Recovery without Hiring, Tapering Quantitative Easing Policy and Peaking Valuations of Risk Financial Assets, IMF View of World Economy and Finance, Collapse of United States Dynamism of Income Growth and Employment Creation, World Economic Slowdown and Global Recession Risk
Carlos M. Pelaez
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013
Executive Summary
I Recovery without Hiring
IA1 Hiring Collapse
IA2 Labor Underutilization
IA3 Ten Million Fewer Full-time Job
IA4 Youth and Middle-Age Unemployment
IB Collapse of United States Dynamism of Income Growth and Employment Creation
II IMF View of World Economy and Finance
III World Financial Turbulence
IIIA Financial Risks
IIIE Appendix Euro Zone Survival Risk
IIIF Appendix on Sovereign Bond Valuation
IV Global Inflation
V World Economic Slowdown
VA United States
VB Japan
VC China
VD Euro Area
VE Germany
VF France
VG Italy
VH United Kingdom
VI Valuation of Risk Financial Assets
VII Economic Indicators
VIII Interest Rates
IX Conclusion
References
Appendixes
Appendix I The Great Inflation
IIIB Appendix on Safe Haven Currencies
IIIC Appendix on Fiscal Compact
IIID Appendix on European Central Bank Large Scale Lender of Last Resort
IIIG Appendix on Deficit Financing of Growth and the Debt Crisis
IIIGA Monetary Policy with Deficit Financing of Economic Growth
IIIGB Adjustment during the Debt Crisis of the 1980s
Executive Summary
Content
ESI Tapering Quantitative Easing and Global Financial and Economic Risk
ESII Recovery without Hiring
ESIII Loss of Full-time Jobs
ESIV Youth Unemployment and Middle-Aged Unemployment
ESI Tapering Quantitative Easing and Global Financial and Economic Risk. The International Monetary Fund (IMF) provides an international safety net for prevention and resolution of international financial crises. The IMF’s Financial Sector Assessment Program (FSAP) provides analysis of the economic and financial sectors of countries (see Pelaez and Pelaez, International Financial Architecture (2005), 101-62, Globalization and the State, Vol. II (2008), 114-23). Relating economic and financial sectors is a challenging task for both theory and measurement. The IMF (2012WEOOct) provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/pubs/ft/weo/2012/02/index.htm), of the world financial system with its Global Financial Stability Report (GFSR) (IMF 2012GFSROct) (http://www.imf.org/external/pubs/ft/gfsr/2012/02/index.htm) and of fiscal affairs with the Fiscal Monitor (IMF 2012FMOct) (http://www.imf.org/external/pubs/ft/fm/2012/02/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 9.9 percent in IIQ2011 to 7.4 percent in IVQ2011 and 6.6 percent in IQ2012, rebounding to 7.8 percent in IIQ2012, 8.7 percent in IIIQ2012 and 8.2 percent in IVQ2012. Annual equivalent growth in IQ2013 fell to 6.6 percent. (See Subsection VC 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 28.7 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically low hiring and declining real wages.
- Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
- World Inflation Waves. Inflation continues in repetitive waves globally (http://cmpassocregulationblog.blogspot.com/2013/06/paring-quantitative-easing-policy-and.html).
A list of financial uncertainties includes:
- Euro Area Survival Risk. The resilience of the euro to fiscal and financial doubts on larger member countries is still an unknown risk.
- Foreign Exchange Wars. Exchange rate struggles continue as zero interest rates in advanced economies induce devaluation of their currencies.
- Valuation of Risk Financial Assets. Valuations of risk financial assets have reached extremely high levels in markets with lower volumes.
- Duration Trap of the Zero Bound. The yield of the US 10-year Treasury rose from 2.031 percent on Mar 9, 2012, to 2.294 percent on Mar 16, 2012. Considering a 10-year Treasury with coupon of 2.625 percent and maturity in exactly 10 years, the price would fall from 105.3512 corresponding to yield of 2.031 percent to 102.9428 corresponding to yield of 2.294 percent, for loss in a week of 2.3 percent but far more in a position with leverage of 10:1. Min Zeng, writing on “Treasurys fall, ending brutal quarter,” published on Mar 30, 2012, in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702303816504577313400029412564.html?mod=WSJ_hps_sections_markets), informs that Treasury bonds maturing in more than 20 years lost 5.52 percent in the first quarter of 2012.
- Credibility and Commitment of Central Bank Policy. There is a credibility issue of the commitment of monetary policy (Sargent and Silber 2012Mar20).
- Carry Trades. Commodity prices driven by zero interest rates have resumed their increasing path with fluctuations caused by intermittent risk aversion
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 in be the nominal interest rate, ir the real or inflation-adjusted interest rate and πe 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 + ir) = (1 + in)/(1 + πe) (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 πe 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 + rr) = 0.9902
That is, ir 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 πe. 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 “tapering” 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 Jun 19, 2013 (http://www.federalreserve.gov/newsevents/press/monetary/20130619a.htm):
“To support continued progress toward maximum employment and price stability, the Committee expects 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. In determining how long to maintain a highly accommodative stance of monetary policy, the Committee will also consider other information, including additional measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial developments. When the Committee decides to begin to remove policy accommodation, it will take a balanced approach consistent with its longer-run goals of maximum employment and inflation of 2 percent” (emphasis added).
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 15,464.30
on Fri Jul 5, 2013, which is higher by 9.2 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 8.9 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 59.6 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Jul 12, 2013; S&P 500 has gained 64.3 percent; and DAX 44.8 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 7/12/13” 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 14.4 percent below the trough; Japan’s Nikkei Average is 64.4 percent above the trough; DJ Asia Pacific TSM is 20.4 percent above the trough; Dow Global is 29.3 percent above the trough; STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 17.1 percent above the trough; and NYSE Financial Index is 38.9 percent above the trough. DJ UBS Commodities is 3.6 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 44.8 percent above the trough. Japan’s Nikkei Average is 64.4 percent above the trough on Aug 31, 2010 and 27.3 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 14,506.25 on Fri Jul 12, 2013 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 41.5 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 9.6 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 7/12/13” in Table VI-4 shows increase of 1.6 percent in the week for China’s Shanghai Composite. DJ Asia Pacific increased 2.6 percent. NYSE Financial increased 2.8 percent in the week. DJ UBS Commodities increased 2.3 percent. Dow Global increased 3.5 percent in the week of Jul 12, 2013. The DJIA increased 2.2 percent and S&P 500 increased 3.0 percent. DAX of Germany increased 5.2 percent. STOXX 50 increased 2.6 percent. The USD depreciated 1.8 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 7/12/13” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Jul 12, 2013. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 7/12/13” but also relative to the peak in column “∆% Peak to 7/12/13.” There are now several equity indexes above the peak in Table VI-4: DJIA 38.0 percent, S&P 500 38.0 percent, DAX 29.7 percent, Dow Global 5.5 percent, DJ Asia Pacific 5.4 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 10.7 percent and Nikkei Average 27.3 percent. There are only two equity indexes below the peak: Shanghai Composite by 35.6 percent and STOXX 50 by 0.8 percent. DJ UBS Commodities Index is now 11.4 percent below the peak. The US dollar strengthened 13.6 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010. Alexandra Scaggs, writing on “Tepid profits, roaring stocks,” on May 16, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323398204578487460105747412.html), analyzes stabilization of earnings growth: 70 percent of 458 reporting companies in the S&P 500 stock index reported earnings above forecasts but sales fell 0.2 percent relative to forecasts of increase of 0.5 percent. Paul Vigna, writing on “Earnings are a margin story but for how long,” on May 17, 2013, published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2013/05/17/earnings-are-a-margin-story-but-for-how-long/), analyzes that corporate profits increase with stagnating sales while companies manage costs tightly. More than 90 percent of S&P components reported moderate increase of earnings of 3.7 percent in IQ2013 relative to IQ2012 with decline of sales of 0.2 percent. Earnings and sales have been in declining trend. In IVQ2009, growth of earnings reached 104 percent and sales jumped 13 percent. Net margins reached 8.92 percent in IQ2013, which is almost the same at 8.95 percent in IIIQ2006. Operating margins are 9.58 percent. There is concern by market participants that reversion of margins to the mean could exert pressure on earnings unless there is more accelerated growth of sales. Vigna (op. cit.) finds sales growth limited by weak economic growth. Kate Linebaugh, writing on “Falling revenue dings stocks,” on Oct 20, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444592704578066933466076070.html?mod=WSJPRO_hpp_LEFTTopStories), identifies a key financial vulnerability: falling revenues across markets for United States reporting companies. Global economic slowdown is reducing corporate sales and squeezing corporate strategies. Linebaugh quotes data from Thomson Reuters that 100 companies of the S&P 500 index have reported declining revenue only 1 percent higher in Jun-Sep 2012 relative to Jun-Sep 2011 but about 60 percent of the companies are reporting lower sales than expected by analysts with expectation that revenue for the S&P 500 will be lower in Jun-Sep 2012 for the entities represented in the index. Results of US companies are likely repeated worldwide. Future company cash flows derive from investment projects. Real private fixed investment fell from $2,111.5 billion in IVQ2007 to $1920.4 billion in IQ2013 or by 9.1 percent compared with growth of 24.1 percent of gross private domestic investment from IQ1980 to IVQ1985 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). Undistributed profits of US corporations swelled 306.9 percent from $118.0 billion IQ2007 to $480.2 billion in IQ2013 and changed signs from minus $22.1 billion in IVQ2007 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). Corporate profits with inventory valuation and capital consumption adjustment fell $27.8 billion relative to IVQ2012 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp1q13_3rd.pdf), from $2013.0 billion in IVQ2012 to $1985.2 billion in IQ2013 at the quarterly rate of minus 1.4 percent. 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 Rτ is expected revenue in the time horizon from τ =1 to T; Cτ denotes costs; and ρ is an appropriate rate of discount. In words, the value today of a stock or investment project is the net revenue, or revenue less costs, in the investment period from τ =1 to T discounted to the present by an appropriate rate of discount. In the current weak economy, revenues have been increasing more slowly than anticipated in investment plans. An increase in interest rates would affect discount rates used in calculations of present value, resulting in frustration of investment decisions. If V represents value of the stock or investment project, as ρ → ∞, meaning that interest rates increase without bound, then V → 0, or
![clip_image001[1]](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQCbStJHirFt29ccKcdyFU_cWwhuWRa_R5aqJ-gpNynU06mQvzBR-nZReSyx6O_NSNU2R-9b64lTADakYUypaAY3nyp_njyQmtrDmndOdU_lNFH5cWw24VM3yKqSzDBYHBme9oTvtRFns/s1600-h/clip_image001%25255B1%25255D%25255B2%25255D.gif "clip_image001[1]"){kind=small}
declines. Equally, decline in expected revenue from the stock or project, Rτ, 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 7/12/ /13 | ∆% Week 7/12/13 | ∆% Trough to 7/12/ 13 | |
| DJIA | 4/26/ | 7/2/10 | -13.6 | 38.0 | 2.2 | 59.6 |
| S&P 500 | 4/23/ | 7/20/ | -16.0 | 38.0 | 3.0 | 64.3 |
| NYSE Finance | 4/15/ | 7/2/10 | -20.3 | 10.7 | 2.8 | 38.9 |
| Dow Global | 4/15/ | 7/2/10 | -18.4 | 5.5 | 3.5 | 29.3 |
| Asia Pacific | 4/15/ | 7/2/10 | -12.5 | 5.4 | 2.6 | 20.4 |
| Japan Nikkei Aver. | 4/05/ | 8/31/ | -22.5 | 27.3 | 1.4 | 64.4 |
| China Shang. | 4/15/ | 7/02 | -24.7 | -35.6 | 1.6 | -14.4 |
| STOXX 50 | 4/15/10 | 7/2/10 | -15.3 | -0.8 | 2.6 | 17.1 |
| DAX | 4/26/ | 5/25/ | -10.5 | 29.7 | 5.2 | 44.8 |
| Dollar | 11/25 2009 | 6/7 | 21.2 | 13.6 | -1.8 | -9.6 |
| DJ UBS Comm. | 1/6/ | 7/2/10 | -14.5 | -11.4 | 2.3 | 3.6 |
| 10-Year T Note | 4/5/ | 4/6/10 | 3.986 | 2.585 |
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
Appendix: Annotated Chronology of Risk Events. Another rising risk is division within the Federal Open Market Committee (FOMC) on risks and benefits of current policies as expressed in the minutes of the meeting held on Jan 29-30, 2013 (http://www.federalreserve.gov/monetarypolicy/files/fomcminutes20130130.pdf 13):
ESII Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels have increased by only 4 percent since Jan 2009. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job currently is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn, there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-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. IA1 Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IA2 Labor Underutilization provides the measures of labor underutilization of the Bureau of Labor Statistics (BLS). Statistics on the decline of full-time employment are in IA3 Ten Million Fewer Full-time Jobs. IA4 Youth and Middle-Age Unemployment provides the data on high unemployment of ages 16 to 24 years and of ages 45 years or over.
IA1 Hiring Collapse. An important characteristic of the current fractured labor market of the US is the closing of the avenue for exiting unemployment and underemployment normally available through dynamic hiring. Another avenue that is closed is the opportunity for advancement in moving to new jobs that pay better salaries and benefits again because of the collapse of hiring in the United States. Those who are unemployed or underemployed cannot find a new job even accepting lower wages and no benefits. The employed cannot escape declining inflation-adjusted earnings because there is no hiring. The objective of this section is to analyze hiring and labor underutilization in the United States.
Blanchard and Katz (1997, 53 consider an appropriate measure of job stress:
“The right measure of the state of the labor market is the exit rate from unemployment, defined as the number of hires divided by the number unemployed, rather than the unemployment rate itself. What matters to the unemployed is not how many of them there are, but how many of them there are in relation to the number of hires by firms.”
The natural rate of unemployment and the similar NAIRU are quite difficult to estimate in practice (Ibid; see Ball and Mankiw 2002).
The Bureau of Labor Statistics (BLS) created the Job Openings and Labor Turnover Survey (JOLTS) with the purpose that (http://www.bls.gov/jlt/jltover.htm#purpose):
“These data serve as demand-side indicators of labor shortages at the national level. Prior to JOLTS, there was no economic indicator of the unmet demand for labor with which to assess the presence or extent of labor shortages in the United States. The availability of unfilled jobs—the jobs opening rate—is an important measure of tightness of job markets, parallel to existing measures of unemployment.”
The BLS collects data from about 16,000 US business establishments in nonagricultural industries through the 50 states and DC. The data are released monthly and constitute an important complement to other data provided by the BLS (see also Lazear and Spletzer 2012Mar, 6-7).
Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 52.0 million in 2012 or by 11.8 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 48.5 million in 2012 or by 11.0 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.2 in 2005 to 38.9 in 2012 and in the private sector (RHP) from 53.1 in 2005 to 43.4 in 2012. Hiring has not recovered as in previous cyclical expansions because of the low rate of economic growth in the current cyclical expansion. There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
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
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.
Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2012
Source: US Bureau of Labor Statistics
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
Chart I-3 plots yearly percentage changes of nonfarm hiring. Percentage declines after 2007 were quite sharp.
Chart I-3, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2001-2012
Source: Bureau of Labor Statistics
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 Private Hiring Level, Annual, 2001-2012
Source: Bureau of Labor Statistics
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, Rate Total Private Hiring, Annual, 2001-2012
Source: Bureau of Labor Statistics
Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of <au in the years from 2001 to 2013 in Table I-3. Hiring numbers are in thousands. There is meager recovery in HNF from 4168 thousand (or 4.2 million) in May 2009 to 4774 thousand in May 2010, 4552 thousand in May 2011, 5011 thousand in May 2012 and 4964 thousand in May 2013 for cumulative gain of 19.1 percent. HP rose from 3896 thousand in May 2009 to 4289 thousand in May 2011, 4691 thousand in May 2012 and 4658 in May 2013 for cumulative gain of 16.7 percent. HNF has fallen from 5036 in Mar 2006 to 4049 in Mar 2012 or by 19.6 percent. HP has fallen from 5619 in May 2006 to 4658 in May 2013 or by 17.1 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 May | 5894 | 4.4 | 5498 | 4.9 |
| 2002 May | 5314 | 4.1 | 4955 | 4.5 |
| 2003 May | 4968 | 3.8 | 4687 | 4.3 |
| 2004 May | 5343 | 4.0 | 5048 | 4.6 |
| 2005 May | 5736 | 4.3 | 5411 | 4.8 |
| 2006 May | 5986 | 4.4 | 5619 | 4.9 |
| 2007 May | 5788 | 4.2 | 5394 | 4.7 |
| 2008 May | 5118 | 3.7 | 4796 | 4.2 |
| 2009 May | 4168 | 3.2 | 3896 | 3.6 |
| 2010 May | 4774 | 3.6 | 4024 | 3.7 |
| 2011 May | 4552 | 3.4 | 4289 | 3.9 |
| 2012 May | 5011 | 3.7 | 4691 | 4.2 |
| 2013 May | 4964 | 3.6 | 4658 | 4.1 |
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 again in Dec 2011 to 2990 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 4964 in May 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 4441 in May 2013 for increase of 5.9 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
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 and 3.1 in Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.1 in Dec 2012 and 3.3 in May 2013. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.2 in Dec 2012, climbing to 3.8 in Jun 2012 but falling to 2.2 in Dec 2012 and 3.6 in May 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
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 but decreasing to 3934 in Sep 2012 or lower by 2.3 percent relative to Sep 2011 and 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 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. The main problem in recovery of the US labor market has been the low rate of growth of 2.1 percent in the fifteen quarters of expansion of the economy from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. 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
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 3.7 in May 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 4.1 in May 2013.
Chart I-9, US, Rate Total Private Hiring Month SA 2001-2013
Source: Bureau of Labor Statistics
ESIII Loss of Full-time Jobs. Chart I-17 provides the number employed part-time for economic reasons or who cannot find full-time employment. There are sharp declines at the end of 2009, 2010 and 2011 but an increase in 2012 followed by stability in 2013.
Chart I-17, US, Working Part-time for Economic Reasons
Thousands, Month SA 2001-2013
Sources: US Bureau of Labor Statistics
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 8.043 million in Aug 2012, seasonally adjusted, or decline of 1.058 million in nine months, as shown in Table I-9, but then rebounded to 8.607 million in Sep 2012 for increase of 564,000 in one month from Aug to Sep 2012, declining 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 15,000 more than in Dec 2012 and to 7,988 million in Feb 2013, declining to 7.904 million in May 2013 but increasing to 8.226 million in Jun 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 four 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. 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 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 116.643 million in May 2013 and increased to 117.400 in Jun 2013 or by 757,000. 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 Jun 2013 is 117.400 million, which is lower by 5.819 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 245.552 million in Jun 2013 or by 13.594 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 5.819 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 13 million. Growth at 2.1 percent on average in the fifteen quarters of expansion from IIIQ2009 to IQ2013 is the main culprit of the fractured US labor market (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. 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 | ||
| 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 | ||
| 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
People lose their marketable job skills after prolonged unemployment and find increasing difficulty in finding another job. Chart I-18 shows the sharp rise in unemployed over 27 weeks and stabilization at an extremely high level.
Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2013
Sources: US Bureau of Labor Statistics
Another segment of U6 consists of people marginally attached to the labor force who continue to seek employment but less frequently on the frustration there may not be a job for them. Chart I-19 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.
Chart I-19, US, Marginally Attached to the Labor Force, NSA Month 2001-2013
Sources: US Bureau of Labor Statistics
Chart I-20 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 2013 with fluctuations around the typical behavior of a stationary series: there is no improvement in the United States in creating full-time jobs. 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 245.552 million in Jun 2013 or by 13.594 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 5.819 million.
Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2013
Sources: US Bureau of Labor Statistics
Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2013. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.
Chart I-20A, US, Noninstitutional Civilian Population, 2001-2013
Sources: US Bureau of Labor Statistics
Chart I-20B provides number of full-time jobs in the US from 1968 to 2013. There were multiple recessions followed by expansions without contraction of full-time jobs without recovery as during the period after 2008.
Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2013
Sources: US Bureau of Labor Statistics
Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.
Chart I-20C, US, Noninstitutional Civilian Population, 1968-2013
Sources: US Bureau of Labor Statistics
ESIV Youth Unemployment and Middle-Aged Unemployment. The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs and to 17.834 million in 2012 or 2.207 million fewer jobs. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.914 million in Jul 2006 with 19.461 million in Jul 2012 for 2.453 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 21.268 million in Jun 2006 to 19.125 million in Jun 2013 or by 2.143 million. The civilian noninstitutional population increased ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.858 million in Jun 2013 or by 1.415 million while the number of jobs for ages 16 to 24 years fell by 2.592 million from 21.717 million in Jul 2007 to 19.125 million in Jun 2013. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.
Table I-10, US, Employment Level 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Annual |
| 2001 | 19678 | 19745 | 19800 | 19778 | 19648 | 21212 | 20088 |
| 2002 | 18653 | 19074 | 19091 | 19108 | 19484 | 20828 | 19683 |
| 2003 | 18811 | 18880 | 18709 | 18873 | 19032 | 20432 | 19351 |
| 2004 | 18852 | 18841 | 18752 | 19184 | 19237 | 20587 | 19630 |
| 2005 | 18858 | 18670 | 18989 | 19071 | 19356 | 20949 | 19770 |
| 2006 | 19003 | 19182 | 19291 | 19406 | 19769 | 21268 | 20041 |
| 2007 | 19407 | 19415 | 19538 | 19368 | 19457 | 21098 | 19875 |
| 2008 | 18724 | 18546 | 18745 | 19161 | 19254 | 20466 | 19202 |
| 2009 | 17467 | 17606 | 17564 | 17739 | 17588 | 18726 | 17601 |
| 2010 | 16166 | 16412 | 16587 | 16764 | 17039 | 17920 | 17077 |
| 2011 | 16512 | 16638 | 16898 | 16970 | 17045 | 18180 | 17362 |
| 2012 | 16944 | 17150 | 17301 | 17387 | 17681 | 18907 | 17834 |
| 2013 | 17183 | 17257 | 17271 | 17593 | 17704 | 19125 |
Sources: US Bureau of Labor Statistics
Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2013. Employment level is sharply lower in Jun 2013 relative to the peak in 2007.
Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-21A provides the US civilian noninstitutional population ages 16 to 24 years not seasonally adjusted from 2001 to 2013. The civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.858 million in Jun 2013, by 1.415 million or 3.8 percent, while employment for ages 16 to 24 years fell from 21.717 million in Jul 2007 to 19.125 million in Jun 2013, by 2.592 million or decline of 11.9 percent.
Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-21B provides the civilian labor force of the US ages 16 to 24 years NSA from 2001 to 2013. The US civilian labor force ages 16 to 24 years fell from 24.339 million in Jul 2007 to 23.322 million in Jun 2013, by 1.017 million or decline of 4.2 percent, while the civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.858 million in Jun 2013, by 1.415 million or 3.8 percent. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.
Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-21C provides the ratio of labor force to noninstitutional population or labor force participation of ages 16 to 24 years not seasonally adjusted. The US labor force participation rates for ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.0 in Jun 2013 because of the frustration of young people who believe there may not be jobs available for them.
Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
An important measure of the job market is the number of people with jobs relative to population available for work or civilian noninstitutional population or employment/population ratio. Chart I-21D provides the employment population ratio for ages 16 to 24 years. The US employment/population ratio NSA collapsed from 59.2 in Jul 2006 to 49.2 in Jun 2013. Chart I-21D shows vertical drop during the global recession without recovery.
Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million and 3451 thousand in 2012 or by 1.109 million. The unemployment level ages 16 to 24 years rose from 2.883 million in Jun 2007 to 4.198 million in Jun 2013 or by 1.315 million. This situation may persist for many years.
Table I-11, US, Unemployment Level 16-24 Years, Thousands NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Annual |
| 2001 | 2250 | 2258 | 2253 | 2095 | 2171 | 2775 | 2371 |
| 2002 | 2754 | 2731 | 2822 | 2515 | 2568 | 3167 | 2683 |
| 2003 | 2748 | 2740 | 2601 | 2572 | 2838 | 3542 | 2746 |
| 2004 | 2767 | 2631 | 2588 | 2387 | 2684 | 3191 | 2638 |
| 2005 | 2661 | 2787 | 2520 | 2398 | 2619 | 3010 | 2521 |
| 2006 | 2366 | 2433 | 2216 | 2092 | 2254 | 2860 | 2353 |
| 2007 | 2363 | 2230 | 2096 | 2074 | 2203 | 2883 | 2342 |
| 2008 | 2633 | 2480 | 2347 | 2196 | 2952 | 3450 | 2830 |
| 2009 | 3278 | 3457 | 3371 | 3321 | 3851 | 4653 | 3760 |
| 2010 | 3983 | 3888 | 3748 | 3803 | 3854 | 4481 | 3857 |
| 2011 | 3851 | 3696 | 3520 | 3365 | 3628 | 4248 | 3634 |
| 2012 | 3416 | 3507 | 3294 | 3175 | 3438 | 4180 | 3451 |
| 2013 | 3674 | 3449 | 3261 | 3129 | 3478 | 4198 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-22 provides the unemployment level ages 16 to 24 from 2002 to 2012. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013.
Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Table I-12 provides the rate of unemployment of young peoples in ages 16 to 24 years. The annual rate jumped from 10.5 percent in 2007 to 18.4 percent in 2010, 17.3 percent in 2011 and 16.2 percent in 2012. During the seasonal peak in Jul the rate of youth unemployed was 18.1 percent in Jul 2011 and 17.1 percent in Jul 2012 compared with 10.8 percent in Jul 2007. The rate of youth unemployment rose from 11.9 in Jun 2006 to 18.0 percent in Jun 2013 and likely higher if adding those who ceased searching for a job in frustration none may be available.
Table I-12, US, Unemployment Rate 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Dec | Annual |
| 2001 | 10.3 | 10.3 | 10.2 | 9.6 | 10.0 | 11.6 | 10.5 | 11.0 | 10.6 |
| 2002 | 12.9 | 12.5 | 12.9 | 11.6 | 11.6 | 13.2 | 12.4 | 10.9 | 12.0 |
| 2003 | 12.7 | 12.7 | 12.2 | 12.0 | 13.0 | 14.8 | 13.3 | 10.5 | 12.4 |
| 2004 | 12.8 | 12.3 | 12.1 | 11.1 | 12.2 | 13.4 | 12.3 | 10.5 | 11.8 |
| 2005 | 12.4 | 13.0 | 11.7 | 11.2 | 11.9 | 12.6 | 11.0 | 9.4 | 11.3 |
| 2006 | 11.1 | 11.3 | 10.3 | 9.7 | 10.2 | 11.9 | 11.2 | 9.1 | 10.5 |
| 2007 | 10.9 | 10.3 | 9.7 | 9.7 | 10.2 | 12.0 | 10.8 | 10.7 | 10.5 |
| 2008 | 12.3 | 11.8 | 11.1 | 10.3 | 13.3 | 14.4 | 14.0 | 13.7 | 12.8 |
| 2009 | 15.8 | 16.4 | 16.1 | 15.8 | 18.0 | 19.9 | 18.5 | 17.5 | 17.6 |
| 2010 | 19.8 | 19.2 | 18.4 | 18.5 | 18.4 | 20.0 | 19.1 | 16.7 | 18.4 |
| 2011 | 18.9 | 18.2 | 17.2 | 16.5 | 17.5 | 18.9 | 18.1 | 15.5 | 17.3 |
| 2012 | 16.8 | 17.0 | 16.0 | 15.4 | 16.3 | 18.1 | 17.1 | 15.2 | 16.2 |
| 2013 | 17.6 | 16.7 | 15.9 | 15.1 | 16.4 | 18.0 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2001 to 2013. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels during the fourteen consecutive quarters of expansion of the economy since IIIQ2009 because of much lower growth at 2.1 percent annual equivalent on (Table I -5 http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2013. The rate of youth unemployment rose to 20 percent during the contractions of the early 1980s and also during the contraction of the global recession in 2008 and 2009. The data illustrate again the argument in this blog that the contractions of the early 1980s are the valid framework for comparison with the global recession of 2008 and 2009 instead of misleading comparisons with the 1930s. During the initial phase of recovery, the rate of youth unemployment 16 to 24 years NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984 while the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 17.5 percent in Dec 2009, 16.7 percent in Dec 2010, 15.5 percent in Dec 2011, 15.2 percent in Dec 2012, 17.6 percent in Jan 2013, 16.7 percent in Feb 2013, 15.9 percent in Mar 2013, 15.1 percent in Apr 2013, 16.4 percent in May 2013 and 18.0 percent in Jun 2013. In Jul 2007, the rate of youth unemployment was 10.8 percent, increasing to 17.1 percent in Jul 2012. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.1 percent on average during the first fourteen fifteen quarters of expansion from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The fractured US labor market denies an early start for young people.
Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
It is more difficult to move to other jobs after a certain age because of fewer available opportunities for mature individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.985 million in Jul 2006 to 4.821 million in July 2010 or by 142.9 percent. The number of unemployed ages 45 years and over declined to 4.405 million in Jul 2012 that is still higher by 121.9 percent than in Jul 2006. The number unemployed age 45 and over jumped from 1.794 million in Dec 2006 to 4.762 million in Dec 2010 or 165.4 percent. At 3.927 million in Dec 2012, mature unemployment is higher by 2.133 million or 118.9 percent higher than 1.794 million in Dec 2006. The level of unemployment of those aged 45 year or more of 3.648 million in Jun 2013 is higher by 1.843 million than 1.805 million in Jun 2007 or higher by 102.1 percent.
Table I-13, US, Unemployment Level 45 Years and Over, Thousands NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Dec | Annual |
| 2000 | 1498 | 1392 | 1291 | 1062 | 1074 | 1163 | 1217 | 1249 |
| 2001 | 1572 | 1587 | 1533 | 1421 | 1259 | 1371 | 1901 | 1576 |
| 2002 | 2235 | 2280 | 2138 | 2101 | 1999 | 2190 | 2210 | 2114 |
| 2003 | 2495 | 2415 | 2485 | 2287 | 2112 | 2212 | 2130 | 2253 |
| 2004 | 2453 | 2397 | 2354 | 2160 | 2025 | 2182 | 2086 | 2149 |
| 2005 | 2286 | 2286 | 2126 | 1939 | 1844 | 1868 | 1963 | 2009 |
| 2006 | 2126 | 2056 | 1881 | 1843 | 1784 | 1813 | 1794 | 1848 |
| 2007 | 2155 | 2138 | 2031 | 1871 | 1803 | 1805 | 2120 | 1966 |
| 2008 | 2336 | 2336 | 2326 | 2104 | 2095 | 2211 | 3485 | 2540 |
| 2009 | 4138 | 4380 | 4518 | 4172 | 4175 | 4505 | 4960 | 4500 |
| 2010 | 5314 | 5307 | 5194 | 4770 | 4565 | 4564 | 4762 | 4879 |
| 2011 | 5027 | 4837 | 4748 | 4373 | 4356 | 4559 | 4182 | 4537 |
| 2012 | 4458 | 4472 | 4390 | 4037 | 4083 | 4084 | 3927 | 4133 |
| 2013 | 4394 | 4107 | 3929 | 3689 | 3605 | 3648 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-25 provides the level unemployed ages 45 years and over. There was an increase in the recessions of the 1980s, 1991 and 2001 followed by declines to earlier levels. The current expansion of the economy after IIIQ2009 has not been sufficiently vigorous to reduce significantly middle-age unemployment.
Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
I 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 (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-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. IA1 Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IA2 Labor Underutilization provides the measures of labor underutilization of the Bureau of Labor Statistics (BLS). Statistics on the decline of full-time employment are in IA3 Ten Million Fewer Full-time Jobs. IA4 Youth and Middle-Age Unemployment provides the data on high unemployment of ages 16 to 24 years and of ages 45 years or over.
IA1 Hiring Collapse. An important characteristic of the current fractured labor market of the US is the closing of the avenue for exiting unemployment and underemployment normally available through dynamic hiring. Another avenue that is closed is the opportunity for advancement in moving to new jobs that pay better salaries and benefits again because of the collapse of hiring in the United States. Those who are unemployed or underemployed cannot find a new job even accepting lower wages and no benefits. The employed cannot escape declining inflation-adjusted earnings because there is no hiring. The objective of this section is to analyze hiring and labor underutilization in the United States.
Blanchard and Katz (1997, 53 consider an appropriate measure of job stress:
“The right measure of the state of the labor market is the exit rate from unemployment, defined as the number of hires divided by the number unemployed, rather than the unemployment rate itself. What matters to the unemployed is not how many of them there are, but how many of them there are in relation to the number of hires by firms.”
The natural rate of unemployment and the similar NAIRU are quite difficult to estimate in practice (Ibid; see Ball and Mankiw 2002).
The Bureau of Labor Statistics (BLS) created the Job Openings and Labor Turnover Survey (JOLTS) with the purpose that (http://www.bls.gov/jlt/jltover.htm#purpose):
“These data serve as demand-side indicators of labor shortages at the national level. Prior to JOLTS, there was no economic indicator of the unmet demand for labor with which to assess the presence or extent of labor shortages in the United States. The availability of unfilled jobs—the jobs opening rate—is an important measure of tightness of job markets, parallel to existing measures of unemployment.”
The BLS collects data from about 16,000 US business establishments in nonagricultural industries through the 50 states and DC. The data are released monthly and constitute an important complement to other data provided by the BLS (see also Lazear and Spletzer 2012Mar, 6-7).
Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 52.0 million in 2012 or by 11.8 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 48.5 million in 2012 or by 11.0 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.2 in 2005 to 38.9 in 2012 and in the private sector (RHP) from 53.1 in 2005 to 43.4 in 2012. Hiring has not recovered as in previous cyclical expansions because of the low rate of economic growth in the current cyclical expansion. There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
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
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.
Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2012
Source: US Bureau of Labor Statistics
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
Chart I-3 plots yearly percentage changes of nonfarm hiring. Percentage declines after 2007 were quite sharp.
Chart I-3, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2001-2012
Source: Bureau of Labor Statistics
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 Private Hiring Level, Annual, 2001-2012
Source: Bureau of Labor Statistics
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, Rate Total Private Hiring, Annual, 2001-2012
Source: Bureau of Labor Statistics
Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of <au in the years from 2001 to 2013 in Table I-3. Hiring numbers are in thousands. There is meager recovery in HNF from 4168 thousand (or 4.2 million) in May 2009 to 4774 thousand in May 2010, 4552 thousand in May 2011, 5011 thousand in May 2012 and 4964 thousand in May 2013 for cumulative gain of 19.1 percent. HP rose from 3896 thousand in May 2009 to 4289 thousand in May 2011, 4691 thousand in May 2012 and 4658 in May 2013 for cumulative gain of 16.7 percent. HNF has fallen from 5036 in Mar 2006 to 4049 in Mar 2012 or by 19.6 percent. HP has fallen from 5619 in May 2006 to 4658 in May 2013 or by 17.1 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 May | 5894 | 4.4 | 5498 | 4.9 |
| 2002 May | 5314 | 4.1 | 4955 | 4.5 |
| 2003 May | 4968 | 3.8 | 4687 | 4.3 |
| 2004 May | 5343 | 4.0 | 5048 | 4.6 |
| 2005 May | 5736 | 4.3 | 5411 | 4.8 |
| 2006 May | 5986 | 4.4 | 5619 | 4.9 |
| 2007 May | 5788 | 4.2 | 5394 | 4.7 |
| 2008 May | 5118 | 3.7 | 4796 | 4.2 |
| 2009 May | 4168 | 3.2 | 3896 | 3.6 |
| 2010 May | 4774 | 3.6 | 4024 | 3.7 |
| 2011 May | 4552 | 3.4 | 4289 | 3.9 |
| 2012 May | 5011 | 3.7 | 4691 | 4.2 |
| 2013 May | 4964 | 3.6 | 4658 | 4.1 |
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 again in Dec 2011 to 2990 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 4964 in May 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 4441 in May 2013 for increase of 5.9 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
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 and 3.1 in Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.1 in Dec 2012 and 3.3 in May 2013. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.2 in Dec 2012, climbing to 3.8 in Jun 2012 but falling to 2.2 in Dec 2012 and 3.6 in May 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
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 but decreasing to 3934 in Sep 2012 or lower by 2.3 percent relative to Sep 2011 and 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 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. The main problem in recovery of the US labor market has been the low rate of growth of 2.1 percent in the fifteen quarters of expansion of the economy from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. 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
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 3.7 in May 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 4.1 in May 2013.
Chart I-9, US, Rate Total Private Hiring Month SA 2001-2013
Source: Bureau of Labor Statistics
The JOLTS report of the Bureau of Labor Statistics also provides total nonfarm job openings (TNF JOB), TNF JOB rate and TNF LD (layoffs and discharges) shown in Table I-4 for the month of Mayfrom 2001 to 2013. The final column provides annual TNF LD for the years from 2001 to 2012. Nonfarm job openings (TNF JOB) fell from a peak of 4520 in May 2006 to 3830 in May 2013 or by 15.3 percent while the rate dropped from 3.2 to 2.7. Nonfarm layoffs and discharges (TNF LD) rose from 1672 in May 2006 to 1916 in May 2009 or by 14.6 percent. The annual data show layoffs and discharges rising from 21.2 million in 2006 to 26.8 million in 2009 or by 26.4 percent. Business pruned payroll jobs to survive the global recession but there has not been hiring because of the low rate of growth of 2.1 percent in the fifteen quarters of expansion of the economy from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Table I-4, US, Total Nonfarm Job Openings and Total Nonfarm Layoffs and Discharges, Thousands NSA
| TNF JOB | TNF JOB | TNF LD | TNF LD | |
| May 2001 | 4550 | 3.3 | 1680 | 24499 |
| May 2002 | 3547 | 2.6 | 1622 | 22922 |
| May 2003 | 3165 | 2.4 | 1592 | 23294 |
| May 2004 | 3672 | 2.7 | 1521 | 22802 |
| May 2005 | 3922 | 2.8 | 1637 | 22185 |
| May 2006 | 4520 | 3.2 | 1672 | 21157 |
| May 2007 | 4513 | 3.2 | 1524 | 22142 |
| May 2008 | 3951 | 2.8 | 1617 | 24181 |
| May 2009 | 2394 | 1.8 | 1916 | 26784 |
| May 2010 | 2834 | 2.1 | 1568 | 21773 |
| May 2011 | 2925 | 2.2 | 1534 | 20401 |
| May 2012 | 3771 | 2.7 | 1736 | 20546 |
| May 2013 | 3830 | 2.7 | 1549 |
Notes: TNF JOB: Total Nonfarm Job Openings; LD: Layoffs and Discharges
Source: Bureau of Labor Statistics http://www.bls.gov/jlt/
Chart I-10 shows monthly job openings rising from the trough in 2009 to a high in the beginning of 2010. Job openings then stabilized into 2011 but have surpassed the peak of 3142 seasonally adjusted in Apr 2010 with 3612 seasonally adjusted in Dec 2012, which is higher by 15.0 percent relative to Apr 2010 but lower by 4.7 percent than 3789 in Nov 2012 and lower by 6.1 percent than 3848 in Mar 2012. Nonfarm job openings increased from 3612 in Dec 2012 to 3828 in May 2013 or by 6.0 percent. The high of job openings not seasonally adjusted in 2010 was 3396 in Apr 2010 that was surpassed by 3554 in Jul 2011, increasing to 3896 in Oct 2012 but declining to 3103 in Dec 2012 and increasing to 3830 in May 2013. The level of job openings not seasonally adjusted fell to 3103 in Dec 2012 or by 19.0 percent relative to 3831 in Apr 2012. There is here again the strong seasonality of year-end labor data. The level of job openings of 3830 in May 2013 NSA is lower by 15.3 percent relative to 4520 in May 2006. The main problem in recovery of the US labor market has been the low rate of growth of 2.1 percent in the fifteen quarters of expansion of the economy from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Chart I-10, US Job Openings, Thousands NSA, 2001-2013
Source: US Bureau of Labor Statistics
The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted rose from 2.2 percent in Jan 2011 to 2.5 percent in Dec 2011, 2.6 in Dec 2012 and 2.7 in May 2013. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 3.0 in Apr 2013 and 2.7 in May 2013. The rate of job openings NSA fell from 3.4 in Jul 2007 to 1.6 in Nov-Dec 2009, recovering insufficiently to 2.7 in May 2013.
Chart I-11, US, Rate of Job Openings, NSA, 2001-2013
Source: US Bureau of Labor Statistics
Total separations are shown in Chart I-12. Separations are much lower in 2012-2-13 than before the global recession but hiring has not recovered.
Chart I-12, US, Total Nonfarm Separations, Month SA, 2001-2013
Source: US Bureau of Labor Statistics
Annual total separations are shown in Chart I-13. Separations are much lower in 2011-2012 than before the global recession but without recovery in hiring.
Chart I-13, US, Total Separations, Annual, 2001-2012
Source: US Bureau of Labor Statistics
Table I-5 provides total nonfarm total separations from 2001 to 2012. Separations fell from 61.6 million in 2006 to 47.6 million in 2010 or by 14.0 million and 47.6 million in 2011 or by 14.0 million. Total separations increased from 47.6 million in 2011 to 49.7 million in 2012 or by 2.1 million.
Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2012
| Year | Annual |
| 2001 | 64765 |
| 2002 | 59190 |
| 2003 | 56487 |
| 2004 | 58340 |
| 2005 | 60733 |
| 2006 | 61565 |
| 2007 | 61162 |
| 2008 | 58627 |
| 2009 | 51532 |
| 2010 | 47646 |
| 2011 | 47626 |
| 2012 | 49676 |
Source: US Bureau of Labor Statistics
Monthly data of layoffs and discharges reach a peak in early 2009, as shown in Chart I-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business. Weak rates of growth of 2.1 percent of GDP on average from IIIQ2009 to IQ2013 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html) frustrated employment recovery. There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly SA, 2011-2013
Source: US Bureau of Labor Statistics
Layoffs and discharges in Chart I-15 rose sharply to a peak in 2009. There was pronounced drop into 2010 and 2011 with mild increase into 2012.
Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2012
Source: US Bureau of Labor Statistics
Table I-6 provides annual nonfarm layoffs and discharges from 2001 to 2012. Layoffs and discharges peaked at 26.8 million in 2009 and then fell to 20.4 million in 2011, by 6.4 million, or 23.9 percent. Total nonfarm layoffs and discharges increased mildly to 20.5 million in 2012.
Table I-6, US, Total Nonfarm Layoffs and Discharges, 2001-2012
| Year | Annual |
| 2001 | 24499 |
| 2002 | 22922 |
| 2003 | 23294 |
| 2004 | 22802 |
| 2005 | 22185 |
| 2006 | 21157 |
| 2007 | 22142 |
| 2008 | 24181 |
| 2009 | 26784 |
| 2010 | 21773 |
| 2011 | 20401 |
| 2012 | 20546 |
Source: US Bureau of Labor Statistics
IA2 Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table I-7. The most comprehensive measure is U6 that consists of total unemployed plus total employed part time for economic reasons plus all marginally attached workers as percent of the labor force. U6 not seasonally annualized has risen from 8.2 percent in 2006 to 14.6 percent in Jun 2013.
Table I-7, US, Alternative Measures of Labor Underutilization NSA %
| U1 | U2 | U3 | U4 | U5 | U6 | |
| 2013 | ||||||
| Jun | 3.9 | 3.8 | 7.8 | 8.4 | 9.3 | 14.6 |
| May | 4.1 | 3.7 | 7.3 | 7.7 | 8.5 | 13.4 |
| Apr | 4.3 | 3.9 | 7.1 | 7.6 | 8.5 | 13.4 |
| Mar | 4.3 | 4.3 | 7.6 | 8.1 | 9.0 | 13.9 |
| Feb | 4.3 | 4.6 | 8.1 | 8.6 | 9.6 | 14.9 |
| Jan | 4.3 | 4.9 | 8.5 | 9.0 | 9.9 | 15.4 |
| 2012 | ||||||
| Dec | 4.2 | 4.3 | 7.6 | 8.3 | 9.2 | 14.4 |
| Nov | 4.2 | 3.9 | 7.4 | 7.9 | 8.8 | 13.9 |
| Oct | 4.3 | 3.9 | 7.5 | 8.0 | 9.0 | 13.9 |
| Sep | 4.2 | 4.0 | 7.6 | 8.0 | 9.0 | 14.2 |
| Aug | 4.3 | 4.4 | 8.2 | 8.7 | 9.7 | 14.6 |
| Jul | 4.3 | 4.6 | 8.6 | 9.1 | 10.0 | 15.2 |
| Jun | 4.5 | 4.4 | 8.4 | 8.9 | 9.9 | 15.1 |
| May | 4.7 | 4.3 | 7.9 | 8.4 | 9.3 | 14.3 |
| Apr | 4.8 | 4.3 | 7.7 | 8.3 | 9.1 | 14.1 |
| Mar | 4.9 | 4.8 | 8.4 | 8.9 | 9.7 | 14.8 |
| Feb | 4.9 | 5.1 | 8.7 | 9.3 | 10.2 | 15.6 |
| Jan | 4.9 | 5.4 | 8.8 | 9.4 | 10.5 | 16.2 |
| 2011 | ||||||
| Dec | 4.8 | 5.0 | 8.3 | 8.8 | 9.8 | 15.2 |
| Nov | 4.9 | 4.7 | 8.2 | 8.9 | 9.7 | 15.0 |
| Oct | 5.0 | 4.8 | 8.5 | 9.1 | 10.0 | 15.3 |
| Sep | 5.2 | 5.0 | 8.8 | 9.4 | 10.2 | 15.7 |
| Aug | 5.2 | 5.1 | 9.1 | 9.6 | 10.6 | 16.1 |
| Jul | 5.2 | 5.2 | 9.3 | 10.0 | 10.9 | 16.3 |
| Jun | 5.1 | 5.1 | 9.3 | 9.9 | 10.9 | 16.4 |
| May | 5.5 | 5.1 | 8.7 | 9.2 | 10.0 | 15.4 |
| Apr | 5.5 | 5.2 | 8.7 | 9.2 | 10.1 | 15.5 |
| Mar | 5.7 | 5.8 | 9.2 | 9.7 | 10.6 | 16.2 |
| Feb | 5.6 | 6.0 | 9.5 | 10.1 | 11.1 | 16.7 |
| Jan | 5.6 | 6.2 | 9.8 | 10.4 | 11.4 | 17.3 |
| Dec 2010 | 5.4 | 5.9 | 9.1 | 9.9 | 10.7 | 16.6 |
| Annual | ||||||
| 2012 | 4.5 | 4.4 | 8.1 | 8.6 | 9.5 | 14.7 |
| 2011 | 5.3 | 5.3 | 8.9 | 9.5 | 10.4 | 15.9 |
| 2010 | 5.7 | 6.0 | 9.6 | 10.3 | 11.1 | 16.7 |
| 2009 | 4.7 | 5.9 | 9.3 | 9.7 | 10.5 | 16.2 |
| 2008 | 2.1 | 3.1 | 5.8 | 6.1 | 6.8 | 10.5 |
| 2007 | 1.5 | 2.3 | 4.6 | 4.9 | 5.5 | 8.3 |
| 2006 | 1.5 | 2.2 | 4.6 | 4.9 | 5.5 | 8.2 |
| 2005 | 1.8 | 2.5 | 5.1 | 5.4 | 6.1 | 8.9 |
| 2004 | 2.1 | 2.8 | 5.5 | 5.8 | 6.5 | 9.6 |
| 2003 | 2.3 | 3.3 | 6.0 | 6.3 | 7.0 | 10.1 |
| 2002 | 2.0 | 3.2 | 5.8 | 6.0 | 6.7 | 9.6 |
| 2001 | 1.2 | 2.4 | 4.7 | 4.9 | 5.6 | 8.1 |
| 2000 | 0.9 | 1.8 | 4.0 | 4.2 | 4.8 | 7.0 |
Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.1 percent in Aug 2011 to 16.3 percent in Sep 2011 and then fell to 14.5 percent in Apr 2012, increasing to 14.3 percent in Jun 2013. Unemployment is an incomplete measure of the stress in US job markets. A different calculation in this blog is provided by using the participation rate in the labor force before the global recession. This calculation shows 28.7 million in job stress of unemployment/underemployment in Jun 2013, not seasonally adjusted, corresponding to 17.7 percent of the labor force (Table I-4http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-million-unemployed-or.html).
Table I-8, US, Alternative Measures of Labor Underutilization SA %
| U1 | U2 | U3 | U4 | U5 | U6 | |
| Jun 2013 | 4.0 | 3.9 | 7.6 | 8.2 | 9.1 | 14.3 |
| May | 4.1 | 3.9 | 7.6 | 8.0 | 8.8 | 13.8 |
| Apr | 4.1 | 4.1 | 7.5 | 8.0 | 8.9 | 13.9 |
| Mar | 4.1 | 4.1 | 7.6 | 8.1 | 8.9 | 13.8 |
| Feb | 4.2 | 4.2 | 7.7 | 8.3 | 9.2 | 14.3 |
| Jan | 4.2 | 4.3 | 7.9 | 8.4 | 9.3 | 14.4 |
| Dec 2012 | 4.3 | 4.1 | 7.8 | 8.5 | 9.4 | 14.4 |
| Nov | 4.3 | 4.1 | 7.8 | 8.3 | 9.2 | 14.4 |
| Oct | 4.4 | 4.2 | 7.9 | 8.4 | 9.3 | 14.5 |
| Sep | 4.3 | 4.2 | 7.8 | 8.3 | 9.3 | 14.7 |
| Aug | 4.4 | 4.5 | 8.1 | 8.6 | 9.6 | 14.7 |
| Jul | 4.5 | 4.6 | 8.2 | 8.7 | 9.7 | 14.9 |
| Jun | 4.6 | 4.6 | 8.2 | 8.7 | 9.6 | 14.8 |
| May | 4.6 | 4.5 | 8.2 | 8.7 | 9.6 | 14.8 |
| Apr | 4.5 | 4.5 | 8.1 | 8.7 | 9.5 | 14.5 |
| Mar | 4.6 | 4.5 | 8.2 | 8.7 | 9.6 | 14.5 |
| Feb | 4.8 | 4.6 | 8.3 | 8.9 | 9.8 | 15.0 |
| Jan | 4.8 | 4.7 | 8.3 | 8.9 | 9.9 | 15.1 |
| Dec 2011 | 4.9 | 4.9 | 8.5 | 9.0 | 10.0 | 15.2 |
| Nov | 5.0 | 4.9 | 8.6 | 9.3 | 10.2 | 15.5 |
| Oct | 5.1 | 5.1 | 8.9 | 9.5 | 10.4 | 16.0 |
| Sep | 5.4 | 5.2 | 9.0 | 9.6 | 10.5 | 16.3 |
| Aug | 5.3 | 5.2 | 9.0 | 9.6 | 10.5 | 16.1 |
| Jul | 5.3 | 5.3 | 9.0 | 9.7 | 10.6 | 16.0 |
| Jun | 5.3 | 5.3 | 9.1 | 9.7 | 10.7 | 16.1 |
| May | 5.3 | 5.4 | 9.0 | 9.5 | 10.3 | 15.8 |
| Apr | 5.2 | 5.4 | 9.0 | 9.6 | 10.5 | 16.0 |
| Mar | 5.3 | 5.4 | 8.9 | 9.5 | 10.4 | 15.8 |
| Feb | 5.4 | 5.5 | 9.0 | 9.6 | 10.6 | 16.0 |
| Jan | 5.5 | 5.5 | 9.1 | 9.7 | 10.8 | 16.2 |
Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-16 provides U6 on a monthly basis from 2001 to 2013. There was a steep climb from 2007 into 2009 and then this measure of unemployment and underemployment stabilized at that high level but declined into 2012. The low of U6 SA was 8.0 percent in Mar 2006 and the peak was 17.1 percent in Apr 2010. The low NSA was 7.6 percent in Oct 2006 and the peak was 18.0 percent in Jan 2010.
Chart I-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed Part-Time for Economic Reasons, Month, SA, 2001-2013
Source: US Bureau of Labor Statistics
Chart I-17 provides the number employed part-time for economic reasons or who cannot find full-time employment. There are sharp declines at the end of 2009, 2010 and 2011 but an increase in 2012 followed by stability in 2013.
Chart I-17, US, Working Part-time for Economic Reasons
Thousands, Month SA 2001-2013
Sources: US Bureau of Labor Statistics
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 8.043 million in Aug 2012, seasonally adjusted, or decline of 1.058 million in nine months, as shown in Table I-9, but then rebounded to 8.607 million in Sep 2012 for increase of 564,000 in one month from Aug to Sep 2012, declining 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 15,000 more than in Dec 2012 and to 7,988 million in Feb 2013, declining to 7.904 million in May 2013 but increasing to 8.226 million in Jun 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 four 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. 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 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 116.643 million in May 2013 and increased to 117.400 in Jun 2013 or by 757,000. 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 Jun 2013 is 117.400 million, which is lower by 5.819 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 245.552 million in Jun 2013 or by 13.594 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 5.819 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 13 million. Growth at 2.1 percent on average in the fifteen quarters of expansion from IIIQ2009 to IQ2013 is the main culprit of the fractured US labor market (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. 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 | ||
| 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 | ||
| 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
People lose their marketable job skills after prolonged unemployment and find increasing difficulty in finding another job. Chart I-18 shows the sharp rise in unemployed over 27 weeks and stabilization at an extremely high level.
Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2013
Sources: US Bureau of Labor Statistics
Another segment of U6 consists of people marginally attached to the labor force who continue to seek employment but less frequently on the frustration there may not be a job for them. Chart I-19 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.
Chart I-19, US, Marginally Attached to the Labor Force, NSA Month 2001-2013
Sources: US Bureau of Labor Statistics
IA3 Ten Million Fewer Full-time Jobs. Chart I-20 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 2013 with fluctuations around the typical behavior of a stationary series: there is no improvement in the United States in creating full-time jobs. 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 245.552 million in Jun 2013 or by 13.594 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 5.819 million.
Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2013
Sources: US Bureau of Labor Statistics
Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2013. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.
Chart I-20A, US, Noninstitutional Civilian Population, 2001-2013
Sources: US Bureau of Labor Statistics
Chart I-20B provides number of full-time jobs in the US from 1968 to 2013. There were multiple recessions followed by expansions without contraction of full-time jobs without recovery as during the period after 2008.
Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2013
Sources: US Bureau of Labor Statistics
Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.
Chart I-20C, US, Noninstitutional Civilian Population, 1968-2013
Sources: US Bureau of Labor Statistics
IA4 Youth Unemployment and Middle-Aged Unemployment. The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs and to 17.834 million in 2012 or 2.207 million fewer jobs. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.914 million in Jul 2006 with 19.461 million in Jul 2012 for 2.453 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 21.268 million in Jun 2006 to 19.125 million in Jun 2013 or by 2.143 million. The civilian noninstitutional population increased ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.858 million in Jun 2013 or by 1.415 million while the number of jobs for ages 16 to 24 years fell by 2.592 million from 21.717 million in Jul 2007 to 19.125 million in Jun 2013. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.
Table I-10, US, Employment Level 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Annual |
| 2001 | 19678 | 19745 | 19800 | 19778 | 19648 | 21212 | 20088 |
| 2002 | 18653 | 19074 | 19091 | 19108 | 19484 | 20828 | 19683 |
| 2003 | 18811 | 18880 | 18709 | 18873 | 19032 | 20432 | 19351 |
| 2004 | 18852 | 18841 | 18752 | 19184 | 19237 | 20587 | 19630 |
| 2005 | 18858 | 18670 | 18989 | 19071 | 19356 | 20949 | 19770 |
| 2006 | 19003 | 19182 | 19291 | 19406 | 19769 | 21268 | 20041 |
| 2007 | 19407 | 19415 | 19538 | 19368 | 19457 | 21098 | 19875 |
| 2008 | 18724 | 18546 | 18745 | 19161 | 19254 | 20466 | 19202 |
| 2009 | 17467 | 17606 | 17564 | 17739 | 17588 | 18726 | 17601 |
| 2010 | 16166 | 16412 | 16587 | 16764 | 17039 | 17920 | 17077 |
| 2011 | 16512 | 16638 | 16898 | 16970 | 17045 | 18180 | 17362 |
| 2012 | 16944 | 17150 | 17301 | 17387 | 17681 | 18907 | 17834 |
| 2013 | 17183 | 17257 | 17271 | 17593 | 17704 | 19125 |
Sources: US Bureau of Labor Statistics
Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2013. Employment level is sharply lower in Jun 2013 relative to the peak in 2007.
Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-21A provides the US civilian noninstitutional population ages 16 to 24 years not seasonally adjusted from 2001 to 2013. The civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.858 million in Jun 2013, by 1.415 million or 3.8 percent, while employment for ages 16 to 24 years fell from 21.717 million in Jul 2007 to 19.125 million in Jun 2013, by 2.592 million or decline of 11.9 percent.
Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-21B provides the civilian labor force of the US ages 16 to 24 years NSA from 2001 to 2013. The US civilian labor force ages 16 to 24 years fell from 24.339 million in Jul 2007 to 23.322 million in Jun 2013, by 1.017 million or decline of 4.2 percent, while the civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.858 million in Jun 2013, by 1.415 million or 3.8 percent. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.
Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-21C provides the ratio of labor force to noninstitutional population or labor force participation of ages 16 to 24 years not seasonally adjusted. The US labor force participation rates for ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.0 in Jun 2013 because of the frustration of young people who believe there may not be jobs available for them.
Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
An important measure of the job market is the number of people with jobs relative to population available for work or civilian noninstitutional population or employment/population ratio. Chart I-21D provides the employment population ratio for ages 16 to 24 years. The US employment/population ratio NSA collapsed from 59.2 in Jul 2006 to 49.2 in Jun 2013. Chart I-21D shows vertical drop during the global recession without recovery.
Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million and 3451 thousand in 2012 or by 1.109 million. The unemployment level ages 16 to 24 years rose from 2.883 million in Jun 2007 to 4.198 million in Jun 2013 or by 1.315 million. This situation may persist for many years.
Table I-11, US, Unemployment Level 16-24 Years, Thousands NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Annual |
| 2001 | 2250 | 2258 | 2253 | 2095 | 2171 | 2775 | 2371 |
| 2002 | 2754 | 2731 | 2822 | 2515 | 2568 | 3167 | 2683 |
| 2003 | 2748 | 2740 | 2601 | 2572 | 2838 | 3542 | 2746 |
| 2004 | 2767 | 2631 | 2588 | 2387 | 2684 | 3191 | 2638 |
| 2005 | 2661 | 2787 | 2520 | 2398 | 2619 | 3010 | 2521 |
| 2006 | 2366 | 2433 | 2216 | 2092 | 2254 | 2860 | 2353 |
| 2007 | 2363 | 2230 | 2096 | 2074 | 2203 | 2883 | 2342 |
| 2008 | 2633 | 2480 | 2347 | 2196 | 2952 | 3450 | 2830 |
| 2009 | 3278 | 3457 | 3371 | 3321 | 3851 | 4653 | 3760 |
| 2010 | 3983 | 3888 | 3748 | 3803 | 3854 | 4481 | 3857 |
| 2011 | 3851 | 3696 | 3520 | 3365 | 3628 | 4248 | 3634 |
| 2012 | 3416 | 3507 | 3294 | 3175 | 3438 | 4180 | 3451 |
| 2013 | 3674 | 3449 | 3261 | 3129 | 3478 | 4198 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-22 provides the unemployment level ages 16 to 24 from 2002 to 2012. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013.
Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Table I-12 provides the rate of unemployment of young peoples in ages 16 to 24 years. The annual rate jumped from 10.5 percent in 2007 to 18.4 percent in 2010, 17.3 percent in 2011 and 16.2 percent in 2012. During the seasonal peak in Jul the rate of youth unemployed was 18.1 percent in Jul 2011 and 17.1 percent in Jul 2012 compared with 10.8 percent in Jul 2007. The rate of youth unemployment rose from 11.9 in Jun 2006 to 18.0 percent in Jun 2013 and likely higher if adding those who ceased searching for a job in frustration none may be available.
Table I-12, US, Unemployment Rate 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Dec | Annual |
| 2001 | 10.3 | 10.3 | 10.2 | 9.6 | 10.0 | 11.6 | 10.5 | 11.0 | 10.6 |
| 2002 | 12.9 | 12.5 | 12.9 | 11.6 | 11.6 | 13.2 | 12.4 | 10.9 | 12.0 |
| 2003 | 12.7 | 12.7 | 12.2 | 12.0 | 13.0 | 14.8 | 13.3 | 10.5 | 12.4 |
| 2004 | 12.8 | 12.3 | 12.1 | 11.1 | 12.2 | 13.4 | 12.3 | 10.5 | 11.8 |
| 2005 | 12.4 | 13.0 | 11.7 | 11.2 | 11.9 | 12.6 | 11.0 | 9.4 | 11.3 |
| 2006 | 11.1 | 11.3 | 10.3 | 9.7 | 10.2 | 11.9 | 11.2 | 9.1 | 10.5 |
| 2007 | 10.9 | 10.3 | 9.7 | 9.7 | 10.2 | 12.0 | 10.8 | 10.7 | 10.5 |
| 2008 | 12.3 | 11.8 | 11.1 | 10.3 | 13.3 | 14.4 | 14.0 | 13.7 | 12.8 |
| 2009 | 15.8 | 16.4 | 16.1 | 15.8 | 18.0 | 19.9 | 18.5 | 17.5 | 17.6 |
| 2010 | 19.8 | 19.2 | 18.4 | 18.5 | 18.4 | 20.0 | 19.1 | 16.7 | 18.4 |
| 2011 | 18.9 | 18.2 | 17.2 | 16.5 | 17.5 | 18.9 | 18.1 | 15.5 | 17.3 |
| 2012 | 16.8 | 17.0 | 16.0 | 15.4 | 16.3 | 18.1 | 17.1 | 15.2 | 16.2 |
| 2013 | 17.6 | 16.7 | 15.9 | 15.1 | 16.4 | 18.0 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2001 to 2013. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels during the fourteen consecutive quarters of expansion of the economy since IIIQ2009 because of much lower growth at 2.1 percent annual equivalent on (Table I -5 http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.2 percent in 2012. The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2013. The rate of youth unemployment rose to 20 percent during the contractions of the early 1980s and also during the contraction of the global recession in 2008 and 2009. The data illustrate again the argument in this blog that the contractions of the early 1980s are the valid framework for comparison with the global recession of 2008 and 2009 instead of misleading comparisons with the 1930s. During the initial phase of recovery, the rate of youth unemployment 16 to 24 years NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984 while the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 17.5 percent in Dec 2009, 16.7 percent in Dec 2010, 15.5 percent in Dec 2011, 15.2 percent in Dec 2012, 17.6 percent in Jan 2013, 16.7 percent in Feb 2013, 15.9 percent in Mar 2013, 15.1 percent in Apr 2013, 16.4 percent in May 2013 and 18.0 percent in Jun 2013. In Jul 2007, the rate of youth unemployment was 10.8 percent, increasing to 17.1 percent in Jul 2012. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.1 percent on average during the first fourteen fifteen quarters of expansion from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The fractured US labor market denies an early start for young people.
Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
It is more difficult to move to other jobs after a certain age because of fewer available opportunities for mature individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.985 million in Jul 2006 to 4.821 million in July 2010 or by 142.9 percent. The number of unemployed ages 45 years and over declined to 4.405 million in Jul 2012 that is still higher by 121.9 percent than in Jul 2006. The number unemployed age 45 and over jumped from 1.794 million in Dec 2006 to 4.762 million in Dec 2010 or 165.4 percent. At 3.927 million in Dec 2012, mature unemployment is higher by 2.133 million or 118.9 percent higher than 1.794 million in Dec 2006. The level of unemployment of those aged 45 year or more of 3.648 million in Jun 2013 is higher by 1.843 million than 1.805 million in Jun 2007 or higher by 102.1 percent.
Table I-13, US, Unemployment Level 45 Years and Over, Thousands NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Dec | Annual |
| 2000 | 1498 | 1392 | 1291 | 1062 | 1074 | 1163 | 1217 | 1249 |
| 2001 | 1572 | 1587 | 1533 | 1421 | 1259 | 1371 | 1901 | 1576 |
| 2002 | 2235 | 2280 | 2138 | 2101 | 1999 | 2190 | 2210 | 2114 |
| 2003 | 2495 | 2415 | 2485 | 2287 | 2112 | 2212 | 2130 | 2253 |
| 2004 | 2453 | 2397 | 2354 | 2160 | 2025 | 2182 | 2086 | 2149 |
| 2005 | 2286 | 2286 | 2126 | 1939 | 1844 | 1868 | 1963 | 2009 |
| 2006 | 2126 | 2056 | 1881 | 1843 | 1784 | 1813 | 1794 | 1848 |
| 2007 | 2155 | 2138 | 2031 | 1871 | 1803 | 1805 | 2120 | 1966 |
| 2008 | 2336 | 2336 | 2326 | 2104 | 2095 | 2211 | 3485 | 2540 |
| 2009 | 4138 | 4380 | 4518 | 4172 | 4175 | 4505 | 4960 | 4500 |
| 2010 | 5314 | 5307 | 5194 | 4770 | 4565 | 4564 | 4762 | 4879 |
| 2011 | 5027 | 4837 | 4748 | 4373 | 4356 | 4559 | 4182 | 4537 |
| 2012 | 4458 | 4472 | 4390 | 4037 | 4083 | 4084 | 3927 | 4133 |
| 2013 | 4394 | 4107 | 3929 | 3689 | 3605 | 3648 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-25 provides the level unemployed ages 45 years and over. There was an increase in the recessions of the 1980s, 1991 and 2001 followed by declines to earlier levels. The current expansion of the economy after IIIQ2009 has not been sufficiently vigorous to reduce significantly middle-age unemployment.
Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
B Collapse of United States Dynamism of Income Growth and Employment Creation. There are four major approaches to the analysis of the depth of the financial crisis and global recession from IVQ2007 (Dec) to IIQ2009 (Jun) and the subpar recovery from IIIQ2009 (Jul) to the present IVQ2012:
(1) Deeper contraction and slower recovery in recessions with financial crises
(2) Counterfactual of avoiding deeper contraction by fiscal and monetary policies
(3) Counterfactual that the financial crises and global recession would have been avoided had economic policies been different
(4) Evidence that growth rates are higher after deeper recessions with financial crises.
A counterfactual consists of theory and measurements of what would have occurred otherwise if economic policies or institutional arrangements had been different. This task is quite difficult because economic data are observed with all effects as they actually occurred while the counterfactual attempts to evaluate how data would differ had policies and institutional arrangements been different (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008b), 125, 136; Pelaez 1979, 26-8). Counterfactual data are unobserved and must be calculated using theory and measurement methods. The measurement of costs and benefits of projects or applied welfare economics (Harberger 1971, 1997) specifies and attempts to measure projects such as what would be economic welfare with or without a bridge or whether markets would be more or less competitive in the absence of antitrust and regulation laws (Winston 2006). Counterfactuals were used in the “new economic history” of the United States to measure the economy with or without railroads (Fishlow 1965, Fogel 1964) and also in analyzing slavery (Fogel and Engerman 1974). A critical counterfactual in economic history is how Britain surged ahead of France (North and Weingast 1989). These four approaches are discussed below in turn followed with comparison of the two recessions of the 1980s from IQ1980 (Jan) to IIIQ1980 (Jul) and from IIIQ1981 (Jul) to IVQ1982 (Nov) as dated by the National Bureau of Economic Research (NBER http://www.nber.org/cycles.html). These comparisons are not idle exercises, defining the interpretation of history and even possibly critical policies and institutional arrangements. There is active debate on these issues (Bordo 2012Oct 21 http://www.bloomberg.com/news/2012-10-21/why-this-u-s-recovery-is-weaker.html Reinhart and Rogoff, 2012Oct14 http://www.economics.harvard.edu/faculty/rogoff/files/Is_US_Different_RR_3.pdf Taylor 2012Oct 25 http://www.johnbtaylorsblog.blogspot.co.uk/2012/10/an-unusually-weak-recovery-as-usually.html, Wolf 2012Oct23 http://www.ft.com/intl/cms/s/0/791fc13a-1c57-11e2-a63b-00144feabdc0.html#axzz2AotsUk1q).
(1) Lower Growth Rates in Recoveries from Recessions with Financial Crises. A monumental effort of data gathering, calculation and analysis by Professors Carmen M. Reinhart and Kenneth Rogoff at Harvard University is highly relevant to banking crises, financial crash, debt crises and economic growth (Reinhart 2010CB; Reinhart and Rogoff 2011AF, 2011Jul14, 2011EJ, 2011CEPR, 2010FCDC, 2010GTD, 2009TD, 2009AFC, 2008TDPV; see also Reinhart and Reinhart 2011Feb, 2010AF and Reinhart and Sbrancia 2011). See http://cmpassocregulationblog.blogspot.com/2011/07/debt-and-financial-risk-aversion-and.html. The dataset of Reinhart and Rogoff (2010GTD, 1) is quite unique in breadth of countries and over time periods:
“Our results incorporate data on 44 countries spanning about 200 years. Taken together, the data incorporate over 3,700 annual observations covering a wide range of political systems, institutions, exchange rate and monetary arrangements and historic circumstances. We also employ more recent data on external debt, including debt owed by government and by private entities.”
Reinhart and Rogoff (2010GTD, 2011CEPR) classify the dataset of 2317 observations into 20 advanced economies and 24 emerging market economies. In each of the advanced and emerging categories, the data for countries is divided into buckets according to the ratio of gross central government debt to GDP: below 30, 30 to 60, 60 to 90 and higher than 90 (Reinhart and Rogoff 2010GTD, Table 1, 4). Median and average yearly percentage growth rates of GDP are calculated for each of the buckets for advanced economies. There does not appear to be any relation for debt/GDP ratios below 90. The highest growth rates are for debt/GDP ratios below 30: 3.7 percent for the average and 3.9 for the median. Growth is significantly lower for debt/GDP ratios above 90: 1.7 for the average and 1.9 percent for the median. GDP growth rates for the intermediate buckets are in a range around 3 percent: the highest 3.4 percent average is for the bucket 60 to 90 and 3.1 percent median for 30 to 60. There is even sharper contrast for the United States: 4.0 percent growth for debt/GDP ratio below 30; 3.4 percent growth for debt/GDP ratio of 30 to 60; 3.3 percent growth for debt/GDP ratio of 60 to 90; and minus 1.8 percent, contraction, of GDP for debt/GDP ratio above 90.
For the five countries with systemic financial crises—Iceland, Ireland, UK, Spain and the US—real average debt levels have increased by 75 percent between 2007 and 2009 (Reinhart and Rogoff 2010GTD, Figure 1). The cumulative increase in public debt in the three years after systemic banking crisis in a group of episodes after World War II is 86 percent (Reinhart and Rogoff 2011CEPR, Figure 2, 10).
An important concept is “this time is different syndrome,” which “is rooted in the firmly-held belief that financial crises are something that happens to other people in other countries at other times; crises do not happen here and now to us” (Reinhart and Rogoff 2010FCDC, 9). There is both an arrogance and ignorance in “this time is different” syndrome, as explained by Reinhart and Rogoff (2010FCDC, 34):
“The ignorance, of course, stems from the belief that financial crises happen to other people at other time in other places. Outside a small number of experts, few people fully appreciate the universality of financial crises. The arrogance is of those who believe they have figured out how to do things better and smarter so that the boom can long continue without a crisis.”
There is sober warning by Reinhart and Rogoff (2011CEPR, 42) based on the momentous effort of their scholarly data gathering, calculation and analysis:
“Despite considerable deleveraging by the private financial sector, total debt remains near its historic high in 2008. Total public sector debt during the first quarter of 2010 is 117 percent of GDP. It has only been higher during a one-year stint at 119 percent in 1945. Perhaps soaring US debt levels will not prove to be a drag on growth in the decades to come. However, if history is any guide, that is a risky proposition and over-reliance on US exceptionalism may only be one more example of the “This Time is Different” syndrome.”
As both sides of the Atlantic economy maneuver around defaults, the experience on debt and growth deserves significant emphasis in research and policy. The world economy is slowing with high levels of unemployment in advanced economies. Countries do not grow themselves out of unsustainable debts but rather through de facto defaults by means of financial repression and in some cases through inflation. The conclusion is that this time is not different.
Professor Alan M. Taylor (2012) at the University of Virginia analyzes own and collaborative research on 140 years of history with data from 14 advanced economies in the effort to elucidate experience preceding, during and after financial crises. The conclusion is (Allan M. Taylor 2012, 8):
“Recessions might be painful, but they tend to be even more painful when combined with financial crises or (worse) global crises, and we already know that post-2008 experience will not overturn this conclusion. The impact on credit is also very strong: financial crises lead to strong setbacks in the rate of growth of loans as compared to what happens in normal recessions, and this effect is strong for global crises. Finally, inflation generally falls in recessions, but the downdraft is stronger in financial crisis times.”
Alan M. Taylor (2012) also finds that advanced economies entered the global recession with the largest financial sector in history. There was doubling after 1980 of the ratio of loans to GDP and tripling of the size of bank balance sheets. In contrast, in the period from 1950 to 1970 there was high investment, savings and growth in advanced economies with firm regulation of finance and controls of foreign capital flows.
(2) Counterfactual of the Global Recession. There is a difficult decision on when to withdraw the fiscal stimulus that could have adverse consequences on current growth and employment analyzed by Krugman (2011Jun18). CBO (2011JunLTBO, Chapter 2) considers the timing of withdrawal as well as the equally tough problems that result from not taking prompt action to prevent a possible debt crisis in the future. Krugman (2011Jun18) refers to Eggertsson and Krugman (2010) on the possible contractive effects of debt. The world does not become poorer as a result of debt because an individual’s asset is another’s liability. Past levels of credit may become unacceptable by credit tightening, such as during a financial crisis. Debtors are forced into deleveraging, which results in expenditure reduction, but there may not be compensatory effects by creditors who may not be in need of increasing expenditures. The economy could be pushed toward the lower bound of zero interest rates, or liquidity trap, remaining in that threshold of deflation and high unemployment.
Analysis of debt can lead to the solution of the timing of when to cease stimulus by fiscal spending (Krugman 2011Jun18). Excessive debt caused the financial crisis and global recession and it is difficult to understand how more debt can recover the economy. Krugman (2011Jun18) argues that the level of debt is not important because one individual’s asset is another individual’s liability. The distribution of debt is important when economic agents with high debt levels are encountering different constraints than economic agents with low debt levels. The opportunity for recovery may exist in borrowing by some agents that can adjust the adverse effects of past excessive borrowing by other agents. As Krugman (2011Jun18, 20) states:
“Suppose, in particular, that the government can borrow for a while, using the borrowed money to buy useful things like infrastructure. The true social cost of these things will be very low, because the spending will be putting resources that would otherwise be unemployed to work. And government spending will also make it easier for highly indebted players to pay down their debt; if the spending is sufficiently sustained, it can bring the debtors to the point where they’re no longer so severely balance-sheet constrained, and further deficit spending is no longer required to achieve full employment. Yes, private debt will in part have been replaced by public debt – but the point is that debt will have been shifted away from severely balance-sheet-constrained players, so that the economy’s problems will have been reduced even if the overall level of debt hasn’t fallen. The bottom line, then, is that the plausible-sounding argument that debt can’t cure debt is just wrong. On the contrary, it can – and the alternative is a prolonged period of economic weakness that actually makes the debt problem harder to resolve.”
Besides operational issues, the consideration of this argument would require specifying and measuring two types of gains and losses from this policy: (1) the benefits in terms of growth and employment currently; and (2) the costs of postponing the adjustment such as in the exercise by CBO (2011JunLTO, 28-31) in Table 11. It may be easier to analyze the costs and benefits than actual measurement.
An analytical and empirical approach is followed by Blinder and Zandi (2010), using the Moody’s Analytics model of the US economy with four different scenarios: (1) baseline with all policies used; (2) counterfactual including all fiscal stimulus policies but excluding financial stimulus policies; (3) counterfactual including all financial stimulus policies but excluding fiscal stimulus; and (4) a scenario excluding all policies. The scenario excluding all policies is an important reference or the counterfactual of what would have happened if the government had been entirely inactive. A salient feature of the work by Blinder and Zandi (2010) is the consideration of both fiscal and financial policies. There was probably more activity with financial policies than with fiscal policies. Financial policies included the Fed balance sheet, 11 facilities of direct credit to illiquid segments of financial markets, interest rate policy, the Financial Stability Plan including stress tests of banks, the Troubled Asset Relief Program (TARP) and others (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 157-67; Regulation of Banks and Finance (2009a), 224-7).
Blinder and Zandi (2010, 4) find that:
“In the scenario that excludes all the extraordinary policies, the downturn continues into 2011. Real GDP falls a stunning 7.4% in 2009 and another 3.7% in 2010 (see Table 3). The peak-to-trough decline in GDP is therefore close to 12%, compared to an actual decline of about 4%. By the time employment hits bottom, some 16.6 million jobs are lost in this scenario—about twice as many as actually were lost. The unemployment rate peaks at 16.5%, and although not determined in this analysis, it would not be surprising if the underemployment rate approached one-fourth of the labor force. The federal budget deficit surges to over $2 trillion in fiscal year 2010, $2.6 trillion in fiscal year 2011, and $2.25 trillion in FY 2012. Remember, this is with no policy response. With outright deflation in prices and wages in 2009-2011, this dark scenario constitutes a 1930s-like depression.”
The conclusion by Blinder and Zandi (2010) is that if the US had not taken massive fiscal and financial measures the economy could have suffered far more during a prolonged period. There are still a multitude of questions that cloud understanding of the impact of the recession and what would have happened without massive policy impulses. Some effects are quite difficult to measure. An important argument by Blinder and Zandi (2010) is that this evaluation of counterfactuals is relevant to the need of stimulus if economic conditions worsened again.
(3) Counterfactual of Policies Causing the Financial Crisis and Global Recession. The counterfactual of avoidance of deeper and more prolonged contraction by fiscal and monetary policies is not the critical issue. As Professor John B. Taylor (2012Oct25) argues the critically important counterfactual is that the financial crisis and global recession would have not occurred in the first place if different economic policies had been followed. The counterfactual intends to verify that a combination of housing policies and discretionary monetary policies instead of rules (Taylor 1993) caused, deepened and prolonged the financial crisis (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB; see http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html) and that the experience resembles that of the Great Inflation of the 1960s and 1970s with stop-and-go growth/inflation that coined the term stagflation (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I).
The explanation of the sharp contraction of United States housing can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:
“On the maturity date T, the firm must either pay the promised payment of B to the debtholders or else the current equity will be valueless. Clearly, if at time T, V(T) > B, the firm should pay the bondholders because the value of equity will be V(T) – B > 0 whereas if they do not, the value of equity would be zero. If V(T) ≤ B, then the firm will not make the payment and default the firm to the bondholders because otherwise the equity holders would have to pay in additional money and the (formal) value of equity prior to such payments would be (V(T)- B) < 0.”
Pelaez and Pelaez (The Global Recession Risk (2007), 208-9) apply this analysis to the US housing market in 2005-2006 concluding:
“The house market [in 2006] is probably operating with low historical levels of individual equity. There is an application of structural models [Duffie and Singleton 2003] to the individual decisions on whether or not to continue paying a mortgage. The costs of sale would include realtor and legal fees. There could be a point where the expected net sale value of the real estate may be just lower than the value of the mortgage. At that point, there would be an incentive to default. The default vulnerability of securitization is unknown.”
There are multiple important determinants of the interest rate: “aggregate wealth, the distribution of wealth among investors, expected rate of return on physical investment, taxes, government policy and inflation” (Ingersoll 1987, 405). Aggregate wealth is a major driver of interest rates (Ibid, 406). Unconventional monetary policy, with zero fed funds rates and flattening of long-term yields by quantitative easing, causes uncontrollable effects on risk taking that can have profound undesirable effects on financial stability. Excessively aggressive and exotic monetary policy is the main culprit and not the inadequacy of financial management and risk controls.
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 restatement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption decisions is the long-run expected yield from wealth r*W. This yield was named permanent income: Y* = r*W” (Darby 1974, 229), where * denotes permanent. The simplified relation of income and wealth can be restated as:
W = Y/r (1)
Equation (1) shows that as r goes to zero, r →0, W grows without bound, W→∞.
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 but 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 close to zero interest rates, 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 used in 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 intended 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).
There are significant elements of the theory of bank financial fragility of Diamond and Dybvig (1983) and Diamond and Rajan (2000, 2001a, 2001b) that help to explain the financial fragility of banks during the credit/dollar crisis (see also Diamond 2007). The theory of Diamond and Dybvig (1983) as exposed by Diamond (2007) is that banks funding with demand deposits have a mismatch of liquidity (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 58-66). A run occurs when too many depositors attempt to withdraw cash at the same time. All that is needed is an expectation of failure of the bank. Three important functions of banks are providing evaluation, monitoring and liquidity transformation. Banks invest in human capital to evaluate projects of borrowers in deciding if they merit credit. The evaluation function reduces adverse selection or financing projects with low present value. Banks also provide important monitoring services of following the implementation of projects, avoiding moral hazard that funds be used for, say, real estate speculation instead of the original project of factory construction. The transformation function of banks involves both assets and liabilities of bank balance sheets. Banks convert an illiquid asset or loan for a project with cash flows in the distant future into a liquid liability in the form of demand deposits that can be withdrawn immediately.
In the theory of banking of Diamond and Rajan (2000, 2001a, 2001b), the bank creates liquidity by tying human assets to capital. The collection of skills of the relationship banker converts an illiquid project of an entrepreneur into liquid demand deposits that are immediately available for withdrawal. The deposit/capital structure is fragile because of the threat of bank runs. In these days of online banking, the run on Washington Mutual was through withdrawals online. A bank run can be triggered by the decline of the value of bank assets below the value of demand deposits.
Pelaez and Pelaez (Regulation of Banks and Finance 2009b, 60, 64-5) find immediate application of the theories of banking of Diamond, Dybvig and Rajan to the credit/dollar crisis after 2007. It is a credit crisis because the main issue was the deterioration of the credit portfolios of securitized banks because of default of subprime mortgages. It is a dollar crisis because of the weakening dollar resulting from relatively low interest rate policies of the US. It caused systemic effects that converted into a global recession not only because of the huge weight of the US economy in the world economy but also because the credit crisis transferred to the UK and Europe. Management skills or human capital of banks are illustrated by financial engineering of complex products. The increasing importance of human relative to inanimate capital (Rajan and Zingales 2000) is revolutionizing the theory of the firm (Zingales 2000) and corporate governance (Rajan and Zingales 2001). Finance is one of the most important examples of this transformation. Bank charters were the source of profits in the original banking institution. Pricing and structuring financial instruments was revolutionized with option pricing formulas developed by Black and Scholes (1973) and Merton (1973, 1974, 1998) that permitted the development of complex products with fair pricing. The successful financial company must attract and retain finance professionals who have invested in human capital, which is a sunk cost to them and not of the institution where they work.
The complex financial products created for securitized banking with high investments in human capital are based on houses, which are as illiquid as the projects of entrepreneurs in the theory of banking. The liquidity fragility of the securitized bank is equivalent to that of the commercial bank in the theory of banking (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65). Banks created off-balance sheet structured investment vehicles (SIV) that issued commercial paper receiving AAA rating because of letters of liquidity guarantee by the banks. The commercial paper was converted into liquidity by its use as collateral in SRPs at the lowest rates and minimal haircuts because of the AAA rating of the guarantor bank. In the theory of banking, default can be triggered when the value of assets is perceived as lower than the value of the deposits. Commercial paper issued by SIVs, securitized mortgages and derivatives all obtained SRP liquidity based on illiquid home mortgage loans at the bottom of the pyramid. The run on the securitized bank had a clear origin (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65):
“The increasing default of mortgages resulted in an increase in counterparty risk. Banks were hit by the liquidity demands of their counterparties. The liquidity shock extended to many segments of the financial markets—interbank loans, asset-backed commercial paper (ABCP), high-yield bonds and many others—when counterparties preferred lower returns of highly liquid safe havens, such as Treasury securities, than the risk of having to sell the collateral in SRPs at deep discounts or holding an illiquid asset. The price of an illiquid asset is near zero.”
Gorton and Metrick (2010H, 507) provide a revealing quote to the work in 1908 of Edwin R. A. Seligman, professor of political economy at Columbia University, founding member of the American Economic Association and one of its presidents and successful advocate of progressive income taxation. The intention of the quote is to bring forth the important argument that financial crises are explained in terms of “confidence” but as Professor Seligman states in reference to historical banking crises in the US, the important task is to explain what caused the lack of confidence. It is instructive to repeat the more extended quote of Seligman (1908, xi) on the explanations of banking crises:
“The current explanations may be divided into two categories. Of these the first includes what might be termed the superficial theories. Thus it is commonly stated that the outbreak of a crisis is due to lack of confidence,--as if the lack of confidence was not in itself the very thing which needs to be explained. Of still slighter value is the attempt to associate a crisis with some particular governmental policy, or with some action of a country’s executive. Such puerile interpretations have commonly been confined to countries like the United States, where the political passions of democracy have had the fullest way. Thus the crisis of 1893 was ascribed by the Republicans to the impending Democratic tariff of 1894; and the crisis of 1907 has by some been termed the ‘[Theodore] Roosevelt panic,” utterly oblivious of the fact that from the time of President Jackson, who was held responsible for the troubles of 1837, every successive crisis had had its presidential scapegoat, and has been followed by a political revulsion. Opposed to these popular, but wholly unfounded interpretations, is the second class of explanations, which seek to burrow beneath the surface and to discover the more occult and fundamental causes of the periodicity of crises.”
Scholars ignore superficial explanations in the effort to seek good and truth. The problem of economic analysis of the credit/dollar crisis is the lack of a structural model with which to attempt empirical determination of causes (Gorton and Metrick 2010SB). There would still be doubts even with a well-specified structural model because samples of economic events do not typically permit separating causes and effects. There is also confusion is separating the why of the crisis and how it started and propagated, all of which are extremely important.
In true heritage of the principles of Seligman (1908), Gorton (2009EFM) discovers a prime causal driver of the credit/dollar crisis. The objective of subprime and Alt-A mortgages was to facilitate loans to populations with modest means so that they could acquire a home. These borrowers would not receive credit because of (1) lack of funds for down payments; (2) low credit rating and information; (3) lack of information on income; and (4) errors or lack of other information. Subprime mortgage “engineering” was based on the belief that both lender and borrower could benefit from increases in house prices over the short run. The initial mortgage would be refinanced in two or three years depending on the increase of the price of the house. According to Gorton (2009EFM, 13, 16):
“The outstanding amounts of Subprime and Alt-A [mortgages] combined amounted to about one quarter of the $6 trillion mortgage market in 2004-2007Q1. Over the period 2000-2007, the outstanding amount of agency mortgages doubled, but subprime grew 800%! Issuance in 2005 and 2006 of Subprime and Alt-A mortgages was almost 30% of the mortgage market. Since 2000 the Subprime and Alt-A segments of the market grew at the expense of the Agency (i.e., the government sponsored entities of Fannie Mae and Freddie Mac) share, which fell from almost 80% (by outstanding or issuance) to about half by issuance and 67% by outstanding amount. The lender’s option to rollover the mortgage after an initial period is implicit in the subprime mortgage. The key design features of a subprime mortgage are: (1) it is short term, making refinancing important; (2) there is a step-up mortgage rate that applies at the end of the first period, creating a strong incentive to refinance; and (3) there is a prepayment penalty, creating an incentive not to refinance early.”
The prime objective of successive administrations in the US during the past 20 years and actually since the times of Roosevelt in the 1930s has been to provide “affordable” financing for the “American dream” of home ownership. The US housing finance system is mixed with public, public/private and purely private entities. Congress established the Federal Home Loan Bank (FHLB) system in 1932 that also created the Federal Housing Administration in 1934 with the objective of insuring homes against default. In 1938, the government created the Federal National Mortgage Association, or Fannie Mae, to foster a market for FHA-insured mortgages. Government-insured mortgages were transferred from Fannie Mae to the Government National Mortgage Association, or Ginnie Mae, to permit Fannie Mae to become a publicly owned company. Securitization of mortgages began in 1970 with the government charter to the Federal Home Loan Mortgage Corporation, or Freddie Mac, with the objective of bundling mortgages created by thrift institutions that would be marketed as bonds with guarantees by Freddie Mac (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 42-8). In the third quarter of 2008, total mortgages in the US were $12,057 billion of which 43.5 percent, or $5423 billion, were retained or guaranteed by Fannie Mae and Freddie Mac (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 45). In 1990, Fannie Mae and Freddie Mac had a share of only 25.4 percent of total mortgages in the US. Mortgages in the US increased from $6922 billion in 2002 to $12,088 billion in 2007, or by 74.6 percent, while the retained or guaranteed portfolio of Fannie and Freddie rose from $3180 billion in 2002 to $4934 billion in 2007, or by 55.2 percent.
According to Pinto (2008) in testimony to Congress:
“There are approximately 25 million subprime and Alt-A loans outstanding, with an unpaid principal amount of over $4.5 trillion, about half of them held or guaranteed by Fannie and Freddie. Their high risk activities were allowed to operate at 75:1 leverage ratio. While they may deny it, there can be no doubt that Fannie and Freddie now own or guarantee $1.6 trillion in subprime, Alt-A and other default prone loans and securities. This comprises over 1/3 of their risk portfolios and amounts to 34% of all the subprime loans and 60% of all Alt-A loans outstanding. These 10.5 million unsustainable, nonprime loans are experiencing a default rate 8 times the level of the GSEs’ 20 million traditional quality loans. The GSEs will be responsible for a large percentage of an estimated 8.8 million foreclosures expected over the next 4 years, accounting for the failure of about 1 in 6 home mortgages. Fannie and Freddie have subprimed America.”
In perceptive analysis of growth and macroeconomics in the past six decades, Rajan (2012FA) argues that “the West can’t borrow and spend its way to recovery.” The Keynesian paradigm is not applicable in current conditions. Advanced economies in the West could be divided into those that reformed regulatory structures to encourage productivity and others that retained older structures. In the period from 1950 to 2000, Cobet and Wilson (2002) find that US productivity, measured as output/hour, grew at the average yearly rate of 2.9 percent while Japan grew at 6.3 percent and Germany at 4.7 percent (see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). In the period from 1995 to 2000, output/hour grew at the average yearly rate of 4.6 percent in the US but at lower rates of 3.9 percent in Japan and 2.6 percent in Germany. Rajan (2012FA) argues that the differential in productivity growth was accomplished by deregulation in the US at the end of the 1970s and during the 1980s. In contrast, Europe did not engage in reform with the exception of Germany in the early 2000s that empowered the German economy with significant productivity advantage. At the same time, technology and globalization increased relative remunerations in highly skilled, educated workers relative to those without skills for the new economy. It was then politically appealing to improve the fortunes of those left behind by the technological revolution by means of increasing cheap credit. As Rajan (2012FA) argues:
“In 1992, Congress passed the Federal Housing Enterprises Financial Safety and Soundness Act, partly to gain more control over Fannie Mae and Freddie Mac, the giant private mortgage agencies, and partly to promote affordable homeownership for low-income groups. Such policies helped money flow to lower-middle-class households and raised their spending—so much so that consumption inequality rose much less than income inequality in the years before the crisis. These policies were also politically popular. Unlike when it came to an expansion in government welfare transfers, few groups opposed expanding credit to the lower-middle class—not the politicians who wanted more growth and happy constituents, not the bankers and brokers who profited from the mortgage fees, not the borrowers who could now buy their dream houses with virtually no money down, and not the laissez-faire bank regulators who thought they could pick up the pieces if the housing market collapsed. The Federal Reserve abetted these shortsighted policies. In 2001, in response to the dot-com bust, the Fed cut short-term interest rates to the bone. Even though the overstretched corporations that were meant to be stimulated were not interested in investing, artificially low interest rates acted as a tremendous subsidy to the parts of the economy that relied on debt, such as housing and finance. This led to an expansion in housing construction (and related services, such as real estate brokerage and mortgage lending), which created jobs, especially for the unskilled. Progressive economists applauded this process, arguing that the housing boom would lift the economy out of the doldrums. But the Fed-supported bubble proved unsustainable. Many construction workers have lost their jobs and are now in deeper trouble than before, having also borrowed to buy unaffordable houses. Bankers obviously deserve a large share of the blame for the crisis. Some of the financial sector’s activities were clearly predatory, if not outright criminal. But the role that the politically induced expansion of credit played cannot be ignored; it is the main reason the usual checks and balances on financial risk taking broke down.”
In fact, Raghuram G. Rajan (2005) anticipated low liquidity in financial markets resulting from low interest rates before the financial crisis that caused distortions of risk/return decisions provoking the credit/dollar crisis and global recession from IVQ2007 to IIQ2009. Near zero interest rates of unconventional monetary policy induced excessive risks and low liquidity in financial decisions that were critical as a cause of the credit/dollar crisis after 2007. Rajan (2012FA) argues that it is not feasible to return to the employment and income levels before the credit/dollar crisis because of the bloated construction sector, financial system and government budgets.
(4) Historically Sharper Recoveries from Deeper Contractions and Financial Crises. Professor Michael D. Bordo (2012Sep27), at Rutgers University, is providing clear thought on the correct comparison of the current business cycles in the United States with those in United States history. There are two issues raised by Professor Bordo: (1) lumping together countries with different institutions, economic policies and financial systems; and (2) the conclusion that growth is mediocre after financial crises and deep recessions, which is repeated daily in the media, but that Bordo and Haubrich (2012DR) persuasively demonstrate to be inconsistent with United States experience.
Depriving economic history of institutions is perilous as is illustrated by the economic history of Brazil. Douglass C. North (1994) emphasized the key role of institutions in explaining economic history. Rondo E. Cameron (1961, 1967, 1972) applied institutional analysis to banking history. Friedman and Schwartz (1963) analyzed the relation of money, income and prices in the business cycle and related the monetary policy of an important institution, the Federal Reserve System, to the Great Depression. Bordo, Choudhri and Schwartz (1995) analyze the counterfactual of what would have been economic performance if the Fed had used during the Great Depression the Friedman (1960) monetary policy rule of constant growth of money (for analysis of the Great Depression see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 198-217). Alan Meltzer (2004, 2010a,b) analyzed the Federal Reserve System over its history. The reader would be intrigued by Figure 5 in Reinhart and Rogoff (2010FCDC, 15) in which Brazil is classified in external default for seven years between 1828 and 1834 but not again until 64 years later in 1989, above the 50 years of incidence for “serial default”. William R. Summerhill, Jr. (2007SC, 2007IR) has filled this void in scholarly research on nineteenth-century Brazil. There are important conclusions by Summerhill on the exceptional sample of institutional change or actually lack of change, public finance and financial repression in Brazil between 1822 and 1899, combining tools of economics, political science and history. During seven continuous decades, Brazil did not miss a single interest payment with government borrowing without repudiation of debt or default. What is surprising is that Brazil borrowed by means of long-term bonds and, even more surprising, interest rates fell over time. The external debt of Brazil in 1870 was ₤41,275,961 and the domestic debt in the internal market was ₤25,708,711, or 62.3 percent of the total (Summerhill 2007IR, 73).
The experience of Brazil differed from that of Latin America (Summerhill 2007IR). During the six decades when Brazil borrowed without difficulty, Latin American countries becoming independent after 1820 engaged in total defaults, suffering hardship in borrowing abroad. The countries that borrowed again fell again in default during the nineteenth century. Venezuela defaulted in four occasions. Mexico defaulted in 1827, rescheduling its debt eight different times and servicing the debt sporadically. About 44 percent of Latin America’s sovereign debt was in default in 1855 and approximately 86 percent of total government loans defaulted in London originated in Spanish American borrowing countries.
External economies of commitment to secure private rights in sovereign credit would encourage development of private financial institutions, as postulated in classic work by North and Weingast (1989), Summerhill (2007IR, 22). This is how banking institutions critical to the Industrial Revolution were developed in England (Cameron 1967). The obstacle in Brazil found by Summerhill (2007IR) is that sovereign debt credibility was combined with financial repression. There was a break in Brazil of the chain of effects from protecting public borrowing, as in North and Weingast (1989), to development of private financial institutions.
Nicia Villela Luz and Carlos Manuel Peláez (1972, 276) find that:
“The lack of interest on historical moments by economists may explain their emphasis on secular trends in their research on the past instead of changes in the historical process. This may be the origin of why they fill gaps in documentation with their extrapolations.”
According to Pelaez 1976, 283) following Cameron:
“The banking law of 1860 placed severe restrictions on two basic modern economic institutions—the corporation and the commercial bank. The growth of the volume of bank credit was one of the most significant factors of financial intermediation and economic growth in the major trading countries of the gold standard group. But Brazil placed strong restrictions on the development of banking and intermediation functions, preventing the channeling of coffee savings into domestic industry at an earlier date.”
Brazil actually abandoned the gold standard during multiple financial crises in the nineteenth century, as it should have to protect domestic economic activity. Pelaez (1975, 447) finds similar experience in the first half of nineteenth-century Brazil:
“Brazil’s experience is particularly interesting in that in the period 1808-1851 there were three types of monetary systems. Between 1808 and 1829, there was only one government-related Bank of Brazil, enjoying a perfect monopoly of banking services. No new banks were established in the 1830s after the liquidation of the Bank of Brazil in 1829. During the coffee boom in the late 1830s and 1840s, a system of banks of issue, patterned after similar institutions in the industrial countries [Cameron 1967], supplied the financial services required in the first stage of modernization of the export economy.”
Financial crises in the advanced economies were transmitted to nineteenth-century Brazil by the arrival of a ship (Pelaez and Suzigan 1981). The explanation of those crises and the economy of Brazil requires knowledge and roles of institutions, economic policies and the financial system chosen by Brazil, in agreement with Bordo (2012Sep27).
The departing theoretical framework of Bordo and Haubrich (2012DR) is the plucking model of Friedman (1964, 1988). Friedman (1988, 1) recalls “I was led to the model in the course of investigating the direction of influence between money and income. Did the common cyclical fluctuation in money and income reflect primarily the influence of money on income or of income on money?” Friedman (1964, 1988) finds useful for this purpose to analyze the relation between expansions and contractions. Analyzing the business cycle in the United States between 1870 and 1961, Friedman (1964, 15) found that “a large contraction in output tends to be followed on the average by a large business expansion; a mild contraction, by a mild expansion.” The depth of the contraction opens up more room in the movement toward full employment (Friedman 1964, 17):
“Output is viewed as bumping along the ceiling of maximum feasible output except that every now and then it is plucked down by a cyclical contraction. Given institutional rigidities and prices, the contraction takes in considerable measure the form of a decline in output. Since there is no physical limit to the decline short of zero output, the size of the decline in output can vary widely. When subsequent recovery sets in, it tends to return output to the ceiling; it cannot go beyond, so there is an upper limit to output and the amplitude of the expansion tends to be correlated with the amplitude of the contraction.”
Kim and Nelson (1999) test the asymmetric plucking model of Friedman (1964, 1988) relative to a symmetric model using reference cycles of the NBER and find evidence supporting the Friedman model. Bordo and Haubrich (2012DR) analyze 27 cycles beginning in 1872, using various measures of financial crises while considering different regulatory and monetary regimes. The revealing conclusion of Bordo and Haubrich (2012DR, 2) is that:
“Our analysis of the data shows that steep expansions tend to follow deep contractions, though this depends heavily on when the recovery is measured. In contrast to much conventional wisdom, the stylized fact that deep contractions breed strong recoveries is particularly true when there is a financial crisis. In fact, on average, it is cycles without a financial crisis that show the weakest relation between contraction depth and recovery strength. For many configurations, the evidence for a robust bounce-back is stronger for cycles with financial crises than those without.”
The average rate of growth of real GDP in expansions after recessions with financial crises was 8 percent but only 6.9 percent on average for recessions without financial crises (Bordo 2012Sep27). Real GDP declined 12 percent in the Panic of 1907 and increased 13 percent in the recovery, consistent with the plucking model of Friedman (Bordo 2012Sep27). Bordo (2012Sep27) finds two probable explanations for the weak recovery during the current economic cycle: (1) collapse of United States housing; and (2) uncertainty originating in fiscal policy, regulation and structural changes. There are serious doubts if monetary policy is adequate to recover the economy under these conditions.
Lucas (2011May) estimates US economic growth in the long-term at 3 percent per year and about 2 percent per year in per capita terms. There are displacements from this trend caused by events such as wars and recessions but the economy then returns to trend. Historical US GDP data exhibit remarkable growth: Lucas (2011May) estimates an increase of US real income per person by a factor of 12 in the period from 1870 to 2010. The explanation by Lucas (2011May) of this remarkable growth experience is that government provided stability and education while elements of “free-market capitalism” were an important driver of long-term growth and prosperity. The analysis is sharpened by comparison with the long-term growth experience of G7 countries (US, UK, France, Germany, Canada, Italy and Japan) and Spain from 1870 to 2010. Countries benefitted from “common civilization” and “technology” to “catch up” with the early growth leaders of the US and UK, eventually growing at a faster rate. Significant part of this catch up occurred after World War II. Lucas (2011May) finds that the catch up stalled in the 1970s. The analysis of Lucas (2011May) is that the 20-40 percent gap that developed originated in differences in relative taxation and regulation that discouraged savings and work incentives in comparison with the US. A larger welfare and regulatory state, according to Lucas (2011May), could be the cause of the 20-40 percent gap. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. The key indicator of growth of real income per capita, or what is earned per person after inflation, measures long-term economic growth and prosperity. A refined concept would include real disposable income per capita, or what a person earns after inflation and taxes.
Table IB-1 provides the data required for broader comparison of the cyclical expansions of IQ1983 to IIIQ1986 and the current one from 2009 to 2012. First, in the 13 quarters from IQ1983 to IQ1986: GDP increased 19.6 percent at the annual equivalent rate of 5.7 percent; real disposable personal income (RDPI) increased 14.9 percent at the annual equivalent rate of 4.4 percent; RDPI per capita increased 11.9 percent at the annual equivalent rate of 3.5 percent; and population increased 2.7 percent at the annual equivalent rate of 0.8 percent. In the 15 quarters from IQ1983 to IQ1II986: GDP increased 21.3 percent at the annual equivalent rate of 5.3 percent; real disposable personal income (RDPI) increased 16.9 percent at the annual equivalent rate of 4.2 percent; RDPI per capita increased 13.3 percent at the annual equivalent rate of 3.4 percent; and population increased 3.2 percent at the annual equivalent rate of 0.8 percent Second, in the 15 quarters of the current cyclical expansion from IIIQ2009 to IQ2013, GDP increased 8.1 percent at the annual equivalent rate of 2.1 percent. In the 15 quarters of cyclical expansion: real disposable personal income (RDPI) increased 5.3 percent at the annual equivalent rate of 1.4 percent; RDPI per capita increased 2.6 percent at the annual equivalent rate of 0.7 percent; and population increased 2.6 percent at the annual equivalent rate of 0.7 percent. Third, since the beginning of the recession in IVQ2007 to IQ2013, GDP increased 3.0 percent, or barely above the level before the recession, at the annual equivalent rate of 0.5 percent. Since the beginning of the recession in IVQ2007 to IQ2013, real disposable personal income increased 3.3 percent at the annual equivalent rate of 0.6 percent; population increased 4.2 percent at the annual equivalent rate of 0.8 percent; and real disposable personal income per capita is 0.9 percent lower than the level before the recession. Real disposable personal income is the actual take home pay after inflation and taxes and real disposable income per capita is what is left per inhabitant. The current cyclical expansion is the worst in the period after World War II in terms of growth of economic activity and income. The United States grew during its history at high rates of per capita income that made its economy the largest in the world. That dynamism is disappearing. Bordo (2012 Sep27) and Bordo and Haubrich (2012DR) provide strong evidence that recoveries have been faster after deeper recessions and recessions with financial crises, casting serious doubts on the conventional explanation of weak growth during the current expansion allegedly because of the depth of the contraction from IVQ2007 to IIQ2009 of 4.7 percent and the financial crisis.
Table IB-1, US, GDP, Real Disposable Personal Income, Real Disposable Income per Capita and Population in 1983-85 and 2007-2012, %
| # Quarters | ∆% | ∆% Annual Equivalent | |
| IQ1983 to IQ1986 IQ1983 to IIIQ1986 | 13 15 | ||
| GDP IQ1983 to IVQ1985 IQ1983 to IIIQ1986 | 13 15 | 19.6 21.3 | 5.7 5.3 |
| RDPI IQ1983 to IQ1986 IQ1983 to IIIQ1986 | 13 15 | 14.9 16.9 | 4.4 4.2 |
| RDPI Per Capita IQ1983 to IVQ1986 IQ1983 to IIIQ1986 | 13 15 | 11.9 13.3 | 3.5 3.4 |
| Population IQ1983 to IQ1986 IQ1983 to IIIQ1986 | 13 15 | 2.7 3.2 | 0.8 0.8 |
| IIIQ2009 to IQ2013 | 15 | ||
| GDP | 8.1 | 2.1 | |
| RDPI | 5.3 | 1.4 | |
| RDPI per Capita | 2.6 | 0.7 | |
| Population | 2.6 | 0.7 | |
| IVQ2007 to IQ2013 | 22 | ||
| GDP | 3.0 | 0.5 | |
| RDPI | 3.3 | 0.6 | |
| RDPI per Capita | -0.9 | NA | |
| Population | 4.2 | 0.8 |
RDPI: Real Disposable Personal Income
Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm
There are seven basic facts illustrating the current economic disaster of the United States: (1) GDP maintained trend growth in the entire business cycle from IQ1980 to IV1985 and IIIQ1986, including contractions and expansions, but is well below trend in the entire business cycle from IVQ2007 to IQ2013, including contractions and expansions; (2) per capita real disposable income exceeded trend growth in the 1980s but is substantially below trend in IQ2013; (3) the number of employed persons increased in the 1980s but declined into IQ2013; (4) the number of full-time employed persons increased in the 1980s but declined into IQ2013; (5) the number unemployed, unemployment rate and number employed part-time for economic reasons fell in the recovery from the recessions of the 1980s but not substantially in the recovery after IIQ2009; (6) wealth of households and nonprofit organizations soared in the 1980s but declined in real terms into IQ2013; and (7) gross private domestic investment increased sharply from IQ1980 to IVQ1985 and IIIQ1986 but gross private domestic investment and private fixed investment have fallen sharply from IVQ2007 to IQ2013. There is a critical issue of whether the United States economy will be able in the future to attain again the level of activity and prosperity of projected trend growth. Growth at trend during the entire business cycles built the largest economy in the world but there may be an adverse, permanent weakness in United States economic performance and prosperity. Table IB-2 provides data for analysis of these seven basic facts. The seven blocks of Table IB-2 are separated initially after individual discussion of each one followed by the full Table IB-2.
1. Trend Growth.
i. As shown in Table IB-2, actual GDP grew cumulatively 20.5 percent from IQ1980 to IIIQ1986, which is relatively close to what trend growth would have been at 22.9 percent. Rapid growth at 5.7 percent annual rate on average per quarter during the expansion from IQ1983 to IQ1986 erased the loss of GDP of 4.8 percent during the contraction and maintained trend growth at 3 percent over the entire cycle.
ii. In contrast, cumulative growth from IVQ2007 to IQ2013 was 3.2 percent while trend growth would have been 17.7 percent. GDP in IQ2013 at seasonally adjusted annual rate is estimated at $13,725.7 billion by the Bureau of Economic Analysis (BEA) (http://www.bea.gov/iTable/index_nipa.cfm) and would have been $15,684.7 billion, or $1,959 billion higher, had the economy grown at trend over the entire business cycle as it happened during the 1980s and throughout most of US history. There is $1.9 trillion of foregone GDP that would have been created as it occurred during past cyclical expansions, which explains why employment has not rebounded to even higher than before. There would not be recovery of full employment even with growth of 3 percent per year beginning immediately because the opportunity was lost to grow faster during the expansion from IIIQ2009 to IQ2013 after the recession from IVQ2007 to IIQ2009. The United States has acquired a heavy social burden of unemployment and underemployment of 28.7 million people or 17.7 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html) that will not be significantly diminished even with return to growth of GDP of 3 percent per year because of growth of the labor force by new entrants. The US labor force grew from 142.583 million in 2000 to 153.124 million in 2007 or by 7.4 percent at the average yearly rate of 1.0 percent per year. The civilian noninstitutional population increased from 212.577 million in 2000 to 231.867 million in 2007 or 9.1 percent at the average yearly rate of 1.3 percent per year (data from http://www.bls.gov/data/). Data for the past five years cloud accuracy because of the number of people discouraged from seeking employment. The noninstitutional population of the United States increased from 231.867 million in 2007 to 243.284 million in 2012 or by 4.9 percent while the labor force increased from 153.124 million in 2007 to 154.975 million in 2012 or by 1.2 percent and only by 0.3 percent to 153.617 million in 2011 while population increased 3.3 percent from 231.867 million in 2007 to 239.618 million in 2011 (data from http://www.bls.gov/data/). People ceased to seek jobs because they do not believe that there is a job available for them (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). Structural change in demography occurs over relatively long periods and not suddenly as shown by Edward P. Lazear and James R. Spletzer (2012JHJul22).
| Period IQ1980 to IIIQ1986 | |
| GDP SAAR USD Billions | |
| IQ1980 | 5,903.4 |
| IIIQ1986 | 7,112.9 |
| ∆% IQ1980 to IIIQ1986 (21.3 percent from IVQ1982 $5866.0 billion) | 20.5 |
| ∆% Trend Growth IQ1980 to IIIQ1986 | 22.9 |
| Period IVQ2007 to IQ2013 | |
| GDP SAAR USD Billions | |
| IVQ2007 | 13,326.0 |
| IVQ2012 | 13,725.7 |
| ∆% IVQ2007 to IVQ2012 Actual | 3.0 |
| ∆% IVQ2007 to IQ2013 Trend | 17.7 |
2. Decline of Per Capita Real Disposable Income
i. In the entire business cycle from IQ1980 to IIIQ1986, as shown in Table IB-2 trend growth of per capita real disposable income, or what is left per person after inflation and taxes, grew cumulatively 17.0 percent, which is close to what would have been trend growth of 14.9 percent.
ii. In contrast, in the entire business cycle from IVQ2007 to IQ2013, per capita real disposable income fell 0.9 percent while trend growth would have been 11.5 percent. Income available after inflation and taxes is about the same or lower as before the contraction after 15 consecutive quarters of GDP growth at mediocre rates relative to those prevailing during historical cyclical expansions. In IQ2013, personal income fell at the SAAR of minus 4.7 percent; real personal income excluding current transfer receipts at minus 7.7 percent; and real disposable personal income at minus 8.6 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0513.pdf). The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):
“The February and January changes in disposable personal income (DPI) mainly reflected the effect of special factors in January, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to November and to December in anticipation of changes in individual tax rates.”
| Period IQ1980 to IIIQ1986 |
| Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD | 18,938 |
| Real Disposable Personal Income per Capita IQ1II986 Chained 2005 USD | 22,165 |
| ∆% IQ1980 to IIIQ1986 | 17.0 |
| ∆% Trend Growth | 14.9 |
| Period IVQ2007 to IQ2013 |
| Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD | 32,837 |
| Real Disposable Personal Income per Capita IQ2013 Chained 2005 USD | 32,554 |
| ∆% IVQ2007 to IQ2013 | -0.9 |
| ∆% Trend Growth | 11.5 |
3. Number of Employed Persons
i. As shown in Table IB-2, the number of employed persons increased over the entire business cycle from 98.527 million not seasonally adjusted (NSA) in IQ1980 to 110.229 million NSA in IIIQ1986 or by 11.9 percent.
ii. In contrast, during the entire business cycle the number employed fell from 146.334 million in IVQ2007 to 142.698 million in IQ2013 or by 2.5 percent. There are 28.7 million persons unemployed or underemployed, which is 17.7 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-million-unemployed-or.html).
| Period IQ1980 to IIIQ1986 |
| Employed Millions IQ1980 NSA End of Quarter | 98.527 |
| Employed Millions IIIQ1986 NSA End of Quarter | 110.229 |
| ∆% Employed IQ1980 to IIIQ1986 | 11.9 |
| Period IVQ2007 to IQ2013 |
| Employed Millions IVQ2007 NSA End of Quarter | 146.334 |
| Employed Millions IQ2013 NSA End of Quarter | 142.698 |
| ∆% Employed IVQ2007 to IQ2013 | -2.5 |
4. Number of Full-Time Employed Persons
i. As shown in Table IB-2, during the entire business cycle in the 1980s, including contractions and expansion, the number of employed full-time rose from 81.280 million NSA in IQ1980 to 91.579 million NSA in IIIQ1986 or 12.7 percent.
ii. In contrast, during the entire current business cycle, including contraction and expansion, the number of persons employed full-time fell from 121.042 million in IVQ2007 to 114.796 million in IQ2013 or by minus 5.2 percent.
| Period IQ1980 to IIIQ1986 |
| Employed Full-time Millions IQ1980 NSA End of Quarter | 81.280 |
| Employed Full-time Millions IIIQ1986 NSA End of Quarter | 91.579 |
| ∆% Full-time Employed IQ1980 to IIIQ1986 | 12.7 |
| Period IVQ2007 to IQ2013 |
| Employed Full-time Millions IVQ2007 NSA End of Quarter | 121.042 |
| Employed Full-time Millions IQ2013 NSA End of Quarter | 114.796 |
| ∆% Full-time Employed IVQ2007 to IQ2013 | -5.2 |
5. Unemployed, Unemployment Rate and Employed Part-time for Economic Reasons.
i. As shown in Table IB-2 and in the following block, in the cycle from IQ1980 to IIIQ1986: (a) the rate of unemployment was virtually the same at 6.8 percent in IIIQ1986 relative to 6.6 percent in IQ1980; (b) the number unemployed increased from 6.983 million in IQ1980 to 8.015 million in IIIQ1986 or 14.8 percent; and (c) the number employed part-time for economic reasons increased 44.7 percent from 3.624 million in IQ1980 to 5.245 million in IIIQ1986.
ii. In contrast, in the economic cycle from IVQ2007 to IVQ2012: (a) the rate of unemployment increased from 4.8 percent in IVQ2007 to 7.6 percent in IQ2013; (b) the number unemployed increased 60.3 percent from 7.371 million in IVQ2007 to 11.815 million in IQ2013; (c) the number employed part-time for economic reasons increased 62.8 percent from 4.750 million in IVQ2007 to 7.734 million in IQ2013; and (d) U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA increased from 8.7 percent in IVQ2007 to 13.9 percent in IQ2013.
| Period IQ1980 to IIIQ1986 |
| Unemployment Rate IQ1980 NSA End of Quarter | 6.6 |
| Unemployment Rate IIIQ1986 NSA End of Quarter | 6.8 |
| Unemployed IQ1980 Millions End of Quarter | 6.983 |
| Unemployed IIIQ1986 Millions End of Quarter | 8.015 |
| Employed Part-time Economic Reasons Millions IQ1980 End of Quarter | 3.624 |
| Employed Part-time Economic Reasons Millions IIIQ1986 End of Quarter | 5.245 |
| ∆% | 44.7 |
| Period IVQ2007 to IQ2013 |
| Unemployment Rate IVQ2007 NSA End of Quarter | 4.8 |
| Unemployment Rate IQ2013 NSA End of Quarter | 7.6 |
| Unemployed IVQ2007 Millions End of Quarter | 7.371 |
| Unemployed IQ2013 Millions End of Quarter | 11.815 |
| ∆% | 60.3 |
| Employed Part-time Economic Reasons IVQ2007 Millions End of Quarter | 4.750 |
| Employed Part-time Economic Reasons Millions IQ2013 End of Quarter | 7.734 |
| ∆% | 62.8 |
| U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA | |
| IVQ2007 | 8.7 |
| IQ2013 | 13.9 |
6. Wealth of Households and Nonprofit Organizations.
i. The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and also from IVQ1979) to IVQ1985 and from IVQ2007 to IIIQ2012 is provided in the following block and in Table IB-2. Net worth of households and nonprofit organizations increased from $8,326.4 billion in IVQ1979 to $14,395.2 billion in IVQ1985 or 72.9 percent or 69.3 percent from $8,502.9 billion in IQ1980. The starting quarter does not bias the results. The US consumer price index not seasonally adjusted increased from 76.7 in Dec 1979 to 109.3 in Dec 1985 or 42.5 percent or 36.5 percent from 80.1 in Mar 1980 (using consumer price index data from the US Bureau of Labor Statistics at http://www.bls.gov/cpi/data.htm). In terms of purchasing power measured by the consumer price index, real wealth of households and nonprofit organizations increased 21.3 percent in constant purchasing power from IVQ1979 to IVQ1985 or 24.0 percent from IQ1980.
ii. In contrast, as shown in Table IB-2, net worth of households and nonprofit organizations increased from $66,861.7 billion in IVQ2007 to $70,439.1 billion in IQ2013 by $3487.4 billion or 5.2 percent. The US consumer price index was 210.036 in Dec 2007 and 232.773 in Mar 2013 for increase of 10.8 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 5.2 percent in Mar 2013 relative to IVQ2007 when the recession began after 15 consecutive quarters of expansion from IIIQ2009 to IQ2013. The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. The average growth rate from IIIQ2009 to IQ2013 has been 2.1 percent, which is substantially lower than the average of 5.7 percent in the expansion from IQ1983 to IQ1986 and 5.3 percent from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). US wealth of households and nonprofit organizations grew from IVQ1945 at $710,125.9 million to IVQ2012 at $67.346.450.1 million or increase of 9,383.7 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 229.601 in Dec 2012 or 1,161.5 percent. There was gigantic increase of US net worth of households and nonprofit organizations over 67 years with inflation-adjusted increase of 651.8 percent. Net worth of households and nonprofit organizations increased at the average annual average rate of 3.1 percent in the 67 years from 1945 to 2012 while GDP increased at the annual average rate of 2.9 percent. The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIQ2009 caused sharp contraction of US household and nonprofit net worth. There is extraordinary contrast between the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the fifteen quarters of the current cyclical expansion from IIIQ2009 to IQ2013 and the average of 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986 and 5.3 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). The average growth rate of 7.8 percent is derived from 7.9 percent from IIIQ1954 to IIQ1955, 9.5 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.7 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. 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). The average of 7.8 percent in the first four quarters of major cyclical expansions is more than twice higher than the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates. As a result, there are 28.7 million unemployed or underemployed in the United States for an effective unemployment rate of 17.7 percent (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011, 2.2 percent in 2012.
| Period IQ1980 to IVQ1985 | |
| Net Worth of Households and Nonprofit Organizations USD Billions | |
| IVQ1979 | 8,326.4 |
| IVQ1985 | 14,395.2 |
| ∆ USD Billions | +6,068.8 |
| Period IVQ2007 to IIIQ2012 | |
| Net Worth of Households and Nonprofit Organizations USD Billions | |
| IVQ2007 | 66,861.7 |
| IVQ2012 | 70,349.1 |
| ∆ USD Billions | 3,487.2 |
7. Gross Private Domestic Investment.
i. The comparison of gross private domestic investment in the entire economic cycles from IQ1980 to IIIIQ1986 and from IVQ2007 to IQ2013 is provided in the following block and in Table IB-2. Gross private domestic investment increased from $778.3 billion in IQ1980 to $913.0 billion in IIIQ1986 or by 17.3 percent.
ii In the current cycle, gross private domestic investment decreased from $2,123.6 billion in IVQ2007 to $1,970.1 billion in IQ2013, or decline by 7.2 percent. Private fixed investment fell from $2,111.5 billion in IVQ2007 to $1,920.4 billion in IQ2013, or decline by 9.1 percent.
| Period IQ1980 to IIIQ1986 | |
| Gross Private Domestic Investment USD 2005 Billions | |
| IQ1980 | 778.3 |
| IIIQ1986 | 913.0 |
| ∆% | 17.3 |
| Period IVQ2007 to IQ2013 | |
| Gross Private Domestic Investment USD Billions | |
| IVQ2007 | 2,123.6 |
| IQ2013 | 1,970.1 |
| ∆% | -7.2 |
| Private Fixed Investment USD 2005 Billions | |
| IVQ2007 | 2,111.5 |
| IQ2013 | 1,920.4 |
| ∆% | -9.1 |
Table IB-2, US, GDP and Real Disposable Personal Income per Capita Actual and Trend Growth and Employment, 1980-1985 and 2007-2012, SAAR USD Billions, Millions of Persons and ∆%
| Period IQ1980 to IIIQ1986 | |
| GDP SAAR USD Billions | |
| IQ1980 | 5,903.4 |
| IIIQ1986 | 7,112.9 |
| ∆% IQ1980 to IIIQ1986 (21.3 percent from IVQ1982 $5866.0 billion) | 20.5 |
| ∆% Trend Growth IQ1980 to IIIQ1986 | 22.9 |
| Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD | 18,938 |
| Real Disposable Personal Income per Capita IIIQ1986 Chained 2005 USD | 22,165 |
| ∆% IQ1980 to IIIQ1986 | 17.0 |
| ∆% Trend Growth | 14.9 |
| Employed Millions IQ1980 NSA End of Quarter | 98.527 |
| Employed Millions III1986 NSA End of Quarter | 110.229 |
| ∆% Employed IQ1980 to IIIQ1986 | 11.9 |
| Employed Full-time Millions IQ1980 NSA End of Quarter | 81.280 |
| Employed Full-time Millions IIIIQ1986 NSA End of Quarter | 91.579 |
| ∆% Full-time Employed IQ1980 to IIIQ1986 | 12.7 |
| Unemployment Rate IQ1980 NSA End of Quarter | 6.6 |
| Unemployment Rate IIIQ1986 NSA End of Quarter | 6.8 |
| Unemployed IQ1980 Millions NSA End of Quarter | 6.983 |
| Unemployed IIIQ1986 Millions NSA End of Quarter | 8.015 |
| ∆% | 16.3 |
| Employed Part-time Economic Reasons IQ1980 Millions NSA End of Quarter | 3.624 |
| Employed Part-time Economic Reasons Millions IIIQ1986 NSA End of Quarter | 5.245 |
| ∆% | 44.7 |
| Net Worth of Households and Nonprofit Organizations USD Billions | |
| IVQ1979 | 8,326.4 |
| IVQ1985 | 14,395.2 |
| ∆ USD Billions | +6,068.8 |
| Gross Private Domestic Investment USD 2005 Billions | |
| IQ1980 | 778.3 |
| IQ1986 | 913.0 |
| ∆% | 17.3 |
| Period IVQ2007 to IQ2013 | |
| GDP SAAR USD Billions | |
| IVQ2007 | 13,326.0 |
| IQ2013 | 13,725.7 |
| ∆% IVQ2007 to IQ2013 | 3.0 |
| ∆% IVQ2007 to IQ2013 Trend Growth | 17.7 |
| Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD | 32,837 |
| Real Disposable Personal Income per Capita IQ2013 Chained 2005 USD | 32,554 |
| ∆% IVQ2007 to IQ2013 | -0.9 |
| ∆% Trend Growth | 11.5 |
| Employed Millions IVQ2007 NSA End of Quarter | 146.334 |
| Employed Millions IQ2013 NSA End of Quarter | 142.698 |
| ∆% Employed IVQ2007 to IQ2013 | -2.5 |
| Employed Full-time Millions IVQ2007 NSA End of Quarter | 121.042 |
| Employed Full-time Millions IQ2013 NSA End of Quarter | 114.796 |
| ∆% Full-time Employed IVQ2007 to IQ2013 | -5.2 |
| Unemployment Rate IVQ2007 NSA End of Quarter | 4.8 |
| Unemployment Rate IQ2013 NSA End of Quarter | 7.6 |
| Unemployed IVQ2007 Millions NSA End of Quarter | 7.371 |
| Unemployed IQ2013 Millions NSA End of Quarter | 11.815 |
| ∆% | 60.3 |
| Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter | 4.750 |
| Employed Part-time Economic Reasons Millions IQ2013 NSA End of Quarter | 7.734 |
| ∆% | 62.8 |
| U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA | |
| IVQ2007 | 8.7 |
| IQ2013 | 13.9 |
| Net Worth of Households and Nonprofit Organizations USD Billions | |
| IVQ2007 | 66,861.7 |
| IQ2013 | 70,349.1 |
| ∆ USD Billions | 3,487.4 |
| Gross Private Domestic Investment USD Billions | |
| IVQ2007 | 2,123.6 |
| IQ2013 | 1,970.1 |
| ∆% | -7.2 |
| Private Fixed Investment USD 2005 Billions | |
| IVQ2007 | 2,111.5 |
| IQ2013 | 1,920.4 |
| ∆% | -9.1 |
Note: GDP trend growth used is 3.0 percent per year and GDP per capita is 2.0 percent per year as estimated by Lucas (2011May) on data from 1870 to 2010.
Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm US Bureau of Labor Statistics http://www.bls.gov/data/. Board of Governors of the Federal Reserve System. 2013Jun6. Flow of funds, balance sheets and integrated macroeconomic accounts. Washington, DC, Federal Reserve System, Jun 6.
The Congressional Budget Office (CBO 2013BEOFeb5) estimates potential GDP, potential labor force and potential labor productivity provided in Table IB-3. The average rate of growth of potential GDP from 1950 to 2012 is estimated at 3.3 percent per year. The projected path is
significantly lower at 2.2 percent per year from 2012 to 2023. The legacy of the economic cycle with expansion from IIIQ2009 to IQ2013 at 2.1 percent on average in contrast with 5.7 percent on average in the expansion from IQ1983 to IVQ1985 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html) may perpetuate unemployment and underemployment estimated at 28.7 million or 17.7 percent of the effective labor force in Jun 2013 (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html) with much lower hiring than in the period before the current cycle (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html).
Table IB-3, US, Congressional Budget Office History and Projections of Potential GDP of US Overall Economy, ∆%
| Potential GDP | Potential Labor Force | Potential Labor Productivity* | |
| Average Annual ∆% | |||
| 1950-1973 | 3.9 | 1.6 | 2.3 |
| 1974-1981 | 3.3 | 2.5 | 0.8 |
| 1982-1990 | 3.1 | 1.6 | 1.5 |
| 1991-2001 | 3.1 | 1.3 | 1.8 |
| 2002-2012 | 2.2 | 0.8 | 1.4 |
| Total 1950-2012 | 3.3 | 1.5 | 1.7 |
| Projected Average Annual ∆% | |||
| 2013-2018 | 2.2 | 0.6 | 1.6 |
| 2019-2023 | 2.3 | 0.5 | 1.8 |
| 2012-2023 | 2.2 | 0.5 | 1.7 |
*Ratio of potential GDP to potential labor force
Source: CBO (2013BEOFeb5).
Chart IB-1 of the Congressional Budget Office (CBO 2013BEOFeb5) provides actual and potential GDP of the United States from 2000 to 2011 and projected to 2024. Lucas (2011May) estimates trend of United States real GDP of 3.0 percent from 1870 to 2010 and 2.2 percent for per capita GDP. The United States successfully returned to trend growth of GDP by higher rates of growth during cyclical expansion as analyzed by Bordo (2012Sep27, 2012Oct21) and Bordo and Haubrich (2012DR). Growth in expansions following deeper contractions and financial crises was much higher in agreement with the plucking model of Friedman (1964, 1988). The unusual weakness of growth at 2.1 percent on average from IIIQ2009 to IVQ2012 during the current economic expansion in contrast with 5.7 percent on average in the cyclical expansion from IQ1983 to IVQ1985 (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html) cannot be explained by the contraction of 4.7 of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 28.7 million or 17.7 percent of the labor as estimated for Jun 2013 (http://cmpassocregulationblog.blogspot.com/2013/07/twenty-nine-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html) and the collapse of hiring (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html).
Chart IB-1, US, Congressional Budget Office, Actual and Projections of Potential GDP, 2000-2024, Trillions of Dollars
Source: Congressional Budget Office, CBO (2013BEOFeb5).
IIA IMF View of World Economy and Finance. The International Financial Institutions (IFI) consist of the International Monetary Fund, World Bank Group, Bank for International Settlements (BIS) and the multilateral development banks, which are the European Investment Bank, Inter-American Development Bank and the Asian Development Bank (Pelaez and Pelaez, International Financial Architecture (2005), The Global Recession Risk (2007), 8-19, 218-29, Globalization and the State, Vol. II (2008b), 114-48, Government Intervention in Globalization (2008c), 145-54). There are four types of contributions of the IFIs:
1. Safety Net. The IFIs contribute to crisis prevention and crisis resolution.
i. Crisis Prevention. An important form of contributing to crisis prevention is by surveillance of the world economy and finance by regions and individual countries. The IMF and World Bank conduct periodic regional and country evaluations and recommendations in consultations with member countries and also jointly with other international organizations. The IMF and the World Bank have been providing the Financial Sector Assessment Program (FSAP) by monitoring financial risks in member countries that can serve to mitigate them before they can become financial crises.
ii. Crisis Resolution. The IMF jointly with other IFIs provides assistance to countries in resolution of those crises that do occur. Currently, the IMF is cooperating with the government of Greece, European Union and European Central Bank in resolving the debt difficulties of Greece as it has done in the past in numerous other circumstances. Programs with other countries involved in the European debt crisis may also be developed.
2. Surveillance. The IMF conducts surveillance of the world economy, finance and public finance with continuous research and analysis. Important documents of this effort are the World Economic Outlook of which the current one is IMF (http://www.imf.org/external/ns/cs.aspx?id=29), Global Financial Stability Report of which the current one is IMF (http://www.imf.org/external/pubs/ft/gfsr/2013/01/index.htm) and Fiscal Monitor of which the current one is IMF (http://www.imf.org/external/pubs/ft/fm/2013/01/fmindex.htm).
3. Infrastructure and Development. The IFIs also engage in infrastructure and development, in particular the World Bank Group and the multilateral development banks.
4. Soft Law. Significant activity by IFIs has consisted of developing standards and codes under multiple forums. It is easier and faster to negotiate international agreements under soft law that are not binding but can be very effective (on soft law see Pelaez and Pelaez, Globalization and the State, Vol. II (2008c), 114-25). These norms and standards can solidify world economic and financial arrangements.
The objective of this section is to analyze current update projections of the IMF database for the most important indicators.
Table II-1 is constructed with the database of the IMF (http://www.imf.org/external/pubs/ft/weo/2013/01/weodata/index.aspx) to show GDP in dollars in 2012 and the growth rate of real GDP of the world and selected regional countries from 2013 to 2016. The IMF provides an update of the macroeconomic forecast of the world (http://www.imf.org/external/pubs/ft/weo/2013/update/02/). The data illustrate the concept often repeated of “two-speed recovery” of the world economy from the recession that affected the US economy from IVQ2007 (Dec) to IIQ2009 (Jun) (http://www.nber.org/cycles.html). A new fact is slowing growth in emerging and developing economies. The IMF has lowered its forecast of the world economy to 3.1 percent in 2013 but accelerating to 3.8 percent in 2014 with the unmodified earlier forecasts of 4.4 percent in 2015 and 4.5 percent in 2016. Slow-speed recovery occurs in the “major advanced economies” of the G7 that account for $33,932 billion of world output of $71,707 billion, or 47.3 percent, but are projected to grow at much lower rates than world output, 1.2 percent in 2013 and 2.1 percent in 2014 and 2.1 on average from 2013 to 2016 in contrast with 3.9 percent for the world as a whole. While the world would grow 16.8 percent in the four years from 2013 to 2016, the G7 as a whole would grow 8.6 percent. The difference in dollars of 2012 is rather high: growing by 16.8 percent would add $12.0 trillion of output to the world economy, or roughly, two times the output of the economy of Japan of $5,964 but growing by 8.6 percent would add $6.2 trillion of output to the world, or about the output of Japan in 2012. The “two speed” concept is in reference to the growth of the 150 countries labeled as emerging and developing economies (EMDE) with joint output in 2012 of $27,290 billion, or 38.1 percent of world output. The EMDEs would grow cumulatively 24.5 percent or at the average yearly rate of 5.6 percent, contributing $6.7 trillion from 2013 to 2016 or the equivalent of somewhat less than the GDP of $8,227 billion of China in 2012. The final four countries in Table 1 often referred as BRIC (Brazil, Russia, India, China), are large, rapidly growing emerging economies. Their combined output in 2012 adds to $14,470 billion, or 20.2 percent of world output, which is equivalent to 42.6 percent of the combined output of the major advanced economies of the G7.
The IMF explains the major factors of the change in forecast (http://www.imf.org/external/pubs/ft/weo/2013/update/02/):
“Global growth is projected to remain subdued at slightly above 3 percent in 2013, the same as in 2012. This is less than forecast in the April 2013 World Economic Outlook (WEO), driven to a large extent by appreciably weaker domestic demand and slower growth in several key emerging market economies, as well as a more protracted recession in the euro area. Downside risks to global growth prospects still dominate: while old risks remain, new risks have emerged, including the possibility of a longer growth slowdown in emerging market economies, especially given risks of lower potential growth, slowing credit, and possibly tighter financial conditions if the anticipated unwinding of monetary policy stimulus in the United States leads to sustained capital flow reversals. Stronger global growth will require additional policy action. Specifically, major advanced economies should maintain a supportive macroeconomic policy mix, combined with credible plans for reaching medium-term debt sustainability and reforms to restore balance sheets and credit channels. Many emerging market and developing economies face a tradeoff between macroeconomic policies to support weak activity and those to contain capital outflows. Macroprudential and structural reforms can help make this tradeoff less stark.”
Table II-1, IMF World Economic Outlook Database Projections of Real GDP Growth
| GDP USD 2012 | Real GDP ∆% | Real GDP ∆% | Real GDP ∆% | Real GDP ∆% | |
| World | 71,707 | 3.1 | 3.8 | 4.4 | 4.5 |
| G7 | 33,932 | 1.2 | 2.1 | 2.5 | 2.5 |
| Canada | 1,819 | 1.7 | 2.2 | 2.5 | 2.4 |
| France | 2,609 | -0.2 | 0.8 | 1.5 | 1.7 |
| DE | 3,401 | 0.3 | 1.3 | 1.3 | 1.3 |
| Italy | 2,014 | -1.8 | 0.7 | 1.2 | 1.4 |
| Japan | 5,964 | 2.0 | 1.2 | 1.1 | 1.2 |
| UK | 2,441 | 0.9 | 1.5 | 1.8 | 1.9 |
| US | 15,685 | 1.7 | 2.7 | 3.6 | 3.4 |
| Euro Area | 12,198 | -0.3 | 1.1 | 1.4 | 1.6 |
| DE | 3,401 | 0.3 | 1.3 | 1.3 | 1.3 |
| France | 2,609 | -0.2 | 0.8 | 1.5 | 1.7 |
| Italy | 2,014 | -1.8 | 0.7 | 1.2 | 1.4 |
| POT | 213 | -2.3 | 0.6 | 1.5 | 1.8 |
| Ireland | 210 | 1.1 | 2.2 | 2.7 | 2.7 |
| Greece | 249 | -4.2 | 0.6 | 2.9 | 3.7 |
| Spain | 1,352 | -1.6 | 0.7 | 1.4 | 1.5 |
| EMDE | 27,290 | 5.0 | 5.4 | 6.0 | 6.1 |
| Brazil | 2,396 | 2.5 | 3.2 | 4.1 | 4.2 |
| Russia | 2,022 | 2.5 | 3.3 | 3.7 | 3.6 |
| India | 1,825 | 5.6 | 6.3 | 6.6 | 6.9 |
| China | 8,227 | 7.8 | 7.7 | 8.5 | 8.5 |
Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries); POT: Portugal
Source: IMF World Economic Outlook databank http://www.imf.org/external/pubs/ft/weo/2013/01/weodata/index.aspx http://www.imf.org/external/pubs/ft/weo/2013/update/02/
© Carlos M. Pelaez, 2010, 2011, 2012, 2013
No comments:
Post a Comment