Twenty Nine Million Unemployed or Underemployed, Collapse of United States Dynamism of Income Growth and Employment Creation, Stagnating Real Wages, United States International Trade, Peaking Valuations of Risk Financial Assets, World Economic Slowdown and Global Recession Risk
Carlos M. Pelaez
© Carlos M. Pelaez, 2010, 2011, 2012, 2013
Executive Summary
I Twenty Nine Million Unemployed or Underemployed
IA1 Summary of the Employment Situation
IA2 Number of People in Job Stress
IA3 Long-term and Cyclical Comparison of Employment
IA4 Job Creation
IB Collapse of United States Dynamism of Income Growth and Employment Creation
II Stagnating Real Wages
IIA United States International Trade
III World Financial Turbulence
IIIA Financial Risks
IIIE Appendix Euro Zone Survival Risk
IIIF Appendix on Sovereign Bond Valuation
IV Global Inflation
V World Economic Slowdown
VA United States
VB Japan
VC China
VD Euro Area
VE Germany
VF France
VG Italy
VH United Kingdom
VI Valuation of Risk Financial Assets
VII Economic Indicators
VIII Interest Rates
IX Conclusion
References
Appendixes
Appendix I The Great Inflation
IIIB Appendix on Safe Haven Currencies
IIIC Appendix on Fiscal Compact
IIID Appendix on European Central Bank Large Scale Lender of Last Resort
IIIG Appendix on Deficit Financing of Growth and the Debt Crisis
IIIGA Monetary Policy with Deficit Financing of Economic Growth
IIIGB Adjustment during the Debt Crisis of the 1980s
Executive Summary
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 15,135.84
on Fri Jul 5, 2013, which is higher by 6.9 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 6.6 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs.
Jon Hilsenrath, writing on “Jobs upturn isn’t enough to satisfy Fed,” on Mar 8, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324582804578348293647760204.html), finds that much stronger labor market conditions are required for the Fed to end quantitative easing. Unconventional monetary policy with zero interest rates and quantitative easing is quite difficult to unwind because of the adverse effects of raising interest rates on valuations of risk financial assets and home prices, including the very own valuation of the securities held outright in the Fed balance sheet. Gradual unwinding of 1 percent fed funds rates from Jun 2003 to Jun 2004 by seventeen consecutive increases of 25 percentage points from Jun 2004 to Jun 2006 to reach 5.25 percent caused default of subprime mortgages and adjustable-rate mortgages linked to the overnight fed funds rate. The zero interest rate has penalized liquidity and increased risks by inducing carry trades from zero interest rates to speculative positions in risk financial assets. There is no exit from zero interest rates without provoking another financial crash.
The carry trade from zero interest rates to leveraged positions in risk financial assets had proved strongest for commodity exposures but US equities have regained leadership. The DJIA has increased 56.3 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Jun 28, 2013; S&P 500 has gained 59.6 percent; and DAX 37.7 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 7/5/13” 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 15.8 percent below the trough; Japan’s Nikkei Average is 66.2 percent above the trough; DJ Asia Pacific TSM is 17.3 percent above the trough; Dow Global is 24.9 percent above the trough; STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 14.1 percent above the trough; and NYSE Financial Index is 35.1 percent above the trough. DJ UBS Commodities is 1.3 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 37.7 percent above the trough. Japan’s Nikkei Average is 62.2 percent above the trough on Aug 31, 2010 and 25.6 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 14,309.97 on Fri Jul 5, 2013 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 39.5 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 7.7 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 7/5/13” in Table VI-4 shows increase of 1.4 percent in the week for China’s Shanghai Composite. DJ Asia Pacific increased 0.8 percent. NYSE Financial increased 1.5 percent in the week. DJ UBS Commodities increased 0.9 percent. Dow Global increased 0.8 percent in the week of Jul 5, 2013. The DJIA increased 1.5 percent and S&P 500 increased 1.6 percent. DAX of Germany decreased 1.9 percent. STOXX 50 increased 0.6 percent. The USD appreciated 1.4 percent. There are still high uncertainties on European sovereign risks and banking soundness, US and world growth slowdown and China’s growth tradeoffs. Sovereign problems in the “periphery” of Europe and fears of slower growth in Asia and the US cause risk aversion with trading caution instead of more aggressive risk exposures. There is a fundamental change in Table VI-4 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 7/5/13” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Jul 5, 2013. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 7/5/13” but also relative to the peak in column “∆% Peak to 7/5/13.” There are now several equity indexes above the peak in Table VI-4: DJIA 35.1 percent, S&P 500 34.1 percent, DAX 23.3 percent, Dow Global 1.9 percent, DJ Asia Pacific 2.7 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 7.6 percent and Nikkei Average 25.6 percent. There are only two equity indexes below the peak: Shanghai Composite by 36.6 percent and STOXX 50 by 3.4 percent. DJ UBS Commodities Index is now 13.4 percent below the peak. The US dollar strengthened 15.2 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
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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 7/5/ /13 | ∆% Week 7/5/13 | ∆% Trough to 7/5/ 13 | |
| DJIA | 4/26/ | 7/2/10 | -13.6 | 35.1 | 1.5 | 56.3 |
| S&P 500 | 4/23/ | 7/20/ | -16.0 | 34.1 | 1.6 | 59.6 |
| NYSE Finance | 4/15/ | 7/2/10 | -20.3 | 7.6 | 1.5 | 35.1 |
| Dow Global | 4/15/ | 7/2/10 | -18.4 | 1.9 | 0.8 | 24.9 |
| Asia Pacific | 4/15/ | 7/2/10 | -12.5 | 2.7 | 0.8 | 17.3 |
| Japan Nikkei Aver. | 4/05/ | 8/31/ | -22.5 | 25.6 | 4.6 | 62.2 |
| China Shang. | 4/15/ | 7/02 | -24.7 | -36.6 | 1.4 | -15.8 |
| STOXX 50 | 4/15/10 | 7/2/10 | -15.3 | -3.4 | 0.6 | 14.1 |
| DAX | 4/26/ | 5/25/ | -10.5 | 23.3 | -1.9 | 37.7 |
| Dollar | 11/25 2009 | 6/7 | 21.2 | 15.2 | 1.4 | -7.7 |
| DJ UBS Comm. | 1/6/ | 7/2/10 | -14.5 | -13.4 | 0.9 | 1.3 |
| 10-Year T Note | 4/5/ | 4/6/10 | 3.986 | 2.734 |
T: trough; Dollar: positive sign appreciation relative to euro (less dollars paid per euro), negative sign depreciation relative to euro (more dollars paid per euro)
Source: http://professional.wsj.com/mdc/page/marketsdata.html?mod=WSJ_hps_marketdata
ESII Twenty Nine Million Unemployed or Underemployed. Table I-4 consists of data and additional calculations using the BLS household survey, illustrating the possibility that the actual rate of unemployment could be 10.9 percent and the number of people in job stress could be around 28.7 million, which is 17.7 percent of the effective labor force. The first column provides for 2006 the yearly average population (POP), labor force (LF), participation rate or labor force as percent of population (PART %), employment (EMP), employment population ratio (EMP/POP %), unemployment (UEM), the unemployment rate as percent of labor force (UEM/LF Rate %) and the number of people not in the labor force (NLF). All data are unadjusted or not-seasonally-adjusted (NSA). The numbers in column 2006 are averages in millions while the monthly numbers for Jun 2012, May 2013 and Jun 2013 are in thousands, not seasonally adjusted. The average yearly participation rate of the population in the labor force was in the range of 66.0 percent minimum to 67.1 percent maximum between 2000 and 2006 with the average of 66.4 percent (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). Table I-4b provides the yearly labor force participation rate from 1979 to 2013. The objective of Table I-4 is to assess how many people could have left the labor force because they do not think they can find another job. Row “LF PART 66.2 %” applies the participation rate of 2006, almost equal to the rates for 2000 to 2006, to the noninstitutional civilian population in Jun 2012 and May 2013 and Jun 2013 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 64.3 percent by Jun 2012 and was 63.5 percent in May 2013 and 63.5 percent in Jun 2013, suggesting that many people simply gave up on finding another job. Row “∆ NLF UEM” calculates the number of people not counted in the labor force because they could have given up on finding another job by subtracting from the labor force with participation rate of 66.2 percent (row “LF PART 66.2%”) the labor force estimated in the household survey (row “LF”). Total unemployed (row “Total UEM”) is obtained by adding unemployed in row “∆NLF UEM” to the unemployed of the household survey in row “UEM.” The row “Total UEM%” is the effective total unemployed “Total UEM” as percent of the effective labor force in row “LF PART 66.2%.” The results are that: (1) there are an estimated 5466 million unemployed in Jun 2013 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM); (2) the total number of unemployed is effectively 17.714 million (Total UEM) and not 12.248 million (UEM) of whom many have been unemployed long term; (3) the rate of unemployment is 10.9 percent (Total UEM%) and not 7.8 percent, not seasonally adjusted, or 7.6 percent seasonally adjusted; and (4) the number of people in job stress is close to 28.7 million by adding the 5.466 million leaving the labor force because they believe they could not find another job. The row “In Job Stress” in Table I-4 provides the number of people in job stress not seasonally adjusted at 28.736 million in Jun 2013, adding the total number of unemployed (“Total UEM”), plus those involuntarily in part-time jobs because they cannot find anything else (“Part Time Economic Reasons”) and the marginally attached to the labor force (“Marginally attached to LF”). The final row of Table I-4 shows that the number of people in job stress is equivalent to 17.7 percent of the labor force in May 2013. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 58.9 percent in Jun 2012, 58.9 percent in May 2013 and 59.0 percent in Jun 2013. The number employed in the US fell from 147.315 million in Jul 2007 to 144.841 million in Jun 2013, by 2.474 million, or decline of 1.7 percent, while the noninstitutional population increased from 231.958 million in Jul 2007 to 245.552 million in Jun 2013, by 13.594 million or increase of 5.9 percent, using not seasonally adjusted data. What really matters for labor input in production and wellbeing is the number of people with jobs or the employment/population ratio, which has declined and does not show signs of increasing. There are several million fewer people working in 2013 than in 2006 and the number employed is not increasing while population increased 13.594 million. The number of hiring relative to the number unemployed measures the chances of becoming employed. The number of hiring in the US economy has declined by 17 million and does not show signs of increasing in an unusual recovery without hiring (http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html).
Table I-4, US, Population, Labor Force and Unemployment, NSA
| 2006 | Jun 2012 | May 2013 | Jun 2013 | |
| POP | 229 | 243,155 | 245,363 | 245,552 |
| LF | 151 | 156,385 | 155,734 | 157,089 |
| PART% | 66.2 | 64.3 | 63.5 | 64.0 |
| EMP | 144 | 143,202 | 144,432 | 144,841 |
| EMP/POP% | 62.9 | 58.9 | 58.9 | 59.0 |
| UEM | 7 | 13,184 | 11,302 | 12,248 |
| UEM/LF Rate% | 4.6 | 8.4 | 7.3 | 7.8 |
| NLF | 77 | 86,770 | 89,629 | 88,463 |
| LF PART 66.2% | 160,969 | 162,430 | 162,555 | |
| ∆NLF UEM | 4,584 | 6,696 | 5,466 | |
| Total UEM | 17,768 | 17,998 | 17,714 | |
| Total UEM% | 11.0 | 11.1 | 10.9 | |
| Part Time Economic Reasons | 8,394 | 7,618 | 8,440 | |
| Marginally Attached to LF | 2,483 | 2,164 | 2,582 | |
| In Job Stress | 28,645 | 27,780 | 28,736 | |
| People in Job Stress as % Labor Force | 17.8 | 17.1 | 17.7 |
Pop: population; LF: labor force; PART: participation; EMP: employed; UEM: unemployed; NLF: not in labor force; ∆NLF UEM: additional unemployed; Total UEM is UEM + ∆NLF UEM; Total UEM% is Total UEM as percent of LF PART 66.2%; In Job Stress = Total UEM + Part Time Economic Reasons + Marginally Attached to LF
Note: the first column for 2006 is in average millions; the remaining columns are in thousands; NSA: not seasonally adjusted
The labor force participation rate of 66.2% in 2006 is applied to current population to obtain LF PART 66.2%; ∆NLF UEM is obtained by subtracting the labor force with participation of 66.2 percent from the household survey labor force LF; Total UEM is household data unemployment plus ∆NLF UEM; and total UEM% is total UEM divided by LF PART 66.2%
Source: US Bureau of Labor Statistics http://www.bls.gov/
In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):
Y = ∑isiyi (1)
This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):
∆Y = ∑i∆siy*i + ∑i∆yis*i (2)
The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:
“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”
Table I-4b and Chart 12-b provide the US labor force participation rate or percentage of the labor force in population. It is not likely that simple demographic trends caused the sharp decline during the global recession and failure to recover earlier levels. The civilian labor force participation rate dropped from the peak of 66.9 percent in Jul 2006 to 64.0 percent in Jun 2013. The civilian labor force participation rate was 63.7 percent on an annual basis in 1979 and 63.4 percent in Dec 1980 and Dec 1981, reaching even 62.9 percent in both Apr and May 1979. The civilian labor force participation rate jumped with the recovery to 64.8 percent on an annual basis in 1985 and 65.9 percent in Jul 1985. Structural factors cannot explain these sudden changes vividly shown visually in the final segment of Chart 12b. Seniors would like to delay their retiring especially because of the adversities of financial repression on their savings. Labor force statistics are capturing the disillusion of potential workers of their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors.
Table I-4b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2013
| Year | Jan | Feb | Mar | Apr | May | Jun | Nov | Dec | Annual |
| 1979 | 62.9 | 63.0 | 63.2 | 62.9 | 62.9 | 64.5 | 63.8 | 63.8 | 63.7 |
| 1980 | 63.3 | 63.2 | 63.2 | 63.2 | 63.5 | 64.6 | 63.7 | 63.4 | 63.8 |
| 1981 | 63.2 | 63.2 | 63.5 | 63.6 | 63.9 | 64.6 | 63.8 | 63.4 | 63.9 |
| 1982 | 63.0 | 63.2 | 63.4 | 63.3 | 63.9 | 64.8 | 64.1 | 63.8 | 64.0 |
| 1983 | 63.3 | 63.2 | 63.3 | 63.2 | 63.4 | 65.1 | 64.1 | 63.8 | 64.0 |
| 1984 | 63.3 | 63.4 | 63.6 | 63.7 | 64.3 | 65.5 | 64.4 | 64.3 | 64.4 |
| 1985 | 64.0 | 64.0 | 64.4 | 64.3 | 64.6 | 65.5 | 64.9 | 64.6 | 64.8 |
| 1986 | 64.2 | 64.4 | 64.6 | 64.6 | 65.0 | 66.3 | 65.4 | 65.0 | 65.3 |
| 1987 | 64.7 | 64.8 | 65.0 | 64.9 | 65.6 | 66.3 | 65.7 | 65.5 | 65.6 |
| 1988 | 65.1 | 65.2 | 65.2 | 65.3 | 65.5 | 66.7 | 66.2 | 65.9 | 65.9 |
| 1989 | 65.8 | 65.6 | 65.7 | 65.9 | 66.2 | 67.4 | 66.7 | 66.3 | 66.5 |
| 1990 | 66.0 | 66.0 | 66.2 | 66.1 | 66.5 | 67.4 | 66.3 | 66.1 | 66.5 |
| 1991 | 65.5 | 65.7 | 65.9 | 66.0 | 66.0 | 67.2 | 66.0 | 65.8 | 66.2 |
| 1992 | 65.7 | 65.8 | 66.0 | 66.0 | 66.4 | 67.6 | 66.2 | 66.1 | 66.4 |
| 1993 | 65.6 | 65.8 | 65.8 | 65.6 | 66.3 | 67.3 | 66.3 | 66.2 | 66.3 |
| 1994 | 66.0 | 66.2 | 66.1 | 66.0 | 66.5 | 67.2 | 66.7 | 66.5 | 66.6 |
| 1995 | 66.1 | 66.2 | 66.4 | 66.4 | 66.4 | 67.2 | 66.5 | 66.2 | 66.6 |
| 1996 | 65.8 | 66.1 | 66.4 | 66.2 | 66.7 | 67.4 | 67.0 | 66.7 | 66.8 |
| 1997 | 66.4 | 66.5 | 66.9 | 66.7 | 67.0 | 67.8 | 67.1 | 67.0 | 67.1 |
| 1998 | 66.6 | 66.7 | 67.0 | 66.6 | 67.0 | 67.7 | 67.1 | 67.0 | 67.1 |
| 1999 | 66.7 | 66.8 | 66.9 | 66.7 | 67.0 | 67.7 | 67.0 | 67.0 | 67.1 |
| 2000 | 66.8 | 67.0 | 67.1 | 67.0 | 67.0 | 67.7 | 66.9 | 67.0 | 67.1 |
| 2001 | 66.8 | 66.8 | 67.0 | 66.7 | 66.6 | 67.2 | 66.6 | 66.6 | 66.8 |
| 2002 | 66.2 | 66.6 | 66.6 | 66.4 | 66.5 | 67.1 | 66.3 | 66.2 | 66.6 |
| 2003 | 66.1 | 66.2 | 66.2 | 66.2 | 66.2 | 67.0 | 66.1 | 65.8 | 66.2 |
| 2004 | 65.7 | 65.7 | 65.8 | 65.7 | 65.8 | 66.5 | 66.1 | 65.8 | 66.0 |
| 2005 | 65.4 | 65.6 | 65.6 | 65.8 | 66.0 | 66.5 | 66.1 | 65.9 | 66.0 |
| 2006 | 65.5 | 65.7 | 65.8 | 65.8 | 66.0 | 66.7 | 66.4 | 66.3 | 66.2 |
| 2007 | 65.9 | 65.8 | 65.9 | 65.7 | 65.8 | 66.6 | 66.1 | 65.9 | 66.0 |
| 2008 | 65.7 | 65.5 | 65.7 | 65.7 | 66.0 | 66.6 | 65.8 | 65.7 | 66.0 |
| 2009 | 65.4 | 65.5 | 65.4 | 65.4 | 65.5 | 66.2 | 64.9 | 64.4 | 65.4 |
| 2010 | 64.6 | 64.6 | 64.8 | 64.9 | 64.8 | 65.1 | 64.4 | 64.1 | 64.7 |
| 2011 | 63.9 | 63.9 | 64.0 | 63.9 | 64.1 | 64.5 | 63.9 | 63.8 | 64.1 |
| 2012 | 63.4 | 63.6 | 63.6 | 63.4 | 63.8 | 64.3 | 63.5 | 63.4 | 63.7 |
| 2013 | 63.3 | 63.2 | 63.1 | 63.1 | 63.5 | 64.0 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart 12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2013
Source: Bureau of Labor Statistics
Broader perspective is provided by Chart 12c of the US Bureau of Labor Statistics. The United States civilian noninstitutional population has increased along a consistent trend since 1948 that continued through earlier recessions and the global recession from IVQ2007 to IIQ2009 and the cyclical expansion after IIIQ2009.
Chart 12c, US, Civilian Noninstitutional Population, Thousands, NSA, 1948-2013
Sources: US Bureau of Labor Statistics
The labor force of the United States in Chart 12d has increased along a trend similar to that of the civilian noninstitutional population in Chart 12c. There is an evident stagnation of the civilian labor force in the final segment of Chart 12d during the current economic cycle. This stagnation is explained by cyclical factors similar to those analyzed by Lazear and Spletzer (2012JHJul22) that motivated an increasing population to drop out of the labor force instead of structural factors. Large segments of the potential labor force are not observed, constituting unobserved unemployment and of more permanent nature because those afflicted have been seriously discouraged from working by the lack of opportunities.
Chart 12d, US, Labor Force, Thousands, NSA, 1948-2013
Sources: US Bureau of Labor Statistics
ESIII Job Creation. What is striking about the data in Table I-8 is that the numbers of monthly increases in jobs in 1983 and 1984 are several times higher than in 2010 to 2013. The civilian noninstitutional population growing by 39.6 percent from 174.215 million in 1983 to 243.284 million in 2012 and labor force higher by 38.9 percent, growing from 111.550 million in 1983 to 154.975 million in 2012. Nonfarm payroll jobs increased 48.1 percent from 90.280 million in 1983 to 133.739 million in 2012. Total nonfarm payroll employment seasonally adjusted (SA) increased 195,000 in Jun 2013 and private payroll employment rose 202,000. The average number of nonfarm jobs created in Jan-Jun 2012 was 185,167 while the average number of nonfarm jobs created in Jan-Jun 2013 was 201,833, or increase by 9.0 percent. The average number of private jobs created in the US in Jan-Jun 2012 was 191,000 while the average in Jan-Jun 2013 was 205,667, or increase by 7.7 percent. The US labor force increased from 153.617 million in 2011 to 154.975 million in 2012 by 1.358 million or 113,167 per month. The average increase of nonfarm jobs in the five months from Jan to Jun 2013 was 201,833, which is a rate of job creation inadequate to reduce significantly unemployment and underemployment in the United States because of 113,167 new entrants in the labor force per month with 28.7 million unemployed or underemployed. The difference between the average increase of 201,833 new private nonfarm jobs per month in the US from Jan to Jun 2013 and the 113,167 average monthly increase in the labor force from 2011 to 2012 is 88,666 monthly new jobs net of absorption of new entrants in the labor force. There are 28.7 million in job stress in the US currently. Creation of 88,666 new jobs per month net of absorption of new entrants in the labor force would require 324 months to provide jobs for the unemployed and underemployed (28.736 million divided by 88,666) or 27 years (324 divided by 12). The civilian labor force of the US in Jun 2013 not seasonally adjusted stood at 157.089 million with 12.248 million unemployed or effectively 17.714 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 162.555 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 0.9 years (1 million divided by product of 88,666 by 12, which is 1,063,992). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.854 million (0.05 times labor force of 157.089 million) for new net job creation of 4.394 million (12.248 million unemployed minus 7.854 million unemployed at rate of 5 percent) that at the current rate would take 4.1 years (4.394 million divided by 1.063992). Under the calculation in this blog, there are 17.714 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 162.555 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 9.586 million jobs net of labor force growth that at the current rate would take 9.0 years (17.714 million minus 0.05(162.555 million) = 9.586 million divided by 1.063992, using LF PART 66.2% and Total UEM in Table I-4). These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply. The number employed in the US fell from 147.315 million in Jul 2007 to 144.841 million in Jun 2013, by 2.474 million, or decline of 1.7 percent, while the noninstitutional population increased from 231.958 million in Jul 2007 to 245.552 million in Jun 2013, by 13.594 million or increase of 5.9 percent, using not seasonally adjusted data. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs. There is 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 United States missed this opportunity of high growth in the initial phase of recovery that historically eliminated unemployment and underemployment created during the contraction. 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 growth rate of GDP is 7.8 percent in the first four quarters of major cyclical expansions while the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 is 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, Table I-4 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 (http://www.bea.gov/iTable/index_nipa.cfm) and cumulative 1.7 percent in the four quarters of 2012 {[(1.02)1/4(1.013)1/4(1.031)1/4(1.004)1/4 – 1]100 = 1.7%} with minor rounding discrepancy using the SSAR of $13,665.4 billion in IVQ2012 relative to the SAAR of $13,441.0 billion in IVQ2011 {[($13665.4/$13441.00-1]100 = 1.7%}. %}. The growth rate in annual equivalent for the four quarters of 2011, the four quarters of 2012 and the first quarter of 2013 is 1.8 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.001 x 1.0044)4/9 -1]100 = 1.8%], or {[($13,725.7/$13,181.2)]4/9-1]100 = 1.8%} dividing the SAAR of IVQ2012 by the SAAR of IVQ2010 in Table I-6 below, obtaining the average for nine quarters and the annual average for one year of four quarters. The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983.
Table I-8, US, Monthly Change in Jobs, Number SA
| Month | 1981 | 1982 | 1983 | 2008 | 2009 | 2010 | Private |
| Jan | 95 | -327 | 225 | 14 | -794 | -13 | -17 |
| Feb | 67 | -6 | -78 | -85 | -695 | -40 | -26 |
| Mar | 104 | -129 | 173 | -79 | -830 | 154 | 111 |
| Apr | 74 | -281 | 276 | -215 | -704 | 229 | 170 |
| May | 10 | -45 | 277 | -186 | -352 | 521 | 102 |
| Jun | 196 | -243 | 378 | -169 | -472 | -130 | 94 |
| Jul | 112 | -343 | 418 | -216 | -351 | -86 | 103 |
| Aug | -36 | -158 | -308 | -270 | -210 | -37 | 129 |
| Sep | -87 | -181 | 1114 | -459 | -233 | -43 | 113 |
| Oct | -100 | -277 | 271 | -472 | -170 | 228 | 188 |
| Nov | -209 | -124 | 352 | -775 | -21 | 144 | 154 |
| Dec | -278 | -14 | 356 | -705 | -220 | 95 | 114 |
| 1984 | 2011 | Private | |||||
| Jan | 447 | 69 | 80 | ||||
| Feb | 479 | 196 | 243 | ||||
| Mar | 275 | 205 | 223 | ||||
| Apr | 363 | 304 | 303 | ||||
| May | 308 | 115 | 183 | ||||
| Jun | 379 | 209 | 177 | ||||
| Jul | 312 | 78 | 206 | ||||
| Aug | 241 | 132 | 129 | ||||
| Sep | 311 | 225 | 256 | ||||
| Oct | 286 | 166 | 174 | ||||
| Nov | 349 | 174 | 197 | ||||
| Dec | 127 | 230 | 249 | ||||
| 1985 | 2012 | Private | |||||
| Jan | 266 | 311 | 323 | ||||
| Feb | 124 | 271 | 265 | ||||
| Mar | 346 | 205 | 208 | ||||
| Apr | 195 | 112 | 120 | ||||
| May | 274 | 125 | 152 | ||||
| Jun | 145 | 87 | 78 | ||||
| Jul | 189 | 153 | 177 | ||||
| Aug | 193 | 165 | 131 | ||||
| Sep | 204 | 138 | 118 | ||||
| Oct | 187 | 160 | 217 | ||||
| Nov | 209 | 247 | 256 | ||||
| Dec | 168 | 219 | 224 | ||||
| 1985 | 2013 | Private | |||||
| Jan | 123 | 148 | 164 | ||||
| Feb | 107 | 332 | 319 | ||||
| Mar | 93 | 142 | 154 | ||||
| Apr | 188 | 199 | 188 | ||||
| May | 125 | 195 | 207 | ||||
| Jun | -93 | 195 | 202 | ||||
| Jul | 318 | ||||||
| Aug | 113 | ||||||
| Sep | 346 | ||||||
| Oct | 187 | ||||||
| Nov | 186 | ||||||
| Dec | 204 |
Source: US Bureau of Labor Statistics
Charts numbered from I-38 to I-41 from the database of the Bureau of Labor Statistics provide a comparison of payroll survey data for the contractions and expansions in the 1980s and after 2007. Chart I-38 provides total nonfarm payroll jobs from 2001 to 2013. The sharp decline in total nonfarm jobs during the contraction after 2007 has been followed by initial stagnation and then inadequate growth in 2012 and 2013.
Chart I-38, US, Total Nonfarm Payroll Jobs SA 2001-2013
Source: US Bureau of Labor Statistics
Chart I-39 provides total nonfarm jobs SA from 1979 to 1989. Recovery is strong throughout the decade with the economy growing at trend.
Chart I-39, US, Total Nonfarm Payroll Jobs SA 1979-1989
Source: US Bureau of Labor Statistics
Most job creation in the US is by the private sector. Chart I-40 shows the sharp destruction of private payroll jobs during the contraction after 2007. There has been growth after 2010 but insufficient to recover higher levels of employment prevailing before the contraction. At current rates, recovery of employment may spread over several years in contrast with past expansions of the business cycle in the US.
Chart I-40, US, Total Private Payroll Jobs SA 2001-2013
Source: US Bureau of Labor Statistics
In contrast, growth of private payroll jobs in the US recovered vigorously during the expansion in 1983 through 1985, as shown in Chart I-41. Rapid growth of creation of private jobs continued throughout the 1980s.
Chart I-41, US, Total Private Payroll Jobs SA 1979-1989
Source: US Bureau of Labor Statistics
ESIV Stagnating Real Wages. Average hourly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are provided in Table II-4. Average hourly earnings fell 0.5 percent after adjusting for inflation in the 12 months ending in Mar 2012 and gained 0.6 percent in the 12 months ending in Apr 2011 but then lost 0.6 percent in the 12 months ending in May 2012 with a gain of 0.3 percent in the 12 months ending in Jun 2012 and 1.0 percent in Jul 2012 followed by 0.1 percent in Aug 2012 and 0.7 percent in Sep 2012. Average hourly earnings adjusted by inflation fell 1.2 percent in the 12 months ending in Oct 2012. Average hourly earnings adjusted by inflation increased 0.1 percent in the 12 months ending in Nov 2012 and 1.1 percent in the 12 months ending in Dec 2012 but fell 0.2 percent in the 12 months ending in Jan 2013 and stagnated with gain of 0.1 percent in the 12 months ending in Feb 2013. Average hourly earnings adjusted for inflation increased 0.4 percent in the 12 months ending in Mar 2013 and increased 0.2 percent in the 12 months ending in Apr 2013. Average hourly earnings adjusted for inflation increased 0.6 percent in the 12 months ending in May 2013. Table II-4 confirms the trend of deterioration of purchasing power of average hourly earnings in 2011 and into 2012 with 12-month percentage declines in three of the first four months of 2012 (-1.1 percent in Jan, -1.1 percent in Feb and -0.5 percent in Mar), declines of 0.6 percent in May and 1.2 percent in Oct and increase in five (0.6 percent in Apr, 0.3 percent in Jun, 1.0 percent in Jul, 0.7 percent in Sep and 1.1 percent in Dec) and stagnation in two (0.1 percent in Aug and 0.1 percent in Nov). Average hourly earnings adjusted for inflation fell 0.2 percent in the 12 months ending in Jan 2013, stagnated with gain of 0.1 percent in the 12 months ending in Feb 2013 and gained 0.4 percent in the 12 months ending Mar 2013. Real average hourly earnings increased 0.2 percent in the 12 months ending in Apr 2013 and 0.6 percent in the 12 months ending in May 2013. Annual data are revealing: -0.7 percent in 2008 during carry trades into commodity futures in a global recession, 3.2 percent in 2009 with reversal of carry trades, no change in 2010 and 2012 and decline by 1.1 percent in 2011. Annual average hourly earnings of all employees in the United States adjusted for inflation increased 1.4 percent from 2007 to 2012 at the yearly average rate of 0.3 percent (from $10.11 in 2007 to $10.25 in 2012 in dollars of 1982-1984 using data in http://www.bls.gov/data/). Those who still work bring back home a paycheck that buys fewer goods than a year earlier and savings in bank deposits do not pay anything because of financial repression (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html).
Table II-4, US, Average Hourly Earnings of All Employees NSA in Constant Dollars of 1982-1984
| Year | Jan | Feb | Mar | Apr | May | Dec |
| 2006 | 10.05 | 10.11 | 9.92 | 10.21 | ||
| 2007 | 10.23 | 10.22 | 10.14 | 10.18 | 10.02 | 10.17 |
| 2008 | 10.11 | 10.12 | 10.11 | 10.00 | 9.91 | 10.47 |
| 2009 | 10.48 | 10.50 | 10.47 | 10.40 | 10.32 | 10.38 |
| 2010 | 10.41 | 10.43 | 10.35 | 10.35 | 10.38 | 10.40 |
| 2011 | 10.53 | 10.41 | 10.26 | 10.22 | 10.22 | 10.30 |
| 2012 | 10.41 | 10.30 | 10.21 | 10.28 | 10.16 | 10.41 |
| ∆% 12 M 2012 | -1.1 | -1.1 | -0.5 | 0.6 | -0.6 | 1.1 |
| 2013 | 10.39 | 10.31 | 10.25 | 10.30 | 10.22 | NA |
| ∆% 12 M 2013 | -0.2 | 0.1 | 0.4 | 0.2 | 0.6 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart II-2 of the US Bureau of Labor Statistics plots average hourly earnings of all US employees in constant 1982-1984 dollars with evident decline from annual earnings of $10.36 in 2009 and $10.36 again in 2010 to $10.25 in 2011 and $10.25 again in 2012 or loss of 1.1 percent (data in http://www.bls.gov/data/).
Chart II-2, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart II-3 provides 12-month percentage changes of average hourly earnings of all employees in constant dollars of 1982-1984, that is, adjusted for inflation. There was sharp contraction of inflation-adjusted average hourly earnings of US employees during parts of 2007 and 2008. Rates of change in 12 months became positive in parts of 2009 and 2010 but then became negative again in 2011 and into 2012 with temporary increase in Apr 2012 that was reversed in May with another gain in Jun and Jul 2012 followed by stagnation in Aug 2012 and marginal gain in Sep 2012 with sharp decline in Oct 2012, stagnation in Nov 2012, increase in Dec 2012 and renewed decrease in Jan 2013 with near stagnation in Feb 2013 followed by mild increase in Mar-Apr 2013. Hourly earnings adjusted for inflation increased in Jun 2013.
Chart II-3, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Average weekly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are provided in Table II-5. Average weekly earnings fell 3.2 percent after adjusting for inflation in the 12 months ending in Aug 2011, decreased 0.9 percent in the 12 months ending in Sep 2011, increased 0.9 percent in the 12 months ending in Oct 2011, fell 1.0 percent in the 12 months ending in Nov 2011 and 0.3 in the 12 months ending in Dec 2011, declining 0.3 percent in the 12 months ending in Jan 2012 and 0.5 percent in the 12 months ending in Feb 2012. Average weekly earnings in constant dollars were virtually flat in Mar 2012 relative to Mar 2011, increasing 0.1 percent. Average weekly earnings in constant dollars increased 1.7 percent in Apr 2012 relative to Apr 2011 but fell 1.4 percent in May 2012 relative to May 2011, increasing 0.3 percent in the 12 months ending in Jun and 2.1 percent in Jul 2012. Real weekly earnings increased 0.4 percent in the 12 months ending in Aug 2012 and 2.1 percent in the 12 months ending in Sep 2012. Real weekly earnings fell 2.9 percent in the 12 months ending in Oct 2012 and increased 0.1 percent in the 12 months ending in Nov 2012 and 2.5 percent in the 12 months ending in Dec 2012. Real weekly earnings fell 1.6 percent in the 12 months ending in Jan 2013 and virtually stagnated with gain of 0.2 percent in the 12 months ending in Feb 2013, increasing 0.4 percent in the 12 months ending in Mar 2013. Real weekly earnings fell 1.0 percent in the 12 months ending in Apr 2013 and increased 0.6 percent in the 12 months ending in May 2013. Table II-5 confirms the trend of deterioration of purchasing power of average weekly earnings in 2011 and into 2012 with oscillations according to carry trades causing world inflation waves (http://cmpassocregulationblog.blogspot.com/2013/06/paring-quantitative-easing-policy-and.html). On an annual basis, average weekly earnings in constant 1982-1984 dollars increased from $349.78 in 2007 to $353.66 in 2012, by 1.1 percent or at the average rate of 0.2 percent per year (data in http://www.bls.gov/data/). Annual average weekly earnings in constant dollars of $353.50 in 2010 were virtually unchanged at $353.66 in 2012. Those who still work bring back home a paycheck that buys fewer high-quality goods than a year earlier. The fractured US job market does not provide an opportunity for advancement as in past booms following recessions (http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html).
Table II-5, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, NSA 2007-2013
| Year | Jan | Feb | Mar | Apr | May | Dec |
| 2006 | 343.71 | 349.95 | 340.12 | 353.37 | ||
| 2007 | 348.72 | 349.40 | 347.76 | 353.41 | 344.58 | 356.11 |
| 2008 | 345.92 | 346.21 | 351.70 | 344.13 | 340.93 | 357.17 |
| 2009 | 354.10 | 360.31 | 355.81 | 349.33 | 347.94 | 351.95 |
| 2010 | 350.71 | 350.51 | 349.76 | 351.99 | 356.97 | 355.61 |
| 2011 | 360.29 | 353.81 | 349.90 | 350.62 | 353.56 | 354.41 |
| 2012 | 359.06 | 352.12 | 350.19 | 356.68 | 348.65 | 363.13 |
| ∆% 12 M 2012 | -0.3 | -0.5 | 0.1 | 1.7 | -1.4 | 2.5 |
| 2013 | 353.17 | 352.66 | 351.59 | 353.13 | 350.59 | NA |
| ∆% 12 M 2013 | -1.6 | 0.2 | 0.4 | -1.0 | 0.6 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart II-4 provides average weekly earnings of all employees in constant dollars of 1982-1984. The same pattern emerges of sharp decline during the contraction, followed by recovery in the expansion and continuing fall with oscillations caused by carry trades from zero interest rates into commodity futures from 2010 to 2011 and into 2012 and 2013.
Chart II-4, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart II-5 provides 12-month percentage changes of average weekly earnings of all employees in the US in constant dollars of 1982-1984. There is the same pattern of contraction during the global recession in 2008 and then again trend of deterioration in the recovery without hiring and inflation waves in 2011 and 2012. (http://cmpassocregulationblog.blogspot.com/2013/06/paring-quantitative-easing-policy-and.html)
Chart II-5, US, Average Weekly Earnings of All Employees NSA in Constant Dollars of 1982-1984 12-Month Percent Change, NSA 2007-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
ESV Collapse of United States Dynamism of Income Growth and Employment Creation. 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
I Twenty Nine Million Unemployed or Underemployed. This section analyzes the employment situation report of the United States of the Bureau of Labor Statistics (BLS). There are four subsections: IA1 Summary of the Employment Situation; IA2 Number of People in Job Stress; IA3 Long-term and Cyclical Comparison of Employment; and IA4 Job Creation.
IA1 Summary of the Employment Situation. The Bureau of Labor Statistics (BLS) of the US Department of Labor provides both seasonally adjusted (SA) and not-seasonally adjusted (NSA) or unadjusted data with important uses (Bureau of Labor Statistics 2012Feb3; 2011Feb11):
“Most series published by the Current Employment Statistics program reflect a regularly recurring seasonal movement that can be measured from past experience. By eliminating that part of the change attributable to the normal seasonal variation, it is possible to observe the cyclical and other nonseasonal movements in these series. Seasonally adjusted series are published monthly for selected employment, hours, and earnings estimates.”
Requirements of using best available information and updating seasonality factors affect the comparability over time of United States employment data. In the first month of the year, the BLS revises data for several years by adjusting benchmarks and seasonal factors (page 4 at http://www.bls.gov/news.release/pdf/empsit.pdf), which is the case of the data for Jan 2013 released on Feb 1, 2013:
“In accordance with annual practice, the establishment survey data released today have been benchmarked to reflect comprehensive counts of payroll jobs. These counts are derived principally from unemployment insurance tax records for March 2012. The benchmark process results in revisions to not seasonally adjusted data from April 2011 forward. Seasonally adjusted data from January 2008 forward are subject to revision. In addition, data for some series prior to 2008, both seasonally adjusted and unadjusted, incorporate minor revisions.
The total nonfarm employment level for March 2012 was revised upward by 422,000 (424,000 on a not seasonally adjusted basis). Table A presents revised total nonfarm employment data on a seasonally adjusted basis for January through December 2012.”
The range of differences in total nonfarm employment in revisions in Table A of the employment situation report for Feb 2013 (page 4 at http://www.bls.gov/news.release/pdf/empsit.pdf) is from 348,000 for Jan 2012 to 647,000 for Dec 2012. There are also adjustments of population that affect comparability of labor statistics over time (page 5 at http://www.bls.gov/news.release/pdf/empsit.pdf):
“Effective with data for January 2013, updated population estimates have been used in the household survey. Population estimates for the household survey are developed by the U.S. Census Bureau. Each year, the Census Bureau updates the estimates to reflect new information and assumptions about the growth of the population since the previous decennial census. The change in population reflected in the new estimates results from adjustments for net international migration, updated vital statistics and other information, and some methodological changes in the estimation process. In accordance with usual practice, BLS will not revise the official household survey estimates for December 2012 and earlier months. To show the impact of the population adjustment, however, differences in selected December 2012 labor force series based on the old and new population estimates are shown in table B.
The adjustment increased the estimated size of the civilian noninstitutional population in December by 138,000, the civilian labor force by 136,000, employment by 127,000, unemployment by 9,000, and persons not in the labor force by 2,000. The total unemployment rate, employment-population ratio, and labor force participation rate were unaffected.
Data users are cautioned that these annual population adjustments affect the comparability of household data series over time. Table C shows the effect of the introduction of new population estimates on the comparison of selected labor force measures between December 2012 and January 2013. Additional information on the population adjustments and their effect on national labor force estimates are available at www.bls.gov/cps/cps13adj.pdf (emphasis added).”
There are also adjustments of benchmarks and seasonality factors for establishment data that affect comparability over time (page 1 at http://www.bls.gov/news.release/pdf/empsit.pdf):
“Establishment survey data have been revised as a result of the annual benchmarking process and the updating of seasonal adjustment factors.”
All comparisons over time are affected by yearly adjustments of benchmarks and seasonality factors. All data in this blog comment use revised data released by the BLS on Jun 7, 2013 (http://www.bls.gov/).
Table I-1 provides summary statistics of the employment situation report of the BLS. The first four rows provide the data from the establishment report of creation of nonfarm payroll jobs and remuneration of workers (for analysis of the differences in employment between the establishment report and the household survey see Abraham, Haltiwanger, Sandusky and Spletzer 2009). Total nonfarm payroll employment seasonally adjusted (SA) increased 195,000 in Jun 2013 and private payroll employment rose 202,000. The average number of nonfarm jobs created in Jan-Jun 2012 was 185,167 while the average number of nonfarm jobs created in Jan-Jun 2013 was 201,833, or increase by 9.0 percent. The average number of private jobs created in the US in Jan-Jun 2012 was 191,000 while the average in Jan-Jun 2013 was 205,667, or increase by 7.7 percent. The US labor force increased from 153.617 million in 2011 to 154.975 million in 2012 by 1.358 million or 113,167 per month. The average increase of nonfarm jobs in the five months from Jan to Jun 2013 was 201,833, which is a rate of job creation inadequate to reduce significantly unemployment and underemployment in the United States because of 113,167 new entrants in the labor force per month with 28.7 million unemployed or underemployed. The difference between the average increase of 201,833 new private nonfarm jobs per month in the US from Jan to Jun 2013 and the 113,167 average monthly increase in the labor force from 2011 to 2012 is 88,666 monthly new jobs net of absorption of new entrants in the labor force. There are 28.7 million in job stress in the US currently. Creation of 88,666 new jobs per month net of absorption of new entrants in the labor force would require 324 months to provide jobs for the unemployed and underemployed (28.736 million divided by 88,666) or 27 years (324 divided by 12). The civilian labor force of the US in Jun 2013 not seasonally adjusted stood at 157.089 million with 12.248 million unemployed or effectively 17.714 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 162.555 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 0.9 years (1 million divided by product of 88,666 by 12, which is 1,063,992). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.854 million (0.05 times labor force of 157.089 million) for new net job creation of 4.394 million (12.248 million unemployed minus 7.854 million unemployed at rate of 5 percent) that at the current rate would take 4.1 years (4.394 million divided by 1.063992). Under the calculation in this blog, there are 17.714 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 162.555 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 9.586 million jobs net of labor force growth that at the current rate would take 9.0 years (17.714 million minus 0.05(162.555 million) = 9.586 million divided by 1.063992, using LF PART 66.2% and Total UEM in Table I-4). These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply. The number employed in the US fell from 147.315 million in Jul 2007 to 144.841 million in Jun 2013, by 2.474 million, or decline of 1.7 percent, while the noninstitutional population increased from 231.958 million in Jul 2007 to 245.552 million in Jun 2013, by 13.594 million or increase of 5.9 percent, using not seasonally adjusted data. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs. Subsection IA4 Job Creation analyzes the types of jobs created, which are lower paying than earlier. Average hourly earnings in Jun 2013 were $24.01 seasonally adjusted (SA), increasing 2.7 percent not seasonally adjusted (NSA) relative to Jun 2012 and increasing 0.4 percent relative to May 2013 seasonally adjusted. In May 2013, average hourly earnings seasonally adjusted were $23.91, increasing 1.9 percent relative to May 2012 not seasonally adjusted and increasing 0.1 percent seasonally adjusted relative to Apr 2013. These are nominal changes in workers’ wages. The following row “average hourly earnings in constant dollars” provides hourly wages in constant dollars calculated by the BLS or what is called “real wages” adjusted for inflation. Data are not available for Jun 2013 because the prices indexes of the BLS for Jun will only be released on Jul 16, 2013 (http://www.bls.gov/cpi/), which will be covered in this blog’s comment on Jul 21, 2013, together with world inflation. The second column provides changes in real wages for May 2013. Average hourly earnings adjusted for inflation or in constant dollars increased 0.2 percent in May 2013 relative to May 2012 but have been decreasing during many consecutive months. World inflation waves in bouts of risk aversion (http://cmpassocregulationblog.blogspot.com/2013/06/paring-quantitative-easing-policy-and.html) mask declining trend of real wages. The fractured labor market of the US is characterized by high levels of unemployment and underemployment together with falling real wages or wages adjusted for inflation in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html). The following section II Stagnating Real Wages provides more detailed analysis. Average weekly hours of US workers seasonally adjusted remained virtually unchanged at 34.5. Another headline number widely followed is the unemployment rate or number of people unemployed as percent of the labor force. The unemployment rate calculated in the household survey did not change from 7.5 percent in May 2013 to 7.6 percent in Jun 2013, seasonally adjusted. This blog provides with every employment situation report the number of people in the US in job stress or unemployed plus underemployed calculated without seasonal adjustment (NSA) at 28.7 million in Jun 2013 and 27.8 million in May 2013. The final row in Table I-1 provides the number in job stress as percent of the actual labor force calculated at 17.7 percent in Jun 2013 and 17.1 percent in May 2013. Almost one in every five workers in the US is unemployed or underemployed. The combination of about thirty million people in job stress, falling or stagnating real wages, collapse of hiring (http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html), decline of US inflation-adjusted household wealth by 5.2 percent from IVQ2007 to IQ2013 while it increased 31.2 percent from IQ1980 to IIIQ1986 (http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html), household median income adjusted for inflation back to 1996 levels, real per capita disposable income of $32,554 in chained 2005 dollars lower in IQ2013 by 0.9 percent relative to $32,837 in IVQ2007 (http://www.bea.gov/iTable/index_nipa.cfm Section IB Collapse), federal deficits of $5.092 trillion in four years and debt/GDP of 72.6 percent in 2012 in the unsustainable path to 89.7 percent of GDP (http://cmpassocregulationblog.blogspot.com/2012/11/united-states-unsustainable-fiscal.html) and forty-eight million people in poverty and without health insurance (http://cmpassocregulationblog.blogspot.com/2012/09/collapse-of-united-states-creation-of.html) constitutes a socio-economic disaster.
Table I-1, US, Summary of the Employment Situation Report SA
| Jun 2013 | May 2013 | |
| New Nonfarm Payroll Jobs | 195,000 | 195,000 |
| New Private Payroll Jobs | 202,000 | 207,000 |
| Average Hourly Earnings | Jun 13 $24.01 SA ∆% Jun 13/Jun 12 NSA: 2.7 ∆% Jun 13/May 13 SA: 0.4 | May 13 $23.91 SA ∆% May 13/May 12 NSA: 1.9 ∆% May 13/Apr 13 SA: 0.1 |
| Average Hourly Earnings in Constant Dollars | ∆% May 2013/May 2012: 0.2 | |
| Average Weekly Hours | 34.5 SA 34.9 NSA | 34.5 SA 34.3 NSA |
| Unemployment Rate Household Survey % of Labor Force SA | 7.6 | 7.6 |
| Number in Job Stress Unemployed and Underemployed Blog Calculation | 28.7 million NSA | 27.8 million NSA |
| In Job Stress as % Labor Force | 17.7 NSA | 17.1 NSA |
Source: US Bureau of Labor Statistics Source: US Bureau of Labor Statistics
IA2 Number of People in Job Stress. There are two approaches to calculating the number of people in job stress. The first approach consists of calculating the number of people in job stress unemployed or underemployed with the raw data of the employment situation report as in Table I-2. The data are seasonally adjusted (SA). The first three rows provide the labor force and unemployed in millions and the unemployment rate of unemployed as percent of the labor force. There is increase in the number unemployed from 11.659 million in Apr 2013 to 11.760 million in May 2013 and increase to 11.777 million in Jun 2013. The rate of unemployment increased from 7.5 in Apr 2013 to 7.6 percent in May 2013 and 7.6 percent in Jun 2013. An important aspect of unemployment is its persistence for more than 27 weeks with 4.28 million in Jun 2013, corresponding to 36.8 percent of the unemployed. The longer the period of unemployment the lower are the chances of finding another job with many long-term unemployed ceasing to search for a job. Another key characteristic of the current labor market is the high number of people trying to subsist with part-time jobs because they cannot find full-time employment or part-time for economic reasons. The BLS explains as follows: “these individuals were working part time because their hours had been cut back or because they were unable to find a full-time job” (http://www.bls.gov/news.release/pdf/empsit.pdf 2). The number of part-time for economic reasons increased from 7.916 million in Apr 2013 to 8.226 million in Jun 2013. Another important fact is the marginally attached to the labor force. The BLS explains as follows: “these individuals were not in the labor force, wanted and were available for work, and had looked for a job sometime in the prior 12 months. They were not counted as unemployed because they had not searched for work in the 4 weeks preceding the survey” (http://www.bls.gov/news.release/pdf/empsit.pdf 2). The number in job stress unemployed or underemployed of 22.585 million in Jun 2013 is composed of 11.777 million unemployed (of whom 4.328 million, or 36.8 percent, unemployed for 27 weeks or more) compared with 11.760 million unemployed in May 2013 (of whom 4.357 million, or 37.1 percent, unemployed for 27 weeks or more), 8.226 million employed part-time for economic reasons in Jun 2013 (who suffered reductions in their work hours or could not find full-time employment) compared with 7.904 million in May 2013 and 2.582 million who were marginally attached to the labor force in Jun 2013 (who were not in the labor force but wanted and were available for work) compared with 2.164 million in May 2013. The final row in Table I-2 provides the number in job stress as percent of the labor force: 14.5 percent in Jun 2013, which is about equal to 14.0 percent in May 2013 and 14.1 percent in Apr 2013.
Table I-2, US, People in Job Stress, Millions and % SA
| 2013 | Jun 2013 | May 2013 | Apr 2013 |
| Labor Force Millions | 155.835 | 155.658 | 155.238 |
| Unemployed | 11.777 | 11.760 | 11.659 |
| Unemployment Rate (unemployed as % labor force) | 7.6 | 7.6 | 7.5 |
| Unemployed ≥27 weeks | 4.328 | 4.357 | 4.353 |
| Unemployed ≥27 weeks % | 36.8 | 37.1 | 37.3 |
| Part Time for Economic Reasons | 8.226 | 7.904 | 7.916 |
| Marginally | 2.582 | 2.164 | 2.347 |
| Job Stress | 22.585 | 21.828 | 21.922 |
| In Job Stress as % Labor Force | 14.5 | 14.0 | 14.1 |
Job Stress = Unemployed + Part Time Economic Reasons + Marginally Attached Labor Force
Source: US Bureau of Labor Statistics http://www.bls.gov/
Table I-3 repeats the data in Table I-2 but including Mar and additional data. What really matters is the number of people with jobs or the total employed. The final row of Table I-3 provides people employed as percent of the population or employment to population ratio. The number has remained relatively constant around 58.6 percent. The employment to population ratio fell from an annual level of 63.1 percent in 2006 to 58.6 percent in 2012 with the lowest level at 58.4 percent in 2011.
Table I-3, US, Unemployment and Underemployment, SA, Millions and Percent
| Jun 2013 | May 2013 | Apr 2013 | Mar 2013 | |
| Labor Force | 155.835 | 155.658 | 155.238 | 155.028 |
| Unemployed | 11.777 | 11.760 | 11.659 | 11.742 |
| UNE Rate % | 7.6 | 7.6 | 7.5 | 7.6 |
| Part Time Economic Reasons | 8.226 | 7.904 | 7.916 | 7.638 |
| Marginally Attached to Labor Force | 2.582 | 2.164 | 2.347 | 2.326 |
| In Job Stress | 22.585 | 21.828 | 21.922 | 21.706 |
| In Job Stress % Labor Force | 14.5 | 14.0 | 14.1 | 14.0 |
| Employed | 144.058 | 143.898 | 143.579 | 143.286 |
| Employment % Population | 58.7 | 58.6 | 58.6 | 58.5 |
Job Stress = Unemployed + Part Time Economic Reasons + Marginally Attached Labor Force
Source: US Bureau of Labor Statistics http://www.bls.gov/
The balance of this section considers the second approach. Charts I-1 to I-12 explain the reasons for considering another approach to calculating job stress in the US. Chart I-1 of the Bureau of Labor Statistics provides the level of employment in the US from 2001 to 2013. There was a big drop of the number of people employed from 147.315 million at the peak in Jul 2007 (NSA) to 136.809 million at the trough in Jan 2010 (NSA) with 10.506 million fewer people employed. Recovery has been anemic compared with the shallow recession of 2001 that was followed by nearly vertical growth in jobs. The number employed in Jun 2013 was 144.841 million (NSA) or 2.474 million fewer people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population increased from 231.958 million in Jul 2007 to 245.552 million in Jun 2013 or by 13.594 million.
Chart I-1, US, Employed, Thousands, SA, 2001-2013
Source: Bureau of Labor Statistics
Chart I-2 of the Bureau of Labor Statistics provides 12-month percentage changes of the number of people employed in the US from 2001 to 2013. There was recovery since 2010 but not sufficient to recover lost jobs. Many people in the US who had jobs before the global recession are not working now.
Chart I-2, US, Employed, 12-Month Percentage Change NSA, 2001-2013
Source: Bureau of Labor Statistics
The foundation of the second approach derives from Chart I-3 of the Bureau of Labor Statistics providing the level of the civilian labor force in the US. The civilian labor force consists of people who are available and willing to work and who have searched for employment recently. The labor force of the US grew from 142.828 million in Jan 2001 to 156.255 million in Jul 2009 but is virtually equal at 157.089 million in Jun 2013, all numbers not seasonally adjusted. Chart 1-3 shows the flattening of the curve of expansion of the labor force and its decline in 2010 and 2011. The ratio of the labor force of 154.871 million in Jul 2007 to the noninstitutional population of 231.958 million in Jul 2007 was 66.8 percent while the ratio of the labor force of 157.089 million in Jun 2013 to the noninstitutional population of 245.552 million in Jun 2013 was 64.0 percent. The labor force of the US in Jun 2013 corresponding to 66.8 percent of participation in the population would be 164.029 million (0.668 x 245.552). The difference between the measured labor force in Jun 2013 of 157.089 million and the labor force in Jun 2013 with participation rate of 66.8 percent (as in Jul 2007) of 164.029 million is 6.940 million. The level of the labor force in the US has stagnated and is 6.940 million lower than what it would have been had the same participation rate been maintained. Millions of people have abandoned their search for employment because they believe there are no jobs available for them. The key issue is whether the decline in participation of the population in the labor force is the result of people giving up on finding another job.
Chart I-3, US, Civilian Labor Force, Thousands, SA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-4 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of the labor force in the US. The rate of growth fell almost instantaneously with the global recession and became negative from 2009 to 2011. The labor force of the US collapsed and did not recover. Growth in the beginning of the summer originates in younger people looking for jobs in the summer after graduation or during school recess.
Chart I-4, US, Civilian Labor Force, Thousands, NSA, 12-month Percentage Change, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-5 of the Bureau of Labor Statistics provides the labor force participation rate in the US or labor force as percent of the population. The labor force participation rate of the US fell from 66.8 percent in Jan 2001 to 64.0 percent NSA in Jun 2013, all numbers not seasonally adjusted. The annual labor force participation rate for 1979 was 63.7 percent and also 63.7 percent in Nov 1980 during sharp economic contraction. This comparison is further elaborated below. Chart I-5 shows an evident downward trend beginning with the global recession that has continued throughout the recovery beginning in IIIQ2009. The critical issue is whether people left the workforce of the US because they believe there is no longer a job for them.
Chart I-5, Civilian Labor Force Participation Rate, Percent of Population in Labor Force SA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-6 of the Bureau of Labor Statistics provides the level of unemployed in the US. The number unemployed rose from the trough of 6.272 million in Oct 2006 to the peak of 16.147 million in Jan 2010, declining to 13.400 million in Jul 2012, 12.696 million in Aug 2012, 11.742 million in Sep 2012. The level unemployed fell to 11.741 million in Oct 2012, 11.404 million in Nov 2012, 11.844 million in Dec 2012, 13.181 million in Jan 2013, 12.500 million in Feb 2013 and 12.248 million in Jun 2013, all numbers not seasonally adjusted.
Chart I-6, US, Unemployed, Thousands, SA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-7 of the Bureau of Labor Statistics provides the rate of unemployment in the US or unemployed as percent of the labor force. The rate of unemployment of the US rose from 4.7 percent in Jan 2001 to 6.5 percent in Jun 2003, declining to 4.1 percent in Oct 2006. The rate of unemployment jumped to 10.6 percent in Jan 2010 and declined to 7.6 percent in Dec 2012 but increased to 8.5 percent in Jan 2013 and 8.1 percent in Feb 2013, falling back to 7.1 percent in Apr 2013 and 7.8 percent in Jun 2013, all number not seasonally adjusted.
Chart I-7, US, Unemployment Rate, SA, 2001-2013
Source: Bureau of Labor Statistics
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-8 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of unemployed. There was a jump of 81.8 percent in Apr 2009 with subsequent decline and negative rates since 2010. On an annual basis, the level of unemployed rose 59.8 percent in 2009 and 26.1 percent in 2008 with increase of 3.9 percent in 2010, decline of 7.3 percent in 2011, decrease of 9.0 percent in 2012 and decrease of 7.1 percent in Jun 2013 relative to Jun 2012.
Chart I-8, US, Unemployed, 12-month Percentage Change, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-9 of the Bureau of Labor Statistics provides the number of people in part-time occupations because of economic reasons, that is, because they cannot find full-time employment. The number underemployed in part-time occupations not seasonally adjusted rose from 3.732 million in Jan 2001 to 5.270 million in Jan 2004, falling to 3.787 million in Apr 2006. The number underemployed seasonally adjusted jumped to 9.103 million in Nov 2009, falling to 8.168 million in Dec 2011 but increasing to 8.220 million in Jan 2012 and 8.127 million in Feb 2012 but then falling to 7.918 million in Dec 2012 and increasing to 7.918 million in Jun 2013. Without seasonal adjustment, the number employed part-time for economic reasons reached 9.354 million in Dec 2009, declining to 8.918 million in Jan 2012 and 8.166 million in Dec 2012 but increasing to 7.440 million in Jun 2013. The longer the period in part-time jobs the worst are the chances of finding another full-time job.
Chart I-9, US, Part-Time for Economic Reasons, Thousands, SA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-10 of the Bureau of Labor Statistics repeats the behavior of unemployment. The 12-month percentage change of the level of people at work part-time for economic reasons jumped 84.7 percent in Mar 2009 and declined subsequently. The declines have been insufficient to reduce significantly the number of people who cannot shift from part-time to full-time employment. On an annual basis, the number of part-time for economic reasons increased 33.5 percent in 2008 and 51.7 percent in 2009, declining 0.4 percent in 2010, 3.5 percent in 2011 and 5.1 percent in 2012. The number of part-time for economic reasons increased 0.5 percent in Jun 2013 relative to Jun 2012.
Chart I-10, US, Part-Time for Economic Reasons NSA 12-Month Percentage Change, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-11 of the Bureau of Labor Statistics provides the same pattern of the number marginally attached to the labor force jumping to significantly higher levels during the global recession and remaining at historically high levels. The number marginally attached to the labor force not seasonally adjusted increased from 1.295 million in Jan 2001 to 1.691 million in Feb 2004. The number of marginally attached to the labor force fell to 1.299 million in Sep 2006 and increased to 2.609 million in Dec 2009 and 2.800 million in Jan 2011. The number marginally attached to the labor force was 2.540 million in Dec 2011, increasing to 2.809 million in Jan 2012, falling to 2.608 million in Feb 2012, 2.352 million in Mar 2012, 2.363 million in Apr 2012, 2.483 million in May 2012, 2.483 million in Jun 2012, 2.529 million in Jul 2012, 2.561 million in Aug 2012, 2.517 million in Sep 2012, 2.433 million in Oct 2012, 2.505 million in Nov 2012 and 2.614 million in Dec 2012. The number marginally attached to the labor force fell to 2.582 million in Jun 2013.
Chart I-11, US, Marginally Attached to the Labor Force, Thousands, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-12 provides 12-month percentage changes of the marginally attached to the labor force from 2001 to 2013. There was a jump of 56.1 percent in May 2009 during the global recession followed by declines in percentage changes but insufficient negative changes. On an annual basis, the number of marginally attached to the labor force increased in four consecutive years: 15.7 percent in 2008, 37.9 percent in 2009, 11.7 percent in 2010 and 3.5 percent in 2011. The number marginally attached to the labor force fell 2.2 percent on annual basis in 2012 but increased 2.9 percent in the 12 months ending in Dec 2012, fell 13.0 percent in the 12 months ending in Jan 2013, falling 10.7 percent in the 12 months ending in May 2013. The number marginally attached to the labor force increased 4.0 percent in the 12 months ending in Jun 2013.
Chart I-12, US, Marginally Attached to the Labor Force 12-Month Percentage Change, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Table I-4 consists of data and additional calculations using the BLS household survey, illustrating the possibility that the actual rate of unemployment could be 10.9 percent and the number of people in job stress could be around 28.7 million, which is 17.7 percent of the effective labor force. The first column provides for 2006 the yearly average population (POP), labor force (LF), participation rate or labor force as percent of population (PART %), employment (EMP), employment population ratio (EMP/POP %), unemployment (UEM), the unemployment rate as percent of labor force (UEM/LF Rate %) and the number of people not in the labor force (NLF). All data are unadjusted or not-seasonally-adjusted (NSA). The numbers in column 2006 are averages in millions while the monthly numbers for Jun 2012, May 2013 and Jun 2013 are in thousands, not seasonally adjusted. The average yearly participation rate of the population in the labor force was in the range of 66.0 percent minimum to 67.1 percent maximum between 2000 and 2006 with the average of 66.4 percent (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). Table I-4b provides the yearly labor force participation rate from 1979 to 2013. The objective of Table I-4 is to assess how many people could have left the labor force because they do not think they can find another job. Row “LF PART 66.2 %” applies the participation rate of 2006, almost equal to the rates for 2000 to 2006, to the noninstitutional civilian population in Jun 2012 and May 2013 and Jun 2013 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 64.3 percent by Jun 2012 and was 63.5 percent in May 2013 and 63.5 percent in Jun 2013, suggesting that many people simply gave up on finding another job. Row “∆ NLF UEM” calculates the number of people not counted in the labor force because they could have given up on finding another job by subtracting from the labor force with participation rate of 66.2 percent (row “LF PART 66.2%”) the labor force estimated in the household survey (row “LF”). Total unemployed (row “Total UEM”) is obtained by adding unemployed in row “∆NLF UEM” to the unemployed of the household survey in row “UEM.” The row “Total UEM%” is the effective total unemployed “Total UEM” as percent of the effective labor force in row “LF PART 66.2%.” The results are that: (1) there are an estimated 5466 million unemployed in Jun 2013 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM); (2) the total number of unemployed is effectively 17.714 million (Total UEM) and not 12.248 million (UEM) of whom many have been unemployed long term; (3) the rate of unemployment is 10.9 percent (Total UEM%) and not 7.8 percent, not seasonally adjusted, or 7.6 percent seasonally adjusted; and (4) the number of people in job stress is close to 28.7 million by adding the 5.466 million leaving the labor force because they believe they could not find another job. The row “In Job Stress” in Table I-4 provides the number of people in job stress not seasonally adjusted at 28.736 million in Jun 2013, adding the total number of unemployed (“Total UEM”), plus those involuntarily in part-time jobs because they cannot find anything else (“Part Time Economic Reasons”) and the marginally attached to the labor force (“Marginally attached to LF”). The final row of Table I-4 shows that the number of people in job stress is equivalent to 17.7 percent of the labor force in May 2013. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 58.9 percent in Jun 2012, 58.9 percent in May 2013 and 59.0 percent in Jun 2013. The number employed in the US fell from 147.315 million in Jul 2007 to 144.841 million in Jun 2013, by 2.474 million, or decline of 1.7 percent, while the noninstitutional population increased from 231.958 million in Jul 2007 to 245.552 million in Jun 2013, by 13.594 million or increase of 5.9 percent, using not seasonally adjusted data. What really matters for labor input in production and wellbeing is the number of people with jobs or the employment/population ratio, which has declined and does not show signs of increasing. There are several million fewer people working in 2013 than in 2006 and the number employed is not increasing while population increased 13.594 million. The number of hiring relative to the number unemployed measures the chances of becoming employed. The number of hiring in the US economy has declined by 17 million and does not show signs of increasing in an unusual recovery without hiring (http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html).
Table I-4, US, Population, Labor Force and Unemployment, NSA
| 2006 | Jun 2012 | May 2013 | Jun 2013 | |
| POP | 229 | 243,155 | 245,363 | 245,552 |
| LF | 151 | 156,385 | 155,734 | 157,089 |
| PART% | 66.2 | 64.3 | 63.5 | 64.0 |
| EMP | 144 | 143,202 | 144,432 | 144,841 |
| EMP/POP% | 62.9 | 58.9 | 58.9 | 59.0 |
| UEM | 7 | 13,184 | 11,302 | 12,248 |
| UEM/LF Rate% | 4.6 | 8.4 | 7.3 | 7.8 |
| NLF | 77 | 86,770 | 89,629 | 88,463 |
| LF PART 66.2% | 160,969 | 162,430 | 162,555 | |
| ∆NLF UEM | 4,584 | 6,696 | 5,466 | |
| Total UEM | 17,768 | 17,998 | 17,714 | |
| Total UEM% | 11.0 | 11.1 | 10.9 | |
| Part Time Economic Reasons | 8,394 | 7,618 | 8,440 | |
| Marginally Attached to LF | 2,483 | 2,164 | 2,582 | |
| In Job Stress | 28,645 | 27,780 | 28,736 | |
| People in Job Stress as % Labor Force | 17.8 | 17.1 | 17.7 |
Pop: population; LF: labor force; PART: participation; EMP: employed; UEM: unemployed; NLF: not in labor force; ∆NLF UEM: additional unemployed; Total UEM is UEM + ∆NLF UEM; Total UEM% is Total UEM as percent of LF PART 66.2%; In Job Stress = Total UEM + Part Time Economic Reasons + Marginally Attached to LF
Note: the first column for 2006 is in average millions; the remaining columns are in thousands; NSA: not seasonally adjusted
The labor force participation rate of 66.2% in 2006 is applied to current population to obtain LF PART 66.2%; ∆NLF UEM is obtained by subtracting the labor force with participation of 66.2 percent from the household survey labor force LF; Total UEM is household data unemployment plus ∆NLF UEM; and total UEM% is total UEM divided by LF PART 66.2%
Source: US Bureau of Labor Statistics http://www.bls.gov/
In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):
Y = ∑isiyi (1)
This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):
∆Y = ∑i∆siy*i + ∑i∆yis*i (2)
The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:
“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”
Table I-4b and Chart 12-b provide the US labor force participation rate or percentage of the labor force in population. It is not likely that simple demographic trends caused the sharp decline during the global recession and failure to recover earlier levels. The civilian labor force participation rate dropped from the peak of 66.9 percent in Jul 2006 to 64.0 percent in Jun 2013. The civilian labor force participation rate was 63.7 percent on an annual basis in 1979 and 63.4 percent in Dec 1980 and Dec 1981, reaching even 62.9 percent in both Apr and May 1979. The civilian labor force participation rate jumped with the recovery to 64.8 percent on an annual basis in 1985 and 65.9 percent in Jul 1985. Structural factors cannot explain these sudden changes vividly shown visually in the final segment of Chart 12b. Seniors would like to delay their retiring especially because of the adversities of financial repression on their savings. Labor force statistics are capturing the disillusion of potential workers of their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors.
Table I-4b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2013
| Year | Jan | Feb | Mar | Apr | May | Jun | Nov | Dec | Annual |
| 1979 | 62.9 | 63.0 | 63.2 | 62.9 | 62.9 | 64.5 | 63.8 | 63.8 | 63.7 |
| 1980 | 63.3 | 63.2 | 63.2 | 63.2 | 63.5 | 64.6 | 63.7 | 63.4 | 63.8 |
| 1981 | 63.2 | 63.2 | 63.5 | 63.6 | 63.9 | 64.6 | 63.8 | 63.4 | 63.9 |
| 1982 | 63.0 | 63.2 | 63.4 | 63.3 | 63.9 | 64.8 | 64.1 | 63.8 | 64.0 |
| 1983 | 63.3 | 63.2 | 63.3 | 63.2 | 63.4 | 65.1 | 64.1 | 63.8 | 64.0 |
| 1984 | 63.3 | 63.4 | 63.6 | 63.7 | 64.3 | 65.5 | 64.4 | 64.3 | 64.4 |
| 1985 | 64.0 | 64.0 | 64.4 | 64.3 | 64.6 | 65.5 | 64.9 | 64.6 | 64.8 |
| 1986 | 64.2 | 64.4 | 64.6 | 64.6 | 65.0 | 66.3 | 65.4 | 65.0 | 65.3 |
| 1987 | 64.7 | 64.8 | 65.0 | 64.9 | 65.6 | 66.3 | 65.7 | 65.5 | 65.6 |
| 1988 | 65.1 | 65.2 | 65.2 | 65.3 | 65.5 | 66.7 | 66.2 | 65.9 | 65.9 |
| 1989 | 65.8 | 65.6 | 65.7 | 65.9 | 66.2 | 67.4 | 66.7 | 66.3 | 66.5 |
| 1990 | 66.0 | 66.0 | 66.2 | 66.1 | 66.5 | 67.4 | 66.3 | 66.1 | 66.5 |
| 1991 | 65.5 | 65.7 | 65.9 | 66.0 | 66.0 | 67.2 | 66.0 | 65.8 | 66.2 |
| 1992 | 65.7 | 65.8 | 66.0 | 66.0 | 66.4 | 67.6 | 66.2 | 66.1 | 66.4 |
| 1993 | 65.6 | 65.8 | 65.8 | 65.6 | 66.3 | 67.3 | 66.3 | 66.2 | 66.3 |
| 1994 | 66.0 | 66.2 | 66.1 | 66.0 | 66.5 | 67.2 | 66.7 | 66.5 | 66.6 |
| 1995 | 66.1 | 66.2 | 66.4 | 66.4 | 66.4 | 67.2 | 66.5 | 66.2 | 66.6 |
| 1996 | 65.8 | 66.1 | 66.4 | 66.2 | 66.7 | 67.4 | 67.0 | 66.7 | 66.8 |
| 1997 | 66.4 | 66.5 | 66.9 | 66.7 | 67.0 | 67.8 | 67.1 | 67.0 | 67.1 |
| 1998 | 66.6 | 66.7 | 67.0 | 66.6 | 67.0 | 67.7 | 67.1 | 67.0 | 67.1 |
| 1999 | 66.7 | 66.8 | 66.9 | 66.7 | 67.0 | 67.7 | 67.0 | 67.0 | 67.1 |
| 2000 | 66.8 | 67.0 | 67.1 | 67.0 | 67.0 | 67.7 | 66.9 | 67.0 | 67.1 |
| 2001 | 66.8 | 66.8 | 67.0 | 66.7 | 66.6 | 67.2 | 66.6 | 66.6 | 66.8 |
| 2002 | 66.2 | 66.6 | 66.6 | 66.4 | 66.5 | 67.1 | 66.3 | 66.2 | 66.6 |
| 2003 | 66.1 | 66.2 | 66.2 | 66.2 | 66.2 | 67.0 | 66.1 | 65.8 | 66.2 |
| 2004 | 65.7 | 65.7 | 65.8 | 65.7 | 65.8 | 66.5 | 66.1 | 65.8 | 66.0 |
| 2005 | 65.4 | 65.6 | 65.6 | 65.8 | 66.0 | 66.5 | 66.1 | 65.9 | 66.0 |
| 2006 | 65.5 | 65.7 | 65.8 | 65.8 | 66.0 | 66.7 | 66.4 | 66.3 | 66.2 |
| 2007 | 65.9 | 65.8 | 65.9 | 65.7 | 65.8 | 66.6 | 66.1 | 65.9 | 66.0 |
| 2008 | 65.7 | 65.5 | 65.7 | 65.7 | 66.0 | 66.6 | 65.8 | 65.7 | 66.0 |
| 2009 | 65.4 | 65.5 | 65.4 | 65.4 | 65.5 | 66.2 | 64.9 | 64.4 | 65.4 |
| 2010 | 64.6 | 64.6 | 64.8 | 64.9 | 64.8 | 65.1 | 64.4 | 64.1 | 64.7 |
| 2011 | 63.9 | 63.9 | 64.0 | 63.9 | 64.1 | 64.5 | 63.9 | 63.8 | 64.1 |
| 2012 | 63.4 | 63.6 | 63.6 | 63.4 | 63.8 | 64.3 | 63.5 | 63.4 | 63.7 |
| 2013 | 63.3 | 63.2 | 63.1 | 63.1 | 63.5 | 64.0 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart 12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2013
Source: Bureau of Labor Statistics
Broader perspective is provided by Chart 12c of the US Bureau of Labor Statistics. The United States civilian noninstitutional population has increased along a consistent trend since 1948 that continued through earlier recessions and the global recession from IVQ2007 to IIQ2009 and the cyclical expansion after IIIQ2009.
Chart 12c, US, Civilian Noninstitutional Population, Thousands, NSA, 1948-2013
Sources: US Bureau of Labor Statistics
The labor force of the United States in Chart 12d has increased along a trend similar to that of the civilian noninstitutional population in Chart 12c. There is an evident stagnation of the civilian labor force in the final segment of Chart 12d during the current economic cycle. This stagnation is explained by cyclical factors similar to those analyzed by Lazear and Spletzer (2012JHJul22) that motivated an increasing population to drop out of the labor force instead of structural factors. Large segments of the potential labor force are not observed, constituting unobserved unemployment and of more permanent nature because those afflicted have been seriously discouraged from working by the lack of opportunities.
Chart 12d, US, Labor Force, Thousands, NSA, 1948-2013
Sources: US Bureau of Labor Statistics
IIA3 Long-term and Cyclical Comparison of Employment. There is initial discussion here of long-term employment trends followed by cyclical comparison. Growth and employment creation have been mediocre in the expansion beginning in Jul IIIQ2009 from the contraction between Dec IVQ2007 and Jun IIQ2009 (http://www.nber.org/cycles.html). A series of charts from the database of the Bureau of Labor Statistics (BLS) provides significant insight. Chart I-13 provides the monthly employment level of the US from 1948 to 2013. The number of people employed has trebled. There are multiple contractions throughout the more than six decades but followed by resumption of the strong upward trend. The contraction after 2007 is deeper and followed by a flatter curve of job creation. The United States missed this opportunity of high growth in the initial phase of recovery that historically eliminated unemployment and underemployment created during the contraction. The average growth rate of GDP in the first 15 quarters of expansion from IIIQ2009 to IQ2013 is only 2.1 percent (http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html). 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). Table I-5 provides an average of 7.8 percent in the first four quarters of major cyclical expansions while the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 is 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, Table I-4 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 (http://www.bea.gov/iTable/index_nipa.cfm) and cumulative 1.7 percent in the four quarters of 2012 {[(1.02)1/4(1.013)1/4(1.031)1/4(1.004)1/4 – 1]100 = 1.7%} with minor rounding discrepancy using the SSAR of $13,665.4 billion in IVQ2012 relative to the SAAR of $13,441.0 billion in IVQ2011 {[($13665.4/$13441.00-1]100 = 1.7%}. %}. The growth rate in annual equivalent for the four quarters of 2011, the four quarters of 2012 and the first quarter of 2013 is 1.8 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.001 x 1.0044)4/9 -1]100 = 1.8%], or {[($13,725.7/$13,181.2)]4/9-1]100 = 1.8%} dividing the SAAR of IVQ2012 by the SAAR of IVQ2010 in Table I-6 below, obtaining the average for nine quarters and the annual average for one year of four quarters. The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983.
Chart I-13, US, Employment Level, Thousands, SA, 1948-2013
Source: US Bureau of Labor Statistics
The steep and consistent curve of growth of the US labor force is shown in Chart I-14. The contraction beginning in Dec 2007 flattened the path of the US civilian labor force and is now followed by a flatter curve during the current expansion.
Chart I-14, US, Civilian Labor Force, SA, 1948-2013, Thousands
Source: US Bureau of Labor Statistics
Chart I-15 for the period from 1948 to 2013. The labor force participation rate is influenced by numerous factors such as the age of the population. There is no comparable episode in the postwar economy to the sharp collapse of the labor force participation rate in Chart I-15 during the contraction and subsequent expansion after 2007. Aging can reduce the labor force participation rate as many people retire but many may have decided to work longer as their wealth and savings have been significantly reduced. There is an important effect of many people just exiting the labor force because they believe there is no job available for them.
Chart I-15, US, Civilian Labor Force Participation Rate, SA, 1948-2013, %
Source: US Bureau of Labor Statistics
The number of unemployed in the US jumped seasonally adjusted from 5.8 million in May 1979 to 12.1 million in Dec 1982, by 6.3 million, or 108.6 percent. The jump not seasonally adjusted was from 5.4 million in May 1979 to 12.5 million in Jan 1983, by 7.1 million or 131.5 percent. The number of unemployed seasonally adjusted jumped from 6.7 million in Mar 2007 to 15.4 million in Oct 2009, by 8.7 million, or 129.9 percent. The number of unemployed not seasonally adjusted jumped from 6.5 million in Apr 2007 to 16.1 million in Jan 2010, by 9.6 million or 147.7 percent. These are the two episodes with steepest increase in the level of unemployment in Chart I-16.
Chart I-16, US, Unemployed, SA, 1948-2013, Thousands
Source: US Bureau of Labor Statistics
Chart I-17 provides the rate of unemployment of the US from 1948 to 2012. The peak of the series is 10.8 percent in both Nov and Dec 1982. The second highest rates are 10.0 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009. The unadjusted rate of unemployment reached 10.6 percent in Jan 2010.
Chart I-17, US, Unemployment Rate, SA, 1948-2013
Source: US Bureau of Labor Statistics
Chart I-18 provides the number unemployed for 27 weeks and over from 1948 to 2013. The number unemployed for 27 weeks and over jumped from 510,000 in Dec 1978 to 2.9 million in Jun 1983, by 2.4 million, or 480 percent. The number of unemployed 27 weeks or over jumped from 1.1 million in May 2007 to 6.6 million in Jun 2010, by 5.5 million, or 500 percent.
Chart I-18, US, Unemployed for 27 Weeks or More, 1948-2013, Thousands
Source: US Bureau of Labor Statistics
The employment-population ratio in Chart I-19 is an important indicator of wellbeing in labor markets, measuring the number of people with jobs. The US employment-population ratio fell from 63.5 in Dec 2006 to 58.6 in Jul 2011 and stands at 59.0 NSA in Jun 2013. There is no comparable decline followed by stabilization during an expansion in Chart I-19.
Chart I-19, US, Employment-Population Ratio, 1948-2013
Source: US Bureau of Labor Statistics
The number employed part-time for economic reasons in Chart I-20 increased in the recessions and declined during the expansions. In the current cycle, the number employed part-time for economic reasons increased sharply and has not returned to normal levels. Lower growth of economic activity in the expansion after IIIQ2009 failed to reduce the number desiring to work full time but finding only part-time occupations.
Chart I-20, US, Part-Time for Economic Reasons, NSA, 1955-2013, Thousands
Source: US Bureau of Labor Statistics
Table I-5 provides percentage change of real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.7 percent cumulatively and fell 45.6 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7). Data are available for the 1930s only on a yearly basis. US GDP fell 4.8 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1981 to IVQ1982 and 4.7 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first three years of the expansions in the 1980s and the current expansion. GDP grew at 4.5 percent in 1983, 7.2 percent in 1984 and 4.1 percent in 1985 while GDP grew, 2.4 percent in 2010, 1.8 percent in 2011 and 2.2 percent in 2012. Actual cumulative GDP growth in the four quarters of 2012 is 1.7 percent. GDP grew at 4.1 percent in 1985 and 3.5 percent in 1986 while the forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 2.3 to 2.6 percent in 2013 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20130619.pdf).
Table I-5, US, Percentage Change of GDP in the 1930s, 1980s and 2000s, ∆%
| Year | GDP ∆% | Year | GDP ∆% | Year | GDP ∆% |
| 1930 | -8.6 | 1980 | -0.3 | 2000 | 4.1 |
| 1931 | -6.5 | 1981 | 2.5 | 2001 | 1.1 |
| 1932 | -13.1 | 1982 | -1.9 | 2002 | 1.8 |
| 1933 | -1.3 | 1983 | 4.5 | 2003 | 2.5 |
| 1934 | 10.9 | 1984 | 7.2 | 2004 | 3.5 |
| 1935 | 8.9 | 1985 | 4.1 | 2005 | 3.1 |
| 1936 | 13.1 | 1986 | 3.5 | 2006 | 2.7 |
| 1937 | 5.1 | 1987 | 3.2 | 2007 | 1.9 |
| 1938 | -3.4 | 1988 | 4.1 | 2008 | -0.3 |
| 1930 | 8.1 | 1989 | 3.6 | 2009 | -3.1 |
| 1940 | 8.8 | 1990 | 1.9 | 2010 | 2.4 |
| 1941 | 17.1 | 1991 | -0.2 | 2011 | 1.8 |
| 1942 | 18.5 | 1992 | 3.4 | 2012 | 2.2 |
Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm
Characteristics of the four cyclical contractions are provided in Table I-6 with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.8 percent, which is almost equal to the decline of 4.7 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.7 percent cumulatively and fell 45.6 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.
Table I-6, US, Number of Quarters, Cumulative Percentage Contraction and Average Percentage Annual Equivalent Rate in Cyclical Contractions
| Number of Quarters | Cumulative Percentage Contraction | Average Percentage Rate | |
| IIQ1953 to IIQ1954 | 3 | -2.6 | -0.7 |
| IIIQ1957 to IIQ1958 | 3 | -3.1 | -1.1 |
| IVQ1973 to IQ1975 | 5 | -3.2 | -0.6 |
| IQ1980 to IIIQ1980 | 2 | -2.2 | -1.1 |
| IIIQ1981 to IVQ1982 | 4 | -2.7 | -0.69 |
| IVQ2007 to IIQ2009 | 6 | -4.7 | -0.80 |
Sources: Business Cycle Reference Dates; US Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Table I-7 shows the 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. The line “average first four quarters in four expansions” provides the average growth rate of 7.8 percent with 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). Table I-7 provides an average of 7.8 percent in the first four quarters of major cyclical expansions while the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 is 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 27.8 million unemployed or underemployed in the United States for an effective unemployment rate of 17.1 percent (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 (http://www.bea.gov/iTable/index_nipa.cfm) and cumulative 1.7 percent in the four quarters of 2012 {[(1.02)1/4(1.013)1/4(1.031)1/4(1.004)1/4 – 1]100 = 1.7%} with minor rounding discrepancy using the SSAR of $13,665.4 billion in IVQ2012 relative to the SAAR of $13,441.0 billion in IVQ2011 {[($13665.4/$13441.00-1]100 = 1.7%}. %}. The growth rate in annual equivalent for the four quarters of 2011, the four quarters of 2012 and the first quarter of 2013 is 1.8 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.001 x 1.0044)4/9 -1]100 = 1.8%], or {[($13,725.7/$13,181.2)]4/9-1]100 = 1.8%} dividing the SAAR of IVQ2012 by the SAAR of IVQ2010 in Table I-6 below, obtaining the average for nine quarters and the annual average for one year of four quarters. The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983.
Table I-7, US, Number of Quarters, Cumulative Growth and Average Annual Equivalent Growth Rate in Cyclical Expansions
| Number | Cumulative Growth ∆% | Average Annual Equivalent Growth Rate | |
| IIIQ 1954 to IQ1957 | 11 | 12.6 | 4.4 |
| First Four Quarters IIIQ1954 to IIQ1955 | 4 | 7.9 | |
| IIQ1958 to IIQ1959 | 5 | 10.2 | 8.1 |
| First Four Quarters IIIQ1958 to IIQ1959 | 4 | 9.5 | |
| IIQ1975 to IVQ1976 | 8 | 9.5 | 4.6 |
| First Four Quarters IIIQ1975 to IIQ1976 | 4 | 6.1 | |
| IQ1983 to IQ1986 IQ1983 to IIIQ1986 | 13 15 | 19.6 21.3 | 5.7 5.3 |
| First Four Quarters IQ1983 to IVQ1983 | 4 | 7.7 | |
| Average First Four Quarters in Four Expansions* | 7.8 | ||
| IIIQ2009 to IQ2013 | 15 | 8.1 | 2.1 |
| First Four Quarters IIIQ2009 to IIIQ2010 | 3.2 |
*First Four Quarters: 7.9% IIIQ1954-IIQ1955; 9.6% IIIQ1958-IIQ1959; 6.1% IIIQ1975-IIQ1976; 7.7% IQ1983-IVQ1983
Sources: Business Cycle Reference Dates: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm
A group of charts from the database of the Bureau of Labor Statistics facilitate the comparison of employment in the 1980s and 2000s. The long-term charts and tables from I-5 to I-7 in the discussion above confirm the view that the comparison of the current expansion should be with that in the 1980s because of similar dimensions. Chart I-21 provides the level of employment in the US between 1979 and 1989. Employment surged after the contraction and grew rapidly during the decade.
Chart I-21, US, Employed, Thousands, 1979-1989
Source: US Bureau of Labor Statistics
The number employed in the US fell from 147.315 million in Jul 2007 to 144.841 million in Jun 2013, by 2.474 million, or decline of 1.7 percent, while the noninstitutional population increased from 231.958 million in Jul 2007 to 245.552 million in Jun 2013, by 13.594 million or increase of 5.9 percent, using not seasonally adjusted data. Chart I-22 shows tepid recovery early in 2010 followed by near stagnation and marginal expansion.
![clip_image013[1]](file:///C:\Users\cmpelaez\AppData\Local\Temp\WindowsLiveWriter393614076\supfiles263FCC1\image111.png "clip_image013[1]")
Chart I-22, US, Employed, Thousands, 2001-2013
Source: US Bureau of Labor Statistics
There was a steady upward trend in growth of the civilian labor force between 1979 and 1989 as shown in Chart I-23. There were fluctuations but strong long-term dynamism over an entire decade.
Chart I-23, US, Civilian Labor Force, Thousands, 1979-1989
Source: US Bureau of Labor Statistics
The civilian labor force in Chart I-24 grew steadily on an upward trend in the 2000s until it contracted together with the economy after 2007. There has not been recovery during the expansion but rather decline and marginal turn of the year 2011 into expansion in 2012 followed by stability and oscillation into 2013.
![clip_image015[1]](file:///C:\Users\cmpelaez\AppData\Local\Temp\WindowsLiveWriter393614076\supfiles263FCC1\image115.png "clip_image015[1]")
Chart I-24, US, Civilian Labor Force, Thousands, 2001-2013
Source: US Bureau of Labor Statistics
The rate of participation of the labor force in population stagnated during the stagflation and conquest of inflation in the late 1970s and early 1980s, as shown in Chart I-25. Recovery was vigorous during the expansion and lasted through the remainder of the decade.
Chart I-25, US, Civilian Labor Force Participation Rate, 1979-1989, %
Source: US Bureau of Labor Statistics
The rate of participation in the labor force declined after the recession of 2001 and stagnated until 2007, as shown in Chart I-26. The rate of participation in the labor force continued to decline both during the contraction after 2007 and the expansion after 2009 with marginal expansion at the turn of the year into 2012 followed by trend of decline and stability.
![clip_image017[1]](file:///C:\Users\cmpelaez\AppData\Local\Temp\WindowsLiveWriter393614076\supfiles263FCC1\image119.png "clip_image017[1]")
Chart I-26, US, Civilian Labor Force Participation Rate, 2001-2013, %
Source: US Bureau of Labor Statistics
Chart I-27 provides the number unemployed during the 1980s. The number unemployed peaked at 12.051 million in Dec 1982 seasonally adjusted and 12.517 in Jan 1983 million not seasonally adjusted, declining to 8.358 million in Dec 1984 seasonally adjusted and 7.978 million not seasonally adjusted during the first two years of expansion from the contraction. The number unemployed then fell to 6.667 million in Dec 1989 seasonally adjusted and 6.300 million not seasonally adjusted.
Chart I-27, US, Unemployed Thousands 1979-1989
Source: US Bureau of Labor Statistics
Chart I-28 provides the number unemployed from 2001 to 2013. Using seasonally adjusted data, the number unemployed rose from 6.727 million in Oct 2006 to 15.382 million in Oct 2009, declining to 13.049 million in Dec 2011 and to 11.777 million in Jun 2013. Using data not seasonally adjusted, the number unemployed rose from 6.272 million in Oct 2006 to 16.147 million in Jan 2010, declining to 11.844 million in Dec 2012, increasing to 13.181 million in Jan 2013 and declining to 12.248 million in Jun 2013.
![clip_image018[1]](file:///C:\Users\cmpelaez\AppData\Local\Temp\WindowsLiveWriter393614076\supfiles263FCC1\image123.png "clip_image018[1]")
Chart I-28, US, Unemployed Thousands 2001-2013
Source: US Bureau of Labor Statistics
The rate of unemployment peaked at 10.8 percent in both Nov and Dec 1982 seasonally adjusted, as shown in Chart I-29. The rate of unemployment dropped sharply during the expansion after 1984 and continued to decline during the rest of the decade to 5.4 percent in Dec 1989. Using not seasonally adjusted data, the rate of unemployment peaked at 11.4 percent in Jan 1983, declining to 7.0 percent in Dec 1984 and 5.1 percent in Dec 1989.
Chart I-29, US, Unemployment Rate, 1979-1989, %
Source: US Bureau of Labor Statistics
The rate of unemployment in the US seasonally adjusted jumped from 4.4 percent in May 2007 to 10.0 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009, as shown in Chart I-30. The rate of unemployment fluctuated at around 9.0 percent in 2011, declining to 7.8 percent in Dec 2012 and 7.6 percent in Jun 2013.
![clip_image019[1]](file:///C:\Users\cmpelaez\AppData\Local\Temp\WindowsLiveWriter393614076\supfiles263FCC1\image130.png "clip_image019[1]")
Chart I-30, US, Unemployment Rate, 2001-2013, %
Source: US Bureau of Labor Statistics
The employment population ratio seasonally adjusted fell from around 60.1 in Dec 1979 to 57.1 in both Feb and Mar 1983, as shown in Chart I-31. The employment population ratio seasonally adjusted rose back to 59.9 in Dec 1984 and reached 63.0 later in the decade in Dec 1989. Using not seasonally adjusted data, the employment population ratio dropped from 60.4 percent in Oct 1979 to 56.1 percent in Jan 1983, increasing to 59.8 in Dec 1984 and to 62.9 percent in Dec 1989.
Chart I-31, US, Employment Population Ratio, 1979-1989, %
Source: US Bureau of Labor Statistics
The US employment-population ratio seasonally adjusted has fallen from 63.4 in Dec 2006 to 58.6 in Dec 2011, 58.6 in Dec 2012 and 58.7 in Jun 2013, as shown in Chart I-32. The employment population-ratio has stagnated during the expansion. Using not seasonally adjusted data, the employment population ratio fell from 63.6 percent in Jul 2006 to 57.6 percent in Jan 2011, 58.5 percent in Dec 2012 and 59.0 percent in Jun 2013.
Chart I-32, US, Employment Population Ratio, 2001-2013, %
Source: US Bureau of Labor Statistics
The number unemployed for 27 weeks or over peaked at 2.885 million in Jun 1983 as shown in Chart I-33. The number unemployed for 27 weeks or over fell sharply during the expansion to 1.393 million in Dec 1984 and continued to decline throughout the 1980s to 0.635 million in Dec 1989.
Chart I-33, US, Number Unemployed for 27 Weeks or More 1979-1989, Thousands
Source: US Bureau of Labor Statistics
The number unemployed for 27 weeks or over, seasonally adjusted, increased sharply during the contraction as shown in Chart I-34 from 1.131 million in Nov 2006 to 6.704 million in Apr 2010. The number of unemployed for 27 weeks remained at around 6 million during the expansion compared with somewhat above 1 million before the contraction, falling to 4.328 million in Jun 2013 seasonally adjusted and 4.245 million not seasonally adjusted.
Chart I-34, US, Number Unemployed for 27 Weeks or More, 2001-2013, Thousands
Source: US Bureau of Labor Statistics
The number of persons working part-time for economic reasons because they cannot find full-time work peaked during the contraction at 6.857 million in Oct 1982, as shown in Chart I-35. The number of persons at work part-time for economic reasons fell sharply during the expansion to 5.797 million in Dec 1984 and continued to fall throughout the decade to 4.817 million in Dec 1989.
Chart I-35, US, Part-Time for Economic Reasons, 1979-1989, Thousands
Source: US Bureau of Labor Statistics
The number of people working part-time because they cannot find full-time employment, not seasonally adjusted, increased sharply during the contraction from 3.787 million in Apr 2006, not seasonally adjusted, to 9.354 million in Dec 2009, as shown in Chart I-36. The number of people working part-time because of failure to find an alternative occupation stagnated at a very high level during the expansion, declining to 8.440 million not seasonally adjusted in Jun 2013.
![clip_image021[1]](file:///C:\Users\cmpelaez\AppData\Local\Temp\WindowsLiveWriter393614076\supfiles263FCC1\image158.png "clip_image021[1]")
Chart I-36, US, Part-Time for Economic Reasons, 2001-2013, Thousands
Source: US Bureau of Labor Statistics
The number marginally attached to the labor force in Chart I-37 jumped from 1.252 million in Dec 2006 to 2.800 million in Jan 2011, remaining at a high level of 2.540 million in Dec 2011, 2.809 million in Jan 2012, 2.614 million in Dec 2012 and 2.582 million in Jun 2013.
![clip_image023[1]](file:///C:\Users\cmpelaez\AppData\Local\Temp\WindowsLiveWriter393614076\supfiles263FCC1\image162.png "clip_image023[1]")
Chart I-37, US, Marginally Attached to the Labor Force, 2001-2013
Source: US Bureau of Labor Statistics
What is striking about the data in Table I-8 is that the numbers of monthly increases in jobs in 1983 and 1984 are several times higher than in 2010 to 2013. The civilian noninstitutional population growing by 39.6 percent from 174.215 million in 1983 to 243.284 million in 2012 and labor force higher by 38.9 percent, growing from 111.550 million in 1983 to 154.975 million in 2012. Nonfarm payroll jobs increased 48.1 percent from 90.280 million in 1983 to 133.739 million in 2012. Total nonfarm payroll employment seasonally adjusted (SA) increased 195,000 in Jun 2013 and private payroll employment rose 202,000. The average number of nonfarm jobs created in Jan-Jun 2012 was 185,167 while the average number of nonfarm jobs created in Jan-Jun 2013 was 201,833, or increase by 9.0 percent. The average number of private jobs created in the US in Jan-Jun 2012 was 191,000 while the average in Jan-Jun 2013 was 205,667, or increase by 7.7 percent. The US labor force increased from 153.617 million in 2011 to 154.975 million in 2012 by 1.358 million or 113,167 per month. The average increase of nonfarm jobs in the five months from Jan to Jun 2013 was 201,833, which is a rate of job creation inadequate to reduce significantly unemployment and underemployment in the United States because of 113,167 new entrants in the labor force per month with 28.7 million unemployed or underemployed. The difference between the average increase of 201,833 new private nonfarm jobs per month in the US from Jan to Jun 2013 and the 113,167 average monthly increase in the labor force from 2011 to 2012 is 88,666 monthly new jobs net of absorption of new entrants in the labor force. There are 28.7 million in job stress in the US currently. Creation of 88,666 new jobs per month net of absorption of new entrants in the labor force would require 324 months to provide jobs for the unemployed and underemployed (28.736 million divided by 88,666) or 27 years (324 divided by 12). The civilian labor force of the US in Jun 2013 not seasonally adjusted stood at 157.089 million with 12.248 million unemployed or effectively 17.714 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 162.555 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 0.9 years (1 million divided by product of 88,666 by 12, which is 1,063,992). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.854 million (0.05 times labor force of 157.089 million) for new net job creation of 4.394 million (12.248 million unemployed minus 7.854 million unemployed at rate of 5 percent) that at the current rate would take 4.1 years (4.394 million divided by 1.063992). Under the calculation in this blog, there are 17.714 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 162.555 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 9.586 million jobs net of labor force growth that at the current rate would take 9.0 years (17.714 million minus 0.05(162.555 million) = 9.586 million divided by 1.063992, using LF PART 66.2% and Total UEM in Table I-4). These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply. The number employed in the US fell from 147.315 million in Jul 2007 to 144.841 million in Jun 2013, by 2.474 million, or decline of 1.7 percent, while the noninstitutional population increased from 231.958 million in Jul 2007 to 245.552 million in Jun 2013, by 13.594 million or increase of 5.9 percent, using not seasonally adjusted data. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs. There is 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 United States missed this opportunity of high growth in the initial phase of recovery that historically eliminated unemployment and underemployment created during the contraction. 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 growth rate of GDP is 7.8 percent in the first four quarters of major cyclical expansions while the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 is 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, Table I-4 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 (http://www.bea.gov/iTable/index_nipa.cfm) and cumulative 1.7 percent in the four quarters of 2012 {[(1.02)1/4(1.013)1/4(1.031)1/4(1.004)1/4 – 1]100 = 1.7%} with minor rounding discrepancy using the SSAR of $13,665.4 billion in IVQ2012 relative to the SAAR of $13,441.0 billion in IVQ2011 {[($13665.4/$13441.00-1]100 = 1.7%}. %}. The growth rate in annual equivalent for the four quarters of 2011, the four quarters of 2012 and the first quarter of 2013 is 1.8 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.001 x 1.0044)4/9 -1]100 = 1.8%], or {[($13,725.7/$13,181.2)]4/9-1]100 = 1.8%} dividing the SAAR of IVQ2012 by the SAAR of IVQ2010 in Table I-6 below, obtaining the average for nine quarters and the annual average for one year of four quarters. The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983.
Table I-8, US, Monthly Change in Jobs, Number SA
| Month | 1981 | 1982 | 1983 | 2008 | 2009 | 2010 | Private |
| Jan | 95 | -327 | 225 | 14 | -794 | -13 | -17 |
| Feb | 67 | -6 | -78 | -85 | -695 | -40 | -26 |
| Mar | 104 | -129 | 173 | -79 | -830 | 154 | 111 |
| Apr | 74 | -281 | 276 | -215 | -704 | 229 | 170 |
| May | 10 | -45 | 277 | -186 | -352 | 521 | 102 |
| Jun | 196 | -243 | 378 | -169 | -472 | -130 | 94 |
| Jul | 112 | -343 | 418 | -216 | -351 | -86 | 103 |
| Aug | -36 | -158 | -308 | -270 | -210 | -37 | 129 |
| Sep | -87 | -181 | 1114 | -459 | -233 | -43 | 113 |
| Oct | -100 | -277 | 271 | -472 | -170 | 228 | 188 |
| Nov | -209 | -124 | 352 | -775 | -21 | 144 | 154 |
| Dec | -278 | -14 | 356 | -705 | -220 | 95 | 114 |
| 1984 | 2011 | Private | |||||
| Jan | 447 | 69 | 80 | ||||
| Feb | 479 | 196 | 243 | ||||
| Mar | 275 | 205 | 223 | ||||
| Apr | 363 | 304 | 303 | ||||
| May | 308 | 115 | 183 | ||||
| Jun | 379 | 209 | 177 | ||||
| Jul | 312 | 78 | 206 | ||||
| Aug | 241 | 132 | 129 | ||||
| Sep | 311 | 225 | 256 | ||||
| Oct | 286 | 166 | 174 | ||||
| Nov | 349 | 174 | 197 | ||||
| Dec | 127 | 230 | 249 | ||||
| 1985 | 2012 | Private | |||||
| Jan | 266 | 311 | 323 | ||||
| Feb | 124 | 271 | 265 | ||||
| Mar | 346 | 205 | 208 | ||||
| Apr | 195 | 112 | 120 | ||||
| May | 274 | 125 | 152 | ||||
| Jun | 145 | 87 | 78 | ||||
| Jul | 189 | 153 | 177 | ||||
| Aug | 193 | 165 | 131 | ||||
| Sep | 204 | 138 | 118 | ||||
| Oct | 187 | 160 | 217 | ||||
| Nov | 209 | 247 | 256 | ||||
| Dec | 168 | 219 | 224 | ||||
| 1985 | 2013 | Private | |||||
| Jan | 123 | 148 | 164 | ||||
| Feb | 107 | 332 | 319 | ||||
| Mar | 93 | 142 | 154 | ||||
| Apr | 188 | 199 | 188 | ||||
| May | 125 | 195 | 207 | ||||
| Jun | -93 | 195 | 202 | ||||
| Jul | 318 | ||||||
| Aug | 113 | ||||||
| Sep | 346 | ||||||
| Oct | 187 | ||||||
| Nov | 186 | ||||||
| Dec | 204 |
Source: US Bureau of Labor Statistics
Charts numbered from I-38 to I-41 from the database of the Bureau of Labor Statistics provide a comparison of payroll survey data for the contractions and expansions in the 1980s and after 2007. Chart I-38 provides total nonfarm payroll jobs from 2001 to 2013. The sharp decline in total nonfarm jobs during the contraction after 2007 has been followed by initial stagnation and then inadequate growth in 2012 and 2013.
Chart I-38, US, Total Nonfarm Payroll Jobs SA 2001-2013
Source: US Bureau of Labor Statistics
Chart I-39 provides total nonfarm jobs SA from 1979 to 1989. Recovery is strong throughout the decade with the economy growing at trend.
Chart I-39, US, Total Nonfarm Payroll Jobs SA 1979-1989
Source: US Bureau of Labor Statistics
Most job creation in the US is by the private sector. Chart I-40 shows the sharp destruction of private payroll jobs during the contraction after 2007. There has been growth after 2010 but insufficient to recover higher levels of employment prevailing before the contraction. At current rates, recovery of employment may spread over several years in contrast with past expansions of the business cycle in the US.
Chart I-40, US, Total Private Payroll Jobs SA 2001-2013
Source: US Bureau of Labor Statistics
In contrast, growth of private payroll jobs in the US recovered vigorously during the expansion in 1983 through 1985, as shown in Chart I-41. Rapid growth of creation of private jobs continued throughout the 1980s.
Chart I-41, US, Total Private Payroll Jobs SA 1979-1989
Source: US Bureau of Labor Statistics
IA4 Creation of Jobs. Types of jobs created, and not only the pace of job creation, may be important. Aspects of growth of payroll jobs from Jun 2012 to Jun 2013, not seasonally adjusted (NSA), are provided in Table I-9. Total nonfarm employment increased by 2,249,000 (row A, column Change), consisting of growth of total private employment by 2,289,000 (row B, column Change) and decrease by 40,000 of government employment (row C, column Change). Monthly average growth of private payroll employment has been 190,750, which is mediocre relative to 24 to 30 million in job stress, while total nonfarm employment has grown on average by only 187,417 per month, which barely keeps with 113,167 new entrants per month in the labor force. These monthly rates of job creation are insufficient to meet the demands of new entrants in the labor force and thus perpetuate unemployment and underemployment. Manufacturing employment increased by 33,000, at the monthly rate of 2,750 while private service providing employment grew by 2,060,000, at the monthly rate of 171,667. An important feature in Table I-9 is that jobs in professional and business services increased by 579,000 with temporary help services increasing by 151,000. This episode of jobless recovery is characterized by part-time jobs and creation of jobs that are inferior to those that have been lost. Monetary and fiscal stimuli fail to increase consumption in a fractured job market. The segment leisure and hospitality added 505,000 jobs in 12 months. An important characteristic is that the loss of government jobs has stabilized in federal government with loss of 67,000 jobs while states reduced 34,000 jobs and local government added 61,000 jobs. Local government provides the bulk of government jobs, 14.255 million, while federal government provides 2.766 million and states government 4.786 million.
Table I-9, US, Employees in Nonfarm Payrolls Not Seasonally Adjusted, in Thousands
| Jun 2012 | Jun 2013 | Change | |
| A Total Nonfarm | 134,556 | 136,805 | 2,249 |
| B Total Private | 112,709 | 114,998 | 2,289 |
| B1 Goods Producing | 18,700 | 18,929 | 229 |
| B1a Manufacturing | 12,016 | 12,049 | 33 |
| B2 Private service providing | 94,009 | 96,069 | 2,060 |
| B2a Wholesale Trade | 5,716 | 5,800 | 84 |
| B2b Retail Trade | 14,837 | 15,144 | 307 |
| B2c Transportation & Warehousing | 4,419 | 4,465 | 46 |
| B2d Financial Activities | 7,833 | 7,947 | 114 |
| B2e Professional and Business Services | 18,062 | 18,641 | 579 |
| B2e1 Temporary help services | 2,538 | 2,689 | 151 |
| B2f Health Care & Social Assistance | 16,954 | 17,297 | 343 |
| B2g Leisure & Hospitality | 14,311 | 14,816 | 505 |
| C Government | 21,847 | 21,807 | -40 |
| C1 Federal | 2,833 | 2,766 | -67 |
| C2 State | 4,820 | 4,786 | -34 |
| C3 Local | 14,194 | 14,255 | 61 |
Note: A = B+C, B = B1 + B2, C=C1 + C2 + C3
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Greater detail on the types of jobs created is provided in Table I-10 with data for May and Jun 2013. Strong seasonal effects are shown by the significant difference between seasonally adjusted (SA) and not-seasonally-adjusted (NSA) data. The purpose of adjusting for seasonality is to isolate nonseasonal effects. The 175,000 SA total nonfarm jobs created in May 2013 relative to Apr 2013 actually correspond to increase of 885,000 jobs NSA, as shown in row A. The 202,000 total private payroll jobs SA created in Jun 2013 relative to May 2013 actually correspond to increase of 856,000 jobs NSA. The analysis of NSA job creation in the prior Table I-9 does show improvement over the 12 months ending in Jun 2013 that is not clouded by seasonal variations but is inadequate number of jobs created. In fact, the 12-month rate of job creation without seasonal adjustment is stronger indication of marginal improvement in the US job market but that is insufficient in even making a dent in about 30 million people unemployed or underemployed. Benchmark and seasonal adjustments affect comparability of data over time.
Table I-10, US, Employees on Nonfarm Payrolls and Selected Industry Detail, Thousands, SA and NSA
| May 2013 SA | Jun 2013 SA | ∆ | May 2013 NSA | Jun 2013 NSA | ∆ | |
| A Total Nonfarm | 135,707 | 135,902 | 195 | 136,383 | 136,805 | 422 |
| B Total Private | 113,849 | 114,051 | 202 | 114,142 | 114,998 | 856 |
| B1 Goods Producing | 18,635 | 18,643 | 8 | 18,665 | 18,929 | 264 |
| B1a Constr. | 5,799 | 5,812 | 13 | 5,837 | 6,003 | 166 |
| B Mfg | 11,970 | 11,964 | -6 | 11,960 | 12,049 | 89 |
| B2 Private Service Providing | 95,214 | 95,408 | 194 | 95,477 | 96,069 | 592 |
| B2a Wholesale Trade | 5,749 | 5,760 | 11 | 5,758 | 5,800 | 42 |
| B2b Retail Trade | 15,099 | 15,136 | 37 | 15,031 | 15,144 | 113 |
| B2c Couriers & Mess. | 529 | 528 | -1 | 518 | 518 | 0 |
| B2d Health-care & Social Assistance | 17,280 | 17,303 | 23 | 17,299 | 17,297 | -2 |
| B2De Profess. & Business Services | 18,484 | 18,537 | 53 | 18,491 | 18,641 | 150 |
| B2De1 Temp Help Services | 2,672 | 2,682 | 10 | 2,664 | 2,689 | 25 |
| B2f Leisure & Hospit. | 14,155 | 14,230 | 75 | 14,370 | 14,816 | 446 |
Notes: ∆: Absolute Change; Constr.: Construction; Mess.: Messengers; Temp: Temporary; Hospit.: Hospitality. SA aggregates do not add because of seasonal adjustment.
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-42 of the Board of Governors of the Federal Reserve System shows that output of durable manufacturing accelerated in the 1980s and 1990s with slower growth in the 2000s perhaps because processes matured. Growth was robust after the major drop during the global recession but appears to vacillate in the final segment.
Chart I-42, US, Output of Durable Manufacturing, 1972-2013
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/default.htm
Manufacturing jobs fell 6,000 in Jun 2013 relative to May 2013, seasonally adjusted (Table I-10 and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html). Manufacturing jobs not seasonally adjusted increased 33,000 from Jun 2012 to Jun 2013 or at the average monthly rate of 2,750. There are effects of the weaker economy and international trade together with the yearly adjustment of labor statistics. In the six months ending in May 2013, United States national industrial production accumulated increase of 0.5 percent at the annual equivalent rate of 1.0 percent, which is lower than growth of 1.6 percent in 12 months. Excluding growth of 0.7 in Feb 2013, growth in the remaining five onths from Dec 2012 to May 2013 accumulated to minus 0.2 percent or minus 0.5 percent annual equivalent. Industrial production stagnated in three of the six months and fell in one. The Fed analyzes capacity utilization of total industry in its report (http://www.federalreserve.gov/releases/g17/Current/default.htm): “The rate of capacity utilization for total industry edged down 0.1 percentage point to 77.6 percent, a rate 0.2 percentage point below its level of a year earlier and 2.6 percentage points below its long-run (1972–2012) average.” United States industry is apparently decelerating with some strength at the margin.
Manufacturing increased 0.1 percent in May 2013 after decreasing 0.4 percent in Apr 2013 seasonally adjusted, increasing 1.7 percent not seasonally adjusted in 12 months. Manufacturing grew cumulatively 0.9 percent in the six months ending in May 2013 or at the annual equivalent rate of 1.8 percent. Excluding the increase of 0.9 percent in Dec 2012 perhaps partly because of recovery from hurricane Sandy, manufacturing accumulated growth of 0.0 percent from Jan 2013 to May 2013 or at the annual equivalent rate of 0.0 percent. Manufacturing fell 7.3 percent from the peak in Jun 2007 to May 2013 and increased 18.6 from the trough in Apr 2009 to May 2013. Manufacturing output in May 2013 is 7.3 percent below the peak in Jun 2007.
Table I-11 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 86.4 percent in US national income in IVQ2012 and 86.7 percent in IQ2013. Most of US national income is in the form of services. In Jun 2013, there were 136.805 million nonfarm jobs NSA in the US, according to estimates of the establishment survey of the Bureau of Labor Statistics (BLS) (http://www.bls.gov/news.release/empsit.nr0.htm Table B-1). Total private jobs of 114.998 million NSA in Jun 2013 accounted for 84.1 percent of total nonfarm jobs of 136.805 million, of which 12.049 million, or 10.5 percent of total private jobs and 8.8 percent of total nonfarm jobs, were in manufacturing. Private service-producing jobs were 96.069 million NSA in Jun 2013, or 70.2 percent of total nonfarm jobs and 83.5 percent of total private-sector jobs. Manufacturing has share of 11.0 percent in US national income in IQ2013, as shown in Table 1-11. Most income in the US originates in services. Subsidies and similar measures designed to increase manufacturing jobs will not increase economic growth and employment and may actually reduce growth by diverting resources away from currently employment-creating activities because of the drain of taxation.
Table I-11, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total
| SAAR | % Total | SAAR IQ2013 | % Total | |
| National Income WCCA | 14,230.5 | 100.0 | 14,317.3 | 100.0 |
| Domestic Industries | 13,963.9 | 97.9 | 14,070.3 | 98.3 |
| Private Industries | 12,300.8 | 86.4 | 12,408.8 | 86.7 |
| Agriculture | 139.6 | 1.0 | 156.2 | 1.1 |
| Mining | 221.7 | 1.6 | 210.3 | 1.5 |
| Utilities | 211.7 | 1.5 | 218.7 | 1.5 |
| Construction | 606.9 | 4.3 | 625.0 | 4.4 |
| Manufacturing | 1599.8 | 11.2 | 1576.9 | 11.0 |
| Durable Goods | 921.3 | 6.5 | 909.6 | 6.4 |
| Nondurable Goods | 678.4 | 4.8 | 667.3 | 4.7 |
| Wholesale Trade | 857.2 | 6.0 | 877.8 | 6.1 |
| Retail Trade | 973.3 | 6.8 | 974.8 | 6.8 |
| Transportation & WH | 417.9 | 2.9 | 425.4 | 3.0 |
| Information | 496.2 | 3.5 | 522.1 | 3.6 |
| Finance, Insurance, RE | 2377.2 | 16.7 | 2395.0 | 16.7 |
| Professional, BS | 2042.5 | 14.4 | 2053.5 | 14.3 |
| Education, Health Care | 1402.0 | 9.9 | 1408.9 | 9.8 |
| Arts, Entertainment | 548.3 | 3.9 | 553.0 | 3.9 |
| Other Services | 406.6 | 2.9 | 411.3 | 2.9 |
| Government | 1663.0 | 11.7 | 1661.5 | 11.6 |
| Rest of the World | 266.6 | 1.9 | 247.0 | 1.7 |
Notes: SSAR: Seasonally-Adjusted Annual Rate; WCCA: Without Capital Consumption Adjustment by Industry; WH: Warehousing; RE, includes rental and leasing: Real Estate; Art, Entertainment includes recreation, accommodation and food services; BS: business services
Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm
The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). Table I-12 provides total annual level nonfarm employment in the US for the 1980s and the 2000s, which is different from 12 months comparisons. Nonfarm jobs rose by 4.853 million from 1982 to 1984, or 5.4 percent, and continued rapid growth in the rest of the decade. In contrast, nonfarm jobs are down by 7.728 million in 2010 relative to 2007 and fell by 959,000 in 2010 relative to 2009 even after six quarters of GDP growth. Monetary and fiscal stimuli have failed in increasing growth to rates required for mitigating job stress. The initial growth impulse reflects a flatter growth curve in the current expansion. Nonfarm jobs declined from 137.645 million in 2007 to 133.739 million in 2012, by 3.906 million or 2.8 percent.
Table I-12, US, Total Nonfarm Employment in Thousands
| Year | Total Nonfarm | Year | Total Nonfarm |
| 1980 | 90,528 | 2000 | 131,881 |
| 1981 | 91,289 | 2001 | 131,919 |
| 1982 | 89,677 | 2002 | 130,450 |
| 1983 | 90,280 | 2003 | 130,100 |
| 1984 | 94,530 | 2004 | 131,509 |
| 1985 | 97,511 | 2005 | 133,747 |
| 1986 | 99,474 | 2006 | 136,125 |
| 1987 | 102,088 | 2007 | 137,645 |
| 1988 | 105,345 | 2008 | 136,852 |
| 1989 | 108,014 | 2009 | 130,876 |
| 1990 | 109,487 | 2010 | 129,917 |
| 1991 | 108,377 | 2011 | 131,497 |
| 1992 | 108,745 | 2012 | 133,739 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
The highest average yearly percentage of unemployed to the labor force since 1940 was 14.6 percent in 1940 followed by 9.9 percent in 1941, 8.5 percent in 1975, 9.7 percent in 1982 and 9.6 percent in 1983 (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). The rate of unemployment remained at high levels in the 1930s, rising from 3.2 percent in 1929 to 22.9 percent in 1932 in one estimate and 23.6 percent in another with real wages increasing by 16.4 percent (Margo 1993, 43; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 214-5). There are alternative estimates of 17.2 percent or 9.5 percent for 1940 with real wages increasing by 44 percent. Employment declined sharply during the 1930s. The number of hours worked remained in 1939 at 29 percent below the level of 1929 (Cole and Ohanian 1999). Private hours worked fell in 1939 to 25 percent of the level in 1929. The policy of encouraging collusion through the National Industrial Recovery Act (NIRA), to maintain high prices, together with the National Labor Relations Act (NLRA), to maintain high wages, prevented the US economy from recovering employment levels until Roosevelt abandoned these policies toward the end of the 1930s (for review of the literature analyzing the Great Depression see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 198-217).
The Bureau of Labor Statistics (BLS) makes yearly revisions of its establishment survey (Harris 2011BA):
“With the release of data for January 2011, the Bureau of Labor Statistics (BLS) introduced its annual revision of national estimates of employment, hours, and earnings from the Current Employment Statistics (CES) monthly survey of nonfarm establishments. Each year, the CES survey realigns its sample-based estimates to incorporate universe counts of employment—a process known as benchmarking. Comprehensive counts of employment, or benchmarks, are derived primarily from unemployment insurance (UI) tax reports that nearly all employers are required to file with State Workforce Agencies.”
The number of not seasonally adjusted total private jobs in the US in Dec 2010 is 108.464 million, declining to 106.079 million in Jan 2011, or by 2.385 million, because of the adjustment of a different benchmark and not actual job losses. The not seasonally adjusted number of total private jobs in Dec 1984 is 80.250 million, declining to 78.704 million in Jan 1985, or by 1.546 million for the similar adjustment. Table I-13 attempts to measure job losses and gains in the recessions and expansions of 1981-1985 and 2007-2011. The final ten rows provide job creation from May 1983 to May 1984 and from May 2010 to May 2011, that is, at equivalent stages of the recovery from two comparable strong recessions. The row “Change ∆%” for May 1983 to May 1984 shows an increase of total nonfarm jobs by 4.9 percent and of 5.9 percent for total private jobs. The row “Change ∆%” for May 2010 to May 2011 shows an increase of total nonfarm jobs by 0.7 percent and of 1.7 percent for total private jobs. The last two rows of Table 7 provide a calculation of the number of jobs that would have been created from May 2010 to May 2011 if the rate of job creation had been the same as from May 1983 to May 1984. If total nonfarm jobs had grown between May 2010 and May 2011 by 4.9 percent, as between May 1983 and May 1984, 6.409 million jobs would have been created in the past 12 months for a difference of 5.457 million more total nonfarm jobs relative to 0.952 million jobs actually created. If total private jobs had grown between May 2010 and May 2011 by 5.9 percent as between May 1983 and May 1984, 6.337 million private jobs would have been created for a difference of 4.539 million more total private jobs relative to 1.798 million jobs actually created.
Table I-13, US, Total Nonfarm and Total Private Jobs Destroyed and Subsequently Created in
Two Recessions IIIQ1981-IVQ1982 and IVQ2007-IIQ2009, Thousands and Percent
| Total Nonfarm Jobs | Total Private Jobs | |
| 06/1981 # | 92,288 | 75,969 |
| 11/1982 # | 89,482 | 73,260 |
| Change # | -2,806 | -2,709 |
| Change ∆% | -3.0 | -3.6 |
| 12/1982 # | 89,383 | 73,185 |
| 05/1984 # | 94,471 | 78,049 |
| Change # | 5,088 | 4,864 |
| Change ∆% | 5.7 | 6.6 |
| 11/2007 # | 139,090 | 116,291 |
| 05/2009 # | 131,626 | 108,601 |
| Change % | -7,464 | -7,690 |
| Change ∆% | -5.4 | -6.6 |
| 12/2009 # | 130,178 | 107,338 |
| 05/2011 # | 131,753 | 108,494 |
| Change # | 1,575 | 1,156 |
| Change ∆% | 1.2 | 1.1 |
| 05/1983 # | 90,005 | 73,667 |
| 05/1984 # | 94,471 | 78,049 |
| Change # | 4,466 | 4,382 |
| Change ∆% | 4.9 | 5.9 |
| 05/2010 # | 130,801 | 107,405 |
| 05/2011 # | 131,753 | 109,203 |
| Change # | 952 | 1,798 |
| Change ∆% | 0.7 | 1.7 |
| Change # by ∆% as in 05/1984 to 05/1985 | 6,409* | 6,337** |
| Difference in Jobs that Would Have Been Created | 5,457 = | 4,539 = |
*[(130,801x1.049)-130,801] = 6,409 thousand
**[(107,405)x1.059 – 107,405] = 6,337 thousand
Source: http://www.bls.gov/data/
IB 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 (Section I 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 (Section I 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 27.8 million persons unemployed or underemployed, which is 17.1 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-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 (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, 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 (Section I an 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 (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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/06/twenty-eight-million-unemployed-or.html) and the collapse of hiring (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).
© Carlos M. Pelaez, 2010, 2011, 2012, 2013
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