Monday, May 12, 2014

Rules, Discretionary Authorities and Slow Productivity Growth, Financial Uncertainty, Recovery without Hiring, United States International Trade, World Cyclical Slow Growth and Global Recession Risk: Part II

 

Rules, Discretionary Authorities and Slow Productivity Growth, Financial Uncertainty, Recovery without Hiring, United States International Trade, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

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

Executive Summary

I Recovery without Hiring

IA1 Hiring Collapse

IA2 Labor Underutilization

ICA3 Ten Million Fewer Full-time Jobs

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

Middle-Age Unemployment

II Rules, Discretionary Authorities and Slow Productivity Growth

IIA United States International Trade

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

IIID Appendix on European Central Bank Large Scale Lender of Last Resort

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during the Debt Crisis of the 1980s

I Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels increased by only 4 percent from Jan 2009 to Jan 2012. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job in early 2012 is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn, there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/04/global-financial-instability-recovery.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).

The Bureau of Labor Statistics (BLS) revised on Mar 11, 2014 “job openings, hires and separations data to incorporate the annual update to the Current Employment Statistics employment estimates and the JOLTS seasonal adjustment factors. Unadjusted data and seasonally adjusted data from December 2000 forward are subject to revisions” (http://www.bls.gov/jlt/). Hiring in the nonfarm sector (HNF) has declined from 63.3 million in 2006 to 54.2 million in 2013 or by 9.1 million while hiring in the private sector (HP) has declined from 59.1 million in 2006 to 50.7 million in 2013 or by 8.4 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.0 in 2005 to 39.7 in 2013 and in the private sector (RHP) from 52.7 in 2005 to 44.3 in 2013. Hiring has not recovered as in previous cyclical expansions because of the low rate of economic growth in the current cyclical expansion. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 19 quarters from IIIQ2009 to IQ2014. 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 first estimate of GDP for IQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp1q14_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier). 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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth under trend in the entire cycle from IVQ2007 to IQ2014 would have accumulated to 21.2 percent. GDP in IQ2014 would be $18,172.7 billion if the US had grown at trend, which is higher by $2,226.1 billion than actual $15,946.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 27.4 million unemployed or underemployed equivalent to actual unemployment of 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,946.6 billion in IQ2014 or 6.3 percent at the average annual equivalent rate of 1.0 percent. 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.

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

 

HNF

Rate RNF

HP

Rate HP

2001

62,633

47.4

58,501

52.7

2002

58,479

44.8

54,665

50.1

2003

56,949

43.7

53,584

49.3

2004

60,263

45.7

56,573

51.4

2005

62,951

47.0

59,179

52.7

2006

63,327

46.4

59,128

51.7

2007

62,104

45.0

57,797

49.9

2008

54,745

39.9

51,316

44.8

2009

45,931

35.0

42,703

39.3

2010

48,743

37.4

44,914

41.7

2011

50,295

38.1

47,183

43.0

2012

52,360

39.0

48,915

43.6

2013

54,191

39.7

50,718

44.3

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.

clip_image001

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2013

Source: US Bureau of Labor Statistics

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

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

clip_image002

Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2013

Source: US Bureau of Labor Statistics

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

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table I-2. There were much milder declines in 2002 of 6.6 percent and 2.6 percent in 2003 followed by strong rebounds of 5.8 percent in 2004 and 4.5 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 1.9 in 2007, 11.8 in 2008 and 16.1 percent in 2009. On a yearly basis, nonfarm hiring grew 6.1 percent in 2010 relative to 2009, 3.2 percent in 2011, 4.1 percent in 2012 and 3.5 percent in 2013. The relatively large length of 18 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, 2002-2013

Year

Annual ∆%

2002

-6.6

2003

-2.6

2004

5.8

2005

4.5

2006

0.6

2007

-1.9

2008

-11.8

2009

-16.1

2010

6.1

2011

3.2

2012

4.1

2013

3.5

Source: US Bureau of Labor Statistics

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

Total private hiring (HP) yearly data are provided in Chart I-4. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2013.

clip_image003

Chart I-4, US, Total Nonfarm Hiring Level, Annual, ∆%, 2001-2013

Source: Bureau of Labor Statistics

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

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

clip_image004

Chart I-5, US, Total Private Hiring, Annual, 2001-2013

Source: Bureau of Labor Statistics

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

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

clip_image005

Chart I-5A, US, Rate Total Private Hiring Level, Annual, 2001-2013

Source: Bureau of Labor Statistics

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

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Mar in the years from 2001 to 2014 in Table I-3. Hiring numbers are in thousands. There is moderate recovery in HNF from 3462 thousand (or 3.5 million) in Mar 2009 to 3905 thousand in Mar 2010, 4008 thousand in Mar 2011, 4220 thousand in Mar 2012, 4055 thousand in Mar 2013 and 4363 thousand in Mar 2014 for cumulative gain of 26.0percent. HP rose from 3294 thousand in Mar 2009 to 3651 thousand in Mar 2010, 3831 thousand in Mar 2011, 4011 thousand in Mar 2012, 3852 thousand in Mar 2013 and 4134 thousand in Mar 2014 for cumulative gain of 25.5 percent. HNF has fallen from 4988 thousand in Mar 2006 to 4363 thousand in Mar 2014 or by 12.5 percent. HP has fallen from 4727 thousand in Mar 2006 to 4134 thousand in Mar 2014 or by 12.5 percent. The civilian noninstitutional population of the US, or individuals in condition to work, rose from 228.815 million in 2006 to 245.679 million in 2013 or by 16.864 million and the civilian labor force from 151.428 million in 2006 to 155.389 million in 2013 or by 3.961 million (http://www.bls.gov/data/). The number of nonfarm hires in the US fell from 63.327 million in 2006 to 54.191 million in 2013 or by 9.136 million and the number of private hires fell from 59.128 million in 2006 to 50.718 million in 2013 or by 8.410 million (http://www.bls.gov/jlt/). Private hiring of 59.128 million in 2006 was equivalent to 25.8 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 50.718 million in 2013 or 20.6 percent of the civilian noninstitutional population of 245.679 million in 2013. The percentage of hiring in civilian noninstitutional population of 25.8 percent in 2006 would correspond to 63.385 million of hiring in 2013, which would be 12.667 million higher than actual 50.718 million in 2013. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-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 Mar

5259

4.0

5010

4.5

2002 Mar

4319

3.3

4098

3.8

2003 Mar

4164

3.2

3970

3.7

2004 Mar

4867

3.7

4636

4.3

2005 Mar

4908

3.7

4691

4.3

2006 Mar

4988

3.7

4727

4.2

2007 Mar

4971

3.6

4719

4.1

2008 Mar

4456

3.2

4235

3.7

2009 Mar

3462

2.6

3294

3.0

2010 Mar

3905

3.0

3651

3.4

2011 Mar

4008

3.1

3831

3.6

2012 Mar

4220

3.2

4011

3.6

2013 Mar

4055

3.0

3852

3.4

2014 Mar

4363

3.2

4134

3.6

Source: Bureau of Labor Statistics

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

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2014. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4841 in May 2010 until it surpassed it with 4975 in Jun 2011 but declined to 3084 in Dec 2012. Nonfarm hiring fell to 3012 in Dec 2011 from 3810 in Nov and to revised 3614 in Feb 2012, increasing to 4220 in Mar 2012, 3084 in Dec 2012 and 4223 in Jan 2013 and declining to 3699 in Feb 2013. Nonfarm hires not seasonally adjusted increased to 4165 in Nov 2013 and 3271 in Dec 2013. Nonfarm hires reached 4363 in Mar 2014. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Oct 2011 was 4237 thousand, increasing to revised 4446 thousand in Feb 2012, or 4.9 percent, moving to 4343 in Dec 2012 for cumulative increase of 2.0 percent from 4256 in Dec 2011 and 4578 in Dec 2013 for increase of 5.4 percent relative to 4343 in Dec 2012. The number of hires not seasonally adjusted was 4975 in Jun 2011, falling to 3012 in Dec 2011 but increasing to 4112 in Jan 2012 and declining to 3084 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 39.5 percent from 4975 in Jun 2011 to 3012 in Dec 2011 and fell 38.7 percent from 5035 in Jun 2012 to 3084 in Dec 2012 in a yearly-repeated seasonal pattern. The number of nonfarm hires not seasonally adjusted fell from 5095 in Jun 2013 to 3271 in Dec 2013, or decline of 35.8 percent, showing strong seasonality.

clip_image006

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2014 Month SA

Source: Bureau of Labor Statistics

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

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

clip_image007

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2014

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 4057 thousand in Sep 2011 to 3962 in Dec 2011 or by 2.3 percent, decreasing to 3998 in Jan 2012 or decline by 1.5 percent relative to the level in Sep 2011. Private hiring fell to 3959 in Sep 2012 or lower by 2.4 percent relative to Sep 2011, moving to 4061 in Dec 2012 for increase of 1.6 percent relative to 3998 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4600 in Jun 2011 to 2833 in Dec 2011 or by 38.4 percent, reaching 3853 in Jan 2012 or decline of 16.2 percent relative to Jun 2011 and moving to 2911 in Dec 2012 or 37.1 percent lower relative to 4629 in Jun 2012. Hires fell from 4706 in Jun 2013 to 3098 in Dec 2013. Companies reduce hiring in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5567 in Jun 2006 to 3568 in Dec 2006 or by 35.9 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Jul 2006, private hiring NSA was 5501, declining to 4326 in Jul 2011 or by 21.4 percent and to 4354 in Jul 2012 or lower by 20.9 percent relative to Jul 2006. Private hiring NSA fell from 4727 in Mar 2006 to 4134 in Mar 2014 or 12.5 percent. Private hiring fell from 5501 in Jul 2006 to 4632 in Jul 2013 or 15.8 percent. The conclusion is that private hiring in the US is around 20 percent below the hiring before the global recession while the noninstitutional population of the United States has grown from 228.815 million in 2006 to 245.679 million in 2013, by 16.864 million or 7.4 percent. The main problem in recovery of the US labor market has been the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

clip_image008

Chart I-8, US, Total Private Hiring Month SA 2001-2014

Source: Bureau of Labor Statistics

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

Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data did not rise significantly above the peak in 2010. The rate seasonally adjusted fell from 3.7 in Sep 2011 to 3.6 in Dec 2011 and reached 3.6 in Dec 2012 and 3.7 in Dec 2013. The rate not seasonally adjusted (NSA) fell from 3.7 in Sep 2011 to 2.5 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. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 19 quarters from IIIQ2009 to IQ2014. 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 first estimate of GDP for IQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp1q14_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier). 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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth under trend in the entire cycle from IVQ2007 to IQ2014 would have accumulated to 21.2 percent. GDP in IQ2014 would be $18,172.7 billion if the US had grown at trend, which is higher by $2,226.1 billion than actual $15,946.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 27.4 million unemployed or underemployed equivalent to actual unemployment of 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,946.6 billion in IQ2014 or 6.3 percent at the average annual equivalent rate of 1.0 percent. 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.ate hires fell from 4.8 in Jul 2006 to 4.0 in Jul 2013.

clip_image009

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2014

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 2014. The final column provides annual TNF LD for the years from 2001 to 2013. Nonfarm job openings (TNF JOB) fell from a peak of 4573 in Mar 2007 to 4013 in Mar 2014 or by 12.2 percent while the rate fell from 3.2 to 2.8. Nonfarm layoffs and discharges (TNF LD) rose from 1329 in Mar 2006 to 1994 in Mar 2009 or by 50.0 percent. The annual data show layoffs and discharges rising from 20.9 million in 2006 to 26.4 million in 2009 or by 26.3 percent. Business pruned payroll jobs to survive the global recession but there has not been hiring because of the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 19 quarters from IIIQ2009 to IQ2014. 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 first estimate of GDP for IQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp1q14_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier). 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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth under trend in the entire cycle from IVQ2007 to IQ2014 would have accumulated to 21.2 percent. GDP in IQ2014 would be $18,172.7 billion if the US had grown at trend, which is higher by $2,226.1 billion than actual $15,946.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 27.4 million unemployed or underemployed equivalent to actual unemployment of 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,946.6 billion in IQ2014 or 6.3 percent at the average annual equivalent rate of 1.0 percent. 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.

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

Mar 2001

4449

3.3

1725

24138

Mar 2002

3466

2.6

1440

22706

Mar 2003

3008

2.3

1511

23490

Mar 2004

3338

2.5

1533

22668

Mar 2005

3816

2.8

1598

22243

Mar 2006

4448

3.2

1329

20896

Mar 2007

4573

3.2

1465

21958

Mar 2008

3919

2.8

1499

24028

Mar 2009

2445

1.8

1994

26444

Mar 2010

2605

2.0

1488

21829

Mar 2011

3102

2.3

1355

20805

Mar 2012

3813

2.8

1319

20892

Mar 2013

3879

2.8

1373

19964

Mar 2014

4013

2.8

1231

 

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 3080 seasonally adjusted in Apr 2010 with 3646 seasonally adjusted in Dec 2012, which is higher by 18.4 percent relative to Apr 2010 but lower by 2.9 percent relative to 3755 in Nov 2012 and lower by 4.7 percent than 3827 in Mar 2012. Nonfarm job openings increased from 3646 in Dec 2012 to 3914 in Dec 2013 or by 7.4 percent. The high of job openings not seasonally adjusted was 3428 in Apr 2010 that was surpassed by 3661 in Jul 2011, increasing to 3939 in Oct 2012 but declining to 3152 in Dec 2012 and decreasing to 3387 in Dec 2013. The level of job openings not seasonally adjusted fell to 3152 in Dec 2012 or by 21.3 percent relative to 4005 in Apr 2012. There is here again the strong seasonality of year-end labor data. Job openings fell from 4209 in Apr 2013 to 3387 in Dec 2013, showing strong seasonal effects. The level of job openings of 4013 in Mar 2014 NSA is lower by 12.2 percent relative to 4573 in Mar 2007. The main problem in recovery of the US labor market has been the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

clip_image010

Chart I-10, US Job Openings, Thousands NSA, 2001-2014

Source: US Bureau of Labor Statistics

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

The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted increased from 2.2 in Jan 2011 to 2.6 in Dec 2011, 2.6 in Dec 2012 and 2.8 in Dec 2013. The rate seasonally adjusted stood at 2.8 in Mar 2014. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 3.0 in Apr 2013 and 2.6 in Nov 2013. The rate of job openings NSA fell from 3.3 in Jul 2007 to 1.6 in Nov-Dec 2009, recovering insufficiently to 2.8 in Mar 2014. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 19 quarters from IIIQ2009 to IQ2014. 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 first estimate of GDP for IQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp1q14_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier). 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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth under trend in the entire cycle from IVQ2007 to IQ2014 would have accumulated to 21.2 percent. GDP in IQ2014 would be $18,172.7 billion if the US had grown at trend, which is higher by $2,226.1 billion than actual $15,946.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 27.4 million unemployed or underemployed equivalent to actual unemployment of 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,946.6 billion in IQ2014 or 6.3 percent at the average annual equivalent rate of 1.0 percent. 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.

clip_image011

Chart I-11, US, Rate of Job Openings, NSA, 2001-2014

Source: US Bureau of Labor Statistics

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

Total separations are shown in Chart I-12. Separations are much lower in 2012-14 than before the global recession but hiring has not recovered.

clip_image012

Chart I-12, US, Total Nonfarm Separations, Month Thousands SA, 2001-2014

Source: US Bureau of Labor Statistics

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

Annual total separations are shown in Chart I-13. Separations are much lower in 2011-2014 than before the global recession but without recovery in hiring.

clip_image013

Chart I-13, US, Total Separations, Annual, Thousands, 2001-2013

Source: US Bureau of Labor Statistics

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

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

Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2013

Year

Annual

2001

64472

2002

59003

2003

56970

2004

58238

2005

60494

2006

61117

2007

60838

2008

58227

2009

51127

2010

47750

2011

48220

2012

50070

2013

51837

Source: US Bureau of Labor Statistics

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

Monthly data of layoffs and discharges reach a peak in early 2009, as shown in Chart I-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business. Weak rates of growth of GDP (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html) frustrated employment recovery. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

clip_image014

Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly Thousands SA, 2001-2014

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.

clip_image015

Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2012

Source: US Bureau of Labor Statistics

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

Table I-6 provides annual nonfarm layoffs and discharges from 2001 to 2013. Layoffs and discharges peaked at 26.4 million in 2009 and then fell to 20.8 million in 2011, by 5.6 million, or 21.2 percent. Total nonfarm layoffs and discharges increased mildly to 20.9 million in 2012, falling to 19.9 million in 2013.

Table I-6, US, Total Nonfarm Layoffs and Discharges, Thousands, 2001-2013

Year

Annual

2001

24138

2002

22706

2003

23490

2004

22668

2005

22243

2006

20896

2007

21958

2008

24028

2009

26444

2010

21829

2011

20805

2012

20892

2013

19964

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 annualized has risen from 8.2 percent in 2006 to 1.8 percent in Apr 2014.

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

 

U1

U2

U3

U4

U5

U6

2014

           

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

           

2013

3.9

3.9

7.4

7.9

8.8

13.8

2012

4.5

4.4

8.1

8.6

9.5

14.7

2011

5.3

5.3

8.9

9.5

10.4

15.9

2010

5.7

6.0

9.6

10.3

11.1

16.7

2009

4.7

5.9

9.3

9.7

10.5

16.2

2008

2.1

3.1

5.8

6.1

6.8

10.5

2007

1.5

2.3

4.6

4.9

5.5

8.3

2006

1.5

2.2

4.6

4.9

5.5

8.2

2005

1.8

2.5

5.1

5.4

6.1

8.9

2004

2.1

2.8

5.5

5.8

6.5

9.6

2003

2.3

3.3

6.0

6.3

7.0

10.1

2002

2.0

3.2

5.8

6.0

6.7

9.6

2001

1.2

2.4

4.7

4.9

5.6

8.1

2000

0.9

1.8

4.0

4.2

4.8

7.0

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.1 percent in Aug 2011 to 16.3 percent in Sep 2011 and then fell to 14.5 percent in Mar 2012, reaching 12.3 percent in Apr 2014. 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 27.4 million in job stress of unemployment/underemployment in Apr 2013, not seasonally adjusted, corresponding to 16.8 percent of the labor force (Table I-4 http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html).

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

 

U1

U2

U3

U4

U5

U6

Apr 2014

3.2

3.4

6.3

6.7

7.6

12.3

Mar

3.5

3.5

6.7

7.1

8.0

12.7

Feb

3.5

3.5

6.7

7.2

8.1

12.6

Jan

3.4

3.5

6.6

7.1

8.1

12.7

Dec 2013

3.6

3.5

6.7

7.2

8.1

13.1

Nov

3.7

3.7

7.0

7.4

8.2

13.1

Oct

3.8

4.0

7.2

7.7

8.6

13.7

Sep

3.8

3.7

7.2

7.7

8.6

13.6

Aug

3.8

3.8

7.2

7.8

8.6

13.6

Jul

3.9

3.8

7.3

7.9

8.7

13.9

Jun

4.0

3.9

7.5

8.1

9.0

14.2

May

4.0

3.9

7.5

8.0

8.8

13.8

Apr

4.1

4.1

7.5

8.0

8.9

13.9

Mar

4.1

4.1

7.5

8.0

8.9

13.8

Feb

4.2

4.2

7.7

8.3

9.3

14.3

Jan

4.2

4.3

7.9

8.4

9.3

14.4

Dec 2012

4.3

4.2

7.9

8.5

9.4

14.4

Nov

4.2

4.1

7.8

8.3

9.2

14.4

Oct

4.4

4.2

7.8

8.3

9.2

14.4

Sep

4.3

4.2

7.8

8.3

9.3

14.7

Aug

4.4

4.5

8.1

8.6

9.6

14.7

Jul

4.5

4.6

8.2

8.7

9.7

14.9

Jun

4.6

4.6

8.2

8.7

9.6

14.8

May

4.6

4.5

8.2

8.7

9.6

14.8

Apr

4.6

4.4

8.2

8.7

9.5

14.6

Mar

4.7

4.6

8.2

8.7

9.6

14.5

Feb

4.8

4.6

8.3

8.9

9.8

15.0

Jan

4.8

4.7

8.2

8.8

9.8

15.1

Dec 2011

4.9

4.9

8.5

9.1

10.0

15.2

Nov

5.0

5.0

8.6

9.3

10.2

15.6

Oct

5.1

5.1

8.8

9.4

10.3

15.9

Sep

5.4

5.2

9.0

9.6

10.5

16.3

Aug

5.3

5.2

9.0

9.6

10.5

16.1

Jul

5.3

5.3

9.0

9.7

10.6

16.0

Jun

5.3

5.3

9.1

9.7

10.7

16.1

May

5.3

5.4

9.0

9.5

10.3

15.8

Apr

5.2

5.4

9.1

9.7

10.5

16.1

Mar

5.3

5.4

9.0

9.5

10.4

15.9

Feb

5.4

5.5

9.0

9.6

10.6

16.0

Jan

5.5

5.5

9.1

9.7

10.7

16.1

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart I-16 provides U6 on a monthly basis from 2001 to 2014. There was a steep climb from 2007 into 2009 and then this measure of unemployment and underemployment stabilized at that high level but declined into 2012. The low of U6 SA was 8.0 percent in Mar 2007 and the peak was 17.1 percent in Apr 2010. The low NSA was 7.6 percent in Oct 2006 and the peak was 18.0 percent in Jan 2010.

clip_image016

Chart I-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed Part-Time for Economic Reasons, Month, SA, 2001-2014

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 stability in 2013-2014.

clip_image017

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

Thousands, Month SA 2001-2014

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 9.068 million in Sep 2011 to 7.780 million in Mar 2012, seasonally adjusted, or decline of 1.288 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.572 million in Sep 2012 for increase of 527,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.231 million in Oct 2012 or by 341,000 again in one month, further declining to 8.164 million in Nov 2012 for another major one-month decline of 67,000 and 7.929 million in Dec 2012 or fewer 235,000 in just one month. The number employed part-time for economic reasons increased to 7.983 million in Jan 2013 or 54,000 more than in Dec 2012 and to 7,991 million in Feb 2013, declining to 7.917 million in May 2013 but increasing to 8.194 million in Jun 2013. The number employed part-time for economic reasons fell to 7.898 million in Aug 2013 for decline of 282,000 in one month from 8.180 million in Jul 2013. The number employed part-time for economic reasons increased 16,000 from 7.898 million in Aug 2013 to 7.914 million in Sep 2013. The number part-time for economic reasons rose to 8.016 million in Oct 2013, falling by 293,000 to 7.723 million in Nov 2013. The number part-time for economic reasons increased to 7.771 million in Dec 2013, decreasing to 7.257 million in Jan 2014. The number employed part-time for economic reasons fell from 7.257 million in Jan 2014 to 7.186 million in Feb 2014. The number employed part-time for economic reasons increased to 7.411 million in Mar 2014 and 7.465 million in Apr 2014. There is an increase of 186,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 119,000 from Aug 2012 to Nov 2012.
  • Seasonally adjusted full-time. The number employed full-time increased from 112.906 million in Oct 2011 to 115.114 million in Mar 2012 or 2.208 million but then fell to 114.279 million in May 2012 or 0.835 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.626 million in Aug 2012 to 115.531 million in Oct 2012 or increase of 0.905 million full-time jobs in two months and further to 115.821 million in Jan 2013 or increase of 1.195 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.785 million in Feb 2013, increasing to 116.288 million in May 2013 and 116.087 million in Jun 2013. Then number of full-time jobs increased to 116.156 million in Jul 2013, 116.301 million in Aug 2013 and 116.883 million in Sep 2013. The number of full-time jobs fell to 116.306 million in Oct 2013 and increased to 116.951 in Nov 2013. The level of full-time jobs fell to 117.278 million in Dec 2013, increasing to 117.656 million in Jan 2014 and 117.819 million in Feb 2014. The number employment full-time increased to 118.003 million in Mar 2014 and 118.415 million in Apr 2014. Benchmark and seasonality-factors adjustments at the turn of every year could affect comparability of labor market indicators (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 less than in Feb 2013 and fell to 7.709 million in Apr 2013. The number employed part-time for economic reasons reached 7.618 million in May 2013. The number employed part-time for economic reasons jumped from 7.618 million in May 2013 to 8.440 million in Jun 2013 or 822,000 in one month. The number employed part-time for economic reasons fell to 8.324 million in Jul 2013 and 7.690 million in Aug 2013. The number employed part-time for economic reasons NSA fell to 7.522 million in Sep 2013, increasing to 7.700 million in Oct 2013. The number employed 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.
  • 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. 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 Apr 2014 is 118.073 million, which is lower by 5.146 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 247.439 million in Apr 2014 or by 15.481 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 5.146 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 131.390 million full-time jobs with population of 247.439 million in Apr 2014 (0.531 x 247.439) or 13.317 million fewer full-time jobs relative to actual 118.073 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 15 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 19 quarters from IIIQ2009 to IQ2014. 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 first estimate of GDP for IQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp1q14_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier). 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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth under trend in the entire cycle from IVQ2007 to IQ2014 would have accumulated to 21.2 percent. GDP in IQ2014 would be $18,172.7 billion if the US had grown at trend, which is higher by $2,226.1 billion than actual $15,946.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 27.4 million unemployed or underemployed equivalent to actual unemployment of 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,946.6 billion in IQ2014 or 6.3 percent at the average annual equivalent rate of 1.0 percent. 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.

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

 

Part-time Thousands

Full-time Millions

Seasonally Adjusted

   

Apr 2014

7,465

118.415

Mar 2014

7,411

118.003

Feb 2014

7,186

117.819

Jan 2014

7,257

117.656

Dec 2013

7,771

117.278

Nov 2013

7,723

116.951

Oct 2013

8,016

116.306

Sep 2013

7,914

116.883

Aug 2013

7,898

116.301

Jul 2013

8,180

116.156

Jun 2013

8,194

116.087

May 2013

7,917

116.288

Apr 2013

7,929

116.062

Mar 2013

7,663

115.901

Feb 2013

7,991

115.785

Jan 2013

7,983

115.821

Dec 2012

7,929

115.735

Nov 2012

8,164

115.581

Oct 2012

8,231

115.531

Sep 2012

8,572

115.229

Aug 2012

8,045

114.626

Jul 2012

8,163

114.589

Jun 2012

8,154

114.728

May 2012

8,138

114.279

Apr 2012

7,913

114.398

Mar 2012

7,780

115.114

Feb 2012

8,133

114.210

Jan 2012

8,228

113.790

Dec 2011

8,177

113.740

Nov 2011

8,457

113.158

Oct 2011

8,675

112.906

Sep 2011

9,068

112.523

Aug 2011

8,820

112.643

Jul 2011

8,342

112.209

Not Seasonally Adjusted

   

Apr 2014

7,243

118.073

Mar 2014

7,455

116.985

Feb 2014

7,397

116.323

Jan 2014

7,771

115.744

Dec 2013

7,990

116.661

Nov 2013

7,563

116.875

Oct 2013

7,700

116.798

Sep 2013

7,522

117.308

Aug 2013

7,690

117.868

Jul 2013

8,324

117.688

Jun 2013

8,440

117.400

May 2013

7,618

116.643

Apr 2013

7,709

115.674

Mar 2013

7,734

114.796

Feb 2013

8,298

114.191

Jan 2013

8,628

113.868

Dec 2012

8,166

115.079

Nov 2012

7,994

115.515

Oct 2012

7,870

116.045

Sep 2012

8,110

115.678

Aug 2012

7,842

116.214

Jul 2012

8,316

116.131

Jun 2012

8,394

116.024

May 2012

7,837

114.634

Apr 2012

7,694

113.999

Mar 2012

7,867

113.916

Feb 2012

8,455

112.587

Jan 2012

8,918

111.879

Dec 2011

8,428

113.050

Nov 2011

8,271

113.138

Oct 2011

8,258

113.456

Sep 2011

8,541

112.980

Aug 2011

8,604

114.286

Jul 2011

8,514

113.759

Jun 2011

8,738

113.255

May 2011

8,270

112.618

Apr 2011

8,425

111.844

Mar 2011

8,737

111.186

Feb 2011

8,749

110.731

Jan 2011

9,187

110.373

Dec 2010

9,205

111.207

Nov 2010

8,670

111.348

Oct 2010

8,408

112.342

Sep 2010

8,628

112.385

Aug 2010

8,628

113.508

Jul 2010

8,737

113.974

Jun 2010

8,867

113.856

May 2010

8,513

112.809

Apr 2010

8,921

111.391

Mar 2010

9,343

109.877

Feb 2010

9,282

109.100

Jan 2010

9,290

108.777 (low)

Dec 2009

9,354 (high)

109.875

Nov 2009

8,894

111.274

Oct 2009

8,474

111.599

Sep 2009

8,255

111.991

Aug 2009

8,835

113.863

Jul 2009

9,103

114.184

Jun 2009

9,301

114.014

May 2009

8,785

113.083

Apr 2009

8,648

112.746

Mar 2009

9,305

112.215

Feb 2009

9,170

112.947

Jan 2009

8,829

113.815

Dec 2008

8,250

116.422

Nov 2008

7,135

118.432

Oct 2008

6,267

120.020

Sep 2008

5,701

120.213

Aug 2008

5,736

121.556

Jul 2008

6,054

122.378

Jun 2008

5,697

121.845

May 2008

5,096

120.809

Apr 2008

5,071

120.027

Mar 2008

5,038

119.875

Feb 2008

5,114

119.452

Jan 2008

5,340

119.332

Dec 2007

4,750

121.042

Nov 2007

4,374

121.846

Oct 2007

4,028

122.006

Sep 2007

4,137

121.728

Aug 2007

4,494

122.870

Jul 2007

4,516

123.219 (high)

Jun 2007

4,469

122.150

May 2007

4,315

120.846

Apr 2007

4,205

119.609

Mar 2007

4,384

119.640

Feb 2007

4,417

119.041

Jan 2007

4,726

119.094

Dec 2006

4,281

120.371

Nov 2006

4,054

120.507

Oct 2006

4,010

121.199

Sep 2006

3,735 (low)

120.780

Aug 2006

4,104

121.979

Jul 2006

4,450

121.951

Jun 2006

4,456

121.070

May 2006

3,968

118.925

Apr 2006

3,787

118.559

Mar 2006

4,097

117.693

Feb 2006

4,403

116.823

Jan 2006

4,597

116.395

Source: US Bureau of Labor Statistics

http://www.bls.gov/

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

clip_image018

Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2014

Sources: US Bureau of Labor Statistics

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

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

clip_image019

Chart I-19, US, Marginally Attached to the Labor Force, NSA Month, Thousands, 2001-2014

Sources: US Bureau of Labor Statistics

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

The number with full-time jobs in Apr 2014 is 118.073 million, which is lower by 5.146 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 247.439 million in Apr 2014 or by 15.481 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 5.146 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 131.390 million full-time jobs with population of 247.439 million in Apr 2014 (0.531 x 247.439) or 13.317 million fewer full-time jobs relative to actual 118.073 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 15 million. Mediocre GDP growth is the main culprit of the fractured US labor market.

Chart I-20 provides unadjusted full-time jobs in the US from 2001 to 2014 with sharp drop and incomplete recovery. There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

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

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

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

clip_image020

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2014

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 2014. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

clip_image021

Chart I-20A, US, Civilian Noninstitutional Population, Thousands, 2001-2014

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 2014. There were multiple recessions followed by expansions without contraction of full-time jobs and without recovery as during the period after 2008. The problem is specific of the current cycle and not secular.

clip_image022

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2014

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 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

clip_image023

Chart I-20C, US, Civilian Noninstitutional Population, Thousands, 1968-2014

Sources: US Bureau of Labor Statistics

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

IA4 Theory and Reality of Secular Stagnation: Youth and Middle-Age Unemployment. Three tables support the argument that the proper comparison of the business cycle is between the recessions of the 1980s and the global recession after IVQ2007 and not as argued erroneously with the Great Depression of the 1930s.

Table I-5 provides percentage change of real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Data are available for the 1930s only on a yearly basis. US GDP fell 4.7 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1981 to IVQ1982 and 4.3 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first three years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985 and 3.5 percent in 1986 while GDP grew, 2.5 percent in 2010, 1.8 percent in 2011, 2.8 percent in 2012 and 1.9 percent in 2013. Actual annual equivalent GDP growth in the four quarters of 2012, and five quarters from IQ2013 to IQ2014 is 2.0 percent and 2.3 percent in the four quarters ending in IQ2014 but only 2.2 percent in the four quarters of 2013 by discounting contribution of 1.67 percentage points of inventory accumulation to growth in IIIQ2013. GDP grew at 4.2 percent in 1985 and 3.5 percent in 1986 while the forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 2.8 to 3.0 percent in 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20140319b.htm) with less reliable forecast of 3.0 to 3.2 percent in 2015 (http://www.federalreserve.gov/newsevents/press/monetary/20140319b.htm). Growth of GDP in the expansion from IIIQ2009 to IQ2014 has been at average 2.2 percent in annual equivalent.

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

Year

GDP ∆%

Year

GDP ∆%

Year

GDP ∆%

1930

-8.5

1980

-0.2

2000

4.1

1931

-6.4

1981

2.6

2001

1.0

1932

-12.9

1982

-1.9

2002

1.8

1933

-1.3

1983

4.6

2003

2.8

1934

10.8

1984

7.3

2004

3.8

1935

8.9

1985

4.2

2005

3.4

1936

12.9

1986

3.5

2006

2.7

1937

5.1

1987

3.5

2007

1.8

1938

-3.3

1988

4.2

2008

-0.3

1930

8.0

1989

3.7

2009

-2.8

1940

8.8

1990

1.9

2010

2.5

1941

17.7

1991

-0.1

2011

1.8

1942

18.9

1992

3.6

2012

2.8

1943

17.0

1993

2.7

2013

1.9

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

Characteristics of the four cyclical contractions are provided in Table I-6 with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.7 percent, which is almost equal to the decline of 4.3 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

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

 

Number of Quarters

Cumulative Percentage Contraction

Average Percentage Rate

IIQ1953 to IIQ1954

3

-2.4

-0.8

IIIQ1957 to IIQ1958

3

-3.0

-1.0

IVQ1973 to IQ1975

5

-3.1

-0.6

IQ1980 to IIIQ1980

2

-2.2

-1.1

IIIQ1981 to IVQ1982

4

-2.5

-0.64

IVQ2007 to IIQ2009

6

-4.3

-0.72

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

Table I-7 shows the mediocre average annual equivalent growth rate of 2.2 percent of the US economy in the nineteen quarters of the current cyclical expansion from IIIQ2009 to IQ2014. 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 eighteen quarters of expansion from IQ1983 to IIQ1987

· 4.9 percent in the nineteen quarters of expansion from IQ1983 to IIIQ1987.

The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011, 2.8 percent in 2012 and 1.9 percent in 2013 (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 and at 7.8 percent from IQ1983 to IVQ1983. GDP growth in the eight quarters of 2012 and 2013 and the first quarter of 2014 accumulated to 4.6 percent that is equivalent to 2.0 percent in a year. This is obtained by dividing GDP in IQ2014 of $15,946.6 billion by GDP in IVQ2011 of $15,242.1 billion and compounding by 4/9: {[($15,946.6/$15,242.1)4/9 -1]100 = 2.0%}. The US economy grew 2.3 percent in IQ2014 relative to the same quarter a year earlier in IQ2013. Another important revelation of the revisions and enhancements is that GDP was flat in IVQ2012 and IQ2014, which is just at the borderline of contraction. The rate of growth of GDP in the third estimate of IIIQ2013 is 4.1 percent in seasonally adjusted annual rate (SAAR). Inventory accumulation contributed 1.67 percentage points to this rate of growth. The actual rate without this impulse of unsold inventories would have been 2.43 percent, or 0.6 percent in IIIQ2013, such that annual equivalent growth in 2013 is closer to 2.2 percent {[(1.003)(1.006)(1.006)(1.007)4/4-1]100 = 2.2%}, compounding the quarterly rates and converting into annual equivalent.

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

 

Number
of
Quarters

Cumulative Growth

∆%

Average Annual Equivalent Growth Rate

IIIQ 1954 to IQ1957

11

12.8

4.5

First Four Quarters IIIQ1954 to IIQ1955

4

7.8

 

IIQ1958 to IIQ1959

5

10.0

7.9

First Four Quarters

IIIQ1958 to IIQ1959

4

9.2

 

IIQ1975 to IVQ1976

8

8.3

4.1

First Four Quarters IIIQ1975 to IIQ1976

4

6.1

 

IQ1983-IQ1986

IQ1983-IIIQ1986

IQ1983-IVQ1986

IQ1983-IQ1987

IQ1983-IIQ1987

IQ1983 to IIIQ1987

13

15

16

17

18

19

19.9

21.6

22.3

23.1

24.5

25.6

5.7

5.4

5.2

5.0

5.0

4.9

First Four Quarters IQ1983 to IVQ1983

4

7.8

 

Average First Four Quarters in Four Expansions*

 

7.7

 

IIIQ2009 to IQ2014

19

11.1

2.2

First Four Quarters IIIQ2009 to IIQ2010

 

2.7

 

*First Four Quarters: 7.8% IIIQ1954-IIQ1955; 9.2% IIIQ1958-IIQ1959; 6.1% IIIQ1975-IIQ1976; 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 2013 and the whole cycle from 1979 to 1986. In the entire cycle from 2007 to 2013, the number employed fell 2.118 million, full-time employed fell 4.777 million, part-time for economic reasons increased 3.534 and population increased 13.812 million. The number employed fell 1.5 percent, full-time employed fell 3.9 percent, part-time for economic reasons increased 80.3 percent and population increased 6.0 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 1986, the number employed increased 10.773 million, full-time employed increased 7.875 million, part-time for economic reasons 2.011 million and population 15.724 million. In the entire cycle from 1979 to 1986, the number employed increased 10.9 percent, full-time employed 9.5 percent, part-time for economic reasons 56.2 percent and population 9.5 million. 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

∆2007-2013

-2.118

-4.777

3.534

13.812

∆% 2007-2013

-1.5

-3.9

80.3

6.0

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

∆1979-1986

10.773

7.875

2.011

15.724

∆% 1979-86

10.9

9.5

56.2

9.5

Source: Bureau of Labor Statistics

http://www.bls.gov/

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). Youth workers would obtain employment at a premium in an economy with declining population. In fact, there is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages. This is merely another case of theory without reality with dubious policy proposals. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design.

In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):

Y = ∑isiyi (1)

This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):

Y = ∑isiy*i + ∑iyis*i (2)

The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:

“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”

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 provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would not be secular but immediate. 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), 11-6). 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 27.4 million or 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.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, Thousands 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

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

4/14

247.4

118.1

145.8

155.8

62.6

58.9

9.1

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, Thousands 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

38.7

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

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

4/14

38.8

18.0

20.5

52.8

46.5

2.4

11.9

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. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.914 million in Jul 2006 with 19.684 million in Jul 2013 for 2.230 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 number of youth jobs fell from 19.368 million in Apr 2007 to 18.021 million in Apr 2014 or 1.347 million fewer youth 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 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 hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

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

Year

Jan

Feb

Mar

Apr

Sep

Oct

Nov

Dec

2001

19678

19745

19800

19778

19706

19694

19675

19547

2002

18653

19074

19091

19108

19466

19542

19397

19394

2003

18811

18880

18709

18873

18909

19139

19163

19136

2004

18852

18841

18752

19184

19158

19609

19615

19619

2005

18858

18670

18989

19071

19503

19794

19750

19733

2006

19003

19182

19291

19406

19604

19853

19903

20129

2007

19407

19415

19538

19368

19498

19564

19660

19361

2008

18724

18546

18745

19161

18818

18757

18454

18378

2009

17467

17606

17564

17739

16972

16671

16689

16615

2010

16166

16412

16587

16764

16874

16867

16946

16727

2011

16512

16638

16898

16970

17238

17532

17402

17234

2012

16944

17150

17301

17387

17687

17842

17877

17604

2013

17183

17257

17271

17593

18043

17976

18104

18106

2014

17372

17357

17939

18021

       

Source: Bureau of Labor Statistics

http://www.bls.gov/

Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2014. Employment level is sharply lower in Feb 2014 relative to the peak in 2007. The following Chart I-21A relates youth employment and youth civilian noninstitutional population.

clip_image024

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2014

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 2014. 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 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 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.

clip_image025

Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2014

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 2014. 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 Jan2014, 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. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.

clip_image026

Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2014

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. Many young people abandoned searches for employment, dropping from the labor force.

clip_image027

Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2014

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 Jan 2007 to 44.8 in Jan 2-14. 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. Chart I-21D shows vertical drop during the global recession without recovery.

clip_image028

Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2014

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 23 years increased from 2342 in 2007 to 3324 thousand in 2013 or by 0.982 million. The unemployment level ages 16 to 24 years rose from 2.074 million in Apr 2007 to 2.440 million in Apr 2014 or by 0.366 million. This situation may persist for many years.

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

Year

Jan

Feb

Mar

Apr

Oct

Nov

Dec

Annual

2001

2250

2258

2253

2095

2424

2470

2412

2371

2002

2754

2731

2822

2515

2468

2570

2374

2683

2003

2748

2740

2601

2572

2522

2522

2248

2746

2004

2767

2631

2588

2387

2572

2448

2294

2638

2005

2661

2787

2520

2398

2285

2369

2055

2521

2006

2366

2433

2216

2092

2252

2242

2007

2353

2007

2363

2230

2096

2074

2258

2250

2323

2342

2008

2633

2480

2347

2196

2842

2833

2928

2830

2009

3278

3457

3371

3321

3789

3699

3532

3760

2010

3983

3888

3748

3803

3731

3561

3352

3857

2011

3851

3696

3520

3365

3386

3287

3161

3634

2012

3416

3507

3294

3175

3285

3102

3153

3451

2013

3674

3449

3261

3129

3028

2721

2536

3324

2014

3051

3033

3002

2440

       

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

clip_image029

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2014

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. 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 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 in Apr 2007 to 11.9 percent in Apr 2014. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them.

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

Year

Jan

Feb

Mar

Apr

Sep

Oct

Nov

Dec

Annual

2001

10.3

10.3

10.2

9.6

10.5

11.0

11.2

11.0

10.6

2002

12.9

12.5

12.9

11.6

11.4

11.2

11.7

10.9

12.0

2003

12.7

12.7

12.2

12.0

12.5

11.6

11.6

10.5

12.4

2004

12.8

12.3

12.1

11.1

11.5

11.6

11.1

10.5

11.8

2005

12.4

13.0

11.7

11.2

10.7

10.3

10.7

9.4

11.3

2006

11.1

11.3

10.3

9.7

10.5

10.2

10.1

9.1

10.5

2007

10.9

10.3

9.7

9.7

11.0

10.3

10.3

10.7

10.5

2008

12.3

11.8

11.1

10.3

13.4

13.2

13.3

13.7

12.8

2009

15.8

16.4

16.1

15.8

18.2

18.5

18.1

17.5

17.6

2010

19.8

19.2

18.4

18.5

17.6

18.1

17.4

16.7

18.4

2011

18.9

18.2

17.2

16.5

17.0

16.2

15.9

15.5

17.3

2012

16.8

17.0

16.0

15.4

15.2

15.5

14.8

15.2

16.2

2013

17.6

16.7

15.9

15.1

14.8

14.4

13.1

12.3

15.5

2014

14.9

14.9

14.3

11.9

         

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

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 2014. 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.

clip_image030

Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2014

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 2014. 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 difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.9 percent during the recovery from IQ1983 to IVQ1985 and 4.9 percent from IQ1983 to IIIQ1987 compared with 2.2 percent on average during the first eighteen quarters of expansion from IIIQ2009 to IQ2014 (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html). US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 19 quarters from IIIQ2009 to IQ2014. 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 first estimate of GDP for IQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp1q14_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier). 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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth under trend in the entire cycle from IVQ2007 to IQ2014 would have accumulated to 21.2 percent. GDP in IQ2014 would be $18,172.7 billion if the US had grown at trend, which is higher by $2,226.1 billion than actual $15,946.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 27.4 million unemployed or underemployed equivalent to actual unemployment of 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,946.6 billion in IQ2014 or 6.3 percent at the average annual equivalent rate of 1.0 percent. 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.

clip_image031

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2014

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 Sep 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 actual number unemployed is likely much higher because many are not accounted who abandoned job searches in frustration there may not be a job for them. Recent improvements may be illusory.

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

Year

Jan

Feb

Mar

Apr

Sep

Oct

Nov

Dec

Annual

2000

1498

1392

1291

1062

1254

1202

1242

1217

1249

2001

1572

1587

1533

1421

1586

1722

1786

1901

1576

2002

2235

2280

2138

2101

1966

1945

2013

2210

2114

2003

2495

2415

2485

2287

2157

2032

2132

2130

2253

2004

2453

2397

2354

2160

1951

1931

2053

2086

2149

2005

2286

2286

2126

1939

1992

1875

1920

1963

2009

2006

2126

2056

1881

1843

1710

1607

1704

1794

1848

2007

2155

2138

2031

1871

1854

1885

1925

2120

1966

2008

2336

2336

2326

2104

2595

2728

3078

3485

2540

2009

4138

4380

4518

4172

4560

4492

4655

4960

4500

2010

5314

5307

5194

4770

4640

4576

4909

4762

4879

2011

5027

4837

4748

4373

4426

4375

4195

4182

4537

2012

4458

4472

4390

4037

3899

3800

3861

3927

4133

2013

4394

4107

3929

3689

3535

3632

3383

3378

3719

2014

3508

3490

3394

3006

         

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

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

clip_image032

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2014

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

The analysis by Kydland (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/kydland-bio.html) and Prescott (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/prescott-bio.html) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:

Ut = Unt – α(πtπe) α > 0 (1)

Where Ut is the rate of unemployment at current time t, Unt is the natural rate of unemployment, πt is the current rate of inflation and πe is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:

W = W(πt, Ut) (2)

The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (πt, Ut - Un) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent on average since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). The Bureau of Labor Statistics important report on productivity and costs released on May 7, 2014 (http://www.bls.gov/lpc/) supports the argument of decline of productivity in the US analyzed by Prescott and Ohanian (2014Feb). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2013. The data confirm the argument of Prescott and Ohanian (2014Feb): productivity increased cumulatively 2.5 percent from 2011 to 2013 at the average annual rate of 0.8 percent. The situation is direr by excluding growth of 1.5 percent in 2013, which leaves an average of 0.5 percent for 2011 and 2013. Average productivity growth for the entire economic cycle from 2007 to 2013 is only 1.6 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.1 percent and 3.3 percent in 2013 consisted on reducing labor hours.

Table II-2, US, Revised Nonfarm Business Sector Productivity and Costs Annual Average, ∆% Annual Average 

 

2013

∆%

2012 ∆%

2011 ∆%

2010 ∆%

2009 ∆%

2008  ∆%   

2007 ∆%

Productivity

0.5

1.5

0.5

3.3

3.1

0.8

1.6

Real Hourly Compensation

0.1

0.5

-0.7

0.4

1.5

-1.1

1.4

Unit Labor Costs

1.1

1.2

2.0

-1.2

-2.0

2.0

2.6

Source: US Bureau of Labor Statistics

http://www.bls.gov/lpc/

In the analysis of Hansen (1939, 3) of secular stagnation, economic progress consists of growth of real income per person driven by growth of productivity. The “constituent elements” of economic progress are “(a) inventions, (b) the discovery and development of new territory and new resources, and (c) the growth of population” (Hansen 1939, 3). Secular stagnation originates in decline of population growth and discouragement of inventions. According to Hansen (1939, 2), US population grew by 16 million in the 1920s but grew by one half or about 8 million in the 1930s with forecasts at the time of Hansen’s writing in 1938 of growth of around 5.3 million in the 1940s. Hansen (1939, 2) characterized demography in the US as “a drastic decline in the rate of population growth.” Hansen’s plea was to adapt economic policy to stagnation of population in ensuring full employment. In the analysis of Hansen (1939, 8), population caused half of the growth of US GDP per year. Growth of output per person in the US and Europe was caused by “changes in techniques and to the exploitation of new natural resources.” In this analysis, population caused 60 percent of the growth of capital formation in the US. Declining population growth would reduce growth of capital formation. Residential construction provided an important share of growth of capital formation. Hansen (1939, 12) argues that market power of imperfect competition discourages innovation with prolonged use of obsolete capital equipment. Trade unions would oppose labor-savings innovations. The combination of stagnating and aging population with reduced innovation caused secular stagnation. Hansen (1939, 12) concludes that there is role for public investments to compensate for lack of dynamism of private investment but with tough tax/debt issues.

The current application of Hansen’s (1938, 1939, 1941) proposition argues that secular stagnation occurs because full employment equilibrium can be attained only with negative real interest rates between minus 2 and minus 3 percent. Professor Lawrence H. Summers (2013Nov8) finds that “a set of older ideas that went under the phrase secular stagnation are not profoundly important in understanding Japan’s experience in the 1990s and may not be without relevance to America’s experience today” (emphasis added). Summers (2013Nov8) argues there could be an explanation in “that the short-term real interest rate that was consistent with full employment had fallen to -2% or -3% sometime in the middle of the last decade. Then, even with artificial stimulus to demand coming from all this financial imprudence, you wouldn’t see any excess demand. And even with a relative resumption of normal credit conditions, you’d have a lot of difficulty getting back to full employment.” The US economy could be in a situation where negative real rates of interest with fed funds rates close to zero as determined by the Federal Open Market Committee (FOMC) do not move the economy to full employment or full utilization of productive resources. Summers (2013Oct8) finds need of new thinking on “how we manage an economy in which the zero nominal interest rates is a chronic and systemic inhibitor of economy activity holding our economies back to their potential.”

Former US Treasury Secretary Robert Rubin (2014Jan8) finds three major risks in prolonged unconventional monetary policy of zero interest rates and quantitative easing: (1) incentive of delaying action by political leaders; (2) “financial moral hazard” in inducing excessive exposures pursuing higher yields of risker credit classes; and (3) major risks in exiting unconventional policy. Rubin (2014Jan8) proposes reduction of deficits by structural reforms that could promote recovery by improving confidence of business attained with sound fiscal discipline.

Professor John B. Taylor (2014Jan01, 2014Jan3) provides clear thought on the lack of relevance of Hansen’s contention of secular stagnation to current economic conditions. The application of secular stagnation argues that the economy of the US has attained full-employment equilibrium since around 2000 only with negative real rates of interest of minus 2 to minus 3 percent. At low levels of inflation, the so-called full-employment equilibrium of negative interest rates of minus 2 to minus 3 percent cannot be attained and the economy stagnates. Taylor (2014Jan01) analyzes multiple contradictions with current reality in this application of the theory of secular stagnation:

  • Secular stagnation would predict idle capacity, in particular in residential investment when fed fund rates were fixed at 1 percent from Jun 2003 to Jun 2004. Taylor (2014Jan01) finds unemployment at 4.4 percent with house prices jumping 7 percent from 2002 to 2003 and 14 percent from 2004 to 2005 before dropping from 2006 to 2007. GDP prices doubled from 1.7 percent to 3.4 percent when interest rates were low from 2003 to 2005.
  • Taylor (2014Jan01, 2014Jan3) finds another contradiction in the application of secular stagnation based on low interest rates because of savings glut and lack of investment opportunities. Taylor (2009) shows that there was no savings glut. The savings rate of the US in the past decade is significantly lower than in the 1980s.
  • Taylor (2014Jan01, 2014Jan3) finds another contradiction in the low ratio of investment to GDP currently and reduced investment and hiring by US business firms.
  • Taylor (2014Jan01, 2014Jan3) argues that the financial crisis and global recession were caused by weak implementation of existing regulation and departure from rules-based policies.
  • Taylor (2014Jan01, 2014Jan3) argues that the recovery from the global recession was constrained by a change in the regime of regulation and fiscal/monetary policies.

The analysis by Kydland (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/kydland-bio.html) and Prescott (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/prescott-bio.html) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:

Ut = Unt – α(πtπe) α > 0 (1)

Where Ut is the rate of unemployment at current time t, Unt is the natural rate of unemployment, πt is the current rate of inflation and πe is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:

W = W(πt, Ut) (2)

The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (πt, Ut - Un) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). The Bureau of Labor Statistics important report on productivity and costs released on Mar 6, 2014 (http://www.bls.gov/lpc/) supports the argument of decline of productivity in the US analyzed by Prescott and Ohanian (2014Feb). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2013. The data confirm the argument of Prescott and Ohanian (2014Feb): productivity increased cumulatively 2.5 percent from 2011 to 2013 at the average annual rate of 0.8 percent. The situation is direr by excluding growth of 1.5 percent in 2013, which leaves an average of 0.5 percent for 2011 and 2013. Average productivity growth for the entire economic cycle from 2007 to 2013 is only 1.6 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.1 percent and 3.3 percent in 2013 consisted on reducing labor hours.

In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):

Y = ∑isiyi (1)

This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):

Y = ∑isiy*i + ∑iyis*i (2)

The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:

“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. 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), 11-6). Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:

“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated. Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”

Chart II-7 provides nonfarm-business labor productivity, measured by output per hour, from 1947 to 2014. The rate of productivity increase continued in the early part of the 2000s but then softened and fell during the global recession. The interruption of productivity increases occurred exclusively in the current business cycle. Lazear and Spletzer (2012JHJul22) find “primarily cyclic” factors in explaining the frustration of currently depressed labor markets in the United States. Stagnation of productivity is another cyclic event and not secular trend. The theory and application of secular stagnation to current US economic conditions is void of reality.

clip_image033

Chart II-7, US, Nonfarm Business Labor Productivity, Output per Hour, 1947-2014, Index 2005=100

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

Table II-6 expands Table II-2 providing more complete measurements of the Productivity and Cost research of the Bureau of Labor Statistics. The proper emphasis of Prescott and Ohanian (2014Feb) is on the low productivity increases from 2011 to 2013. Labor productivity increased 3.3 percent in 2010 and 3.1 percent in 2009. There is much stronger yet not sustained performance in 2010 with productivity growing 3.3 percent because of growth of output of 3.2 percent with decline of hours worked of 0.1 percent. Productivity growth of 3.1 percent in 2009 consists of decline of output by 4.3 percent while hours worked collapsed 7.2 percent, which is not a desirable route to progress. The expansion phase of the economic cycle concentrated in one year, 2010, with underperformance in the remainder of the expansion from 2011 to 2013 of productivity growth at average 0.8 percent per year.

Table II-6, US, Productivity and Costs, Annual Percentage Changes 2007-2013

 

2013

2012

2011

2010

2009

2008

2007

Productivity

0.5

1.5

0.5

3.3

3.1

0.8

1.6

Output

2.2

3.7

2.5

3.2

-4.3

-1.3

2.3

Hours Worked

1.7

2.2

2.0

-0.1

-7.2

-2.0

0.7

Employment

1.8

2.0

1.5

-1.2

-5.7

-1.5

0.9

Average Weekly Hours Worked

-0.2

0.2

0.5

1.1

-1.6

-0.6

-0.2

Hourly Compensation

1.6

2.6

2.5

2.1

1.1

2.7

4.3

Consumer Price Inflation

1.5

2.1

3.2

1.6

-0.4

3.8

2.8

Real Hourly Compensation

0.1

0.5

-0.7

0.4

1.5

-1.1

1.4

Non-labor Payments

3.8

6.5

4.0

7.3

-0.1

-0.4

3.4

Output per Job

0.3

1.7

1.0

4.4

1.5

0.2

1.4

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

Productivity growth can bring about prosperity while productivity regression can jeopardize progress. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Table II-7 provides average growth rates of indicators in the research of productivity and growth of the US Bureau of Labor Statistics. There is dramatic decline of productivity growth in the whole cycle from 2.2 percent per year on average from 1947 to 2013 to 1.6 percent per year on average from 2007 to 2013. Productivity increased at the average rate of 2.3 percent from 1947 to 2007. There is profound drop in the average rate of output growth from 3.4 percent on average from 1947 to 2013 to 1.0 percent from 2007 to 2013. Output grew at 3.7 percent per year on average from 1947 to 2007. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions (Lucas 2011May). Growth under trend in the entire cycle from IVQ2007 to IQ2014 would have accumulated to 21.2 percent. GDP in IQ2014 would be $18,172.7 billion if the US had grown at trend, which is higher by $2,226.1 billion than actual $15,946.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 27.4 million unemployed or underemployed equivalent to actual unemployment of 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,946.6 billion in IQ2014 or 6.3 percent at the average annual equivalent rate of 1.0 percent. 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. The antithesis of secular stagnation is cyclical slow growth. The policy design deserves consideration of Kydland and Prescott (1977) and Prescott and Ohanian (2014Feb) to induce productivity growth for future progress. Hourly compensation increased at the average yearly rate of 5.1 percent from 1947 to 2013 and consumer price inflation at 3.6 percent with real hourly compensation increasing at the average yearly rate of 1.6 percent. Hourly compensation increased at the average yearly rate of 2.1 percent from 2007 to 2013 while consumer price inflation increased at 2.0 percent with real hourly compensation changing at the average yearly rate of 0.0 percent. Hourly compensation increased at the average rate of 5.4 percent from 1947 to 2007 and the consumer price index at 3.8 percent for real hourly compensation of 1.7 percent per year. While hours worked increased at the average yearly rate of 1.2 percent from 1947 to 2013, hours worked fell 3.7 percent from 2007 to 2013. Hours worked increased at the average rate of 1.4 percent from 1947 to 2007. While employment increased at the average yearly rate of 1.4 percent from 1947 to 2013, employment fell 3.3 percent from 2007 to 2013. Employment increased at the average rate of 1.6 percent from 1947 to 2007.

Table II-7, US, Productivity and Costs, Average Annual Percentage Changes 2007-2013 and 1947-2013

 

Average Annual Percentage Rate 2007-2013

Average Annual Percentage Rate 1947-2007

Average Annual Percentage Rate  1947-2013

Productivity

1.6

2.3

2.2

Output

1.0

3.7

3.4

Hours

-3.7*

1.4

1.2

Employment

-3.3*

1.6

1.4

Average Weekly Hours

-0.5*

-14.6*

-15.0*

Hourly Compensation

2.1

5.4

5.1

Consumer Price Inflation

2.0

3.8

3.6

Real Hourly Compensation

0.1

1.7

1.6

Unit Non-labor Payments

2.5

3.5

3.4

Output per Job

1.5

2.0

2.0

* Percentage Change

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

Unit labor costs increased sharply during the Great Inflation from the late 1960s to 1981 as shown by sharper slope in Chart II-8. Unit labor costs continued to increase but at a lower rate because of cyclic factors and not because of imaginary secular stagnation.

clip_image034

Chart II-8, US, Nonfarm Business, Unit Labor Costs, 1947-2014, Index 2009=100

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

Real hourly compensation increased at relatively high rates after 1947 to the early 1970s but reached a plateau that lasted until the early 1990s, as shown in Chart II-9. There were rapid increases until the global recession. Cyclic factors and not alleged secular stagnation explain the interruption of increases in real hourly compensation.

clip_image035

Chart II-9, US, Nonfarm Business, Real Hourly Compensation, 1947-2014, Index 2009=100

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

II Rules, Discretionary Authorities and Slow Productivity Growth. The Bureau of Labor Statistics (BLS) of the Department of Labor provides the quarterly report on productivity and costs. The operational definition of productivity used by the BLS is (http://www.bls.gov/news.release/pdf/prod2.pdf 1): “Labor productivity, or output per hour, is calculated by dividing an index of real output by an index of hours worked of all persons, including employees, proprietors, and unpaid family workers.” The BLS has revised the estimates for productivity and unit costs. Table II-1 provides the new estimate for IQ2014 and revised data for nonfarm business sector productivity and unit labor costs for IVQ2013 and IIIQ2013 in seasonally adjusted annual equivalent (SAAE) rate and the percentage change from the same quarter a year earlier. Reflecting increases in output of 0.3 percent and of 2.0 percent in hours worked, nonfarm business sector labor productivity decreased at a SAAE rate of 1.7 percent in IQ2014, as shown in column 2 “IQ2014 SAEE.” The increase of labor productivity from IQ2013 to IQ2014 was 1.4 percent, reflecting increases in output of 3.2 percent and of hours worked of 1.7 percent, as shown in column 3 “IQ2014 YoY.” Hours worked increased from 1.9 percent in IIIQ2013 in SAAE to 1.4 percent in IVQ2013 and 2.0 percent in IQ2014 while output growth decreased from 5.4 percent in IIIQ2013 to 3.8 percent in IVQ2013 and 0.3 percent in IQ2014. The BLS defines unit labor costs as (http://www.bls.gov/news.release/pdf/prod2.pdf 1): “BLS defines unit labor costs as the ratio of hourly compensation to labor productivity; increases in hourly compensation tend to increase unit labor costs and increases in output per hour tend to reduce them.” Unit labor costs increased at the SAAE rate of 4.2 percent in IQ2014 and increased 0.9 percent in IQ2014 relative to IQ2013. Hourly compensation increased at the SAAE rate of 2.4 percent in IQ2014, which deflating by the estimated consumer price increase SAAE rate in IQ2014 results in increase of real hourly compensation at 0.5 percent. Real hourly compensation increased 0.9 percent in IQ2014 relative to IQ2013.

Table II-1, US, Nonfarm Business Sector Productivity and Costs %

 

IQ
2014
SAAE

IQ
2014
YoY

IVQ 2013 SAAE

IVQ 2013 YoY

IIIQ 2013 SSAE

IIIQ 2013 YOY

Productivity

-1.7

1.4

2.3

1.4

3.5

0.5

Output

0.3

3.2

3.8

3.0

5.4

2.3

Hours

2.0

1.7

1.4

1.6

1.9

1.8

Hourly
Comp.

2.4

2.3

1.9

0.4

1.3

2.4

Real Hourly Comp.

0.5

0.9

0.6

-0.8

-0.7

0.8

Unit Labor Costs

4.2

0.9

-0.4

-1.0

-2.1

1.9

Unit Nonlabor Payments

-2.7

2.1

3.8

4.5

8.5

0.3

Implicit Price Deflator

1.1

1.4

1.4

1.3

2.4

1.2

Notes: SAAE: seasonally adjusted annual equivalent; Comp.: compensation; YoY: Quarter on Same Quarter Year Earlier

Source: US Bureau of Labor Statistics

http://www.bls.gov/lpc/

The analysis by Kydland (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/kydland-bio.html) and Prescott (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/prescott-bio.html) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:

Ut = Unt – α(πtπe) α > 0 (1)

Where Ut is the rate of unemployment at current time t, Unt is the natural rate of unemployment, πt is the current rate of inflation and πe is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:

W = W(πt, Ut) (2)

The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (πt, Ut - Un) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent on average since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). The Bureau of Labor Statistics important report on productivity and costs released on May 7, 2014 (http://www.bls.gov/lpc/) supports the argument of decline of productivity in the US analyzed by Prescott and Ohanian (2014Feb). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2013. The data confirm the argument of Prescott and Ohanian (2014Feb): productivity increased cumulatively 2.5 percent from 2011 to 2013 at the average annual rate of 0.8 percent. The situation is direr by excluding growth of 1.5 percent in 2013, which leaves an average of 0.5 percent for 2011 and 2013. Average productivity growth for the entire economic cycle from 2007 to 2013 is only 1.6 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.1 percent and 3.3 percent in 2013 consisted on reducing labor hours.

Table II-2, US, Revised Nonfarm Business Sector Productivity and Costs Annual Average, ∆% Annual Average 

 

2013

∆%

2012 ∆%

2011 ∆%

2010 ∆%

2009 ∆%

2008  ∆%   

2007 ∆%

Productivity

0.5

1.5

0.5

3.3

3.1

0.8

1.6

Real Hourly Compensation

0.1

0.5

-0.7

0.4

1.5

-1.1

1.4

Unit Labor Costs

1.1

1.2

2.0

-1.2

-2.0

2.0

2.6

Source: US Bureau of Labor Statistics

http://www.bls.gov/lpc/

Productivity jumped in the recovery after the recession from Mar IQ2001 to Nov IVQ2001 (http://www.nber.org/cycles.html). Table II-3 provides quarter on quarter and annual percentage changes in nonfarm business output per hour, or productivity, from 1999 to 2013. The annual average jumped from 2.7 percent in 2001 to 4.3 percent in 2002. Nonfarm business productivity increased at the SAAE rate of 9.5 percent in the first quarter after the recession in IQ2002. Productivity increases decline later in the expansion period. Productivity increases were mediocre during the recession from Dec IVQ2007 to Jun IIIQ2009 (http://www.nber.org/cycles.html) and increased during the first phase of expansion from IIQ2009 to IQ2010, trended lower and collapsed in 2011 and 2012 with sporadic jumps and declines. Productivity increased at 2.3 percent in IVQ2013 and contracted at 1.7 percent in IQ2014.

Table II-3, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2014

Year

Qtr1

Qtr2

Qtr3

Qtr4

Annual

1999

4.5

0.8

3.5

6.8

3.5

2000

-1.4

8.6

0.1

3.9

3.3

2001

-1.2

6.8

2.3

4.8

2.7

2002

9.5

0.3

3.1

-0.7

4.3

2003

4.0

5.7

9.0

3.7

3.7

2004

0.0

4.2

1.2

1.2

3.1

2005

4.6

-0.3

2.9

0.1

2.1

2006

2.6

-0.3

-1.8

3.2

0.9

2007

0.4

2.7

4.6

1.8

1.6

2008

-3.9

4.0

0.9

-2.7

0.8

2009

3.2

8.0

5.9

4.8

3.1

2010

2.0

1.2

2.4

1.9

3.3

2011

-2.7

1.6

-0.3

3.2

0.5

2012

1.7

1.1

2.1

-1.5

1.5

2013

-1.8

1.8

3.5

2.3

0.5

2014

-1.7

       

Source: US Bureau of Labor Statistics

http://www.bls.gov/lpc/

Chart II-1 of the Bureau of Labor Statistics (BLS) provides SAAE rates of nonfarm business productivity from 1999 to 2014. There is a clear pattern in both episodes of economic cycles in 2001 and 2007 of rapid expansion of productivity in the transition from contraction to expansion followed by more subdued productivity expansion. Part of the explanation is the reduction in labor utilization resulting from adjustment of business to the sudden shock of collapse of revenue. Productivity rose briefly in the expansion after 2009 but then collapsed and moved to negative change with some positive changes recently at lower rates. Contractions in the cycle from 2007 to 2014 have been more frequent and sharper.

clip_image036

Chart II-1, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2014

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

Percentage changes from prior quarter at SAAE rates and annual average percentage changes of nonfarm business unit labor costs are provided in Table II-4. Unit labor costs fell during the contractions with continuing negative percentage changes in the early phases of the recovery. Weak labor markets partly explain the decline in unit labor costs. As the economy moves toward full employment, labor markets tighten with increase in unit labor costs. The expansion beginning in IIIQ2009 has been characterized by high unemployment and underemployment. Table II-4 shows continuing subdued increases in unit labor costs in 2011 but with increase of 7.4 percent in IQ2012 followed by increase of 0.7 percent in IIQ2012, decline of 1.8 percent in IIIQ2012 and increase of 11.8 percent in IVQ2012. Unit labor costs decreased at 3.5 percent in IQ2013 and increased at 2.0 percent in IIQ2013. Unit labor costs decreased at 2.1 percent in IIIQ2013 and at 0.4 percent in IVQ2013. Unit labor costs increased at 4.2 percent in IQ2014.

Table II-4, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2014

Year

Qtr1

Qtr2

Qtr3

Qtr4

Annual

1999

2.0

0.1

-0.1

1.7

0.7

2000

17.5

-6.8

8.2

-1.6

4.0

2001

11.4

-5.4

-1.7

-1.3

1.6

2002

-6.7

3.3

-1.1

1.8

-1.9

2003

-1.4

1.5

-2.7

1.7

0.1

2004

-0.6

3.7

5.8

0.6

1.4

2005

-1.5

2.5

2.1

2.4

1.5

2006

6.0

0.4

2.3

4.0

3.0

2007

9.8

-2.7

-3.2

2.6

2.6

2008

8.2

-3.6

2.5

7.3

2.0

2009

-12.3

1.9

-2.9

-2.2

-2.0

2010

-4.4

3.5

-0.1

-0.1

-1.2

2011

10.2

-2.9

3.0

-7.3

2.0

2012

7.4

0.7

-1.8

11.8

1.2

2013

-3.5

2.0

-2.1

-0.4

1.1

2014

4.2

       

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

Chart II-2 provides percentage change from prior quarter at annual rate of nonfarm business real hourly compensation from 1999 to 2013. There are significant fluctuations in quarterly percentage changes oscillating between positive and negative. There is no clear pattern in the two contractions in the 2000s.

clip_image037

Chart II-2, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2014

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

Table II-5 provides percentage change from prior quarter at annual rates for nonfarm business real hourly worker compensation. The expansion after the contraction of 2001 was followed by strong recovery of real hourly compensation. Real hourly compensation increased at the rate of 2.9 percent in IQ2011 but fell at annual rates of 6.1 percent in IIQ2011 and 5.7 percent in IVQ2011. Real hourly compensation increased at 6.9 percent in IQ2012 and at 0.4 percent in IIQ2012, declining at 1.4 percent in IIIQ2012 and increasing at 7.5 percent in IVQ2012. Real hourly compensation fell 0.7 percent in 2011 and increased 0.5 percent in 2012. Real hourly compensation fell at 6.4 percent in IQ2013 and increased at 3.3 percent in IIQ2013, falling at 0.7 percent in IIIQ2013. Real hourly compensation increased at 0.6 percent in IVQ2013 and at 0.5 percent in IQ2014. The annual rate of increase of real hourly compensation for 2013 is 0.1 percent.

Table II-5, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate 1999-2014

Year

Qtr1

Qtr2

Qtr3

Qtr4

Annual

1999

5.0

-2.0

0.3

5.5

2.0

2000

11.5

-1.8

4.4

-0.5

3.9

2001

6.0

-1.8

-0.7

4.0

1.5

2002

0.7

0.4

-0.2

-1.4

0.7

2003

-1.5

8.0

2.9

3.9

1.5

2004

-3.9

4.8

4.2

-2.5

1.8

2005

1.2

-0.6

-1.1

-1.2

0.3

2006

6.4

-3.3

-3.4

9.2

0.6

2007

6.0

-4.5

-1.2

-0.5

1.4

2008

-0.5

-4.7

-2.7

14.6

-1.1

2009

-7.1

7.9

-0.6

-0.8

1.5

2010

-3.0

4.7

1.1

-1.2

0.4

2011

2.9

-6.1

0.0

-5.7

-0.7

2012

6.9

0.4

-1.4

7.5

0.5

2013

-6.4

3.3

-0.7

0.6

0.1

2014

0.5

       

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

Chart II-3 provides percentage change from prior quarter at annual rate of nonfarm business real hourly compensation. There have been multiple negative percentage quarterly changes in the current cycle since IVQ2007.

clip_image038

Chart II-3, US, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate 1999-2014

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

Chart II-4 provides percentage change of nonfarm business output per hour in a quarter relative to the same quarter a year earlier. As in most series of real output, productivity increased sharply in 2010 but the momentum was lost after 2011 as with the rest of the real economy.

clip_image039

Chart II-4, US, Nonfarm Business Output per Hour, Percent Change from Same Quarter a Year Earlier 1999-2014

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

Chart II-5 provides percentage changes of nonfarm business unit labor costs relative to the same quarter a year earlier. Softening of labor markets caused relatively high yearly percentage changes in the recession of 2001 repeated in the recession in 2009. Recovery was strong in 2010 but then weakened.

clip_image040

Chart II-5, US, Nonfarm Business Unit Labor Costs, Percent Change from Same Quarter a Year Earlier 1999-2014

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

Chart II-6 provides percentage changes in a quarter relative to the same quarter a year earlier for nonfarm business real hourly compensation. Labor compensation eroded sharply during the recession with brief recovery in 2010 and another fall until recently.

clip_image041

Chart II-6, US, Nonfarm Business Real Hourly Compensation, Percent Change from Same Quarter a Year Earlier 1999-2014

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

In the analysis of Hansen (1939, 3) of secular stagnation, economic progress consists of growth of real income per person driven by growth of productivity. The “constituent elements” of economic progress are “(a) inventions, (b) the discovery and development of new territory and new resources, and (c) the growth of population” (Hansen 1939, 3). Secular stagnation originates in decline of population growth and discouragement of inventions. According to Hansen (1939, 2), US population grew by 16 million in the 1920s but grew by one half or about 8 million in the 1930s with forecasts at the time of Hansen’s writing in 1938 of growth of around 5.3 million in the 1940s. Hansen (1939, 2) characterized demography in the US as “a drastic decline in the rate of population growth.” Hansen’s plea was to adapt economic policy to stagnation of population in ensuring full employment. In the analysis of Hansen (1939, 8), population caused half of the growth of US GDP per year. Growth of output per person in the US and Europe was caused by “changes in techniques and to the exploitation of new natural resources.” In this analysis, population caused 60 percent of the growth of capital formation in the US. Declining population growth would reduce growth of capital formation. Residential construction provided an important share of growth of capital formation. Hansen (1939, 12) argues that market power of imperfect competition discourages innovation with prolonged use of obsolete capital equipment. Trade unions would oppose labor-savings innovations. The combination of stagnating and aging population with reduced innovation caused secular stagnation. Hansen (1939, 12) concludes that there is role for public investments to compensate for lack of dynamism of private investment but with tough tax/debt issues.

The current application of Hansen’s (1938, 1939, 1941) proposition argues that secular stagnation occurs because full employment equilibrium can be attained only with negative real interest rates between minus 2 and minus 3 percent. Professor Lawrence H. Summers (2013Nov8) finds that “a set of older ideas that went under the phrase secular stagnation are not profoundly important in understanding Japan’s experience in the 1990s and may not be without relevance to America’s experience today” (emphasis added). Summers (2013Nov8) argues there could be an explanation in “that the short-term real interest rate that was consistent with full employment had fallen to -2% or -3% sometime in the middle of the last decade. Then, even with artificial stimulus to demand coming from all this financial imprudence, you wouldn’t see any excess demand. And even with a relative resumption of normal credit conditions, you’d have a lot of difficulty getting back to full employment.” The US economy could be in a situation where negative real rates of interest with fed funds rates close to zero as determined by the Federal Open Market Committee (FOMC) do not move the economy to full employment or full utilization of productive resources. Summers (2013Oct8) finds need of new thinking on “how we manage an economy in which the zero nominal interest rates is a chronic and systemic inhibitor of economy activity holding our economies back to their potential.”

Former US Treasury Secretary Robert Rubin (2014Jan8) finds three major risks in prolonged unconventional monetary policy of zero interest rates and quantitative easing: (1) incentive of delaying action by political leaders; (2) “financial moral hazard” in inducing excessive exposures pursuing higher yields of risker credit classes; and (3) major risks in exiting unconventional policy. Rubin (2014Jan8) proposes reduction of deficits by structural reforms that could promote recovery by improving confidence of business attained with sound fiscal discipline.

Professor John B. Taylor (2014Jan01, 2014Jan3) provides clear thought on the lack of relevance of Hansen’s contention of secular stagnation to current economic conditions. The application of secular stagnation argues that the economy of the US has attained full-employment equilibrium since around 2000 only with negative real rates of interest of minus 2 to minus 3 percent. At low levels of inflation, the so-called full-employment equilibrium of negative interest rates of minus 2 to minus 3 percent cannot be attained and the economy stagnates. Taylor (2014Jan01) analyzes multiple contradictions with current reality in this application of the theory of secular stagnation:

  • Secular stagnation would predict idle capacity, in particular in residential investment when fed fund rates were fixed at 1 percent from Jun 2003 to Jun 2004. Taylor (2014Jan01) finds unemployment at 4.4 percent with house prices jumping 7 percent from 2002 to 2003 and 14 percent from 2004 to 2005 before dropping from 2006 to 2007. GDP prices doubled from 1.7 percent to 3.4 percent when interest rates were low from 2003 to 2005.
  • Taylor (2014Jan01, 2014Jan3) finds another contradiction in the application of secular stagnation based on low interest rates because of savings glut and lack of investment opportunities. Taylor (2009) shows that there was no savings glut. The savings rate of the US in the past decade is significantly lower than in the 1980s.
  • Taylor (2014Jan01, 2014Jan3) finds another contradiction in the low ratio of investment to GDP currently and reduced investment and hiring by US business firms.
  • Taylor (2014Jan01, 2014Jan3) argues that the financial crisis and global recession were caused by weak implementation of existing regulation and departure from rules-based policies.
  • Taylor (2014Jan01, 2014Jan3) argues that the recovery from the global recession was constrained by a change in the regime of regulation and fiscal/monetary policies.

The analysis by Kydland (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/kydland-bio.html) and Prescott (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/prescott-bio.html) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:

Ut = Unt – α(πtπe) α > 0 (1)

Where Ut is the rate of unemployment at current time t, Unt is the natural rate of unemployment, πt is the current rate of inflation and πe is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:

W = W(πt, Ut) (2)

The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (πt, Ut - Un) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). The Bureau of Labor Statistics important report on productivity and costs released on Mar 6, 2014 (http://www.bls.gov/lpc/) supports the argument of decline of productivity in the US analyzed by Prescott and Ohanian (2014Feb). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2013. The data confirm the argument of Prescott and Ohanian (2014Feb): productivity increased cumulatively 2.5 percent from 2011 to 2013 at the average annual rate of 0.8 percent. The situation is direr by excluding growth of 1.5 percent in 2013, which leaves an average of 0.5 percent for 2011 and 2013. Average productivity growth for the entire economic cycle from 2007 to 2013 is only 1.6 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.1 percent and 3.3 percent in 2013 consisted on reducing labor hours.

In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):

Y = ∑isiyi (1)

This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):

Y = ∑isiy*i + ∑iyis*i (2)

The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:

“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. 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), 11-6). Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:

“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated. Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”

Chart II-7 provides nonfarm-business labor productivity, measured by output per hour, from 1947 to 2014. The rate of productivity increase continued in the early part of the 2000s but then softened and fell during the global recession. The interruption of productivity increases occurred exclusively in the current business cycle. Lazear and Spletzer (2012JHJul22) find “primarily cyclic” factors in explaining the frustration of currently depressed labor markets in the United States. Stagnation of productivity is another cyclic event and not secular trend. The theory and application of secular stagnation to current US economic conditions is void of reality.

clip_image033[1]

Chart II-7, US, Nonfarm Business Labor Productivity, Output per Hour, 1947-2014, Index 2005=100

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

Table II-6 expands Table II-2 providing more complete measurements of the Productivity and Cost research of the Bureau of Labor Statistics. The proper emphasis of Prescott and Ohanian (2014Feb) is on the low productivity increases from 2011 to 2013. Labor productivity increased 3.3 percent in 2010 and 3.1 percent in 2009. There is much stronger yet not sustained performance in 2010 with productivity growing 3.3 percent because of growth of output of 3.2 percent with decline of hours worked of 0.1 percent. Productivity growth of 3.1 percent in 2009 consists of decline of output by 4.3 percent while hours worked collapsed 7.2 percent, which is not a desirable route to progress. The expansion phase of the economic cycle concentrated in one year, 2010, with underperformance in the remainder of the expansion from 2011 to 2013 of productivity growth at average 0.8 percent per year.

Table II-6, US, Productivity and Costs, Annual Percentage Changes 2007-2013

 

2013

2012

2011

2010

2009

2008

2007

Productivity

0.5

1.5

0.5

3.3

3.1

0.8

1.6

Output

2.2

3.7

2.5

3.2

-4.3

-1.3

2.3

Hours Worked

1.7

2.2

2.0

-0.1

-7.2

-2.0

0.7

Employment

1.8

2.0

1.5

-1.2

-5.7

-1.5

0.9

Average Weekly Hours Worked

-0.2

0.2

0.5

1.1

-1.6

-0.6

-0.2

Hourly Compensation

1.6

2.6

2.5

2.1

1.1

2.7

4.3

Consumer Price Inflation

1.5

2.1

3.2

1.6

-0.4

3.8

2.8

Real Hourly Compensation

0.1

0.5

-0.7

0.4

1.5

-1.1

1.4

Non-labor Payments

3.8

6.5

4.0

7.3

-0.1

-0.4

3.4

Output per Job

0.3

1.7

1.0

4.4

1.5

0.2

1.4

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

Productivity growth can bring about prosperity while productivity regression can jeopardize progress. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Table II-7 provides average growth rates of indicators in the research of productivity and growth of the US Bureau of Labor Statistics. There is dramatic decline of productivity growth in the whole cycle from 2.2 percent per year on average from 1947 to 2013 to 1.6 percent per year on average from 2007 to 2013. Productivity increased at the average rate of 2.3 percent from 1947 to 2007. There is profound drop in the average rate of output growth from 3.4 percent on average from 1947 to 2013 to 1.0 percent from 2007 to 2013. Output grew at 3.7 percent per year on average from 1947 to 2007. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions (Lucas 2011May). Growth under trend in the entire cycle from IVQ2007 to IQ2014 would have accumulated to 21.2 percent. GDP in IQ2014 would be $18,172.7 billion if the US had grown at trend, which is higher by $2,226.1 billion than actual $15,946.6 billion. There are about two trillion dollars of GDP less than under trend, explaining the 27.4 million unemployed or underemployed equivalent to actual unemployment of 16.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,946.6 billion in IQ2014 or 6.3 percent at the average annual equivalent rate of 1.0 percent. 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. The antithesis of secular stagnation is cyclical slow growth. The policy design deserves consideration of Kydland and Prescott (1977) and Prescott and Ohanian (2014Feb) to induce productivity growth for future progress. Hourly compensation increased at the average yearly rate of 5.1 percent from 1947 to 2013 and consumer price inflation at 3.6 percent with real hourly compensation increasing at the average yearly rate of 1.6 percent. Hourly compensation increased at the average yearly rate of 2.1 percent from 2007 to 2013 while consumer price inflation increased at 2.0 percent with real hourly compensation changing at the average yearly rate of 0.0 percent. Hourly compensation increased at the average rate of 5.4 percent from 1947 to 2007 and the consumer price index at 3.8 percent for real hourly compensation of 1.7 percent per year. While hours worked increased at the average yearly rate of 1.2 percent from 1947 to 2013, hours worked fell 3.7 percent from 2007 to 2013. Hours worked increased at the average rate of 1.4 percent from 1947 to 2007. While employment increased at the average yearly rate of 1.4 percent from 1947 to 2013, employment fell 3.3 percent from 2007 to 2013. Employment increased at the average rate of 1.6 percent from 1947 to 2007.

Table II-7, US, Productivity and Costs, Average Annual Percentage Changes 2007-2013 and 1947-2013

 

Average Annual Percentage Rate 2007-2013

Average Annual Percentage Rate 1947-2007

Average Annual Percentage Rate  1947-2013

Productivity

1.6

2.3

2.2

Output

1.0

3.7

3.4

Hours

-3.7*

1.4

1.2

Employment

-3.3*

1.6

1.4

Average Weekly Hours

-0.5*

-14.6*

-15.0*

Hourly Compensation

2.1

5.4

5.1

Consumer Price Inflation

2.0

3.8

3.6

Real Hourly Compensation

0.1

1.7

1.6

Unit Non-labor Payments

2.5

3.5

3.4

Output per Job

1.5

2.0

2.0

* Percentage Change

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

Unit labor costs increased sharply during the Great Inflation from the late 1960s to 1981 as shown by sharper slope in Chart II-8. Unit labor costs continued to increase but at a lower rate because of cyclic factors and not because of imaginary secular stagnation.

clip_image034[1]

Chart II-8, US, Nonfarm Business, Unit Labor Costs, 1947-2014, Index 2009=100

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

Real hourly compensation increased at relatively high rates after 1947 to the early 1970s but reached a plateau that lasted until the early 1990s, as shown in Chart II-9. There were rapid increases until the global recession. Cyclic factors and not alleged secular stagnation explain the interruption of increases in real hourly compensation.

clip_image035[1]

Chart II-9, US, Nonfarm Business, Real Hourly Compensation, 1947-2014, Index 2009=100

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

IIA United States International Trade. Table IIA-1 provides the trade balance of the US and monthly growth of exports and imports seasonally adjusted with the latest release and revisions (http://www.census.gov/foreign-trade/). Because of heavy dependence on imported oil, fluctuations in the US trade account originate largely in fluctuations of commodity futures prices caused by carry trades from zero interest rates into commodity futures exposures in a process similar to world inflation waves (http://cmpassocregulationblog.blogspot.com/2014/04/imf-view-world-inflation-waves-squeeze.html). The Census Bureau revised data for 2013. The US trade balance improved from deficits of $39,770 million in Oct 2013 and $43,434 million in Sep 2013 to deficit of $35,171 million in Nov 2013 but higher deficit of $38,975 million in Dec 2013. The trade deficit increased to $39,280 million in Jan 2014 and deficit of $41,784 million in Feb 2014. The trade deficit fell to $40,738 million in Mar 2014. Exports increased 0.8 percent in Nov 2013 while imports fell 1.3 percent. Exports fell 1.7 percent in Dec 2013 while imports increased 0.2 percent. Exports increased 0.6 percent in Jan 2014 and imports increased 0.6 percent. In Feb 2014, exports fell 1.3 percent while imports changed 0.4 percent. Exports increased 2.1 percent in Mar 2013 while imports increased 1.1 percent. The trade balance deteriorated from cumulative deficit of $499,379 million in Jan-Dec 2010 to deficit of $556,838 million in Jan-Dec 2011 and improved to marginally lower deficit of $534,656 million in Jan-Dec 2012. The trade deficit improved to $474,864 million in Jan-Dec 2013.

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

 

Trade Balance

Exports

Month ∆%

Imports

Month ∆%

Mar 2014

-40,738

193,910

2.1

234,288

1.1

Feb

-41,874

189,963

-1.3

231,837

0.0

Jan

-39,280

192,459

0.6

231,740

0.6

Dec 2013

-38,975

191,290

-1.7

230,265

0.2

Nov

-35,171

194,644

0.8

229,815

-1.3

Oct

-39,770

193,112

2.0

232,882

0.1

Sep

-43,434

189,251

-0.2

232,685

1.7

Aug

-39,207

189,635

-0.1

228,842

0.1

Jul

-38,900

189,753

-0.7

228,652

1.4

Jun

-34,414

191,055

2.2

225,469

-2.2

May

-43,661

186,909

-0.2

230,571

1.7

Apr

-39,374

187,308

1.4

226,682

2.4

Mar

-36,562

184,758

-1.1

221,321

-3.8

Feb

-43,257

186,880

0.0

230,137

0.5

Jan

-42,139

186,789

-1.0

228,928

0.9

Jan-Dec 2013

-474,864

2,271,385

 

2,746,249

 

Dec 2012

-38,307

188,686

1.9

226,994

-2.0

Nov

-46,422

185,220

1.4

231,641

2.8

Oct

-42,650

182,655

-2.2

225,304

-1.4

Sep

-41,570

186,829

2.6

228,400

1.0

Aug

-44,007

182,071

-0.7

226,078

-0.3

Jul

-43,451

183,375

-1.0

226,826

-0.4

Jun

-42,430

185,218

0.5

227,648

-1.2

May

-46,247

184,217

0.0

230,464

-0.2

Apr

-46,625

184,267

-1.2

230,892

-1.5

Mar

-47,790

186,505

2.4

234,295

3.7

Feb

-43,763

182,064

1.4

225,827

-2.2

Jan

-51,393

179,477

0.2

230,871

0.2

Jan-Dec 2012

-534,656

2,210,585

 

2,745,240

 

Jan-Dec
2011

-556,838

2,112,825

 

2,669,663

 

Jan-Dec
2010

-499,379

1,844,468

 

2,343,847

 

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

Period

Balance

∆%

Exports

∆%

Imports

∆%

1960

4,608

(X)

19,626

(X)

15,018

(X)

1961

5,476

18.8

20,190

2.9

14,714

-2.0

1962

4,583

-16.3

20,973

3.9

16,390

11.4

1963

5,289

15.4

22,427

6.9

17,138

4.6

1964

7,006

32.5

25,690

14.5

18,684

9.0

1965

5,333

-23.9

26,699

3.9

21,366

14.4

1966

3,837

-28.1

29,379

10.0

25,542

19.5

1967

4,122

7.4

30,934

5.3

26,812

5.0

1968

837

-79.7

34,063

10.1

33,226

23.9

1969

1,289

54.0

37,332

9.6

36,043

8.5

1970

3,224

150.1

43,176

15.7

39,952

10.8

1971

-1,476

-145.8

44,087

2.1

45,563

14.0

1972

-5,729

288.1

49,854

13.1

55,583

22.0

1973

2,389

-141.7

71,865

44.2

69,476

25.0

1974

-3,884

-262.6

99,437

38.4

103,321

48.7

1975

9,551

-345.9

108,856

9.5

99,305

-3.9

1976

-7,820

-181.9

116,794

7.3

124,614

25.5

1977

-28,352

262.6

123,182

5.5

151,534

21.6

1978

-30,205

6.5

145,847

18.4

176,052

16.2

1979

-23,922

-20.8

186,363

27.8

210,285

19.4

1980

-19,696

-17.7

225,566

21.0

245,262

16.6

1981

-22,267

13.1

238,715

5.8

260,982

6.4

1982

-27,510

23.5

216,442

-9.3

243,952

-6.5

1983

-52,409

90.5

205,639

-5.0

258,048

5.8

1984

-106,702

103.6

223,976

8.9

330,678

28.1

1985

-117,711

10.3

218,815

-2.3

336,526

1.8

1986

-138,279

17.5

227,159

3.8

365,438

8.6

1987

-152,119

10.0

254,122

11.9

406,241

11.2

1988

-118,526

-22.1

322,426

26.9

440,952

8.5

1989

-109,399

-7.7

363,812

12.8

473,211

7.3

1990

-101,719

-7.0

393,592

8.2

495,311

4.7

1991

-66,723

-34.4

421,730

7.1

488,453

-1.4

1992

-84,501

26.6

448,164

6.3

532,665

9.1

1993

-115,568

36.8

465,091

3.8

580,659

9.0

1994

-150,630

30.3

512,626

10.2

663,256

14.2

1995

-158,801

5.4

584,742

14.1

743,543

12.1

1996

-170,214

7.2

625,075

6.9

795,289

7.0

1997

-180,522

6.1

689,182

10.3

869,704

9.4

1998

-229,758

27.3

682,138

-1.0

911,896

4.9

1999

-328,821

43.1

695,797

2.0

1,024,618

12.4

2000

-436,104

32.6

781,918

12.4

1,218,022

18.9

2001

-411,899

-5.6

729,100

-6.8

1,140,999

-6.3

2002

-468,263

13.7

693,103

-4.9

1,161,366

1.8

2003

-532,350

13.7

724,771

4.6

1,257,121

8.2

2004

-654,830

23.0

814,875

12.4

1,469,704

16.9

2005

-772,373

18.0

901,082

10.6

1,673,455

13.9

2006

-827,971

7.2

1,025,967

13.9

1,853,938

10.8

2007

-808,763

-2.3

1,148,199

11.9

1,956,962

5.6

2008

-816,199

0.9

1,287,442

12.1

2,103,641

7.5

2009

-503,582

-38.3

1,056,043

-18.0

1,559,625

-25.9

2010

-635,362

26.2

1,278,495

21.1

1,913,857

22.7

2011

-727,765

14.5

1,480,290

15.8

2,208,055

15.4

2012

-729,611

0.3

1,545,709

4.4

2,275,320

3.0

2013

-688,450

-5.6

1,578,972

2.2

2,267,421

-0.3

Source: US Census Bureau, Foreign Trade Division

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

Chart IIA-1 of the US Census Bureau of the Department of Commerce shows that the trade deficit (gap between exports and imports) fell during the economic contraction after 2007 but has grown again during the expansion. The low average rate of growth of GDP of 2.4 percent during the expansion beginning since IIIQ2009 does not deteriorate further the trade balance. Higher rates of growth may cause sharper deterioration.

clip_image043

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

Source: US Census Bureau

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

Table IIA-2B provides the US international trade balance, exports and imports of goods and services on an annual basis from 1992 to 2013. 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 decreased from $99.2 billion in IVQ2012, or 2.5 percent of GDP to $83.7 billion in IVQ2013, or 1.9 percent of GDP (http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html). The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71). The last row of Table IIA-2B shows marginal improvement of the trade deficit from $556,838 million in 2011 to lower $534,656 million in 2012 with exports growing 4.6 percent and imports 2.8 percent. The trade balance improved further to deficit of $474,864 million in 2013 with growth of exports of 2.8 percent while imports stagnated. Growth and commodity shocks under alternating inflation waves (http://cmpassocregulationblog.blogspot.com/2014/04/imf-view-world-inflation-waves-squeeze.html) have deteriorated the trade deficit from the low of $383,657 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

Period

Balance

Exports

Imports

1960

3,508

25,940

22,432

1961

4,195

26,403

22,208

1962

3,370

27,722

24,352

1963

4,210

29,620

25,410

1964

6,022

33,341

27,319

1965

4,664

35,285

30,621

1966

2,939

38,926

35,987

1967

2,604

41,333

38,729

1968

250

45,543

45,293

1969

91

49,220

49,129

1970

2,254

56,640

54,386

1971

-1,302

59,677

60,979

1972

-5,443

67,222

72,665

1973

1,900

91,242

89,342

1974

-4,293

120,897

125,190

1975

12,404

132,585

120,181

1976

-6,082

142,716

148,798

1977

-27,246

152,301

179,547

1978

-29,763

178,428

208,191

1979

-24,565

224,131

248,696

1980

-19,407

271,834

291,241

1981

-16,172

294,398

310,570

1982

-24,156

275,236

299,391

1983

-57,767

266,106

323,874

1984

-109,072

291,094

400,166

1985

-121,880

289,070

410,950

1986

-138,538

310,033

448,572

1987

-151,684

348,869

500,552

1988

-114,566

431,149

545,715

1989

-93,141

487,003

580,144

1990

-80,864

535,233

616,097

1991

-31,135

578,344

609,479

1992

-39,212

616,882

656,094

1993

-70,311

642,863

713,174

1994

-98,493

703,254

801,747

1995

-96,384

794,387

890,771

1996

-104,065

851,602

955,667

1997

-108,273

934,453

1,042,726

1998

-166,140

933,174

1,099,314

1999

-263,755

967,008

1,230,764

2000

-377,337

1,072,782

1,450,119

2001

-362,339

1,007,725

1,370,065

2002

-418,165

980,879

1,399,044

2003

-490,545

1,023,937

1,514,482

2004

-604,897

1,163,724

1,768,622

2005

-707,914

1,288,257

1,996,171

2006

-752,399

1,460,792

2,213,191

2007

-699,065

1,652,859

2,351,925

2008

-702,302

1,840,332

2,542,634

2009

-383,657

1,578,187

1,961,844

2010

-499,379

1,844,468

2,343,847

2011

-556,838

2,112,825

2,669,663

2012

-534,656

2,210,585

2,745,240

2013

-474,864

2,271,385

2,746,249

Source: US Census Bureau, Foreign Trade Division

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 Mar 2014. There is long-term trend of deterioration of the US trade deficit shown vividly by Chart IIA-2. The global recession from IVQ2007 to IIQ2009 reversed the trend of deterioration. Deterioration resumed together with incomplete recovery and was influenced significantly by the carry trade from zero interest rates to commodity futures exposures (these arguments are elaborated in Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4 http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html). Earlier research focused on the long-term external imbalance of the US in the form of trade and current account deficits (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). US external imbalances have not been fully resolved and tend to widen together with improving world economic activity and commodity price shocks.

clip_image044

Chart IIA-2, US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-Mar 2014

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 Mar 2014. There was sharp acceleration from 2003 to 2007 during worldwide economic boom and increasing inflation. Exports fell sharply during the financial crisis and global recession from IVQ2007 to IIQ2009. Growth picked up again together with world trade and inflation but stalled in the final segment with less rapid global growth and inflation.

clip_image045

Chart IIA-3, US, Exports SA, Monthly, Millions of Dollars Jan 1992-Mar 2014

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 2014. Growth was stronger between 2003 and 2007 with worldwide economic boom and inflation. There was sharp drop during the financial crisis and global recession. There is stalling import levels in the final segment resulting from weaker world economic growth and diminishing inflation because of risk aversion and portfolio reallocations from commodity exposures to equities.

clip_image046

Chart IIA-4, US, Imports SA, Monthly, Millions of Dollars Jan 1992-Mar 2014

Source: US Census Bureau

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

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

 

Mar 2014

Mar 2013

∆%

Total Balance

-60,748

-55,352

 

Petroleum

-18,603

-20,500

 

Non Petroleum

-40,569

-33,422

 

Total Exports

135,096

129,289

4.5

Petroleum

11,407

9,604

18.8

Non Petroleum

122,685

118,912

3.2

Total Imports

195,843

184,641

6.1

Petroleum

30,010

30,104

-0.3

Non Petroleum

163,254

152,334

7.2

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-Mar 2014 and Jan-Mar 2013 are in Table IIA-4. The rate of growth of exports was 2.6 percent and minus 1.8 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that increased 10.0 percent and of mineral fuels that increased 17.3 percent both because prices of raw materials and commodities increase and fall recurrently as a result of shocks of risk aversion and portfolio reallocations. The US exports an insignificant amount of crude oil. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports decreased 0.1 percent while manufactured imports rose 2.3 percent. Significant part of the US trade imbalance originates in imports of mineral fuels decreasing 2.9 percent and petroleum decreasing 4.7 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 (http://cmpassocregulationblog.blogspot.com/2014/04/imf-view-world-inflation-waves-squeeze.html).

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

 

Jan-Mar 2014 $ Millions

Jan-Mar 2014 $ Millions

∆%

Exports

393,197

383,410

2.6

Manufactured

286,901

287,312

-0.1

Agricultural
Commodities

40,925

37,194

10.0

Mineral Fuels

38,338

32,684

17.3

Petroleum

30,943

26,694

15.9

Imports

546,888

537,051

1.8

Manufactured

440,186

430,101

2.3

Agricultural
Commodities

27,183

26,722

1.7

Mineral Fuels

90,215

92,917

-2.9

Petroleum

84,125

88,291

-4.7

Source: US Census Bureau

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

The current account of the US balance of payments is provided in Table IIA2-1 for IVQ2012 and IVQ2013. 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 decreased from $99.2 billion in IVQ2012 to $83.7 billion in IVQ2013. The current account deficit seasonally adjusted at annual rate fell from 2.5 percent of GDP in IVQ2012 to 2.3 percent of GDP in IIIQ2013 and 1.9 percent of GDP in IVQ2013. The ratio of the current account deficit to GDP has stabilized below 3 percent of GDP compared with much higher percentages before the recession but is combined now with much higher imbalance in the Treasury budget (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71).

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

 

IVQ2012

IVQ2013

Difference

Goods Balance

-178,547

-170,150

-8,397

X Goods

398,156

412,235

3.5 ∆%

M Goods

-576,703

-582,384

1.0 ∆%

Services Balance

56,151

58,171

2,020

X Services

165,425

172,451

4.2 ∆%

M Services

-109,274

-114,280

4.6 ∆%

Balance Goods and Services

-122,396

-111,979

10,417

Balance Income

54,839

59,918

5,079

Unilateral Transfers

-31,621

-31,679

-58

Current Account Balance

-99,178

-83,739

15,439

% GDP

IVQ2012

IVQ2013

IIIQ2013

 

2.5

1.9

2.3

X: exports; M: imports

Balance on Current Account = Balance on Goods and Services + Balance on Income + Unilateral Transfers

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.

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.”

Table IIA2-2 provides data on the US fiscal and balance of payments imbalances. In 2007, the federal deficit of the US was $161 billion corresponding to 1.1 percent of GDP while the Congressional Budget Office (CBO 2013Sep11) estimates the federal deficit in 2012 at $1087 billion or 6.8 percent of GDP. The combined record federal deficits of the US from 2009 to 2012 are $5090 billion or 31.6 percent of the estimate of GDP for fiscal year 2012 implicit in the CBO (CBO 2013Sep11) estimate of debt/GDP. The deficits from 2009 to 2012 exceed one trillion dollars per year, adding to $5.090 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, less than the combined deficits from 2009 to 2012 of $5090 billion. Federal debt in 2012 was 70.1 percent of GDP (CBO 2013Sep11). 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.”

Table IIA2-2, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and %

 

2007

2008

2009

2010

2011

2012

Goods &
Services

-699

-702

-384

-499

-557

-535

Income

101

146

124

178

233

224

UT

-115

-125

-122

-128

-134

-130

Current Account

-713

-681

-382

-449

-458

-440

NGDP

14480

14720

14418

14958

15534

16245

Current Account % GDP

-4.9

-4.6

-2.6

-3.0

-2.9

-2.7

NIIP

-1796

-3260

-2275

-2250

-3730

-3863

US Owned Assets Abroad

18400

19464

18558

20555

21636

21638

Foreign Owned Assets in US

20196

22724

20833

22805

25366

25501

NIIP % GDP

-12.4

-22.1

-15.8

-15.0

-24.0

-23.8

Exports
Goods
Services
Income

2487

2654

2185

2523

2874

2987

NIIP %
Exports
Goods
Services
Income

-72

-123

-104

-89

-130

-129

DIA MV

5274

3102

4322

4809

4514

5249

DIUS MV

3551

2486

2995

3422

3510

3924

Fiscal Balance

-161

-459

-1413

-1294

-1296

-1087

Fiscal Balance % GDP

-1.1

-3.1

-9.8

-8.8

-8.4

-6.8

Federal   Debt

5035

5803

7545

9019

10128

11281

Federal Debt % GDP

35.1

39.3

52.3

61.0

65.8

70.1

Federal Outlays

2729

2983

3518

3457

3603

3537

∆%

2.8

9.3

17.9

-1.7

4.2

-1.8

% GDP

19.0

20.2

24.4

23.4

23.4

22.0

Federal Revenue

2568

2524

2105

2163

2304

2450

∆%

6.7

-1.7

-16.6

2.7

6.5

6.4

% GDP

17.9

17.1

14.6

14.6

15.0

15.2

Sources: 

Notes: UT: unilateral transfers; 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. These discrepancies do not alter conclusions. Budget http://www.cbo.gov/ Balance of Payments and NIIP http://www.bea.gov/international/index.htm#bop Gross Domestic Product, Bureau of Economic Analysis (BEA) http://www.bea.gov/iTable/index_nipa.cfm

Table IIA2-3 provides quarterly estimates NSA of the external imbalance of the United States. The current account deficit seasonally adjusted falls from 2.6 percent of GDP in IIIQ2012 to 2.5 percent in IQ2013 and 2.3 percent of GDP in IIIQ2013. The net international investment position increases from $3.9 trillion in IVQ2012 to $4.2 trillion in IQ2013 and $4.6 trillion in IIQ2013, decreasing to $4.2 trillion in IIIQ2013.

Table IIA2-3, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and % NSA

 

IIIQ2012

IVQ2012

IQ2013

IIQ2013

IIIQ2013

Goods &
Services

-145

-122

-100

-126

-137

Income

55

55

52

57

60

UT

-33

-32

-34

-33

-35

Current Account

-123

-99

-82

-102

-111

Current Account % GDP

-2.6

-2.5

-2.5

-2.3

-2.3

NIIP

-4109

-3863

-4236

-4555

-4166

US Owned Assets Abroad

21551

21638

21590

20969

21591

Foreign Owned Assets in US

-25660

-25501

-25826

-25424

-25756

DIA MV

5059

5249

5501

5435

5980

DIUS MV

3962

3924

4251

4333

4524

Notes: UT: unilateral transfers; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value..

Sources: US Bureau of Economic Analysis

Notes: UT: unilateral transfers; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value.

Sources: US Bureau of Economic Analysis http://www.bea.gov/international/index.htm#bop

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 May 8, 2014, at 0.08 percent per year. US recessions are in shaded areas according to the reference dates of the NBER (http://www.nber.org/cycles.html). In the Fed effort to control the “Great Inflation” of the 1930s (see http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I The Great Inflation; see Taylor 1993, 1997, 1998LB, 1999, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB and http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html), the fed funds rate increased from 8.34 percent on Jan 3, 1979 to a high in Chart VI-10 of 22.36 percent per year on Jul 22, 1981 with collateral adverse effects in the form of impaired savings and loans associations in the United States, emerging market debt and money-center banks (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 72-7; Pelaez 1986, 1987). Another episode in Chart VI-10 is the increase in the fed funds rate from 3.15 percent on Jan 3, 1994, to 6.56 percent on Dec 21, 1994, which also had collateral effects in impairing emerging market debt in Mexico and Argentina and bank balance sheets in a world bust of fixed income markets during pursuit by central banks of non-existing inflation (Pelaez and Pelaez, International Financial Architecture (2005), 113-5). Another interesting policy impulse is the reduction of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of equally non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85), followed by increments of 25 basis points from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006 in Chart VI-10. Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment but the exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).

The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever-increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4). A final episode in Chart VI-10 is the reduction of the fed funds rate from 5.41 percent on Aug 9, 2007, to 2.97 percent on October 7, 2008, to 0.12 percent on Dec 5, 2008 and close to zero throughout a long period with the final point at 0.08 percent on May 8, 2014. Evidently, this behavior of policy would not have occurred had there been theory, measurements and forecasts to avoid these violent oscillations that are clearly detrimental to economic growth and prosperity without inflation. Current policy consists of forecast mandate of maintaining policy accommodation until the forecast of the rate of unemployment reaches 6.5 percent and the rate of personal consumption expenditures excluding food and energy reaches 2.5 percent (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm). The FOMC dropped the numbers but affirmed guidance (http://www.federalreserve.gov/newsevents/press/monetary/20140319a.htm): “With the unemployment rate nearing 6-1/2 percent, the Committee has updated its forward guidance. The change in the Committee's guidance does not indicate any change in the Committee's policy intentions as set forth in its recent statements.” It is a forecast mandate because of the lags in effect of monetary policy impulses on income and prices (Romer and Romer 2004). The intention is to reduce unemployment close to the “natural rate” (Friedman 1968, Phelps 1968) of around 5 percent and inflation at or below 2.0 percent. If forecasts were reasonably accurate, there would not be policy errors. A commonly analyzed risk of zero interest rates is the occurrence of unintended inflation that could precipitate an increase in interest rates similar to the Himalayan rise of the fed funds rate from 9.91 percent on Jan 10, 1979, at the beginning in Chart VI-10, to 22.36 percent on Jul 22, 1981. There is a less commonly analyzed risk of the development of a risk premium on Treasury securities because of the unsustainable Treasury deficit/debt of the United States (http://cmpassocregulationblog.blogspot.com/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.

clip_image047

Chart VI-10, US, Fed Funds Rate, Business Days, Jul 1, 1954 to May 8, 2014, Percent per Year

Source: Board of Governors of the Federal Reserve System

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

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

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

1994

FF

30Y

30P

10Y

10P

MOR

CPI

Jan

3.00

6.29

100

5.75

100

7.06

2.52

Feb

3.25

6.49

97.37

5.97

98.36

7.15

2.51

Mar

3.50

6.91

92.19

6.48

94.69

7.68

2.51

Apr

3.75

7.27

88.10

6.97

91.32

8.32

2.36

May

4.25

7.41

86.59

7.18

88.93

8.60

2.29

Jun

4.25

7.40

86.69

7.10

90.45

8.40

2.49

Jul

4.25

7.58

84.81

7.30

89.14

8.61

2.77

Aug

4.75

7.49

85.74

7.24

89.53

8.51

2.69

Sep

4.75

7.71

83.49

7.46

88.10

8.64

2.96

Oct

4.75

7.94

81.23

7.74

86.33

8.93

2.61

Nov

5.50

8.08

79.90

7.96

84.96

9.17

2.67

Dec

6.00

7.87

81.91

7.81

85.89

9.20

2.67

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

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

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

ChVI-14DDPChart

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

Source: Board of Governors of the Federal Reserve System

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

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

clip_image049

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

Source: Bureau of Labor Statistics

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

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

clip_image050

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

Source: Bureau of Labor Statistics

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

The Congressional Budget Office (CBO 2014BEOFeb4) estimates potential GDP, potential labor force and potential labor productivity provided in Table IB-3. The CBO estimates average rate of growth of potential GDP from 1950 to 2012 at 3.3 percent per year. The projected path is significantly lower at 2.1 percent per year from 2013 to 2024. The legacy of the economic cycle expansion from IIIQ2009 to IVQ2013 at 2.3 percent on average is in contrast with 5.0 percent on average in the expansion from IQ1983 to IIQ1987 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). Subpar economic growth may perpetuate unemployment and underemployment estimated at 29.1 million or 17.8 percent of the effective labor force in Feb 2014 (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html) with much lower hiring than in the period before the current cycle (http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html).

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

 

Potential GDP

Potential Labor Force

Potential Labor Productivity*

Average Annual ∆%

     

1950-1973

3.9

1.6

2.3

1974-1981

3.2

2.5

0.8

1982-1990

3.2

1.6

1.6

1991-2001

3.2

1.3

1.9

2002-2012

2.2

0.8

1.4

2007-2012

1.7

0.6

1.1

Total 1950-2012

3.3

1.5

1.8

Projected Average Annual ∆%

     

2013-2018

2.1

0.6

1.5

2019-2024

2.1

0.5

1.6

2013-2024

2.1

0.5

1.6

*Ratio of potential GDP to potential labor force

Source: CBO (2014BEOFeb4), CBO, Key assumptions in projecting potential GDP—February 2014 baseline. Washington, DC, Congressional Budget Office, Feb 4, 2014.

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 2.3 percent on average from IIIQ2009 to IVQ2013 during the current economic expansion in contrast with 5.0 percent on average in the cyclical expansion from IQ1983 to IQ1987 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html) cannot be explained by the contraction of 4.3 percent of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 29.1 million or 17.8 percent of the labor force as estimated for Feb 2014 (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html). There is no exit from unemployment/underemployment and stagnating real wages because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html). The US economy and labor markets collapsed without recovery. Abrupt collapse of economic conditions can be explained only with cyclic factors (Lazear and Spletzer 2012Jul22) and not by secular stagnation (Hansen 1938, 1939, 1941 with early dissent by Simons 1942).

clip_image051

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

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

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

clip_image052

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.

image

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

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

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

clip_image054

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

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

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

clip_image055

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

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

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

clip_image056

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 2012. The contraction of economic activity during the global recession was a major factor in the reduction of the current account deficit as percent of GDP.

clip_image057

Chart IIA2-6, US, Real GDP, 1960-2013, 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.

clip_image058

Chart IIB-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 three trillion dollars of securities held outright. Net foreign purchases of US long-term securities (row C in Table VA-8) increased from $7.7 billion in Jan 2013 to $85.7 billion in Feb 2014. Foreign (residents) purchases minus sales of US long-term securities (row A in Table VA-8) in Jan 2014 of minus $14.8 billion increased to $84.8 billion in Feb 2014. Net US (residents) purchases of long-term foreign securities (row B in Table VA-8) deteriorated from $22.5 billion in Jan 2014 to $1.0 billion in Feb 2014. In Feb 2014,

C = A + B = $84.8 billion + $1.0 billion = $85.7 billion

There are minor rounding errors. There is improving demand in Table VA-8 in Feb in A1 private purchases by residents overseas of US long-term securities of $66.3 billion of which improvement in A11 Treasury securities of $75.9 billion, improving in A12 of minus $2.5 billion in agency securities, deterioration of minus $6.2 billion of corporate bonds and improvement of minus $0.8 billion in equities. Worldwide risk aversion causes flight into US Treasury obligations with significant oscillations. Official purchases of securities in row A2 increased $18.5 billion with increase of Treasury securities of $16.6 billion in Feb 2014. Official purchases of agency securities increased $2.5 billion in Feb. Row D shows increase in Feb 2013 of $4.6 billion in purchases of short-term dollar denominated obligations. Foreign private holdings of US Treasury bills increased $8.4 billion (row D11) with foreign official holdings decreasing $5.5 billion while the category “other” increased $1.8 billion. Foreign private holdings of US Treasury bills increased $8.4 billion in what could be arbitrage of duration exposures. 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-8, Net Cross-Borders Flows of US Long-Term Securities, Billion Dollars, NSA

 

Feb 2013 12 Months

Feb 2014 12 Months

Jan 2014

Feb 2014

A Foreign Purchases less Sales of
US LT Securities

570.1

89.6

-14.8

84.8

A1 Private

338.2

69.2

1.8

66.3

A11 Treasury

140.0

155.5

16.1

75.9

A12 Agency

118.1

-17.1

-4.5

-2.5

A13 Corporate Bonds

-9.3

-24.3

-4.4

-6.2

A14 Equities

89.4

-44.9

-5.4

-0.8

A2 Official

231.9

20.4

-16.5

18.5

A21 Treasury

209.7

-54.8

-16.7

16.6

A22 Agency

0.6

69.0

0.5

2.5

A23 Corporate Bonds

10.4

11.7

0.0

-0.5

A24 Equities

11.3

-5.5

-0.4

0.0

B Net US Purchases of LT Foreign Securities

-64.0

-146.5

22.5

1.0

B1 Foreign Bonds

5.2

1.7

33.8

2.5

B2 Foreign Equities

-69.2

-148.2

-11.4

-1.5

C Net Foreign Purchases of US LT Securities

506.1

-56.9

7.7

85.7

D Increase in Foreign Holdings of Dollar Denominated Short-term 

72.3

-56.7

5.5

4.6

D1 US Treasury Bills

58.3

-12.4

-10.8

2.8

D11 Private

35.3

-15.2

-6.4

8.4

D12 Official

23.1

2.8

-4.4

-5.5

D2 Other

14.0

-44.3

16.3

1.8

C = A + B;

A = A1 + A2

A1 = A11 + A12 + A13 + A14

A2 = A21 + A22 + A23 + A24

B = B1 + B2

D = D1 + D2

Sources: United States Treasury

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

Table VA-9 provides major foreign holders of US Treasury securities. China is the largest holder with $1272.9 billion in Feb 2014, increasing 1.7 percent from $1251.9 billion in Feb 2013 while decreasing $2.7 billion from Jan 2014 or 0.2 percent. Japan increased its holdings from $1105.3 billion in Feb 2013 to $1210.5 billion in Feb 2014 or by 9.5 percent. Japan increased its holdings from $1201.4 billion in Jan 2014 to $1210.5 billion in Feb 2014 by $9.1 billion or 0.8 percent. Total foreign holdings of Treasury securities rose from $5691.1 billion in Feb 2013 to $5885.3 billion in Feb 2014, or 3.4 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-9, US, Major Foreign Holders of Treasury Securities $ Billions at End of Period

 

Feb 2014

Jan 2014

Feb 2013

Total

5885.3

5840.3

5691.1

China

1272.9

1275.6

1251.9

Japan

1210.5

1201.4

1105.5

Belgium

341.2

310.3

187.3

Caribbean Banking Centers

299.7

298.2

284.2

Brazil

243.9

246.0

256.5

Oil Exporters

243.7

246.4

256.8

Taiwan

180.0

179.1

190.0

United Kingdom

175.4

163.1

138.6

Switzerland

166.5

173.8

186.9

Hong Kong

160.4

160.3

144.7

Luxembourg

136.8

135.4

151.2

Russia

126.2

131.8

164.9

Ireland

111.4

108.8

109.6

Foreign Official Holdings

4069.2

4068.0

4100.4

A. Treasury Bills

388.4

393.9

385.6

B. Treasury Bonds and Notes

3680.8

3674.0

3714.9

Source: United States Treasury

http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/ticpress.aspx#1

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

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