Sunday, July 12, 2015

Oscillating Valuations of Risk Financial Assets, Recovery without Hiring, Ten Million Fewer Full-time Jobs, Youth and Middle-Age Unemployment, Collapse of United States Dynamism of Income Growth and Employment Creation, World Cyclical Slow Growth and Global Recession Risk: Part II

 

Oscillating Valuations of Risk Financial Assets, Recovery without Hiring, Ten Million Fewer Full-time Jobs, Youth and Middle-Age Unemployment, Collapse of United States Dynamism of Income Growth and Employment Creation, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015

I Recovery without Hiring

IA1 Hiring Collapse

IA2 Labor Underutilization

ICA3 Ten Million Fewer Full-time Jobs

IA4 Theory and Reality of Cyclical Slow Growth Not Secular Stagnation: Youth and

Middle-Age Unemployment

II United States International Trade

II IB Collapse of United States Dynamism of Income Growth and Employment Creation

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

I Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels increased by only 4 percent from Jan 2009 to Jan 2012. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job in early 2012 is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn, there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html). Lazear and Spletzer (2012Mar, 1) argue that reductions of churn reduce the operational effectiveness of labor markets. Churn is part of the allocation of resources or in this case labor to occupations of higher marginal returns. The decline in churn can harm static and dynamic economic efficiency. Losses from decline of churn during recessions can affect an economy over the long-term by preventing optimal growth trajectories because resources are not used in the occupations where they provide highest marginal returns. Lazear and Spletzer (2012Mar 7-8) conclude that: “under a number of assumptions, we estimate that the loss in output during the recession [of 2007 to 2009] and its aftermath resulting from reduced churn equaled $208 billion. On an annual basis, this amounts to about .4% of GDP for a period of 3½ years.”

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

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

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

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

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

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

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

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

There is socio-economic stress in the combination of adverse events and cyclical performance: 

The Bureau of Labor Statistics (BLS) revised on Mar 10, 2015 “Effective with this release, revisions to data from January 2010 forward incorporate annual updates to| the Current Employment Statistics employment estimates and the Job Openings and Labor Turnover Survey seasonal adjustment factors.” (http://www.bls.gov/jlt/). Hiring in the nonfarm sector (HNF) has declined from 63.327 million in 2006 to 58.657 million in 2014 or by 4.670 million while hiring in the private sector (HP) has declined from 59.128 million in 2006 to 55.048 million in 2014 or by 4.080 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.0 in 2005 to 42.2 in 2014 and in the private sector (RHP) from 52.7 in 2005 to 47.0 in 2014. Hiring has not recovered as in previous cyclical expansions because of the low rate of economic growth in the current cyclical expansion. The civilian noninstitutional population or those in condition to work increased from 228.815 million in 2006 to 247.947 million in 2014 or by 19.132 million. Hiring has not recovered precession levels while needs of hiring multiplied because of growth of population by more than 19 million. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 23 quarters from IIIQ2009 to IQ2015. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IQ2015 (http://www.bea.gov/newsreleases/national/gdp/2015/pdf/gdp1q15_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IQ2015 would have accumulated to 23.9 percent. GDP in IQ2015 would be $18,574.8 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,287.1 billion than actual $16,287.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 25.0 million unemployed or underemployed equivalent to actual unemployment/underemployment of 15.1 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html). US GDP in IQ2015 is 12.3 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,287.7 billion in IQ2015 or 8.6 percent at the average annual equivalent rate of 1.2 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth at average 3.3 percent per year from May 1919 to May 2015. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 126.2585 in May 2015. The actual index NSA in May 2015 is 101.5858, which is 19.5 percent below trend. Manufacturing output grew at average 2.4 percent between Dec 1986 and Dec 2014. Using trend growth of 2.4 percent per year, the index would increase to 118.3245 in May 2015. The output of manufacturing at 101.5858 in May 2015 is 14.1 percent below trend under this alternative calculation.

Table I-1, US, Annual Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US in Thousands and Percentage of Total Employment

 

HNF

Rate RNF

HP

Rate HP

2001

62,633

47.4

58,501

52.7

2002

58,479

44.8

54,665

50.1

2003

56,949

43.7

53,584

49.3

2004

60,263

45.7

56,573

51.4

2005

62,951

47.0

59,179

52.7

2006

63,327

46.4

59,128

51.7

2007

62,104

45.0

57,797

49.9

2008

54,745

39.9

51,316

44.8

2009

45,931

35.0

42,703

39.3

2010

48,740

37.4

44,903

41.7

2011

50,283

38.1

47,179

43.0

2012

52,367

39.0

48,916

43.6

2013

54,241

39.8

50,787

44.3

2014

58,657

42.2

55,048

47.0

Source: Bureau of Labor Statistics

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

Chart I-1 shows the annual level of total nonfarm hiring (HNF) that collapsed during the global recession after 2007 in contrast with milder decline in the shallow recession of 2001. Nonfarm hiring has not recovered, remaining at a depressed level. The civilian noninstitutional population or those in condition to work increased from 228.815 million in 2006 to 247.947 million in 2014 or by 19.132 million. Hiring has not recovered precession levels while needs of hiring multiplied because of growth of population by more than 19 million.

clip_image001

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2014

Source: US Bureau of Labor Statistics

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

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

clip_image002

Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2014

Source: US Bureau of Labor Statistics

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

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table I-2. There were much milder declines in 2002 of 6.6 percent and 2.6 percent in 2003 followed by strong rebounds of 5.8 percent in 2004 and 4.5 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 1.9 in 2007, 11.8 in 2008 and 16.1 percent in 2009. On a yearly basis, nonfarm hiring grew 6.1 percent in 2010 relative to 2009, 3.2 percent in 2011, 4.1 percent in 2012 and 3.6 percent in 2013. Nonfarm hiring grew 8.1 percent in 2014. The relatively large length of 23 quarters of the current expansion reduces the likelihood of significant recovery of hiring levels in the United States because lower rates of growth and hiring in the final phase of expansions.

Table I-2, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2002-2014

Year

Annual

∆%

2002

-6.6

2003

-2.6

2004

5.8

2005

4.5

2006

0.6

2007

-1.9

2008

-11.8

2009

-16.1

2010

6.1

2011

3.2

2012

4.1

2013

3.6

2014

8.1

Source: US Bureau of Labor Statistics

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

Total private hiring (HP) 12-month percentage changes of annual data are provided in Chart I-4. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2014.

clip_image003

Chart I-4, US, Total Nonfarm Hiring Level, Annual, ∆%, 2001-2014

Source: Bureau of Labor Statistics

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

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

clip_image004

Chart I-5, US, Total Private Hiring, Annual, 2001-2014

Source: Bureau of Labor Statistics

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

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

clip_image005

Chart I-5A, US, Rate Total Private Hiring Level, Annual, 2001-2014

Source: Bureau of Labor Statistics

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

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of May in the years from 2001 to 2015 in Table I-3. Hiring numbers are in thousands. There is recovery in HNF from 4143 thousand (or 4.1 million) in May 2009 to 4830 thousand in May 2010, 4647 thousand in May 2011, 4979 thousand in May 2012, 5122 thousand in May 2013, 5435 thousand in May 2014 and 5597 thousand in May 2015 for cumulative gain of 35.1 percent at average rate of 5.1 percent per year. HP rose from 3871 thousand in May 2009 to 4071 thousand in May 2010, 4367 thousand in May 2011, 4657 thousand in May 2012, 4820 thousand in May 2013, 5008 thousand in May 2014 and 5241 thousand in May 2015 for cumulative gain of 35.4 percent at the average yearly rate of 5.2 percent. HNF has fallen from 5955 thousand in May 2006 to 5597 thousand in May 2015 or by 6.0 percent. HP has fallen from 5599 thousand in May 2006 to 5241 thousand in May 2015 or by 6.4 percent. The civilian noninstitutional population of the US, or those in condition of working, rose from 228.428 million in May 2006 to 250.455 million in May 2015, by 22.027 million or 9.6 percent. There is often ignored ugly fact that hiring fell by around 6.4 percent while population available for working increased around 9.6 percent. The civilian noninstitutional population of the US, or individuals in condition to work, rose from 228.815 million in 2006 to 247.947 million in 2014 or by 19.132 million and the civilian labor force from 151.428 million in 2006 to 155.922 million in 2014 or by 4.494 million (http://www.bls.gov/data/). The number of nonfarm hires in the US fell from 63.327 million in 2006 to 58.657 million in 2014 or by 4.670 million and the number of private hires fell from 59.128 million in 2006 to 55.048 million in 2014 or by 4.080 million (http://www.bls.gov/jlt/). Private hiring of 59.128 million in 2006 was equivalent to 25.8 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 55.048 million in 2014 or 22.2 percent of the civilian noninstitutional population of 247.947 million in 2014. The percentage of hiring in civilian noninstitutional population of 25.8 percent in 2006 would correspond to 63.970 million of hiring in 2014, which would be 8.922 million higher than actual 55.048 million in 2014. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html) explains the fact that there are many million fewer hires in the US than before the global recession. The labor market continues to be fractured, failing to provide an opportunity to exit from unemployment/underemployment or to find an opportunity for advancement away from declining inflation-adjusted earnings.

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

Thousands and in Percentage of Total Employment Not Seasonally Adjusted

 

HNF

Rate RNF

HP

Rate HP

2001 May

5811

4.4

5437

4.9

2002 May

5305

4.0

4956

4.5

2003 May

5023

3.8

4740

4.4

2004 May

5385

4.1

5095

4.6

2005 May

5720

4.3

5403

4.8

2006 May

5955

4.4

5599

4.9

2007 May

5728

4.1

5335

4.6

2008 May

5088

3.7

4761

4.1

2009 May

4143

3.1

3871

3.6

2010 May

4830

3.7

4071

3.8

2011 May

4647

3.5

4367

4.0

2012 May

4979

3.7

4657

4.1

2013 May

5122

3.7

4820

4.2

2014 May

5435

3.9

5108

4.4

2015 May

5597

3.9

5241

4.4

Source: Bureau of Labor Statistics

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

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2015. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4830 in May 2010 until it surpassed it with 4962 in Jun 2011 but declined to 3114 in Dec 2012. Nonfarm hiring fell to 3025 in Dec 2011 from 3809 in Nov 2011 and to revised 3626 in Feb 2012, increasing to 4195 in Mar 2012, 3114 in Dec 2012 and 4232 in Jan 2013 and declining to 3828 in Feb 2014. Nonfarm hires not seasonally adjusted increased to 4273 in Nov 2013 and 3263 in Dec 2013. Nonfarm hires reached 3750 in Dec 2014 and 5597 in Mar 2015. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Oct 2011 was 4217 thousand, increasing to revised 4451 thousand in Feb 2012, or 5.5 percent, moving to 4361 in Dec 2012 for cumulative increase of 2.5 percent from 4254 in Dec 2011 and 4545 in Dec 2013 for increase of 4.2 percent relative to 4361 in Dec 2012. The number of hires not seasonally adjusted was 4962 in Jun 2011, falling to 3025 in Dec 2011 but increasing to 4135 in Jan 2012 and declining to 3114 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 39.0 percent from 4962 in Jun 2011 to 3025 in Dec 2011 and fell 37.9 percent from 5013 in Jun 2012 to 3114 in Dec 2012 in a yearly-repeated seasonal pattern. The number of nonfarm hires not seasonally adjusted fell from 5079 in Jun 2013 to 3263 in Dec 2013, or decline of 35.8 percent, showing strong seasonality. The number of nonfarm hires not seasonally adjusted fell from 5459 in Jun 2014 to 3750 in Dec 2014 or 31.3 percent.

clip_image006

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2015 Month SA

Source: Bureau of Labor Statistics

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

Similar behavior occurs in the rate of nonfarm hiring in Chart I-7. Recovery in early 2010 was followed by decline and stabilization at a lower level but with stability in monthly SA estimates of 3.2 in Aug 2011 to 3.2 in Jan 2012, increasing to 3.3 in May 2012 and falling to 3.2 in Jun 2012. The rate stabilized at 3.2 in Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.2 in Dec 2012 and 3.3 in Dec 2013. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.3 in Dec 2011, climbing to 3.7 in Jun 2012 but falling to 2.3 in Dec 2012. The rate of nonfarm hires not seasonally adjusted fell from 3.7 in Jun 2013 to 2.4 in Dec 2013. The NSA rate of nonfarm hiring fell from 3.9 in Jun 2014 to 2.7 in Dec 2014. Rates of nonfarm hiring NSA were in the range of 2.7 (Dec) to 4.4 (Jun) in 2006. The rate of nonfarm hiring SA stood at 3.5 in Apr 2015 and at 3.9 NSA.

clip_image007

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2015

Source: Bureau of Labor Statistics

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

There is only milder improvement in total private hiring shown in Chart I-8. Hiring private (HP) rose in 2010 with stability and renewed increase in 2011 followed by almost stationary series in 2012. The number of private hiring seasonally adjusted fell from 4056 thousand in Sep 2011 to 3961 in Dec 2011 or by 2.3 percent, decreasing to 4018 in Jan 2012 or decline by 0.9 percent relative to the level in Sep 2011. Private hiring fell to 3947 in Sep 2012 or lower by 2.7 percent relative to Sep 2011, moving to 4073 in Dec 2012 for increase of 1.4 percent relative to 4018 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4601 in Jun 2011 to 2844 in Dec 2011 or by 38.2 percent, reaching 3874 in Jan 2012 or decline of 15.8 percent relative to Jun 2011 and moving to 2935 in Dec 2012 or 36.6 percent lower relative to 4626 in Jun 2012. Hires not seasonally adjusted fell from 4738 in Jun 2013 to 3090 in Dec 2013. The level of private hiring NSA fell from 5110 in Jun 2014 to 3549 in Dec 2014 or 30.5 percent. Companies reduce hiring in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5567 in Jun 2006 to 3568 in Dec 2006 or by 35.9 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Aug 2006, private hiring NSA was 5115, declining to 4182 in Aug 2011 or by 18.2 percent and to 4392 in Aug 2012 or lower by 14.1 percent relative to Aug 2006. Private hiring NSA fell from 5501 in Jul 2006 to 5139 in Jul 2014 or 6.6 percent. Private hiring fell from 3568 in Dec 2006 to 3090 in Dec 2013 or 13.4 percent and to 3549 in Dec 2014 or decline of 0.5 percent. The conclusion is that private hiring in the US is around 3 percent below the hiring before the global recession while the noninstitutional population of the United States has grown from 228.815 million in 2006 to 247.947 million in 2014, by 19.132 million or 8.4 percent. Private hiring of 59.128 million in 2006 was equivalent to 25.8 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 55.048 million in 2014 or 22.2 percent of the civilian noninstitutional population of 247.947 million in 2014. The percentage of hiring in civilian noninstitutional population of 25.8 percent in 2006 would correspond to 63.970 million of hiring in 2014, which would be 8.922 million higher than actual 55.048 million in 2014. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

clip_image008

Chart I-8, US, Total Private Hiring Month SA 2001-2015

Source: Bureau of Labor Statistics

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

Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data did not rise significantly above the peak in 2010. The rate seasonally adjusted fell from 3.7 in Sep 2011 to 3.6 in Dec 2011 and reached 3.6 in Dec 2012 and 3.7 in Dec 2013. The rate not seasonally adjusted (NSA) fell from 3.7 in Sep 2011 to 2.6 in Dec 2011, increasing to 3.8 in Oct 2012 but falling to 2.6 in Dec 2012 and 3.4 in Mar 2013. The NSA rate of private hiring fell from 4.8 in Jul 2006 to 3.4 in Aug 2009 but recovery was insufficient to only 3.9 in Aug 2012, 2.6 in Dec 2012 and 2.7 in Dec 2013. The NSA rate increased to 4.4 in May 2015.

clip_image009

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2015

Source: Bureau of Labor Statistics

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

The JOLTS report of the Bureau of Labor Statistics also provides total nonfarm job openings (TNF JOB), TNF JOB rate and TNF LD (layoffs and discharges) shown in Table I-4 for the month of May from 2001 to 2015. The final column provides annual TNF LD for the years from 2001 to 2014. Nonfarm job openings (TNF JOB) increased from a peak of 4414 in May 2006 to 5430 in May 2015 or by 23.0 percent while the rate increased from 3.1 to 3.7. This was mediocre performance because the civilian noninstitutional population of the US, or those in condition of working, rose from 228.428 million in May 2006 to 250.455 million in May 2015, by 22.027 million or 9.6 percent. Nonfarm layoffs and discharges (TNF LD) rose from 1657 in May 2006 to 1902 in May 2009 or by 14.8 percent. The annual data show layoffs and discharges rising from 20.9 million in 2006 to 26.4 million in 2009 or by 26.3 percent. Business pruned payroll jobs to survive the global recession but there has not been hiring because of the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions.

Table I-4, US, Total Nonfarm Job Openings and Total Nonfarm Layoffs and Discharges, Thousands NSA

 

TNF JOB

TNF JOB
Rate

TNF LD

TNF LD
Annual

May 2001

4485

3.3

1647

24138

May 2002

3555

2.6

1617

22706

May 2003

3215

2.4

1634

23490

May 2004

3658

2.7

1545

22668

May 2005

3813

2.8

1610

22243

May 2006

4414

3.1

1657

20896

May 2007

4253

3.2

1487

21958

May 2008

4002

2.8

1609

24028

May 2009

2411

1.8

1902

26444

May 2010

2922

2.2

1610

21827

May 2011

3050

2.3

1596

20801

May 2012

3722

2.7

1737

20872

May 2013

3849

2.7

1631

19889

May 2014

4639

3.2

1583

20418

May 2015

5430

3.7

1554

 

Notes: TNF JOB: Total Nonfarm Job Openings; LD: Layoffs and Discharges

Source: Bureau of Labor Statistics

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

Chart I-10 shows monthly job openings rising from the trough in 2009 to a high in the beginning of 2010. Job openings then stabilized into 2011 but have surpassed the peak of 3097 seasonally adjusted in Apr 2010 with 3640 seasonally adjusted in Dec 2012, which is higher by 17.5 percent relative to Apr 2010 but lower by 2.7 percent relative to 3741 in Nov 2012 and lower by 5.1 percent than 3837 in Mar 2012. Nonfarm job openings increased from 3640 in Dec 2012 to 3977 in Dec 2013 or by 9.3 percent and to 4877 in 2014 or 22.6 percent relative to 2013. The high of job openings not seasonally adjusted was 3428 in Apr 2010 that was surpassed by 3671 in Jul 2011, increasing to 3942 in Oct 2012 but declining to 3189 in Dec 2012 and increasing to 3507 in Dec 2013. The level of job opening NSA increased to 5430 in May 2015. The level of job openings not seasonally adjusted fell to 3189 in Dec 2012 or by 21.3 percent relative to 3988 in Apr 2012. There is here again the strong seasonality of year-end labor data. Job openings fell from 4215 in Apr 2013 to 3507 in Dec 2013 and from 4816 in Apr 2014 to 4373 in Dec 2014, showing strong seasonal effects. Nonfarm job openings (TNF JOB) increased from a peak of 4523 in May 2007 to 5430 in May 2015 or by 20.1 percent while the rate increased from 3.2 to 3.7. This was mediocre performance because the civilian noninstitutional population of the US, or those in condition of working, rose from 228.428 million in May 2006 to 250.455 million in May 2015, by 22.027 million or 9.6 percent. The main problem in recovery of the US labor market has been the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 23 quarters from IIIQ2009 to IQ2015. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IQ2015 (http://www.bea.gov/newsreleases/national/gdp/2015/pdf/gdp1q15_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IQ2015 would have accumulated to 23.9 percent. GDP in IQ2015 would be $18,574.8 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,287.1 billion than actual $16,287.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 25.0 million unemployed or underemployed equivalent to actual unemployment/underemployment of 15.1 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html). US GDP in IQ2015 is 12.3 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,287.7 billion in IQ2015 or 8.6 percent at the average annual equivalent rate of 1.2 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth at average 3.3 percent per year from May 1919 to May 2015. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 126.2585 in May 2015. The actual index NSA in May 2015 is 101.5858, which is 19.5 percent below trend. Manufacturing output grew at average 2.4 percent between Dec 1986 and Dec 2014. Using trend growth of 2.4 percent per year, the index would increase to 118.3245 in May 2015. The output of manufacturing at 101.5858 in May 2015 is 14.1 percent below trend under this alternative calculation.

clip_image010

Chart I-10, US Job Openings, Thousands NSA, 2001-2015

Source: US Bureau of Labor Statistics

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

The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted increased from 2.2 in Jan 2011 to 2.6 in Dec 2011, 2.6 in Dec 2012, 2.8 in Dec 2013 and 3.4 in Dec 2014. The rate seasonally adjusted stood at 3.6 in May 2015. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 3.0 in Apr 2013, easing to 2.5 in Dec 2013. The rate of job openings NSA fell from 3.3 in Jul 2007 to 1.6 in Nov-Dec 2009, recovering to 3.7 in May 2015.

clip_image011

Chart I-11, US, Rate of Job Openings, NSA, 2001-2015

Source: US Bureau of Labor Statistics

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

Total separations are shown in Chart I-12. Separations are much lower in 2012-15 than before the global recession but hiring has not recovered.

clip_image012

Chart I-12, US, Total Nonfarm Separations, Month Thousands SA, 2001-2015

Source: US Bureau of Labor Statistics

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

Chart I-13 provides annual total separations. Separations fell sharply during the global recession but hiring has not recovered relative to population growth.

clip_image013

Chart I-13, US, Total Separations, Annual, Thousands, 2001-2014

Source: US Bureau of Labor Statistics

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

Table I-5 provides total nonfarm total separations from 2001 to 2014. Separations fell from 61.1 million in 2006 to 47.8 million in 2010 or by 13.3 million and 48.2 million in 2011 or by 12.9 million. Total separations increased from 48.2 million in 2011 to 51.8 million in 2013 or by 3.6 million and to 55.5 million in 2014 or by 7.3 million relative to 2011.

Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2014

Year

Annual Thousands

2001

64472

2002

59003

2003

56970

2004

58238

2005

60494

2006

61117

2007

60838

2008

58227

2009

51127

2010

47752

2011

48227

2012

50047

2013

51783

2014

55524

Source: US Bureau of Labor Statistics

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

Monthly data of layoffs and discharges reach a peak in early 2009, as shown in Chart I-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business. Weak rates of growth of GDP (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html) frustrated employment recovery. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

clip_image014

Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly Thousands SA, 2001-2015

Source: US Bureau of Labor Statistics

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

Layoffs and discharges in Chart I-15 rose sharply to a peak in 2009. There was pronounced drop into 2010 and 2011 with mild increase into 2012 and renewed decline into 2013. There is mild increase into 2014.

clip_image015

Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2014

Source: US Bureau of Labor Statistics

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

Annual layoff and discharges are in Table I-6. Layoffs and discharges increased sharply from 20.896 million in 2006 to 26.444 million in 2009 or 26.6 percent. Layoff and discharges fell to 19.889 million in 2013 or 24.8 percent relative to 2009 and increased to 20.418 million in 2014 or 2.7 relative to 2013.

Table I-6, US, Total Nonfarm Layoffs and Discharges, Thousands, 2001-2014

Year

Annual

Thousands

2001

24138

2002

22706

2003

23490

2004

22668

2005

22243

2006

20896

2007

21958

2008

24028

2009

26444

2010

21827

2011

20801

2012

20872

2013

19889

2014

20418

Source: US Bureau of Labor Statistics

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

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

Thousands and in Percentage of Total Employment Not Seasonally Adjusted

 

HNF

Rate RNF

HP

Rate HP

2001 May

5811

4.4

5437

4.9

2002 May

5305

4.0

4956

4.5

2003 May

5023

3.8

4740

4.4

2004 May

5385

4.1

5095

4.6

2005 May

5720

4.3

5403

4.8

2006 May

5955

4.4

5599

4.9

2007 May

5728

4.1

5335

4.6

2008 May

5088

3.7

4761

4.1

2009 May

4143

3.1

3871

3.6

2010 May

4830

3.7

4071

3.8

2011 May

4647

3.5

4367

4.0

2012 May

4979

3.7

4657

4.1

2013 May

5122

3.7

4820

4.2

2014 May

5435

3.9

5108

4.4

2015 May

5597

3.9

5241

4.4

Source: Bureau of Labor Statistics

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

clip_image006[1]

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2015 Month SA

Source: Bureau of Labor Statistics

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

clip_image007[1]

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2015

Source: Bureau of Labor Statistics

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

clip_image008[1]

Chart I-8, US, Total Private Hiring Month SA 2001-2015

Source: Bureau of Labor Statistics

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

clip_image009[1]

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2015

Source: Bureau of Labor Statistics

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

  IA2 Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table I-7. The most comprehensive measure is U6 that consists of total unemployed plus total employed part time for economic reasons plus all marginally attached workers as percent of the labor force. U6 not seasonally adjusted has risen from 8.2 percent in 2006 to 10.8 percent in Jun 2015.

Table I-7, US, Alternative Measures of Labor Underutilization NSA %

 

U1

U2

U3

U4

U5

U6

2015

           

Jun

2.1

2.5

5.5

5.8

6.6

10.8

May

2.4

2.5

5.3

5.6

6.4

10.4

Apr

2.4

2.5

5.1

5.5

6.4

10.4

Mar

2.6

2.9

5.6

6.0

6.8

11.0

Feb

2.7

3.0

5.8

6.3

7.1

11.4

Jan

2.7

3.1

6.1

6.5

7.4

12.0

2014

           

Dec

2.5

2.8

5.4

5.8

6.7

11.1

Nov

2.7

2.7

5.5

5.9

6.8

11.0

Oct

2.7

2.6

5.5

6.0

6.8

11.1

Sep

2.7

2.7

5.7

6.2

7.1

11.3

Aug

2.8

3.0

6.3

6.7

7.5

12.0

Jul

2.8

3.1

6.5

7.0

7.8

12.6

Jun

2.8

3.0

6.3

6.7

7.5

12.4

May

3.1

3.0

6.1

6.5

7.3

11.7

Apr

3.3

3.2

5.9

6.3

7.2

11.8

Mar

3.7

3.7

6.8

7.2

8.1

12.8

Feb

3.6

3.9

7.0

7.5

8.4

13.1

Jan

3.5

4.0

7.0

7.5

8.6

13.5

2013

           

Dec

3.5

3.5

6.5

7.0

7.9

13.0

Nov

3.7

3.5

6.6

7.1

7.9

12.7

Oct

3.7

3.6

7.0

7.4

8.3

13.2

Sep

3.7

3.5

7.0

7.5

8.4

13.1

Aug

3.7

3.8

7.3

7.9

8.7

13.6

Jul

3.7

3.8

7.7

8.3

9.1

14.3

Jun

3.9

3.8

7.8

8.4

9.3

14.6

May

4.1

3.7

7.3

7.7

8.5

13.4

Apr

4.3

3.9

7.1

7.6

8.5

13.4

Mar

4.3

4.3

7.6

8.1

9.0

13.9

Feb

4.3

4.6

8.1

8.6

9.6

14.9

Jan

4.3

4.9

8.5

9.0

9.9

15.4

2012

           

Dec

4.2

4.3

7.6

8.3

9.2

14.4

Nov

4.2

3.9

7.4

7.9

8.8

13.9

Oct

4.3

3.9

7.5

8.0

9.0

13.9

Sep

4.2

4.0

7.6

8.0

9.0

14.2

Aug

4.3

4.4

8.2

8.7

9.7

14.6

Jul

4.3

4.6

8.6

9.1

10.0

15.2

Jun

4.5

4.4

8.4

8.9

9.9

15.1

May

4.7

4.3

7.9

8.4

9.3

14.3

Apr

4.8

4.3

7.7

8.3

9.1

14.1

Mar

4.9

4.8

8.4

8.9

9.7

14.8

Feb

4.9

5.1

8.7

9.3

10.2

15.6

Jan

4.9

5.4

8.8

9.4

10.5

16.2

2011

           

Dec

4.8

5.0

8.3

8.8

9.8

15.2

Nov

4.9

4.7

8.2

8.9

9.7

15.0

Oct 

5.0

4.8

8.5

9.1

10.0

15.3

Sep

5.2

5.0

8.8

9.4

10.2

15.7

Aug

5.2

5.1

9.1

9.6

10.6

16.1

Jul

5.2

5.2

9.3

10.0

10.9

16.3

Jun

5.1

5.1

9.3

9.9

10.9

16.4

May

5.5

5.1

8.7

9.2

10.0

15.4

Apr

5.5

5.2

8.7

9.2

10.1

15.5

Mar

5.7

5.8

9.2

9.7

10.6

16.2

Feb

5.6

6.0

9.5

10.1

11.1

16.7

Jan

5.6

6.2

9.8

10.4

11.4

17.3

Dec  2010

5.4

5.9

9.1

9.9

10.7

16.6

Annual

           

2014

3.0

3.1

6.2

6.6

7.5

12.0

2013

3.9

3.9

7.4

7.9

8.8

13.8

2012

4.5

4.4

8.1

8.6

9.5

14.7

2011

5.3

5.3

8.9

9.5

10.4

15.9

2010

5.7

6.0

9.6

10.3

11.1

16.7

2009

4.7

5.9

9.3

9.7

10.5

16.2

2008

2.1

3.1

5.8

6.1

6.8

10.5

2007

1.5

2.3

4.6

4.9

5.5

8.3

2006

1.5

2.2

4.6

4.9

5.5

8.2

2005

1.8

2.5

5.1

5.4

6.1

8.9

2004

2.1

2.8

5.5

5.8

6.5

9.6

2003

2.3

3.3

6.0

6.3

7.0

10.1

2002

2.0

3.2

5.8

6.0

6.7

9.6

2001

1.2

2.4

4.7

4.9

5.6

8.1

2000

0.9

1.8

4.0

4.2

4.8

7.0

Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.1 percent in Aug 2011 to 16.3 percent in Sep 2011 and then fell to 14.5 percent in Mar 2012, reaching 10.5 percent in Jun 2015. Unemployment is an incomplete measure of the stress in US job markets. A different calculation in this blog is provided by using the participation rate in the labor force before the global recession. This calculation shows 25.0 million in job stress of unemployment/underemployment in Jun 2015, not seasonally adjusted, corresponding to 15.1 percent of the labor force (http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html).

Table I-8, US, Alternative Measures of Labor Underutilization SA %

 

U1

U2

U3

U4

U5

U6

Jun 2015

2.2

2.6

5.3

5.7

6.4

10.5

May

2.4

2.7

5.5

5.8

6.6

10.8

Apr

2.3

2.6

5.4

5.9

6.7

10.8

Mar

2.4

2.7

5.5

5.9

6.7

10.9

Feb

2.6

2.7

5.5

6.0

6.8

11.0

Jan

2.7

2.7

5.7

6.1

7.0

11.3

Dec 2014

2.6

2.8

5.6

6.0

6.9

11.2

Nov

2.7

2.9

5.8

6.2

7.1

11.4

Oct

2.8

2.8

5.7

6.2

7.1

11.5

Sep

2.8

2.9

5.9

6.3

7.3

11.7

Aug

2.9

3.1

6.1

6.6

7.4

12.0

July

2.9

3.1

6.2

6.6

7.5

12.2

Jun

2.9

3.1

6.1

6.5

7.3

12.0

May

3.1

3.2

6.3

6.7

7.5

12.1

Apr

3.2

3.3

6.2

6.7

7.5

12.3

Mar

3.4

3.5

6.6

7.1

7.9

12.6

Feb

3.5

3.5

6.7

7.1

8.0

12.6

Jan

3.4

3.4

6.6

7.1

8.1

12.7

Dec 2013

3.6

3.5

6.7

7.2

8.1

13.1

Nov

3.7

3.7

7.0

7.4

8.2

13.1

Oct

3.8

4.0

7.2

7.7

8.6

13.7

Sep

3.8

3.8

7.2

7.7

8.6

13.6

Aug

3.9

3.8

7.2

7.7

8.6

13.6

Jul

3.9

3.8

7.3

7.9

8.7

13.8

Jun

4.0

3.9

7.5

8.1

9.0

14.2

May

4.1

3.9

7.5

8.0

8.8

13.8

Apr

4.1

4.1

7.6

8.0

8.9

14.0

Mar

4.1

4.0

7.5

8.0

8.9

13.8

Feb

4.1

4.1

7.7

8.2

9.2

14.3

Jan

4.2

4.3

8.0

8.5

9.4

14.5

Dec 2012

4.3

4.2

7.9

8.5

9.4

14.4

Nov

4.2

4.2

7.7

8.3

9.2

14.4

Oct

4.4

4.2

7.8

8.3

9.2

14.4

Sep

4.4

4.2

7.8

8.3

9.3

14.7

Aug

4.4

4.5

8.0

8.5

9.5

14.6

Jul

4.5

4.6

8.2

8.7

9.6

14.8

Jun

4.6

4.6

8.2

8.7

9.6

14.8

May

4.6

4.5

8.2

8.7

9.6

14.8

Apr

4.6

4.4

8.2

8.7

9.6

14.6

Mar

4.6

4.5

8.2

8.7

9.6

14.5

Feb

4.7

4.6

8.3

8.9

9.8

15.0

Jan

4.8

4.7

8.3

8.9

9.9

15.2

Dec 2011

4.9

4.9

8.5

9.0

10.0

15.2

Nov

5.0

5.0

8.6

9.3

10.1

15.5

Oct

5.1

5.1

8.8

9.4

10.3

15.8

Sep

5.4

5.2

9.0

9.6

10.5

16.3

Aug

5.4

5.2

9.0

9.6

10.5

16.1

Jul

5.3

5.3

9.0

9.6

10.6

15.9

Jun

5.3

5.3

9.1

9.7

10.7

16.1

May

5.3

5.4

9.0

9.5

10.3

15.8

Apr

5.2

5.4

9.1

9.7

10.5

16.1

Mar

5.3

5.4

9.0

9.5

10.4

15.9

Feb

5.3

5.5

9.0

9.6

10.6

16.0

Jan

5.5

5.5

9.2

9.7

10.8

16.2

Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart I-16 provides U6 on a monthly basis from 2001 to 2015. There was a steep climb from 2007 into 2009 and then this measure of unemployment and underemployment stabilized at that high level but declined into 2012. The low of U6 SA was 8.0 percent in Mar 2007 and the peak was 17.1 percent in Apr 2010. The low NSA was 7.6 percent in Oct 2006 and the peak was 18.0 percent in Jan 2010.

clip_image016

Chart I-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed Part-Time for Economic Reasons, Month, SA, 2001-2015

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart I-17 provides the number employed part-time for economic reasons or who cannot find full-time employment. There are sharp declines at the end of 2009, 2010 and 2011 but an increase in 2012 followed by relative stability in 2013-2015.

clip_image017

Chart I-17, US, Working Part-time for Economic Reasons

Thousands, Month SA 2001-2015

Sources: US Bureau of Labor Statistics

http://www.bls.gov/

ICA3 Ten Million Fewer Full-time Jobs. There is strong seasonality in US labor markets around the end of the year.

  • Seasonally adjusted part-time for economic reasons. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.109 million in Sep 2011 to 7.808 million in Mar 2012, seasonally adjusted, or decline of 1.301 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.600 million in Sep 2012 for increase of 603,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.195 million in Oct 2012 or by 405,000 again in one month, further declining to 8.156 million in Nov 2012 for another major one-month decline of 39,000 and 7.926 million in Dec 2012 or fewer 230,000 in just one month. The number employed part-time for economic reasons increased to 8.055 million in Jan 2013 or 129,000 more than in Dec 2012 and to 8.064 million in Feb 2013, declining to 7.947 million in May 2013 but increasing to 8.124 million in Jun 2013. The number employed part-time for economic reasons fell to 7.843 million in Aug 2013 for decline of 244,000 in one month from 8.087 million in Jul 2013. The number employed part-time for economic reasons increased 96,000 from 7.843 million in Aug 2013 to 7.939 million in Sep 2013. The number part-time for economic reasons rose to 7.982 million in Oct 2013, falling by 267,000 to 7.715 million in Nov 2013. The number part-time for economic reasons increased to 7.776 million in Dec 2013, decreasing to 7.274 million in Jan 2014. The number employed part-time for economic reasons fell from 7.274 million in Jan 2014 to 7.204 million in Feb 2014. The number employed part-time for economic reasons increased to 7.449 million in Mar 2014 and 7.460 million in Apr 2014. The number employed part-time for economic reasons fell to 7.268 million in May 2014, increasing to 7.496 million in Jun 2014. The level employed part-time for economic reasons fell to 7.433 million in Jul 2014 and 7.223 million in Aug 2014. The level employed part-time for economic reasons fell to 7.058 million in Sep 2014, 7.012 million in Oct 2014 and 6.851 million in Nov 2014. The level employed part-time for economic reasons fell to 6.790 million in Dec 2014, increasing to 6.810 million in Jan 2015. The level employed part-time for economic reasons fell to 6.635 million in Feb 2015, increasing to 6.705 million in Mar 2015. The level of employed part-time for economic reasons fell to 6.580 million in Apr 2015, increasing to 6.652 million in May 2015. The level employed part-time for economic reasons fell to 6.605 million in Jun 2015. There is an increase of 198,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 159,000 from Aug 2012 to Nov 2012.
  • Seasonally adjusted full-time. The number employed full-time increased from 112.891 million in Oct 2011 to 115.086 million in Mar 2012 or 2.195 million but then fell to 114.245 million in May 2012 or 0.841 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.735 million in Aug 2012 to 115.514 million in Oct 2012 or increase of 0.779 million full-time jobs in two months and further to 115.807 million in Jan 2013 or increase of 1.072 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.751 million in Feb 2013, increasing to 116.244 million in May 2013 and 116.143 million in Jun 2013. Then number of full-time jobs increased to 116.147 million in Jul 2013, 116.453 million in Aug 2013 and 116.869 million in Sep 2013. The number of full-time jobs fell to 116.293 million in Oct 2013 and increased to 116.946 in Nov 2013. The level of full-time jobs fell to 117.240 million in Dec 2013, increasing to 117.650 million in Jan 2014 and 117.859 million in Feb 2014. The level of employment full-time increased to 118.062 million in Mar 2014 and 118.458 million in Apr 2014. The level of full-time employment reached 118.790 million in May 2014, decreasing to 118.252 million in Jun 2014. The level of full-time jobs increased to 118.448 million in Jul 2014 and 118.758 million in Aug 2014. The level of full-time jobs increased to 119.310 million in Sep 2014, 119.681 million in Oct 2014 and 119.507 million in Nov 2014. The level of full-time jobs increased to 119.934 million in Dec 2014 and 120.711 million in Jan 2015. The level of full-time jobs increased to 120.834 million in Feb 2015 and 121.024 million in Mar 2015. The level of full-time jobs decreased to 120.772 million in Apr 2015, increasing to 121.402 million in May 2015 and decreasing to 121.053 million in Jun 2015. Adjustments of benchmark and seasonality-factors at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2015/02/job-creation-and-monetary-policy-twenty.html http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html).
  • Not seasonally adjusted part-time for economic reasons. The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.051 million and to 7.694 million in Apr 2012 or 1.224 million fewer relative to Jan 2012. In Aug 2012, the number employed part-time for economic reasons reached 7.842 million NSA or 148,000 more than in Apr 2012. The number employed part-time for economic reasons increased from 7.842 million in Aug 2012 to 8.110 million in Sep 2012 or by 3.4 percent. The number part-time for economic reasons fell from 8.110 million in Sep 2012 to 7.870 million in Oct 2012 or by 240.000 in one month. The number employed part-time for economic reasons NSA increased to 8.628 million in Jan 2013 or 758,000 more than in Oct 2012. The number employed part-time for economic reasons fell to 8.298 million in Feb 2013, which is lower by 330,000 relative to 8.628 million in Jan 2013 but higher by 428,000 relative to 7.870 million in Oct 2012. The number employed part time for economic reasons fell to 7.734 million in Mar 2013 or 564,000 fewer than in Feb 2013 and fell to 7.709 million in Apr 2013. The number employed part-time for economic reasons reached 7.618 million in May 2013. The number employed part-time for economic reasons jumped from 7.618 million in May 2013 to 8.440 million in Jun 2013 or 822,000 in one month. The number employed part-time for economic reasons fell to 8.324 million in Jul 2013 and 7.690 million in Aug 2013. The number employed part-time for economic reasons NSA fell to 7.522 million in Sep 2013, increasing to 7.700 million in Oct 2013. The number employed part-time for economic reasons fell to 7.563 million in Nov 2013 and increased to 7.990 million in Dec 2013. The number employed part-time for economic reasons fell to 7.771 million in Jan 2014 and 7.397 million in Feb 2014. The level of part-time for economic reasons increased to 7.455 million in Mar 2014 and fell to 7.243 million in Apr 2014. The number of part-time for economic reasons fell to 6.960 million in May 2014, increasing to 7.805 million in Jun 2014. The level of part-time for economic reasons fell to 7.665 million in Jul 2014 and 7.083 million in Aug 2014. The level of part-time for economic reasons fell to 6.711 million in Sep 2014 and increased to 6.787 million in Oct 2014. The level of part-time for economic reasons reached 6.713 million in Nov 2014 and 6.970 million in Dec 2014, increasing to 7.269 million in Jan 2015. The level of part-time for economic reasons fell to 6.772 million in Feb 2015 and 6.672 million in Mar 2015, falling to 6.356 million in Apr 2015. The level of part-time for economic reasons increased to 6.363 million in May 2015 and to 6.776 million in Jun 2015.
  • Not seasonally adjusted full-time. The number employed full time without seasonal adjustment fell from 113.138 million in Nov 2011 to 113.050 million in Dec 2011 or by 88,000 and fell further to 111.879 in Jan 2012 for cumulative decrease of 1.259 million. The number employed full-time not seasonally adjusted fell from 113.138 million in Nov 2011 to 112.587 million in Feb 2012 or by 551.000 but increased to 116.214 million in Aug 2012 or 3.076 million more full-time jobs than in Nov 2011. The number employed full-time not seasonally adjusted decreased from 116.214 million in Aug 2012 to 115.678 million in Sep 2012 for loss of 536,000 full-time jobs and rose to 116.045 million in Oct 2012 or by 367,000 full-time jobs in one month relative to Sep 2012. The number employed full-time NSA fell from 116.045 million in Oct 2012 to 115.515 million in Nov 2012 or decline of 530.000 in one month. The number employed full-time fell from 115.515 in Nov 2012 to 115.079 million in Dec 2012 or decline by 436,000 in one month. The number employed full time fell from 115.079 million in Dec 2012 to 113.868 million in Jan 2013 or decline of 1.211 million in one month. The number of full time jobs increased to 114.191 in Feb 2012 or by 323,000 in one month and increased to 114.796 million in Mar 2013 for cumulative increase from Jan by 928,000 full-time jobs but decrease of 283,000 from Dec 2012. The number employed full time reached 117.400 million in Jun 2013 and increased to 117.688 in Jul 2013 or by 288,000. The number employed full-time reached 117.868 million in Aug 2013 for increase of 180,000 in one month relative to Jul 2013. The number employed full-time fell to 117.308 million in Sep 2013 or by 560,000. The number employed full-time fell to 116.798 million in Oct 2013 or decline of 510.000 in one month. The number employed full-time rose to 116.875 million in Nov 2013, falling to 116.661 million in Dec 2013. The number employed full-time fell to 115.744 million in Jan 2014 but increased to 116.323 million in Feb 2014. The level of full-time jobs increased to 116.985 in Mar 2014 and 118.073 million in Apr 2014. The number of full-time jobs increased to 119.179 million in May 2014, increasing to 119.472 million in Jun 2014. The level of full-time jobs increased to 119.900 million in Jul 2014. Comparisons over long periods require use of NSA data. The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in May 2015 is 122.268 million, which is lower by 0.951 million relative to the peak of 123.219 million in Jul 2007.
  • Loss of full-time jobs. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 250.663 million in Jun 2015 or by 18.705 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 0.951 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 133.102 million full-time jobs with population of 250.266 million in Apr 2015 (0.531 x 250.663) or 10.834 million fewer full-time jobs relative to actual 122.268 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 18 million. Mediocre GDP growth is the main culprit of the fractured US labor market. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 23 quarters from IIIQ2009 to IQ2015. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IQ2015 (http://www.bea.gov/newsreleases/national/gdp/2015/pdf/gdp1q15_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IQ2015 would have accumulated to 23.9 percent. GDP in IQ2015 would be $18,574.8 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,287.1 billion than actual $16,287.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 25.0 million unemployed or underemployed equivalent to actual unemployment/underemployment of 15.1 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html). US GDP in IQ2015 is 12.3 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,287.7 billion in IQ2015 or 8.6 percent at the average annual equivalent rate of 1.2 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth at average 3.3 percent per year from May 1919 to May 2015. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 126.2585 in May 2015. The actual index NSA in May 2015 is 101.5858, which is 19.5 percent below trend. Manufacturing output grew at average 2.4 percent between Dec 1986 and Dec 2014. Using trend growth of 2.4 percent per year, the index would increase to 118.3245 in May 2015. The output of manufacturing at 101.5858 in May 2015 is 14.1 percent below trend under this alternative calculation.

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

 

Part-time Thousands

Full-time Millions

Seasonally Adjusted

   

Jun 2015

6,605

121.053

May 2015

6,652

121.402

Apr 2015

6,580

120.772

Mar 2015

6,705

121.024

Feb 2015

6,635

120.834

Jan 2015

6,810

120.711

Dec 2014

6,790

119.934

Nov 2014

6,851

119.507

Oct 2014

7,012

119.681

Sep 2014

7,058

119.310

Aug 2014

7,223

118.758

Jul 2014

7,433

118.448

Jun 2014

7,496

118.252

May 2014

7,268

118.790

Apr 2014

7,460

118.458

Mar 2014

7,449

118.062

Feb 2014

7,204

117.859

Jan 2014

7,274

117.650

Dec 2013

7,776

117.240

Nov 2013

7,715

116.946

Oct 2013

7,982

116.293

Sep 2013

7,939

116.869

Aug 2013

7,843

116.453

Jul 2013

8,087

116.147

Jun 2013

8,124

116.143

May 2013

7,947

116.244

Apr 2013

7,933

116.018

Mar 2013

7,699

115.877

Feb 2013

8,064

115.751

Jan 2013

8,055

115.807

Dec 2012

7,926

115.724

Nov 2012

8,156

115.592

Oct 2012

8,195

115.514

Sep 2012

8,600

115.227

Aug 2012

7,997

114.735

Jul 2012

8,087

114.571

Jun 2012

8,098

114.764

May 2012

8,163

114.245

Apr 2012

7,915

114.365

Mar 2012

7,808

115.086

Feb 2012

8,193

114.186

Jan 2012

8,291

113.789

Dec 2011

8,174

113.740

Nov 2011

8,450

113.177

Oct 2011

8,637

112.891

Sep 2011

9,109

112.527

Aug 2011

8,781

112.715

Jul 2011

8,277

112.191

Not Seasonally Adjusted

   

Jun 2015

6,776

122.268

May 2015

6,363

121.863

Apr 2015

6,356

120.402

Mar 2015

6,672

119.981

Feb 2015

6,772

119.313

Jan 2015

7,269

118.840

Dec 2014

6,970

119.394

Nov 2014

6,713

119.441

Oct 2014

6,787

120.176

Sep 2014

6,711

119.791

Aug 2014

7,083

120.110

Jul 2014

7,665

119.900

Jun 2014

7,805

119.472

May 2014

6,960

119.179

Apr 2014

7,243

118.073

Mar 2014

7,455

116.985

Feb 2014

7,397

116.323

Jan 2014

7,771

115.744

Dec 2013

7,990

116.661

Nov 2013

7,563

116.875

Oct 2013

7,700

116.798

Sep 2013

7,522

117.308

Aug 2013

7,690

117.868

Jul 2013

8,324

117.688

Jun 2013

8,440

117.400

May 2013

7,618

116.643

Apr 2013

7,709

115.674

Mar 2013

7,734

114.796

Feb 2013

8,298

114.191

Jan 2013

8,628

113.868

Dec 2012

8,166

115.079

Nov 2012

7,994

115.515

Oct 2012

7,870

116.045

Sep 2012

8,110

115.678

Aug 2012

7,842

116.214

Jul 2012

8,316

116.131

Jun 2012

8,394

116.024

May 2012

7,837

114.634

Apr 2012

7,694

113.999

Mar 2012

7,867

113.916

Feb 2012

8,455

112.587

Jan 2012

8,918

111.879

Dec 2011

8,428

113.050

Nov 2011

8,271

113.138

Oct 2011

8,258

113.456

Sep 2011

8,541

112.980

Aug 2011

8,604

114.286

Jul 2011

8,514

113.759

Jun 2011

8,738

113.255

May 2011

8,270

112.618

Apr 2011

8,425

111.844

Mar 2011

8,737

111.186

Feb 2011

8,749

110.731

Jan 2011

9,187

110.373

Dec 2010

9,205

111.207

Nov 2010

8,670

111.348

Oct 2010

8,408

112.342

Sep 2010

8,628

112.385

Aug 2010

8,628

113.508

Jul 2010

8,737

113.974

Jun 2010

8,867

113.856

May 2010

8,513

112.809

Apr 2010

8,921

111.391

Mar 2010

9,343

109.877

Feb 2010

9,282

109.100

Jan 2010

9,290

108.777 (low)

Dec 2009

9,354 (high)

109.875

Nov 2009

8,894

111.274

Oct 2009

8,474

111.599

Sep 2009

8,255

111.991

Aug 2009

8,835

113.863

Jul 2009

9,103

114.184

Jun 2009

9,301

114.014

May 2009

8,785

113.083

Apr 2009

8,648

112.746

Mar 2009

9,305

112.215

Feb 2009

9,170

112.947

Jan 2009

8,829

113.815

Dec 2008

8,250

116.422

Nov 2008

7,135

118.432

Oct 2008

6,267

120.020

Sep 2008

5,701

120.213

Aug 2008

5,736

121.556

Jul 2008

6,054

122.378

Jun 2008

5,697

121.845

May 2008

5,096

120.809

Apr 2008

5,071

120.027

Mar 2008

5,038

119.875

Feb 2008

5,114

119.452

Jan 2008

5,340

119.332

Dec 2007

4,750

121.042

Nov 2007

4,374

121.846

Oct 2007

4,028

122.006

Sep 2007

4,137

121.728

Aug 2007

4,494

122.870

Jul 2007

4,516

123.219 (high)

Jun 2007

4,469

122.150

May 2007

4,315

120.846

Apr 2007

4,205

119.609

Mar 2007

4,384

119.640

Feb 2007

4,417

119.041

Jan 2007

4,726

119.094

Dec 2006

4,281

120.371

Nov 2006

4,054

120.507

Oct 2006

4,010

121.199

Sep 2006

3,735 (low)

120.780

Aug 2006

4,104

121.979

Jul 2006

4,450

121.951

Jun 2006

4,456

121.070

May 2006

3,968

118.925

Apr 2006

3,787

118.559

Mar 2006

4,097

117.693

Feb 2006

4,403

116.823

Jan 2006

4,597

116.395

Source: US Bureau of Labor Statistics

http://www.bls.gov/

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

clip_image018

Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2015

Sources: US Bureau of Labor Statistics

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

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

clip_image019

Chart I-19, US, Marginally Attached to the Labor Force, NSA Month, Thousands, 2001-2015

Sources: US Bureau of Labor Statistics

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

The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in May 2015 is 122.268 million, which is lower by 0.951 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 250.663 million in Jun 2015 or by 18.705 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 0.951 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 133.102 million full-time jobs with population of 250.266 million in Apr 2015 (0.531 x 250.663) or 10.834 million fewer full-time jobs relative to actual 122.268 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 18 million. Mediocre GDP growth is the main culprit of the fractured US labor market.

Chart I-20 provides unadjusted full-time jobs in the US from 2001 to 2015 with sharp drop and incomplete recovery. There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

“Not until the problem of full employment of our productive resources from the long-run, secular standpoint was upon us, were we compelled to give serious consideration to those factors and forces in our economy which tend to make business recoveries weak and anaemic (sic) and which tend to prolong and deepen the course of depressions. This is the essence of secular stagnation-sick recoveries which die in their infancy and depressions which feed on them-selves and leave a hard and seemingly immovable core of unemployment. Now the rate of population growth must necessarily play an important role in determining the character of the output; in other words, the com-position of the flow of final goods. Thus a rapidly growing population will demand a much larger per capita volume of new residential building construction than will a stationary population. A stationary population with its larger proportion of old people may perhaps demand more personal services; and the composition of consumer demand will have an important influence on the quantity of capital required. The demand for housing calls for large capital outlays, while the demand for personal services can be met without making large investment expenditures. It is therefore not unlikely that a shift from a rapidly growing population to a stationary or declining one may so alter the composition of the final flow of consumption goods that the ratio of capital to output as a whole will tend to decline.”

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). This is merely another case of theory without reality with dubious policy proposals.

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

clip_image020

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2015

Sources: US Bureau of Labor Statistics

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

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2015. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

clip_image021

Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2015

Sources: US Bureau of Labor Statistics

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

Chart I-20B provides number of full-time jobs in the US from 1968 to 2015. There were multiple recessions followed by expansions without contraction of full-time jobs and without recovery as during the period after 2008. The problem is specific of the current cycle and not secular.

clip_image022

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2015

Sources: US Bureau of Labor Statistics

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

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2015. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

clip_image023

Chart I-20C, US, Noninstitutional Civilian Population, Thousands, 1968-2015

Sources: US Bureau of Labor Statistics

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

IA4 Theory and Reality of Secular Stagnation: Youth and Middle-Age Unemployment. Three tables support the argument that the proper comparison of the business cycle is between the recessions of the 1980s and the global recession after IVQ2007 and not as argued erroneously with the Great Depression of the 1930s. Table I-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 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Data are available for the 1930s only on a yearly basis. US GDP fell 4.7 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1981 to IVQ1982 and 4.2 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987 and 4.2 percent in 1988. In contrast, GDP grew 2.5 percent in 2010, 1.6 percent in 2011, 2.3 percent in 2012, 2.2 percent in 2013 and 2.4 percent in 2014. Actual annual equivalent GDP growth in the four quarters of 2012, and nine quarters from IQ2013 to IQ2015 is 2.2 percent and 2.9 percent in the four quarters ending in IQ2015. GDP grew at 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987 and 4.2 percent in 1988. The forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 1.8 to 2.0 percent in 2015 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20150617.pdf) with less reliable forecast of 2.4 to 2.7 percent in 2016 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20150617.pdf). Growth of GDP in the expansion from IIIQ2009 to IQ2015 has been at average 2.2 percent in annual equivalent.

Table I-5, US, Percentage Change of GDP in the 1930s, 1980s and 2000s, ∆%

Year

GDP ∆%

Year

GDP ∆%

Year

GDP ∆%

1930

-8.5

1980

-0.2

2000

4.1

1931

-6.4

1981

2.6

2001

1.0

1932

-12.9

1982

-1.9

2002

1.8

1933

-1.3

1983

4.6

2003

2.8

1934

10.8

1984

7.3

2004

3.8

1935

8.9

1985

4.2

2005

3.3

1936

12.9

1986

3.5

2006

2.7

1937

5.1

1987

3.5

2007

1.8

1938

-3.3

1988

4.2

2008

-0.3

1930

8.0

1989

3.7

2009

-2.8

1940

8.8

1990

1.9

2010

2.5

1941

17.7

1991

-0.1

2011

1.6

1942

18.9

1992

3.6

2012

2.3

1943

17.0

1993

2.7

2013

2.2

1944

8.0

1994

4.0

2014

2.4

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 4.7 percent, which is almost equal to the decline of 4.2 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

Table I-6, US, Number of Quarters, GDP Cumulative Percentage Contraction and Average Percentage Annual Equivalent Rate in Cyclical Contractions   

 

Number of Quarters

Cumulative Percentage Contraction

Average Percentage Rate

IIQ1953 to IIQ1954

3

-2.4

-0.8

IIIQ1957 to IIQ1958

3

-3.0

-1.0

IVQ1973 to IQ1975

5

-3.1

-0.6

IQ1980 to IIIQ1980

2

-2.2

-1.1

IIIQ1981 to IVQ1982

4

-2.5

-0.64

IVQ2007 to IIQ27009

6

-4.2

-0.72

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

Table I-7 shows the mediocre average annual equivalent growth rate of 2.2 percent of the US economy in the twenty-three quarters of the current cyclical expansion from IIIQ2009 to IQ2015. In sharp contrast, the average growth rate of GDP was:

  • 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986
  • 5.4 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986
  • 5.2 percent in the first sixteen quarters of expansion from IQ1983 to IVQ1986
  • 5.0 percent in the first seventeen quarters of expansion from IQ1983 to IQ1987
  • 5.0 percent in the first eighteen quarters of expansion from IQ1983 to IIQ1987
  • 4.9 percent in the first nineteen quarters of expansion from IQ1983 to IIIQ1987
  • 5.0 percent in the first twenty quarters of expansion from IQ1983 to IVQ1987
  • 4.9 percent in the first twenty-first quarters of expansion from IQ1983 to IQ1988
  • 4.9 percent in the first twenty-two quarters of expansion from IQ1983 to IIQ1988
  • 4.8 percent in the first twenty-three quarters of expansion from IQ1983 to IIIQ1988

The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill with annual growth of 2.5 percent in 2010 decelerating to 1.6 percent annual growth in 2011, 2.3 percent in 2012, 2.2 percent in 2013 and 2.4 percent in 2014 (http://www.bea.gov/iTable/index_nipa.cfm) The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988 and at 7.8 percent from IQ1983 to IVQ1983. GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the four quarters of 2012, the four quarters of 2013, the four quarters of 2014 and IQ2015 accumulated to 7.2 percent. This growth is equivalent to 2.2 percent per year, obtained by dividing GDP in IQ2015 of $16,287.7 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/13: {[($16,287.7/$15,190.3)4/13 -1]100 = 2.2 percent.

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

 

Number
of
Quarters

Cumulative Growth

∆%

Average Annual Equivalent Growth Rate

IIIQ 1954 to IQ1957

11

12.8

4.5

First Four Quarters IIIQ1954 to IIQ1955

4

7.8

 

IIQ1958 to IIQ1959

5

10.0

7.9

First Four Quarters

IIIQ1958 to IIQ1959

4

9.2

 

IIQ1975 to IVQ1976

8

8.3

4.1

First Four Quarters IIIQ1975 to IIQ1976

4

6.1

 

IQ1983-IQ1986

IQ1983-IIIQ1986

IQ1983-IVQ1986

IQ1983-IQ1987

IQ1983-IIQ1987

IQ1983 to IIIQ1987

IQ1983 to IVQ1987

IQ1983 to IQ1988

IQ1983 to IIQ1988

IQ1983 to IIIQ1988

13

15

16

17

18

19

20

21

22

23

19.9

21.6

22.3

23.1

24.5

25.6

27.7

28.4

30.1

30.9

5.7

5.4

5.2

5.0

5.0

4.9

5.0

4.9

4.9

4.8

First Four Quarters IQ1983 to IVQ1983

4

7.8

 

Average First Four Quarters in Four Expansions*

 

7.7

 

IIIQ2009 to IVQ2014

23

13.5

2.2

First Four Quarters IIIQ2009 to IIQ2010

 

2.7

 

*First Four Quarters: 7.8% IIIQ1954-IIQ1955; 9.2% IIIQ1958-IIQ1959; 6.1% IIIQ1975-IQ1976; 7.8% IQ1983-IVQ1983

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

Table EMP provides the comparison between the labor market in the current whole cycle from 2007 to 2014 and the whole cycle from 1979 to 1988. In the entire cycle from 2007 to 2014, the number employed increased 0.258 million, full-time employed fell 2.373 million, part-time for economic reasons increased 2.812 million and population increased 16.080 million. The number employed increased 0.2 percent, full-time employed fell 2.0 percent, part-time for economic reasons increased 63.9 percent and population increased 6.9 percent. There is sharp contrast with the contractions of the 1980s and with most economic history of the United States. In the whole cycle from 1979 to 1988, the number employed increased 16.144 million, full-time employed increased 12.560 million, part-time for economic reasons 1.629 million and population 19.750 million. In the entire cycle from 1979 to 1988, the number employed increased 16.3 percent, full-time employed 15.2 percent, part-time for economic reasons 45.5 percent and population 12.0 percent. The difference between the 1980s and the current cycle after 2007 is in the high rate of growth after the contraction that maintained trend growth around 3.0 percent for the entire cycle and per capital growth at 2.0 percent. The evident fact is that current weakness in labor markets originates in cyclical slow growth and not in imaginary secular stagnation.

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

 

Employed

Full-Time Employed

Part Time Economic Reasons

Noninstitutional Civilian Population

2000s

       

2000

136.891

113.846

3.227

212.577

2001

136.933

113.573

3.715

215.092

2002

136.485

112.700

4.213

217.570

2003

137.736

113.324

4.701

221.168

2004

139.252

114.518

4.567

223.357

2005

141.730

117.016

4.350

226.082

2006

144.427

119.688

4.162

228.815

2007

146.047

121.091

4.401

231.867

2008

145.362

120.030

5.875

233.788

2009

139.877

112.634

8.913

235.801

2010

139.064

111.714

8.874

237.830

2011

139.869

112.556

8.560

239.618

2012

142.469

114.809

8.122

243.284

2013

143.929

116.314

7.935

245.679

2014

146.305

118.718

7.213

247.947

∆2007-2014

0.258

-2,373

2.812

16.080

∆% 2007-2013

0.2

-2.0

63.9

6.9

1980s

       

1979

98.824

82.654

3.577

164.863

1980

99.303

82.562

4.321

167.745

1981

100.397

83.243

4.768

170.130

1982

99.526

81.421

6.170

172.271

1983

100.834

82.322

6.266

174.215

1984

105.005

86.544

5.744

176.383

1985

107.150

88.534

5.590

178.206

1986

109.597

90.529

5.588

180.587

1987

112.440

92.957

5.401

182.753

1988

114.968

95.214

5.206

184.613

1989

117.342

97.369

4.894

186.393

∆1979-1988

16.144

12.560

1.629

19.750

∆% 1979-88

16.3

15.2

45.5

12.0

Source: Bureau of Labor Statistics

http://www.bls.gov/

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. There are accentuated cyclic factors for both the entire population and the young population of ages 16 to 24 years. Table Summary Total provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment level (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would spread over long periods instead of immediately. All indicators of the labor market weakened sharply during the contraction and did not recover. Population continued to grow but all other variables collapsed and did not recover. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-16). Hansen (1938, 1939) finds secular stagnation in lower growth of an aging population. In the current US economy, Table Summary shows that population is dynamic while the labor market is fractured. There is key explanation in the behavior of the civilian labor force participation rate (CLFP) and the employment population ratio (EPOP) that collapsed during the global recession with inadequate recovery. Abandoning job searches are difficult to capture in labor statistics but likely explain the decline in the participation of the population in the labor force. Allowing for abandoning job searches, the total number of people unemployed or underemployed is 25.0 million or 15.1 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html).

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

 

ICP

FTE

EMP

CLF

CLFP

EPOP

UNE

2006

228.8

119.7

144.4

151.4

66.2

63.1

7.0

2009

235.8

112.6

139.9

154.1

65.4

59.3

14.3

2012

243.3

114.8

142.5

155.0

63.7

58.6

12.5

2013

245.7

116.3

143.9

155.4

63.2

58.6

11.5

2014

247.9

118.7

146.3

155.9

62.9

59.0

9.6

12/07

233.2

121.0

146.3

153.7

65.9

62.8

7.4

9/09

236.3

112.0

139.1

153.6

65.0

58.9

14.5

6/15

250.7

122.3

149.6

158.2

63.1

59.7

8.6

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

Source: Bureau of Labor Statistics

http://www.bls.gov/

http://www.bls.gov/

The same situation is present in the labor market for young people in ages 16 to 24 years with data in Table Summary Youth. The youth noninstitutional civilian population (ICP) continued to increase during and after the global recession. There is the same disastrous labor market with decline for young people in employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP) and employment population ratio (EPOP). There are only increases for unemployment of young people (UNE) and youth unemployment rate (UNER). If aging were a factor of secular stagnation, growth of population of young people would attract a premium in remuneration in labor markets. The sad fact is that young people are also facing tough labor markets. The application of the theory of secular stagnation to the US economy and labor markets is void of reality in the form of key facts, which are best explained by accentuated cyclic factors analyzed by Lazear and Spletzer (2012JHJul22).

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

 

ICP

EMP

CLF

CLFP

EPOP

UNE

UNER

2006

36.9

20.0

22.4

60.6

54.2

2.4

10.5

2009

37.6

17.6

21.4

56.9

46.9

3.8

17.6

2012

38.8

17.8

21.3

54.9

46.0

3.5

16.2

2013

38.8

18.1

21.4

55.0

46.5

3.3

15.5

2014

38.7

18.4

21.3

55.0

47.6

2.9

13.4

12/07

37.5

19.4

21.7

57.8

51.6

2.3

10.7

9/09

37.6

17.0

20.7

55.2

45.1

3.8

18.2

6/15

38.6

19.8

22.9

59.4

51.3

3.1

13.7

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

Source: Bureau of Labor Statistics

http://www.bls.gov/

The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs and to 17.834 million in 2012 or 2.207 million fewer jobs. Youth employment fell from 20.041 million in 2006 to 18.057 million in 2013 or 1.984 million fewer jobs. Youth employment fell from 20.041 million in 2006 to 18.442 million in 2014 or 1.599 million. The level of youth jobs fell from 20.129 million in Dec 2006 to 18.347 million in Dec 2014 for 1.782 million fewer youth jobs. The level of youth jobs fell from 21.268 million in Jun 2006 to 19.789 million in Jun 2015 or 1.479 million fewer jobs. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.167 million in Aug 2006 to 18.972 million in Aug 2014 for 2.195 million fewer jobs. Youth employment fell from 21.914 million in Jul 2006 to 20.085 million in Jul 2014 for 1.829 million fewer youth jobs. The number of youth jobs fell from 21.268 million in Jun 2006 million to 19.421 million in Jun 2014 or 1.847 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 21.167 million in Aug 2006 to 18.636 million in Aug 2013 or by 2.531 million. The number of youth jobs fell from 19.604 million in Sep 2006 to 18.043 million in Sep 2013 or 1.561 million fewer youth jobs. The number of youth jobs fell from 20.129 million in Dec 2006 to 18.106 million in Dec 2013 or 2.023 million fewer jobs. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The youth civilian noninstitutional population increased 1.464 million from 37.302 in Feb 2007 to 38.766 million in Feb 2014 while the number of youth jobs decreased 2.058 million. The civilian noninstitutional population increased 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 while jobs for ages 16 to 24 years decreased 1.599 million from 19.538 million in Mar 2007 to 17.939 million in Mar 2014. The civilian noninstitutional population ages 16 to 24 years increased 1.410 million from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 while the number of youth jobs fell 1.347 million. The civilian noninstitutional population increased 1.370 million from 37.379 million in May 2007 to 38.749 million in May 2014 while the number of youth jobs decreased 1.128 million. The civilian noninstitutional population increased 1.330 million from 37.410 million in Jun 2007 to 38.740 million in Jun 2014 while the number of youth jobs fell 1.847 million from 21.268 million in Jun 2006 to 19.421 million in Jun 2014. The youth civilian noninstitutional population increased by 1.292 million from 37.443 million in Jul 2007 to 38.735 million in Jul 2014 while the number of youth jobs fell 1.632 million. The youth civilian noninstitutional population increased from 37.445 million in Aug 2007 to 38.706 million in Aug 2014 or 1.251 million while the number of youth jobs fell 1.441 million. The youth civilian noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014 while the number of youth jobs fell 1.500 million. The youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million while the number of youth jobs fell 1.072 million. The youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million while the number of youth jobs fell 1.327 million. The civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million while the number of youth jobs fell 1.782 million. The civilian noninstitutional population increased 1.971 million from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 while the number of youth jobs fell 1.091 million. The civilian noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015 while the number of youth jobs fell 0.960 million. The civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015 while the number of youth jobs fell 1.215 million. The youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015 while the number of youth jobs fell 1.165 million. The youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015 while the number of youth jobs fell 1.060 million. The youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015 while the number of youth jobs fell 1.479 million. The hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

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

Year

Jan

Feb

Mar

Apr

May

Jun

Oct

Dec

2001

19678

19745

19800

19778

19648

21212

19694

19547

2002

18653

19074

19091

19108

19484

20828

19542

19394

2003

18811

18880

18709

18873

19032

20432

19139

19136

2004

18852

18841

18752

19184

19237

20587

19609

19619

2005

18858

18670

18989

19071

19356

20949

19794

19733

2006

19003

19182

19291

19406

19769

21268

19853

20129

2007

19407

19415

19538

19368

19457

21098

19564

19361

2008

18724

18546

18745

19161

19254

20466

18757

18378

2009

17467

17606

17564

17739

17588

18726

16671

16615

2010

16166

16412

16587

16764

17039

17920

16867

16727

2011

16512

16638

16898

16970

17045

18180

17532

17234

2012

16944

17150

17301

17387

17681

18907

17842

17604

2013

17183

17257

17271

17593

17704

19125

17976

18106

2014

17372

17357

17939

18021

18329

19421

18781

18347

2015

17912

18222

18076

18241

18709

19789

   

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

Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2015. Employment level is sharply lower in May 2015 relative to the peak in 2007. The following Chart I-21A relates youth employment and youth civilian noninstitutional population.

clip_image024

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2015

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

Chart I-21A provides the US civilian noninstitutional population ages 16 to 24 years not seasonally adjusted from 2001 to 2015. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The youth civilian noninstitutional population increased 1.464 million from 37.302 in Feb 2007 to 38.766 million in Feb 2014 while the number of youth jobs decreased 2.058 million. The civilian noninstitutional population increased 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 while jobs for ages 16 to 24 years decreased 1.599 million from 19.538 million in Mar 2007 to 17.939 million in Mar 2014. The civilian noninstitutional population ages 16 to 24 years increased 1.410 million from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 while the number of youth jobs fell 1.347 million. The civilian noninstitutional population increased 1.370 million from 37.379 million in May 2007 to 38.749 million in May 2014 while the number of youth jobs decreased 1.128 million. The civilian noninstitutional population increased 1.330 million from 37.410 million in Jun 2007 to 38.740 million in Jun 2014 while the number of youth jobs fell 1.847 million from 21.268 million in Jun 2006 to 19.421 million in Jun 2014. The youth civilian noninstitutional population increased by 1.292 million from 37.443 million in Jul 2007 to 38.735 million in Jul 2014 while the number of youth jobs fell 1.632 million. The youth civilian noninstitutional population increased from 37.445 million in Aug 2007 to 38.706 million in Aug 2014 or 1.251 million while the number of youth jobs fell 1.441 million. The youth civilian noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014 while the number of youth jobs fell 1.500 million. The youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million while the number of youth jobs fell 1.072 million. The youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million while the number of youth jobs fell 1.327 million. The civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million while the number of youth jobs fell 1.782 million. The civilian noninstitutional population increased 1.971 million from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 while the number of youth jobs fell 1.091 million. The civilian noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015 while the number of youth jobs fell 0.960 million. The civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015 while the number of youth jobs fell 1.215 million. The youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015 while the number of youth jobs fell 1.165 million. The youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015 while the number of youth jobs fell 1.060 million. The youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015 while the number of youth jobs fell 1.479 million. The hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

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Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2015

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

Chart I-21B provides the civilian labor force of the US ages 16 to 24 years NSA from 2001 to 2015. The US civilian labor force ages 16 to 24 years fell from 24.339 million in Jul 2007 to 23.506 million in Jul 2013, by 0.833 million or decline of 3.4 percent, while the civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013, by 1.418 million or 3.8 percent. The US civilian labor force ages 16 to 24 fell from 22.801 million in Aug 2007 to 22.089 million in Aug 2013, by 0.712 million or 3.1 percent, while the noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013, by 1.386 million or 3.7 percent. The US civilian labor force ages 16 to 24 years fell from 21.917 million in Sep 2007 to 21.183 million in Sep 2013, by 0.734 million or 3.3 percent while the civilian noninstitutional youth population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 by 1.355 million or 3.6 percent. The US civilian labor force fell from 21.821 million in Oct 2007 to 21.003 million in Oct 2013, by 0.818 million or 3.7 percent while the noninstitutional youth population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013, by 1.324 million or 3.5 percent. The US youth civilian labor force fell from 21.909 million in Nov 2007 to 20.825 million in Nov 2013, by 1.084 million or 4.9 percent while the civilian noninstitutional youth population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million. The US youth civilian labor force fell from 21.684 million in Dec 2007 to 20.642 million in Dec 2013, by 1.042 million or 4.8 percent, while the civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013, by 1.272 million or 3.4 percent. The youth civilian labor force of the US fell from 21.770 million in Jan 2007 to 20.423 million in Jan 2014, by 1.347 million or 6.2 percent while the youth civilian noninstitutional population increased 37.282 million in Jan 2007 to 38.770 million in Jan 2014, by 1.488 million or 4.0 percent. The youth civilian labor force of the US fell 1.255 million from 21.645 million in Feb 2007 to 20.390 million in Feb 2014 while the youth civilian noninstitutional population increased 1.464 million from 37.302 million in Feb 2007 to 38.766 million in Feb 2014. The youth civilian labor force of the US fell 0.693 million from 21.634 million in Mar 2007 to 20.941 million in Mar 2014 or 3.2 person while the youth noninstitutional civilian population 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 or 3.9 percent. The US youth civilian labor force fell 981 thousand from 21.442 million in Apr 2007 to 20.461 million in Apr 2014 while the youth civilian noninstitutional population increased from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 by 1.410 thousand or 3.8 percent. The youth civilian labor force decreased from 21.659 million in May 2007 to 21.160 million in May 2014 by 499 thousand or 2.3 percent while the youth civilian noninstitutional population increased 1.370 million from 37.739 million in May 2007 to 38.749 million in May 2007 or by 2.7 percent. The youth civilian labor force decreased from 24.128 million in Jun 2006 to 22.851 million in Jun 2014 by 1.277 million or 5.3 percent while the civilian noninstitutional population increased from 36.943 million in Jun 2006 to 38.740 million in Jun 2014 by 1.797 million or 4.9 percent. The youth civilian labor force fell from 24.664 million in Jul 2006 to 23.437 million in Jul 2014 while the civilian noninstitutional population increased from 36.989 million in Jul 2006 to 38.735 million in Jul 2014. The youth civilian labor force fell 1.818 million from 23.634 million in Aug 2006 to 21.816 million in Aug 2014 while the civilian noninstitutional population increased from 37.008 million in Aug 2006 to 38.706 million in Aug 2914 or 1.698 million. The youth civilian labor force fell 0.942 million from 21.901 million in Sep 2006 to 20.959 million in Sep 2014 while the noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014. The youth civilian labor force decreased 0.702 million from 22.105 million in Oct 2006 to 21.403 million in Oct 2014 while the youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million. The youth civilian labor force decreased 1.111 million from 22.145 million in Nov 2006 to 21.034 million in Nov 2014 while the youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million. The youth civilian labor force decreased 1.472 million from 22.136 million in Dec 2006 to 20.664 million in Dec 2014 while the youth civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million. The youth civilian labor force decreased 0.831 million from 21.368 million in Jan 2006 to 20.555 million in Jan 2015 while the youth noninstitutional population increased from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 or 1.971 million. The youth civilian labor force decreased 0.864 million from 21.615 million in Feb 2006 to 20.751 million in Feb 2015 while the youth noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015. The youth civilian labor force decreased 0.907 million from 21.507 million in Mar 2006 to 20.600 million in Mar 2015 while the civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015. The youth civilian labor force decreased 1.082 million from 21.498 million in Apr 2006 to 20.416 million in Apr 2015 while the youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015. The youth civilian labor force decreased 0.681 million from 22.023 million in May 2006 to 21.342 million in May 2015 while the youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015. The youth civilian labor force decreased 1.202 million from 24.128 million in Jun 2006 to 22.926 million in Jun 2015 while the youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.

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Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2015

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

Chart I-21C provides the ratio of labor force to noninstitutional population or labor force participation of ages 16 to 24 years not seasonally adjusted. The US labor force participation rates for ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2013 because of the frustration of young people who believe there may not be jobs available for them. The US labor force participation rate of young people fell from 63.9 in Aug 2006 to 56.9 in Aug 2013. The US labor force participation rate of young people fell from 59.1 percent in Sep 2006 to 54.6 percent in Sep 2013. The US labor force participation rate of young people fell from 59.7 percent in Oct 2006 to 54.1 in Oct 2013. The US labor force participation rate of young people fell from 59.7 percent in Nov 2006 to 53.7 percent in Nov 2013. The US labor force participation rate fell from 57.8 in Dec 2007 to 53.2 in Dec 2013. The youth labor force participation rate fell from 58.4 in Jan 2007 to 52.7 in Jan 2014. The US youth labor force participation rate fell from 58.0 percent in Feb 2007 to 52.6 percent in Feb 2013. The labor force participation rate of ages 16 to 24 years fell from 58.0 in Mar 2007 to 54.0 in Mar 2014. The labor force participation rate of ages 16 to 24 years fell from 57.4 in Apr 2007 to 52.8 in Apr 2014. The labor force participation rate of ages 16 to 24 years fell from 57.9 in May 2007 to 54.6 in May 2014. The labor force participation rate of ages 16 to 24 years fell from 65.3 in Jun 2006 to 59.0 in Jun 2014. The labor force participation rate ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2014. The labor force participation rate ages 16 to 24 years fell from 63.9 in Aug 2006 to 56.4 in Aug 2014. The labor force participation rate ages 16 to 24 years fell from 59.1 in Sep 2006 to 54.2 in Sep 2014. The labor force participation rate ages 16 to 24 years fell from 59.7 in Oct 2006 to 55.4 in Oct 2014. The labor force participation rate ages 16 to 24 years fell from 59.7 in Nov 2006 to 54.5 in Nov 2014. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 53.5 in Dec 2014. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 53.1 in Jan 2015. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 53.6 in Feb 2015. The labor force participation rate ages 16 to 64 fell from 58.4 in Mar 2006 to 53.3 in Mar 2015. The labor force participation rate ages 16 to 64 fell from 58.7 in Apr 2005 to 52.8 in Apr 2006. The labor force participation rate ages 16 to 64 fell from 59.7 in May 2006 to 55.2 in May 2015. The labor force participation rates ages 16 to 64 fell from 65.3 in Jun 2006 to 59.4 in Jun 2015. Many young people abandoned searches for employment, dropping from the labor force.

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Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2015

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

An important measure of the job market is the number of people with jobs relative to population available for work (civilian noninstitutional population) or employment/population ratio. Chart I-21D provides the employment population ratio for ages 16 to 24 years. The US employment/population ratio NSA for ages 16 to 24 years collapsed from 59.2 in Jul 2006 to 50.7 in Jul 2013. The employment population ratio for ages 16 to 24 years dropped from 57.2 in Aug 2006 to 48.0 in Aug 2013. The employment population ratio for ages to 16 to 24 years declined from 52.9 in Sep 2006 to 46.5 in Sep 2013. The employment population ratio for ages 16 to 24 years fell from 53.6 in Oct 2006 to 46.3 in Oct 2013. The employment population ratio for ages 16 to 24 years fell from 53.7 in Nov 2007 to 46.7 in Nov 2013. The US employment population ratio for ages 16 to 24 years fell from 51.6 in Dec 2007 to 46.7 in Dec 2013. The US employment population ratio fell from 52.1 in Jan 2007 to 44.8 in Jan 2014. The US employment population ratio for ages 16 to 24 fell from 52.0 in Feb 2007 to 44.8 in Feb 2014. The US employment population ratio for ages 16 to 24 years fell from 52.3 in Mar 2007 to 46.3 in Mar 2014. The US employment population ratio for ages 16 to 24 years fell from 51.9 in Apr 2007 to 46.5 in Apr 2014. The US employment population ratio for ages 16 to 24 years fell from 52.1 in May 2007 to 47.3 in May 2014. The US employment population ratio for ages 16 to 24 years fell from 57.6 in Jun 2006 to 50.1 in Jun 2014. The US employment population ratio for ages 16 to 24 years fell from 59.2 in Jul 2006 to 50.1 in Jul 2014. The employment population ratio for ages 16 to 24 years fell from 57.2 in Aug 2006 to 49.0 in Aug 2014. The employment population ratio for ages 16 to 24 fell from 52.9 in Sep 2006 to 46.8 in Sep 2014. The employment population ratio for ages 16 to 24 fell from 53.6 in Oct 2006 to 48.6 in Oct 2014. The employment population ratio for ages 16 to 24 fell from 53.7 in Nov 2006 to 48.1 in Nov 2014. The employment population ration for ages 16 to 24 fell from 54.3 in Dec 2006 to 47.5 in Dec 2014. The employment population ration for ages 16 to 24 years fell from 51.7 in Jan 2006 to 46.2 in Jan 2015. The employment population ratio for ages 16 to 24 fell from 52.1 in Feb 2006 to 47.1 in Feb 2015. The employment population ratio for ages 16 to 24 years fell from 52.4 in Mar 2006 to 46.7 in Mar 2015. The employment population ratio for ages 16 to 24 years fell from 52.7 in Apr 2006 to 47.2 in Apr 2015. The employment population ratio for ages 16 to 24 fell from 53.6 in May 206 to 48.4 in May 2015. The employment population ratio for ages 16 to 24 fell from 57.6 in Jun 2006 to 51.3 in Jun 2015. Chart I-21D shows vertical drop during the global recession without recovery.

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Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2015

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

Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million and 3451 thousand in 2012 or by 1.109 million. The unemployment level ages 16 to 24 years increased from 2342 in 2007 to 3324 thousand in 2013 or by 0.982 million. The unemployment level ages 16 to 24 years increased from 2342 thousand in 2007 to 2853 thousand in 2014 or by 0.511 million.. The unemployment level ages 16 to 24 years increased from 2.203 million in May 2007 to 2.633 million in May 2015 or increase by 0.430 million. The unemployment level ages 16 to 24 years increased from 2.860 million in Jun 2006 in to 3.138 million in Jun 2015 or increase by 0.278 million. This situation may persist for many years.

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

Year

Jan

Feb

Mar

Apr

May

Jun

Dec

Annual

2001

2250

2258

2253

2095

2171

2775

2412

2371

2002

2754

2731

2822

2515

2568

3167

2374

2683

2003

2748

2740

2601

2572

2838

3542

2248

2746

2004

2767

2631

2588

2387

2684

3191

2294

2638

2005

2661

2787

2520

2398

2619

3010

2055

2521

2006

2366

2433

2216

2092

2254

2860

2007

2353

2007

2363

2230

2096

2074

2203

2883

2323

2342

2008

2633

2480

2347

2196

2952

3450

2928

2830

2009

3278

3457

3371

3321

3851

4653

3532

3760

2010

3983

3888

3748

3803

3854

4481

3352

3857

2011

3851

3696

3520

3365

3628

4248

3161

3634

2012

3416

3507

3294

3175

3438

4180

3153

3451

2013

3674

3449

3261

3129

3478

4198

2536

3324

2014

3051

3033

3002

2440

2831

3429

2317

2853

2015

2644

2529

2524

2175

2633

3138

   

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

Chart I-22 provides the unemployment level for ages 16 to 24 from 2001 to 2015. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013-2014 with recent marginal improvement iin 2015 alternating with deterioration.

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Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2015

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

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

Table I-12 provides the rate of unemployment of young peoples in ages 16 to 24 years. The annual rate jumped from 10.5 percent in 2007 to 18.4 percent in 2010, 17.3 percent in 2011 and 16.2 percent in 2012. The rate of youth unemployment fell marginally to 15.5 percent in 2013, declining to 13.4 percent in Dec 2014. During the seasonal peak in Jul, the rate of youth unemployed was 18.1 percent in Jul 2011, 17.1 percent in Jul 2012 and 16.3 percent in Jul 2013 compared with 10.8 percent in Jul 2007. The rate of youth unemployment rose from 11.2 percent in Jul 2006 to 16.3 percent in Jul 2013 and likely higher if adding those who ceased searching for a job in frustration none may be available. The rate of youth unemployment rose from 10.8 in Jul 2007 to 14.3 in Jul 2014. The rate of youth unemployment increased from 9.1 percent in Dec 2006 to 12.3 percent in Dec 2013. The rate of youth unemployment increased from 10.9 percent in Jan 2007 to 14.9 percent in Jan and Feb 2014. The rate of youth unemployment increased from 9.7 percent in Mar 2007 to 14.3 percent in Mar 2014. The rate of youth unemployment increased from 9.7 percent in Apr 2007 to 11.9 percent in Apr 2014. The rate of youth unemployment increased from 10.2 percent in May 2007 to 13.4 percent in May 2014. The rate of youth unemployment increased from 12.0 percent in Jun 2007 to 15.0 percent in Jun 2014. The rate of youth unemployment increased from 10.8 in Jul 2007 to 14.3 in Jul 2014. The rate of youth unemployment increased from 10.5 in Aug 2007 to 13.0 in Aug 2014. The rate of youth unemployment increased from 11.0 in Sep 2007 to 13.6 in Sep 2014. The rate of youth unemployment increased from 10.3 in Oct 2007 to 12.2 in Oct 2014. The rate of youth unemployment increased from 10.3 in Nov 2007 to 11.7 in Nov 2014. The rate of youth unemployment increased from 10.7 in Dec 2007 to 11.2 in Dec 2014. The rate of youth unemployment increased from 10.9 in Jan 2007 to 12.9 in Jan 2015. The rate of youth unemployment increased from 10.3 percent in Feb 2007 to 12.2 percent in Feb 2015. The rate of youth unemployment increased from 9.7 in Mar 2007 to 12.3 in Mar 2015. The rate of youth unemployment increased from 9.7 in Apr 2007 to 10.7 in Apr 2015. The rate of youth unemployment increased from 10.2 in May 2007 to 12.3 in May 2015. The rate of youth unemployment increased from 11.9 in Jun 2007 to 13.7 in Jun 2015. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them.

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

Year

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

2001

10.3

10.3

10.2

9.6

10.0

11.6

10.5

10.7

10.5

11.0

11.2

11.0

10.6

2002

12.9

12.5

12.9

11.6

11.6

13.2

12.4

11.5

11.4

11.2

11.7

10.9

12.0

2003

12.7

12.7

12.2

12.0

13.0

14.8

13.3

11.9

12.5

11.6

11.6

10.5

12.4

2004

12.8

12.3

12.1

11.1

12.2

13.4

12.3

11.1

11.5

11.6

11.1

10.5

11.8

2005

12.4

13.0

11.7

11.2

11.9

12.6

11.0

10.8

10.7

10.3

10.7

9.4

11.3

2006

11.1

11.3

10.3

9.7

10.2

11.9

11.2

10.4

10.5

10.2

10.1

9.1

10.5

2007

10.9

10.3

9.7

9.7

10.2

12.0

10.8

10.5

11.0

10.3

10.3

10.7

10.5

2008

12.3

11.8

11.1

10.3

13.3

14.4

14.0

13.0

13.4

13.2

13.3

13.7

12.8

2009

15.8

16.4

16.1

15.8

18.0

19.9

18.5

18.0

18.2

18.5

18.1

17.5

17.6

2010

19.8

19.2

18.4

18.5

18.4

20.0

19.1

17.8

17.6

18.1

17.4

16.7

18.4

2011

18.9

18.2

17.2

16.5

17.5

18.9

18.1

17.5

17.0

16.2

15.9

15.5

17.3

2012

16.8

17.0

16.0

15.4

16.3

18.1

17.1

16.8

15.2

15.5

14.8

15.2

16.2

2013

17.6

16.7

15.9

15.1

16.4

18.0

16.3

15.6

14.8

14.4

13.1

12.3

15.5

2014

14.9

14.9

14.3

11.9

13.4

15.0

14.3

13.0

13.6

12.2

11.7

11.2

13.4

2015

12.9

12.2

12.3

10.7

12.3

13.7

             

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

Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2001 to 2015. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels because of low growth of GDP. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E. Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

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Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2015

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

Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2015. The rate of youth unemployment rose to 20 percent during the contractions of the early 1980s and also during the contraction of the global recession in 2008 and 2009. The data illustrate again the argument in this blog that the contractions of the early 1980s are the valid framework for comparison with the global recession of 2008 and 2009 instead of misleading comparisons with the 1930s. During the initial phase of recovery, the rate of youth unemployment 16 to 24 years NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984. In contrast, the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 17.5 percent in Dec 2009, 16.7 percent in Dec 2010, 15.5 percent in Dec 2011, 15.2 percent in Dec 2012, 17.6 percent in Jan 2013, 16.7 percent in Feb 2013, 15.9 percent in Mar 2013, 15.1 percent in Apr 2013. The rate of youth unemployment was 16.4 percent in May 2013, 18.0 percent in Jun 2013, 16.3 percent in Jul 2013 and 15.6 percent in Aug 2013. In Sep 2006, the rate of youth unemployment was 10.5 percent, increasing to 14.8 percent in Sep 2013. The rate of youth unemployment was 10.3 in Oct 2007, increasing to 14.4 percent in Oct 2013. The rate of youth unemployment was 10.3 percent in Nov 2007, increasing to 13.1 percent in Nov 2013. The rate of youth unemployment was 10.7 percent in Dec 2013, increasing to 12.3 percent in Dec 2013. The rate of youth unemployment was 10.9 percent in Jan 2007, increasing to 14.9 percent in Jan 2014. The rate of youth unemployment was 10.3 percent in Feb 2007, increasing to 14.9 percent in Feb 2014. The rate of youth unemployment was 9.7 percent in Mar 2007, increasing to 14.3 percent in Mar 2014. The rate of youth unemployment was 9.7 percent in Apr 2007, increasing to 11.9 percent in Apr 2014. The rate of youth unemployment was 10.2 percent in May 2007, increasing to 13.4 percent in May 2014. The rate of youth unemployment was 12.0 percent in Jun 2007, increasing to 15.0 percent in Jun 2014. The rate of youth unemployment was 10.8 percent in Jul 2007, increasing to 14.3 percent in Jul 2014. The rate of youth unemployment was 10.5 percent in Aug 2007, increasing to 13.0 percent in Aug 2014. The rate of youth unemployment was 11.0 percent in Sep 2007, increasing to 13.6 percent in Sep 2014. The rate of youth unemployment increased from 10.3 in Oct 2007 to 12.2 in Oct 2014. The rate of youth unemployment increased from 10.3 percent in Nov 2007 to 11.7 percent in Nov 2014. The rate of youth unemployment increased from 10.7 in Dec 2007 to 11.2 in Dec 2014. The rate of youth unemployment increased from 9.7 in Mar 2007 to 12.3 in Mar 2015. The rate of youth unemployment increased from 9.7 in Apr 2007 to 10.7 in Apr 2015. The rate of youth unemployment increased from 10.2 in May 2007 to 12.3 in May 2015. The rate of youth unemployment increased from 12.0 in Jun 2007 to 13.7 in Jun 2015. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.9 percent during the recovery from IQ1983 to IVQ1985 and 4.8 percent from IQ1983 to IIIQ1988 compared with 2.2 percent on average during the first 23 quarters of expansion from IIIQ2009 to IQ2015. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 23 quarters from IIIQ2009 to IQ2015. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IQ2015 (http://www.bea.gov/newsreleases/national/gdp/2015/pdf/gdp1q15_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IQ2015 would have accumulated to 23.9 percent. GDP in IQ2015 would be $18,574.8 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,287.1 billion than actual $16,287.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 25.0 million unemployed or underemployed equivalent to actual unemployment/underemployment of 15.1 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html). US GDP in IQ2015 is 12.3 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,287.7 billion in IQ2015 or 8.6 percent at the average annual equivalent rate of 1.2 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth at average 3.3 percent per year from May 1919 to May 2015. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 126.2585 in May 2015. The actual index NSA in May 2015 is 101.5858, which is 19.5 percent below trend. Manufacturing output grew at average 2.4 percent between Dec 1986 and Dec 2014. Using trend growth of 2.4 percent per year, the index would increase to 118.3245 in May 2015. The output of manufacturing at 101.5858 in May 2015 is 14.1 percent below trend under this alternative calculation.

clip_image031

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2015

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

It is more difficult to move to other jobs after a certain age because of fewer available opportunities for mature individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.607 million in Oct 2006 to 4.576 million in Oct 2010 or by 184.8 percent. The number of unemployed ages 45 years and over declined to 3.800 million in Oct 2012 that is still higher by 136.5 percent than in Oct 2006. The number unemployed age 45 and over increased from 1.704 million in Nov 2006 to 3.861 million in Nov 2012, or 126.6 percent. The number unemployed age 45 and over is still higher by 98.5 percent at 3.383 million in Nov 2013 than 1.704 million in Nov 2006. The number unemployed age 45 and over jumped from 1.794 million in Dec 2006 to 4.762 million in Dec 2010 or 165.4 percent. At 3.927 million in Dec 2012, mature unemployment is higher by 2.133 million or 118.9 percent higher than 1.794 million in Dec 2006. The level of unemployment of those aged 45 year or more of 3.632 million in Oct 2013 is higher by 2.025 million than 1.607 million in Oct 2006 or higher by 126.0 percent. The number of unemployed 45 years and over increased from 1.794 million in Dec 2006 to 3.378 million in Nov 2013 or 88.3 percent. The annual number of unemployed 45 years and over increased from 1.848 million in 2006 to 3.719 million in 2013 or 101.2 percent. The number of unemployed 45 years and over increased from 2.126 million in Jan 2006 to 4.394 million in Jan 2013, by 2.618 million or 106.7 percent. The number of unemployed 45 years and over rose from 2.126 million in Jan 2006 to 3.508 million in Jan 2014, by 1.382 million or 65.0 percent. The level of unemployed 45 years or older increased 2.051 million or 99.8 percent from 2.056 million in Feb 2006 to 4.107 million in Feb 2013 and at 3.490 million in Feb 2014 is higher by 69.7 percent than in Feb 2006. The number of unemployed 45 years and over increased 2.048 million or 108.9 percent from 1.881 million in Mar 2006 to 3.929 million in Mar 2013 and at 3.394 million in Mar 2014 is higher by 80.4 percent than in Mar 2006. The number of unemployed 45 years and over increased 1.846 million or 100.2 percent from 1.843 million in Apr 2006 to 3.689 million in Apr 2013 and at 3.006 million in Apr 2014 is higher by 1.163 million or 63.1 percent. The number of unemployed ages 45 years and over increased 102.1 percent from 1.784 million in May 2006 to 3.605 million in May 2014 and at 2.913 million in May 2014 is higher by 63.3 percent than in May 2007.

The number of unemployed ages 45 years and over increased 102.1 percent from 1.805 million in Jun 2007 to 3.648 million in Jun 2013 and at 2.832 million in Jun 2014 is higher by 56.9 percent than in Jun 2007. The number of unemployed ages 45 years and over increased 81.5 percent from 2.053 million in Jul 2007 to 3.727 million in Jul 2013 and at 3.083 million in Jul 2014 is higher by 50.2 percent than in Jul 2007. The level unemployed ages 45 years and over increased 84.4 percent from 1.956 million in Aug 2007 to 3.607 million in Aug 2013 and at 3.037 million in Aug 2014 is 55.2 percent higher than in Aug 2007. The level unemployed ages 45 years and over increased 90.7 percent from 1.854 million in Sep 2007 to 3.535 million in Sep 2013 and at 2.640 million in Sep 2014 is 42.4 percent higher than in Sep 2007. The level unemployed ages 45 years and over increased 1.747 million from 1.885 million in Oct 2007 to 3.632 million in Oct 2013 and at 2.606 million in Oct 2014 is 38.2 percent higher than in Oct 2007. The level unemployed ages 45 years and over increased 1.458 million from 1.925 million in Nov 2007 to 3.383 million in Nov 2013 and at 2.829 million in Nov 2014 is 47.0 percent higher than in Nov 2007. The level of unemployed ages 45 years and over increased 1.258 million from Dec 2007 to Dec 2013 and at 2.667 million in Dec 2014 is 25.8 higher than in Dec 2007. The level unemployed ages 45 years and over increased 1.353 million from Jan 2007 to Jan 2015 and at 3.077 million in Jan 2015 is 42.8 percent higher than in Jan 2007. The level unemployed ages 45 years and over increased 1.352 million from 2.138 million in Feb 2007 to 3.490 million in Feb 2014 and at 2.991 million in Feb 2015 is 39.9 percent higher than in Feb 2007. The level of unemployed ages 45 years and over increased 1.363 million from 2.031 million in Mar 2007 to 3.394 million in Mar 2014 and at 2.724 million in Mar 2015 is 34.1 percent higher than in Mar 2007. The level of unemployed ages 45 years and over increased from 1.871 million in Apr 2007 to 3.006 million in Apr 2014 and at 2.579 million in Apr 2015 is 37.8 higher than in Apr 2007. The level of unemployed ages 45 years and over increased from 1.803 million in May 2007 to 2.913 million in Jun 2014 and at 2.457 million in May 2015 is 36.3 percent higher than in May 2007. The level of unemployed ages 45 years and over increased from 1.805 million in Jun 2007 to 2.832 million in Jun 2014 and at 2.359 million in Jun 2015 is 30.7 percent higher than in Jun 2007. The actual number unemployed is likely much higher because many are not accounted who abandoned job searches in frustration there may not be a job for them. Recent improvements may be illusory.

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

Year

Jan

Feb

Mar

Apr

May

Jun

Dec

Annual

2000

1498

1392

1291

1062

1074

1163

1217

1249

2001

1572

1587

1533

1421

1259

1371

1901

1576

2002

2235

2280

2138

2101

1999

2190

2210

2114

2003

2495

2415

2485

2287

2112

2212

2130

2253

2004

2453

2397

2354

2160

2025

2182

2086

2149

2005

2286

2286

2126

1939

1844

1868

1963

2009

2006

2126

2056

1881

1843

1784

1813

1794

1848

2007

2155

2138

2031

1871

1803

1805

2120

1966

2008

2336

2336

2326

2104

2095

2211

3485

2540

2009

4138

4380

4518

4172

4175

4505

4960

4500

2010

5314

5307

5194

4770

4565

4564

4762

4879

2011

5027

4837

4748

4373

4356

4559

4182

4537

2012

4458

4472

4390

4037

4083

4084

3927

4133

2013

4394

4107

3929

3689

3605

3648

3378

3719

2014

3508

3490

3394

3006

2913

2832

2667

3000

2015

3077

2991

2724

2579

2457

2359

   

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

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

clip_image032

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2015

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

  IIA United States International Trade. Table IIA-1 provides the trade balance of the US and monthly growth of exports and imports seasonally adjusted with the latest release and revisions (http://www.census.gov/foreign-trade/). Because of heavy dependence on imported oil, fluctuations in the US trade account originate largely in fluctuations of commodity futures prices caused by carry trades from zero interest rates into commodity futures exposures in a process similar to world inflation waves (http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html). The Census Bureau revised data for 2014, 2013 and 2012. Exports decreased 0.8 percent in May 2015 while imports decreased 0.1 percent. The trade deficit increased from $40,698 million in Apr 2015 to $41,871 million in May 2015. The trade deficit increased to $39,462 million in Jan 2014 and deficit of $42,835 million in Feb 2014. The trade deficit increased to $43,121 million in Mar 2014 and $44,271 million in Apr 2014. The deficit improved to $42,070 million in May 2014 and $41,411 million in Jul 2014. The trade deficit moved to $41,275 million in Aug 2014, deteriorating to $43,186 million in Sep 2014 and $42,753 million in Oct 2014. The trade deficit improved to $40,021 million in Nov 2014, deteriorating to $45,549 million in Dec 2014 and improving to $42,447 million in Jan 2015 and $37,248 million in Feb 2015. The trade deficit deteriorated to $40,698 million in Apr 2015 and $41,871 in May 2015.

Table IIA-1, US, Trade Balance of Goods and Services Seasonally Adjusted Millions of Dollars and ∆%  

 

Trade Balance

Exports

Month ∆%

Imports

Month ∆%

May 2015

-41,871

188,595

-0.8

230,466

-0.1

Apr

-40,698

190,067

1.1

230,765

-3.3

Mar

-50,566

188,001

0.7

238,567

6.5

Feb

-37,248

186,765

-1.4

224,013

-3.4

Jan

-42,447

189,495

-2.8

231,941

-3.6

Dec 2014

-45,549

194,975

-0.6

240,524

1.8

Nov

-40,021

196,201

-0.8

236,222

-1.8

Oct

-42,753

197,759

1.4

240,513

1.0

Sep

-43,186

195,053

-1.1

238,239

-0.1

Aug

-41,275

197,303

0.2

238,578

0.1

Jul

-41,411

196,907

0.7

238,317

0.2

Jun

-42,371

195,579

-0.9

237,950

-0.6

May

-42,070

197,269

1.2

239,340

0.0

Apr

-44,271

195,024

0.1

239,295

0.6

Mar

-43,121

194,759

2.8

237,881

2.4

Feb

-42,835

189,495

-1.8

232,330

0.0

Jan

-39,462

192,879

0.1

232,341

0.8

Jan-Dec 2014

-508,324

2,343,205

2.9

2,851,529

3.4

Note: Trade Balance of Goods = Exports of Goods less Imports of Goods. Trade balance may not add exactly because of errors of rounding and seasonality. Source: US Census Bureau, Foreign Trade Division

http://www.census.gov/foreign-trade/

Table IIA-1B provides US exports, imports and the trade balance of goods. The US has not shown a trade surplus in trade of goods since 1976. The deficit of trade in goods deteriorated sharply during the boom years from 2000 to 2007. The deficit improved during the contraction in 2009 but deteriorated in the expansion after 2009. The deficit could deteriorate sharply with growth at full employment.

Table IIA-1B, US, International Trade Balance of Goods, Exports and Imports of Goods, Millions of Dollars, Census Basis

 

Balance

∆%

Exports

∆%

Imports

∆%

1960

4,608

(X)

19,626

(X)

15,018

(X)

1961

5,476

18.8

20,190

2.9

14,714

-2.0

1962

4,583

-16.3

20,973

3.9

16,390

11.4

1963

5,289

15.4

22,427

6.9

17,138

4.6

1964

7,006

32.5

25,690

14.5

18,684

9.0

1965

5,333

-23.9

26,699

3.9

21,366

14.4

1966

3,837

-28.1

29,379

10.0

25,542

19.5

1967

4,122

7.4

30,934

5.3

26,812

5.0

1968

837

-79.7

34,063

10.1

33,226

23.9

1969

1,289

54.0

37,332

9.6

36,043

8.5

1970

3,224

150.1

43,176

15.7

39,952

10.8

1971

-1,476

-145.8

44,087

2.1

45,563

14.0

1972

-5,729

288.1

49,854

13.1

55,583

22.0

1973

2,389

-141.7

71,865

44.2

69,476

25.0

1974

-3,884

-262.6

99,437

38.4

103,321

48.7

1975

9,551

-345.9

108,856

9.5

99,305

-3.9

1976

-7,820

-181.9

116,794

7.3

124,614

25.5

1977

-28,352

262.6

123,182

5.5

151,534

21.6

1978

-30,205

6.5

145,847

18.4

176,052

16.2

1979

-23,922

-20.8

186,363

27.8

210,285

19.4

1980

-19,696

-17.7

225,566

21.0

245,262

16.6

1981

-22,267

13.1

238,715

5.8

260,982

6.4

1982

-27,510

23.5

216,442

-9.3

243,952

-6.5

1983

-52,409

90.5

205,639

-5.0

258,048

5.8

1984

-106,702

103.6

223,976

8.9

330,678

28.1

1985

-117,711

10.3

218,815

-2.3

336,526

1.8

1986

-138,279

17.5

227,159

3.8

365,438

8.6

1987

-152,119

10.0

254,122

11.9

406,241

11.2

1988

-118,526

-22.1

322,426

26.9

440,952

8.5

1989

-109,399

-7.7

363,812

12.8

473,211

7.3

1990

-101,719

-7.0

393,592

8.2

495,311

4.7

1991

-66,723

-34.4

421,730

7.1

488,453

-1.4

1992

-84,501

26.6

448,164

6.3

532,665

9.1

1993

-115,568

36.8

465,091

3.8

580,659

9.0

1994

-150,630

30.3

512,626

10.2

663,256

14.2

1995

-158,801

5.4

584,742

14.1

743,543

12.1

1996

-170,214

7.2

625,075

6.9

795,289

7.0

1997

-180,522

6.1

689,182

10.3

869,704

9.4

1998

-229,758

27.3

682,138

-1.0

911,896

4.9

1999

-328,821

43.1

695,797

2.0

1,024,618

12.4

2000

-436,104

32.6

781,918

12.4

1,218,022

18.9

2001

-411,899

-5.6

729,100

-6.8

1,140,999

-6.3

2002

-468,263

13.7

693,103

-4.9

1,161,366

1.8

2003

-532,350

13.7

724,771

4.6

1,257,121

8.2

2004

-654,830

23.0

814,875

12.4

1,469,704

16.9

2005

-772,373

18.0

901,082

10.6

1,673,455

13.9

2006

-827,971

7.2

1,025,967

13.9

1,853,938

10.8

2007

-808,763

-2.3

1,148,199

11.9

1,956,962

5.6

2008

-816,199

0.9

1,287,442

12.1

2,103,641

7.5

2009

-503,582

-38.3

1,056,043

-18.0

1,559,625

-25.9

2010

-635,362

26.2

1,278,495

21.1

1,913,857

22.7

2011

-725,447

14.2

1,482,508

16.0

2,207,954

15.4

2012

-730,446

0.7

1,545,821

4.3

2,276,267

3.1

2013

-689,931

-5.5

1,578,439

2.1

2,268,370

-0.3

2014

-727,153

5.4

1,620,532

2.7

2,347,685

3.5

Source: US Census Bureau, Foreign Trade Division

http://www.census.gov/foreign-trade/

Chart IIA-1 of the US Census Bureau of the Department of Commerce shows that the trade deficit (gap between exports and imports) fell during the economic contraction after 2007 but has grown again during the expansion. The low average rate of growth of GDP of 2.2 percent during the expansion beginning since IIIQ2009 does not deteriorate further the trade balance. Higher rates of growth may cause sharper deterioration.

clip_image034

Chart IIA-1, US, International Trade Balance, Exports and Imports of Goods and Services USD Billions

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr042.html

Table IIA-2B provides the US international trade balance, exports and imports of goods and services on an annual basis from 1992 to 2014. The trade balance deteriorated sharply over the long term. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US not seasonally adjusted increased from $73 billion in IQ2014 to $89 billion in IQ2015 (http://www.bea.gov/international/index.htm). The current account deficit seasonally adjusted at annual rate decreased from 2.3 percent of GDP in IQ2014 to 2.1 percent of GDP in IIQ2014, increasing to 2.2 percent of GDP in IIIQ2014 and 2.3 percent of GDP in IVQ2014. The current account deficit increased to 2.6 percent of GDP in IQ2015 (http://www.bea.gov/international/index.htm http://www.bea.gov/iTable/index_nipa.cfm). The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71). The last row of Table IIA-2B shows marginal improvement of the trade deficit from $548,625 million in 2011 to lower $536,773 million in 2012 with exports growing 4.3 percent and imports 3.0 percent. The trade balance improved further to deficit of $478,394 million in 2013 with growth of exports of 2.7 percent while imports virtually stagnated. The trade deficit deteriorated in 2014 to $508,324 million with growth of exports of 2.8 percent and of imports of 3.4 percent. Growth and commodity shocks under alternating inflation waves (http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html) have deteriorated the trade deficit from the low of $383,774 million in 2009.

Table IIA-2B, US, International Trade Balance of Goods and Services, Exports and Imports of Goods and Services, SA, Millions of Dollars, Balance of Payments Basis

 

Balance

Exports

∆%

Imports

∆%

1960

3,508

25,940

NA

22,432

NA

1961

4,195

26,403

1.8

22,208

-1.0

1962

3,370

27,722

5.0

24,352

9.7

1963

4,210

29,620

6.8

25,410

4.3

1964

6,022

33,341

12.6

27,319

7.5

1965

4,664

35,285

5.8

30,621

12.1

1966

2,939

38,926

10.3

35,987

17.5

1967

2,604

41,333

6.2

38,729

7.6

1968

250

45,543

10.2

45,293

16.9

1969

91

49,220

8.1

49,129

8.5

1970

2,254

56,640

15.1

54,386

10.7

1971

-1,302

59,677

5.4

60,979

12.1

1972

-5,443

67,222

12.6

72,665

19.2

1973

1,900

91,242

35.7

89,342

23.0

1974

-4,293

120,897

32.5

125,190

40.1

1975

12,404

132,585

9.7

120,181

-4.0

1976

-6,082

142,716

7.6

148,798

23.8

1977

-27,246

152,301

6.7

179,547

20.7

1978

-29,763

178,428

17.2

208,191

16.0

1979

-24,565

224,131

25.6

248,696

19.5

1980

-19,407

271,834

21.3

291,241

17.1

1981

-16,172

294,398

8.3

310,570

6.6

1982

-24,156

275,236

-6.5

299,391

-3.6

1983

-57,767

266,106

-3.3

323,874

8.2

1984

-109,072

291,094

9.4

400,166

23.6

1985

-121,880

289,070

-0.7

410,950

2.7

1986

-138,538

310,033

7.3

448,572

9.2

1987

-151,684

348,869

12.5

500,552

11.6

1988

-114,566

431,149

23.6

545,715

9.0

1989

-93,141

487,003

13.0

580,144

6.3

1990

-80,864

535,233

9.9

616,097

6.2

1991

-31,135

578,344

8.1

609,479

-1.1

1992

-39,212

616,882

6.7

656,094

7.6

1993

-70,311

642,863

4.2

713,174

8.7

1994

-98,493

703,254

9.4

801,747

12.4

1995

-96,384

794,387

13.0

890,771

11.1

1996

-104,065

851,602

7.2

955,667

7.3

1997

-108,273

934,453

9.7

1,042,726

9.1

1998

-166,140

933,174

-0.1

1,099,314

5.4

1999

-258,617

969,867

3.9

1,228,485

11.8

2000

-372,517

1,075,321

10.9

1,447,837

17.9

2001

-361,511

1,005,654

-6.5

1,367,165

-5.6

2002

-418,955

978,706

-2.7

1,397,660

2.2

2003

-493,890

1,020,418

4.3

1,514,308

8.3

2004

-609,883

1,161,549

13.8

1,771,433

17.0

2005

-714,245

1,286,022

10.7

2,000,267

12.9

2006

-761,716

1,457,642

13.3

2,219,358

11.0

2007

-705,375

1,653,548

13.4

2,358,922

6.3

2008

-708,726

1,841,612

11.4

2,550,339

8.1

2009

-383,774

1,583,053

-14.0

1,966,827

-22.9

2010

-494,658

1,853,606

17.1

2,348,263

19.4

2011

-548,625

2,127,021

14.8

2,675,646

13.9

2012

-536,773

2,218,989

4.3

2,755,762

3.0

2013

-478,394

2,279,937

2.7

2,758,331

0.1

2014

-508,324

2,343,205

2.8

2,851,529

3.4

Source: US Census Bureau

http://www.census.gov/foreign-trade/

Chart IIA-2 of the US Census Bureau provides the US trade account in goods and services SA from Jan 1992 to May 2015. There is long-term trend of deterioration of the US trade deficit shown vividly by Chart IIA-2. The global recession from IVQ2007 to IIQ2009 reversed the trend of deterioration. Deterioration resumed together with incomplete recovery and was influenced significantly by the carry trade from zero interest rates to commodity futures exposures (these arguments are elaborated in Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4 http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html). Earlier research focused on the long-term external imbalance of the US in the form of trade and current account deficits (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). US external imbalances have not been fully resolved and tend to widen together with improving world economic activity and commodity price shocks.

clip_image035

Chart IIA-2, US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-May 2015

Source: US Census Bureau

http://www.census.gov/foreign-trade/

Chart IIA-3 of the US Census Bureau provides US exports SA from Jan 1992 to May 2015. There was sharp acceleration from 2003 to 2007 during worldwide economic boom and increasing inflation. Exports fell sharply during the financial crisis and global recession from IVQ2007 to IIQ2009. Growth picked up again together with world trade and inflation but stalled in the final segment with less rapid global growth and inflation.

clip_image036

Chart IIA-3, US, Exports SA, Monthly, Millions of Dollars Jan 1992-May 2015

Source: US Census Bureau

http://www.census.gov/foreign-trade/

Chart IIA-4 of the US Census Bureau provides US imports SA from Jan 1992 to May 2015. Growth was stronger between 2003 and 2007 with worldwide economic boom and inflation. There was sharp drop during the financial crisis and global recession. There is stalling import levels in the final segment resulting from weaker world economic growth and diminishing inflation because of risk aversion and portfolio reallocations from commodity exposures to equities.

clip_image037

Chart IIA-4, US, Imports SA, Monthly, Millions of Dollars Jan 1992-May 2015

Source: US Census Bureau

http://www.census.gov/foreign-trade/

There is improvement of the US trade balance in goods in Table IIA-3 from deficit of $62,091 million in May 2014 to deficit of $61,511 million in May 2015. The nonpetroleum deficit increased by $8,619 million while the petroleum deficit shrank by $9,418 million. Total exports of goods decreased 7.0 percent in May 2015 relative to a year earlier while total imports decreased 5.1 percent. Nonpetroleum exports decreased 4.5 percent from May 2014 to May 2015 while nonpetroleum imports increased 1.9 percent. Petroleum imports fell 45.8 percent.

Table IIA-3, US, International Trade in Goods Balance, Exports and Imports $ Millions and ∆% SA

 

May 2015

May 2014

∆%

Total Balance

-61,511

-62,091

 

Petroleum

-5,775

-15,193

 

Non Petroleum

-54,649

-46,030

 

Total Exports

127,722

137,314

-7.0

Petroleum

9,520

13,043

-27.0

Non Petroleum

117,499

122,989

-4.5

Total Imports

189,233

199,405

-5.1

Petroleum

15,296

28,235

-45.8

Non Petroleum

172,148

169,019

1.9

Details may not add because of rounding and seasonal adjustment

Source: US Census Bureau

http://www.census.gov/foreign-trade/

US exports and imports of goods not seasonally adjusted in Jan-May 2015 and Jan-May 2014 are in Table IIA-4. The rate of growth of exports was minus 5.1 percent and minus 3.9 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that decreased 10.8 percent and of mineral fuels that decreased 29.6 percent both because prices of raw materials and commodities increase and fall recurrently as a result of shocks of risk aversion and portfolio reallocations. The US exports an insignificant but growing amount of crude oil, decreasing 28.5 percent in cumulative Jan-May 2015 relative to a year earlier. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports decreased 4.4 percent while manufactured imports increased 2.5 percent. Significant part of the US trade imbalance originates in imports of mineral fuels decreasing 45.2 percent and petroleum decreasing 45.8 percent with wide oscillations in oil prices. The limited hedge in exports of agricultural commodities and mineral fuels compared with substantial imports of mineral fuels and crude oil results in waves of deterioration of the terms of trade of the US, or export prices relative to import prices, originating in commodity price increases caused by carry trades from zero interest rates. These waves are similar to those in worldwide inflation.

Table IIA-4, US, Exports and Imports of Goods, Not Seasonally Adjusted Millions of Dollars and %, Census Basis

 

Jan-May 2015 $ Millions

Jan-May 2014 $ Millions

∆%

Exports

630,231

664,288

-5.1

Manufactured

466,455

488,529

-4.5

Agricultural
Commodities

57,723

64,684

-10.8

Mineral Fuels

45,834

65,147

-29.6

Petroleum

37,600

52,588

-28.5

Imports

914,069

950,693

-3.9

Manufactured

786,771

767,524

2.5

Agricultural
Commodities

48,946

47,412

3.2

Mineral Fuels

84,810

154,804

-45.2

Petroleum

77,952

143,802

-45.8

Source: US Census Bureau

http://www.census.gov/foreign-trade/

IIA2 Unresolved US Balance of Payments Deficits. The current account of the US balance of payments is provided in Table IIA2-1 for IQ2014 and IQ2015. The Bureau of Economic Analysis analyzes as follows (http://www.bea.gov/newsreleases/international/transactions/2015/pdf/trans115.pdf):

“The U.S. current-account deficit—a net measure of transactions between the United States and the rest of the world in goods, services, primary income (investment income and compensation), and secondary income (current transfers)— increased to $113.3 billion (preliminary) in the first quarter of 2015 from $103.1 billion (revised) in the fourth quarter of 2014. The deficit increased to 2.6 percent of current dollar gross domestic product (GDP) from 2.3 percent in the fourth quarter. The increase in the current-account deficit was largely accounted for by a decrease in the surplus on primary income. In addition, the deficit on goods increased. These changes were partly offset by an increase in the surplus on services and a decrease in the deficit on secondary income.”

The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US not seasonally adjusted increased from $73.2 billion in IQ2014 to $88.6 billion in IQ2015. The current account deficit seasonally adjusted at annual rate did not change from 2.3 percent of GDP in IQ2014 to 2.3 percent of GDP in IVQ2014, increasing to 2.6 percent of GDP in IQ2015. The ratio of the current account deficit to GDP has stabilized below 3 percent of GDP compared with much higher percentages before the recession but is combined now with much higher imbalance in the Treasury budget (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71).

Table IIA2-1, US, Balance of Payments, Millions of Dollars NSA

 

IQ2014

IQ2015

Difference

Goods Balance

-161,423

-168,585

7,162

X Goods

395,538

375,795

-5.0 ∆%

M Goods

-556,961

-544,380

-2.3 ∆%

Services Balance

61,249

62,589

1,340

X Services

171,715

179,003

4.2 ∆%

M Services

-110,466

-116,414

5.4 ∆%

Balance Goods and Services

-100,174

-105,995

5,821

Exports of Goods and Services and Income Receipts

799,957

783,293

 

Imports of Goods and Services and Income Payments

-873,121

-871,942

 

Current Account Balance

-73,164

-88,648

15,484

% GDP

IQ2014

IQ2015

IVQ2014

 

2.3

2.6

2.3

X: exports; M: imports

Balance on Current Account = Exports of Goods and Services – Imports of Goods and Services and Income Payments

Source: Bureau of Economic Analysis

http://www.bea.gov/international/index.htm#bop

In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):

“Imagine that fiscal policy dominates monetary policy. The fiscal authority independently sets its budgets, announcing all current and future deficits and surpluses and thus determining the amount of revenue that must be raised through bond sales and seignorage. Under this second coordination scheme, the monetary authority faces the constraints imposed by the demand for government bonds, for it must try to finance with seignorage any discrepancy between the revenue demanded by the fiscal authority and the amount of bonds that can be sold to the public. Suppose that the demand for government bonds implies an interest rate on bonds greater than the economy’s rate of growth. Then if the fiscal authority runs deficits, the monetary authority is unable to control either the growth rate of the monetary base or inflation forever. If the principal and interest due on these additional bonds are raised by selling still more bonds, so as to continue to hold down the growth of base money, then, because the interest rate on bonds is greater than the economy’s growth rate, the real stock of bonds will growth faster than the size of the economy. This cannot go on forever, since the demand for bonds places an upper limit on the stock of bonds relative to the size of the economy. Once that limit is reached, the principal and interest due on the bonds already sold to fight inflation must be financed, at least in part, by seignorage, requiring the creation of additional base money.”

The alternative fiscal scenario of the CBO (2012NovCDR, 2013Sep17) resembles an economic world in which eventually the placement of debt reaches a limit of what is proportionately desired of US debt in investment portfolios. This unpleasant environment is occurring in various European countries.

The current real value of government debt plus monetary liabilities depends on the expected discounted values of future primary surpluses or difference between tax revenue and government expenditure excluding interest payments (Cochrane 2011Jan, 27, equation (16)). There is a point when adverse expectations about the capacity of the government to generate primary surpluses to honor its obligations can result in increases in interest rates on government debt.

First, Unpleasant Monetarist Arithmetic. Fiscal policy is described by Sargent and Wallace (1981, 3, equation 1) as a time sequence of D(t), t = 1, 2,…t, …, where D is real government expenditures, excluding interest on government debt, less real tax receipts. D(t) is the real deficit excluding real interest payments measured in real time t goods. Monetary policy is described by a time sequence of H(t), t=1,2,…t, …, with H(t) being the stock of base money at time t. In order to simplify analysis, all government debt is considered as being only for one time period, in the form of a one-period bond B(t), issued at time t-1 and maturing at time t. Denote by R(t-1) the real rate of interest on the one-period bond B(t) between t-1 and t. The measurement of B(t-1) is in terms of t-1 goods and [1+R(t-1)] “is measured in time t goods per unit of time t-1 goods” (Sargent and Wallace 1981, 3). Thus, B(t-1)[1+R(t-1)] brings B(t-1) to maturing time t. B(t) represents borrowing by the government from the private sector from t to t+1 in terms of time t goods. The price level at t is denoted by p(t). The budget constraint of Sargent and Wallace (1981, 3, equation 1) is:

D(t) = {[H(t) – H(t-1)]/p(t)} + {B(t) – B(t-1)[1 + R(t-1)]} (1)

Equation (1) states that the government finances its real deficits into two portions. The first portion, {[H(t) – H(t-1)]/p(t)}, is seigniorage, or “printing money.” The second part,

{B(t) – B(t-1)[1 + R(t-1)]}, is borrowing from the public by issue of interest-bearing securities. Denote population at time t by N(t) and growing by assumption at the constant rate of n, such that:

N(t+1) = (1+n)N(t), n>-1 (2)

The per capita form of the budget constraint is obtained by dividing (1) by N(t) and rearranging:

B(t)/N(t) = {[1+R(t-1)]/(1+n)}x[B(t-1)/N(t-1)]+[D(t)/N(t)] – {[H(t)-H(t-1)]/[N(t)p(t)]} (3)

On the basis of the assumptions of equal constant rate of growth of population and real income, n, constant real rate of return on government securities exceeding growth of economic activity and quantity theory equation of demand for base money, Sargent and Wallace (1981) find that “tighter current monetary policy implies higher future inflation” under fiscal policy dominance of monetary policy. That is, the monetary authority does not permanently influence inflation, lowering inflation now with tighter policy but experiencing higher inflation in the future.

Second, Unpleasant Fiscal Arithmetic. The tool of analysis of Cochrane (2011Jan, 27, equation (16)) is the government debt valuation equation:

(Mt + Bt)/Pt = Et∫(1/Rt, t+τ)stdτ (4)

Equation (4) expresses the monetary, Mt, and debt, Bt, liabilities of the government, divided by the price level, Pt, in terms of the expected value discounted by the ex-post rate on government debt, Rt, t+τ, of the future primary surpluses st, which are equal to TtGt or difference between taxes, T, and government expenditures, G. Cochrane (2010A) provides the link to a web appendix demonstrating that it is possible to discount by the ex post Rt, t+τ. The second equation of Cochrane (2011Jan, 5) is:

MtV(it, ·) = PtYt (5)

Conventional analysis of monetary policy contends that fiscal authorities simply adjust primary surpluses, s, to sanction the price level determined by the monetary authority through equation (5), which deprives the debt valuation equation (4) of any role in price level determination. The simple explanation is (Cochrane 2011Jan, 5):

“We are here to think about what happens when [4] exerts more force on the price level. This change may happen by force, when debt, deficits and distorting taxes become large so the Treasury is unable or refuses to follow. Then [4] determines the price level; monetary policy must follow the fiscal lead and ‘passively’ adjust M to satisfy [5]. This change may also happen by choice; monetary policies may be deliberately passive, in which case there is nothing for the Treasury to follow and [4] determines the price level.”

An intuitive interpretation by Cochrane (2011Jan 4) is that when the current real value of government debt exceeds expected future surpluses, economic agents unload government debt to purchase private assets and goods, resulting in inflation. If the risk premium on government debt declines, government debt becomes more valuable, causing a deflationary effect. If the risk premium on government debt increases, government debt becomes less valuable, causing an inflationary effect.

There are multiple conclusions by Cochrane (2011Jan) on the debt/dollar crisis and Global recession, among which the following three:

(1) The flight to quality that magnified the recession was not from goods into money but from private-sector securities into government debt because of the risk premium on private-sector securities; monetary policy consisted of providing liquidity in private-sector markets suffering stress

(2) Increases in liquidity by open-market operations with short-term securities have no impact; quantitative easing can affect the timing but not the rate of inflation; and purchase of private debt can reverse part of the flight to quality

(3) The debt valuation equation has a similar role as the expectation shifting the Phillips curve such that a fiscal inflation can generate stagflation effects similar to those occurring from a loss of anchoring expectations.

This analysis suggests that there may be a point of saturation of demand for United States financial liabilities without an increase in interest rates on Treasury securities. A risk premium may develop on US debt. Such premium is not apparent currently because of distressed conditions in the world economy and international financial system. Risk premiums are observed in the spread of bonds of highly indebted countries in Europe relative to bonds of the government of Germany.

The issue of global imbalances centered on the possibility of a disorderly correction (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). Such a correction has not occurred historically but there is no argument proving that it could not occur. The need for a correction would originate in unsustainable large and growing United States current account deficits (CAD) and net international investment position (NIIP) or excess of financial liabilities of the US held by foreigners net relative to financial liabilities of foreigners held by US residents. The IMF estimated that the US could maintain a CAD of two to three percent of GDP without major problems (Rajan 2004). The threat of disorderly correction is summarized by Pelaez and Pelaez, The Global Recession Risk (2007), 15):

“It is possible that foreigners may be unwilling to increase their positions in US financial assets at prevailing interest rates. An exit out of the dollar could cause major devaluation of the dollar. The depreciation of the dollar would cause inflation in the US, leading to increases in American interest rates. There would be an increase in mortgage rates followed by deterioration of real estate values. The IMF has simulated that such an adjustment would cause a decline in the rate of growth of US GDP to 0.5 percent over several years. The decline of demand in the US by four percentage points over several years would result in a world recession because the weakness in Europe and Japan could not compensate for the collapse of American demand. The probability of occurrence of an abrupt adjustment is unknown. However, the adverse effects are quite high, at least hypothetically, to warrant concern.”

The United States could be moving toward a situation typical of heavily indebted countries, requiring fiscal adjustment and increases in productivity to become more competitive internationally. The CAD and NIIP of the United States are not observed in full deterioration because the economy is well below trend. There are two complications in the current environment relative to the concern with disorderly correction in the first half of the past decade. In the release of Jun 14, 2013, the Bureau of Economic Analysis (http://www.bea.gov/newsreleases/international/transactions/2013/pdf/trans113.pdf) informs of revisions of US data on US international transactions since 1999:

“The statistics of the U.S. international transactions accounts released today have been revised for the first quarter of 1999 to the fourth quarter of 2012 to incorporate newly available and revised source data, updated seasonal adjustments, changes in definitions and classifications, and improved estimating methodologies.”

The BEA introduced new concepts and methods (http://www.bea.gov/international/concepts_methods.htm) in comprehensive restructuring on Jun 18, 2014 (http://www.bea.gov/international/modern.htm):

“BEA introduced a new presentation of the International Transactions Accounts on June 18, 2014 and will introduce a new presentation of the International Investment Position on June 30, 2014. These new presentations reflect a comprehensive restructuring of the international accounts that enhances the quality and usefulness of the accounts for customers and bring the accounts into closer alignment with international guidelines.”

Table IIA2-3 provides data on the US fiscal and balance of payments imbalances incorporating all revisions and methods. In 2007, the federal deficit of the US was $161 billion corresponding to 1.1 percent of GDP while the Congressional Budget Office estimates the federal deficit in 2012 at $1087 billion or 6.8 percent of GDP. The estimate of the deficit for 2013 is $680 billion or 4.1 percent of GDP. The combined record federal deficits of the US from 2009 to 2012 are $5090 billion or 31.6 percent of the estimate of GDP for fiscal year 2012 implicit in the CBO (CBO 2013Sep11) estimate of debt/GDP. The deficits from 2009 to 2012 exceed one trillion dollars per year, adding to $5.094 trillion in four years, using the fiscal year deficit of $1087 billion for fiscal year 2012, which is the worst fiscal performance since World War II. Federal debt in 2007 was $5035 billion, slightly less than the combined deficits from 2009 to 2012 of $5094 billion. Federal debt in 2012 was 70.4 percent of GDP (CBO 2015Jan26) and 72.3 percent of GDP in 2013 (http://www.cbo.gov/). The US fiscal deficit was 2.8 percent of GDP in 2014 and federal debt reached 74.1 percent of GDP. The sum of the current account deficit of 2.2 percent of GDP and the fiscal deficit of 2.8 percent of GDP is 5.0 percent, in large part financed with foreign savings and artificially low interest rates of unconventional monetary policy. This situation may worsen in the future (CBO 2013Sep17):

“Between 2009 and 2012, the federal government recorded the largest budget deficits relative to the size of the economy since 1946, causing federal debt to soar. Federal debt held by the public is now about 73 percent of the economy’s annual output, or gross domestic product (GDP). That percentage is higher than at any point in U.S. history except a brief period around World War II, and it is twice the percentage at the end of 2007. If current laws generally remained in place, federal debt held by the public would decline slightly relative to GDP over the next several years, CBO projects. After that, however, growing deficits would ultimately push debt back above its current high level. CBO projects that federal debt held by the public would reach 100 percent of GDP in 2038, 25 years from now, even without accounting for the harmful effects that growing debt would have on the economy. Moreover, debt would be on an upward path relative to the size of the economy, a trend that could not be sustained indefinitely.

The gap between federal spending and revenues would widen steadily after 2015 under the assumptions of the extended baseline, CBO projects. By 2038, the deficit would be 6½ percent of GDP, larger than in any year between 1947 and 2008, and federal debt held by the public would reach 100 percent of GDP, more than in any year except 1945 and 1946. With such large deficits, federal debt would be growing faster than GDP, a path that would ultimately be unsustainable.

Incorporating the economic effects of the federal policies that underlie the extended baseline worsens the long-term budget outlook. The increase in debt relative to the size of the economy, combined with an increase in marginal tax rates (the rates that would apply to an additional dollar of income), would reduce output and raise interest rates relative to the benchmark economic projections that CBO used in producing the extended baseline. Those economic differences would lead to lower federal revenues and higher interest payments. With those effects included, debt under the extended baseline would rise to 108 percent of GDP in 2038.”

The most recent CBO long-term budget on Jun 16, 2015, projects US federal debt at 103 percent of GDP in 2040 (CBO (2015Jun15). The 2015 long-term budget outlook. Washington, DC, Congressional Budget Office, Jun 16).

Table VI-3B, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and %

 

2007

2008

2009

2010

2011

2012

2013

2014

Goods &
Services

-705

-709

-384

-495

-549

-538

-478

-508

Primary Income

101

146

124

178

221

212

225

238

Secondary Income

-114

-128

-124

-125

-133

-125

-123

-119

Current Account

-719

-691

-384

-442

-460

-450

-377

-390

NGDP

14478

14719

14419

14964

15518

16163

16768

17419

Current Account % GDP

-5.0

-4.7

-2.7

-3.0

-3.0

-2.8

-2.2

-2.2

NIIP

-1279

-3995

-2628

-2512

-4455

-4518

-5328

-7020

US Owned Assets Abroad

20705

19423

19426

21768

22209

22562

24159

24595

Foreign Owned Assets in US

21984

23418

22054

24280

26664

27080

29487

31615

NIIP % GDP

-8.8

-27.1

-18.2

-16.8

-28.7

-28.0

-31.8

-40.3

Exports
Goods,
Services and
Income

2569

2751

2286

2631

2988

3085

3179

3291

NIIP %
Exports
Goods,
Services and
Income

-50

-145

-115

-95

-149

-146

-168

-213

DIA MV

5858

3707

4945

5486

5215

5968

7117

7124

DIUS MV

4134

3091

3619

4099

4199

4661

5781

6229

Fiscal Balance

-161

-459

-1413

-1294

-1300

-1087

-680

-483

Fiscal Balance % GDP

-1.1

-3.1

-9.8

-8.7

-8.5

-6.8

-4.1

-2.8

Federal   Debt

5035

5803

7545

9019

10128

11281

11983

12779

Federal Debt % GDP

35.1

39.3

52.3

61.0

65.8

70.1

72.0

74.1

Federal Outlays

2729

2983

3518

3457

3603

3537

3455

3504

∆%

2.8

9.3

17.9

-1.7

4.2

-1.8

-2.3

1.4

% GDP

19.1

20.2

24.4

23.4

23.4

22.1

20.8

20.3

Federal Revenue

2568

2524

2105

2163

2304

2450

2775

3021

∆%

6.7

-1.7

-16.6

2.7

6.5

6.3

13.3

8.9

% GDP

17.9

17.1

14.6

14.6

15.0

15.3

16.7

17.5

Sources: 

Notes: NGDP: nominal GDP or in current dollars; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value. There are minor discrepancies in the decimal point of percentages of GDP between the balance of payments data and federal debt, outlays, revenue and deficits in which the original number of the CBO source is maintained. See Bureau of Economic Analysis, US International Economic Accounts: Concepts and Methods. 2014. Washington, DC: BEA, Department of Commerce, Jun 2014 http://www.bea.gov/international/concepts_methods.htm These discrepancies do not alter conclusions. Budget http://www.cbo.gov/ Balance of Payments and NIIP http://www.bea.gov/international/index.htm#bop Gross Domestic Product, Bureau of Economic Analysis (BEA) http://www.bea.gov/iTable/index_nipa.cfm

Table VI-3C provides quarterly estimates NSA of the external imbalance of the United States. The current account deficit seasonally adjusted decreases from 2.3 percent of GDP in IQ2014 to 2.1 percent in IIQ2014. The current account deficit increases to 2.2 percent of GDP in IIIQ2014 and stabilizes at 2.3 percent of GDP in IVQ2014. The deficit increases to 2.6 percent of GDP in IQ2015. The net international investment position increases from $5.4 trillion in IQ2014 to $5.5 trillion in IIQ2014, increasing at $6.2 trillion in IIIQ2014. The net international investment position increases to 7.0 trillion in IVQ2014 and decreases to $6.8 trillion in IQ2015.

Table VI-3C, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and % NSA

 

IQ2014

IIQ2014

IIIQ2014

IVQ2014

IQ2015

Goods &
Services

-100

-139

-143

-126

-106

Primary

Income

57

59

63

59

51

Secondary Income

-30

-20

-35

-34

-34

Current Account

-73

-99

-115

-102

-89

Current Account % GDP

-2.3

-2.1

-2.2

-2.3

-2.6

NIIP

-5483

-5519

-6205

-7020

-6794

US Owned Assets Abroad

24081

24987

24597

24595

25324

Foreign Owned Assets in US

-29564

-30506

-30802

-31615

-32118

DIA MV

7183

7481

7232

7124

7261

DIA MV Equity

6120

6413

6156

6052

6187

DIUS MV

5684

5935

6023

6229

6394

DIUS MV Equity

4371

4603

4639

4839

4981

Notes: NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value. See Bureau of Economic Analysis, US International Economic Accounts: Concepts and Methods. 2014. Washington, DC: BEA, Department of Commerce, Jun 2014 http://www.bea.gov/international/concepts_methods.htm

Chart VI-10 of the Board of Governors of the Federal Reserve System provides the overnight Fed funds rate on business days from Jul 1, 1954 at 1.13 percent through Jan 10, 1979, at 9.91 percent per year, to Jul 9, 2015, at 0.13 percent per year. US recessions are in shaded areas according to the reference dates of the NBER (http://www.nber.org/cycles.html). In the Fed effort to control the “Great Inflation” of the 1930s (see 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 Great Inflation; see Taylor 1993, 1997, 1998LB, 1999, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB and http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html), the fed funds rate increased from 8.34 percent on Jan 3, 1979 to a high in Chart VI-10 of 22.36 percent per year on Jul 22, 1981 with collateral adverse effects in the form of impaired savings and loans associations in the United States, emerging market debt and money-center banks (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 72-7; Pelaez 1986, 1987). Another episode in Chart VI-10 is the increase in the fed funds rate from 3.15 percent on Jan 3, 1994, to 6.56 percent on Dec 21, 1994, which also had collateral effects in impairing emerging market debt in Mexico and Argentina and bank balance sheets in a world bust of fixed income markets during pursuit by central banks of non-existing inflation (Pelaez and Pelaez, International Financial Architecture (2005), 113-5). Another interesting policy impulse is the reduction of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of equally non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85), followed by increments of 25 basis points from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006 in Chart VI-10. Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment 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 interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).

The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever-increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4). A final episode in Chart VI-10 is the reduction of the fed funds rate from 5.41 percent on Aug 9, 2007, to 2.97 percent on October 7, 2008, to 0.12 percent on Dec 5, 2008 and close to zero throughout a long period with the final point at 0.13 percent on Jul 9, 2015. Evidently, this behavior of policy would not have occurred had there been theory, measurements and forecasts to avoid these violent oscillations that are clearly detrimental to economic growth and prosperity without inflation. Current policy consists of forecast mandate of maintaining policy accommodation until the forecast of the rate of unemployment reaches 6.5 percent and the rate of personal consumption expenditures excluding food and energy reaches 2.5 percent (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm). The FOMC dropped the numbers but affirmed guidance (http://www.federalreserve.gov/newsevents/press/monetary/20140319a.htm): “With the unemployment rate nearing 6-1/2 percent, the Committee has updated its forward guidance. The change in the Committee's guidance does not indicate any change in the Committee's policy intentions as set forth in its recent statements.” It is a forecast mandate because of the lags in effect of monetary policy impulses on income and prices (Romer and Romer 2004). The intention is to reduce unemployment close to the “natural rate” (Friedman 1968, Phelps 1968) of around 5 percent and inflation at or below 2.0 percent. If forecasts were reasonably accurate, there would not be policy errors. A commonly analyzed risk of zero interest rates is the occurrence of unintended inflation that could precipitate an increase in interest rates similar to the Himalayan rise of the fed funds rate from 9.91 percent on Jan 10, 1979, at the beginning in Chart VI-10, to 22.36 percent on Jul 22, 1981. There is a less commonly analyzed risk of the development of a risk premium on Treasury securities because of the unsustainable Treasury deficit/debt of the United States (http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html

and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2014/02/theory-and-reality-of-cyclical-slow.html and earlier (http://cmpassocregulationblog.blogspot.com/2013/02/united-states-unsustainable-fiscal.html). There is not a fiscal cliff or debt limit issue ahead but rather free fall into a fiscal abyss. The combination of the fiscal abyss with zero interest rates could trigger the risk premium on Treasury debt or Himalayan hike in interest rate.

clip_image038

Chart VI-10, US, Fed Funds Rate, Business Days, Jul 1, 1954 t0 Jul 9, 2015, Percent per Year

Source: Board of Governors of the Federal Reserve System

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

There is a false impression of the existence of a monetary policy “science,” measurements and forecasting with which to steer the economy into “prosperity without inflation.” Market participants are remembering the Great Bond Crash of 1994 shown in Table VI-7G when monetary policy pursued nonexistent inflation, causing trillions of dollars of losses in fixed income worldwide while increasing the fed funds rate from 3 percent in Jan 1994 to 6 percent in Dec. The exercise in Table VI-7G shows a drop of the price of the 30-year bond by 18.1 percent and of the 10-year bond by 14.1 percent. CPI inflation remained almost the same and there is no valid counterfactual that inflation would have been higher without monetary policy tightening because of the long lag in effect of monetary policy on inflation (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). The pursuit of nonexistent deflation during the past ten years has resulted in the largest monetary policy accommodation in history that created the 2007 financial market crash and global recession and is currently preventing smoother recovery while creating another financial crash in the future. The issue is not whether there should be a central bank and monetary policy but rather whether policy accommodation in doses from zero interest rates to trillions of dollars in the fed balance sheet endangers economic stability.

Table VI-7G, Fed Funds Rates, Thirty and Ten Year Treasury Yields and Prices, 30-Year Mortgage Rates and 12-month CPI Inflation 1994

1994

FF

30Y

30P

10Y

10P

MOR

CPI

Jan

3.00

6.29

100

5.75

100

7.06

2.52

Feb

3.25

6.49

97.37

5.97

98.36

7.15

2.51

Mar

3.50

6.91

92.19

6.48

94.69

7.68

2.51

Apr

3.75

7.27

88.10

6.97

91.32

8.32

2.36

May

4.25

7.41

86.59

7.18

88.93

8.60

2.29

Jun

4.25

7.40

86.69

7.10

90.45

8.40

2.49

Jul

4.25

7.58

84.81

7.30

89.14

8.61

2.77

Aug

4.75

7.49

85.74

7.24

89.53

8.51

2.69

Sep

4.75

7.71

83.49

7.46

88.10

8.64

2.96

Oct

4.75

7.94

81.23

7.74

86.33

8.93

2.61

Nov

5.50

8.08

79.90

7.96

84.96

9.17

2.67

Dec

6.00

7.87

81.91

7.81

85.89

9.20

2.67

Notes: FF: fed funds rate; 30Y: yield of 30-year Treasury; 30P: price of 30-year Treasury assuming coupon equal to 6.29 percent and maturity in exactly 30 years; 10Y: yield of 10-year Treasury; 10P: price of 10-year Treasury assuming coupon equal to 5.75 percent and maturity in exactly 10 years; MOR: 30-year mortgage; CPI: percent change of CPI in 12 months

Sources: yields and mortgage rates http://www.federalreserve.gov/releases/h15/data.htm CPI ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.t

Chart VI-14 provides the overnight fed funds rate, the yield of the 10-year Treasury constant maturity bond, the yield of the 30-year constant maturity bond and the conventional mortgage rate from Jan 1991 to Dec 1996. In Jan 1991, the fed funds rate was 6.91 percent, the 10-year Treasury yield 8.09 percent, the 30-year Treasury yield 8.27 percent and the conventional mortgage rate 9.64 percent. Before monetary policy tightening in Oct 1993, the rates and yields were 2.99 percent for the fed funds, 5.33 percent for the 10-year Treasury, 5.94 for the 30-year Treasury and 6.83 percent for the conventional mortgage rate. After tightening in Nov 1994, the rates and yields were 5.29 percent for the fed funds rate, 7.96 percent for the 10-year Treasury, 8.08 percent for the 30-year Treasury and 9.17 percent for the conventional mortgage rate.

ChVI-14DDPChart

Chart VI-14, US, Overnight Fed Funds Rate, 10-Year Treasury Constant Maturity, 30-Year Treasury Constant Maturity and Conventional Mortgage Rate, Monthly, Jan 1991 to Dec 1996

Source: Board of Governors of the Federal Reserve System

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

Chart VI-15 of the Bureau of Labor Statistics provides the all items consumer price index from Jan 1991 to Dec 1996. There does not appear acceleration of consumer prices requiring aggressive tightening.

clip_image040

Chart VI-15, US, Consumer Price Index All Items, Jan 1991 to Dec 1996

Source: Bureau of Labor Statistics

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

Chart IV-16 of the Bureau of Labor Statistics provides 12-month percentage changes of the all items consumer price index from Jan 1991 to Dec 1996. Inflation collapsed during the recession from Jul 1990 (III) and Mar 1991 (I) and the end of the Kuwait War on Feb 25, 1991 that stabilized world oil markets. CPI inflation remained almost the same and there is no valid counterfactual that inflation would have been higher without monetary policy tightening because of the long lag in effect of monetary policy on inflation (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). Policy tightening had adverse collateral effects in the form of emerging market crises in Mexico and Argentina and fixed income markets worldwide.

clip_image041

Chart VI-16, US, Consumer Price Index All Items, Twelve-Month Percentage Change, Jan 1991 to Dec 1996

Source: Bureau of Labor Statistics

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

  The Congressional Budget Office (CBO 2014BEOFeb4) estimates potential GDP, potential labor force and potential labor productivity provided in Table IB-3. The CBO estimates average rate of growth of potential GDP from 1950 to 2014 at 3.3 percent per year. The projected path is significantly lower at 2.1 percent per year from 2015 to 2025. The legacy of the economic cycle expansion from IIIQ2009 to IQ2015 at 2.2 percent on average is in contrast with 4.8 percent on average in the expansion from IQ1983 to IIIQ1988 (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html). Subpar economic growth may perpetuate unemployment and underemployment estimated at 25.0 million or 15.1 percent of the effective labor force in Jun 2015 (http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html) with much lower hiring than in the period before the current cycle (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.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

4.0

1.6

2.4

1974-1981

3.3

2.5

0.8

1982-1990

3.2

1.6

1.6

1991-2001

3.2

1.3

1.9

2002-2007

2.8

0.9

1.9

2008-2014

1.4

0.5

0.9

Total 1950-2014

3.3

1.5

1.8

Projected Average Annual ∆%

     

2015-2019

2.1

0.5

1.6

2019-2025

2.2

0.6

1.6

2015-2025

2.1

0.5

1.6

*Ratio of potential GDP to potential labor force

Source: CBO (2014BEOFeb4), CBO, Key assumptions in projecting potential GDP—February 2014 baseline. Washington, DC, Congressional Budget Office, Feb 4, 2014. CBO, The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015.

Chart IB-1A of the Congressional Budget Office provides historical and projected potential and actual US GDP. The gap between actual and potential output closes by 2017. Potential output expands at a lower rate than historically. Growth is even weaker relative to trend.

clip_image042

Chart IB-1A, Congressional Budget Office, Estimate of Potential GDP and Gap

Source: Congressional Budget Office

https://www.cbo.gov/publication/49890

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 2.2 percent on average from IIIQ2009 to IQ2015 during the current economic expansion in contrast with 4.8 percent on average in the cyclical expansion from IQ1983 to IIIQ1988 (http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html) cannot be explained by the contraction of 4.2 percent of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 25.0 million or 15.1 percent of the labor force as estimated for Jun 2015 (http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html). There is no exit from unemployment/underemployment and stagnating real wages because of the collapse of hiring (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html). The US economy and labor markets collapsed without recovery. Abrupt collapse of economic conditions can be explained only with cyclic factors (Lazear and Spletzer 2012Jul22) and not by secular stagnation (Hansen 1938, 1939, 1941 with early dissent by Simons 1942).

clip_image044

Chart IB-1, US, Congressional Budget Office, Actual and Projections of Potential GDP, 2000-2024, Trillions of Dollars

Source: Congressional Budget Office, CBO (2013BEOFeb5). The last year in common in both projections is 2017. The revision lowers potential output in 2017 by 7.3 percent relative to the projection in 2007.

Chart IB-2 provides differences in the projections of potential output by the CBO in 2007 and more recently on Feb 4, 2014, which the CBO explains in CBO (2014Feb28).

clip_image046

Chart IB-2, Congressional Budget Office, Revisions of Potential GDP

Source: Congressional Budget Office, 2014Feb 28. Revisions to CBO’s Projection of Potential Output since 2007. Washington, DC, CBO, Feb 28, 2014.

Chart IB-3 provides actual and projected potential GDP from 2000 to 2024. The gap between actual and potential GDP disappears at the end of 2017 (CBO2014Feb4). GDP increases in the projection at 2.5 percent per year.

clip_image048

Chart IB-3, Congressional Budget Office, GDP and Potential GDP

Source: CBO (2013BEOFeb5), CBO, Key assumptions in projecting potential GDP—February 2014 baseline. Washington, DC, Congressional Budget Office, Feb 4, 2014.

Chart IIA2-3 of the Bureau of Economic Analysis of the Department of Commerce shows on the lower negative panel the sharp increase in the deficit in goods and the deficits in goods and services from 1960 to 2012. The upper panel shows the increase in the surplus in services that was insufficient to contain the increase of the deficit in goods and services. The adjustment during the global recession has been in the form of contraction of economic activity that reduced demand for goods.

clip_image049

Chart IIA2-3, US, Balance of Goods, Balance on Services and Balance on Goods and Services, 1960-2013, Millions of Dollars

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

Chart IIA2-4 of the Bureau of Economic Analysis shows exports and imports of goods and services from 1960 to 2012. Exports of goods and services in the upper positive panel have been quite dynamic but have not compensated for the sharp increase in imports of goods. The US economy apparently has become less competitive in goods than in services.

clip_image050

Chart IIA2-4, US, Exports and Imports of Goods and Services, 1960-2013, Millions of Dollars

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

Chart IIA2-5 of the Bureau of Economic Analysis shows the US balance on current account from 1960 to 2012. The sharp devaluation of the dollar resulting from unconventional monetary policy of zero interest rates and elimination of auctions of 30-year Treasury bonds did not adjust the US balance of payments. Adjustment only occurred after the contraction of economic activity during the global recession.

clip_image051

Chart IIA2-5, US, Balance on Current Account, 1960-2013, Millions of Dollars

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

Chart IIA2-6 of the Bureau of Economic Analysis provides real GDP in the US from 1960 to 2014. The contraction of economic activity during the global recession was a major factor in the reduction of the current account deficit as percent of GDP.

clip_image052

Chart IIA2-6, US, Real GDP, 1960-2014, Billions of Chained 2009 Dollars

Source: Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

Chart IIA-7 provides the US current account deficit on a quarterly basis from 1980 to IQ2013. The deficit is at a lower level because of growth below potential not only in the US but worldwide. The combination of high government debt and deficit with external imbalance restricts potential prosperity in the US.

clip_image053

Chart IIA-7, US, Balance on Current Account, Quarterly, 1980-2013

Source: Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015.

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