

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

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

Chart I-20C, US, Noninstitutional Civilian Population, Thousands, 1968-2013

Sources: US Bureau of Labor Statistics

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

ESIV Theory and Reality of Secular Stagnation: Youth and Middle-Age Unemployment. Three tables support the argument that the proper comparison of the business cycle is between the recessions of the 1980s and the global recession after IVQ2007 and not as argued erroneously with the Great Depression of the 1930s. Table I-GDP provides percentage change of real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Data are available for the 1930s only on a yearly basis. US GDP fell 4.7 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1981 to IVQ1982 and 4.3 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first three years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985 and 3.5 percent in 1986 while GDP grew, 2.5 percent in 2010, 1.8 percent in 2011, 2.8 percent in 2012 and 1.9 percent in 2013. Actual annual equivalent GDP growth in the four quarters of 2012 and first four quarters of 2013 is 2.3 percent and 2.7 percent in the four quarters of 2013 but only 2.3 percent discounting contribution of 1.67 percentage points of inventory accumulation to growth in IIIQ2013. GDP grew at 4.2 percent in 1985 and 3.5 percent in 1986 while the forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 2.2 to 2.3 percent in 2013 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20131218.pdf) with less reliable forecast of 2.8 to 3.2 percent in 2014 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20131218.pdf). Growth of GDP in the expansion from IIIQ2009 to IVQ2013 has been at average 2.4 percent in annual equivalent.

Table I-GDP, US, Percentage Change of GDP in the 1930s, 1980s and 2000s, ∆%

Year	GDP ∆%	Year	GDP ∆%	Year	GDP ∆%
1930	-8.5	1980	-0.2	2000	4.1
1931	-6.4	1981	2.6	2001	1.0
1932	-12.9	1982	-1.9	2002	1.8
1933	-1.3	1983	4.6	2003	2.8
1934	10.8	1984	7.3	2004	3.8
1935	8.9	1985	4.2	2005	3.4
1936	12.9	1986	3.5	2006	2.7
1937	5.1	1987	3.5	2007	1.8
1938	-3.3	1988	4.2	2008	-0.3
1930	8.0	1989	3.7	2009	-2.8
1940	8.8	1990	1.9	2010	2.5
1941	17.7	1991	-0.1	2011	1.8
1942	18.9	1992	3.6	2012	2.8
1943	17.0	1993	2.7	2013	1.9

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

Characteristics of the four cyclical contractions are provided in Table I-GDPA with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.7 percent, which is almost equal to the decline of 4.3 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

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

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

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

Table I-GDPB shows the extraordinary contrast between the mediocre average annual equivalent growth rate of 2.4 percent of the US economy in the eighteen quarters of the current cyclical expansion from IIIQ2009 to IVQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986, 5.4 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986, 5.2 percent in the first sixteen quarters of expansion from IQ1983 to IVQ1986, 5.0 percent in the first seventeen quarters of expansion from IQ1983 to IQ1987 and 5.0 percent in the eighteen quarters of expansion from IQ1983 to IIQ1987. The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.8 percent in 2012 (http://www.bea.gov/iTable/index_nipa.cfm) The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987 and at 7.8 percent from IQ1983 to IVQ1983. GDP growth in the four quarters of 2012 and 2013 accumulated to 4.7 percent that is equivalent to 2.3 percent in a year. This is obtained by dividing GDP in IVQ2013 of $15,965.6 billion by GDP in IVQ2011 of $15,242.1 billion and compounding by 4/8: {[($15,965.6/$15,242.1)^4/8 -1]100 = 2.3%}. The US economy grew 2.7 percent in IVQ2013 relative to the same quarter a year earlier in IVQ2012. Another important revelation of the revisions and enhancements is that GDP was flat in IVQ2012, which is just at the borderline of contraction. The rate of growth of GDP in the third estimate of IIIQ2013 is 4.1 percent in seasonally adjusted annual rate (SAAR). Inventory accumulation contributed 1.67 percentage points to this rate of growth. The actual rate without this impulse of unsold inventories would have been 2.43 percent, or 0.6 percent in IIIQ2013, such that annual equivalent growth in 2013 is closer to 2.3 percent {[(1.003)(1.006)(1.006)(1.008^4/4-1]100 = 2.3%}, compounding the quarterly rates and converting into annual equivalent.

Table I-7, US, Number of Quarters, Cumulative Growth and Average Annual Equivalent Growth Rate in Cyclical Expansions

	Number of Quarters	Cumulative Growth ∆%	Average Annual Equivalent Growth Rate
IIIQ 1954 to IQ1957	11	12.8	4.5
First Four Quarters IIIQ1954 to IIQ1955	4	7.8
IIQ1958 to IIQ1959	5	10.0	7.9
First Four Quarters IIIQ1958 to IIQ1959	4	9.2
IIQ1975 to IVQ1976	8	8.3	4.1
First Four Quarters IIIQ1975 to IIQ1976	4	6.1
IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987 IQ1983-IIQ1987	13 15 16 17 18	19.9 21.6 22.3 23.1 24.5	5.7 5.4 5.2 5.0 5.0
First Four Quarters IQ1983 to IVQ1983	4	7.8
Average First Four Quarters in Four Expansions*		7.7
IIIQ2009 to IVQ2013	18	11.2	2.4
First Four Quarters IIIQ2009 to IIQ2010		2.7

*First Four Quarters: 7.8% IIIQ1954-IIQ1955; 9.2% IIIQ1958-IIQ1959; 6.1% IIIQ1975-IIQ1976; 7.8% IQ1983-IVQ1983

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

Table EMP provides the comparison between the labor market in the current whole cycle from 2007 to 2013 and the whole cycle from 1979 to 1986. In the entire cycle from 2007 to 2013, the number employed fell 2.118 million, full-time employed fell 4.777 million, part-time for economic reasons increased 3.534 and population increased 13.812 million. The number employed fell 1.5 percent, full-time employed fell 3.9 percent, part-time for economic reasons increased 80.3 percent and population increased 6.0 percent. There is sharp contrast with the contractions of the 1980s and with most economic history of the United States. In the whole cycle from 1979 to 1986, the number employed increased 10.773 million, full-time employed increased 7.875 million, part-time for economic reasons 2.011 million and population 15.724 million. In the entire cycle from 1979 to 1986, the number employed increased 10.9 percent, full-time employed 9.5 percent, part-time for economic reasons 56.2 percent and population 9.5 million. The difference between the 1980s and the current cycle after 2007 is in the high rate of growth after the contraction that maintained trend growth around 3.0 percent for the entire cycle and per capital growth at 2.0 percent. The evident fact is that current weakness in labor markets originates in cyclical slow growth and not in imaginary secular stagnation.

Table EMP, US, Annual Level of Employed, Full-Time Employed, Employed Part-Time for Economic Reasons and Noninstitutional Civilian Population, Millions

	Employed	Full-Time Employed	Part Time Economic Reasons	Noninstitutional Civilian Population
2000s
2000	136.891	113.846	3.227	212.577
2001	136.933	113.573	3.715	215.092
2002	136.485	112.700	4.213	217.570
2003	137.736	113.324	4.701	221.168
2004	139.252	114.518	4.567	223.357
2005	141.730	117.016	4.350	226.082
2006	144.427	119.688	4.162	228.815
2007	146.047	121.091	4.401	231.867
2008	145.362	120.030	5.875	233.788
2009	139.877	112.634	8.913	235.801
2010	139.064	111.714	8.874	237.830
2011	139.869	112.556	8.560	239.618
2012	142.469	114.809	8.122	243.284
2013	143.929	116.314	7.935	245.679
∆2007-2013	-2.118	-4.777	3.534	13.812
∆% 2007-2013	-1.5	-3.9	80.3	6.0
1980s
1979	98.824	82.654	3.577	164.863
1980	99.303	82.562	4.321	167.745
1981	100.397	83.243	4.768	170.130
1982	99.526	81.421	6.170	172.271
1983	100.834	82.322	6.266	174.215
1984	105.005	86.544	5.744	176.383
1985	107.150	88.534	5.590	178.206
1986	109.597	90.529	5.588	180.587
1987	112.440	92.957	5.401	182.753
1988	114.968	95.214	5.206	184.613
1989	117.342	97.369	4.894	186.393
∆1979-1986	10.773	7.875	2.011	15.724
∆% 1979-86	10.9	9.5	56.2	9.5

Source: Bureau of Labor Statistics

http://www.bls.gov/

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). Youth workers would obtain employment at a premium in an economy with declining population. In fact, 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. This is merely another case of theory without reality with dubious policy proposals. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design.

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.”

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. There are accentuated cyclic factors for both the entire population and the young population of ages 16 to 24 years. Table Summary provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would not be secular but immediate. All indicators of the labor market weakened sharply during the contraction and did not recover. Population continued to grow but all other variables collapsed and did not recover. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-6). Hansen (1938, 1939) finds secular stagnation in lower growth of an aging population. In the current US economy, Table Summary shows that population is dynamic while the labor market is fractured. There is key explanation in the behavior of the civilian labor force participation rate (CLFP) and the employment population ratio (EPOP) that collapsed during the global recession with inadequate recovery. Abandoning job searches are difficult to capture in labor statistics but likely explain the decline in the participation of the population in the labor force. Allowing for abandoning job searches, the total number of people unemployed or underemployed is 30.3 million or 18.5 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html).

Table Summary Total, US, Total Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Thousands and Percent

	ICP	FTE	EMP	CLF	CLFP	EPOP	UNE
2006	228.8	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
2013	245.7	116.3	143.9	155.4	63.2	58.6	11.5
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
1/14	246.9	115.8	143.5	154.4	62.5	58.1	10.9

ICP: Total Noninstitutional Civilian Population; FT: Full-time Employment Level, EMP: Total Employment Level; CLF: Civilian Labor Force; CLFP: Civilian Labor Force Participation Rate; EPOP: Employment Population Ratio; UNE: Unemployment

Source: Bureau of Labor Statistics

http://www.bls.gov/

The same situation is present in the labor market for young people in ages 16 to 24 years with data in Table Summary Youth. The youth noninstitutional civilian population (ICP) continued to increase during and after the global recession. There is the same disastrous labor market with decline for young people in employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP) and employment population ratio (EPOP). There are only increases for unemployment of young people (UNE) and youth unemployment rate (UNER). If aging were a factor of secular stagnation, growth of population of young people would attract a premium in remuneration in labor markets. The sad fact is that young people are also facing tough labor markets. The application of the theory of secular stagnation to the US economy and labor markets is void of reality in the form of key facts.

Table Summary Youth, US, Youth, Ages 16 to 24 Years, Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Thousands and Percent

	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	38.7	17.8	21.3	54.9	46.0	3.5	16.2
2013	38.8	18.1	21.4	55.0	46.5	3.3	15.5
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
1/14	38.8	17.4	20.4	52.7	44.8	3.1	14.9

ICP: Youth Noninstitutional Civilian Population; EMP: Youth Employment Level; CLF: Youth Civilian Labor Force; CLFP: Youth Civilian Labor Force Participation Rate; EPOP: Youth Employment Population Ratio; UNE: Unemployment; UNER: Youth Unemployment Rate

Source: Bureau of Labor Statistics

http://www.bls.gov/

The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs and to 17.834 million in 2012 or 2.207 million fewer jobs. Youth employment fell from 20.041 million in 2006 to 18.057 million in 2013 or 1.984 million fewer jobs. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.914 million in Jul 2006 with 19.684 million in Jul 2013 for 2.230 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 21.167 million in Aug 2006 to 18.636 million in Aug 2013 or by 2.531 million. The number of youth jobs fell from 19.604 million in Sep 2006 to 18.043 million in Sep 2013 or 1.561 million fewer youth jobs. The number of youth jobs fell from 20.129 million in Dec 2006 to 18.106 million in Dec 2013 or 2.023 million fewer jobs. The number of youth jobs fell from 19.407 million in Jan 2007 to 17.372 million in Jan 2014 or 2.035 million fewer youth jobs. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

Table I-10, US, Employment Level 16-24 Years, Thousands, NSA

Year	Jan	Feb	Oct	Nov	Dec
2001	19678	19745	19694	19675	19547
2002	18653	19074	19542	19397	19394
2003	18811	18880	19139	19163	19136
2004	18852	18841	19609	19615	19619
2005	18858	18670	19794	19750	19733
2006	19003	19182	19853	19903	20129
2007	19407	19415	19564	19660	19361
2008	18724	18546	18757	18454	18378
2009	17467	17606	16671	16689	16615
2010	16166	16412	16867	16946	16727
2011	16512	16638	17532	17402	17234
2012	16944	17150	17842	17877	17604
2013	17183	17257	17976	18104	18106
2014	17372

Source: Bureau of Labor Statistics

http://www.bls.gov/

Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2014. Employment level is sharply lower in Jan 2014 relative to the peak in 2007.

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2014

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

Chart I-21A provides the US civilian noninstitutional population ages 16 to 24 years not seasonally adjusted from 2001 to 2014. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million.

Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2014

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

Chart I-21B provides the civilian labor force of the US ages 16 to 24 years NSA from 2001 to 2014. The US civilian labor force ages 16 to 24 years fell from 24.339 million in Jul 2007 to 23.506 million in Jul 2013, by 0.833 million or decline of 3.4 percent, while the civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013, by 1.418 million or 3.8 percent. The US civilian labor force ages 16 to 24 fell from 22.801 million in Aug 2007 to 22.089 million in Aug 2013, by 0.712 million or 3.1 percent, while the noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013, by 1.386 million or 3.7 percent. The US civilian labor force ages 16 to 24 years fell from 21.917 million in Sep 2007 to 21.183 million in Sep 2013, by 0.734 million or 3.3 percent while the civilian noninstitutional youth population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 by 1.355 million or 3.6 percent. The US civilian labor force fell from 21.821 million in Oct 2007 to 21.003 million in Oct 2013, by 0.818 million or 3.7 percent while the noninstitutional youth population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013, by 1.324 million or 3.5 percent. The US youth civilian labor force fell from 21.909 million in Nov 2007 to 20.825 million in Nov 2013, by 1.084 million or 4.9 percent while the civilian noninstitutional youth population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million. The US youth civilian labor force fell from 21.684 million in Dec 2007 to 20.642 million in Dec 2013, by 1.042 million or 4.8 percent, while the civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013, by 1.272 million or 3.4 percent. The yough civilian labor force of the US fell from 21.770 million in Jan 2007 to 20.423 million in Jan2014, by 1.347 million or 6.2 percent while the youth civilian noninstitutional population increased 37.282 million in Jan 2007 to 38.770 million in Jan 2014, by 1.488 million or 4.0 percent. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.

Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2014

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

Chart I-21C provides the ratio of labor force to noninstitutional population or labor force participation of ages 16 to 24 years not seasonally adjusted. The US labor force participation rates for ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2013 because of the frustration of young people who believe there may not be jobs available for them. The US labor force participation rate of young people fell from 63.9 in Aug 2006 to 56.9 in Aug 2013. The US labor force participation rate of young people fell from 59.1 percent in Sep 2006 to 54.6 percent in Sep 2013. The US labor force participation rate of young people fell from 59.7 percent in Oct 2006 to 54.1 in Oct 2013. The US labor force participation rate of young people fell from 59.7 percent in Nov 2006 to 53.7 percent in Nov 2013. The US labor force participation rate fell from 57.8 in Dec 2007 to 53.2 in Dec 2013. The youth labor force participation rate fell from 58.4 in Jan 2007 to 52.7 in Jan 2014. Many young people abandoned searches for employment, dropping from the labor force.

Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2014

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

An important measure of the job market is the number of people with jobs relative to population available for work or civilian noninstitutional population or employment/population ratio. Chart I-21D provides the employment population ratio for ages 16 to 24 years. The US employment/population ratio NSA for ages 16 to 24 years collapsed from 59.2 in Jul 2006 to 50.7 in Jul 2013. The employment population ratio for ages 16 to 24 years dropped from 57.2 in Aug 2006 to 48.0 in Aug 2013. The employment population ratio for ages to 16 to 24 years declined from 52.9 in Sep 2006 to 46.5 in Sep 2013. The employment population ratio for ages 16 to 24 years fell from 53.6 in Oct 2006 to 46.3 in Oct 2013. The employment population ratio for ages 16 to 24 years fell from 53.7 in Nov 2007 to 46.7 in Nov 2013. The US employment population ratio for ages 16 to 24 years fell from 51.6 in Dec 2007 to 46.7 in Dec 2013. The US employment population ratio fell from 52.1 in Jan 2007 to 44.8 in Jan 2014. Chart I-21D shows vertical drop during the global recession without recovery.

Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2014

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

Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million and 3451 thousand in 2012 or by 1.109 million. The unemployment level ages 16 to 23 years increased from 2342 in 2007 to 3324 thousand in 2013 or by 0.982 million. The unemployment level ages 16 to 24 years rose from 2.363 million in Jan 2007 to 3.051 million in Jan 2014 or by 0.688 million. This situation may persist for many years.

Table I-11, US, Unemployment Level 16-24 Years, NSA, Thousands

Year	Jan	Feb	Sep	Oct	Nov	Dec	Annual
2001	2250	2258	2301	2424	2470	2412	2371
2002	2754	2731	2506	2468	2570	2374	2683
2003	2748	2740	2698	2522	2522	2248	2746
2004	2767	2631	2493	2572	2448	2294	2638
2005	2661	2787	2339	2285	2369	2055	2521
2006	2366	2433	2297	2252	2242	2007	2353
2007	2363	2230	2419	2258	2250	2323	2342
2008	2633	2480	2904	2842	2833	2928	2830
2009	3278	3457	3774	3789	3699	3532	3760
2010	3983	3888	3604	3731	3561	3352	3857
2011	3851	3696	3541	3386	3287	3161	3634
2012	3416	3507	3174	3285	3102	3153	3451
2013	3674	3449	3139	3028	2721	2536	3324
2014	3051

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

Chart I-22 provides the unemployment level for ages 16 to 24 from 2001 to 2014. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013 with recent marginal improvement alternating with deterioration.

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2014

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

Table I-12 provides the rate of unemployment of young peoples in ages 16 to 24 years. The annual rate jumped from 10.5 percent in 2007 to 18.4 percent in 2010, 17.3 percent in 2011 and 16.2 percent in 2012. The rate of youth unemployment fell marginally to 15.5 percent in Dec 2013. During the seasonal peak in Jul, the rate of youth unemployed was 18.1 percent in Jul 2011, 17.1 percent in Jul 2012 and 16.3 percent in Jul 2013 compared with 10.8 percent in Jul 2007. The rate of youth unemployment rose from 11.2 in Jul 2006 to 16.3 percent in Jul 2013 and likely higher if adding those who ceased searching for a job in frustration none may be available. The rate of youth unemployment increased from 9.1 percent in Dec 2006 to 12.3 percent in Dec 2013. The rate of youth unemployment increased from 10.9 percent in Jan 2007 to 14.9 percent in Jan 2014. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them.

Table I-12, US, Unemployment Rate 16-24 Years, Thousands, NSA

Year	Jan	Feb	Jul	Aug	Sep	Oct	Nov	Dec	Annual
2001	10.3	10.3	10.5	10.7	10.5	11.0	11.2	11.0	10.6
2002	12.9	12.5	12.4	11.5	11.4	11.2	11.7	10.9	12.0
2003	12.7	12.7	13.3	11.9	12.5	11.6	11.6	10.5	12.4
2004	12.8	12.3	12.3	11.1	11.5	11.6	11.1	10.5	11.8
2005	12.4	13.0	11.0	10.8	10.7	10.3	10.7	9.4	11.3
2006	11.1	11.3	11.2	10.4	10.5	10.2	10.1	9.1	10.5
2007	10.9	10.3	10.8	10.5	11.0	10.3	10.3	10.7	10.5
2008	12.3	11.8	14.0	13.0	13.4	13.2	13.3	13.7	12.8
2009	15.8	16.4	18.5	18.0	18.2	18.5	18.1	17.5	17.6
2010	19.8	19.2	19.1	17.8	17.6	18.1	17.4	16.7	18.4
2011	18.9	18.2	18.1	17.5	17.0	16.2	15.9	15.5	17.3
2012	16.8	17.0	17.1	16.8	15.2	15.5	14.8	15.2	16.2
2013	17.6	16.7	16.3	15.6	14.8	14.4	13.1	12.3	15.5
2014	14.9

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

Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2001 to 2014. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels because of low growth of GDP. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2014

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

Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2014. The rate of youth unemployment rose to 20 percent during the contractions of the early 1980s and also during the contraction of the global recession in 2008 and 2009. The data illustrate again the argument in this blog that the contractions of the early 1980s are the valid framework for comparison with the global recession of 2008 and 2009 instead of misleading comparisons with the 1930s. During the initial phase of recovery, the rate of youth unemployment 16 to 24 years NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984. In contrast, the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 17.5 percent in Dec 2009, 16.7 percent in Dec 2010, 15.5 percent in Dec 2011, 15.2 percent in Dec 2012, 17.6 percent in Jan 2013, 16.7 percent in Feb 2013, 15.9 percent in Mar 2013, 15.1 percent in Apr 2013. The rate of youth unemployment was 16.4 percent in May 2013, 18.0 percent in Jun 2013, 16.3 percent in Jul 2013 and 15.6 percent in Aug 2013. In Sep 2006, the rate of youth unemployment was 10.5 percent, increasing to 14.8 percent in Sep 2013. The rate of youth unemployment was 10.3 in Oct 2007, increasing to 14.4 percent in Oct 2013. The rate of youth unemployment was 10.3 percent in Nov 2007, increasing to 13.1 percent in Nov 2013. The rate of youth unemployment was 10.7 percent in Dec 2013, increasing to 12.3 percent in Dec 2013. The rate of youth unemployment was 10.9 percent in Jan 2007, increasing to 14.9 percent in Jan 2014. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 and 5.2 percent from IQ1983 to IIIQ1986 compared with 2.4 percent on average during the first seventeen quarters of expansion from IIIQ2009 to IVQ2013 (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html).US economic growth has been at only 2.4 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the first estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). As a result, there are 30.3 million unemployed or underemployed in the United States for an effective underutilization rate of 18.5 percent (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.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). US GDP grew 6.5 percent from $14,996.1 billion in IVQ2007 in constant dollars to $15,965.6 billion in IVQ2013 or 6.5 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US GDP grew 6.5 percent from $14,996.1 billion in IVQ2007 in constant dollars to $15,965.6 billion in IVQ2013 or 6.5 percent. 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 $2,074.7 billion than actual $15,965.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 30.3 million unemployed or underemployed equivalent to actual unemployment of 18.5 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.html). 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. 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.

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2013

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

It is more difficult to move to other jobs after a certain age because of fewer available opportunities for mature individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.607 million in Oct 2006 to 4.576 million in Oct 2010 or by 184.8 percent. The number of unemployed ages 45 years and over declined to 3.800 million in Oct 2012 that is still higher by 136.5 percent than in Oct 2006. The number unemployed age 45 and over increased from 1.704 million in Nov 2006 to 3.861 million in Nov 2012, or 126.6 percent. The number unemployed age 45 and over is still higher by 98.5 percent at 3.383 million in Nov 2013 than 1.704 million in Nov 2006. The number unemployed age 45 and over jumped from 1.794 million in Dec 2006 to 4.762 million in Dec 2010 or 165.4 percent. At 3.927 million in Dec 2012, mature unemployment is higher by 2.133 million or 118.9 percent higher than 1.794 million in Dec 2006. The level of unemployment of those aged 45 year or more of 3.632 million in Oct 2013 is higher by 2.025 million than 1.607 million in Sep 2006 or higher by 126.0 percent. The number of unemployed 45 years and over increased from 1.794 million in Dec 2006 to 3.378 million in Nov 2013 or 88.3 percent. The annual number of unemployed 45 years and over increased from 1.848 million 2006 to 3.719 million in 2013 or 101.2 percent. The number of unemployed 45 years and over increased from 2.126 million in Jan 2006 to 4.394 million in Jan 2013, by 2.618 million or 106.7 percent. The number of unemployed 45 years and over rose from 2.126 million in Jan 2006 to 3.508 million in Jan 2014, by 1.382 million or 65.0 percent. The actual number unemployed is likely much higher because many are not accounted who abandoned job searches in frustration there may not be a job for them. Recent improvements may be illusory.

Table I-13, US, Unemployment Level 45 Years and Over, Thousands NSA

Year	Jan	Feb	Aug	Sep	Oct	Nov	Dec	Annual
2000	1498	1392	1339	1254	1202	1242	1217	1249
2001	1572	1587	1640	1586	1722	1786	1901	1576
2002	2235	2280	2114	1966	1945	2013	2210	2114
2003	2495	2415	2301	2157	2032	2132	2130	2253
2004	2453	2397	2082	1951	1931	2053	2086	2149
2005	2286	2286	1895	1992	1875	1920	1963	2009
2006	2126	2056	1869	1710	1607	1704	1794	1848
2007	2155	2138	1956	1854	1885	1925	2120	1966
2008	2336	2336	2695	2595	2728	3078	3485	2540
2009	4138	4380	4683	4560	4492	4655	4960	4500
2010	5314	5307	5128	4640	4576	4909	4762	4879
2011	5027	4837	4592	4426	4375	4195	4182	4537
2012	4458	4472	4179	3899	3800	3861	3927	4133
2013	4394	4107	3607	3535	3632	3383	3378	3719
2014	3508

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

Chart I-25 provides the level unemployed ages 45 years and over. There was an increase in the recessions of the 1980s, 1991 and 2001 followed by declines to earlier levels. The current expansion of the economy after IIIQ2009 has not been sufficiently vigorous to reduce significantly middle-age unemployment. Recent improvements could be illusory because many abandoned job searches in frustration that there may not be jobs for them and are not counted as unemployed.

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2014

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

The analysis by Kydland (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/kydland-bio.html) and Prescott (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/prescott-bio.html) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:

U_t = Uⁿ_t – α(π_t – π^e) α > 0 (1)

Where U_t is the rate of unemployment at current time t, Uⁿ_t is the natural rate of unemployment, π_t is the current rate of inflation and π^e is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:

W = W(π_t, U_t) (2)

The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (π_t, U_t - Uⁿ) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent on average since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). The Bureau of Labor Statistics important report on productivity and costs released on Feb 6, 2014 (http://www.bls.gov/lpc/) supports the argument of decline of productivity in the US analyzed by Prescott and Ohanian (2014Feb). Table VA-3 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2013. The data confirm the argument of Prescott and Ohanian (2014Feb): productivity increased cumulatively 2.6 percent from 2011 to 2013 at the average annual rate of 0.9 percent. The situation is direr by excluding growth of 1.5 percent in 2012, which leaves an average of 0.55 percent for 2011 and 2013. Average productivity growth for the entire economic cycle from 2007 to 2013 is only 1.6 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.2 percent and 3.3 percent in 2010 consisted on reducing labor hours.

Table VA-3, US, Revised Nonfarm Business Sector Productivity and Costs Annual Average, ∆% Annual Average 

	2013 ∆%	2012 ∆%	2011 ∆%	2010 ∆%	2009 ∆%	2008  ∆%	2007 ∆%
Productivity	0.6	1.5	0.5	3.3	3.2	0.8	1.6
Real Hourly Compensation	0.2	0.5	-0.7	0.4	1.5	-1.1	1.4
Unit Labor Costs	1.0	1.2	2.0	-1.2	-2.0	2.0	2.6

Source: US Bureau of Labor Statistics

http://www.bls.gov/lpc/

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.

Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent on average since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those analyzed by Kydland and Prescott (1977). The Bureau of Labor Statistics important report on productivity and costs released on Feb 6, 2014 (http://www.bls.gov/lpc/) supports the argument of decline of productivity in the US analyzed by Prescott and Ohanian (2014Feb). Table VA-3 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2013. The data confirm the argument of Prescott and Ohanian (2014Feb): productivity increased cumulatively 2.6 percent from 2011 to 2013 at the average annual rate of 0.9 percent. The situation is direr by excluding growth of 1.5 percent in 2012, which leaves an average of 0.55 percent for 2011 and 2013. Average productivity growth for the entire economic cycle from 2007 to 2013 is only 1.6 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.2 percent and 3.3 percent in 2010 consisted on reducing labor hours.

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.”

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-6). Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:

“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated. Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”

Chart VA-20 provides nonfarm-business labor productivity, measured by output per hour, from 1947 to 2013. The rate of productivity increase continued in the early part of the 2000s but then softened and fell during the global recession. The interruption of productivity increases occurred exclusively in the current business cycle. Lazear and Spletzer (2012JHJul22) find “primarily cyclic” factors in explaining the frustration of currently depressed labor markets in the United States. Stagnation of productivity is another cyclic event and not secular trend. The theory and application of secular stagnation to current US economic conditions is void of reality.

Chart VA-20, US, Nonfarm Business Labor Productivity, Output per Hour, 1947-2013, Index 2005=100

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

Table VA-3A expands Table VA-3 providing more complete measurements of the Productivity and Cost research of the Bureau of Labor Statistics. The proper emphasis of Prescott and Ohanian (2014Feb) is on the low productivity increases from 2011 to 2013. Labor productivity increased 3.3 percent in 2010 and 3.2 percent in 2009. There is much stronger yet not sustained performance in 2010 with productivity growing 3.3 percent because of growth of output of 3.2 percent with decline of hours worked of 0.1 percent. Productivity growth of 3.2 percent in 2009 consists of decline of output by 4.3 percent while hours worked collapsed 7.2 percent, which is not a desirable route to progress. The expansion phase of the economic cycle concentrated in one year, 2010, with underperformance in the remainder of the expansion from 2011 to 2013 of productivity growth at average 0.9 percent per year.

VA-3A, US, Productivity and Costs, Annual Percentage Changes 2007-2013

	2013	2012	2011	2010	2009	2008	2007
Productivity	0.6	1.5	0.5	3.3	3.2	0.8	1.6
Output	2.3	3.7	2.5	3.2	-4.3	-1.3	2.3
Hours Worked	1.6	2.2	2.0	-0.1	-7.2	-2.0	0.7
Employment	1.8	2.0	1.5	-1.2	-5.7	-1.5	0.9
Average Weekly Hours Worked	-0.1	0.2	0.5	1.1	-1.6	-0.5	-0.2
Hourly Compensation	1.6	2.6	2.5	2.1	1.1	2.7	4.3
Consumer Price Inflation	1.5	2.1	3.2	1.6	-0.4	3.8	2.8
Real Hourly Compensation	0.2	0.5	-0.7	0.4	1.4	-1.1	1.4
Non-labor Payments	3.9	6.5	4.0	7.3	-0.1	-0.4	3.4
Output per Job	0.5	1.7	1.0	4.4	1.5	0.2	1.4

Source: US Bureau of Labor Statistics

http://www.bls.gov/lpc/

Productivity growth can bring about prosperity while productivity regression can jeopardize progress. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Table V-3B provide average growth rates of indicators in the research of productivity and growth of the US Bureau of Labor Statistics. There is dramatic decline of productivity growth in the whole cycle from 2.2 percent per year on average from 1947 to 2013 to 1.6 percent per year on average from 2007 and 2013. There is profound drop in the average rate of output growth from 3.4 percent on average from 1947 to 2013 to 1.2 percent from 2007 to 2013. Real hourly compensation collapsed from average 1.6 percent per year from 1947 to 2013 to 0.3 percent per year from 2007 to 2013. The antithesis of secular stagnation is cyclical slow growth. The policy design deserves consideration of Kydland and Prescott (1977) and Prescott and Ohanian (2014Feb) to induce productivity growth for future progress.

Table V-3B, US, Productivity and Costs, Average Annual Percentage Changes 2007-2013 and 1947-2013

	Average Annual Percentage Rate 2007-2013	Average Annual Percentage Rate  1947-2013
Productivity	1.6	2.2
Output	1.2	3.4
Hours	0.0	1.2
Employment	0.0	1.4
Average Weekly Hours	0.0	NA
Hourly Compensation	2.4	5.1
Consumer Price Inflation	2.1	3.6
Real Hourly Compensation	0.3	1.6
Non-labor Payments	3.5	3.4
Output per Job	1.5	2.0

Source: US Bureau of Labor Statistics

http://www.bls.gov/lpc/

ESV United States Budget Quagmire. Table IIA1-1 of the CBO (2012NovMBR, 2013BEOFeb5, 2013HBDFFeb5, 2013MEFFeb5, 2013Aug12, CBO, Feb 2014) shows the significant worsening of United States fiscal affairs from 2007-2008 to 2009-2012 with marginal improvement in 2013 but with much higher debt relative to GDP. The deficit of $1.1 trillion in fiscal year 2012 was the fourth consecutive federal deficit exceeding one trillion dollars. All four deficits are the highest in share of GDP since 1946 (CBO 2012MBR, 2013HBDFeb5, 2013Aug12, 2013AugHBD).

Table IAI-1, US, Budget Fiscal Year Totals, Billions of Dollars and % GDP

	2007	2008	2009	2010	2011	2012	2013
Receipts	2568	2524	2105	2163	2304	2450	2774
Outlays	2729	2983	3518	3457	3603	3537	3454
Deficit	-161	-459	1413	1294	1300	1087	680
% GDP	-1.1	-3.1	-9.8	-8.8	-8.4	-6.8	-4.1

Source: CBO (2012NovMBR), CBO (2013BEOFeb5), CBO (2013HBDFeb5), CBO (2013Aug12). CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb.

Table IIA1-2 provides additional information required for understanding the deficit/debt situation of the United States. The table is divided into three parts: federal fiscal data for the years from 2009 to 2012; federal fiscal data for the years from 2005 to 2008; and Treasury debt held by the public from 2005 to 2012. There are also receipts, outlays, deficit and debt for fiscal year 2013. Total revenues of the US from 2009 to 2012 accumulate to $9021 billion, or $9.0 trillion, while expenditures or outlays accumulate to $14,109 billion, or $14.1 trillion, with the deficit accumulating to $5090 billion, or $5.1 trillion. Revenues decreased 6.5 percent from $9653 billion in the four years from 2005 to 2008 to $9021 billion in the years from 2009 to 2012. Decreasing revenues were caused by the global recession from IVQ2007 (Dec) to IIQ2009 (Jun) and also by growth of only 2.4 percent on average in the cyclical expansion from IIIQ2009 to IVQ2013. In contrast, the expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). Because of mediocre GDP growth, there are 30.3 million unemployed or underemployed in the United States for an effective unemployment rate of 18.5 percent (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). Weakness of growth and employment creation is analyzed in IB Collapse of United States Dynamism of Income Growth and Employment Creation (http://cmpassocregulationblog.blogspot.com/2014/01/world-inflation-waves-interest-rate.html). In contrast with the decline of revenue, outlays or expenditures increased 30.2 percent from $10,839 billion, or $10.8 trillion, in the four years from 2005 to 2008, to $14,109 billion, or $14.1 trillion, in the four years from 2009 to 2012. Increase in expenditures by 30.2 percent while revenue declined by 6.5 percent caused the increase in the federal deficit from $1186 billion in 2005-2008 to $5090 billion in 2009-2012. Federal revenue was 14.9 percent of GDP on average in the years from 2009 to 2012, which is well below 17.4 percent of GDP on average from 1973 to 2012. Federal outlays were 23.3 percent of GDP on average from 2009 to 2012, which is well above 20.4 percent of GDP on average from 1973 to 2012. The lower part of Table I-2 shows that debt held by the public swelled from $5803 billion in 2008 to $11,982 billion in 2013, by $5478 billion or 106.5 percent. Debt held by the public as percent of GDP or economic activity jumped from 39.3 percent in 2008 to 72.1 percent in 2013, which is well above the average of 38.0 percent from 1973 to 2012. The United States faces tough adjustment because growth is unlikely to recover, creating limits on what can be obtained by increasing revenues, while continuing stress of social programs restricts what can be obtained by reducing expenditures.

Table IIA1-2, US, Treasury Budget and Debt Held by the Public, Billions of Dollars and Percent of GDP 

	Receipts	Outlays	Deficit (-), Surplus (+)
$ Billions
Fiscal Year 2013	2,774	3,454	-680
% GDP	16.7	20.8	-4.1
Fiscal Year 2012	2,450	3,537	-1,087
% GDP	15.2	22.0	-6.8
Fiscal Year 2011	2,304	3,603	-1,300
% GDP	15.0	23.4	-8.4
Fiscal Year 2010	2,163	3,457	-1,294
% GDP	14.6	23.4	-8.8
Fiscal Year 2009	2,105	3,518	-1,413
% GDP	14.6	24.4	-9.8
Total 2009-2012	9,021	14,109	-5,090
Average % GDP 2009-2012	14.9	23.3	-8.4
Fiscal Year 2008	2,524	2,983	-459
% GDP	17.1	20.2	-3.1
Fiscal Year 2007	2,568	2,729	-161
% GDP	17.9	19.0	-1.1
Fiscal Year 2006	2,407	2,655	-248
% GDP	17.6	19.4	-1.8
Fiscal Year 2005	2,154	2,472	-318
% GDP	16.7	19.2	-2.5
Total 2005-2008	9,653	10,839	-1,186
Average % GDP 2005-2008	17.3	19.5	-2.1
Debt Held by the Public	Billions of Dollars	Percent of GDP
2005	4,592	35.6
2006	4,829	35.3
2007	5,035	35.1
2008	5,803	39.3
2009	7,545	52.3
2010	9,019	61.0
2011	10,128	65.8
2012	11,281	70.1
2013	11,982	72.1

Source: http://www.fms.treas.gov/mts/index.html CBO (2012NovMBR). CBO (2011AugBEO); Office of Management and Budget 2011. Historical Tables. Budget of the US Government Fiscal Year 2011. Washington, DC: OMB; CBO. 2011JanBEO. Budget and Economic Outlook. Washington, DC, Jan. CBO. 2012AugBEO. Budget and Economic Outlook. Washington, DC, Aug 22. CBO. 2012Jan31. Historical budget data. Washington, DC, Jan 31. CBO. 2012NovCDR. Choices for deficit reduction. Washington, DC. Nov. CBO. 2013HBDFeb5. Historical budget data—February 2013 baseline projections. Washington, DC, Congressional Budget Office, Feb 5. CBO. 2013HBDFeb5. Historical budget data—February 2013 baseline projections. Washington, DC, Congressional Budget Office, Feb 5. CBO (2013Aug12). 2013AugHBD. Historical budget data—August 2013. Washington, DC, Congressional Budget Office, Aug. CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb.

Unusually low economic growth of average 2.4 percent of GDP in the current expansion from IIIQ2009 to IVQ2013 and 2.7 percent in the first four quarters from IIIQ2009 to IIQ2010 (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html) has had adverse impact on revenue generation. The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.8 percent in the first four quarters from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). Because of mediocre GDP growth, there are 30.3 million unemployed or underemployed in the United States for an effective unemployment rate of 18.5 percent (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). The impact of low growth on employment creation and labor market hiring is discussed in Subsection IB Collapse of United States Dynamism of Income Growth and Employment (http://cmpassocregulationblog.blogspot.com/2014/01/world-inflation-waves-interest-rate.html). Table IIAI-3 provides total United States federal receipts from 2010 to 2013. Individual income taxes of $1132 billion, or $1.1 trillion, increased 25.9 percent from 2010 to 2012 and account for 46.2 percent of US total receipts in 2012. Individual income taxes increased 16.3 percent from $1132 billion in 2012 to $1316 billion in 2013, contributing 47.4 percent of total receipts. Total receipts stood at 15.2 percent of GDP in 2012, which is lower than 17.4 percent in the past 40 years (CBO 2013Aug12Av). Total receipts increased to 16.7 percent of GDP in 2013.

Table IIA1-3, United States, Total Receipts, Billions of Dollars and ∆%

Major Source	2010	2011	2012	2013	∆% 2012-2013
Individual Income Taxes	899	1092	1132	1316	16.3
Corporate Income Taxes	191	181	242	274	13.2
Social Insurance	865	819	845	948	12.2
Other	208	212	231	236	10.0
Total	2163	2304	2450	2774	13.2
% of GDP	14.6	15.0	15.2	16.7	NA

Source: CBO (2012NovMBR), CBO (2013BEOFeb5), CBO 2013HBDFeb5), CBO (2013Aug12). CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb.

Total outlays of the federal government of the United States have grown to extremely high levels. Table IIA1-4 of the CBO (2014Feb) provides total outlays in 2006 and 2013. Total outlays of $3454.3 billion in 2013, or $3.5 trillion, are higher by $799.2 billion, or $0.8 trillion, relative to $2655.1 billion in 2006, or $2.7 trillion. Outlays have grown from 19.4 percent of GDP in 2007 to 20.8 percent of GDP in 2013. Outlays as percent of GDP were on average 20.4 percent from 1973 to 2012 and receipts as percent of GDP were on average 17.4 percent of GDP. It has proved extremely difficult to increase receipts above 19 percent of GDP. Mandatory outlays increased from $1411.8 billion in 2006 to $2031.8 billion in 2013, by $620 billion. The first to the final row shows that the total of social security, Medicare, Medicaid, Income Security, net interest and defense absorbs 82.4 percent of US total outlays, which is equal to 17.1 percent of GDP. There has been no meaningful constraint of spending, which is quite difficult because of the rigid structure of social programs.

Table IIA1-4, US, Central Government Total Revenue and Outlays, Billions of Dollars and Percent

	2006	% Total	2013	% Total
I TOTAL REVENUE $B	2406.9	100.0	2774	100.0
% GDP	17.6		16.7
Individual Income Taxes $B	1043.9		1316.4
% GDP	7.6		7.9
Corporate Income Taxes $B	353.9		273.5
% GDP	2.6		5.7
Social Insurance Taxes	837.8		947.5
% GDP	6.1		1.6
II TOTAL OUTLAYS	2655.1		3454.3
% GDP	19.4		20.8
Discretionary	1016.6		1201.2
% GDP	7.4		7.2
Defense	520.0		624.9
% GDP	3.8		3.8
Nondefense	496.7		576.3
% GDP	3.6		3.5
Mandatory	1411.8		2031.8
% GDP	10.3		12.2
Social Security	543.9		807.8
% GDP	4.0		4.9
Medicare	376.8		585.3
% GDP	2.8		3.5
Medicaid	180.6		265.4
% GDP	1.3		1.6
Income Security	200.0		339.9
% GDP	1.5		2.0
Offsetting Receipts	-144.3		-306.1
% GDP	-1.1		-1.8
Net Interest	226.6		221.3
% GDP	1.7		1.3
Defense +Social Security          +Medicare +Medicaid +Income Security +Net interest	2048.0	77.1*	2844.6	82.4*
% GDP	15.1		17.1

*Percent of Total Outlays

Source: CBO (2013Aug12). 2013AugHBD. Historical budget data—August 2013. Washington, DC, Congressional Budget Office, Aug. CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb.

The US is facing a major fiscal challenge. Table IIA1-5 provides federal revenues, expenditures, deficit and debt as percent of GDP and the yearly change in GDP in the more than eight decades from 1930 to 2013. The most recent period of debt exceeding 90 percent of GDP based on yearly observations in Table IIA1-5 is between 1944 and 1948. The data in Table IIA-15 use the earlier GDP estimates of the Bureau of Economic Analysis (BEA) until 1972 for the ratios to GDP of revenue, expenditures, deficit and debt and the revised CBO (2013Aug12) after 1973 that incorporate the new BEA GDP estimates (http://www.bea.gov/iTable/index_nipa.cfm). The percentage change of GDP is based on the new BEA estimates for all years. The debt/GDP ratio actually rose to 106.2 percent of GDP in 1945 and to 108.7 percent of GDP in 1946. GDP fell revised 11.6 percent in 1946, which is only matched in Table I-5 by the decline of revised 12.9 percent in 1932. Part of the decline is explained by the bloated US economy during World War II, growing at revised 17.7 percent in 1941, 18.9 percent in 1942 and 17.0 percent in 1943. Expenditures as a share of GDP rose to their highest in the series: 43.6 percent in 1943, 43.6 percent in 1944 and 41.9 percent in 1945. The repetition of 43.6 percent in 1943 and 1944 is in the original source of Table IIA1-5. During the Truman administration from Apr 1945 to Jan 1953, the federal debt held by the public fell systematically from the peak of 108.7 percent of GDP in 1946 to 61.6 percent of GDP in 1952. During the Eisenhower administration from Jan 1953 to Jan 1961, the federal debt held by the public fell from 58.6 percent of GDP in 1953 to 45.6 percent of GDP in 1960. The Truman and Eisenhower debt reductions were facilitated by diverse factors such as low interest rates, lower expenditure/GDP ratios that could be attained again after lowering war outlays and less rigid structure of mandatory expenditures than currently. There is no subsequent jump of debt as the one from revised 39.3 percent of GDP in 2008 to 65.8 percent of GDP in 2011, 70.1 percent in 2012 and 72.1 percent in 2013.

Table IIA1-5, United States Central Government Revenue, Expenditure, Deficit, Debt and GDP Growth 1930-2011

	Rev % GDP	Exp % GDP	Deficit % GDP	Debt % GDP	GDP ∆%
1930	4.2	3.4	0.8		-8.5
1931	3.7	4.3	-0.6		-6.4
1932	2.8	6.9	-4.0		-12.9
1933	3.5	8.0	-4.5		-1.3
1934	4.8	10.7	-5.9		10.8
1935	5.2	9.2	-4.0		8.9
1936	5.0	10.5	-5.5		12.9
1937	6.1	8.6	-2.5		5.1
1938	7.6	7.7	-0.1		-3.3
1939	7.1	10.3	-3.2		8.0
1940s
1940	6.8	9.8	-3.0	44.2	8.8
1941	7.6	12.0	-4.3	42.3	17.7
1942	10.1	24.3	-14.2	47.0	18.9
1943	13.3	43.6	-30.3	70.9	17.0
1944	20.9	43.6	-22.7	88.3	8.0
1945	20.4	41.9	-21.5	106.2	-1.0
1946	17.7	24.8	-7.2	108.7	-11.6
1947	16.5	14.8	1.7	96.2	-1.1
1948	16.2	11.6	4.6	84.3	4.1
1949	14.5	14.3	0.2	79.0	-0.5
1950s
1950	14.4	15.6	-1.1	80.2	8.7
1951	16.1	14.2	1.9	66.9	8.1
1952	19.0	19.4	-0.4	61.6	4.1
1953	18.7	20.4	-1.7	58.6	4.7
1954	18.5	18.8	-0.3	59.5	-0.6
1955	16.5	17.3	-0.8	57.2	7.1
1956	17.5	16.5	0.9	52.0	2.1
1957	17.7	17.0	0.8	48.6	2.1
1958	17.3	17.9	-0.6	49.2	-0.7
1959	16.2	18.8	-2.6	47.9	6.9
1960s
1960	17.8	17.8	0.1	45.6	2.6
1961	17.8	18.4	-0.6	45.0	2.6
1962	17.6	18.8	-1.3	43.7	6.1
1963	17.8	18.6	-0.8	42.4	4.4
1964	17.6	18.5	-0.9	40.0	5.8
1965	17.0	17.2	-0.2	37.9	6.5
1966	17.3	17.8	-0.5	34.9	6.6
1967	18.4	19.4	-1.1	32.9	2.7
1968	17.6	20.5	-2.9	33.9	4.9
1969	19.7	19.4	0.3	29.3	3.1
1970s
1970	19.0	19.3	-0.3	28.0	0.2
1971	17.3	19.5	-2.1	28.1	3.3
1972	17.6	19.6	-2.0	27.4	5.2
1973	17.0	18.1	-1.1	25.1	5.6
1974	17.7	18.1	-0.4	23.1	-0.5
1975	17.3	20.6	-3.3	24.5	-0.2
1976	16.6	20.8	-4.1	26.7	5.4
1977	17.5	20.2	-2.6	27.1	4.6
1978	17.5	20.1	-2.6	26.6	5.6
1979	18.0	19.6	-1.6	24.9	3.2
1980s
1980	18.5	21.1	-2.6	25.5	-0.2
1981	19.1	21.6	-2.5	25.2	2.6
1982	18.6	22.5	-3.9	27.9	-1.9
1983	17.0	22.8	-5.9	32.1	4.6
1984	16.9	21.5	-4.7	33.1	7.3
1985	17.2	22.2	-5.0	35.3	4.2
1986	17.0	21.8	-4.9	38.4	3.5
1987	17.9	21.0	-3.1	39.5	3.5
1988	17.6	20.6	-3.0	39.8	4.2
1989	17.8	20.5	-2.7	39.3	3.7
1990s
1990	17.4	21.2	-3.7	40.8	1.9
1991	17.3	21.7	-4.4	44.0	-0.1
1992	17.0	21.5	-4.5	46.6	3.6
1993	17.0	20.7	-3.8	47.8	2.7
1994	17.5	20.3	-2.8	47.7	4.0
1995	17.8	20.0	-2.2	47.5	2.7
1996	18.2	19.6	-1.3	46.8	3.8
1997	18.6	18.9	-0.3	44.5	4.5
1998	19.2	18.5	0.8	41.6	4.4
1999	19.2	17.9	1.3	38.2	4.8
2000s
2000	19.9	17.6	2.3	33.6	4.1
2001	18.8	17.6	1.2	31.4	1.0
2002	17.0	18.5	-1.5	32.5	1.8
2003	15.7	19.1	-3.3	34.5	2.8
2004	15.6	19.0	-3.4	35.5	3.8
2005	16.7	19.2	-2.5	35.6	3.4
2006	17.6	19.4	-1.8	35.3	2.7
2007	17.9	19.0	-1.1	35.1	1.8
2008	17.1	20.2	-3.1	39.3	-0.3
2009	14.6	24.4	-9.8	52.3	-2.8
2010s
2010	14.6	23.4	-8.8	61.0	2.5
2011	15.0	23.4	-8.4	65.8	1.8
2012	15.2	22.0	-6.8	70.1	2.8
2013	16.7	20.8	-4.1	72.1	1.9

Sources:

Office of Management and Budget. 2011. Historical Tables. Budget of the US Government Fiscal Year 2011. Washington, DC: OMB. CBO (2012JanBEO). CBO (2012Jan31). CBO (2012AugBEO). CBO (2013BEOFeb5). CBO2013HBDFeb5), CBO (2013Aug12). CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb.

Table IIA1-6 provides 40-year average ratios of fiscal variables to GDP before and after the revision by the Bureau of Economic Analysis (BEA) in Aug 2013 (http://www.bea.gov/iTable/index_nipa.cfm). The ratios are equal or slightly higher because of the addition of intellectual property to GDP estimates. There are no major changes.

Table IIA1-6, US, Congressional Budget Office, 40-Year Averages of Revenues and Outlays Before and After Update of the US National Income Accounts by the Bureau of Economic Analysis, % of GDP 

	Before Update	After Update
Revenues
Individual Income Taxes	8.2	7.9
Social Insurance Taxes	6.2	6.0
Corporate Income Taxes	1.9	1.9
Other	1.6	1.6
Total Revenues	17.9	17.4
Outlays
Mandatory	10.2	9.9
Discretionary	8.6	8.4
Net Interest	2.2	2.2
Total Outlays	21.0	20.4
Deficit	-3.1	-3.0
Debt Held by the Public	39.2	38.0

Source: CBO (2013Aug12Av). Kim Kowaleski and Amber Marcellino.

The capital budgeting decision of business requires the calculation of present value of projects. This calculation consists of a projection toward the horizon of planning of revenues net of costs, which are discounted to present value by the weighted average cost of capital. Business invests in the projects with highest net present value. The nonpartisan Congressional Budget Office (CBO) provides a similar service. Congress and the administration send budget proposals and legislation for evaluation by the CBO of their effects on federal government revenues, expenditures, deficit or surpluses and debt. The CBO does not provide its own policy proposals but analyzes alternative policies. The CBO uses state of the art knowledge but significant uncertainty remains because of the hurdle of projecting financial and economic variables to the future.

Table IIA1-7 provides the latest exercise by the CBO (2013BEOFeb5, 2012AugBEO, CBO2012NovCDR, 2013Sep11, CBO Feb2014) of projecting the fiscal accounts of the US. Table IIA1-7 extends data back to 1995 with the projections of the CBO from 2014 to 2024, using the new estimates of the Bureau of Economic Analysis of US GDP (http://www.bea.gov/iTable/index_nipa.cfm). Budget analysis in the US uses a ten-year horizon. The significant event in the data before 2011 is the budget surpluses from 1998 to 2001, from 0.8 percent of GDP in 1998 to 2.3 percent of GDP in 2000 and 1.2 percent of GDP in 2001. Debt held by the public fell from 47.5 percent of GDP in 1995 to 31.4 percent of GDP in 2001.

Table IIA1-7, US, CBO Baseline Budget Outlook 2014-2024

	Out $B	Out % GDP	Deficit $B	Deficit % GDP	Debt	Debt % GDP
1995	1,516	20.0	-164	-2.2	3,604	47.5
1996	1,560	19.6	-107	-1.3	3,734	46.8
1997	1,601	18.9	-22	-0.3	3,772	44.5
1998	1,652	18.5	+69	+0.8	3,721	41.6
1999	1,702	17.9	+126	+1.3	3,632	38.2
2000	1,789	17.6	+236	+2.3	3,410	33.6
2001	1,863	17.6	+128	+1.2	3,320	31.4
2002	2,011	18.5	-158	-1.5	3,540	32.5
2003	2,159	19.1	-378	-3.3	3,913	34.5
2004	2,293	19.0	-413	-3.4	4,295	35.5
2005	2,472	19.2	-318	-2.5	4,592	35.6
2006	2,655	19.4	-248	-1.8	4,829	35.3
2007	2,729	19.0	-161	-1.1	5,035	35.1
2008	2,983	20.2	-459	-3.1	5,803	39.3
2009	3,518	24.4	-1,413	-9.8	7,545	52.3
2010	3,457	23.4	-1,294	-8.7	9,019	61.0
2011	3,603	23.4	-1,300	-8.4	10,128	65.8
2012	3,537	22.0	-1,087	-6.8	11,281	70.1
2013	3,454	20.8	-680	-4.1	11,982	72.1
2014	3,543	20.5	-514	-3.0	12,717	73.6
2015	3,783	20.9	-478	-2.6	13,263	73.2
2016	4,020	21.1	-539	-2.8	13,861	72.6
2017	4,212	21.0	-581	-2.9	14,507	72.3
2018	4,425	21.1	-655	-3.1	15,218	72.6
2019	4,684	21.4	-752	-3.4	16,028	73.3
2020	4,939	21.7	-836	-3.7	16,925	74.2
2021	5,200	21.9	-912	-3.8	17,899	75.3
2022	5,522	22.3	-1,031	-4.2	19,001	76.8
2023	5,749	22.3	-1,047	-4.1	20,115	78.0
2024	6,000	22.4	-1,074	-4.0	21,260	79.2
2015 to 2019	21,124	21.1	-3,005	-3.0	NA	NA
2014 to 2023	48,534	21.7	-7,904	-3.5	NA	NA

Note: Out = outlays

Sources: CBO (2011AugBEO); Office of Management and Budget. 2011. Historical Tables. Budget of the US Government Fiscal Year 2011. Washington, DC: OMB; CBO. 2011JanBEO. Budget and Economic Outlook. Washington, DC, Jan. CBO. 2012AugBEO. Budget and Economic Outlook. Washington, DC, Aug 22. CBO. 2012Jan31. Historical budget data. Washington, DC, Jan 31. CBO. 2012NovCDR. Choices for deficit reduction. Washington, DC. Nov. CBO. 2013HBDFeb5. Historical budget data—February 2013 baseline projections. Washington, DC, Congressional Budget Office, Feb 5. CBO. 2013HBDFeb5. Historical budget data—February 2013 baseline projections. Washington, DC, Congressional Budget Office, Feb 5. CBO (2013Sep11). CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb. CBO, The Budget and Economic Outlook 2014 to 2024. Washington, DC, Congressional Budget Office, Feb 2014.

Chart IIA1-1 of the Congressional Budget Office (CBO) provides the deficits of the US as percent of GDP from 1974 to 2013 followed on the right with the projections of the CBO in Feb 2014. Large deficits from 2009 to 2013, all above the average from 1974 to 2013, doubled the debt held by the public. Fiscal adjustment is now more challenging with rigidities in revenues and expenditures. The projections of the CBO in Feb 2014 for the years from 2014 to 2024 show lower deficits in proportion of GDP in the initial years that eventually become larger than the average in the second half of the ten-year window.

Chart IIA1-1, US, Total Federal Deficits and Surpluses

Source: Congressional Budget Office

The Budget and Economic Outlook 2014 to 2024. Washington, DC, Congressional Budget Office, Feb 2014.

http://www.cbo.gov/publication/45073

Table IIA1-8 provides baseline CBO projections of federal revenues, outlays, deficit and debt as percent of GDP. The adjustment depends on increasing revenues from 15.0 percent of GDP in 2011 and 16.7 percent in 2013 to 18.4 percent of GDP in 2024, which is above the 40-year average of 17.4 percent of GDP. Outlays fall from 23.4 percent of GDP in 2011 and 20.8 percent of GDP in 2013 to 22.4 percent of GDP in 2024. The last row of Table IIA1-8 provides the CBO estimates of averages for 1973 to 2012 of 17.4 percent for revenues/GDP, 20.4 percent for outlays/GDP and 38.0 percent for debt/GDP. The debt/GDP ratio increases to 79.2 percent of GDP. The United States faces tough adjustment of its fiscal accounts. There is an additional source of pressure on financing the current account deficit of the balance of payments (http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html).

Table IIA1-8, US, Baseline CBO Projections of Federal Government Revenues, Outlays, Deficit and Debt as Percent of GDP

	Revenues % GDP	Outlays % GDP	Deficit % GDP	Debt GDP
2011	15.0	23.4	-8.4	65.8
2012	15.2	22.0	-6.8	70.1
2013	16.7	20.8	-4.1	72.1
2014	17.5	20.5	-3.0	73.6
2015	18.2	20.9	-2.6	73.2
2016	18.2	21.1	-2.8	72.6
2017	18.1	21.0	-2.9	72.3
2018	18.0	21.1	-3.1	72.6
2019	18.0	21.4	-3.4	73.3
2020	18.0	21.7	-3.7	74.2
2021	18.1	21.9	-3.8	75.3
2022	18.1	22.3	-4.2	76.8
2023	18.2	22.3	-4.1	78.0
2024	18.4	22.4	-4.0	79.2
Total 2015-2019	18.1	21.1	-3.0	NA
Total 2015-2024	18.1	21.7	-3.5	NA
Average 1973-2012	17.4	20.4	-3.0	38.0

Source: CBO (2012AugBEO). CBO (2012NovCDR). CBO (2013BEOFeb5). CBO 2013HBDFeb5), CBO (2013Sep11), CBO (2013Aug12Av). Kim Kowaleski and Amber Marcellino. CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb. CBO, The Budget and Economic Outlook 2014 to 2024. Washington, DC, Congressional Budget Office, Feb 2014.

Chart IIA1-2 of the Congressional Budget Office (CBO) provides the actual federal debt as percent of GDP from 1940 to 2013 and the projected path by the CBO from 2014 to 2024. The federal debt exceeded 100 percent of GDP because of the war effort during World War II. Adjustment was swift and continuous during rapid economic growth in large part because of less rigid structures of expenditures and revenues. The jump of the federal debt from 35.1 percent of GDP in 2007 to 72.1 percent of GDP in 2013 with CBO projection of 79.2 percent of GDP in 2024 poses a major challenge of fiscal adjustment.

Chart IIA1-2, US, Federal Debt Held by the Public

Source: Congressional Budget Office

The Budget and Economic Outlook 2014 to 2024. Washington, DC, Congressional Budget Office, Feb 2014.

http://www.cbo.gov/publication/45073

ESVI United States Industrial Production. Industrial production decreased 0.3 percent in Jan 2014 after increasing 0.3 percent in Dec 2013 and increasing 0.7 percent in Nov 2013, as shown in Table I-1, with all data seasonally adjusted. The report of the Board of Governors of the Federal Reserve System states (http://www.federalreserve.gov/releases/g17/Current/default.htm):

“Industrial production decreased 0.3 percent in January after having risen 0.3 percent in December. In January, manufacturing output fell 0.8 percent, partly because of the severe weather that curtailed production in some regions of the country. Additionally, manufacturing production is now reported to have been lower in the fourth quarter; the index is now estimated to have advanced at an annual rate of 4.6 percent in the fourth quarter rather than 6.2 percent. The output of utilities rose 4.1 percent in January, as demand for heating was boosted by unseasonably cold temperatures. The production at mines declined 0.9 percent following a gain of 1.8 percent in December. At 101.0 percent of its 2007 average, total industrial production in January was 2.9 percent above its level of a year earlier. The capacity utilization rate for total industry decreased in January to 78.5 percent, a rate that is 1.6 percentage points below its long-run (1972–2013) average.”

In the six months ending in Jan 2014, United States national industrial production accumulated increase of 2.1 percent at the annual equivalent rate of 4.3 percent, which is higher than growth of 2.9 percent in the 12 months ending in Jan 2014. Excluding growth of -0.3 percent in Jan 2014, growth in the remaining five months from Aug to Dec 2013 accumulated to 2.4 percent or 5.9 percent annual equivalent. Industrial production fell in one of the past six months. Business equipment accumulated growth of 0.6 percent in the six months from Aug 2013 to Jan 2014 at the annual equivalent rate of 1.2 percent, which is lower than growth of 2.4 percent in the 12 months ending in Jan 2014. The Fed analyzes capacity utilization of total industry in its report (http://www.federalreserve.gov/releases/g17/Current/default.htm): “The capacity utilization rate for total industry decreased in January to 78.5 percent, a rate that is 1.6 percentage points below its long-run (1972–2013) average.” United States industry apparently decelerated to a lower growth rate with possible acceleration in the past few months.

Table I-1, US, Industrial Production and Capacity Utilization, SA, ∆% 

2012-2013	Jan 14	Dec   13	Nov  13	Oct  13	Sep  13	Aug 13	Jan  14/ Jan  13
Total	-0.3	0.3	0.7	0.2	0.6	0.6	2.9
Market Groups
Final Products	-0.4	0.3	0.4	0.2	1.1	0.6	2.5
Consumer Goods	-0.5	0.6	0.7	0.3	1.0	0.5	2.7
Business Equipment	-0.1	-0.7	-0.4	0.1	1.1	0.6	2.4
Non Industrial Supplies	-0.3	-0.1	0.5	0.4	0.8	0.3	2.4
Construction	-1.0	-0.6	0.4	0.9	1.1	0.2	1.7
Materials	-0.3	0.5	1.0	0.1	0.2	0.5	3.4
Industry Groups
Manufacturing	-0.8	0.3	0.3	0.4	0.2	0.8	1.3
Mining	-0.9	1.8	0.9	-1.5	1.0	0.5	6.7
Utilities	4.1	-1.4	2.9	1.0	3.2	-1.0	9.3
Capacity	78.5	78.9	78.8	78.4	78.4	78.0	1.9

Sources: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/g17/Current/default.htm

Manufacturing decreased 0.8 percent in Jan 2014 after increasing 0.3 percent in Dec 2013 and increasing 0.3 percent in Nov 2013 seasonally adjusted, increasing 1.3 percent not seasonally adjusted in 12 months ending in Jan 2014, as shown in Table I-2. Manufacturing grew cumulatively 1.2 percent in the six months ending in Jan 2014 or at the annual equivalent rate of 2.4 percent. Excluding the decrease of 0.3 percent in Jan 2014, manufacturing accumulated growth of 2.0 percent from Aug 2013 to Dec 2013 or at the annual equivalent rate of 4.9 percent. Table I-2 provides a longer perspective of manufacturing in the US. There has been evident deceleration of manufacturing growth in the US from 2010 and the first three months of 2011 into more recent months as shown by 12 months rates of growth. Growth rates appeared to be increasing again closer to 5 percent in Apr-Jun 2012 but deteriorated. The rates of decline of manufacturing in 2009 are quite high with a drop of 18.2 percent in the 12 months ending in Apr 2009. Manufacturing recovered from this decline and led the recovery from the recession. Rates of growth appeared to be returning to the levels at 3 percent or higher in the annual rates before the recession but the pace of manufacturing fell steadily in the past six months with some strength at the margin. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 22, 2013 (http://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization. Measured from fourth quarter to fourth quarter, total IP is now reported to have increased 0.7 percentage point less in 2011 than was previously published. The revisions to IP for other years were smaller: Compared to the previous estimates, industrial production fell slightly less in 2008 and 2009 and increased slightly less in 2010 and 2012. At 97.7 percent of its 2007 average, the index in the fourth quarter of 2012 now stands 0.4 percent below its previous estimate. With these revisions, IP is still estimated to have advanced about 6 percent in 2010, the first full year following the trough in June 2009 of the most recent recession, but it is now estimated to have risen about 3 percent both in 2011 and in 2012. Since the trough of the recession, total IP has reversed about 90 percent of its peak-to-trough decline.”

The bottom part of Table I-2 shows decline of manufacturing by 21.9 from the peak in Jun 2007 to the trough in Apr 2009 and increase by 19.1 percent from the trough in Apr 2009 to Dec 2013. Manufacturing grew 17.2 percent from the trough in Apr 2009 to Jan 2014. Manufacturing output in Jan 2014 is 8.5 percent below the peak in Jun 2007.

Table I-2, US, Monhly and 12-Month Rates of Growth of Manufacturing ∆%

	Month SA ∆%	12-Month NSA ∆%
Jan 2014	-0.8	1.3
Dec 2013	0.3	2.0
Nov	0.3	2.7
Oct	0.4	3.8
Sep	0.2	2.6
Aug	0.8	2.6
Jul	-0.5	1.4
Jun	0.3	1.8
May	0.3	1.8
Apr	-0.3	2.2
Mar	-0.2	1.8
Feb	0.6	1.9
Jan	-0.1	2.4
Dec 2012	0.9	3.0
Nov	1.4	3.3
Oct	-0.4	2.1
Sep	0.1	3.1
Aug	-0.7	3.5
Jul	0.2	4.0
Jun	0.3	5.0
May	-0.3	4.8
Apr	0.6	5.1
Mar	-0.5	3.9
Feb	0.6	5.3
Jan	1.0	4.2
Dec 2011	1.0	3.8
Nov	0.0	3.2
Oct	0.6	3.1
Sep	0.4	3.0
Aug	0.4	2.4
Jul	0.7	2.5
Jun	0.1	2.1
May	0.3	1.9
Apr	-0.7	3.1
Mar	0.7	4.9
Feb	0.0	5.4
Jan	0.2	5.6
Dec 2010	0.6	6.2
Nov	0.2	5.3
Oct	0.1	6.6
Sep	0.1	7.0
Aug	0.1	7.4
Jul	0.7	7.8
Jun	0.0	9.3
May	1.4	8.9
Apr	0.9	7.1
Mar	1.3	4.9
Feb	0.0	1.3
Jan	1.0	1.2
Dec 2009	0.0	-3.1
Nov	1.1	-6.1
Oct	0.1	-9.1
Sep	0.8	-10.6
Aug	1.1	-13.6
Jul	1.2	-15.2
Jun	-0.3	-17.6
May	-1.1	-17.6
Apr	-0.8	-18.2
Mar	-1.9	-17.3
Feb	-0.2	-16.1
Jan	-2.9	-16.4
Dec 2008	-3.4	-14.0
Nov	-2.2	-11.3
Oct	-0.6	-9.0
Sep	-3.4	-8.6
Aug	-1.3	-5.1
Jul	-1.1	-3.5
Jun	-0.5	-3.1
May	-0.5	-2.4
Apr	-1.1	-1.1
Mar	-0.3	-0.5
Feb	-0.6	0.9
Jan	-0.4	2.3
Dec 2007	0.2	2.0
Nov	0.5	3.4
Oct	-0.4	2.8
Sep	0.5	3.0
Aug	-0.4	2.6
Jul	0.1	3.4
Jun	0.3	2.9
May	-0.1	3.1
Apr	0.7	3.6
Mar	0.7	2.4
Feb	0.4	1.6
Jan	-0.5	1.3
Dec 2006		2.7
Dec 2005		3.4
Dec 2004		4.0
Dec 2003		1.7
Dec 2002		2.4
Dec 2001		-5.5
Dec 2000		0.4
Dec 1999		5.4
Average ∆% Dec 1986-Dec 2013		2.3
Average ∆% Dec 1986-Dec 2012		2.3
Average ∆% Dec 1986-Dec 1999		4.3
Average ∆% Dec 1999-Dec 2006		1.3
Average ∆% Dec 1999-Dec 2013		0.5
∆% Peak 103.0005 in 06/2007 to 95.8087 in 12/2013		-7.0
∆% Peak 103.0005 in 06/2007 to Trough 80.4617 in 4/2009		-21.9
∆% Trough  80.4617 in 04/2009 to 95.8087 in 12/2013		19.1
∆% Trough  80.4617 in 04/2009 to 94.2907 in 12/2013		17.2
∆% Peak 103.0005 on 06/2007 to 94.2907 in 1/2014		-8.5

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/g17/current/default.htm

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