CMP Associates Regulation Blog: Risks of Zero Interest Rates, World Inflation Waves, Recovery without Hiring, World Economic Slowdown and Global Recession Risk: Part I

Risks of Zero Interest Rates, World Inflation Waves, Recovery without Hiring, World Economic Slowdown and Global Recession Risk

Carlos M. Pelaez

Executive Summary

I World Inflation Waves

IA Appendix: Transmission of Unconventional Monetary Policy

IA1 Theory

IA2 Policy

IA3 Evidence

IA4 Unwinding Strategy

IB United States Inflation

IC Long-term US Inflation

ID Current US Inflation

IE Theory and Reality of Economic History and Monetary Policy Based on Fear of Deflation

II Recovery without Hiring

IIA Hiring Collapse

IIB Labor Underutilization

IIC Ten Million Fewer Full-time Job

IID Youth and Middle-Age Unemployment

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 World Inflation Waves

ESIII Recovery without Hiring

ESIV Ten Million Fewer Full-time Jobs

ESV Youth Unemployment and Middle-Aged Unemployment

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

Economic risks include the following:

China’s Economic Growth. China is lowering its growth target to 7.5 percent per year. China’s GDP growth decelerated significantly from annual equivalent 10.8 percent in IIQ2011 to 7.4 percent in IVQ2011 and 5.7 percent in IQ2012, rebounding to 9.1 percent in IIQ2012, 8.2 percent in IIIQ2012 and 7.8 percent in IVQ2012. Annual equivalent growth in IQ2013 fell to 6.1 percent and to 7.8 percent in IIQ2013, rebounding to 9.1 percent in IIIQ2013 (http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/07/tapering-quantitative-easing-policy-and_7005.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/01/recovery-without-hiring-world-inflation.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html).
United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 28.9 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically low hiring and declining/stagnating real wages.
Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
World Inflation Waves. Inflation continues in repetitive waves globally (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-world-inflation.htm).

A list of financial uncertainties includes:

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

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

The Federal Open Market Committee (FOMC) lowered the target of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85). Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment. The exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV). The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever-increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4). 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 to 5.25 percent in Jun 2006 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 $2489 billion, or $2.5 trillion bank reserves (http://www.federalreserve.gov/releases/h41/current/h41.htm#h41tab1), would cause Himalayan increase in interest rates that would cause 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 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.

Chart VIII-1, Fed Funds Rate and Yields of Ten-year Treasury Constant Maturity and Baa Seasoned Corporate Bond, Jan 2, 2001 to Nov 21, 2013

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

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 States, Vol. (I) (2008a), 78-100). Frederick R. Macaulay (1938) introduced the concept of duration in contrast with maturity for analyzing bonds. Duration is the sensitivity of bond prices to changes in yields. In economic jargon, duration is the yield elasticity of bond price to changes in yield, or the percentage change in price after a percentage change in yield, typically expressed as the change in price resulting from change of 100 basis points in yield. The mathematical formula is the negative of the yield elasticity of the bond price or –[dB/d(1+y)]((1+y)/B), where d is the derivative operator of calculus, B the bond price, y the yield and the elasticity does not have dimension (Hallerbach 2001). The duration trap of unconventional monetary policy is that duration is higher the lower the coupon and higher the lower the yield, other things being constant. Coupons and yields are historically low because of unconventional monetary policy. Duration dumping during a rate increase may trigger the same crossfire selling of high duration positions that magnified the credit crisis. Traders reduced positions because capital losses in one segment, such as mortgage-backed securities, triggered haircuts and margin increases that reduced capital available for positioning in all segments, causing fire sales in multiple segments (Brunnermeier and Pedersen 2009; see Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 217-24). Financial markets are currently experiencing fear of duration resulting from the debate within and outside the Fed on tapering quantitative easing. Table VIII-2 provides the yield curve of Treasury securities on Nov 22, 2013, Sep 5, 2013, May 1, 2013, Nov 21, 2012 and Nov 22, 2006. There is ongoing steepening of the yield curve for longer maturities, which are also the ones with highest duration. The 10-year yield increased from 1.45 percent on Jul 26, 2012 to 2.98 percent on Sep 5, 2013, as measured by the United States Treasury. Assume that a bond with maturity in 10 years were issued on Sep 5, 2013 at par or price of 100 with coupon of 1.45 percent. The price of that bond would be 86.8530 with instantaneous increase of the yield to 2.98 percent for loss of 13.1 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 Nov 22, 2013 would jump instantaneously from yield of 2.75 percent on Nov 22, 2013 to 4.57 percent as occurred on Nov 22, 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 85.5215 after an instantaneous increase of the yield to 4.57 percent. The price loss would be 14.5 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

	11/22/13	9/05/13	5/01/13	11/21/12	11/22/06
1 M	0.02	0.03	0.03	0.17	5.25
3 M	0.07	0.02	0.06	0.10	5.05
6 M	0.10	0.06	0.08	0.14	5.15
1 Y	0.12	0.16	0.11	0.17	5.01
2 Y	0.31	0.52	0.20	0.27	4.74
3 Y	0.57	0.97	0.30	0.37	4.63
5 Y	1.37	1.85	0.65	0.69	4.57
7 Y	2.10	2.45	1.07	1.11	4.57
10 Y	2.75	2.98	1.66	1.69	4.57
20 Y	3.54	3.64	2.44	2.42	4.76
30 Y	3.84	3.88	2.83	2.83	4.65

Source: United States Treasury

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

Interest rate risk is increasing in the US. Chart VI-13 of the Board of Governors provides the conventional mortgage rate for a fixed-rate 30-year mortgage. The rate stood at 5.87 percent on Jan 8, 2004, increasing to 6.79 percent on Jul 6, 2006. The rate bottomed at 3.35 percent on May 2, 2013. Fear of duration risk in longer maturities such as mortgage-backed securities caused continuing increases in the conventional mortgage rate that rose to 4.51 percent on Jul 11, 2013, 4.58 percent on Aug 22, 2013 and 4.22 percent on Nov 21, 2013, which is the last data point in Chart VI-13.

Chart VI-13, US, Conventional Mortgage Rate, Jan 8, 2004 to Nov 21, 2013

Source: Board of Governors of the Federal Reserve System

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

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

(1 + i_r) = (1 + i_n)/(1 + π^e) (1)

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

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

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

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

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

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

Current focus is on tapering quantitative easing by the Federal Open Market Committee (FOMC). There is sharp distinction between the two measures of unconventional monetary policy: (1) fixing of the overnight rate of fed funds at 0 to ¼ percent; and (2) outright purchase of Treasury and agency securities and mortgage-backed securities for the balance sheet of the Federal Reserve. Market are overreacting to the so-called “paring” of outright purchases of $85 billion of securities per month for the balance sheet of the Fed. 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 Oct 30, 2013 (http://www.federalreserve.gov/newsevents/press/monetary/20131030a.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. In particular, the Committee decided to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that this exceptionally low range for the federal funds rate will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee's 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored” (emphasis added).

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

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.”

W = Y/r (10

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

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

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

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

The key policy is maintaining fed funds rate between 0 and ¼ percent. An increase in fed funds rates could cause flight out of risk financial markets worldwide. There is no exit from this policy without major financial market repercussions. Indefinite financial repression induces carry trades with high leverage, risks and illiquidity. A competing event is the high level of valuations of risk financial assets (http://cmpassocregulationblog.blogspot.com/2013/01/peaking-valuation-of-risk-financial.html). Matt Jarzemsky, writing on “Dow industrials set record,” on Mar 5, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324156204578275560657416332.html), analyzes that the DJIA broke the closing high of 14,164.53 set on Oct 9, 2007, and subsequently also broke the intraday high of 14,198.10 reached on Oct 11, 2007. The DJIA closed at 16,064.77 on Fri Nov 22, 2013, which is higher by 13.4 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 13.1 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 65.8 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Nov 22, 2013; S&P 500 has gained 76.5 percent and DAX 62.6 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 11/22/13” 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 7.8 percent below the trough. Japan’s Nikkei Average is 74.3 percent above the trough. DJ Asia Pacific TSM is 26.1 percent above the trough. Dow Global is 43.3 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 25.8 percent above the trough. NYSE Financial Index is 48.0 percent above the trough. DJ UBS Commodities is 0.1 percent below the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 62.6 percent above the trough. Japan’s Nikkei Average is 74.3 percent above the trough on Aug 31, 2010 and 35.0 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 15,381.72 on Fri Nov 22, 2013 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 50.0 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 13.7 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 11/22/13” in Table VI-4 shows increase of 2.8 percent in the week for China’s Shanghai Composite. DJ Asia Pacific decreased 0.4 percent. NYSE Financial increased 0.9 percent in the week. DJ UBS Commodities increased 0.5 percent. Dow Global increased 0.5 percent in the week of Nov 22, 2013. The DJIA increased 0.6 percent and S&P 500 increased 0.4 percent. DAX of Germany increased 0.5 percent. STOXX 50 decreased 0.1 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 11/22/13” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Nov 22, 2013. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 11/22/13” but also relative to the peak in column “∆% Peak to 11/22/13.” There are now several equity indexes above the peak in Table VI-4: DJIA 43.4 percent, S&P 500 48.3 percent, DAX 45.6 percent, Dow Global 16.9 percent, DJ Asia Pacific 10.4 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 17.9 percent, Nikkei Average 35.0 percent and STOXX 50 6.6 percent. There is only one equity index below the peak: Shanghai Composite by 30.6 percent. DJ UBS Commodities Index is now 14.6 percent below the peak. The US dollar strengthened 10.4 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010. Alexandra Scaggs, writing on “Tepid profits, roaring stocks,” on May 16, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323398204578487460105747412.html), analyzes stabilization of earnings growth: 70 percent of 458 reporting companies in the S&P 500 stock index reported earnings above forecasts but sales fell 0.2 percent relative to forecasts of increase of 0.5 percent. Paul Vigna, writing on “Earnings are a margin story but for how long,” on May 17, 2013, published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2013/05/17/earnings-are-a-margin-story-but-for-how-long/), analyzes that corporate profits increase with stagnating sales while companies manage costs tightly. More than 90 percent of S&P components reported moderate increase of earnings of 3.7 percent in IQ2013 relative to IQ2012 with decline of sales of 0.2 percent. Earnings and sales have been in declining trend. In IVQ2009, growth of earnings reached 104 percent and sales jumped 13 percent. Net margins reached 8.92 percent in IQ2013, which is almost the same at 8.95 percent in IIIQ2006. Operating margins are 9.58 percent. There is concern by market participants that reversion of margins to the mean could exert pressure on earnings unless there is more accelerated growth of sales. Vigna (op. cit.) finds sales growth limited by weak economic growth. Kate Linebaugh, writing on “Falling revenue dings stocks,” on Oct 20, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444592704578066933466076070.html?mod=WSJPRO_hpp_LEFTTopStories), identifies a key financial vulnerability: falling revenues across markets for United States reporting companies. Global economic slowdown is reducing corporate sales and squeezing corporate strategies. Linebaugh quotes data from Thomson Reuters that 100 companies of the S&P 500 index have reported declining revenue only 1 percent higher in Jun-Sep 2012 relative to Jun-Sep 2011 but about 60 percent of the companies are reporting lower sales than expected by analysts with expectation that revenue for the S&P 500 will be lower in Jun-Sep 2012 for the entities represented in the index. Results of US companies are likely repeated worldwide. Future company cash flows derive from investment projects. In IQ1980, gross private domestic investment in the US was $951.6 billion of 2009 dollars, growing to $1,143.0 billion in IVQ1986 or 20.1 percent. Real gross private domestic investment in the US decreased 3.1 percent from $2,605.2 billion of 2009 dollars in IVQ2007 to $2,524.9 billion in IIQ2013. Real private fixed investment fell 4.9 percent from $2,586.3 billion of 2009 dollars in IVQ2007 to $2,458.4 billion in IIQ2013. Growth of real private investment in is mediocre for all but four quarters from IIQ2011 to IQ2012 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/09/increasing-interest-rate-risk.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. 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. 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. 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 of US corporations swelled 263.4 percent from $107.7 billion IQ2007 to $391.4 billion in IIQ2013 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 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_3rd.pdf). Uncertainty originating in fiscal, regulatory and monetary policy causes wide swings in expectations and decisions by the private sector with adverse effects on investment, real economic activity and employment. The investment decision of US business is fractured.

It may be quite painful to exit QE→∞ or use of the balance sheet of the central together with zero interest rates forever. 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 11/22/ /13	∆% Week 11/22/13	∆% Trough to 11/22/ 13
DJIA	4/26/ 10	7/2/10	-13.6	43.4	0.6	65.8
S&P 500	4/23/ 10	7/20/ 10	-16.0	48.3	0.4	76.5
NYSE Finance	4/15/ 10	7/2/10	-20.3	17.9	0.9	48.0
Dow Global	4/15/ 10	7/2/10	-18.4	16.9	0.5	43.3
Asia Pacific	4/15/ 10	7/2/10	-12.5	10.4	-0.4	26.1
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	35.0	1.4	74.3
China Shang.	4/15/ 10	7/02 /10	-24.7	-30.6	2.8	-7.8
STOXX 50	4/15/10	7/2/10	-15.3	6.6	-0.1	25.8
DAX	4/26/ 10	5/25/ 10	-10.5	45.6	0.5	62.6
Dollar Euro	11/25 2009	6/7 2010	21.2	10.4	-0.4	-13.7
DJ UBS Comm.	1/6/ 10	7/2/10	-14.5	-14.6	0.5	-0.1
10-Year T Note	4/5/ 10	4/6/10	3.986	2.784	2.746

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 World Inflation Waves. Table IA-1 provides annual equivalent rates of inflation for producer price indexes followed in this blog of countries and regions that account for close to three quarters of world output. The behavior of the US producer price index in 2011 and into 2012-2013 shows neatly multiple waves. (1) In Jan-Apr 2011, without risk aversion, US producer prices rose at the annual equivalent rate of 10.0 percent. (2) After risk aversion, producer prices increased in the US at the annual equivalent rate of 1.8 percent in May-Jun 2011. (3) From Jul to Sep 2011, under alternating episodes of risk aversion, producer prices increased at the annual equivalent rate of 4.9 percent. (4) Under the pressure of risk aversion because of the European debt crisis, US producer prices increased at the annual equivalent rate of 0.6 percent in Oct-Nov 2011. (5) From Dec 2011 to Jan 2012, US producer were flat at the annual equivalent rate of 0.0 percent. (6) Inflation of producer prices returned with 2.4 percent annual equivalent in Feb-Mar 2012. (7) With return of risk aversion from the European debt crisis, producer prices fell at the annual equivalent rate of 4.7 percent in Apr-May 2012. (8) New positions in commodity futures even with continuing risk aversion caused annual equivalent inflation of 3.0 percent in Jun-Jul 2012. (9) Relaxed risk aversion because of announcement of sovereign bond buying by the European Central Bank induced carry trades that resulted in annual equivalent producer price inflation in the US of 12.7 percent in Aug-Sep 2012. (10) Renewed risk aversion caused unwinding of carry trades of zero interest rates to commodity futures exposures with annual equivalent inflation of minus 3.2 percent in Oct-Dec 2012. (10) In Jan-Feb 2013, producer prices rose at the annual equivalent rate of 5.5 percent with more relaxed risk aversion at the margin. (11) Return of risk aversion resulted in annual equivalent inflation of minus 7.5 percent in Mar-Apr 2013 with worldwide portfolio reallocation toward equities and high-yield bonds and away from commodity exposures. (12) Inflation of producer prices returned at 4.9 percent in annual equivalent in May-Aug 2013. (13) Continuing reallocation of investment portfolios away from commodities into equities is causing downward pressure on prices. In Sep-Oct 2013, the US producer price index fell at the annual equivalent rate of 1.8 percent. Resolution of the European debt crisis if there is not an unfavorable growth event with political development in China would result in jumps of valuations of risk financial assets. Increases in commodity prices would cause the same high producer price inflation experienced in Jan-Apr 2011 and Aug-Sep 2012. An episode of exploding commodity prices could ignite inflationary expectations that would result in an inflation phenomenon of costly resolution. There are nine producer-price indexes in Table IA-1 for seven countries (two for the UK) and one region (euro area) showing very similar behavior. Zero interest rates without risk aversion cause increases in commodity prices that in turn increase input prices at a faster pace than output prices. Producer price inflation rose at very high rates during the first part of 2011 for the US, Japan, China, Euro Area, Germany, France, Italy and the UK when risk aversion was contained. With the increase in risk aversion in May and Jun 2011, inflation moderated because carry trades were unwound. Producer price inflation returned after Jul 2011, with alternating bouts of risk aversion. In the final months of the year producer price inflation collapsed because of the disincentive to exposures in commodity futures resulting from fears of resolution of the European debt crisis. There is renewed worldwide inflation in the early part of 2012 with subsequent collapse because of another round of sharp risk aversion and relative portfolio reallocation away from commodities and into equities and high-yield bonds. Sharp worldwide jump in producer prices occurred recently because of the combination of zero interest rates forever or QE→∞ with temporarily relaxed risk aversion. Producer prices were moderating or falling in the final months of 2012 because of renewed risk aversion that causes unwinding of carry trades from zero interest rates to commodity futures exposures. In the first months of 2013, new carry trades caused higher worldwide inflation. Lower inflation recently originates in portfolio reallocations away from commodity exposures into equities. Unconventional monetary policy fails in stimulating the overall real economy, merely introducing undesirable instability because monetary authorities cannot control allocation of floods of money at zero interest rates to carry trades into risk financial assets. The economy is constrained in a suboptimal allocation of resources that is perpetuated along a continuum of short-term periods. The result is long-term or dynamic inefficiency in the form of a trajectory of economic activity that is lower than what would be attained with rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html).

Table IA-1, Annual Equivalent Rates of Producer Price Indexes

INDEX 2011-2013	AE ∆%
US Producer Price Index
AE ∆% Sep-Oct 2013	-1.8
AE ∆% May-Aug 2013	4.9
AE ∆% Mar-Apr 2013	-7.5
AE ∆% Jan-Feb 2013	5.5
AE ∆% Oct-Dec 2012	-3.2
AE ∆% Aug-Sep 2012	12.7
AE ∆% Jun-Jul 2012	3.0
AE ∆% Apr-May 2012	-4.7
AE ∆% Feb-Mar 2012	2.4
AE ∆% Dec 2011-Jan-2012	0.0
AE ∆% Oct-Nov 2011	0.6
AE ∆% Jul-Sep 2011	4.9
AE ∆% May-Jun 2011	1.8
AE ∆% Jan-Apr 2011	10.0
Japan Corporate Goods Price Index
AE ∆% Oct 2013	-1.2
AE ∆% Dec 2012-Sep 2013	3.3
AE ∆% Oct-Nov 2012	-3.0
AE ∆% Aug-Sep 2012	2.4
AE ∆% May-Jul 2012	-5.5
AE ∆% Feb-Apr 2012	2.0
AE ∆% Dec 2011-Jan 2012	-0.6
AE ∆% Jul-Nov 2011	-2.1
AE ∆% May-Jun 2011	-1.2
AE ∆% Jan-Apr 2011	5.8
China Producer Price Index
AE ∆% Aug-Oct 2013	1.2
AE ∆% Mar-Jul 2013	-4.9
AE ∆% Jan-Feb 2013	2.4
AE ∆% Nov-Dec 2012	-1.2
AE ∆% Oct 2012	2.4
AE ∆% May-Sep 2012	-5.8
AE ∆% Feb-Apr 2012	2.4
AE ∆% Dec 2011-Jan 2012	-2.4
AE ∆% Jul-Nov 2011	-3.1
AE ∆% Jan-Jun 2011	6.4
Euro Zone Industrial Producer Prices
AE ∆% Jul-Sep 2013	1.2
AE ∆% Mar-Jun 2013	-3.5
AE ∆% Jan-Feb 2013	2.4
AE ∆% Nov-Dec 2012	-2.4
AE ∆% Sep-Oct 2012	0.6
AE ∆% Jul-Aug 2012	6.8
AE ∆% Apr-Jun 2012	-2.4
AE ∆% Jan-Mar 2012	7.9
AE ∆% Oct-Dec 2011	0.4
AE ∆% Jul-Sep 2011	2.4
AE ∆% May-Jun 2011	0.0
AE ∆% Jan-Apr 2011	11.3
Germany Producer Price Index
AE ∆% Oct	-2.4 NSA –2.4 SA
AE ∆% Sep	3.7 NSA 0.0 SA
AE ∆% May-Aug 2013	-1.8 NSA –0.3 SA
AE ∆% Feb-Apr 2013	-2.4 NSA –3.5 SA
AE ∆% Jan 2013	7.4 NSA 1.2 SA
AE ∆% Oct-Dec 2012	-0.8 NSA 1.2 SA
AE ∆% Aug-Sep 2012	4.3 NSA 3.0 SA
AE ∆% May-Jul 2012	-2.8 NSA –0.4 SA
AE ∆% Feb-Apr 2012	4.9 NSA 2.0 SA
AE ∆% Dec 2011-Jan 2012	0.0 NSA –0.6 SA
AE ∆% Oct-Nov 2011	0.6 NSA 1.8 SA
AE ∆% Jul-Sep 2011	2.4 NSA 3.2 SA
AE ∆% May-Jun 2011	0.6 NSA 3.7 SA
AE ∆% Jan-Apr 2011	10.4 NSA 6.2 SA
France Producer Price Index for the French Market
AE ∆% Jul-Sep 2013	4.5
AE ∆% Apr-Jun 2013	-11.4
AE ∆% Jan-Mar 2013	4.9
AE ∆% Nov-Dec 2012	-4.1
AE ∆% Jul-Oct 2012	7.4
AE ∆% Apr-Jun 2012	-4.3
AE ∆% Jan-Mar 2012	6.2
AE ∆% Oct-Dec 2011	2.8
AE ∆% Jul-Sep 2011	3.7
AE ∆% May-Jun 2011	-1.8
AE ∆% Jan-Apr 2011	10.4
Italy Producer Price Index
AE ∆% Jun-Sep 2013	0.3
AE ∆% Apr-May 2013	-3.5
AE ∆% Feb-Mar 2013	1.2
AE ∆% Sep 2012-Jan 2013	-5.2
AE ∆% Jul-Aug 2012	9.4
AE ∆% May-Jun 2012	-0.6
AE ∆% Mar-Apr 2012	6.8
AE ∆% Jan-Feb 2012	8.1
AE ∆% Oct-Dec 2011	2.0
AE ∆% Jul-Sep 2011	4.9
AE ∆% May-Jun 2011	1.8
AE ∆% Jan-April 2011	10.7
UK Output Prices
AE ∆% Sep-Oct 2013	4.9
AE ∆% Jun-Aug 2013	2.0
AE ∆% Apr-May 2013	-0.6
AE ∆% Jan-Mar 2013	4.9
AE ∆% Nov-Dec 2012	-2.4
AE ∆% Jul-Oct 2012	4.1
AE ∆% May-Jun 2012	-3.5
AE ∆% Feb-Apr 2012	5.3
AE ∆% Nov 2011-Jan-2012	1.2
AE ∆% May-Oct 2011	1.6
AE ∆% Jan-Apr 2011	10.0
UK Input Prices
AE ∆% Aug-Oct 2013	-9.9
AE ∆% Jul 2013	18.2
AE ∆% Mar-Jun 2013	-9.5
AE ∆% Jan-Feb 2013	24.6
AE ∆% Sep-Dec 2012	3.0
AE ∆% Aug 2012	23.9
AE ∆% Apr-Jul 2012	-16.1
AE ∆% Jan-Mar 2012	14.9
AE ∆% Nov-Dec 2011	0.0
AE ∆% May-Oct 2011	-1.3
AE ∆% Jan-Apr 2011	30.6
AE ∆% Oct-Dec 2010	31.8

AE: Annual Equivalent

Sources: http://www.bls.gov/cpi/ http://www.boj.or.jp/en/

http://www.stats.gov.cn/enGliSH/

http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database

https://www.destatis.de/EN/Homepage.html

http://www.insee.fr/en/default.asp

http://www.istat.it/en/

http://www.ons.gov.uk/ons/index.html

Similar world inflation waves are in the behavior of consumer price indexes of six countries and the euro zone in Table IA-2. US consumer price inflation shows similar waves. (1) Under risk appetite in Jan-Apr 2011, consumer prices increased at the annual equivalent rate of 4.6 percent. (2) Risk aversion caused the collapse of inflation to annual equivalent 3.0 percent in May-Jun 2011. (3) Risk appetite drove the rate of consumer price inflation in the US to 3.3 percent in Jul-Sep 2011. (4) Gloomier views of carry trades caused the collapse of inflation in Oct-Nov 2011 to annual equivalent 0.6 percent. (5) Consumer price inflation resuscitated with increased risk appetite at annual equivalent of 1.2 percent in Dec 2011 to Jan 2012. (6) Consumer price inflation returned at 2.4 percent annual equivalent in Feb-Apr 2012. (7) Under renewed risk aversion, annual equivalent consumer price inflation in the US was 0.0 percent in May-Jul 2012. (8) Inflation jumped to annual equivalent 4.9 percent in Aug-Oct 2012. (9) Unwinding of carry trades caused negative annual equivalent inflation of 0.8 percent in Nov 2012-Jan 2013 but some countries experienced higher inflation in Dec 2012 and Jan 2013. (10) Inflation jumped again with annual equivalent inflation of 8.7 percent in Feb 2013 in a mood of relaxed risk aversion. (11) Inflation fell at 3.5 percent annual equivalent in Mar-Apr 2013. (12) Inflation rose at 2.7 percent in annual equivalent in May-Sep 2013. (3) Inflation fell at the annual equivalent rate of 1.2 percent in Oct 2013. Inflationary expectations can be triggered in one of these episodes of accelerating inflation because of commodity carry trades induced by unconventional monetary policy of zero interest rates in perpetuity or QE→∞ in almost continuous time. Alternating episodes of increase and decrease of inflation introduce uncertainty in household planning that frustrates consumption and home buying. Announcement of purchases of impaired sovereign bonds by the European Central Bank relaxed risk aversion that induced carry trades into commodity exposures, increasing prices of food, raw materials and energy. There is similar behavior in all the other consumer price indexes in Table IA-2. China’s CPI increased at annual equivalent 8.3 percent in Jan-Mar 2011, 2.0 percent in Apr-Jun, 2.9 percent in Jul-Nov and resuscitated at 5.8 percent annual equivalent in Dec 2011 to Mar 2012, declining to minus 3.9 percent in Apr-Jun 2012 but resuscitating at 4.1 percent in Jul-Sep 2012, declining to minus 1.2 percent in Oct 2012 and 0.0 percent in Oct-Nov 2012. High inflation in China at annual equivalent 5.5 percent in Nov-Dec 2012 is attributed to inclement winter weather that caused increases in food prices. Continuing pressure of food prices caused annual equivalent inflation of 12.2 percent in China in Dec 2012 to Feb 2013. Inflation in China fell at annual equivalent 10.3 percent in Mar 2013 and increased at annual equivalent 2.4 percent in Apr 2013. Adjustment to lower food prices caused annual equivalent inflation of minus 7.0 percent in May 2013 and minus 3.5 percent in annual equivalent in May-Jun 2013. Inflation in China returned at annual equivalent 4.6 percent in Jul-Oct 2013. The euro zone harmonized index of consumer prices (HICP) increased at annual equivalent 5.2 percent in Jan-Apr 2011, minus 2.4 percent in May-Jul 2011, 4.3 percent in Aug-Dec 2011, minus 3.0 percent in Dec 2011-Jan 2012 and then 9.6 percent in Feb-Apr 2012, falling to minus 2.8 percent annual equivalent in May-Jul 2012 but resuscitating at 5.3 percent in Aug-Oct 2012. The recent shock of risk aversion forced minus 2.4 percent annual equivalent in Nov 2012. As in several European countries, annual equivalent inflation jumped to 4.9 percent in the euro area in Dec 2012. The HICP price index fell at annual equivalent 11.4 percent in Jan 2013 and increased at 10.0 percent in Feb-Mar 2013. As in most countries and regions, euro zone inflation fell at the annual equivalent rate of 1.2 percent in Apr 2013. Prices in the euro zone rose at 1.2 percent in May-Jun 2013. Inflation in the euro zone fell at annual equivalent 5.8 percent in Jul 2013. Inflation returned in the euro zone at annual equivalent 3.7 percent in Aug-Sep 2013. Euro zone inflation fell at the annual equivalent rate of 1.2 percent in Oct 2013. The price indexes of the largest members of the euro zone, Germany, France and Italy, and the euro zone as a whole, exhibit the same inflation waves. The United Kingdom CPI increased at annual equivalent 6.5 percent in Jan-Apr 2011, falling to only 0.4 percent in May-Jul 2011 and then increasing at 4.6 percent in Aug-Nov 2011. UK consumer prices fell at 0.6 percent annual equivalent in Dec 2011 to Jan 2012 but increased at 6.2 percent annual equivalent from Feb to Apr 2012. In May-Jun 2012, with renewed risk aversion, UK consumer prices fell at the annual equivalent rate of minus 3.0 percent. Inflation returned in the UK at average annual equivalent of 4.5 percent in Jul-Dec 2012 with inflation in Oct 2012 caused mostly by increases of university tuition fees. Inflation returned at 4.5 percent annual equivalent in Jul-Dec 2012 and was higher in annual equivalent inflation of producer prices in the UK in Jul-Oct 2012 at 4.1 percent for output prices and 23.9 percent for input prices in Aug 2012 (see Table IA-1). Consumer prices in the UK fell at annual equivalent 5.8 percent in Jan 2013. Inflation returned in the UK with annual equivalent 4.3 percent in Feb-May 2013 and fell at 1.2 percent in Jun-Jul 2013. UK annual equivalent inflation returned at 3.7 percent in Aug-Oct 2013.

Table IA-2, Annual Equivalent Rates of Consumer Price Indexes

Index 2011-2013	AE ∆%
US Consumer Price Index
AE ∆% Oct 2013	-1.2
AE ∆% May-Sep 2013	2.7
AE ∆% Mar-Apr 2013	-3.5
AE ∆% Feb 2013	8.7
AE ∆% Nov 2012-Jan 2013	-0.8
AE ∆% Aug-Oct 2012	4.9
AE ∆% May-Jul 2012	0.0
AE ∆% Feb-Apr 2012	2.4
AE ∆% Dec 2011-Jan 2012	1.2
AE ∆% Oct-Nov 2011	0.6
AE ∆% Jul-Sep 2011	3.3
AE ∆% May-Jun 2011	3.0
AE ∆% Jan-Apr 2011	4.6
China Consumer Price Index
AE ∆% Jul-Oct 2013	4.6
AE ∆% May-Jun 2013	-3.5
AE ∆% Apr 2013	2.4
AE ∆% Mar 2013	-10.3
AE ∆% Dec 2012-Feb 2013	12.2
AE ∆% Oct-Nov 2012	0.0
AE ∆% Jul-Sep 2012	4.1
AE ∆% Apr-Jun 2012	-3.9
AE ∆% Dec 2011-Mar 2012	5.8
AE ∆% Jul-Nov 2011	2.9
AE ∆% Apr-Jun 2011	2.0
AE ∆% Jan-Mar 2011	8.3
Euro Zone Harmonized Index of Consumer Prices
AE ∆% Oct	-1.2
AE ∆% Aug-Sep 2013	3.7
AE ∆% Jul 2013	-5.8
AE ∆% May-Jun 2013	1.2
AE ∆% Apr 2013	-1.2
AE ∆% Feb-Mar 2013	10.0
AE ∆% Jan 2013	-11.4
AE ∆% Dec 2012	4.9
AE ∆% Nov 2012	-2.4
AE ∆% Aug-Oct 2012	5.3
AE ∆% May-Jul 2012	-2.8
AE ∆% Feb-Apr 2012	9.6
AE ∆% Dec 2011-Jan 2012	-3.0
AE ∆% Aug-Nov 2011	4.3
AE ∆% May-Jul 2011	-2.4
AE ∆% Jan-Apr 2011	5.2
Germany Consumer Price Index
AE ∆% Oct	-2.4 NSA 0.0 SA
AE ∆% Aug-Sep 2013	0.0 NSA 0.0 SA
AE ∆% May-Jul 2013	4.1 NSA 3.7 SA
AE ∆% Apr 2013	-5.8 NSA 0.0 SA
AE ∆% Feb-Mar 2013	6.8 NSA 1.2 SA
AE ∆% Jan 2013	-5.8 NSA 0.0 SA
AE ∆% Sep-Dec 2012	1.5 NSA 1.8 SA
AE ∆% Jul-Aug 2012	4.9 NSA 3.0 SA
AE ∆% May-Jun 2012	-1.2 NSA 0.6 SA
AE ∆% Feb-Apr 2012	4.5 NSA 2.4 SA
AE ∆% Dec 2011-Jan 2012	0.6 NSA 1.8 SA
AE ∆% Jul-Nov 2011	1.7 NSA 1.9 SA
AE ∆% May-Jun 2011	0.6 NSA 3.0 SA
AE ∆% Feb-Apr 2011	3.0 NSA 2.4 SA
France Consumer Price Index
AE ∆% Sep-Oct 2013	-1.8
AE ∆% Aug 2013	6.2
AE ∆% Jul 2013	-3.5
AE ∆% May-Jun 2013	1.8
AE ∆% Apr 2013	-1.2
AE ∆% Feb-Mar 2013	6.8
AE ∆% Nov 2012-Jan 2013	-1.6
AE ∆% Aug-Oct 2012	2.8
AE ∆% May-Jul 2012	-2.4
AE ∆% Feb-Apr 2012	5.3
AE ∆% Dec 2011-Jan 2012	0.0
AE ∆% Aug-Nov 2011	3.0
AE ∆% May-Jul 2011	-1.2
AE ∆% Jan-Apr 2011	4.3
Italy Consumer Price Index
AE ∆% Sep-Oct 2013	-3.0
AE ∆% Dec 2012-Aug 2013	2.0
AE ∆% Sep-Nov 2012	-0.8
AE ∆% Jul-Aug 2012	3.0
AE ∆% May-Jun 2012	1.2
AE ∆% Feb-Apr 2012	5.7
AE ∆% Dec 2011-Jan 2012	4.3
AE ∆% Oct-Nov 2011	3.0
AE ∆% Jul-Sep 2011	2.4
AE ∆% May-Jun 2011	1.2
AE ∆% Jan-Apr 2011	4.9
UK Consumer Price Index
AE ∆% Aug-Oct 2013	3.7
AE ∆% Jun-Jul 2013	-1.2
AE ∆% Feb-May 2013	4.3
AE ∆% Jan 2013	-5.8
AE ∆% Jul-Dec 2012	4.5
AE ∆% May-Jun 2012	-3.0
AE ∆% Feb-Apr 2012	6.2
AE ∆% Dec 2011-Jan 2012	-0.6
AE ∆% Aug-Nov 2011	4.6
AE ∆% May-Jul 2011	0.4
AE ∆% Jan-Apr 2011	6.5

AE: Annual Equivalent

Sources: http://www.bls.gov/cpi/

http://www.stats.gov.cn/enGliSH/

http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database

https://www.destatis.de/EN/Homepage.html

http://www.insee.fr/en/default.asp

ESIII 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/2013/09/twenty-eight-million-unemployed-or.html). 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. IIA1 Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IIA2 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 IIA3 Ten Million Fewer Full-time Jobs. IIA4 Youth and Middle-Age Unemployment provides the data on high unemployment of ages 16 to 24 years and of ages 45 years or over.

IIA1 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 2.3 percent on average in the cyclical expansion in the 17 quarters from IIIQ2009 to IIIQ2013. 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 http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf

http://bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_adv.pdf http://bea.gov/newsreleases/national/pi/2013/pdf/pi0613.pdf) and the first estimate of GDP for IIIQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.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/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html). 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 (ahttp://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html). As a result, there are 28.9 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html).Zero interest rates and quantitative easing have not provided the impulse for growth and were not required in past successful cyclical expansions.

Table I-1, US, Annual Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US 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 been 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.

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

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 Sep in the years from 2001 to 2013 in Table I-3. Hiring numbers are in thousands. There is meager recovery in HNF from 4045 thousand (or 4.0 million) in Sep 2009 to 4118 thousand in Sep 2010, 4461 thousand in Sep 2011, 4370 thousand in Sep 2012 and 4769 thousand in Sep 2013 for cumulative gain of 17.9 percent. HP rose from 3727 thousand in Sep 2009 to 3792 thousand in Sep 2010, 4106 in Sep 2011, 4005 thousand in Sep 2012 and 4381 in Sep 2013 for cumulative gain of 17.5 percent. HNF has fallen from 5674 in Sep 2005 to 4769 in Sep 2013 or by 15.9 percent. HP has fallen from 5215 in Sep 2005 to 4381 in Sep 2013 or by 16.0 percent. The civilian noninstitutional population of the US rose from 228.815 million in 2006 to 243.284 million in 2012 or by 14.469 million and the civilian labor force from 151.428 million in 2006 to 154.975 million in 2012 or by 3.547 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/). 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 Sep	5170	3.9	4716	4.3
2002 Sep	5028	3.9	4622	4.2
2003 Sep	4919	3.8	4548	4.2
2004 Sep	5282	4.0	4776	4.3
2005 Sep	5674	4.2	5215	4.6
2006 Sep	5541	4.1	4934	4.3
2007 Sep	5436	3.9	4880	4.2
2008 Sep	4584	3.4	4201	3.7
2009 Sep	4045	3.1	3727	3.5
2010 Sep	4118	3.2	3792	3.5
2011 Sep	4461	3.4	4106	3.7
2012 Sep	4370	3.3	4005	3.6
2013 Sep	4769	3.5	4381	3.8

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 4769 in Aug 2013. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Aug 2011 was 4187 thousand, increasing to revised 4489 thousand in Feb 2012, or 7.2 percent, moving to 4195 in Dec 2012 for cumulative increase of 0.5 percent from 4174 in Dec 2011 and 4585 in Sep 2013 for increase of 9.3 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.

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 3.4 in Sep 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 and 3.5 in Sep 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, increasing 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. 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 5215 in Sep 2005 to 4005 in Sep 2012 or 23.2 percent and declined to 4381 in Sep 2013 or lower by 16.0 percent relative to Sep 2005. Private hiring fell from 3635 in Dec 2006 to 2842 in Dec 2012 or 21.8 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 14.5 million or 6.3 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. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 17 quarters from IIIQ2009 to IIIQ2013. 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 http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf

http://bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_adv.pdf http://bea.gov/newsreleases/national/pi/2013/pdf/pi0613.pdf) and the first estimate of GDP for IIIQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.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/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html). 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 (ahttp://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html). As a result, there are 28.9 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html). Zero interest rates and quantitative easing have not provided the impulse for growth and were not required in past successful cyclical expansions. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

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 3.8 in Sep 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 3.8 in Sep 2013.

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

Source: Bureau of Labor Statistics

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

ESIV 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 9.101 million in Sep 2011 to 7.664 million in Mar 2012, seasonally adjusted, or decline of 1.437 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.607 million in Sep 2012 for increase of 564,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.286 million in Oct 2012 or by 321,000 again in one month, further declining to 8.138 million in Nov 2012 for another major one-month decline of 148,000 and 7.918 million in Dec 2012 or fewer 220,000 in just one month. The number employed part-time for economic reasons increased to 7.973 million in Jan 2013 or 55,000 more than in Dec 2012 and to 7,988 million in Feb 2013, declining to 7.904 million in May 2013 but increasing to 8.245 million in Jul 2013. The number employed part-time for economic reasons fell to 7.911 million in Aug 2013 for decline of 334.000 in one month from 8.245 million in Jul 2013. The number employed part-time for economic reasons increased 15,000 from 7.911 million in Aug 2013 to 7.926 million in Sep 2013. There is an increase of 243,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 95,000 from Aug 2012 to Nov 2012. The number employed full-time increased from 112.871 million in Oct 2011 to 115.145 million in Mar 2012 or 2.274 million but then fell to 114.300 million in May 2012 or 0.845 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.492 million in Aug 2012 to 115.469 million in Oct 2012 or increase of 0.977 million full-time jobs in two months and further to 115.918 million in Jan 2013 or increase of 1.426 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.841 in Feb 2013, increasing to 116.238 million in May 2013 and 115.998 million in Jun 2013. Then number of full-time jobs increased to 116.090 million in Jul 2013, 116.208 million in Aug 2013 and 116.899 million in Sep 2013. The number of full-time jobs fell to 116.276 million in Oct 2013. Benchmark and seasonality-factors adjustments at the turn of every year could affect comparability of labor market indicators (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 1.0151 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 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. 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 Oct 2013 is 116.798 million, which is lower by 6.421 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 246.381 million in Oct 2013 or by 14.423 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 6.421 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 130.828 million full-time jobs with population of 246.381 million in Oct 2013 or 14.030 million fewer full-time jobs in actual 116.798 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 2.3 percent on average in the cyclical expansion in the 17 quarters from IIIQ2009 to IIIQ2013. 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 http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.pdf

http://bea.gov/newsreleases/national/gdp/2013/pdf/gdp2q13_adv.pdf http://bea.gov/newsreleases/national/pi/2013/pdf/pi0613.pdf) and the first estimate of GDP for IIIQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_adv.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/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html). 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 (ahttp://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html). As a result, there are 28.9 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html and earlier http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html). Zero interest rates and quantitative easing have not provided the impulse for growth and were not required in past successful cyclical expansions. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

Table I-9, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Oct 2013	8050	116.276
Sep 2013	7,926	116.899
Aug 2013	7,911	116.208
Jul 2013	8,245	116.090
Jun 2013	8,226	115.998
May 2013	7,904	116.238
Apr 2013	7,916	116.053
Mar 2013	7,638	115.903
Feb 2013	7,988	115.841
Jan 2013	7,973	115.918
Dec 2012	7,918	115.868
Nov 2012	8,138	115.665
Oct 2012	8,286	115.469
Sep 2012	8,607	115.259
Aug 2012	8,043	114.492
Jul 2012	8,245	114.478
Jun 2012	8,210	114.606
May 2012	8,116	114.300
Apr 2012	7,896	114.441
Mar 2012	7,664	115.145
Feb 2012	8,127	114.263
Jan 2012	8,220	113.833
Dec 2011	8,168	113.820
Nov 2011	8,436	113.217
Oct 2011	8,726	112.871
Sep 2011	9,101	112.541
Aug 2011	8,816	112.555
Jul 2011	8,416	112.141
Not Seasonally Adjusted
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.