Sunday, June 10, 2018

Twenty-One Million Unemployed or Underemployed in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Job Creation, Cyclically Stagnating Real Wages, Recovery without Hiring, Labor Underutilization, Ten Million Fewer Full-Time Jobs, Youth and Middle-Age Unemployment, United States International Trade, World Cyclical Slow Growth and Global Recession Risk: Part II

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Twenty-One Million Unemployed or Underemployed in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Job Creation, Cyclically Stagnating Real Wages, Recovery without Hiring, Labor Underutilization, Ten Million Fewer Full-Time Jobs, Youth and Middle-Age Unemployment, United States International Trade, World Cyclical Slow Growth and Global Recession Risk

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018

I Twenty-One Million Unemployed or Underemployed

IA1 Summary of the Employment Situation

IA2 Number of People in Job Stress

IA3 Long-term and Cyclical Comparison of Employment

IA4 Job Creation

IB Stagnating Real Wages

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

IIB United States International Trade

III World Financial Turbulence

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

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 number 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 II and earlier https://cmpassocregulationblog.blogspot.com/2018/05/recovery-without-hiring-ten-million.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:

and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/exchange-rate-conflicts-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/imf-view-squeeze-of-economic-activity.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html)

The Bureau of Labor Statistics (BLS) revised on Mar 17, 2016 “With the release of January 2016 data on March 17, job openings, hires, and separations data have been revised from December 2000 forward to incorporate annual updates to the Current Employment Statistics employment estimates and the Job Openings and Labor Turnover Survey (JOLTS) seasonal adjustment factors. In addition, all data series are now available on a seasonally adjusted basis. Tables showing the revisions from 2000 through 2015 can be found using this link: http://www.bls.gov/jlt/revisiontables.htm.” (https://www.bls.gov/jlt/). The Bureau of Labor Statistics (BLS) revised on Mar 16, 2017: “With the release of January 2017 data on March 16, job openings, hires, and separations data have been revised to incorporate annual updates to the Current Employment Statistics employment estimates and the Job Openings and Labor Turnover Survey (JOLTS) seasonal adjustment factors” (https://www.bls.gov/jlt/revisiontables.htm) (https://www.bls.gov/jlt/). The Bureau of Labor Statistics (BLS) revised on Mar 16, 2018 “With the release of January 2018 data on March 16, job openings, hires, and separations data have been revised to incorporate annual updates to the Current Employment Statistics employment estimates and the Job Openings and Labor Turnover Survey (JOLTS) seasonal adjustment factors. Tables showing the revisions from 2013 through 2017 can be found using this link: https://www.bls.gov/jlt/revisiontables.htm (https://www.bls.gov/jlt/).“ Hiring in the nonfarm sector (HNF) has increased from 63.491 million in 2006 to 65.259 million in 2017 or by 1.768 million while hiring in the private sector (HP) has increased from 59.206 million in 2006 to 61.122 million in 2017 or by 1.916 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.1 in 2005 to 44.5 in 2017 and in the private sector (RHP) from 52.8 in 2005 to 49.2 in 2017. 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 255.079 million in 2017 or by 26.264 million. Hiring has not recovered prerecession levels while needs of hiring multiplied because of growth of population by more than 26 million. Private hiring of 59.206 million in 2006 was equivalent to 25.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, increasing to 61.122 million in 2017 or 24.0 percent of the civilian noninstitutional population of 255.079 million in 2017. The percentage of hiring in civilian noninstitutional population of 25.9 percent in 2006 would correspond to 66.065 million of hiring in 2017 (0.259x255.079), which would be 4.943 million higher than actual 61.122 million in 2017. 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 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.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 dividing 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 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/twenty-two-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. 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 of manufacturing at average 3.2 percent per year from Apr 1919 to Apr 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 154.7937 in Apr 2018. The actual index NSA in Apr 2018 is 104.3625, which is 32.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Apr 2018. Using trend growth of 2.0 percent per year, the index would increase to 135.5768 in Apr 2018. The output of manufacturing at 104.3625 in Apr 2018 is 23.0 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

62,727

47.5

58,616

52.8

2002

58,416

44.7

54,592

50.0

2003

56,919

43.7

53,529

49.2

2004

60,236

45.7

56,567

51.3

2005

63,089

47.1

59,298

52.8

2006

63,491

46.5

59,206

51.7

2007

62,239

45.1

57,816

49.9

2008

54,764

39.9

51,260

44.7

2009

46,190

35.2

42,882

39.4

2010

48,659

37.3

44,831

41.6

2011

50,253

38.1

47,166

42.9

2012

52,332

39.0

48,898

43.6

2013

54,297

39.8

50,866

44.4

2014

58,629

42.2

54,985

47.0

2015

62,027

43.7

57,899

48.3

2016

63,240

43.8

58,936

48.3

2017

65,259

44.5

61,122

49.2

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 255.079 million in 2017 or by 26.264 million. Hiring has not recovered precession levels while needs of hiring multiplied because of growth of population by more than 24 million.

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2017

Source: US Bureau of Labor Statistics

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

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

Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2017

Source: US Bureau of Labor Statistics

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

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table I-2. There were much milder declines in 2002 of 6.9 percent and 2.6 percent in 2003 followed by strong rebounds of 5.8 percent in 2004 and 4.7 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.0 in 2007, 12.0 in 2008 and 15.7 percent in 2009. On a yearly basis, nonfarm hiring grew 5.3 percent in 2010 relative to 2009, 3.3 percent in 2011, 4.1 percent in 2012 and 3.8 percent in 2013. Nonfarm hiring grew 8.0 percent in 2014 and increased 5.8 percent in 2015. Nonfarm hiring grew 2.0 percent in 2016, increasing 3.2 percent in 2017. The relatively large length of 34 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, 2002-2017

Year

Annual ∆%

2002

-6.9

2003

-2.6

2004

5.8

2005

4.7

2006

0.6

2007

-2.0

2008

-12.0

2009

-15.7

2010

5.3

2011

3.3

2012

4.1

2013

3.8

2014

8.0

2015

5.8

2016

2.0

2017

3.2

Source: US Bureau of Labor Statistics

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

Total private hiring (HP) annual data are in Chart I-5. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2017.

Chart I-5, US, Total Private Hiring, Annual, 2001-2017

Source: Bureau of Labor Statistics

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

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

Chart I-5A, US, Rate Total Private Hiring, Annual, 2001-2017

Source: Bureau of Labor Statistics

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

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are in Table I-3 for the month of Apr in the years from 2001 to 2018. Hiring numbers are in thousands. There is recovery in HNF from 4228 thousand in Apr 2009 to 4510 thousand in Apr 2010, 4641 thousand in Apr 2011, 4697 thousand in Apr 2012, 4948 thousand in Apr 2013, 5232 thousand in Apr 2014, 5554 thousand in Apr 2015, 5647 thousand in Apr 2016, 5633 thousand in Apr 2017 and 5990 thousand in Apr 2018 for cumulative gain of 41.7 percent at the average yearly rate of 3.9 percent. HP rose from 3917 thousand in Apr 2009 to 4243 thousand in Apr 2010, 4439 thousand in Apr 2011, 4479 thousand in Apr 2012, 4713 thousand in Apr 2013, 4992 thousand in Apr 2014, 5272 thousand in Apr 2015, 5361 thousand in Apr 2016, 5372 thousand in Apr 2017 and 5711 thousand in Apr 2018 for cumulative gain of 45.8 percent at the average yearly rate of 4.3 percent. HNF has increased from 5612 thousand in Apr 2006 to 5990 thousand in Apr 2018 or by 6.7 percent. HP has increased from 5352 thousand in Apr 2006 to 5711 thousand in Apr 2018 or by 6.7 percent. The civilian noninstitutional population of the US, or those in condition of working, rose from 228.199 million in Apr 2006 to 257.272 million in Apr 2018, by 29.073 million or 12.7 percent. There is often ignored ugly fact that hiring increased by around 6.7 percent while population available for working increased around 12.7 percent. Private hiring of 59.206 million in 2006 was equivalent to 25.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, increasing to 61.122 million in 2017 or 24.0 percent of the civilian noninstitutional population of 255.079 million in 2017. The percentage of hiring in civilian noninstitutional population of 25.9 percent in 2006 would correspond to 66.065 million of hiring in 2016 (0.259x255.079), which would be 4.943 million higher than actual 61.122 million in 2017. 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. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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 Apr

5946

4.5

5696

5.1

2002 Apr

5480

4.2

5227

4.8

2003 Apr

5221

4.0

5001

4.6

2004 Apr

5652

4.3

5419

4.9

2005 Apr

5821

4.4

5591

5.0

2006 Apr

5612

4.1

5352

4.7

2007 Apr

5647

4.1

5356

4.7

2008 Apr

5351

3.9

5118

4.4

2009 Apr

4228

3.2

3917

3.6

2010 Apr

4510

3.5

4243

4.0

2011 Apr

4641

3.5

4439

4.1

2012 Apr

4697

3.5

4479

4.0

2013 Apr

4948

3.6

4713

4.1

2014 Apr

5232

3.8

4992

4.3

2015 Apr

5554

3.9

5272

4.4

2016 Apr

5647

3.9

5361

4.4

2017 Apr

5633

3.9

5372

4.4

2018 Apr

5990

4.0

5711

4.5

Source: Bureau of Labor Statistics

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

Chart I-6 provides total nonfarm hiring monthly from 2001 to 2018. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4815 in May 2010 until it surpassed it with 5006 in Jun 2011 but declined to 3097 in Dec 2012. Nonfarm hiring fell to 2997 in Dec 2011 from 3814 in Nov 2011 and to revised 3627 in Feb 2012, increasing to 4182 in Mar 2012, 3097 in Dec 2012 and 4277 in Jan 2013 and declining to 3683 in Feb 2013. Nonfarm hires not seasonally adjusted increased to 4221 in Nov 2013 and 3267 in Dec 2013. Nonfarm hires reached 3738 in Dec 2014, 4067 in Dec 2015 and 3898 in Dec 2016. Nonfarm hires reached 4111 in Dec 2017. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Oct 2011 was 4239 thousand, increasing to revised 4419 thousand in Feb 2012, or 4.2 percent, moving to 4360 in Dec 2012 for cumulative increase of 3.0 percent from 4234 in Dec 2011 and 4542 in Dec 2013 for increase of 4.2 percent relative to 4360 in Dec 2012. The number of hires not seasonally adjusted was 5006 in Jun 2011, falling to 2997 in Dec 2011 but increasing to 4140 in Jan 2012 and declining to 3097 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 40.1 percent from 5006 in Jun 2011 to 2997 in Dec 2011 and fell 39.9 percent from 5151 in Jun 2012 to 3097 in Dec 2012 in a yearly-repeated seasonal pattern. The number of nonfarm hires not seasonally adjusted fell from 5077 in Jun 2013 to 3267 in Dec 2013, or decline of 35.7 percent, showing strong seasonality. The number of nonfarm hires not seasonally adjusted fell from 5509 in Jun 2014 to 3738 in Dec 2014 or 32.4 percent. The level of nonfarm hires fell from 5856 in Jun 2015 to 4067 in Dec 2015 or 30.5 percent. The level of nonfarm hires not seasonally adjusted fell from 6008 in Jun 2016 to 3898 in Dec 2016 or 35.1 percent. The level of nonfarm hires not seasonally adjusted fell from 6272 in Jun 2017 to 4111 in Dec 2017 or 34.5 percent.

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2018 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 stabilizing to 3.3 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 3.8 in Jun 2011 to 2.2 in Dec 2011, climbing to 3.8 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 2.6 in Dec 2014. The NSA rate fell from 4.1 in Jun 2015 to 2.8 in Dec 2015. The NSA rate fell from 4.1 in Jun 2016 to 2.7 in Dec 2016. The NSA rate fell from 4.1 in Jun 2016 to 2.7 in Dec 2016. The NSA rate fell from 4.3 in Jun 2017 to 2.8 in Dec 2017. 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 3.8 in Apr 2018 and at 4.0 NSA.

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2018

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 4043 thousand in Sep 2011 to 3933 in Dec 2011 or by 2.7 percent, decreasing to 4014 in Jan 2012 or decline by 0.7 percent relative to the level in Sep 2011. Private hiring fell to 3959 in Sep 2012 or lower by 2.1 percent relative to Sep 2011, moving to 4063 in Dec 2012 for increase of 1.2 percent relative to 4014 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4626 in Jun 2011 to 2817 in Dec 2011 or by 39.1 percent, reaching 3885 in Jan 2012 or decline of 16.0 percent relative to Jun 2011 and moving to 2918 in Dec 2012 or 38.5 percent lower relative to 4745 in Jun 2012. Hires not seasonally adjusted fell from 4727 in Jun 2013 to 3103 in Dec 2013, or 34.4 percent. The level of private hiring NSA fell from 5102 in Jun 2014 to 3539 in Dec 2014 or 30.6 percent. The level of private hiring fell from 5437 in Jun 2015 to 3841 in Dec 2015 or 29.4 percent. The level of private hiring not seasonally adjusted fell from 5570 in Jun 2016 to 3697 in Dec 2016 or 33.6 percent. The level of private hiring not seasonally adjusted fell from 5841 in Jun 2017 to 3899 in Dec 2017 or 33.2 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 5614 in Jun 2006 to 3579 in Dec 2006 or by 36.2 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. Hiring in the nonfarm sector (HNF) has increased from 63.491 million in 2006 to 65.259 million in 2017 or by 1.768 million while hiring in the private sector (HP) has increased from 59.206 million in 2006 to 61.122 million in 2017 or by 1.916 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.1 in 2005 to 44.5 in 2017 and in the private sector (RHP) from 52.8 in 2005 to 49.2 in 2017. 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 255.079 million in 2017 or by 26.264 million. Hiring has not recovered prerecession levels while needs of hiring multiplied because of growth of population by more than 26 million. Private hiring of 59.206 million in 2006 was equivalent to 25.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, increasing to 61.122 million in 2017 or 24.0 percent of the civilian noninstitutional population of 255.079 million in 2016. The percentage of hiring in civilian noninstitutional population of 25.9 percent in 2006 would correspond to 66.065 million of hiring in 2017 (0.259x255.079), which would be 4.943 million higher than actual 61.122 million in 2017.

Chart I-8, US, Total Private Hiring Month SA 2001-2018

Source: Bureau of Labor Statistics

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

Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data did not rise significantly above the peak in 2010. The rate seasonally adjusted fell from 3.7 in Sep 2011 to 3.5 in Dec 2011 and reached 3.6 in Dec 2012 and 3.7 in Dec 2013. The rate not seasonally adjusted (NSA) fell from 3.7 in Sep 2011 to 2.5 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 3.2 in Dec 2015 and 3.0 in Dec

2016. The rate NSA reached 3.1 in Dec 2017. The rate NSA stood at 4.5 in Apr 2018.

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2018

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 Mar from 2001 to 2018. The final column provides annual TNF LD for the years from 2001 to 2017. Nonfarm job openings (TNF JOB) increased from 5070 in Apr 2007 to 7195 in Apr 2018 or by 41.9 percent while the rate increased from 3.6 to 4.6. This was mediocre performance because the civilian noninstitutional population of the US, or those in condition of working rose from 231.253 million in Apr 2007 to 257.272 million in Apr 2018, by 26.019 million or 11.3 percent. Nonfarm layoffs and discharges (TNF LD) increased from 1648 in Apr 2006 to 2351 in Apr 2009 or 42.7 percent. The annual data show layoffs and discharges rising from 20.9 million in 2006 to 26.6 million in 2009 or by 27.3 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

Apr 2001

5213

3.8

1838

24271

Apr 2002

3781

2.8

1791

22719

Apr 2003

3641

2.7

1884

23420

Apr 2004

3922

2.9

1787

22584

Apr 2005

4538

3.3

1724

22151

Apr 2006

4975

3.5

1648

20856

Apr 2007

5070

3.6

1735

21997

Apr 2008

4317

3.0

1706

23969

Apr 2009

2533

1.9

2351

26557

Apr 2010

3408

2.6

1521

21703

Apr 2011

3486

2.6

1516

20756

Apr 2012

3893

2.8

1702

20942

Apr 2013

4207

3.0

1604

19889

Apr 2014

4851

3.4

1596

20402

Apr 2015

5982

4.1

1675

20963

Apr 2016

6286

4.2

1601

20152

Apr 2017

6511

4.3

1530

20676

Apr 2018

7195

4.6

1580

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 3220 seasonally adjusted in Apr 2010 with 3570 seasonally adjusted in Dec 2012, which is higher by 10.9 percent relative to Apr 2010 but higher by 1.4 percent relative to 3521 in Nov 2012 and lower by 6.8 percent than 3831 in Mar 2012. Nonfarm job openings increased from 3570 in Dec 2012 to 3783 in Dec 2013 or by 6.0 percent and to 4820 in Dec 2014 or 27.4 percent relative to Dec 2013. The high of job openings not seasonally adjusted was 3408 in Apr 2010 that was surpassed by 3647 in Jul 2011, increasing to 3906 in Oct 2012 but declining to 3213 in Dec 2012 and increasing to 3407 in Dec 2013. The level of job opening NSA increased to 4972 in Dec 2015. The level of job opening NSA increased to 5044 in Dec 2016, reaching 5222 in Dec 2017. The level of job openings not seasonally adjusted fell to 3213 in Dec 2012 or by 17.5 percent relative to 3893 in Apr 2012. There is here again the strong seasonality of year-end labor data. Job openings fell from 4207 in Apr 2013 to 3407 in Dec 2013 and from 4851 in Apr 2014 to 4413 in Dec 2014, showing strong seasonal effects. The level of nonfarm job openings decreased from 5982 in Apr 2015 to 4972 in Dec 2015 or by 16.9 percent. The level of nonfarm job openings decreased from 6286 in Apr 2016 to 5044 in Dec 2016 or by 19.8 percent. The level of nonfarm job openings decreased from 6511 in Apr 2017 to 5222 in Dec 2017 or by 19.8 percent. Nonfarm job openings (TNF JOB) increased from 4583 in Mar 2007 to 6469 in Mar 2018 or by 41.2 percent while the rate increased from 3.2 to 4.2. This was mediocre performance because the civilian noninstitutional population of the US, or those in condition of working rose from 231.253 million in Apr 2007 to 257.272 million in Apr 2018, by 26.019 million or 11.3 percent. Nonfarm layoffs and discharges (TNF LD) increased from 1648 in Apr 2006 to 2351 in Apr 2009 or 42.7 percent. 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 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.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 dividing 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 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/twenty-two-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. 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 of manufacturing at average 3.2 percent per year from Apr 1919 to Apr 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 154.7937 in Apr 2018. The actual index NSA in Apr 2018 is 104.3625, which is 32.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Apr 2018. Using trend growth of 2.0 percent per year, the index would increase to 135.5768 in Apr 2018. The output of manufacturing at 104.3625 in Apr 2018 is 23.0 percent below trend under this alternative calculation.

Chart I-10, US Job Openings, Thousands NSA, 2001-2017

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 2.5 in Dec 2011, 2.6 in Dec 2012, 2.7 in Dec 2013 and 3.3 in Dec 2014. The rate seasonally adjusted stood at 3.6 in Dec 2015 and 3.6 in Dec 2016. The rate seasonally adjusted reached 3.7 in Dec 2017. The rate SA stood at 4.2 in Mar 2018. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 3.0 in Apr 2013, easing to 2.4 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 3.3 in Dec 2015. The rate of job opening NSA stood at 3.3 in Dec 2016, reaching 3.4 in Dec 2017. The rate of job openings NSA was 4.6 in Apr 2018.

Chart I-11, US, Rate of Job Openings, NSA, 2001-2017

Source: US Bureau of Labor Statistics

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

Total separations are in Chart I-12. Separations are lower in 2012-18 than before the global recession but hiring has not recovered.

Chart I-12, US, Total Nonfarm Separations, Month Thousands SA, 2001-2018

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.

Chart I-13, US, Total Separations, Annual, Thousands, 2001-2017

Source: US Bureau of Labor Statistics

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

Table I-5 provides total nonfarm total separations from 2001 to 2017. Separations fell from 61.3 million in 2006 to 47.6 million in 2010 or by 13.6 million and 48.2 million in 2011 or by 13.1 million. Total separations increased from 48.2 million in 2011 to 51.9 million in 2013 or by 3.7 million and to 55.6 million in 2014 or by 7.4 million relative to 2011. Total separations increased to 59.3 million in 2015 or by 11.1 million relative to 2011. Total separations increased to 60.896 million in 2016 or 12.7 million relative to 2011. Total separations increased to 63.031 million in 2017 or 14.8 million relative to 2011.

Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2017

Year

Annual

2001

64560

2002

58942

2003

56961

2004

58224

2005

60633

2006

61284

2007

60984

2008

58209

2009

51358

2010

47649

2011

48214

2012

50131

2013

51937

2014

55596

2015

59296

2016

60896

2017

63031

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. 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. Growth rates have been unusually low in the expansion of the current economic cycle.

Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly Thousands SA, 2001-2018

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 2014-2015 followed by decline in 2016 and increase in 2017.

Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2017

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 20.856 million in 2006 to 26.557 million in 2009 or 27.3 percent. Layoff and discharges fell to 19.889 million in 2013 or 25.1 percent relative to 2009 and increased to 20.402 million in 2014 or 2.6 percent relative to 2013. Layoffs and discharges increased to 20.963 million in 2015 or 2.7 percent relative to 2014. Layoffs and discharges fell to 20.152 in 2016 or 3.9 percent relative to 2015. Layoffs and discharges increased to 20.676 million in 2017 or 2.6 percent relative to 2016.

Table I-6, US, Total Nonfarm Layoffs and Discharges, Thousands, 2001-2017

Year

Annual

2001

24271

2002

22719

2003

23420

2004

22584

2005

22151

2006

20856

2007

21997

2008

23969

2009

26557

2010

21703

2011

20756

2012

20942

2013

19889

2014

20402

2015

20963

2016

20152

2017

20676

Source: US 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 moved from 8.2 percent in 2006 to 7.3 percent in May 2018.

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

U1

U2

U3

U4

U5

U6

2018

May

1.4

1.5

3.6

3.8

4.4

7.3

Apr

1.5

1.7

3.7

3.9

4.5

7.4

Mar

1.5

2.1

4.1

4.4

5.0

8.1

Feb

1.6

2.3

4.4

4.6

5.3

8.6

Jan

1.5

2.4

4.5

4.8

5.5

8.9

2017

Dec

1.4

2.1

3.9

4.2

4.9

8.0

Nov

1.5

1.8

3.9

4.2

4.8

7.7

Oct

1.5

1.8

3.9

4.2

4.8

7.6

Sep

1.6

1.9

4.1

4.3

5.0

8.0

Aug

1.7

2.2

4.5

4.8

5.4

8.6

Jul

1.6

2.2

4.6

4.9

5.5

8.9

Jun

1.5

2.1

4.5

4.8

5.4

8.9

May

1.8

1.9

4.1

4.3

5.0

8.1

Apr

1.8

2.1

4.1

4.4

5.0

8.1

Mar

1.9

2.4

4.6

4.8

5.5

8.9

Feb

1.9

2.6

4.9

5.3

6.0

9.5

Jan

2.0

2.7

5.1

5.5

6.2

10.1

2016

Dec

1.9

2.3

4.5

4.8

5.5

9.1

Nov

1.8

2.1

4.4

4.8

5.6

9.0

Oct

1.9

2.1

4.7

5.0

5.7

9.2

Sep

1.9

2.2

4.8

5.1

5.9

9.3

Aug

1.8

2.4

5.0

5.3

6.0

9.7

Jul

1.9

2.4

5.1

5.5

6.3

10.1

Jun

1.9

2.3

5.1

5.4

6.1

9.9

May

2.0

2.1

4.5

4.9

5.6

9.4

Apr

2.2

2.3

4.7

5.0

5.7

9.3

Mar

2.3

2.6

5.1

5.5

6.1

9.9

Feb

2.2

2.7

5.2

5.6

6.3

10.1

Jan

2.1

2.7

5.3

5.7

6.5

10.5

2015

Dec

2.1

2.4

4.8

5.2

5.9

9.8

Nov

2.1

2.3

4.8

5.2

5.8

9.6

Oct

2.1

2.3

4.8

5.2

6.0

9.5

Sep

2.0

2.2

4.9

5.3

6.0

9.6

Aug

2.1

2.5

5.2

5.6

6.3

10.3

Jul

2.0

2.7

5.6

6.0

6.7

10.7

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

2017

1.7

2.1

4.4

4.6

5.3

8.5

2016

2.0

2.3

4.9

5.2

5.9

9.6

2015

2.3

2.6

5.3

5.7

6.4

10.4

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 16.4 percent in Sep 2011 and then fell to 14.5 percent in Mar 2012, reaching 7.6 percent in May 2018. 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 20.6 million in job stress of unemployment/underemployment in May 2018, not seasonally adjusted, corresponding to 12.1 percent of the labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html).

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

U1

U2

U3

U4

U5

U6

May 2018

1.3

1.8

3.8

4.0

4.6

7.6

Apr

1.4

1.8

3.9

4.2

4.7

7.8

Mar

1.4

1.9

4.1

4.3

4.9

8.0

Feb

1.4

2.0

4.1

4.4

5.1

8.2

Jan

1.5

2.0

4.1

4.4

5.1

8.2

Dec 2017

1.5

2.0

4.1

4.4

5.1

8.1

Nov

1.6

2.0

4.1

4.4

5.0

8.0

Oct

1.6

2.0

4.1

4.4

5.0

8.0

Sep

1.7

2.1

4.2

4.4

5.1

8.3

Aug

1.7

2.2

4.4

4.7

5.4

8.6

Jul

1.7

2.1

4.3

4.7

5.3

8.5

Jun

1.7

2.2

4.3

4.7

5.3

8.5

May

1.7

2.1

4.3

4.5

5.2

8.4

Apr

1.7

2.2

4.4

4.7

5.3

8.6

Mar

1.7

2.2

4.5

4.7

5.4

8.8

Feb

1.8

2.3

4.7

5.0

5.7

9.2

Jan

1.9

2.3

4.8

5.1

5.8

9.4

Dec 2016

1.9

2.3

4.7

5.0

5.7

9.1

Nov

1.8

2.2

4.6

5.0

5.8

9.3

Oct

2.0

2.4

4.9

5.1

5.9

9.6

Sep

2.0

2.5

5.0

5.3

6.0

9.7

Aug

1.9

2.4

4.9

5.2

5.9

9.6

Jul

2.0

2.3

4.9

5.2

6.0

9.7

Jun

2.0

2.4

4.9

5.2

6.0

9.5

May

1.9

2.3

4.7

5.0

5.7

9.8

Apr

2.1

2.4

5.0

5.3

6.0

9.8

Mar

2.1

2.4

5.0

5.4

6.1

9.8

Feb

2.1

2.4

4.9

5.3

6.0

9.7

Jan

2.0

2.3

4.9

5.3

6.2

9.9

Dec 2015

2.1

2.4

5.0

5.4

6.1

9.9

Nov

2.1

2.5

5.0

5.4

6.1

9.9

Oct

2.1

2.5

5.0

5.4

6.2

9.8

Sep

2.1

2.4

5.0

5.4

6.2

10.0

Aug

2.2

2.5

5.1

5.5

6.2

10.2

Jul

2.2

2.6

5.2

5.6

6.4

10.3

Jun

2.3

2.6

5.3

5.7

6.4

10.4

May

2.4

2.8

5.5

5.8

6.6

10.8

Apr

2.3

2.6

5.4

5.9

6.7

10.9

Mar

2.4

2.7

5.5

5.9

6.7

10.9

Feb

2.5

2.7

5.5

5.9

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

7.0

11.4

Oct

2.7

2.8

5.7

6.2

7.0

11.5

Sep

2.8

2.9

5.9

6.4

7.3

11.7

Aug

2.9

3.0

6.2

6.6

7.4

11.9

July

3.0

3.1

6.2

6.6

7.5

12.1

Jun

3.0

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

6.3

6.7

7.5

12.3

Mar

3.5

3.5

6.7

7.1

8.0

12.7

Feb

3.5

3.5

6.7

7.1

8.0

12.7

Jan

3.4

3.5

6.6

7.1

8.1

12.7

Dec 2013

3.6

3.5

6.7

7.3

8.1

13.1

Nov

3.7

3.7

6.9

7.4

8.2

13.1

Oct

3.7

4.0

7.2

7.7

8.5

13.6

Sep

3.8

3.8

7.2

7.7

8.6

13.5

Aug

3.8

3.8

7.2

7.8

8.6

13.6

Jul

3.9

3.8

7.3

7.9

8.7

13.8

Jun

4.0

3.9

7.5

8.2

9.1

14.2

May

4.1

3.9

7.5

8.0

8.8

13.8

Apr

4.1

4.1

7.6

8.1

8.9

14.0

Mar

4.1

4.0

7.5

8.0

8.9

13.8

Feb

4.2

4.2

7.7

8.2

9.2

14.4

Jan

4.2

4.3

8.0

8.5

9.4

14.6

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

14.8

Aug

4.5

4.4

8.1

8.6

9.6

14.6

Jul

4.5

4.6

8.2

8.7

9.6

14.8

Jun

4.7

4.6

8.2

8.7

9.6

14.8

May

4.6

4.5

8.2

8.7

9.6

14.7

Apr

4.6

4.4

8.2

8.8

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

9.1

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

9.7

10.5

16.4

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

9.1

9.7

10.8

16.2

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart I-16 provides U6 monthly from 2001 to 2018. 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.

Chart I-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed Part-Time for Economic Reasons, Month, SA, 2001-2018

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 2013-2018.

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

Thousands, Month SA 2001-2018

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 9.166 million in Sep 2011 to 7.775 million in Mar 2012, seasonally adjusted, or decline of 1.391 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.671 million in Sep 2012 for increase of 697,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.203 million in Oct 2012 or by 468,000 again in one month, further declining to 8.166 million in Nov 2012 for another major one-month decline of 37,000 and 7.943 million in Dec 2012 or fewer 223,000 in just one month. The number employed part-time for economic reasons increased to 8.151 million in Jan 2013 or 208,000 more than in Dec 2012 and to 8.178 million in Feb 2013, declining to 7.937 million in May 2013 but increasing to 8.103 million in Jun 2013. The number employed part-time for economic reasons fell to 7.816 million in Aug 2013 for decline of 283,000 in one month from 8.099 million in Jul 2013. The number employed part-time for economic reasons decreased 52,000 from 7.816 million in Aug 2013 to 7.764 million in Sep 2013. The number part-time for economic reasons rose to 7.936 million in Oct 2013, falling by 218,000 to 7.718 million in Nov 2013. The number part-time for economic reasons increased to 7.827 million in Dec 2013, decreasing to 7.302 million in Jan 2014. The number employed part-time for economic reasons increased from 7.302 million in Jan 2014 to 7.304 million in Feb 2014. The number employed part-time for economic reasons increased to 7.451 million in Mar 2014 and 7.516 million in Apr 2014. The number employed part-time for economic reasons fell to 7.260 million in May 2014, increasing to 7.425 million in Jun 2014. The level employed part-time for economic reasons fell to 7.400 million in Jul 2014 and 7.169 million in Aug 2014. The level employed part-time for economic reasons fell to 7.007 million in Sep 2014, 7.031 million in Oct 2014 and 6.885 million in Nov 2014. The level employed part-time for economic reasons fell to 6.817 million in Dec 2014, increasing to 6.820 million in Jan 2015. The level employed part-time for economic reasons fell to 6.693 million in Feb 2015, increasing to 6.653 million in Mar 2015. The level of employed part-time for economic reasons fell to 6.622 million in Apr 2015, increasing to 6.643 million in May 2015. The level employed part-time for economic reasons fell to 6.386 million in Jun 2015 and 6.234 million in Jul 2015. The level employed part-time for economic reasons increased to 6.411 million in Aug 2015, declining to 6.025 million in Sep 2015. The level employed part-time for economic reasons fell to 5.807 million in Oct 2015, increasing to 6.159 million in Nov 2015. The level of part-time for economic reasons fell to 6.027 million in Dec 2015, decreasing to 5.960 million in Jan 2016. The level employed part-time for economic reasons decreased to 6.021 million in Feb 2016 and increased to 6.099 million in Mar 2016. The level employed part-time for economic reasons fell to 6.027 million in Apr 2016 and increased to 6.491 million in May 2016. The level of part-time for economic reasons fell to 5.751 million in Jun 2016, increasing to 5.898 million in Jul 2016. The level of part-time for economic reasons increased to 5.977 million in Aug 2016, decreasing to 5.893 million in Sep 2016. The level of part-time for economic reasons reached 5.955 million in Oct 2016, decreasing to 5.719 million in Nov 2016 and 5.554 million in Dec 2016. The level of part-time for economic reasons increased to 5.776 million in Jan 2017, decreasing to 5.670 million in Feb 2017. The level of part-time for economic reasons fell to 5.500 million in Mar 2017 and fell to 5.309 million in Apr 2017, decreasing to 5.268 million in May 2017. The level of part-time for economic reasons increased to 5.264 million in Jun 2017, decreasing to 5.236 million in Jul 2017 and 5.209 million in Aug 2017. The level of part-time for economic reasons fell to 5.148 million in Sep 2017, decreasing to 4.880 million in Oct 2017 and decreasing to 4.851 million in Nov 2017. The level of part-time for economic reasons increased to 4.915 million in Dec 2017, increasing to 4.989 million in Jan 2018 and increasing to 5.160 million in Feb 2018. The level of part-time for economic reasons fell to 5.019 million in Mar 2018, decreasing to 4.985 million in Apr 2018. The level of part-time for economic reasons eased to 4.948 million in May 2018.
  • Seasonally adjusted full-time. The number employed full-time increased from 112.923 million in Oct 2011 to 115.024 million in Mar 2012 or 2.101 million but then fell to 114.233 million in May 2012 or 0.791 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.736 million in Aug 2012 to 115.570 million in Oct 2012 or increase of 0.834 million full-time jobs in two months and further to 115.563 million in Jan 2013 or increase of 0.827 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.695 million in Feb 2013, increasing to 116.240 million in May 2013 and 116.166 million in Jun 2013. Then number of full-time jobs increased to 116.201 million in Jul 2013, 116.417 million in Aug 2013 and 116.846 million in Sep 2013. The number of full-time jobs fell to 116.352 million in Oct 2013 and increased to 117.078 in Nov 2013. The level of full-time jobs increased to 117.394 million in Dec 2013, increasing to 117.746 million in Jan 2014 and 117.774 million in Feb 2014. The level of employment full-time increased to 117.953 million in Mar 2014 and 118.433 million in Apr 2014. The level of full-time employment reached 118.800 million in May 2014, decreasing to 118.248 million in Jun 2014. The level of full-time jobs increased to 118.436 million in Jul 2014 and 118.701 million in Aug 2014. The level of full-time jobs increased to 119.298 million in Sep 2014, 119.762 million in Oct 2014 and 119.672 million in Nov 2014. The level of full-time jobs increased to 120.115 million in Dec 2014 and 120.477 million in Jan 2015. The level of full-time jobs increased to 120.750 million in Feb 2015 and 120.951 million in Mar 2015. The level of full-time jobs decreased to 120.781 million in Apr 2015, increasing to 121.518 million in May 2015 and decreasing to 121.035 million in Jun 2015. The level of full-time jobs increased to 121.662 million in Jul 2015 and increased to 122.014 million in Aug 2015, decreasing to 121.773 million in Sep 2015. The level of full-time jobs increased to 122.069 million in Oct 2015 and increased to 122.153 million in Nov 2015. The level of full-time jobs increased to 122.740 million in Dec 2015 and 123.020 million in Jan 2016. The level of full-time jobs increased to 123.200 million in Feb 2016 and increased to 123.509 million in Mar 2016. The level of full-time jobs decreased to 123.154 million in Apr 2016 and 123.224 million in May 2016. The level of full-time jobs increased to 123.648 million in Jun 2016, increasing to 123.995 million in Jul 2016. The level of full-time jobs increased to 124.453 million in Aug 2016, decreasing to 124.185 million in Sep 2016 and 124.185 million in Oct 2016. The level of full-time jobs increased to 124.239 million in Nov 2016 and 124.301 million in Dec 2016. The level of full-time jobs increased to 124.625 million in Jan 2017, increasing to 125.071 million in Feb 2017. The level of full-time jobs increased to 125.563 million in Mar 2017 and increased to 125.963 million in Apr 2017, decreasing to 125.621 million in May 2017. The level of full-time jobs increased to 126.050 million in Jun 2017, decreasing to 126.002 million in Jul 2017 and 125.882 million in Aug 2017. The level of full-time jobs increased to 126.676 million in Sep 2017, decreasing to 126.636 million in Oct 2017. The level of full-time jobs increased to 126.758 million in Nov 2017, decreasing to 126.723 million in Dec 2017. The level of full-time jobs increased to 127.016 million in Jan 2018, increasing to 127.745 million in Feb 2018. The level of full-time jobs decreased to 127.434 million in Mar 2018, increasing to 127.753 million in Apr 2018. The level of full-time jobs increased to 128.657 million in May 2018. Adjustments of benchmark and seasonality-factors at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2016/02/fluctuating-risk-financial-assets-in.html 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, decreasing to 6.511 million in Jul 2015. The level of part-time for economic reasons fell to 6.361 million in Aug 2015 and 5.693 million in Sep 2015. The level of part-time for economic reasons fell to 5.536 million in Oct 2015, increasing to 5.967 million in Nov 2015. The level of part-time for economic reasons increased to 6.179 million in Dec 2015, increasing to 6.406 million in Jan 2016. The level of part-time for economic reasons decreased to 6.106 million in Feb 2016 and increased to 6.138 million in Mar 2016. The level of part-time for economic reasons decreased to 5.771 million in Apr 2016 and increased to 6.238 million in May 2016. The level of part-time for economic reasons decreased to 6.119 million in Jun 2016, increasing to 6.157 million in Jul 2016. The level of part-time for economic reasons fell to 5.963 million in Aug 2016, decreasing to 5.550 million in Sep 2016. The level of part-time for economic reasons increased to 5.648 million in Oct 2016, decreasing to 5.518 million in Nov 2016 and increasing to 5.707 million in Dec 2016. The level of part-time for economic reasons increased to 6.226 million in Jan 2017, decreasing to 5.773 million in Feb 2017. The level of part-time for economic reasons fell to 5.552 million in Mar 2017, decreasing to 5.058 million in Apr 2017. The level of part-time for economic reasons fell to 5.038 million in May 2017, increasing to 5.602 million in Jun 2017. The level of part-time for economic reasons fell to 5.475 million in Jul 2017, 5.204 million in Aug 2017 and 4.818 million in Sep 2017. The level of part-time for economic reasons decreased to 4.553 million in Oct 2017, decreasing to 4.462 million in Nov 2017. The level of part-time for economic reasons increased to 5.060 million in Dec 2017, increasing to 5.474 million in Jan 2018 and decreasing to 5.331 million in Feb 2018. The level of part-time for economic reasons decreased to 5.080 million in Mar 2018, decreasing to 4.734 million in Apr 2018. The level of part-time for economic reasons increased to 4.739 million in May 2018.
  • 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 2018 is 129.014 million, which is higher by 5.795 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 257.454 million in May 2018 or by 25.496 million (http://www.bls.gov/data/). The number with full-time jobs in May 2018 is 129.014 million, which is higher by 5.795 million relative to the peak of 123.219 million in Jul 2007. The ratio of full-time jobs of 123.219 million in Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 136.708 million full-time jobs with population of 257.454 million in May 2018 (0.531 x 257.454) or 7.694 million fewer full-time jobs relative to actual 129.014 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 20 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 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.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 dividing 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 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/twenty-two-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. 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 of manufacturing at average 3.2 percent per year from Apr 1919 to Apr 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 154.7937 in Apr 2018. The actual index NSA in Apr 2018 is 104.3625, which is 32.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Apr 2018. Using trend growth of 2.0 percent per year, the index would increase to 135.5768 in Apr 2018. The output of manufacturing at 104.3625 in Apr 2018 is 23.0 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

May 2018

4,948

128.657

Apr 2018

4,985

127.753

Mar 2018

5,019

127.434

Feb 2018

5,160

127.745

Jan 2018

4,989

127.016

Dec 2017

4,915

126.723

Nov 2017

4,851

126.758

Oct 2017

4,880

126.636

Sep 2017

5,148

126.676

Aug 2017

5,209

125.882

Jul 2017

5,236

126.002

Jun 2017

5,264

126.050

May 2017

5,268

125.621

Apr 2017

5,309

125.963

Mar 2017

5,500

125.563

Feb 2017

5,670

125.071

Jan 2017

5,776

124.625

Dec 2016

5,554

124.301

Nov 2016

5,719

124.239

Oct 2016

5,955

124.185

Sep 2016

5,893

124.185

Aug 2016

5,977

124.453

Jul 2016

5,898

123.995

Jun 2016

5,751

123.648

May 2016

6,491

123.224

Apr 2016

6,027

123.154

Mar 2016

6,099

123.509

Feb 2016

6,021

123.200

Jan 2016

5,960

123.020

Dec 2015

6,027

122.740

Nov 2015

6,159

122.153

Oct 2015

5,807

122.069

Sep 2015

6,025

121.773

Aug 2015

6,411

122.014

Jul 2015

6,234

121.662

Jun 2015

6,386

121.035

May 2015

6,643

121.518

Apr 2015

6,622

120.781

Mar 2015

6,653

120.951

Feb 2015

6,693

120.750

Jan 2015

6,820

120.477

Dec 2014

6,817

120.115

Nov 2014

6,885

119.672

Oct 2014

7,031

119.762

Sep 2014

7,007

119.298

Aug 2014

7,169

118.701

Jul 2014

7,400

118.436

Jun 2014

7,425

118.248

May 2014

7,260

118.800

Apr 2014

7,516

118.433

Mar 2014

7,451

117.953

Feb 2014

7,304

117.774

Jan 2014

7,302

117.746

Dec 2013

7,827

117.394

Nov 2013

7,718

117.078

Oct 2013

7,936

116.352

Sep 2013

7,764

116.846

Aug 2013

7,816

116.417

Jul 2013

8,099

116.201

Jun 2013

8,103

116.166

May 2013

7,937

116.240

Apr 2013

7,964

116.014

Mar 2013

7,722

115.808

Feb 2013

8,178

115.695

Jan 2013

8,151

115.563

Dec 2012

7,943

115.791

Nov 2012

8,166

115.655

Oct 2012

8,203

115.570

Sep 2012

8,671

115.252

Aug 2012

7,974

114.736

Jul 2012

8,082

114.575

Jun 2012

8,072

114.749

May 2012

8,101

114.233

Apr 2012

7,913

114.371

Mar 2012

7,775

115.024

Feb 2012

8,238

114.141

Jan 2012

8,305

113.755

Dec 2011

8,171

113.774

Nov 2011

8,447

113.213

Oct 2011

8,657

112.923

Sep 2011

9,166

112.544

Aug 2011

8,788

112.723

Jul 2011

8,281

112.193

Not Seasonally Adjusted

May 2018

4,739

129.014

Apr 2018

4,734

127.340

Mar 2018

5,080

126.424

Feb 2018

5,331

126.401

Jan 2018

5,474

125.435

Dec 2017

5,060

125.985

Nov 2017

4,462

126.468

Oct 2017

4,553

127.055

Sep 2017

4,818

127.235

Aug 2017

5,204

127.353

Jul 2017

5,475

127.542

Jun 2017

5,602

127.337

May 2017

5,038

125.911

Apr 2017

5,058

125.532

Mar 2017

5,552

124.566

Feb 2017

5,773

123.610

Jan 2017

6,226

123.015

Dec 2016

5,707

123.570

Nov 2016

5,518

123.960

Oct 2016

5,648

124.588

Sep 2016

5,550

124.728

Aug 2016

5,963

125.892

Jul 2016

6,157

125.507

Jun 2016

6,119

124.903

May 2016

6,238

123.548

Apr 2016

5,771

122.742

Mar 2016

6,138

122.522

Feb 2016

6,106

121.757

Jan 2016

6,406

121.411

Dec 2015

6,179

122.013

Nov 2015

5,967

121.897

Oct 2015

5,536

122.466

Sep 2015

5,693

122.303

Aug 2015

6,361

123.420

Jul 2015

6,511

123.142

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

115.774

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/

Chart I-20 provides the level of full-time jobs from 2001 to 2018. 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 257.454 million in May 2018 or by 25.496 million (http://www.bls.gov/data/). The number with full-time jobs in May 2018 is 129.014 million, which is higher by 5.795 million relative to the peak of 123.219 million in Jul 2007. The ratio of full-time jobs of 123.219 million in Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 136.708 million full-time jobs with population of 257.454 million in May 2018 (0.531 x 257.454) or 7.694 million fewer full-time jobs relative to actual 129.014 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 20 million. Mediocre GDP growth is the main culprit of the fractured US labor market.

There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

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

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

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

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2018

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 2018. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2018

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 2018. 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.

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2018

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 2018. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

Chart I-20C, US, Noninstitutional Civilian Population, Thousands, 1968-2018

Sources: US Bureau of Labor Statistics

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

Table I-9A 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 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, 4.2 percent in 1988 and 3.7 percent in 1989. In contrast, GDP grew 2.5 percent in 2010, 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.6 percent in 2014 and 2.9 percent in 2015. GDP grew 1.5 percent in 2016 and 2.3 percent in 2017. Actual annual equivalent GDP growth in the twenty-five quarters from IQ2012 to IQ2018 is 2.2 percent and 2.8 percent in the four quarters ending in IQ2018. GDP grew at 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. The forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 2.5 to 3.0 percent in 2018 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20180321.pdf) with less reliable forecast of 2.0 to 2.8 percent in 2019 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20180321.pdf). Growth of GDP in the expansion from IIIQ2009 to IQ2018 has been at average 2.2 percent in annual equivalent.

Table I-9A, 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

1939

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

2.2

1943

17.0

1993

2.7

2013

1.7

1944

8.0

1994

4.0

2014

2.6

1945

-1.0

1995

2.7

2015

2.9

1946

-11.6

1996

3.8

2016

1.5

1947

-1.1

1997

4.5

2017

2.3

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

Characteristics of the four cyclical contractions are in Table I-9B 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-9B, US, Number of Quarters, GDP Cumulative Percentage Contraction and Average Percentage Annual Equivalent Rate in Cyclical Contractions   

Number of Quarters

Cumulative Percentage Contraction

Average Percentage Rate

IIQ1953 to IIQ1954

3

-2.4

-0.8

IIIQ1957 to IIQ1958

3

-3.0

-1.0

IVQ1973 to IQ1975

5

-3.1

-0.6

IQ1980 to IIIQ1980

2

-2.2

-1.1

IIIQ1981 to IVQ1982

4

-2.5

-0.64

IVQ2007 to IIQ2009

6

-4.2

-0.72

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

Table I-9C shows the mediocre average annual equivalent growth rate of 2.2 percent of the US economy in the thirty-five quarters of the current cyclical expansion from IIIQ2009 to IQ2018. 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
  • 4.8 percent in the first twenty-four quarters of expansion from IQ1983 to IVQ1988
  • 4.8 percent in the first twenty-five quarters of expansion from IQ1983 to IQ1989
  • 4.7 percent in the first twenty-six quarters of expansion from IQ1983 to IIQ1989
  • 4.7 percent in the first twenty-seven quarters of expansion from IQ1983 to IIIQ1989
  • 4.5 percent in the first twenty-eight quarters of expansion from IQ1983 to IVQ1989
  • 4.5 percent in the first twenty-nine quarters of expansion from IQ1983 to IQ1990
  • 4.4 percent in the first thirty quarters of expansion from IQ1983 to IIQ1990
  • 4.3 percent in the first thirty-one quarters of expansion from IQ1983 to IIIQ1990
  • 4.0 percent in the first thirty-two quarters of expansion from IQ1983 to IVQ1990
  • 3.8 percent in the first thirty-three quarters of expansion from IQ1983 to IQ1991
  • 3.8 percent in the first thirty-four quarters of expansion from IQ1983 to IIQ1991
  • 3.8 percent in the first thirty-five quarters of expansion from IQ1983 to IIIQ1991:

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 relative to historical experience with annual growth of 2.5 percent in 2010 decelerating to 1.6 percent annual growth in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.6 percent in 2014, 2.9 percent in 2015, 1.5 percent in 2016 and 2.3 percent in 2017 (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. 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989. 4.5 percent from IQ1983 to IVQ1989, 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990. 4.0 percent from IQ1983 to IVQ1990. 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991 and at 7.8 percent from IQ1983 to IVQ1983. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the twenty-five quarters from 2012 to 2018 accumulated to 14.4 percent. This growth is equivalent to 2.2 percent per year, obtained by dividing GDP in IQ2018 of $17,385.8 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/25: {[($17,379.7/$15,190.3)4/25 -1]100 = 2.2 percent}.

Table I-9C, 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

IQ1983 to IVQ1988

IQ1983 to IQ1989

IQ1983 to IIQ1989

IQ1983 to IIIQ1989

IQ1983 to IVQ1989

IQ1983 to IQ1990

IQ1983 to IIQ1990

IQ1983 to IIIQ1990

IQ1983 to IVQ1990

IQ1983 to IQ1991

IQ1983 to IIQ1991

IQ1983 to IIIQ1991

13

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

19.9

21.6

22.3

23.1

24.5

25.6

27.7

28.4

30.1

30.9

32.6

34.0

35.0

36.0

36.3

37.8

38.3

38.4

37.2

36.5

37.6

38.3

5.7

5.4

5.2

5.0

5.0

4.9

5.0

4.9

4.9

4.8

4.8

4.8

4.7

4.7

4.5

4.5

4.4

4.3

4.0

3.8

3.8

3.8

First Four Quarters IQ1983 to IVQ1983

4

7.8

Average First Four Quarters in Four Expansions*

7.7

IIIQ2009 to IQ2018

35

21.1

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 2017 and the whole cycle from 1979 to 1989. In the entire cycle from 2007 to 2017, the number employed increased 7.290 million, full-time employed increased 4.876 million, part-time for economic reasons increased 0.849 million and population increased 23.212 million. The number employed increased 5.0 percent, full-time employed increased 4.0 percent, part-time for economic reasons increased 19.3 percent and population increased 10.0 percent. There is sharp contrast with the contractions of the 1980s and with most economic history of the United States. In the whole cycle from 1979 to 1989, the number employed increased 18.518 million, full-time employed increased 14.715 million, part-time for economic reasons increased 1.317 million and population increased 21.530 million. In the entire cycle from 1979 to 1989, the number employed increased 18.7 percent, full-time employed increased 17.8 percent, part-time for economic reasons increased 36.8 percent and population increased 13.1 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

2015

148.834

121.492

6.371

250.801

2016

151.436

123.761

5.943

253.538

2017

153.337

125.967

5.250

255.079

∆2007-2017

7.290

4.876

0.849

23.212

∆% 2007-2016

5.0

4.0

19.3

10.0

1980s

1979

98.824

82.654

3.577

164.863

1980

99.303

82.562

4.321

167.745

1981

100.397

83.243

4.768

170.130

1982

99.526

81.421

6.170

172.271

1983

100.834

82.322

6.266

174.215

1984

105.005

86.544

5.744

176.383

1985

107.150

88.534

5.590

178.206

1986

109.597

90.529

5.588

180.587

1987

112.440

92.957

5.401

182.753

1988

114.968

95.214

5.206

184.613

1989

117.342

97.369

4.894

186.393

∆1979-1989

18.518

14.715

1.317

21.530

∆% 1979-1989

18.7

17.8

36.8

13.1

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 20.6 million or 12.1 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.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

2015

250.8

121.5

148.8

157.1

62.7

59.3

8.3

2016

253.5

123.8

151.4

159.2

62.8

59.7

7.8

2017

255.1

126.0

155.3

160.3

62.9

60.1

7.0

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

5/18

257.5

129.0

156.1

161.8

62.8

60.6

5.8

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

Source: Bureau of Labor Statistics

http://www.bls.gov/

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

2015

38.6

18.8

21.2

55.0

48.6

2.5

11.6

2016

38.4

19.0

21.2

55.2

49.4

2.2

10.4

2017

38.2

19.2

21.2

55.5

50.3

2.0

9.2

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

5/18

38.0

19.0

20.8

54.6

49.9

1.8

8.6

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. Youth employment fell from 20.041 million in 2006 to 18.756 Youth employment fell from 20.041 million in 2006 to 18.756 million in 2015 or 1.285 million. Youth employment fell from 20.041 million in 2006 to 18.992 million in 2016 or 1.049 million. Youth employment fell from 20.041 million in 2006 to 19.206 million in 2017 or 0.835 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 20.129 million in Dec 2006 to 18.720 million in Dec 2015 or 1.409 million fewer jobs. Youth jobs fell from 20.129 million in Dec 2006 to 18.830 million in Dec 2016 or 1.299 million. Youth jobs fell from 21.167 million in Aug 2006 to 20.038 million in Aug 2017 or 1.129 million. 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 youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015 while the number of youth jobs fell 1.581 million. The youth civilian noninstitutional population increased 1.548 million from 37.008 million in Aug 2006 to 38.556 million in Aug 2015 while the number of youth jobs fell 1.590 million. The youth civilian noninstitutional population increased 1,498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015 while the number of youth jobs fell 1.249 million. The youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015 while the number of youth jobs fell 1.199 million. The youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015 while the number of youth jobs fell 1.418 million. The youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015 while the level of youth jobs 1.409 million. The youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016 while the level of youth jobs fell 0.844 million. The youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016 while the number of youth jobs fell 0.726 million. The youth civilian noninstitutional population increased 1,662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016 while the number of youth jobs fell 0.711 million. The youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016 while the number of youth jobs fell 0.895 million. The youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016 while the number of youth jobs fell 0.894 million. The youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016 while the number of youth jobs fell 1.301 million. The youth civilian noninstitutional population increased 1.461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016 while the number of youth jobs fell 1.458 million. The youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016 while the number of youth jobs fell 1.291 million. The youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016 while the number of youth jobs fell 0.911 million. The youth civilian noninstitutional population increased 1.320 million from 37.047 million in Oct 2006 to 38.367 million in Oct 2016 while the number of youth jobs fell 1.158 million. The youth civilian noninstitutional population increased 1.283 million from 37.076 million in Nov 2006 to 38.359 million in Nov 2016 while the number of youth jobs fell 1.102 million. The youth civilian noninstitutional population increased 1.248 million from 37.100 million in Dec 2006 to 38.348 million in Dec 2016 while the number of youth jobs fell 1.299 million. The youth civilian noninstitutional population increased 1.488 million from 36.761 million in Jan 2006 to 38.249 million in Jan 2017 while the number of youth jobs decreased 0.692 million. The youth civilian noninstitutional population increased 1.440 million from 36.791 million in Feb 2006 to 38.231 million in Feb 2017 while the number of youth jobs decreased 0.578 million. The youth civilian noninstitutional population increased 1.393 million from 36.821 million in Mar 2006 to 38.214 million in Mar 2017 while the number of youth jobs decreased 0.377 million. The youth civilian noninstitutional population increased 1.343 million from 36.854 million in Apr 2006 to 38.197 million in Apr 2017 while the number of youth jobs decreased 0.458 million. The youth civilian noninstitutional population increased 1.284 million from 36.897 million in May 2006 to 38.181 million in May 2017 while the number of youth jobs decreased 0.699 million. The youth civilian noninstitutional population increased 1.223 million from 36.943 million in Jun 2006 to 38.166 million in Jun 2017 while the number of youth jobs decreased 0.938 million. The youth civilian noninstitutional population increased 1.163 million from 36.989 million in Jul 2006 to 38.152 million in Jul 2017 while the number of youth jobs decreased 1.024 million. The youth civilian noninstitutional population increased 1.163 million from 36.989 million in Jul 2006 to 38.152 million in Jul 2017 while the number of youth jobs decreased 1.024 million. The youth civilian noninstitutional population increased 1.120 million from 37.008 million in Aug 2006 to 38.128 million in Aug 2017 while the number of youth jobs decreased 1.129 million. The youth civilian noninstitutional population increased 1.076 million from 37.027 million in Sep 2006 to 38.103 million in Sep 2017 while the number of youth jobs decreased 0.485 million. The youth civilian noninstitutional population increased 1.032 million from 37.047 million in Oct 2006 to 38.079 million in Oct 2017 while the number of youth jobs decreased 0.852 million. The youth civilian noninstitutional population increased 0.984 million from 37.076 million in Nov 2006 to 38.060 million in Nov 2017 while the number of youth jobs decreased 1.272 million. The youth civilian noninstitutional population increased 0.938 million from 37.100 million in Dec 2006 to 38.038 million in Dec 2017 while the number of youth jobs decreased 1.519 million. The youth civilian noninstitutional population increased 1.304 million from 36.761 million in Jan 2006 to 38.065 million in Jan 2018 while the number of youth jobs decreased 0.500 million. The youth civilian noninstitutional population increased 1.264 million from 36.791 million in Feb 2006 to 38.055 million in Feb 2018 while the number of youth jobs decreased 0.380 million. The youth civilian noninstitutional population increased 1.225 million from 36.821 million in Mar 2006 to 38.046 million in Mar 2018 while the number of youth jobs decreased 0.244 million. The youth civilian noninstitutional population increased 1.185 million from 36.854 million in Apr 2006 to 38.039 million in Apr 2018 while the number of youth jobs decreased 0.533 million. The youth civilian noninstitutional population increased 1.126 million from 36.897 million in May 2006 to 38.023 million in May 2018 while the number of youth jobs decreased 0.785 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

Mar

Apr

May

Dec

Annual

2001

19800

19778

19648

19547

20088

2002

19091

19108

19484

19394

19683

2003

18709

18873

19032

19136

19351

2004

18752

19184

19237

19619

19630

2005

18989

19071

19356

19733

19770

2006

19291

19406

19769

20129

20041

2007

19538

19368

19457

19361

19875

2008

18745

19161

19254

18378

19202

2009

17564

17739

17588

16615

17601

2010

16587

16764

17039

16727

17077

2011

16898

16970

17045

17234

17362

2012

17301

17387

17681

17604

17834

2013

17271

17593

17704

18106

18057

2014

17939

18021

18329

18347

18442

2015

18076

18241

18709

18720

18756

2016

18580

18511

18875

18830

18992

2017

18914

18948

19070

18610

19206

2018

19047

18873

18984

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

Chart I-21 provides the level of employment for ages 16 to 24 years. There was much sharper decline in employment levels of youth in the global recession than in the recession of 2001 to 2002. There has not been full recovery of the employment levels of youth before the global recession after 2007.

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2018

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 2018. 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 youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015 while the number of youth jobs fell 1.581 million. The youth civilian noninstitutional population increased 1.548 million from 37.008 million in Aug 2006 to 38.556 million in Aug 2015 while the number of youth jobs fell 1.590 million. The youth civilian noninstitutional population increased 1,498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015 while the number of youth jobs fell 1.249 million. The youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015 while the number of youth jobs fell 1.199 million. The youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015 while the number of youth jobs fell 1.418 million. The youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015 while the level of youth jobs 1.409 million. The youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016 while the level of youth jobs fell 0.844 million. The youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016 while the number of youth jobs fell 0.726 million. The youth civilian noninstitutional population increased 1,662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016 while the number of youth jobs fell 0.711 million. The youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016 while the number of youth jobs fell 0.895 million. The youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016 while the number of youth jobs fell 0.894 million. The youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016 while the number of youth jobs fell 1.301 million. The youth civilian noninstitutional population increased 1.461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016 while the number of youth jobs fell 1.458 million. The youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016 while the number of youth jobs fell 1.291 million. The youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016 while the number of youth jobs fell 0.911 million. The youth civilian noninstitutional population increased 1.320 million from 37.047 million in Oct 2006 to 38.367 million in Oct 2016 while the number of youth jobs fell 1.158 million. The youth civilian noninstitutional population increased 1.283 million from 37.076 million in Nov 2006 to 38.359 million in Nov 2016 while the number of youth jobs fell 1.102 million. The youth civilian noninstitutional population increased 1.248 million from 37.100 million in Dec 2006 to 38.348 million in Dec 2016 while the number of youth jobs fell 1.299 million. The youth civilian noninstitutional population increased 1.488 million from 36.761 million in Jan 2006 to 38.249 million in Jan 2017 while the number of youth jobs decreased 0.692 million. The youth civilian noninstitutional population increased 1.440 million from 36.791 million in Feb 2006 to 38.231 million in Feb 2017 while the number of youth jobs decreased 0.578 million. The youth civilian noninstitutional population increased 1.393 million from 36.821 million in Mar 2006 to 38.214 million in Mar 2017 while the number of youth jobs decreased 0.377 million. The youth civilian noninstitutional population increased 1.343 million from 36.854 million in Apr 2006 to 38.197 million in Apr 2017 while the number of youth jobs decreased 0.458 million. The youth civilian noninstitutional population increased 1.284 million from 36.897 million in May 2006 to 38.181 million in May 2017 while the number of youth jobs decreased 0.699 million. The youth civilian noninstitutional population increased 1.223 million from 36.943 million in Jun 2006 to 38.166 million in Jun 2017 while the number of youth jobs decreased 0.938 million. The youth civilian noninstitutional population increased 1.163 million from 36.989 million in Jul 2006 to 38.152 million in Jul 2017 while the number of youth jobs decreased 1.024 million. The youth civilian noninstitutional population increased 1.163 million from 36.989 million in Jul 2006 to 38.152 million in Jul 2017 while the number of youth jobs decreased 1.024 million. The youth civilian noninstitutional population increased 1.120 million from 37.008 million in Aug 2006 to 38.128 million in Aug 2017 while the number of youth jobs decreased 1.129 million. The youth civilian noninstitutional population increased 1.076 million from 37.027 million in Sep 2006 to 38.103 million in Sep 2017 while the number of youth jobs decreased 0.485 million. The youth civilian noninstitutional population increased 1.032 million from 37.047 million in Oct 2006 to 38.079 million in Oct 2017 while the number of youth jobs decreased 0.852 million. The youth civilian noninstitutional population increased 0.984 million from 37.076 million in Nov 2006 to 38.060 million in Nov 2017 while the number of youth jobs decreased 1.272 million. The youth civilian noninstitutional population increased 0.938 million from 37.100 million in Dec 2006 to 38.038 million in Dec 2017 while the number of youth jobs decreased 1.519 million. The youth civilian noninstitutional population increased 1.304 million from 36.761 million in Jan 2006 to 38.065 million in Jan 2018 while the number of youth jobs decreased 0.500 million. The youth civilian noninstitutional population increased 1.264 million from 36.791 million in Feb 2006 to 38.055 million in Feb 2018 while the number of youth jobs decreased 0.380 million. The youth civilian noninstitutional population increased 1.225 million from 36.821 million in Mar 2006 to 38.046 million in Mar 2018 while the number of youth jobs decreased 0.244 million. The youth civilian noninstitutional population increased 1.185 million from 36.854 million in Apr 2006 to 38.039 million in Apr 2018 while the number of youth jobs decreased 0.533 million. The youth civilian noninstitutional population increased 1.126 million from 36.897 million in May 2006 to 38.023 million in May 2018 while the number of youth jobs decreased 0.785 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.

Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2018

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 2018. 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. The youth civilian labor force decreased 1.502 million from 24.664 million in Jul 2007 to 23.162 million in Jul 2015 while the youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015. The youth civilian labor force decreased 1.667 million from 23.634 million in Aug 2006 to 21.967 million in Aug 2015 while the youth civilian noninstitutional population increased 1.548 million from 37.008 in Aug 2006 to 38.556 million in Aug 2015. The youth civilian labor force decreased 1.290 million from 21.901 million in Sep 2006 to 20.611 in Sep 2015 while the youth civilian noninstitutional population increased 1.498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015. The youth civilian labor force decreased 1.228 million from 22.105 million in Oct 2006 to 20.877 million in Oct 2015 while the youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015. The youth civilian labor force decreased 1.513 million from 22.145 million in Nov 2006 to 20.632 million in Nov 2015 while the youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015. The youth civilian labor force decreased 1.301 million from 22.136 million in Dec 2006 to 20.835 million in Dec 2015 while the youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015. The youth civilian labor force decreased 1.004 million from 21.368 million in Jan 2006 to 20.364 million in Jan 2016 while the youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016. The youth civilian labor force decreased 0.930 million from 21.615 million in Feb 2006 to 20.685 million in Feb 2016 while the youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016. The youth civilian labor force decreased 0.767 million from 21.507 million in Mar 2006 to 20.740 million in Mar 2016 while the youth civilian noninstitutional population increased 1.662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016. The youth civilian labor force decreased 0.950 million from 21.498 million in Apr 2006 to 20.548 million in Apr 2016 while the youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016. The youth civilian labor force decreased 0.921 million from 22.023 million in May 2006 to 21.102 million in May 2016 while the youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016. The youth civilian labor force decreased 1.373 million from 24.128 million in Jun 2006 to 22.755 million in Jun 2016 while the youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016. The youth civilian labor force decreased 1.560 million from 24.664 million in Jul 2006 to 23.104 million in Jul 2016 while the youth civilian noninstitutional population increased 1,461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016. The youth civilian labor force decreased 1.536 million from 23.634 million in Aug 2006 to 22.098 million in Aug 2016 while the youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016. The youth civilian labor force decreased 1.082 million from 21.901 million in Sep 2006 to 20.891 million in Sep 2016 while the youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016. The youth civilian labor force decreased 1.315 million from 22.105 million in Oct 2006 to 20.790 million in Oct 2016 while the youth civilian noninstitutional population increased 1.320 million from 37.047 million in Oct 2006 to 38.367 million in Oct 2016. The youth civilian labor force decreased 1.410 million from 22.145 million in Nov 2006 to 20.735 million in Nov 2016 while the youth civilian noninstitutional population increased 1.283 million from 37.076 million in Nov 2006 to 38.359 million in Nov 2016. The youth civilian labor force decreased 1.447 million from 22.136 million in Dec 2006 to 20.689 million in Dec 2016 while the youth civilian noninstitutional population increased 1.248 million from 37.100 million in Dec 2006 to 38.348 million in Dec 2016. The youth civilian labor force decreased 0.861 million from 21.368 million in Jan 2006 to 20.507 million in Jan 2017 while the youth civilian noninstitutional population increased 1.488 million from 36.761 million in Jan 2006 to 38.249 million in Jan 2017. The youth civilian labor force decreased 0.918 million from 21.615 million in Feb 2006 to 20.697 million in Feb 2017 while the youth civilian noninstitutional population increased 1.440 million from 36.791 million in Feb 2006 to 38.231 million in Feb 2017. The youth civilian labor force decreased 0.751 million from 21.507 million in Mar 2006 to 20.756 million in Mar 2017 while the youth civilian noninstitutional population increased 1.393 million from 36.821 million in Mar 2006 to 38.214 million in Mar 2017. The youth civilian labor force decreased 0.790 million from 21.498 million in Apr 2006 to 20.708 million in Apr 2017 while the youth civilian noninstitutional population increased 1.343 million from 36.854 million in Apr 2006 to 38.197 million in Apr 2017. The youth civilian labor force decreased 1.124 million from 22.023 million in May 2006 to 20.899 million in May 2017 while the youth civilian noninstitutional population increased 1.284 million from 36.897 million in May 2006 to 38.181 million in May 2017. The youth civilian labor force decreased 1.408 million from 24.128 million in Jun 2006 to 22.720 million in Jun 2017 while the youth civilian noninstitutional population increased 1.223 million from 36.943 million in Jun 2006 to 38.166 million in Jun 2017. The youth civilian labor force decreased 1.557 million from 24.664 million in Jul 2006 to 23.107 million in Jul 2017 while the youth civilian noninstitutional population increased 1.163 million from 36.989 million in Jul 2006 to 38.152 million in Jul 2017. The youth civilian labor force decreased 1.666 million from 23.634 million in Aug 2006 to 21.968 million in Aug 2017 while the youth civilian noninstitutional population increased 1.120 million from 37.008 million in Aug 2006 to 38.128 million in Aug 2017. The youth civilian labor force decreased 0.904 million from 21.901 million in Sep 2006 to 20.997 million in Sep 2017 while the youth civilian noninstitutional population increased 1.076 million from 37.027 million in Sep 2006 to 38.103 million in Sep 2017. The youth civilian labor force decreased 1.284 million from 22.105 million in Oct 2006 to 20.821 million in Oct 2017 while the youth civilian noninstitutional population increased 1.032 million from 37.047 million in Oct 2006 to 38.079 million in Oct 2017. The youth civilian labor force decreased 1.652 million from 22.145 million in Nov 2006 to 20.493 million in Nov 2017 while the youth civilian noninstitutional population increased 0.984 million from 37.076 million in Nov 2006 to 38.060 million in Nov 2017. The youth civilian labor force decreased 1.885 million from 22.136 million in Dec 2006 to 20.251 million in Dec 2017 while the youth civilian noninstitutional population increased 0.938 million from 37.100 million in Dec 2006 to 38.038 million in Dec 2017. The youth civilian labor force decreased 0.835 million from 21.368 million in Jan 2006 to 20.533 million in Jan 2018 while the youth civilian noninstitutional population increased 1.304 million from 36.761 million in Jan 2006 to 38.065 million in Jan 2018. The youth civilian labor force decreased 0.835 million from 21.368 million in Jan 2006 to 20.533 million in Jan 2018 while the youth civilian noninstitutional population increased 1.304 million from 36.761 million in Jan 2006 to 38.065 million in Jan 2018. The youth civilian labor force decreased 0.907 million from 21.615 million in Feb 2006 to 20.708 million in Jan 2018 while the youth civilian noninstitutional population increased 1.264 million from 36.791 million in Feb 2006 to 38.055 million in Feb 2018. The youth civilian labor force decreased 0.755 million from 21.507 million in Mar 2006 to 20.752 million in Mar 2018 while the youth civilian noninstitutional population increased 1.225 million from 36.821 million in Mar 2006 to 38.046 million in Mar 2018. The youth civilian labor force decreased 1.073 million from 21.498 million in Apr 2006 to 20.425 million in Apr 2018 while the youth civilian noninstitutional population increased 1.185 million from 36.854 million in Apr 2006 to 38.039 million in Apr 2018. The youth civilian labor force decreased 1.244 million from 22.023 million in May 2006 to 20.779 million in May 2018 while the youth civilian noninstitutional population increased 1.126 million from 36.897 million in Apr 2006 to 38.023 million in Apr 2018. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.

Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2018

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 rate ages 16 to 64 fell from 65.3 in Jun 2006 to 59.4 in Jun 2015. The labor force participation rate ages 16 to 24 fell from 66.7 in Jul 2006 to 60.0 in Jul 2014. The labor force participation rate ages 16 to 24 fell from 63.9 in Aug 2006 to 57.0 in Aug 2015. The labor force participation rate ages 16 to 24 fell from 59.1 in Sep 2006 to 53.5 in Sep 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Oct 2006 to 54.2 in Oct 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Nov 2006 to 53.6 in Nov 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 54.2 in Dec 2015. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 52.9 in Jan 2016. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 53.7 in Feb 2016. The labor force participation rate ages 16 to 24 fell from 58.4 in Mar 2006 to 53.9 in Mar 2016. The labor force participation rate ages 16 to 24 fell from 58.3 in Apr 2006 to 53.4 in Apr 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in May 2006 to 54.9 in May 2016. The labor force participation rate ages 16 to 24 fell from 65.3 in Jun 2006 to 59.2 in Jun 2016. The labor force participation rate ages 16 to 24 fell from 66.7 in Jul 2006 to 60.1 in Jul 2016. The labor force participation rate ages 16 to 24 fell from 63.9 in Aug 2006 to 57.5 in Aug 2016. The labor force participation rate ages 16 to 24 fell from 59.1 in Sep 2006 to 54.2 in Sep 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in Oct 2006 to 54.2 in Oct 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in Nov 2006 to 54.1 in Nov 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 54.0 in Dec 2016. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 53.6 in Jan 2017. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 54.1 in Feb 2017. The labor force participation rate ages 16 to 24 fell from 58.4 in Mar 2006 to 54.3 in Mar 2017. The labor force participation rate ages 16 to 24 fell from 58.4 in Mar 2006 to 54.3 in Mar 2017. The labor force participation rate ages 16 to 24 fell from 58.3 in Apr 2006 to 54.2 in Apr 2017. The labor force participation rate ages 16 to 24 fell from 59.7 in May 2006 to 54.7 in May 2017. The labor force participation rate ages 16 to 24 fell from 65.3 in Jun 2006 to 59.5 in Jun 2017. The labor force participation rate ages 16 to 24 fell from 66.7 in Jul 2006 to 60.6 in Jul 2017. The labor force participation rate ages 16 to 24 fell from 63.9 in Aug 2006 to 57.6 in Aug 2017. The labor force participation rate ages 16 to 24 fell from 59.1 in Sep 2006 to 55.1 in Sep 2017. The labor force participation rate ages 16 to 24 fell from 59.7 in Oct 2006 to 54.7 in Oct 2017. The labor force participation rate ages 16 to 24 fell from 59.7 in Nov 2006 to 53.8 in Nov 2017. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 53.2 in Dec 2017. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 53.9 in Jan 2018. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 54.4 in Feb 2018. The labor force participation rate ages 16 to 24 fell from 58.4 in Mar 2006 to 54.5 in Mar 2018. The labor force participation rate ages 16 to 24 fell from 58.3 in Apr 2006 to 53.7 in Apr 2018. The labor force participation rate ages 16 to 24 fell from 59.7 in May 2006 to 54.6 in May 2018. Many young people abandoned searches for employment, dropping from the labor force.

Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2018

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. The employment population ratio for ages 16 to 24 fell from 59.2 in Jul 2006 to 52.7 in Jul 2015. The employment population ratio for ages 16 to 24 fell from 57.2 in Aug 2006 to 50.8 in Aug 2015. The employment population ratio for ages 16 to 24 years fell from 52.9 in Sep 2006 to 47.6 in Sep 2015. The employment population ratio for ages 16 to 24 years fell from 53.6 in Oct 2006 to 48.5 in Oct 2015. The employment population ratio for ages 16 to 24 years fell from 53.7 in Nov 2006 to 48.1 in Nov 2015. The employment population ratio for ages 16 to 24 years fell from 54.3 in Dec 2006 to 48.7 in Dec 2015. The employment population ratio for ages 16 to 24 years fell from 51.7 in Jan 2006 to 47.2 in Jan 2016. The employment population ration for ages 16 to 24 years fell from 52.1 in Feb 2006 to 48.0 in Feb 2016. The employment population ratio for ages 16 to 24 fell from 52.4 in Mar 2006 to 48.3 in Mar 2016. The employment population ratio for ages 16 to 24 fell from 52.7 in Apr 2006 to 48.1 in Apr 2016. The employment population ratio for ages 16 to 24 fell from 53.6 in May 2006 to 49.1 in May 2016. The employment population ratio for ages 16 to 24 fell from 57.6 in Jun 2006 to 51.9 in Jun 2016. The employment population ratio for ages 16 to 24 fell from 59.2 in Jul 2006 to 53.2 in Jul 2016. The employment population ratio for ages 16 to 24 fell from 57.2 in Aug 2006 to 51.7 in Aug 2016. The employment population ratio for ages 16 to 24 fell from 52.9 in Sep 2006 to 48.7 in Sep 2016. The employment population ratio for ages 16 to 24 fell from 53.6 in Oct 2006 to 48.7 in Oct 2016. The employment population ratio for ages 16 to 24 fell from 53.7 in Nov 2006 to 49.0 in Nov 2016. The employment population ratio for ages 16 to 24 fell from 54.3 in Dec 2006 to 49.1 in Dec 2016. The employment population ratio for ages 16 to 24 fell from 51.7 in Jan 2006 to 47.9 in Jan 2017. The employment population ratio for ages 16 to 24 fell from 52.1 in Feb 2006 to 48.7 in Feb 2017. The employment population ratio for ages 16 to 24 fell from 52.4 in Mar 2006 to 49.5 in Mar 2017. The employment population ratio for ages 16 to 24 fell from 52.7 in Apr 2006 to 49.6 in Apr 2017. The employment population ratio for ages 16 to 24 fell from 53.6 in May 2006 to 49.9 in May 2017. The employment population ratio for ages 16 to 24 fell from 57.6 in Jun 2006 to 53.3 in Jun 2017. The employment population ratio for ages 16 to 24 fell from 59.2 in Jul 2006 to 54.8 in Jul 2017. The employment population ratio for ages 16 to 24 fell from 57.2 in Aug 2006 to 52.6 in Aug 2017. The employment population ratio for ages 16 to 24 fell from 52.9 in Sep 2006 to 50.2 in Sep 2017. The employment population ratio for ages 16 to 24 fell from 53.6 in Oct 2006 to 49.9 in Oct 2017. The employment population ratio for ages 16 to 24 fell from 53.7 in Nov 2006 to 49.0 in Nov 2017. The employment population ratio for ages 16 to 24 fell from 54.3 in Dec 2006 to 48.9 in Dec 2017. The employment population ratio for ages 16 to 24 fell from 51.7 in Jan 2006 to 48.6 in Jan 2018. The employment population ratio for ages 16 to 24 fell from 52.1 in Feb 2006 to 49.4 in Feb 2018. The employment population ratio for ages 16 to 24 fell from 52.4 in Mar 2006 to 50.1 in Mar 2018. The employment population ratio for ages 16 to 24 fell from 52.7 in Apr 2006 to 49.6 in Apr 2018. The employment population ratio for ages 16 to 24 fell from 53.6 in May 2006 to 49.9 in May 2018. Chart I-21D shows vertical drop during the global recession without recovery.

Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2018

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 for ages 16 to 24 increased from 2342 thousand in 2007 to 2467 thousand in 2015, decreasing to 2.211 million in 2016. The unemployment level for ages 16 to 24 increased from 2342 thousand in 2007 to 2467 thousand in 2015, decreasing to 2.211 million in 2016. The unemployment level decreased to 1.955 million in 2017. The unemployment level ages 16 to 24 years decreased from 2.254 million in May 2006 to 1.795 million in May 2018 or decrease by 0.459 million. This situation may persist for many years.

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

Year

Mar

Apr

May

Dec

Annual

2001

2253

2095

2171

2412

2371

2002

2822

2515

2568

2374

2683

2003

2601

2572

2838

2248

2746

2004

2588

2387

2684

2294

2638

2005

2520

2398

2619

2055

2521

2006

2216

2092

2254

2007

2353

2007

2096

2074

2203

2323

2342

2008

2347

2196

2952

2928

2830

2009

3371

3321

3851

3532

3760

2010

3748

3803

3854

3352

3857

2011

3520

3365

3628

3161

3634

2012

3294

3175

3438

3153

3451

2013

3261

3129

3478

2536

3324

2014

3002

2440

2831

2317

2853

2015

2524

2175

2633

2114

2467

2016

2160

2037

2227

1859

2211

2017

1842

1759

1829

1640

1955

2018

1705

1552

1795

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 2018. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013-2014 with recent marginal improvement in 2015-2017 alternating with deterioration.

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2018

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. The rate of youth unemployment fell to 11.6 percent in 2015, 10.4 percent in 2016 and 9.2 percent in 2017. 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 2006 to 13.7 in Jun 2015. The rate of youth unemployment increased from 10.8 in Jul 2007 to 12.2 in Jul 2015. The rate of youth unemployment increased from 10.5 in Aug 2007 to 10.9 in Aug 2015. The rate of youth unemployment decreased from 11.0 in Sep 2007 to 10.9 in Sep 2015. The rate of youth unemployment increased from 10.3 in Oct 2007 to 10.6 in Oct 2015. The rate of youth unemployment increased from 10.3 in Nov 2007 to 10.4 in Nov 2015. The rate of youth unemployment decreased from 10.7 in Dec 2007 to 10.1 in Dec 2015. The rate of youth unemployment decreased from 10.9 in Jan 2007 to 10.8 in Jan 2016. The rate of youth unemployment increased from 10.3 in Feb 2007 to 10.8 in Feb 2016. The rate of youth unemployment increased from 9.7 in Mar 2007 to 10.4 in Mar 2016. The rate of youth unemployment increased from 9.7 in Apr 2007 to 9.9 in Apr 2016. The rate of youth unemployment increased from 10.2 in May 2007 to 10.6 in May 2016. The rate of youth unemployment increased from 12.0 in Jun 2007 to 12.3 in Jun 2016. The rate of youth unemployment increased from 10.8 in Jul 2007 to 11.5 in Jul 2016. The rate of youth unemployment fell from 10.5 in Aug 2007 to 10.1 in Aug 2016. The rate of youth unemployment fell from 11.0 in Sep 2007 to 10.2 in Sep 2016. The rate of youth unemployment fell from 10.3 in Oct 2007 to 10.1 in Oct 2016. The rate of youth unemployment fell from 10.3 in Nov 2007 to 9.3 in Nov 2016. The rate of youth unemployment fell from 10.7 in Dec 2007 to 9.0 in Dec 2016. The rate of youth unemployment fell from 10.9 in Jan 2007 to 10.7 in Jan 2017. The rate of youth unemployment fell from 10.3 in Feb 2007 to 10.1 in Feb 2017. The rate of youth unemployment fell from 9.7 in Mar 2007 to 8.9 in Mar 2017. The rate of youth unemployment fell from 9.7 in Apr 2007 to 8.5 in Apr 2017. The rate of youth unemployment fell from 10.2 in May 2007 to 8.8 in May 2017. The rate of youth unemployment fell from 12.0 in Jun 2007 to 10.5 in Jun 2017. The rate of youth unemployment fell from 10.8 in Jul 2007 to 9.6 in Jul 2017. The rate of youth unemployment fell from 10.5 in Aug 2007 to 8.8 in Aug 2017. The rate of youth unemployment fell from 10.8 in Jul 2007 to 9.6 in Jul 2017. The rate of youth unemployment fell from 10.5 in Aug 2007 to 8.8 in Aug 2017. The rate of youth unemployment fell from 11.0 in Sep 2007 to 8.9 in Sep 2017. The rate of youth unemployment fell from 10.3 in Oct 2007 to 8.7 in Oct 2017. The rate of youth unemployment fell from 10.3 in Nov 2007 to 9.1 in Nov 2017. The rate of youth unemployment fell from 10.7 in Dec 2007 to 8.1 in Dec 2017. The rate of youth unemployment fell from 10.9 in Jan 2007 to 9.9 in Jan 2018, decreasing to 9.2 percent in Feb 2018. The rate of youth unemployment fell to 8.2 in Mar 2018, decreasing to 7.6 in Apr 2018. The rate of youth unemployment fell to 8.2 in Mar 2018, decreasing to 7.6 in Apr 2018. The rate of youth unemployment increased to 8.6 in May 2018. 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

Feb

Mar

Apr

May

Dec

Annual

2001

10.3

10.2

9.6

10.0

11.0

10.6

2002

12.5

12.9

11.6

11.6

10.9

12.0

2003

12.7

12.2

12.0

13.0

10.5

12.4

2004

12.3

12.1

11.1

12.2

10.5

11.8

2005

13.0

11.7

11.2

11.9

9.4

11.3

2006

11.3

10.3

9.7

10.2

9.1

10.5

2007

10.3

9.7

9.7

10.2

10.7

10.5

2008

11.8

11.1

10.3

13.3

13.7

12.8

2009

16.4

16.1

15.8

18.0

17.5

17.6

2010

19.2

18.4

18.5

18.4

16.7

18.4

2011

18.2

17.2

16.5

17.5

15.5

17.3

2012

17.0

16.0

15.4

16.3

15.2

16.2

2013

16.7

15.9

15.1

16.4

12.3

15.5

2014

14.9

14.3

11.9

13.4

11.2

13.4

2015

12.2

12.3

10.7

12.3

10.1

11.6

2016

10.8

10.4

9.9

10.6

9.0

10.4

2017

10.1

8.9

8.5

8.8

8.1

9.2

2018

9.2

8.2

7.6

8.6

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 2018. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels because of low growth of GDP. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E. Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2018

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 2018. 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 rate of youth unemployment increased from 10.8 in Jul 2007 to 12.2 in Jul 2015. The rate of youth unemployment increased from 10.5 in Aug 2007 to 10.9 in Aug 2015. The rate of youth unemployment decreased from 11.0 in Sep 2007 to 10.9 in Sep 2015. The rate of youth unemployment increased from 10.3 in Oct 2007 to 10.6 in Oct 2015, decreasing to 10.4 in Nov 2015. The rate of youth unemployment decreased to 10.1 in Dec 2015. The rate of youth unemployment stood at 10.8 in Jan 2016, 10.8 in Feb 2016, 10.4 in Mar 2016 and 9.9 in Apr 2016. The rate of youth unemployment increased to 10.6 in May 2016 and 12.3 in Jun 2016. The rate of youth unemployment fell to 11.5 in Jul 2016, decreasing to 10.1 in Aug 2016. The rate of youth unemployment increased to 10.2 in Sep 2016, decreasing to 10.1 in Oct 2016 and 9.3 in Nov 2016. The rate of youth unemployment decreased to 9.0 in Dec 2016, increasing to 10.7 in Jan 2017. The rate of youth unemployment fell to 10.1 in Feb 2017, decreasing to 8.9 in Mar 2017. The rate of youth unemployment fell to 8.5 in Apr 2017, increasing to 8.8 in May 2017. The rate of youth unemployment increased to 10.5 percent in Jun 2017, decreasing to 9.6 in Jul 2017. The rate of youth unemployment decreased to 8.8 percent in Aug 2017, increasing to 8.9 percent in Sep 2017. The rate of youth unemployment fell to 8.7 percent in Oct 2017, increasing to 9.1 percent in Nov 2017. The rate of youth unemployment fell to 8.1 percent in Dec 2017, increasing to 9.9 percent in Jan 2018. The rate of youth unemployment decreased to 9.2 percent in Feb 2018, decreasing to 8.2 percent in Mar 2018. The rate of youth unemployment decreased to 7.6 percent in Apr 2018. The rate of youth unemployment increased to 8.6 percent in May 2018. he 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 3.8 percent from IQ1983 to IIQ1991 compared with 2.2 percent on average during the first 35 quarters of expansion from IIIQ2009 to IQ2018. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.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 dividing 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 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/twenty-two-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. 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 of manufacturing at average 3.2 percent per year from Apr 1919 to Apr 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 154.7937 in Apr 2018. The actual index NSA in Apr 2018 is 104.3625, which is 32.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Apr 2018. Using trend growth of 2.0 percent per year, the index would increase to 135.5768 in Apr 2018. The output of manufacturing at 104.3625 in Apr 2018 is 23.0 percent below trend under this alternative calculation.

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2017

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 level of unemployed ages 45 years and over increased from 2.053 million in Jul 2007 to 3.083 million in Jul 2014 and at 2.666 million in Jul 2015 is 30.0 percent higher than in Jul 2007. The level of unemployed ages 45 years and over increased from 1.956 million in Aug 2007 to 3.037 million in Aug 2014 and at 2.693 million in Aug 2015 is 37.7 higher than in Aug 2007. The level of unemployed ages 45 years and over increased from 1.854 million in Sep 2007 to 2.640 million in Sep 2015 and at 2.388 million in Sep 2015 is 28.8 percent higher than in Sep 2007. The level of unemployment ages 45 years and over increased from 1.885 million in Oct 2007 to 2.606 million in Oct 2014 and at 2.290 million in Oct 2015 is 21.5 percent higher than in Oct 2007. The level of unemployment ages 45 years and over increased from 1.925 million in Nov 2007 to 2.829 million in Nov 2014 and at 2.349 million in Nov 2015 is 22.0 percent higher than in Nov 2007. The level of unemployment ages 45 years and over increased from 2.120 million in Dec 2007 to 2.667 million in Dec 2014 and at 2.317 million in Dec 2015 is 9.3 percent higher than in Dec 2007. The level of unemployment ages 45 and over increased from 2.155 million in Jan 2007 to 3.077 million in Jan 2015 and at 2.736 million in Jan 2016 is 27.0 percent higher than in Jan 2007. The level of unemployment ages 45 and over increased from 2.138 million in Feb 2007 to 2.991 million in Feb 2015 and at 2.744 million in Feb 2016 is 28.3 percent higher than in Feb 2007. The level of unemployment ages 45 and over increased from 2.031 million in Mar 2007 to 2.724 million in Mar 2015 and at 2.747 million in Mar 2016 is 35.3 percent higher than in Mar 2007. The level of unemployment ages 45 and over increased from 1.871 million in Apr 2007 to 2.579 million in Apr 2015 and at 2.410 million in Apr 2016 is 28.8 percent higher than in Apr 2007. The level of unemployment ages 45 and over increased from 1.803 million in May 2007 to 2.457 million in May 2015 and at 2.190 million in May 2016 is 21.5 percent higher than in May 2007. The level of unemployment ages 45 and over increased from 1.805 million in Jun 2007 to 2.359 million in Jun 2015 and at 2.345 million in Jun 2016 is 29.9 percent higher than in Jun 2007. The level of unemployment ages 45 and over increased from 2.053 million in Jul 2007 to 2.666 million in Jul 2015 and at 2.619 million in Jul 2016 is 27.6 percent higher than in Jul 2007. The level of unemployment ages 45 and over increased from 1.956 million in Aug 2007 to 2.693 million in Aug 2015 and at 2.565 million in Aug 2016 is 31.1 percent higher than in Aug 2007. The level of unemployment ages 45 and over increased from 1.854 million in Sep 2007 to 2.388 million in Sep 2015 and at 2.414 million in Sep 2016 is 30.2 percent higher than in Sep 2007. The level of unemployment ages 45 and over increased from 1.885 million in Oct 2007 to 2.290 million in Oct 2015 and at 2.337 million in Oct 2016 is 24.0 percent higher than in Oct 2007. The level of unemployment ages 45 and over increased from 1.925 million in Nov 2007 to 2.349 million in Nov 2015 and at 2.355 million in Nov 2016 is 22.3 percent higher than in Nov 2007. The level of unemployment ages 45 and over increased from 2.120 million in Dec 2007 to 2.317 million in Dec 2015 and at 2.360 million in Dec 2016 is 11.3 percent higher than in Dec 2007. The level of unemployment ages 45 and over increased from 2.155 million in Jan 2007 to 2.736 million in Jan 2016 and at 2.585 million in Jan 2017 is 20.0 percent higher than in Jan 2007. The level of unemployment ages 45 and over increased from 2.138 million in Feb 2007 to 2.744 million in Feb 2016 and at 2.493 million in Feb 2017 is 16.6 percent higher than in Feb 2007. The level of unemployment ages 45 and over increased from 2.031 million in Mar 2007 to 2.747 million in Mar 2016 and at 2.413 million in Mar 2017 is 18.8 percent higher than in Mar 2007. The level of unemployment ages 45 and over increased from 2.031 million in Mar 2007 to 2.747 million in Mar 2016 and at 2.413 million in Mar 2017 is 18.8 percent higher than in Mar 2007. The level of unemployment ages 45 and over increased from 1.871 million in Apr 2007 to 2.410 million in Apr 2016 and at 2.202 million in Apr 2017 is 17.7 percent higher than in Apr 2007. The level of unemployment ages 45 and over increased from 1.803 million in May 2007 to 2.190 million in May 2016 and at 2.052 million in May 2017 is 13.8 percent higher than in May 2007. The level of unemployment ages 45 and over increased from 1.805 million in Jun 2007 to 2.345 million in Jun 2016 and at 2.256 million in Jun 2017 is 25.0 percent higher than in Jun 2007. The level of unemployment ages 45 and over increased from 2.053 million in Jul 2007 to 2.619 million in Jul 2016 and at 2.335 million in Jul 2017 is 13.7 percent higher than in Jul 2007. The level of unemployment ages 45 and over increased from 1.956 million in Aug 2007 to 2.565 million in Aug 2016 and at 2.444 million in Aug 2017 is 24.9 percent higher than in Aug 2007. The level of unemployment ages 45 and over increased from 1.854 million in Sep 2007 to 2.414 million in Sep 2016 and at 2.140 million in Sep 2017 is 15.4 percent higher than in Sep 2007. The level of unemployment ages 45 and over increased from 1.885 million in Oct 2007 to 2.337 million in Oct 2016 and at 1.899 million in Oct 2017 is 0.7 percent higher than in Oct 2007. The level of unemployment ages 45 and over increased from 1.925 million in Nov 2007 to 2.355 million in Nov 2016 and at 1.958 million in Nov 2017 is 1.7 percent higher than in Nov 2007. The level of unemployment ages 45 and over increased from 2.120 million in Dec 2007 to 2.360 million in Dec 2016 and at 2.079 million in Dec 2017 is 1.9 percent lower than in Dec 2007. The level of unemployment ages 45 and over increased from 2.155 million in Jan 2007 to 2.585 million in Jan 2017 and at 2.300 million in Jan 2018 is 6.7 percent higher than in Jan 2007. The level of unemployment ages 45 and over increased from 2.138 million in Feb 2007 to 2.493 million in Feb 2017 and at 2.354 million in Feb 2018 is 10.1 percent higher than in Feb 2007. The level of unemployment ages 45 and over increased from 2.031 million in Mar 2007 to 2.413 million in Mar 2017 and at 2.266 million in Mar 2018 is 11.6 percent higher than in Mar 2007. The level of unemployment ages 45 and over increased from 1.871 million in Apr 2007 to 2.202 million in Apr 2017 and at 1.937 million in Apr 2018 is 3.5 percent higher than in Apr 2007. The level of unemployment ages 45 and over increased from 1.803 million in May 2007 to 2.252 million in May 2017 and at 1.174 million in May 2018 is 1.6 percent lower than in May 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. 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 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.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 dividing 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 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/twenty-two-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. 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 of manufacturing at average 3.2 percent per year from Apr 1919 to Apr 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 154.7937 in Apr 2018. The actual index NSA in Apr 2018 is 104.3625, which is 32.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Apr 2018. Using trend growth of 2.0 percent per year, the index would increase to 135.5768 in Apr 2018. The output of manufacturing at 104.3625 in Apr 2018 is 23.0 percent below trend under this alternative calculation.

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

Year

Mar

Apr

May

Dec

Annual

2000

1291

1062

1074

1217

1249

2001

1533

1421

1259

1901

1576

2002

2138

2101

1999

2210

2114

2003

2485

2287

2112

2130

2253

2004

2354

2160

2025

2086

2149

2005

2126

1939

1844

1963

2009

2006

1881

1843

1784

1794

1848

2007

2031

1871

1803

2120

1966

2008

2326

2104

2095

3485

2540

2009

4518

4172

4175

4960

4500

2010

5194

4770

4565

4762

4879

2011

4748

4373

4356

4182

4537

2012

4390

4037

4083

3927

4133

2013

3929

3689

3605

3378

3719

2014

3394

3006

2913

2667

3000

2015

2724

2579

2457

2317

2574

2016

2747

2410

2190

2360

2485

2017

2413

2202

2052

2079

2238

2018

2266

1937

1774

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

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

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2018

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 (https://www.census.gov/foreign-trade/index.html). 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 (https://cmpassocregulationblog.blogspot.com/2018/05/dollar-strengthening-world-inflation.htm). The Census Bureau revised data for 2018, 2017, 2016, 2015, 2014 and 2013. Exports increased 0.3 percent in Apr 2018 while imports decreased 0.2 percent. The trade deficit decreased from $47,210 million in Mar 2018 to $46,199 million in Apr 2018. The trade deficit deteriorated to $45,695 million in Feb 2016, improving to $37,350 million in Mar 2016. The trade deficit deteriorated to $38,192 million in Apr 2016, deteriorating to $40,170 million in May 2016 and $43,737 million in Jun 2016. The trade deficit improved to $41,136 million in Jul 2016, moving to $41,635 million in Aug 2016. The trade deficit improved to $39,000 million in Sep 2016, deteriorating to $42,644 million in Oct 2016. The trade deficit deteriorated to $46,127 million in Nov 2016, improving to $44,100 million in Dec 2016. The trade deficit deteriorated to $46,879 million in Jan 2017, improving to $44,171 million in Feb 2017. The trade deficit deteriorated to $43,909 million in Mar 2017 and $46,074 million in Apr 2017, improving to $45,823 million in May 2017. The trade deficit improved to $44,803 million in Jun 2017 and to $44,221 million in Jul 2017. The trade deficit improved to $44,163 million in Aug 2017, deteriorating to $44,407 million in Sep 2017. The trade deficit deteriorated to $49,986 million in Oct 2017, deteriorating to $48,952 million in Nov 2017. The trade deficit deteriorated to 51,889 million in Dec 2017, deteriorating to $52,881 million in Jan 2018. The trade deficit deteriorated to $55,356 million in Feb 2018, improving to $47,210 million in Mar 2018. The trade deficit improved to $46,199 million in Apr 2018.

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

Trade Balance

Exports

Month ∆%

Imports

Month ∆%

2016

January

-42,217

179,028

-2.0

221,245

-1.3

February

-45,695

180,853

1.0

226,547

2.4

March

-37,350

180,354

-0.3

217,704

-3.9

April

-38,192

182,472

1.2

220,664

1.4

May

-40,170

183,487

0.6

223,657

1.4

June

-43,737

184,317

0.5

228,054

2.0

July

-41,136

186,188

1.0

227,324

-0.3

August

-41,635

187,987

1.0

229,622

1.0

September

-39,000

188,868

0.5

227,868

-0.8

October

-42,644

186,780

-1.1

229,424

0.7

November

-46,127

185,378

-0.8

231,505

0.9

December

-44,100

190,132

2.6

234,232

1.2

2017

January

-46,879

191,430

0.7

238,309

1.7

February

-44,171

192,340

0.5

236,510

-0.8

March

-43,909

192,536

0.1

236,446

0.0

April

-46,074

192,194

-0.2

238,268

0.8

May

-45,823

192,772

0.3

238,595

0.1

June

-44,803

194,778

1.0

239,580

0.4

July

-44,221

195,160

0.2

239,382

-0.1

August

-44,163

195,594

0.2

239,757

0.2

September

-44,407

198,352

1.4

242,760

1.3

October

-46,986

198,629

0.1

245,615

1.2

November

-48,952

202,295

1.8

251,246

2.3

December

-51,889

204,992

1.3

256,881

2.2

2018

January

-52,881

202,506

-1.2

255,387

-0.6

February

-55,536

206,077

1.8

261,613

2.4

March

-47,210

210,660

2.2

257,870

-1.4

April

-46,199

211,245

0.3

257,444

-0.2

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

-468,262

13.7

693,104

-4.9

1,161,366

1.8

2003

-532,350

13.7

724,771

4.6

1,257,121

8.2

2004

-654,829

23.0

814,875

12.4

1,469,703

16.9

2005

-772,374

18.0

901,082

10.6

1,673,456

13.9

2006

-827,970

7.2

1,025,969

13.9

1,853,939

10.8

2007

-808,765

-2.3

1,148,197

11.9

1,956,962

5.6

2008

-816,200

0.9

1,287,441

12.1

2,103,641

7.5

2009

-503,583

-38.3

1,056,042

-18.0

1,559,625

-25.9

2010

-635,365

26.2

1,278,493

21.1

1,913,858

22.7

2011

-725,447

14.2

1,482,507

16.0

2,207,954

15.4

2012

-730,446

0.7

1,545,821

4.3

2,276,267

3.1

2013

-689,470

-5.6

1,578,517

2.1

2,267,987

-0.4

2014

-734,482

6.5

1,621,874

2.7

2,356,356

3.9

2015

-745,483

1.5

1,503,328

-7.3

2,248,811

-4.6

2016

-736,577

-1.2

1,451,024

-3.5

2,187,600

-2.7

2017

-795,690

8.0

1,546,273

6.6

2,341,963

7.1

Source: US Census Bureau

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

There is recent sharp deterioration of the US trade balance and the three-month moving average in Chart IIA-1 of the US Census Bureau.

Chart IIA-1A, US, International Trade Balance, Exports and Imports of Goods and Services and Three-Month Moving Average, USD Billions

Source: US Census Bureau

https://www.census.gov/foreign-trade/data/ustrade.jpg

Chart IIA-1A 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.

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

Source: US Census Bureau

https://www.census.gov/foreign-trade/data/ustrade.jpg

Table IIA-2B provides the US international trade balance, exports and imports of goods and services on an annual basis from 1992 to 2017. 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 $111.9 billion in IVQ2016 to $126.5 billion in IVQ2017 (https://www.bea.gov/international/index.htm). The current account deficit seasonally adjusted at annual rate decreased from 2.4 percent of GDP in IVQ2016 to 2.1 percent of GDP in IIIQ2017, increasing to 2.6 percent of GDP in IVQ2017. 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). There is still a major challenge in the combined deficits in current account and in federal budgets. The final rows of Table IIA-2B show marginal improvement of the trade deficit from $549,699 million in 2011 to lower $537,408 million in 2012 with exports growing 4.3 percent and imports 3.0 percent. The trade balance improved further to deficit of $461,135 million in 2013 with growth of exports of 3.4 percent while imports virtually stagnated. The trade deficit deteriorated in 2014 to $489,584 million with growth of exports of 3.6 percent and of imports of 4.0 percent. The trade deficit deteriorated in 2015 to $498,525 million with decrease of exports of 4.6 percent and decrease of imports of 3.5 percent. The trade deficit deteriorated in 2016 to $502.001 million with decrease of exports of 2.2 percent and decrease of imports of 1.7 percent. The trade deficit deteriorated in 2017 to $552,277 million with growth of exports of 6.1 percent and of imports of 6.8 percent. Growth and commodity shocks under alternating inflation waves (https://cmpassocregulationblog.blogspot.com/2018/05/dollar-strengthening-world-inflation.htm) 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

22,432

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

-495,225

1,853,038

17.1

2,348,263

19.4

2011

-549,699

2,125,947

14.7

2,675,646

13.9

2012

-537,408

2,218,354

4.3

2,755,762

3.0

2013

-461,135

2,294,199

3.4

2,755,334

0.0

2014

-489,584

2,376,657

3.6

2,866,241

4.0

2015

-498,525

2,266,691

-4.6

2,765,216

-3.5

2016

-502,001

2,215,844

-2.2

2,717,846

-1.7

2017

-552,277

2,351,072

6.1

2,903,349

6.8

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 Apr 2018. 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. There are additional effects for revaluation of the dollar with the Fed orienting interest rate increases while the European Central Bank and the Bank of Japan determine negative nominal interest rates.

Chart IIA-2, US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-Apr 2018

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 Apr 2018. 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.

Chart IIA-3, US, Exports SA, Monthly, Millions of Dollars Jan 1992-Apr 2018

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 Mar 2018. 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.

Chart IIA-4, US, Imports SA, Monthly, Millions of Dollars Jan 1992-Apr 2018

Source: US Census Bureau

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

There is deterioration of the US trade balance in goods in Table IIA-3 from deficit of $67,288 million in Apr 2017 to deficit of $68,265 million in Apr 2018. The nonpetroleum deficit increased $1349 million while the petroleum deficit decreased $271 million. Total exports of goods increased 11.4 percent in Apr 2018 relative to a year earlier while total imports increased 7.9 percent. Nonpetroleum exports increased 8.9 percent from Apr 2017 to Apr 2018 while nonpetroleum imports increased 6.6 percent. Petroleum imports increased 24.7 percent.

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

Apr 2018

Apr 2017

∆%

Total Balance

-68,265

-67,288

Petroleum

-4,864

-5,135

Non-Petroleum

-62,471

-61,122

Total Exports

141,248

126,832

11.4

Petroleum

14,068

10,046

40.0

Non-Petroleum

126,558

116,259

8.9

Total Imports

209,513

194,120

7.9

Petroleum

18,932

15,180

24.7

Non-Petroleum

189,029

177,381

6.6

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-Apr 2018 and Jan-Apr 2017 are in Table IIA-4. The rate of growth of exports was 8.8 percent and 9.4 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that increased 1.8 percent and of mineral fuels that increased 31.6 percent both because prices of raw materials and commodities increase and fall recurrently because of shocks of risk aversion and portfolio reallocations. The US exports a growing amount of crude oil, increasing 37.7 percent in cumulative Jan-Apr 2018 relative to a year earlier. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports increased 6.7 percent while manufactured imports increased 9.8 percent. Significant part of the US trade imbalance originates in imports of mineral fuels increasing 10.9 percent and petroleum increasing 12.2 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-Apr 2018 $ Millions

Jan-Apr 2017 $ Millions

∆%

Exports

540,150

496,456

8.8

Manufactured

377,279

353,441

6.7

Agricultural
Commodities

47,530

46,698

1.8

Mineral Fuels

55,447

42,137

31.6

Petroleum

42,746

31,045

37.7

Imports

804,539

735,472

9.4

Manufactured

689,709

628,377

9.8

Agricultural
Commodities

44,602

40,656

9.7

Mineral Fuels

72,271

65,157

10.9

Petroleum

67,706

60,339

12.2

Source: US Census Bureau

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

The current account of the US balance of payments is in Table VI-3A for IVQ2016 and IVQ2017. The Bureau of Economic Analysis analyzes as follows (https://www.bea.gov/newsreleases/international/transactions/2018/pdf/trans417.pdf):

“The U.S. current-account deficit increased to $128.2 billion (preliminary) in the fourth quarter of 2017 from $101.5 billion (revised) in the third quarter, according to statistics released by the Bureau of Economic Analysis (BEA). The deficit was 2.6 percent of current-dollar gross domestic product (GDP) in the fourth quarter, up from 2.1 percent in the third quarter.”

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 $111.9 billion in IVQ2016 to $126.5 billion in IVQ2017. The current account deficit seasonally adjusted at annual rate decreased from 2.4 percent of GDP in IVQ2016 to 2.1 percent of GDP in IIIQ2017, increasing to 2.6 percent of GDP in IVQ2017. 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). There is still a major challenge in the combined deficits in current account and in federal budgets.

Table VI-3A, US, Balance of Payments, Millions of Dollars NSA

IVQ2016

IVQ2017

Difference

Goods Balance

-192,971

-215,103

-22,132

X Goods

379,029

405,539

7.0 ∆%

M Goods

-572,000

-623,642

9.0 ∆%

Services Balance

60,996

62,041

1,045

X Services

188,320

199,460

5.9 ∆%

M Services

-127,325

-137,419

7.9 ∆%

Balance Goods and Services

-131,975

-153,062

-21,087

Exports of Goods and Services and Income Receipts

815,899

889,568

Imports of Goods and Services and Income Payments

-927,774

-1,016,026

Current Account Balance

-111,875

-126,458

-14,583

% GDP

IVQ2016

IVQ2017

IIIQ2017

2.4

2.6

2.1

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+Ï„)st+Ï„dÏ„ (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+Ï„, of the future primary surpluses st+Ï„, which are equal to Tt+Ï„Gt+Ï„ 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+Ï„. 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 VI-3B 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 $5094 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 72.6 percent of GDP in 2013 (http://www.cbo.gov/). 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 CBO long-term budget on Mar 27, 2017, projects US federal debt at 150.0 percent of GDP in 2047 (Congressional Budget Office, The 2017 Long-term Budget Outlook. Washington, DC, Mar 30, 2017 https://www.cbo.gov/publication/52480).

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

2007

2008

2009

2010

2011

Goods &
Services

-705

-709

-384

-495

-549

Primary Income

85

130

115

168

211

Secondary Income

-91

-102

-104

-104

-107

Current Account

-711

-681

-373

-431

-445

NGDP

14478

14719

14419

14964

15518

Current Account % GDP

-4.9

-4.6

-2.6

-2.9

-2.9

NIIP

-1279

-3995

-2628

-2512

-4455

US Owned Assets Abroad

20705

19423

19426

21767

22209

Foreign Owned Assets in US

21984

23418

22054

24279

26664

NIIP % GDP

-8.8

-27.1

-18.2

-16.8

-28.7

Exports
Goods,
Services and
Income

2559

2742

2283

2625

2983

NIIP %
Exports
Goods,
Services and
Income

-50

-145

-115

-95

-149

DIA MV

5858

3707

4945

5486

5215

DIUS MV

4134

3091

3619

4099

4199

Fiscal Balance

-161

-459

-1413

-1294

-1300

Fiscal Balance % GDP

-1.1

-3.1

-9.8

-8.7

-8.5

Federal   Debt

5035

5803

7545

9019

10128

Federal Debt % GDP

35.2

39.3

52.3

60.9

65.9

Federal Outlays

2729

2983

3518

3457

3603

∆%

2.8

9.3

17.9

-1.7

4.2

% GDP

19.1

20.2

24.4

23.4

23.4

Federal Revenue

2568

2524

2105

2163

2303

∆%

6.7

-1.7

-16.6

2.7

6.5

% GDP

17.9

17.1

14.6

14.6

15.0

2012

2013

2014

2015

2016

Goods &
Services

-537

-462

-490

-500

-505

Primary Income

207

206

210

181

173

Secondary Income

-97

-94

-94

-115

-120

Current Account

-426

-350

-374

-434

-452

NGDP

16155

16692

17428

18121

18625

Current Account % GDP

-2.6

-2.1

-2.1

-2.4

-2.4

NIIP

-4518

-5373

-6980

-7493

-8318

US Owned Assets Abroad

22562

24145

24832

23352

23849

Foreign Owned Assets in US

27080

29517

31813

30846

32168

NIIP % GDP

-28.0

-32.2

-40.1

-41.3

-44.7

Exports
Goods,
Services and
Income

3096

3212

3333

3173

3157

NIIP %
Exports
Goods,
Services and
Income

-146

-167

-209

-236

-263

DIA MV

5969

7121

7189

6999

7375

DIUS MV

4662

5815

6370

6701

7569

Fiscal Balance

-1087

-680

-485

-439

-585

Fiscal Balance % GDP

-6.8

-4.1

-2.8

-2.4

-3.2

Federal   Debt

11281

11983

12780

13117

14168

Federal Debt % GDP

70.4

72.6

74.2

73.3

77.0

Federal Outlays

3537

3455

3506

3688

3853

∆%

-1.8

-2.3

1.5

5.2

4.5

% GDP

22.1

20.9

20.4

20.6

20.9

Federal Revenue

2450

2775

3022

3250

3268

∆%

6.4

13.3

8.9

7.6

0.5

% GDP

15.3

16.8

17.5

18.2

17.8

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/

https://www.cbo.gov/about/products/budget-economic-data#6

https://www.cbo.gov/about/products/budget_economic_data#3

https://www.cbo.gov/about/products/budget-economic-data#2

https://www.cbo.gov/about/products/budget_economic_data#2 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 at 2.4 percent in IVQ2016 stabilizes to 2.4 percent of GDP in IQ2017. The deficit increases to 2.6 percent in IIQ2017. The current account deficit decreased to 2.1 percent in IIIQ2017. The current account deficit increased to 2.6 percent in IVQ2017. The absolute value of the net international investment position decreases from minus $8.3 trillion in IVQ2016 to minus $8.1 trillion in IQ2017. The absolute value of the net international investment position decreases to minus $8.0 trillion in IIQ2017. The absolute value of the net international investment position decreased to $7.7 trillion in IIIQ2017. The absolute value of the net international investment position stabilizes at $7.8 trillion in IVQ2017. The BEA explains as follows (https://www.bea.gov/newsreleases/international/intinv/2018/pdf/intinv417.pdf):

“The U.S. net international investment position decreased to −$7,845.8 billion (preliminary) at the end of the fourth quarter from −$7,739.7 billion (revised) at the end of the third quarter, according to statistics released by the Bureau of Economic Analysis (BEA). The $106.1 billion decrease reflected a $727.2 billion increase in U.S. assets and an $833.3 billion increase in U.S. liabilities (table 1).”

The BEA explains further (https://www.bea.gov/newsreleases/international/intinv/2018/pdf/intinv417.pdf): “

“The $106.1 billion decrease in the net investment position reflected net financial transactions of –$52.4 billion and net other changes in position, such as price and exchange-rate changes, of –$53.8 billion (table A). The net investment position decreased 1.4 percent in the fourth quarter, compared with an increase of 3.3 percent in the third quarter. The net investment position decreased an average of 5.0 percent per quarter from the first quarter of 2011 through the second quarter of 2017.

“U.S. assets increased $727.2 billion to $27,632.8 billion at the end of the fourth quarter, mostly reflecting increases in portfolio investment and direct investment assets.

• Assets excluding financial derivatives increased $809.8 billion to $26,010.4 billion. The increase resulted from other changes in position of $658.8 billion and financial transactions of $151.0 billion (table A). Other changes in position mostly reflected (1) foreign equity price increases that raised the value of portfolio investment and direct investment equity assets and (2) the appreciation of major foreign currencies against the U.S. dollar that raised the value of foreign currency-denominated assets in dollar terms. Financial transactions mostly reflected net acquisition of portfolio investment debt securities and direct investment equity assets.

• Financial derivatives decreased $82.6 billion to $1,622.5 billion, mostly in single-currency interest rate contracts and foreign exchange contracts.”

“U.S. liabilities increased $833.3 billion to $35,478.6 billion at the end of the fourth quarter, mostly reflecting increases in portfolio investment and direct investment liabilities.

· Liabilities excluding financial derivatives increased $910.5 billion to $33,884.4 billion. The increase resulted from other changes in position of $706.3 billion and financial transactions of $204.2 billion (table A). Other changes in position mostly reflected U.S. equity price increases that raised the value of portfolio investment and direct investment equity liabilities. Financial transactions reflected net incurrence of liabilities in all major investment categories.

· Financial derivatives decreased $77.1 billion to $1,594.2 billion, mostly in single-currency interest rate contracts and foreign exchange contracts.”

Table VI-3C, US, Current Account, Net International Investment Position and Direct Investment, Dollar Billions, NSA

IVQ2016

IQ2017

IIQ2017

IIIQ2017

IVQ2017

Goods &
Services

-132

-113

-155

-147

-153

Primary

Income

51

49

51

59

58

Secondary Income

-31

-26

-31

-26

-31

Current Account

-112

-90

-136

-114

-126

Current Account % GDP SA

-2.4

-2.4

-2.6

-2.1

-2.6

NIIP

-8318

-8092

-8004

-7740

-7846

US Owned Assets Abroad

23849

24933

25853

26906

27633

Foreign Owned Assets in US

-32168

-33025

-33857

-34645

-35479

DIA MV

7375

7895

8125

8595

8863

DIA MV Equity

6172

6609

6909

7347

7623

DIUS MV

7569

7952

8135

8454

8871

DIUS MV Equity

5784

6153

6341

6630

7055

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-3C of the US Bureau of Economic Analysis provides the quarterly and annual US net international investment position (NIIP) NSA in billion dollars. The NIIP deteriorated in 2008, improving in 2009-2011 followed by deterioration after 2012. There is improvement in 2017.

Chart VI-3C, US Net International Investment Position, NSA, Billion US Dollars

Source: Bureau of Economic Analysis

http://www.bea.gov/newsreleases/international/intinv/intinvnewsrelease.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 Jun 7, 2018, at 1.70 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 1970s (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/2017/01/rules-versus-discretionary-authorities.html 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 1.70 percent on Jun 7, 2018. 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. The Chair of the Board of Governors of the Federal Reserve System, Janet L. Yellen, stated on Jul 10, 2015 that (http://www.federalreserve.gov/newsevents/speech/yellen20150710a.htm):

“Based on my outlook, I expect that it will be appropriate at some point later this year to take the first step to raise the federal funds rate and thus begin normalizing monetary policy. But I want to emphasize that the course of the economy and inflation remains highly uncertain, and unanticipated developments could delay or accelerate this first step. I currently anticipate that the appropriate pace of normalization will be gradual, and that monetary policy will need to be highly supportive of economic activity for quite some time. The projections of most of my FOMC colleagues indicate that they have similar expectations for the likely path of the federal funds rate. But, again, both the course of the economy and inflation are uncertain. If progress toward our employment and inflation goals is more rapid than expected, it may be appropriate to remove monetary policy accommodation more quickly. However, if progress toward our goals is slower than anticipated, then the Committee may move more slowly in normalizing policy.”

There is essentially the same view in the Testimony of Chair Yellen in delivering the Semiannual Monetary Policy Report to the Congress on Jul 15, 2015 (http://www.federalreserve.gov/newsevents/testimony/yellen20150715a.htm). The FOMC (Federal Open Market Committee) raised the fed funds rate to ¼ to ½ percent at its meeting on Dec 16, 2015 (http://www.federalreserve.gov/newsevents/press/monetary/20151216a.htm).

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 (Section II and earlier http://cmpassocregulationblog.blogspot.com/2017/01/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/unresolved-us-balance-of-payments.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-reducing.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/weakening-equities-and-dollar.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/monetary-policy-designed-on-measurable.html and earlier 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 rates.

Chart VI-10, US, Fed Funds Rate, Business Days, Jul 1, 1954 to Jun 7, 2018, Percent per Year

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/datadownload/Choose.aspx?rel=H15

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

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

1994

FF

30Y

30P

10Y

10P

MOR

CPI

Jan

3.00

6.29

100

5.75

100

7.06

2.52

Feb

3.25

6.49

97.37

5.97

98.36

7.15

2.51

Mar

3.50

6.91

92.19

6.48

94.69

7.68

2.51

Apr

3.75

7.27

88.10

6.97

91.32

8.32

2.36

May

4.25

7.41

86.59

7.18

88.93

8.60

2.29

Jun

4.25

7.40

86.69

7.10

90.45

8.40

2.49

Jul

4.25

7.58

84.81

7.30

89.14

8.61

2.77

Aug

4.75

7.49

85.74

7.24

89.53

8.51

2.69

Sep

4.75

7.71

83.49

7.46

88.10

8.64

2.96

Oct

4.75

7.94

81.23

7.74

86.33

8.93

2.61

Nov

5.50

8.08

79.90

7.96

84.96

9.17

2.67

Dec

6.00

7.87

81.91

7.81

85.89

9.20

2.67

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

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

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

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

Source: Board of Governors of the Federal Reserve System

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

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

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

Source: Bureau of Labor Statistics

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

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

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

Source: Bureau of Labor Statistics

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

The Congressional Budget Office (CBO 2017Jun29, CBO 2017Jan24) 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 2016 at 3.2 percent per year. The projected path is significantly lower at 1.8 percent per year from 2017 to 2027. The legacy of the economic cycle expansion from IIIQ2009 to IQ2018 at 2.2 percent on average is in contrast with 3.8 percent on average in the expansion from IQ1983 to IIQ1991 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier (https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). Subpar economic growth may perpetuate unemployment and underemployment estimated at 20.6 million or 12.1 percent of the effective labor force in May 2018 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html) with much lower hiring than in the period before the current cycle (Section II and earlier https://cmpassocregulationblog.blogspot.com/2018/05/recovery-without-hiring-ten-million.html).

Table IB-3, US, Congressional Budget Office History and Projections of Potential GDP of US Overall Economy, ∆%

Potential GDP

Potential Labor Force

Potential Labor Productivity*

Average Annual ∆%

1950-1973

4.0

1.6

2.4

1974-1981

3.2

2.5

0.6

1982-1990

3.4

1.7

1.7

1991-2001

3.3

1.2

2.0

2002-2007

2.4

1.0

1.4

2008-2016

1.4

0.5

0.9

Total 1950-2016

3.2

1.4

1.7

Projected Average Annual ∆%

2017-2020

1.7

0.5

1.2

2021-2027

1.9

0.5

1.4

2017-2027

1.8

0.5

1.3

*Ratio of potential GDP to potential labor force

Source: CBO, The budget and economic outlook: 2017-2027. Washington, DC, Jan 24, 2017 https://www.cbo.gov/publication/52370 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. Aug 2016

https://www.cbo.gov/about/products/budget-economic-data#6

Chart IB1-A1 of the Congressional Budget Office provides historical and projected annual growth of United States potential GDP. There is sharp decline of growth of United States potential GDP.

Chart IB-1A1, Congressional Budget Office, Projections of Annual Growth of United States Potential GDP

Source: CBO, The budget and economic outlook: 2017-2027. Washington, DC, Jan 24, 2017 https://www.cbo.gov/publication/52370

https://www.cbo.gov/about/products/budget-economic-data#6

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.

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 IQ2018 during the current economic expansion in contrast with 3.8 percent on average in the cyclical expansion from IQ1983 to IIQ1991 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier (https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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 20.6 million or 12.1 percent of the labor force as estimated for May 2018 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html). There is no exit from unemployment/underemployment and stagnating real wages because of the collapse of hiring (Section II and earlier https://cmpassocregulationblog.blogspot.com/2018/05/recovery-without-hiring-ten-million.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).

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).

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.

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.

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.

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.

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 2016. 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.

Chart IIA2-6, US, Real GDP, 1960-2016, Billions of Chained 2009 Dollars

Source: Bureau of Economic Analysis

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

Chart IIA2-6, US, Real GDP, 1960-2016, 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 IQ1983. 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.

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

Source: Bureau of Economic Analysis

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

Risk aversion channels funds toward US long-term and short-term securities that finance the US balance of payments and fiscal deficits benefitting from risk flight to US dollar denominated assets. There are now temporary interruptions because of fear of rising interest rates that erode prices of US government securities because of mixed signals on monetary policy and exit from the Fed balance sheet of four trillion dollars of securities held outright. Net foreign purchases of US long-term securities (row C in Table VA-4) strengthened from $35.8 billion in Feb 2018 to $48.4 billion in Mar

2018. Foreign residents’ purchases minus sales of US long-term securities (row A in Table VA-4) in Feb 2018 of $57.7 billion weakened to $18.6 billion in Mar 2018. Net US (residents) purchases of long-term foreign securities (row B in Table VA-4) strengthened from minus $8.6 billion in Feb 2018 to $43.2 billion in Mar 2018. Other transactions (row C2 in Table VA-4) changed from minus $13.2 billion in Mar 2018 to minus $13.4 billion in Mar 2018. In Mar 2018,

C = A + B + C2 = $18.6 billion + $43.2 billion - $13.4 billion = $48.4 billion

There are minor rounding errors. There is weakening demand in Table VA-4 in Mar 2018 in A1 private purchases by residents overseas of US long-term securities of minus $17.3 billion of which weakening in A11 Treasury securities of minus $23.3 billion, strengthening in A12 of $7.0 billion in agency securities, strengthening of $20.8 billion of corporate bonds and weakening of minus $21.8 billion in equities. Worldwide risk aversion causes flight into US Treasury obligations with significant oscillations. Official purchases of securities in row A2 increased $35.9 billion with increase of Treasury securities of $18.4 billion in Mar 2018. Official purchases of agency securities increased $18.2 billion in Mar 2018. Row D shows decrease in Mar 2018 of $11.5 billion in purchases of short-term dollar denominated obligations. Foreign holdings of US Treasury bills decreased $10.4 billion (row D11) with foreign official holdings decreasing $15.3 billion while the category “other” decreased $1.1 billion. Foreign private holdings of US Treasury bills increased $4.9 billion in what could be arbitrage of duration exposures and international risks. Risk aversion of default losses in foreign securities dominates decisions to accept zero interest rates in Treasury securities with no perception of principal losses. In the case of long-term securities, investors prefer to sacrifice inflation and possible duration risk to avoid principal losses with significant oscillations

in risk perceptions.

Table VA-4, Net Cross-Borders Flows of US Long-Term Securities, Billion Dollars, NSA

Mar 2017 12 Months

Mar 2018 12 Months

Feb 2018

Mar 2018

A Foreign Purchases less Sales of
US LT Securities

94.7

457.5

57.7

18.6

A1 Private

326.1

444.1

31.4

-17.3

A11 Treasury

-35.2

117.4

24.1

-23.3

A12 Agency

197.8

105.1

5.5

7.0

A13 Corporate Bonds

106.6

130.3

2.0

20.8

A14 Equities

57.0

91.3

-0.3

-21.8

A2 Official

-231.4

13.4

26.3

35.9

A21 Treasury

-273.4

-54.6

19.1

18.4

A22 Agency

38.2

65.4

6.3

18.2

A23 Corporate Bonds

-4.0

3.9

1.5

1.6

A24 Equities

7.9

-1.3

-0.5

-2.3

B Net US Purchases of LT Foreign Securities

173.1

114.7

-8.6

43.2

B1 Foreign Bonds

226.2

213.8

-3.1

37.8

B2 Foreign Equities

-53.0

-99.1

-5.5

5.4

C1 Net Transactions

267.9

572.2

49.0

61.8

C2 Other

-299.8

-186.3

-13.2

-13.4

C Net Foreign Purchases of US LT Securities

-31.9

386.0

35.8

48.4

D Increase in Foreign Holdings of Dollar Denominated Short-term 

US Securities & Other Liab

13.1

98.1

46.4

-11.5

D1 US Treasury Bills

-57.4

46.8

16.3

-10.4

D11 Private

-72.3

46.1

7.4

4.9

D12 Official

14.9

0.7

8.9

-15.3

D2 Other

70.5

51.3

30.1

-1.1

C1 = A + B; C = C1+C2

A = A1 + A2

A1 = A11 + A12 + A13 + A14

A2 = A21 + A22 + A23 + A24

B = B1 + B2

D = D1 + D2

Sources: United States Treasury

https://www.treasury.gov/resource-center/data-chart-center/tic/Pages/ticpress.aspx

http://www.treasury.gov/press-center/press-releases/Pages/jl2609.aspx

Table VA-5 provides major foreign holders of US Treasury securities. China is the largest holder with $1187.7 billion in Mar 2017, increasing 0.9 percent from $1176.7 billion in Feb 2018 while increasing $99.6 billion from Feb 2017 or 9.2 percent. The United States Treasury estimates US government debt held by private investors at $11,941 billion in Dec 2017 (Fiscal Year 2018). China’s holding of US Treasury securities represents 9.9 percent of US government marketable interest-bearing debt held by private investors (https://www.fiscal.treasury.gov/fsreports/rpt/treasBulletin/treasBulletin_home.htm). Min Zeng, writing on “China plays a big role as US Treasury yields fall,” on Jul 16, 2014, published in the Wall Street Journal (http://online.wsj.com/articles/china-plays-a-big-role-as-u-s-treasury-yields-fall-1405545034?tesla=y&mg=reno64-wsj), finds that acceleration in purchases of US Treasury securities by China has been an important factor in the decline of Treasury yields in 2014. Japan decreased its holdings from $1120.7 billion in Mar 2017 to $1043.5 billion in Mar 2018 or 6.9 percent. The combined holdings of China and Japan in Mar 2018 add to $2231.2 billion, which is equivalent to 18.7 percent of US government marketable interest-bearing securities held by investors of $11,941 billion in Dec 2017 (Fiscal Year 2018) (https://www.fiscal.treasury.gov/fsreports/rpt/treasBulletin/treasBulletin_home.htm). Total foreign holdings of Treasury securities increased from $6012.5 billion in Feb 2017 to $6291.6 billion in Feb 2018, or 4.6 percent. The US continues to finance its fiscal and balance of payments deficits with foreign savings (see Pelaez and Pelaez, The Global Recession Risk (2007)). A point of saturation of holdings of US Treasury debt may be reached as foreign holders evaluate the threat of reduction of principal by dollar devaluation and reduction of prices by increases in yield, including possibly risk premium. Shultz et al (2012) find that the Fed financed three-quarters of the US deficit in fiscal year 2011, with foreign governments financing significant part of the remainder of the US deficit while the Fed owns one in six dollars of US national debt. Concentrations of debt in few holders are perilous because of sudden exodus in fear of devaluation and yield increases and the limit of refinancing old debt and placing new debt. 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.”

Table VA-5, US, Major Foreign Holders of Treasury Securities $ Billions at End of Period

Mar 2018

Feb 2018

Mar 2017

Total

6294.0

6291.7

6075.3

China

1187.7

1176.7

1088.1

Japan

1043.5

1059.5

1120.7

Ireland

317.9

314.0

313.9

Brazil

286.0

272.9

259.5

United Kingdom

263.7

250.5

228.3

Switzerland

245.4

248.0

227.6

Cayman Island

242.9

252.2

248.2

Luxembourg

221.6

218.6

218.3

Hong Kong

196.2

196.5

195.1

Taiwan

170.1

170.7

183.8

India

157.0

152.9

117.1

Saudi Arabia

151.2

150.9

124.5

Belgium

125.5

125.7

109.9

Singapore

117.8

118.0

103.1

Foreign Official Holdings

4049.5

4030.0

3880.1

A. Treasury Bills

318.6

333.9

317.9

B. Treasury Bonds and Notes

3730.9

3696.1

3562.2

Source: United States Treasury

http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/ticpress.aspx

http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/index.aspx

http://ticdata.treasury.gov/Publish/mfh.txt

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018.

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