Sunday, March 12, 2017

Increasing Interest Rates, Twenty-Four Million Unemployed or Underemployed, Job Creation, Cyclically Stagnating Real Wages, United States International Trade, Rules, Discretionary Authorities and Slow Productivity Growth, World Cyclical Slow Growth and Global Recession Risk: Part I

 

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Increasing Interest Rates, Twenty-Four Million Unemployed or Underemployed, Job Creation, Cyclically Stagnating Real Wages, United States International Trade, Rules, Discretionary Authorities and Slow Productivity Growth, World Cyclical Slow Growth and Global Recession Risk

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

I Twenty-Four Million Unemployed or Underemployed

IA1 Summary of the Employment Situation

IA2 Number of People in Job Stress

IA3 Long-term and Cyclical Comparison of Employment

IA4 Job Creation

IB Stagnating Real Wages

II United States International Trade

IIA Rules, Discretionary Authorities and Slow Productivity Growth

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 Twenty-Four Million Unemployed or Underemployed. This section analyzes the employment situation report of the United States of the Bureau of Labor Statistics (BLS). There are four subsections: IA1 Summary of the Employment Situation; IA2 Number of People in Job Stress; IA3 Long-term and Cyclical Comparison of Employment; and IA4 Job Creation.

IA1 Summary of the Employment Situation. Table I-1 provides summary statistics of the employment situation report of the BLS. The first four rows provide the data from the establishment report of creation of nonfarm payroll jobs and remuneration of workers (for analysis of the differences in employment between the establishment report and the household survey see Abraham, Haltiwanger, Sandusky and Spletzer 2009). Total nonfarm payroll employment seasonally adjusted (SA) increased 235,000 in Feb 2017 and private payroll employment increased 227,000. The average monthly number of nonfarm jobs created from Feb 2015 to Feb 2016 was 217,000 using seasonally adjusted data, while the average number of nonfarm jobs created from Feb 2016 to Feb 2017 was 195,833, or decrease by 9.8 percent. The average number of private jobs created in the US from Feb 2015 to Feb 2016 was 203,583, using seasonally adjusted data, while the average from Feb 2016 to Feb 2017 was 179,667, or decrease by 11.7 percent. This blog calculates the effective labor force of the US at 168.311 million in Feb 2017 and 167,206 million in Feb 2016 (Table I-4), for growth of 1.105 million at average 92,083 per month. The difference between the average increase of 179,667 new private nonfarm jobs per month in the US from Feb 2016 to Feb 2017 and the 92,083 average monthly increase in the labor force from Feb 2016 to Feb 2017 is 87,584 monthly new jobs net of absorption of new entrants in the labor force. There are 24.212 million in job stress in the US currently. Creation of 87,584 new jobs per month net of absorption of new entrants in the labor force would require 276 months to provide jobs for the unemployed and underemployed (24.212 million divided by 87,584) or 23 years (276 divided by 12). The civilian labor force of the US in Feb 2017 not seasonally adjusted stood at 159.482 million with 7.887 million unemployed or effectively 16.716 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 168.311 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 0.9 years (1 million divided by product of 87,584 by 12, which is 1,051,008). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.974 million (0.05 times labor force of 159.482 million). New net job creation would be minus 0.087 million (7.887 million unemployed minus 7.974 million unemployed at rate of 5 percent) that at the current rate would take 0.0 years (0.087 million divided by 1,051,008). Under the calculation in this blog, there are 16.716 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 168.311 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 9.265 million jobs net of labor force growth that at the current rate would take 7.9 years (16.716 million minus 0.05(168.311 million) = 8.300 million divided by 1,051,008 using LF PART 66.2% and Total UEM in Table I-4). These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply. The number employed in Feb 2017 was 151.594 million (NSA) or 4.279 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 254.246 million in Feb 2016 or by 22.288 million. The number employed increased 2.9 percent from Jul 2007 to Feb 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.6 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Feb 2017 would result in 161.446 million jobs (0.635 multiplied by noninstitutional civilian population of 254.246 million). There are effectively 9.852 million fewer jobs in Feb 2017 than in Jul 2007, or 161.446 million minus 151.594 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

There is 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). 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 (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html). The proper explanation is not in secular stagnation but in cyclically slow growth. Secular stagnation is merely another case of theory without reality with dubious policy proposals. Subsection IA4 Job Creation analyzes the types of jobs created, which are lower paying than earlier. Average hourly earnings in Feb 2017 were $26.09 seasonally adjusted (SA), increasing 2.8 percent not seasonally adjusted (NSA) relative to Feb 2016 and increasing 0.2 percent relative to Jan 2017 seasonally adjusted. In Jan 2017, average hourly earnings seasonally adjusted were $26.03, increasing 3.3 percent relative to Jan 2016 not seasonally adjusted and increasing 0.2 percent seasonally adjusted relative to Dec 2016. These are nominal changes in workers’ wages. The following row “average hourly earnings in constant dollars” provides hourly wages in constant dollars calculated by the BLS or what is called “real wages” adjusted for inflation. Data are not available for Feb 2017 because the prices indexes of the BLS for Dec 2016 will only be released on Mar 15, 2017 (http://www.bls.gov/cpi/), which will be covered in this blog’s comment on Mar 19, 2017, together with world inflation. The second column provides changes in real wages for Jan 2017. Average hourly earnings adjusted for inflation or in constant dollars increased 0.8 percent in Jan 2017 relative to Jan 2016 but have been decreasing/stagnating during multiple months. World inflation waves in bouts of risk aversion (https://cmpassocregulationblog.blogspot.com/2017/02/world-inflation-waves-united-states.html) mask declining trend of real wages. The fractured labor market of the US is characterized by high levels of unemployment and underemployment together with falling real wages or wages adjusted for inflation (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). The following section IB Stagnating Real Wages provides more detailed analysis. Average weekly hours of US workers seasonally adjusted remained virtually unchanged, not changing from 34.4 in Jan 2017 to 34.4 in Feb 2017, which could be substantial additional work on a labor force of 160.056 million SA in Feb 2017. Another headline number widely followed is the unemployment rate or number of people unemployed as percent of the labor force. The unemployment rate calculated in the household survey decreased from 4.8 percent in Jan 2017 to 4.7 percent in Feb 2017, seasonally adjusted. This blog provides with every employment situation report the number of people in the US in job stress or unemployed plus underemployed calculated without seasonal adjustment (NSA) at 24.2 million in Feb 2017 and 25.7 million in Jan 2017. The final row in Table I-1 provides the number in job stress as percent of the actual labor force calculated at 14.4 percent in Feb 2017 and 15.3 percent in Jan 2017. Almost one in every five workers in the US is unemployed or underemployed.

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

Table I-1, US, Summary of the Employment Situation Report SA

 

Feb 2017

Jan 2017

New Nonfarm Payroll Jobs

235,000

238,000

New Private Payroll Jobs

227,000

221,000

Average Hourly Earnings

Feb 17 $26.09 SA

∆% Feb 17/Feb 16 NSA: 2.8

∆% Feb 17/Jan 17 SA: 0.2

Jan 17 $26.03 SA

∆% Jan 17/Jan 16 NSA: 3.3

∆% Jan 17/Dec 16 SA: 0.2

Average Hourly Earnings in Constant Dollars

 

∆% Jan 2017/Jan 2016 NSA: 0.8

Average Weekly Hours

34.4 SA

34.1 NSA

34.4 SA

34.4 NSA

Unemployment Rate Household Survey % of Labor Force SA

4.7

4.8

Number in Job Stress Unemployed and Underemployed Blog Calculation

24.2 million NSA

25.7 million NSA

In Job Stress as % Labor Force

14.4 NSA

15.3 NSA

Source: US Bureau of Labor Statistics

http://www.bls.gov/

The Bureau of Labor Statistics (BLS) of the US Department of Labor provides both seasonally adjusted (SA) and not-seasonally adjusted (NSA) or unadjusted data with important uses (Bureau of Labor Statistics 2012Feb3; 2011Feb11):

“Most series published by the Current Employment Statistics program reflect a regularly recurring seasonal movement that can be measured from past experience. By eliminating that part of the change attributable to the normal seasonal variation, it is possible to observe the cyclical and other nonseasonal movements in these series. Seasonally adjusted series are published monthly for selected employment, hours, and earnings estimates.”

Requirements of using best available information and updating seasonality factors affect the comparability over time of United States employment data. In the first month of the year, the BLS revises data for several years by adjusting benchmarks and seasonal factors (page 4 at http://www.bls.gov/news.release/pdf/empsit.pdf release of Jan 2015 at http://www.bls.gov/schedule/archives/empsit_nr.htm#2015), which is the case of the data for Jan 2015 released on Feb 6, 2015:

“In accordance with annual practice, the establishment survey data released today have been benchmarked to reflect comprehensive counts of payroll jobs for March 2014. These counts are derived principally from the Quarterly Census of Employment and Wages (QCEW), which enumerates jobs covered by the unemployment insurance tax system. The benchmark process results in revisions to not seasonally adjusted data from April 2013 forward.

Seasonally adjusted data from January 2010 forward are subject to revision. In addition, data for some series prior to 2010, both seasonally adjusted and unadjusted, incorporate revisions. The total nonfarm employment level for March 2014 was revised upward by 91,000 (+67,000 on a not seasonally adjusted basis, or less than 0.05 percent). The average benchmark revision over the past 10 years was plus or minus 0.3 percent. Table A presents revised total nonfarm employment data on a seasonally adjusted basis for January through

December 2014.

An article that discusses the benchmark and post-benchmark revisions and other technical issues can be accessed through the BLS website at www.bls.gov/web/empsit/cesbmart.pdf.

Information on the data released today also may be obtained by calling (202) 691-6555.”

There are also adjustments of population that affect comparability of labor statistics over time (page 5 at http://www.bls.gov/news.release/pdf/empsit.pdf release of Jan 2015 at http://www.bls.gov/schedule/archives/empsit_nr.htm#2015):

“Effective with data for January 2015, updated population estimates have been used in the household survey. Population estimates for the household survey are developed by the U.S. Census Bureau. Each year, the Census Bureau updates the estimates to reflect new information and assumptions about the growth of the population since the previous decennial census. The change in population reflected in the new estimates results from adjustments for net international migration, updated vital statistics and other information, and some methodological changes in the estimation process. In accordance with usual practice, BLS will not revise the official household survey estimates for December 2014 and earlier months. To show the impact of the population adjustments, however, differences in selected December 2014 labor force series based on the old and new population estimates are shown in table B.”

There are also adjustments of benchmarks and seasonality factors for establishment data that affect comparability over time (page 4 at http://www.bls.gov/news.release/pdf/empsit.pdf release of Jan 2015 at http://www.bls.gov/schedule/archives/empsit_nr.htm#2015):

“In accordance with annual practice, the establishment survey data released today [Feb 6, 2015] have been benchmarked to reflect comprehensive counts of payroll jobs for March 2014. These counts are derived principally from the Quarterly Census of Employment and Wages (QCEW), which enumerates jobs covered by the unemployment insurance tax system. The benchmark process results in revisions to not seasonally adjusted data from April 2013 forward. Seasonally adjusted data from January 2010 forward are subject to revision. In addition, data for some series prior to 2010, both seasonally adjusted and unadjusted, incorporate revisions.”

The Bureau of Labor Statistics (BLS) revised household data for seasonal factors in the release for Dec 2015 (http://www.bls.gov/news.release/pdf/empsit.pdf):

“Seasonally adjusted household survey data have been revised using updated seasonal adjustment factors, a procedure done at the end of each calendar year. Seasonally adjusted estimates back to January 2011 were subject to revision. The unemployment rates for January 2015 through November 2015 (as originally published and as revised) appear in table A on page 5, along with additional information about the revisions.”

The Bureau of Labor Statistics (BLS) revised household data for seasonal factors in the release for Dec 2016 (https://www.bls.gov/news.release/pdf/empsit.pdf):

“Seasonally adjusted household survey data have been revised using updated seasonal adjustment factors, a procedure done at the end of each calendar year. Seasonally adjusted estimates back to January 2012 were subject to revision. The unemployment rates for January 2016 through November 2016 (as originally published and as revised) appear in table A on page 5, along with additional information about the revisions.”

The Bureau of Labor Statistics (BLS) revised establishment data for seasonal and benchmarks in the release for Jan 2016 (http://www.bls.gov/news.release/pdf/empsit.pdf): “Establishment survey data have been revised as a result of the annual benchmarking process and the updating of seasonal adjustment factors. Also, household survey data for January 2016 reflect updated population estimates. See the notes beginning on page 4 for more information about these changes.”

The Bureau of Labor Statistics (BLS) revised establishment data for seasonal and benchmarks in the release for Jan 2017 (https://www.bls.gov/news.release/pdf/empsit.pdf): “Establishment survey data have been revised as a result of the annual benchmarking process and the updating of seasonal adjustment factors using an improved methodology to select models. Also, household survey data for January 2017 reflect updated population estimates. See the notes beginning on page 4 for more information about these changes.”

All comparisons over time are affected by yearly adjustments of benchmarks and seasonality factors. All data in this blog comment use revised data released by the BLS (http://www.bls.gov/).

IA2 Number of People in Job Stress. There are two approaches to calculating the number of people in job stress. The first approach consists of calculating the number of people in job stress unemployed or underemployed with the raw data of the employment situation report as in Table I-2. The data are seasonally adjusted (SA). The first three rows provide the labor force and unemployed in millions and the unemployment rate of unemployed as percent of the labor force. There is increase in the number unemployed from 7.529 million in Dec 2016 to 7.635 million in Jan 2017 and decrease to 7.528 million in Feb 2017. The rate of unemployment increased from 4.7 percent in Dec 2016 to 4.8 percent in Jan 2016 and decreased to 4.7 percent in Feb 2017. An important aspect of unemployment is its persistence for more than 27 weeks with 1.801 million in Feb 2017, corresponding to 23.9 percent of the unemployed. The longer the period of unemployment the lower are the chances of finding another job with many long-term unemployed ceasing to search for a job. Another key characteristic of the current labor market is the high number of people trying to subsist with part-time jobs because they cannot find full-time employment or part-time for economic reasons. The BLS explains as follows: “these individuals were working part time because their hours had been cut back or because they were unable to find full-time work” (http://www.bls.gov/news.release/pdf/empsit.pdf 2). The number of part-time for economic reasons increased from 5.598 million in Dec 2016 to 5.840 million in Jan 2017 and decreased to 5.704 million in Feb 2017. Another important fact is the marginally attached to the labor force. The BLS explains as follows: “these individuals were not in the labor force, wanted and were available for work, and had looked for a job sometime in the prior 12 months. They were not counted as unemployed because they had not searched for work in the 4 weeks preceding the survey” (http://www.bls.gov/news.release/pdf/empsit.pdf 2). The number in job stress unemployed or underemployed of 14.995 million in Feb 2017 consists of:

· 7.528 million unemployed (of whom 1.801 million, or 23.9 percent, unemployed for 27 weeks or more) compared with 7.635 million unemployed in Jan 2017 (of whom 1.850 million, or 24.2 percent, unemployed for 27 weeks or more).

· 5.704 million employed part-time for economic reasons in Feb 2017 (who suffered reductions in their work hours or could not find full-time employment) compared with 5.804 million in Jan 2017

· 1.723 million who were marginally attached to the labor force in Feb 2017 (who were not in the labor force but wanted and were available for work) compared with 1.752 million in Jan 2017

Table I-2, US, People in Job Stress, Millions and % SA

 

Feb 2017

Jan 2017

Dec 2016

Labor Force Millions

160.056

159.716

159.640

Unemployed
Millions

7.528

7.635

7.529

Unemployment Rate (unemployed as % labor force)

4.7

4.8

4.7

Unemployed ≥27 weeks
Millions

1.801

1.850

1.831

Unemployed ≥27 weeks %

23.9

24.2

24.3

Part Time for Economic Reasons
Millions

5.704

5.840

5.598

Marginally
Attached to Labor Force
Millions

1.723

1.752

1.684

Job Stress
Millions

14.995

15.227

14.811

In Job Stress as % Labor Force

9.3

9.5

9.3

Job Stress = Unemployed + Part Time Economic Reasons + Marginally Attached Labor Force

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Table I-3 repeats the data in Table I-2 but including Nov and additional data. What really matters is the number of people with jobs or the total employed, representing the opportunity for exit from unemployment. The final row of Table I-3 provides people employed as percent of the population or employment to population ratio. The number has remained relatively constant around 59 percent, reaching 59.7 in Nov 2016, 59.7 in Dec 2016, 59.9 in Jan 2017 and 59.7 in Feb 2017. The employment to population ratio fell from an annual level of 63.1 percent in 2006 to 58.6 percent in 2012, 58.6 percent in 2013 and 59.0 in 2014 with the lowest level at 58.4 percent in 2011. The employment population ratio reached 59.4 in Dec 2015 and 59.6 in Dec 2016.

Table I-3, US, Unemployment and Underemployment, SA, Millions and Percent

 

Feb 2017

Jan 2017

Dec 2016

Nov 2016

Labor Force

160.056

159.716

159.640

159.456

Participation Rate

63.0

62.9

62.7

62.6

Unemployed

7.528

7.635

7.529

7.409

UNE Rate %

4.7

4.8

4.7

4.6

Part Time Economic Reasons

5.704

5.840

5.598

5.659

Marginally Attached to Labor Force

1.723

1.752

1.684

1.932

In Job Stress

14.955

15.227

14.811

15.000

In Job Stress % Labor Force

9.3

9.5

9.3

9.4

Employed

151.902

152.081

152.111

152.048

Employment % Population

59.7

59.9

59.7

59.7

Job Stress = Unemployed + Part Time Economic Reasons + Marginally Attached Labor Force

Source: US Bureau of Labor Statistics

http://www.bls.gov/cps/

The balance of this section considers the second approach. Charts I-1 to I-12 explain the reasons for considering another approach to calculating job stress in the US. Chart I-1 of the Bureau of Labor Statistics provides the level of employment in the US from 2001 to 2017. There was a big drop of the number of people employed from 147.315 million at the peak in Jul 2007 (NSA) to 136.809 million at the trough in Jan 2010 (NSA) with 10.506 million fewer people employed. Recovery has been anemic compared with the shallow recession of 2001 that was followed by nearly vertical growth in jobs. The number employed in Feb 2017 was 151.594 million (NSA) or 4.279 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 254.246 million in Feb 2016 or by 22.288 million. The number employed increased 2.9 percent from Jul 2007 to Feb 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.6 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Feb 2017 would result in 161.446 million jobs (0.635 multiplied by noninstitutional civilian population of 254.246 million). There are effectively 9.852 million fewer jobs in Feb 2017 than in Jul 2007, or 161.446 million minus 151.594 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

 

Chart I-1, US, Employed, Thousands, SA, 2001-2017

Source: Bureau of Labor Statistics

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

Chart I-2 of the Bureau of Labor Statistics provides 12-month percentage changes of the number of people employed in the US from 2001 to 2016. There was recovery since 2010 but not sufficient to recover lost jobs. Many people in the US who had jobs before the global recession are not working now and many who entered the labor force cannot find employment.

 

Chart I-2, US, Employed, 12-Month Percentage Change NSA, 2001-2017

Source: Bureau of Labor Statistics

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

The foundation of the second approach derives from Chart I-3 of the Bureau of Labor Statistics providing the level of the civilian labor force in the US. The civilian labor force consists of people who are available and willing to work and who have searched for employment recently. The labor force of the US NSA grew 9.4 percent from 142.828 million in Jan 2001 to 156.255 million in Jul 2009. The civilian labor force is 2.1 percent higher at 159.482 million in Feb 2017 than in Jul 2009, all numbers not seasonally adjusted. Chart I-3 shows the flattening of the curve of expansion of the labor force and its decline in 2010 and 2011. The ratio of the labor force of 154.871 million in Jul 2007 to the noninstitutional population of 231.958 million in Jul 2007 was 66.8 percent while the ratio of the labor force of 159.482 million in Feb 2017 to the noninstitutional population of 254.246 million in Feb 2017 was 62.7 percent. The labor force of the US in Feb 2017 corresponding to 66.8 percent of participation in the population would be 169.836 million (0.668 x 254.246). The difference between the measured labor force in Feb 2017 of 159.482 million and the labor force in Feb 2017 with participation rate of 66.8 percent (as in Jul 2007) of 169.836 million is 10.354 million. The level of the labor force in the US has stagnated and is 10.354 million lower than what it would have been had the same participation rate been maintained. Millions of people have abandoned their search for employment because they believe there are no jobs available for them. The key issue is whether the decline in participation of the population in the labor force is the result of people giving up on finding another job.

 

Chart I-3, US, Civilian Labor Force, Thousands, SA, 2001-2017

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

Chart I-4 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of the labor force in the US. The rate of growth fell almost instantaneously with the global recession and became negative from 2009 to 2011. The labor force of the US collapsed and did not recover. Growth in the beginning of the summer originates in younger people looking for jobs in the summer after graduation or during school recess.

 

Chart I-4, US, Civilian Labor Force, Thousands, NSA, 12-month Percentage Change, 2001-2017

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

Chart I-5 of the Bureau of Labor Statistics provides the labor force participation rate in the US or labor force as percent of the population. The labor force participation rate of the US fell from 66.8 percent in Jan 2001 to 62.7 percent NSA in Feb 2017, all numbers not seasonally adjusted. The annual labor force participation rate for 1979 was 63.7 percent and also 63.7 percent in Nov 1980 during sharp economic contraction. This comparison is further elaborated below. Chart I-5 shows an evident downward trend beginning with the global recession that has continued throughout the recovery beginning in IIIQ2009. The critical issue is whether people left the workforce of the US because they believe there is no longer a job for them.

 

Chart I-5, Civilian Labor Force Participation Rate, Percent of Population in Labor Force SA, 2001-2017

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

Chart I-6 of the Bureau of Labor Statistics provides the level of unemployed in the US. The number unemployed rose from the trough of 6.272 million NSA in Oct 2006 to the peak of 16.147 million in Jan 2010, declining to 13.400 million in Jul 2012, 12.696 million in Aug 2012 and 11.741 million in Sep 2012. The level unemployed fell to 11.741 million in Oct 2012, 11.404 million in Nov 2012, 11.844 million in Dec 2012, 13.181 million in Jan 2013, 12.500 million in Feb 2013 and 9.984 million in Dec 2013. The level of unemployment reached 7.887 million in Feb 2017, all numbers not seasonally adjusted.

 

Chart I-6, US, Unemployed, Thousands, SA, 2001-2017

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

Chart I-7 of the Bureau of Labor Statistics provides the rate of unemployment in the US or unemployed as percent of the labor force. The rate of unemployment of the US rose from 4.7 percent in Jan 2001 to 6.5 percent in Jun 2003, declining to 4.1 percent in Oct 2006. The rate of unemployment jumped to 10.6 percent in Jan 2010 and declined to 7.6 percent in Dec 2012 but increased to 8.5 percent in Jan 2013 and 8.1 percent in Feb 2013, falling back to 7.3 percent in May 2013 and 7.8 percent in Jun 2013, all numbers not seasonally adjusted. The rate of unemployment not seasonally adjusted stabilized at 7.7 percent in Jul 2013 and fell to 6.5 percent in Dec 2013 and 5.4 percent in Dec 2014. The rate of unemployment NSA decreased to 4.8 percent in Dec 2015 and 4.5 percent in Dec 2016, reaching 4.9 percent in Feb 2017.

 

Chart I-7, US, Unemployment Rate, SA, 2001-2017

Source: Bureau of Labor Statistics

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

Chart I-8 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of unemployed. There was a jump of 81.8 percent in Apr 2009 with subsequent decline and negative rates since 2010. On an annual basis, the level of unemployed rose 59.8 percent in 2009 and 26.1 percent in 2008 with increase of 3.9 percent in 2010, decline of 7.3 percent in 2011 and decrease of 9.0 percent in 2012. The annual level of unemployment decreased 8.4 percent in 2013 and fell 16.1 percent in 2014. The annual level of unemployment fell 13.7 percent in 2015 and fell 6.6 percent in 2016. The level of unemployment decreased 4.0 percent in Feb 2017 relative to a year earlier.

 

Chart I-8, US, Unemployed, 12-month Percentage Change, NSA, 2001-2017

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

Chart I-9 of the Bureau of Labor Statistics provides the number of people in part-time occupations because of economic reasons, that is, because they cannot find full-time employment. The number underemployed in part-time occupations not seasonally adjusted rose from 3.732 million in Jan 2001 to 5.270 million in Jan 2004, falling to 3.787 million in Apr 2006. The number underemployed seasonally adjusted jumped to 9.114 million in Nov 2009, falling to 8.171 million in Dec 2011 but increasing to 8.305 million in Jan 2012 and 8.238 million in Feb 2012 but then falling to 7.943 million in Dec 2012 and increasing to 8.083 million in Jul 2013. The number employed part-time for economic reasons seasonally adjusted reached 5.704 million in Feb 2017. Without seasonal adjustment, the number employed part-time for economic reasons reached 9.354 million in Dec 2009, declining to 8.918 million in Jan 2012 and 8.166 million in Dec 2012 but increasing to 8.324 million in Jul 2013. The number employed part-time for economic reasons NSA stood at 7.990 million in Dec 2013, 6.970 million in Dec 2014 and 6.179 million in Dec 2015. The number employed part-time for economic reasons NSA stood at 5.707 million in Dec 2016. The number employed part-time for economic reasons reached 5.773 million in Feb 2017. The longer the period in part-time jobs the lower are the chances of finding another full-time job.

 

Chart I-9, US, Part-Time for Economic Reasons, Thousands, SA, 2001-2017

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

Chart I-10 of the Bureau of Labor Statistics repeats the behavior of unemployment. The 12-month percentage change of the level of people at work part-time for economic reasons jumped 84.7 percent in Mar 2009 and declined subsequently. The declines have been insufficient to reduce significantly the number of people who cannot shift from part-time to full-time employment. On an annual basis, the number of part-time for economic reasons increased 33.5 percent in 2008 and 51.7 percent in 2009, declining 0.4 percent in 2010, 3.5 percent in 2011 and 5.1 percent in 2012. The annual number of part-time for economic reasons decreased 2.3 percent in 2013 and fell 9.1 percent in 2014. The annual number of part-time for economic reasons fell 11.7 percent in 2015. The number of part-time for economic reasons decreased 6.7 percent in Dec 2016 relative to a year earlier. The level of part-time for economic reason fell 5.5 percent in Feb 2017 relative to a year earlier.

 

Chart I-10, US, Part-Time for Economic Reasons NSA 12-Month Percentage Change, 2001-2017

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

Chart I-11 of the Bureau of Labor Statistics provides the same pattern of the number marginally attached to the labor force jumping to significantly higher levels during the global recession and remaining at historically high levels. The number marginally attached to the labor force not seasonally adjusted increased from 1.295 million in Jan 2001 to 1.691 million in Feb 2004. The number of marginally attached to the labor force fell to 1.299 million in Sep 2006 and increased to 2.609 million in Dec 2010 and 2.800 million in Jan 2011. The number marginally attached to the labor force was 2.540 million in Dec 2011, increasing to 2.809 million in Jan 2012, falling to 2.608 million in Feb 2012. The number marginally attached to the labor force fell to 2.352 million in Mar 2012, 2.363 million in Apr 2012, 2.423 million in May 2012, 2.483 million in Jun 2012, 2.529 million in Jul 2012 and 2.561 million in Aug 2012. The number marginally attached to the labor force fell to 2.517 million in Sep 2012, 2.433 million in Oct 2012, 2.505 million in Nov 2012 and 2.427 million in in Dec 2013. The number marginally attached to the labor force reached 2.260 million in Dec 2014 and 1.833 million in Dec 2015. The number marginally attached to the labor force stood at 1.684 million in Dec 2016. The level marginally attached to the labor force reached 1.723 million Feb 2017.

 

Chart I-11, US, Marginally Attached to the Labor Force, Thousands, NSA, 2001-2017

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

Chart I-12 provides 12-month percentage changes of the marginally attached to the labor force from 2001 to 2017. There was a jump of 56.1 percent in May 2009 during the global recession followed by declines in percentage changes but insufficient negative changes. On an annual basis, the number of marginally attached to the labor force increased in four consecutive years: 15.7 percent in 2008, 37.9 percent in 2009, 11.7 percent in 2010 and 3.5 percent in 2011. The number marginally attached to the labor force fell 2.2 percent on annual basis in 2012 but increased 2.9 percent in the 12 months ending in Dec 2012, fell 13.0 percent in the 12 months ending in Jan 2013, falling 10.7 percent in the 12 months ending in May 2013. The number marginally attached to the labor force increased 4.0 percent in the 12 months ending in Jun 2013 and fell 4.5 percent in the 12 months ending in Jul 2013 and 8.6 percent in the 12 months ending in Aug 2013. The annual number of marginally attached to the labor force fell 6.2 percent in 2013 and fell 6.5 percent in 2014. The annual number of marginally attached to the labor force fell 11.4 percent in 2015. The number marginally attached to the labor force fell 7.2 percent in the 12 months ending in Dec 2013 and fell 6.9 percent in the 12 months ending in Dec 2014. The number marginally attached to the labor force fell 18.9 percent in the 12 months ending in Dec 2015 and decreased 8.1 percent in the 12 months ending in Dec 2016. The level of marginally attached to the labor force decreased 4.4 percent in the 12 months ending in Feb 2017.

 

Chart I-12, US, Marginally Attached to the Labor Force 12-Month Percentage Change, NSA, 2001-2017

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

Table I-4 consists of data and additional calculations using the BLS household survey, illustrating the possibility that the actual rate of unemployment could be 9.9 percent and the number of people in job stress could be around 24.2 million, which is 14.4 percent of the effective labor force. The first column provides for 2006 the yearly average population (POP), labor force (LF), participation rate or labor force as percent of population (PART %), employment (EMP), employment population ratio (EMP/POP %), unemployment (UEM), the unemployment rate as percent of labor force (UEM/LF Rate %) and the number of people not in the labor force (NLF). All data are unadjusted or not-seasonally-adjusted (NSA). The numbers in column 2006 are averages in millions while the monthly numbers for Feb 2016, Jan 2016 and Feb 2017 are in thousands, not seasonally adjusted. The average yearly participation rate of the population in the labor force was in the range of 66.0 percent minimum to 67.1 percent maximum between 2000 and 2006 with the average of 66.4 percent (http://www.bls.gov/data/). Table I-4b provides the yearly labor force participation rate from 1979 to 2017. The objective of Table I-4 is to assess how many people could have left the labor force because they do not think they can find another job. Row “LF PART 66.2 %” applies the participation rate of 2006, almost equal to the rates for 2000 to 2006, to the noninstitutional civilian population in Feb 2016, Jan 2017 and Feb 2017 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 62.7 percent by Feb 2016 and was 62.5 percent in Jan 2017 and 62.7 percent in Feb 2017, suggesting that many people simply gave up on finding another job. Row “∆ NLF UEM” calculates the number of people not counted in the labor force because they could have given up on finding another job by subtracting from the labor force with participation rate of 66.2 percent (row “LF PART 66.2%”) the labor force estimated in the household survey (row “LF”). Total unemployed (row “Total UEM”) is obtained by adding unemployed in row “∆NLF UEM” to the unemployed of the household survey in row “UEM.” The row “Total UEM%” is the effective total unemployed “Total UEM” as percent of the effective labor force in row “LF PART 66.2%.” The results are that:

  • there are an estimated 8.829 million unemployed in Feb 2017 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM), that is, they dropped out of their job searches
  • the total number of unemployed is effectively 16.716 million (Total UEM) and not 7.887 million (UEM) of whom many have been unemployed long term
  • the rate of unemployment is 9.9 percent (Total UEM%) and not 4.9 percent, not seasonally adjusted, or 4.7 percent seasonally adjusted
  • the number of people in job stress is close to 24.2 million by adding the 8.829 million leaving the labor force because they believe they could not find another job, corresponding to 14.4 percent of the effective labor force.

The row “In Job Stress” in Table I-4 provides the number of people in job stress not seasonally adjusted at 24.212 million in Feb 2017, adding the total number of unemployed (“Total UEM”), plus those involuntarily in part-time jobs because they cannot find anything else (“Part Time Economic Reasons”) and the marginally attached to the labor force (“Marginally attached to LF”). The final row of Table I-4 shows that the number of people in job stress is equivalent to 14.4 percent of the labor force in Feb 2017. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 59.4 percent in Feb 2016, 59.2 percent in Jan 2017 and 59.6 percent in Feb 2017. The number employed in Feb 2017 was 151.594 million (NSA) or 4.279 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 254.246 million in Feb 2016 or by 22.288 million. The number employed increased 2.9 percent from Jul 2007 to Feb 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.6 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Feb 2017 would result in 161.446 million jobs (0.635 multiplied by noninstitutional civilian population of 254.246 million). There are effectively 9.852 million fewer jobs in Feb 2017 than in Jul 2007, or 161.446 million minus 151.594 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

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). 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 (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html). This is merely another case of theory without reality with dubious policy proposals. The number of hiring relative to the number unemployed measures the chances of becoming employed. The number of hiring in the US economy has declined by 10 million and does not show signs of increasing in an unusual recovery without hiring. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Jan 1919 to Jan 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.7575 in Jan 2017. The actual index NSA in Jan 2017 is 101.5620, which is 28.9 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Jan 2017. Using trend growth of 2.0 percent per year, the index would increase to 129.5532 in Jan 2017. The output of manufacturing at 101.5620 in Jan 2017 is 21.6 percent below trend under this alternative calculation.

Table I-4, US, Population, Labor Force and Unemployment, NSA

 

2006

Feb 2016

Jan 2017

Feb 2017

POP

229

252,577

254,082

254,246

LF

151

158,279

158,676

159,482

PART%

66.2

62.7

62.5

62.7

EMP

144

150,060

150,527

151,594

EMP/POP%

62.9

59.4

59.2

59.6

UEM

7

8,219

8,149

7,887

UEM/LF Rate%

4.6

5.2

5.1

4.9

NLF

77

94,298

95,406

95,764

LF PART 66.2%

 

167,206

168,202

168,311

NLF UEM

 

8,927

9,526

8,829

Total UEM

 

17,146

17,675

16,716

Total UEM%

 

10.3

10.5

9.9

Part Time Economic Reasons

 

6,106

6,226

5,773

Marginally Attached to LF

 

1,803

1,752

1,723

In Job Stress

 

25,055

25,653

24,212

People in Job Stress as % Labor Force

 

15.0

15.3

14.4

Pop: population; LF: labor force; PART: participation; EMP: employed; UEM: unemployed; NLF: not in labor force; NLF UEM: additional unemployed; Total UEM is UEM + NLF UEM; Total UEM% is Total UEM as percent of LF PART 66.2%; In Job Stress = Total UEM + Part Time Economic Reasons + Marginally Attached to LF

Note: the first column for 2006 is in average millions; the remaining columns are in thousands; NSA: not seasonally adjusted

The labor force participation rate of 66.2% in 2006 is applied to current population to obtain LF PART 66.2%; NLF UEM is obtained by subtracting the labor force with participation of 66.2 percent from the household survey labor force LF; Total UEM is household data unemployment plus NLF UEM; and total UEM% is total UEM divided by LF PART 66.2%

Source: US Bureau of Labor Statistics

http://www.bls.gov/cps/

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.

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.”

Table I-4b and Chart I-12-b provide the US labor force participation rate or percentage of the labor force in population. It is not likely that simple demographic trends caused the sharp decline during the global recession and failure to recover earlier levels. The civilian labor force participation rate dropped from the peak of 66.9 percent in Jul 2006 to 62.6 percent in Dec 2013, 62.5 percent in Dec 2014, 62.4 percent in Dec 2015 and 62.4 in Dec 2016. The civilian labor force participation rate was 62.4 percent in Dec 2016. The civilian labor force participation rate reached 62.7 in Feb 2017. The civilian labor force participation rate was 63.7 percent on an annual basis in 1979 and 63.4 percent in Dec 1980 and Dec 1981, reaching even 62.9 percent in both Apr and May 1979. The civilian labor force participation rate jumped with the recovery to 64.8 percent on an annual basis in 1985 and 65.9 percent in Jul 1985. Structural factors cannot explain these sudden changes vividly shown visually in the final segment of Chart I-12b. Seniors would like to delay their retiring especially because of the adversities of financial repression on their savings. Labor force statistics are capturing the disillusion of potential workers with their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors. 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). 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 (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html). “Secular stagnation” would be a process over many years and not from one year to another. This is merely another case of theory without reality with dubious policy proposals.

Table I-4b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2017

Year

Jan

Feb

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

1979

62.9

63.0

62.9

64.5

64.9

64.5

63.8

64.0

63.8

63.8

63.7

1980

63.3

63.2

63.5

64.6

65.1

64.5

63.6

63.9

63.7

63.4

63.8

1981

63.2

63.2

63.9

64.6

65.0

64.6

63.5

64.0

63.8

63.4

63.9

1982

63.0

63.2

63.9

64.8

65.3

64.9

64.0

64.1

64.1

63.8

64.0

1983

63.3

63.2

63.4

65.1

65.4

65.1

64.3

64.1

64.1

63.8

64.0

1984

63.3

63.4

64.3

65.5

65.9

65.2

64.4

64.6

64.4

64.3

64.4

1985

64.0

64.0

64.6

65.5

65.9

65.4

64.9

65.1

64.9

64.6

64.8

1986

64.2

64.4

65.0

66.3

66.6

66.1

65.3

65.5

65.4

65.0

65.3

1987

64.7

64.8

65.6

66.3

66.8

66.5

65.5

65.9

65.7

65.5

65.6

1988

65.1

65.2

65.5

66.7

67.1

66.8

65.9

66.1

66.2

65.9

65.9

1989

65.8

65.6

66.2

67.4

67.7

67.2

66.3

66.6

66.7

66.3

66.5

1990

66.0

66.0

66.5

67.4

67.7

67.1

66.4

66.5

66.3

66.1

66.5

1991

65.5

65.7

66.0

67.2

67.3

66.6

66.1

66.1

66.0

65.8

66.2

1992

65.7

65.8

66.4

67.6

67.9

67.2

66.3

66.2

66.2

66.1

66.4

1993

65.6

65.8

66.3

67.3

67.5

67.0

66.1

66.4

66.3

66.2

66.3

1994

66.0

66.2

66.5

67.2

67.5

67.2

66.5

66.8

66.7

66.5

66.6

1995

66.1

66.2

66.4

67.2

67.7

67.1

66.5

66.7

66.5

66.2

66.6

1996

65.8

66.1

66.7

67.4

67.9

67.2

66.8

67.1

67.0

66.7

66.8

1997

66.4

66.5

67.0

67.8

68.1

67.6

67.0

67.1

67.1

67.0

67.1

1998

66.6

66.7

67.0

67.7

67.9

67.3

67.0

67.1

67.1

67.0

67.1

1999

66.7

66.8

67.0

67.7

67.9

67.3

66.8

67.0

67.0

67.0

67.1

2000

66.8

67.0

67.0

67.7

67.6

67.2

66.7

66.9

66.9

67.0

67.1

2001

66.8

66.8

66.6

67.2

67.4

66.8

66.6

66.7

66.6

66.6

66.8

2002

66.2

66.6

66.5

67.1

67.2

66.8

66.6

66.6

66.3

66.2

66.6

2003

66.1

66.2

66.2

67.0

66.8

66.3

65.9

66.1

66.1

65.8

66.2

2004

65.7

65.7

65.8

66.5

66.8

66.2

65.7

66.0

66.1

65.8

66.0

2005

65.4

65.6

66.0

66.5

66.8

66.5

66.1

66.2

66.1

65.9

66.0

2006

65.5

65.7

66.0

66.7

66.9

66.5

66.1

66.4

66.4

66.3

66.2

2007

65.9

65.8

65.8

66.6

66.8

66.1

66.0

66.0

66.1

65.9

66.0

2008

65.7

65.5

66.0

66.6

66.8

66.4

65.9

66.1

65.8

65.7

66.0

2009

65.4

65.5

65.5

66.2

66.2

65.6

65.0

64.9

64.9

64.4

65.4

2010

64.6

64.6

64.8

65.1

65.3

65.0

64.6

64.4

64.4

64.1

64.7

2011

63.9

63.9

64.1

64.5

64.6

64.3

64.2

64.1

63.9

63.8

64.1

2012

63.4

63.6

63.8

64.3

64.3

63.7

63.6

63.8

63.5

63.4

63.7

2013

63.3

63.2

63.5

64.0

64.0

63.4

63.2

62.9

62.9

62.6

63.2

2014

62.5

62.7

62.9

63.4

63.5

63.0

62.8

63.0

62.8

62.5

62.9

2015

62.5

62.5

63.0

63.1

63.2

62.7

62.3

62.5

62.5

62.4

62.7

2016

62.3

62.7

62.7

63.2

63.4

62.9

62.8

62.8

62.6

62.4

62.8

2017

62.5

62.7

                 

Source: US Bureau of Labor Statistics

http://www.bls.gov/cps/

 

Chart I-12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2017

Source: Bureau of Labor Statistics

http://www.bls.gov/cps/

Broader perspective is in Chart I-12c of the US Bureau of Labor Statistics. The United States civilian noninstitutional population has increased along a consistent trend since 1948 that continued through earlier recessions and the global recession from IVQ2007 to IIQ2009 and the cyclical expansion after IIIQ2009.

 

Chart I-12c, US, Civilian Noninstitutional Population, Thousands, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

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

The labor force of the United States in Chart I-12d has increased along a trend similar to that of the civilian noninstitutional population in Chart I-12c. There is an evident stagnation of the civilian labor force in the final segment of Chart I-12d during the current economic cycle. This stagnation is explained by cyclical factors similar to those analyzed by Lazear and Spletzer (2012JHJul22) that motivated an increasing population to drop out of the labor force instead of structural factors. Large segments of the potential labor force are not observed, constituting unobserved unemployment and of more permanent nature because those afflicted have been seriously discouraged from working by the lack of opportunities.

 

Chart I-12d, US, Labor Force, Thousands, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

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

The rate of labor force participation in the US is in Chart I-12E from 1948 to 2017. There is sudden decline during the global recession after 2007 without recovery explained by cyclical factors (Lazear and Spletzer2012JHJul22) as may many potential workers stopped their searches disillusioned that there could be an opportunity for them in sharply contracted markets.

 

Chart I-12E, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

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

IA3 Long-term and Cyclical Comparison of Employment. There is initial discussion here of long-term employment trends followed by cyclical comparison. Growth and employment creation have been mediocre in the expansion beginning in Jul IIIQ2009 from the contraction between Dec IVQ2007 and Jun IIQ2009 (http://www.nber.org/cycles.html). A series of charts from the database of the Bureau of Labor Statistics (BLS) provides significant insight. Chart I-13 provides the monthly employment level of the US from 1948 to 2017. The number of people employed has trebled. There are multiple contractions throughout the more than six decades but followed by resumption of the strong upward trend. The contraction of employment after 2007 is sharp and followed by a flatter curve of job creation. The United States missed this opportunity of high growth in the initial phase of recovery that historically eliminated unemployment and underemployment created during the contraction. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. IA3 Long-term and Cyclical Comparison of Employment. There is initial discussion here of long-term employment trends followed by cyclical comparison. Growth and employment creation have been mediocre in the expansion beginning in Jul IIIQ2009 from the contraction between Dec IVQ2007 and Jun IIQ2009 (http://www.nber.org/cycles.html). A series of charts from the database of the Bureau of Labor Statistics (BLS) provides significant insight. Chart I-13 provides the monthly employment level of the US from 1948 to 2016. The number of people employed has trebled. There are multiple contractions throughout the more than six decades but followed by resumption of the strong upward trend. The contraction of employment after 2007 is sharp and followed by a flatter curve of job creation. The United States missed this opportunity of high growth in the initial phase of recovery that historically eliminated unemployment and underemployment created during the contraction. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Jan 1919 to Jan 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.7575 in Jan 2017. The actual index NSA in Jan 2017 is 101.5620, which is 28.9 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Jan 2017. Using trend growth of 2.0 percent per year, the index would increase to 129.5532 in Jan 2017. The output of manufacturing at 101.5620 in Jan 2017 is 21.6 percent below trend under this alternative calculation.

 

Chart I-13, US, Employment Level, Thousands, SA, 1948-2017

Source: US Bureau of Labor Statistics

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

The steep and consistent curve of growth of the US labor force is in Chart I-14. The contraction beginning in Dec 2007 flattened the path of the US civilian labor force and with flatter curve during the current expansion.

 

Chart I-14, US, Civilian Labor Force, SA, 1948-2017, Thousands

Source: US Bureau of Labor Statistics

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

Chart I-15 for the period from 1948 to 2017. The labor force participation rate is influenced by numerous factors such as the age of the population. There is no comparable episode in the postwar economy to the sharp collapse of the labor force participation rate in Chart I-15 during the contraction and subsequent expansion after 2007. Aging can reduce the labor force participation rate as many people retire but many may have decided to work longer as their wealth and savings have been significantly reduced. There is an important effect of many people just exiting the labor force because they believe there is no job available for them.

 

Chart I-15, US, Civilian Labor Force Participation Rate, SA, 1948-2017, %

Source: US Bureau of Labor Statistics

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

The number of unemployed in the US jumped seasonally adjusted from 5.8 million in May 1979 to 12.1 million in Dec 1982, by 6.3 million, or 108.6 percent. The jump not seasonally adjusted was from 5.4 million in May 1979 to 12.5 million in Jan 1983, by 7.1 million or 131.5 percent. The number of unemployed seasonally adjusted jumped from 6.7 million in Mar 2007 to 15.4 million in Oct 2009, by 8.7 million, or 129.9 percent. The number of unemployed not seasonally adjusted jumped from 6.5 million in Apr 2007 to 16.1 million in Jan 2010, by 9.6 million or 147.7 percent. These are the two episodes with steepest increase in the level of unemployment in Chart I-16.

 

Chart I-16, US, Unemployed, SA, 1948-2017, Thousands

Source: US Bureau of Labor Statistics

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

Chart I-17 provides the rate of unemployment of the US from 1948 to 2017. The peak of the series is 10.8 percent in both Nov and Dec 1982. The second highest rates are 10.0 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009 SA. The unadjusted rate of unemployment NSA reached 4.9 percent in Feb 2017.

 

Chart I-17, US, Unemployment Rate, SA, 1948-2017

Source: US Bureau of Labor Statistics

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

The number unemployed 27 weeks or more in Chart I-18 jumped to peak levels in the current cycle. There is insufficient decline to return to earlier levels.

 

Chart I-18, US, Unemployed for 27 Weeks or More, SA, 1948-2016, Thousands

Source: US Bureau of Labor Statistics

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

The employment-population ratio in Chart I-19 is an important indicator of wellbeing in labor markets, measuring the number of people with jobs. The US employment-population ratio fell from 63.5 in Dec 2006 to 58.6 in Jul 2011 and stands at 59.6 NSA in Dec 2016. The employment population ration reached 59.6 NSA in Feb 2017. There is no comparable decline followed by stabilization during a cyclical expansion in Chart I-19.

 

Chart I-19, US, Employment-Population Ratio, 1948-2017

Source: US Bureau of Labor Statistics

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

The number employed part-time for economic reasons in Chart I-20 increased in the recessions and declined during the expansions. In the current cycle, the number employed part-time for economic reasons increased sharply and has not returned to normal levels. Lower growth of economic activity in the expansion after IIIQ2009 failed to reduce the number desiring to work full time but finding only part-time occupations. The lack of full-time jobs is evidently cyclical and not secular.

 

Chart I-20, US, Part-Time for Economic Reasons, NSA, 1955-2017, Thousands

Source: US Bureau of Labor Statistics

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

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 IVQ1982 and 4.2 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. In contrast, GDP grew 2.5 percent in 2010, 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014 and 2.6 percent in 2015. GDP grew 1.6 percent in 2016. Actual annual equivalent GDP growth in the twenty quarters from 2012 to 2016 is 2.0 percent and 1.9 percent in the four quarters ending in IVQ2016. GDP grew at 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. The forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 1.9 to 2.3 percent in 2017 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20161214.pdf) with less reliable forecast of 1.8 to 2.2 percent in 2017 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20161214.pdf). Growth of GDP in the expansion from IVQ2009 to IVQ2016 has been at average 2.1 percent in annual equivalent.

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

Year

GDP ∆%

Year

GDP ∆%

Year

GDP ∆%

1930

-8.5

1980

-0.2

2000

4.1

1931

-6.4

1981

2.6

2001

1.0

1932

-12.9

1982

-1.9

2002

1.8

1933

-1.3

1983

4.6

2003

2.8

1934

10.8

1984

7.3

2004

3.8

1935

8.9

1985

4.2

2005

3.3

1936

12.9

1986

3.5

2006

2.7

1937

5.1

1987

3.5

2007

1.8

1938

-3.3

1988

4.2

2008

-0.3

1939

8.0

1989

3.7

2009

-2.8

1940

8.8

1990

1.9

2010

2.5

1941

17.7

1991

-0.1

2011

1.6

1942

18.9

1992

3.6

2012

2.2

1943

17.0

1993

2.7

2013

1.7

1944

8.0

1994

4.0

2014

2.4

1945

-1.0

1995

2.7

2015

2.6

1946

-11.6

1996

3.8

2016

1.6

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

Characteristics of the four cyclical contractions are in Table I-6 with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.7 percent, which is almost equal to the decline of 4.2 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

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

 

Number of Quarters

Cumulative Percentage Contraction

Average Percentage Rate

IIQ1953 to IIQ1954

3

-2.4

-0.8

IIIQ1957 to IIQ1958

3

-3.0

-1.0

IVQ1973 to IQ1975

5

-3.1

-0.6

IQ1980 to IIIQ1980

2

-2.2

-1.1

IIIQ1981 to IVQ1982

4

-2.5

-0.64

IVQ2007 to IIQ2009

6

-4.2

-0.72

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

Table I-7 shows the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the thirty quarters of the current cyclical expansion from IIIQ2009 to IVQ2016. In sharp contrast, the average growth rate of GDP was:

  • 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986
  • 5.4 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986
  • 5.2 percent in the first sixteen quarters of expansion from IQ1983 to IVQ1986
  • 5.0 percent in the first seventeen quarters of expansion from IQ1983 to IQ1987
  • 5.0 percent in the first eighteen quarters of expansion from IQ1983 to IIQ1987
  • 4.9 percent in the first nineteen quarters of expansion from IQ1983 to IIIQ1987
  • 5.0 percent in the first twenty quarters of expansion from IQ1983 to IVQ1987
  • 4.9 percent in the first twenty-first quarters of expansion from IQ1983 to IQ1988
  • 4.9 percent in the first twenty-two quarters of expansion from IQ1983 to IIQ1988
  • 4.8 percent in the first twenty-three quarters of expansion from IQ1983 to IIIQ1988
  • 4.8 percent in the first twenty-four quarters of expansion from IQ1983 to IVQ1988
  • 4.8 percent in the first twenty-five quarters of expansion from IQ1983 to IQ1989
  • 4.7 percent in the first twenty-six quarters of expansion from IQ1983 to IIQ1989
  • 4.7 percent in the first twenty-seven quarters of expansion from IQ1983 to IIIQ1989
  • 4.5 percent in the first twenty-eight quarters of expansion from IQ1983 to IVQ1989
  • 4.5 percent in the first twenty-nine quarters of expansion from IQ1983 to IQ1990
  • 4.4 percent in the first thirty quarters of expansion from IQ1983 to IIQ1990

The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill with annual growth of 2.5 percent in 2010 decelerating to 1.6 percent annual growth in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014, 2.6 percent in 2015 and 1.6 percent in 2016 (http://www.bea.gov/iTable/index_nipa.cfm). The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988. 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989. 4.5 percent from IQ1983 to IVQ1989, 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983. GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the twenty quarters from 2012 to 2016 accumulated to 10.6 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IVQ2016 of $16,804.1 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/20: {[($16,804.1/$15,190.3)4/20 -1]100 = 2.0 percent}.

Table I-7 shows that GDP grew 17.1 percent in the first thirty quarters of expansion from IIIQ2009 to IVQ2016 at the annual equivalent rate of 2.1 percent.

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

 

Number
of
Quarters

Cumulative Growth

∆%

Average Annual Equivalent Growth Rate

IIIQ 1954 to IQ1957

11

12.8

4.5

First Four Quarters IIIQ1954 to IIQ1955

4

7.8

 

IIQ1958 to IIQ1959

5

10.0

7.9

First Four Quarters

IIIQ1958 to IIQ1959

4

9.2

 

IIQ1975 to IVQ1976

8

8.3

4.1

First Four Quarters IIIQ1975 to IIQ1976

4

6.1

 

IQ1983-IQ1986

IQ1983-IIIQ1986

IQ1983-IVQ1986

IQ1983-IQ1987

IQ1983-IIQ1987

IQ1983 to IIIQ1987

IQ1983 to IVQ1987

IQ1983 to IQ1988

IQ1983 to IIQ1988

IQ1983 to IIIQ1988

IQ1983 to IVQ1988

IQ1983 to IQ1989

IQ1983 to IIQ1989

IQ1983 to IIIQ1989

IQ1983 to IVQ1989

IQ1983 to IQ1990

IQ1983 to IIQ1990

13

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

19.9

21.6

22.3

23.1

24.5

25.6

27.7

28.4

30.1

30.9

32.6

34.0

35.0

36.0

36.3

37.8

38.3

5.7

5.4

5.2

5.0

5.0

4.9

5.0

4.9

4.9

4.8

4.8

4.8

4.7

4.7

4.5

4.5

4.4

First Four Quarters IQ1983 to IVQ1983

4

7.8

 

Average First Four Quarters in Four Expansions*

 

7.7

 

IIIQ2009 to IVQ2016

30

17.1

2.1

First Four Quarters IIIQ2009 to IIQ2010

 

2.7

 

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

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

A group of charts from the database of the Bureau of Labor Statistics facilitates the comparison of employment in the 1980s and 2000s. The long-term charts and tables from I-5 to I-7 in the discussion above confirm the view that the comparison of the current expansion should be with that in the 1980s because of similar dimensions. Chart I-21 provides the level of employment in the US between 1979 and 1989. Employment surged after the contraction and grew rapidly during the decade.

 

Chart I-21, US, Employed, Thousands, 1979-1989

Source: US Bureau of Labor Statistics

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

Chart I-22 provides the level of employment in the US from 2001 to 2016. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs. Recovery has been anemic compared with the shallow recession of 2001 that was followed by nearly vertical growth in jobs. The number employed in Feb 2017 was 151.594 million (NSA) or 4.279 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 254.246 million in Feb 2016 or by 22.288 million. The number employed increased 2.9 percent from Jul 2007 to Feb 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.6 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Feb 2017 would result in 161.446 million jobs (0.635 multiplied by noninstitutional civilian population of 254.246 million). There are effectively 9.852 million fewer jobs in Feb 2017 than in Jul 2007, or 161.446 million minus 151.594 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

 

Chart I-22, US, Employed, Thousands, 2001-2017

Source: US Bureau of Labor Statistics

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

The US civilian labor force in Chart I-23 grew with few interruptions from 1979 to 1989.

 

Chart I-23, US, Civilian Labor Force, Thousands, 1979-1989

Source: US Bureau of Labor Statistics

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

The civilian labor force in Chart I-24 grew steadily on an upward trend in the 2000s until it contracted together with the economy after 2007. There has not been recovery during the expansion but rather decline and marginal turn of the year 2011 into expansion in 2012 followed by stability and oscillation into 2013-2017. There is substantial underperformance relative to trend before the global recession. The civilian labor force consists of people who are available and willing to work and who have searched for employment recently. The labor force of the US NSA grew 9.4 percent from 142.828 million in Jan 2001 to 156.255 million in Jul 2009. The civilian labor force is 2.1 percent higher at 159.482 million in Feb 2017 than in Jul 2009, all numbers not seasonally adjusted. Chart I-3 shows the flattening of the curve of expansion of the labor force and its decline in 2010 and 2011. The ratio of the labor force of 154.871 million in Jul 2007 to the noninstitutional population of 231.958 million in Jul 2007 was 66.8 percent while the ratio of the labor force of 159.482 million in Feb 2017 to the noninstitutional population of 254.246 million in Feb 2017 was 62.7 percent. The labor force of the US in Feb 2017 corresponding to 66.8 percent of participation in the population would be 169.836 million (0.668 x 254.246). The difference between the measured labor force in Feb 2017 of 159.482 million and the labor force in Feb 2017 with participation rate of 66.8 percent (as in Jul 2007) of 169.836 million is 10.354 million. The level of the labor force in the US has stagnated and is 10.354 million lower than what it would have been had the same participation rate been maintained. Millions of people have abandoned their search for employment because they believe there are no jobs available for them. The key issue is whether the decline in participation of the population in the labor force is the result of people giving up on finding another job.

 

Chart I-24, US, Civilian Labor Force, Thousands, 2001-2017

Source: US Bureau of Labor Statistics

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

The rate of participation of the labor force in population stagnated during the stagflation and conquest of inflation in the late 1970s and early 1980s, as shown in Chart I-25. Recovery was vigorous during the expansion and lasted through the remainder of the decade.

 

Chart I-25, US, Civilian Labor Force Participation Rate, 1979-1989, %

Source: US Bureau of Labor Statistics

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

The rate of participation in the labor force declined after the recession of 2001 followed by stability until 2007, as shown in Chart I-26. The rate of participation in the labor force continued to decline both during the contraction after 2007 and during the expansion after 2009 with marginal expansion at the turn of the year into 2012 followed by trend of decline and stability. Sharp decline occurred during the cycle and not secularly.

 

Chart I-26, US, Civilian Labor Force Participation Rate, 2001-2017, %

Source: US Bureau of Labor Statistics

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

Chart I-27 provides the number unemployed during the 1980s. The number unemployed peaked at 12.051 million in Dec 1982 seasonally adjusted and 12.517 in Jan 1983 million not seasonally adjusted, declining to 8.358 million in Dec 1984 seasonally adjusted and 7.978 million in Dec 1984 not seasonally adjusted during the first two years of expansion from the contraction. The number unemployed then fell to 6.667 million in Dec 1989 seasonally adjusted and 6.300 million not seasonally adjusted.

 

Chart I-27, US, Unemployed Thousands 1979-1989

Source: US Bureau of Labor Statistics

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

Chart I-28 provides the number unemployed from 2001 to 2017. Using seasonally adjusted data, the number unemployed rose from 6.727 million in Oct 2006 to 15.352 million in Oct 2009, declining to 13.093 million in Dec 2011, 8.718 million in Dec 2014 and 7.927 million in Dec 2015. The number unemployed SA stood at 7.529 million in Dec 2016. The level of unemployment SA was 7.528 million in Feb 2017. Using data not seasonally adjusted, the number unemployed rose from 6.272 million in Oct 2006 to 16.147 million in Jan 2010, declining to 11.844 million in Dec 2012, increasing to 13.181 million in Jan 2013 and declining to 9.984 million in Dec 2013. The level of unemployment fell from 10.855 million in Jan 2014 to 8.331 million in Dec 2014. The level of unemployment was 7.542 million in Dec 2015 and 7.170 million in Dec 2016. The level of unemployment was 7.887 million in Feb 2017.

 

Chart I-28, US, Unemployed Thousands 2001-2017

Source: US Bureau of Labor Statistics

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

The rate of unemployment peaked at 10.8 percent in both Nov and Dec 1982 seasonally adjusted, as shown in Chart I-29. The rate of unemployment dropped sharply during the expansion after 1984 and continued to decline during the rest of the decade to 5.4 percent in Dec 1989. Using not seasonally adjusted data, the rate of unemployment peaked at 11.4 percent in Jan 1983, declining to 7.0 percent in Dec 1984 and 5.1 percent in Dec 1989.

 

Chart I-29, US, Unemployment Rate, 1979-1989, %

Source: US Bureau of Labor Statistics

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

The rate of unemployment in the US seasonally adjusted jumped from 4.4 percent in May 2007 to 10.0 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009, as shown in Chart I-30. The rate of unemployment fluctuated at around 9.0 percent in 2011, declining to 7.9 percent in Dec 2012 and 6.7 percent in Dec 2013. The rate of unemployed eased to 5.6 percent in Dec 2014 and 5.0 percent in Dec 2015. The rate of unemployment SA stood at 4.7 percent in Dec 2016. The rate of unemployment SA reached 4.7 percent in Feb 2017.

 

Chart I-30, US, Unemployment Rate, 2001-2017, %

Source: US Bureau of Labor Statistics

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

The employment population ratio seasonally adjusted fell from around 60.1 in Dec 1979 to 57.1 in both Feb and Mar 1983, as shown in Chart I-31. The employment population ratio seasonally adjusted rose back to 59.9 in Dec 1984 and reached 63.0 later in the decade in Dec 1989. Using not seasonally adjusted data, the employment population ratio dropped from 60.4 percent in Oct 1979 to 56.1 percent in Jan 1983, increasing to 59.8 in Dec 1984 and to 62.9 percent in Dec 1989.

 

Chart I-31, US, Employment Population Ratio, 1979-1989, %

Source: US Bureau of Labor Statistics

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

The US employment-population ratio seasonally adjusted has fallen from 63.4 in Dec 2006 to 58.6 in Dec 2011, 58.7 in Dec 2012, 58.7 in Dec 2013, 59.2 in Dec 2014 and 59.6 in Dec 2015, as shown in Chart I-32. The employment-population ratio reached 59.7 in Dec 2016. The employment population ratio stood at 59.7 in Feb 2017. The employment population-ratio has stagnated during the expansion. Using not seasonally adjusted data, the employment population ratio fell from 63.6 percent in Jul 2006 to 57.6 percent in Jan 2011, 58.5 percent in Dec 2012, 58.5 percent in Dec 2013 and 59.1 in Dec 2014. The employment population ratio reached 59.4 percent in Dec 2015 and 59.6 percent in Dec 2016. The employment population ratio stood at 59.6 in Feb 2017.

 

Chart I-32, US, Employment Population Ratio, 2001-2017, %

Source: US Bureau of Labor Statistics

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

The number unemployed 27 weeks or more rose in Chart I-33 rose from 492,000 NSA in Oct 1979 to 2.978 million in Mar 1983. The level unemployed 27 weeks or more NSA fell to 566,000 in Aug 1989.

 

Chart I-33, US, Number Unemployed for 27 Weeks or More 1979-1989, SA, Thousands

Source: US Bureau of Labor Statistics

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

The number unemployed for 27 weeks or over, seasonally adjusted, increased sharply during the contraction as shown in Chart I-34 from 1.131 million in Nov 2006 to 6.800 million in Apr 2010 seasonally adjusted. The number of unemployed for 27 weeks or over remained at around 6 million during the expansion compared with somewhat above 1 million before the contraction, falling to 1.831 million in Dec 2016 seasonally adjusted and 1.769 million not seasonally adjusted. The level unemployed for 27 week or over reached 1.801 million SA in Feb 2017 and 1.878 million NSA.

 

Chart I-34, US, Number Unemployed for 27 Weeks or More, 2001-2017, SA, Thousands

Source: US Bureau of Labor Statistics

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

The number of persons working part-time for economic reasons because they cannot find full-time work peaked during the contraction at 6.857 million SA in Oct 1982, as shown in Chart I-35. The number of persons at work part-time for economic reasons fell sharply during the expansion to 5.797 million in Dec 1984 and continued to fall throughout the decade to 4.817 million in Dec 1989 SA and 4.709 million NSA.

 

Chart I-35, US, Part-Time for Economic Reasons, 1979-1989, Thousands

Source: US Bureau of Labor Statistics

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

The number of people working part-time because they cannot find full-time employment, not seasonally adjusted, increased sharply during the contraction from 3.787 million in Apr 2006, not seasonally adjusted, to 9.354 million in Dec 2009, as shown in Chart I-36. The number of people working part-time because of failure to find an alternative occupation stagnated at a very high level during the expansion, declining to 5.773 million not seasonally adjusted in Feb 2017.

 

Chart I-36, US, Part-Time for Economic Reasons, 2001-2017, Thousands

Source: US Bureau of Labor

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

The number marginally attached to the labor force in Chart I-37 jumped from 1.252 million in Dec 2006 to 2.800 million in Jan 2011, remaining at a high level of 2.540 million in Dec 2011, 2.809 million in Jan 2012 and 2.614 million in Dec 2012. The number marginally attached to the labor force eased to 2.427 million in Dec 2013, 2.260 million in Dec 2014 and 1.833 million in Dec 2015. The level of marginally attached to the labor force reached 1.684 million in Dec 2016. The number of marginally attached to the labor force stood at 1.723 million in Feb 2017.

 

Chart I-37, US, Marginally Attached to the Labor Force, 2001-2017

Source: US Bureau of Labor Statistics

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

IA4 Job Creation. What is striking about the data in Table I-8 is that the numbers of monthly increases in jobs in 1983 and 1984 are several times higher than in 2010 to 2016. The civilian noninstitutional population grew by 45.5 percent from 174.215 million in 1983 to 253.538 million in 2016 and labor force higher by 42.7 percent, growing from 111.550 million in 1983 to 159.187 million in 2016. Total nonfarm payroll employment seasonally adjusted (SA) increased 235,000 in Feb 2017 and private payroll employment increased 227,000. The average monthly number of nonfarm jobs created from Feb 2015 to Feb 2016 was 217,000 using seasonally adjusted data, while the average number of nonfarm jobs created from Feb 2016 to Feb 2017 was 195,833, or decrease by 9.8 percent. The average number of private jobs created in the US from Feb 2015 to Feb 2016 was 203,583, using seasonally adjusted data, while the average from Feb 2016 to Feb 2017 was 179,667, or decrease by 11.7 percent. This blog calculates the effective labor force of the US at 168.311 million in Feb 2017 and 167,206 million in Feb 2016 (Table I-4), for growth of 1.105 million at average 92,083 per month. The difference between the average increase of 179,667 new private nonfarm jobs per month in the US from Feb 2016 to Feb 2017 and the 92,083 average monthly increase in the labor force from Feb 2016 to Feb 2017 is 87,584 monthly new jobs net of absorption of new entrants in the labor force. There are 24.212 million in job stress in the US currently. Creation of 87,584 new jobs per month net of absorption of new entrants in the labor force would require 276 months to provide jobs for the unemployed and underemployed (24.212 million divided by 87,584) or 23 years (276 divided by 12). The civilian labor force of the US in Feb 2017 not seasonally adjusted stood at 159.482 million with 7.887 million unemployed or effectively 16.716 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 168.311 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 0.9 years (1 million divided by product of 87,584 by 12, which is 1,051,008). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.974 million (0.05 times labor force of 159.482 million). New net job creation would be minus 0.087 million (7.887 million unemployed minus 7.974 million unemployed at rate of 5 percent) that at the current rate would take 0.0 years (0.087 million divided by 1,051,008). Under the calculation in this blog, there are 16.716 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 168.311 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 9.265 million jobs net of labor force growth that at the current rate would take 7.9 years (16.716 million minus 0.05(168.311 million) = 8.300 million divided by 1,051,008 using LF PART 66.2% and Total UEM in Table I-4). These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply. The number employed in Feb 2017 was 151.594 million (NSA) or 4.279 million more people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population of ages 16 years and over increased from 231.958 million in Jul 2007 to 254.246 million in Feb 2016 or by 22.288 million. The number employed increased 2.9 percent from Jul 2007 to Feb 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.6 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employment as percent of population of 231.958 million). The same ratio in Feb 2017 would result in 161.446 million jobs (0.635 multiplied by noninstitutional civilian population of 254.246 million). There are effectively 9.852 million fewer jobs in Feb 2017 than in Jul 2007, or 161.446 million minus 151.594 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

There is 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). 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 (http://cmpassocregulationblog.blogspot.com/2017/01/unconventional-monetary-policy-and.html). The proper explanation is not in secular stagnation but in cyclically slow growth. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Jan 1919 to Jan 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.7575 in Jan 2017. The actual index NSA in Jan 2017 is 101.5620, which is 28.9 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Jan 2017. Using trend growth of 2.0 percent per year, the index would increase to 129.5532 in Jan 2017. The output of manufacturing at 101.5620 in Jan 2017 is 21.6 percent below trend under this alternative calculation.

Table I-8, US, Monthly Change in Jobs, Number SA

Month

1981

1982

1983

2008

2009

2010

Private

Jan

94

-326

224

17

-793

23

14

Feb

68

-5

-75

-84

-702

-68

-53

Mar

105

-130

172

-78

-823

164

122

Apr

73

-280

276

-210

-687

243

192

May

10

-45

277

-186

-349

524

97

Jun

197

-243

379

-162

-471

-137

119

Jul

112

-342

418

-213

-329

-68

103

Aug

-36

-158

-308

-267

-213

-36

113

Sep

-87

-181

1115

-450

-220

-52

121

Oct

-99

-277

271

-474

-204

262

212

Nov

-209

-123

353

-766

-2

119

129

Dec

-278

-14

356

-694

-275

87

108

     

1984

   

2011

Private

Jan

   

446

   

43

51

Feb

   

481

   

189

232

Mar

   

275

   

225

248

Apr

   

363

   

346

354

May

   

308

   

77

132

Jun

   

379

   

225

190

Jul

   

313

   

69

184

Aug

   

242

   

110

142

Sep

   

310

   

248

282

Oct

   

286

   

209

194

Nov

   

349

   

141

168

Dec

   

128

   

209

226

     

1985

   

2012

Private

Jan

   

266

   

358

366

Feb

   

124

   

237

236

Mar

   

346

   

233

237

Apr

   

196

   

78

90

May

   

274

   

115

135

Jun

   

146

   

76

57

Jul

   

190

   

143

160

Aug

   

193

   

177

174

Sep

   

203

   

203

194

Oct

   

188

   

146

168

Nov

   

209

   

132

152

Dec

   

167

   

244

240

     

1986

   

2013

Private

Jan

   

125

   

211

226

Feb

   

107

   

286

267

Mar

   

94

   

130

152

Apr

   

187

   

197

195

May

   

127

   

226

242

Jun

   

-94

   

162

179

Jul

   

318

   

122

146

Aug

   

114

   

261

242

Sep

   

347

   

190

184

Oct

   

186

   

212

214

Nov

   

186

   

258

250

Dec

   

205

   

47

73

     

1987

   

2014

Private

Jan

   

172

   

190

204

Feb

   

232

   

151

139

Mar

   

249

   

272

261

Apr

   

338

   

329

299

May

   

226

   

246

252

Jun

   

172

   

304

259

Jul

   

347

   

202

226

Aug

   

171

   

230

238

Sep

   

228

   

280

237

Oct

   

492

   

227

214

Nov

   

232

   

312

302

Dec

   

294

   

255

240

     

1988

   

2015

Private

Jan

   

94

   

234

227

Feb

   

453

   

238

222

Mar

   

276

   

86

97

Apr

   

245

   

262

235

May

   

229

   

344

324

Jun

   

363

   

206

195

Jul

   

222

   

254

239

Aug

   

124

   

157

115

Sep

   

339

   

100

116

Oct

   

268

   

321

314

Nov

   

339

   

272

260

Dec

   

290

   

239

217

     

1989

   

2016

Private

Jan

   

262

   

126

110

Feb

   

258

   

237

221

Mar

   

193

   

225

189

Apr

   

173

   

153

158

May

   

118

   

43

17

Jun

   

116

   

297

269

Jul

   

40

   

291

249

Aug

   

49

   

176

143

Sep

   

250

   

249

223

Oct

   

111

   

124

132

Nov

   

277

   

164

178

Dec

   

96

   

155

150

     

1990

   

2017

Private

Jan

   

336

   

238

221

Feb

   

248

   

235

227

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Charts numbered from I-38 to I-41 from the database of the Bureau of Labor Statistics provide a comparison of payroll survey data for the contractions and expansions in the 1980s and after 2007. Chart I-38 provides total nonfarm payroll jobs from 2001 to 2016. The sharp decline in total nonfarm jobs during the contraction after 2007 has been followed by initial stagnation and then inadequate growth in 2012 and 2013-2017 while population growth continued.

 

Chart I-38, US, Total Nonfarm Payroll Jobs SA 2001-2017

Source: US Bureau of Labor Statistics

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

Chart I-39 provides total nonfarm jobs SA from 1979 to 1989. Recovery is strong throughout the decade with the economy growing at trend over the entire economic cycle.

 

Chart I-39, US, Total Nonfarm Payroll Jobs SA 1979-1989

Source: US Bureau of Labor Statistics

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

Most job creation in the US is by the private sector. Chart I-40 shows the sharp destruction of private payroll jobs during the contraction after 2007. There has been growth after 2010 but insufficient to recover higher levels of employment prevailing before the contraction. At current rates, recovery of employment may spread over several years in contrast with past expansions of the business cycle in the US.

 

Chart I-40, US, Total Private Payroll Jobs SA 2001-2017

Source: US Bureau of Labor Statistics

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

In contrast, growth of private payroll jobs in the US recovered vigorously during the expansion in 1983 through 1985, as shown in Chart I-41. Rapid growth of creation of private jobs continued throughout the 1980s.

 

Chart I-41, US, Total Private Payroll Jobs SA 1979-1989

Source: US Bureau of Labor Statistics

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

Types of jobs created, and not only the pace of job creation, may be important. Aspects of growth of payroll jobs from Feb 2016 to Feb 2017, not seasonally adjusted (NSA), are in Table I-9. Total nonfarm employment increased by 2,352,000 (row A, column Change), consisting of growth of total private employment by 2,144,000 (row B, column Change) and increase by 208,000 of government employment (row C, column Change). Monthly average growth of private payroll employment has been 178,667, which is mediocre relative to 24 to 30 million in job stress, while total nonfarm employment has grown on average by only 196,000 per month, which does not significantly reduce job stress with 154.750 new entrants per month in the labor force. These monthly rates of job creation net of the demands of new entrants in the labor force perpetuate unemployment and underemployment. Manufacturing employment increased by 11,000, at the monthly rate of 917 while private service providing employment grew by 1,942,000, at the monthly average rate of 161,833. An important feature in Table I-9 is that jobs in professional and business services increased 598,000 with temporary help services increasing 88,000. This episode of jobless recovery is characterized by part-time jobs and creation of jobs that are inferior to those that have been lost. Monetary and fiscal stimuli fail to increase consumption and investment in a fractured job market. The segment leisure and hospitality added 286,000 jobs in 12 months. An important characteristic is that the loss of government jobs has stabilized in federal government with increase of 42,000 jobs while states increased 15,000 jobs and local government added 151,000 jobs. Local government provides the bulk of government jobs, 14.593 million, while federal government provides 2.803 million and states’ government 5.225 million.

Table I-9, US, Employees in Nonfarm Payrolls Not Seasonally Adjusted, in Thousands

 

Feb 2016

Feb 2017

Change

A Total Nonfarm

141,919

144,271

2,352

B Total Private

119,506

121,650

2,144

B1 Goods Producing

19,244

19,446

202

B1a

Manufacturing

12,290

12,301

11

B2 Private service providing

100,262

102,204

1,942

B2a Wholesale Trade

5,812

5,862

50

B2b Retail Trade

15,481

15,607

126

B2c Transportation & Warehousing

4,880

4972

92

B2d Financial Activities

8,155

8,342

187

B2e Professional and Business Services

19,609

20,207

598

B2e1 Temporary help services

2,753

2,841

88

B2f Health Care & Social Assistance

18,840

19,290

450

B2g Leisure & Hospitality

14,889

15,175

286

C Government

22,413

22,621

208

C1 Federal

2,761

2,803

42

C2 State

5,210

5,225

15

C3 Local

14,442

14,593

151

Note: A = B+C, B = B1 + B2, C=C1 + C2 + C3

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Greater detail on the types of jobs created is provided in Table I-10 with data for Dec 2016 and

Jan 2017. Strong seasonal effects are shown by the significant difference between seasonally adjusted (SA) and not-seasonally-adjusted (NSA) data. The purpose of adjusting for seasonality is to isolate nonseasonal effects. The 235,000 SA total nonfarm jobs created in Feb 2017 relative to Jan 2017 actually correspond to increase of 1460 thousand jobs NSA, as shown in row A. Most of this difference in Jan 2017 is due to the necessary benchmark and seasonal adjustments in the beginning of every year. The 227,000 total private payroll jobs SA created in Feb 2017 relative to Jan 2017 actually correspond to increase of 552 thousand jobs NSA. The analysis of NSA job creation in the prior Table I-9 does show improvement over the 12 months ending in Feb 2017 that is not clouded by seasonal variations but is inadequate number of jobs created. In fact, the 12-month rate of job creation without seasonal adjustment is stronger indication of marginal improvement in the US job market but that is insufficient in even making a dent in about 30 million people unemployed or underemployed. Benchmark and seasonal adjustments affect comparability of data over time.

Table I-10, US, Employees on Nonfarm Payrolls and Selected Industry Detail, Thousands, SA and NSA

 

Jan  2017 SA

Feb  2017 SA

Jan   2017 NSA

Feb   2017 NSA

A Total Nonfarm

145,563

145,798

235

143,261

144,721

1460

B Total Private

123,247

123,474

227

121,098

121,650

552

B1 Goods Producing

19,848

19,943

95

19,337

19,446

109

B1a Constr.

6,823

6,881

58

6,414

6,475

61

B Mfg

12,354

12,382

28

12,261

12,301

40

B2 Private Service Providing

103,399

103,531

132

101,761

102,204

443

B2a Wholesale Trade

5,894

5,904

10

5,845

5,862

17

B2b Retail Trade

15,921

15,895

-26

15,833

15,607

-226

B2c Couriers     & Mess.

658

659

1

672

635

-37

B2d Health-care & Social Assistance

19,293

19,326

33

19,236

19,290

54

B2De Profess. & Business Services

20,462

20,499

37

20,088

20,207

119

B2De1 Temp Help Services

2,968

2,971

3

2,835

2,841

6

B2f Leisure & Hospit.

15,768

15,794

26

15,027

15,175

148

Notes: ∆: Absolute Change; Constr.: Construction; Mess.: Messengers; Temp: Temporary; Hospit.: Hospitality. SA aggregates do not add because of seasonal adjustment.

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Manufacturing jobs not seasonally adjusted decreased 11,000 from Feb 2016 to
Feb 2017 or at the average monthly rate of 917. Industrial production decreased 0.3 percent in Jan 2017 and increased 0.6 percent in Dec 2016 after decreasing 0.2 percent in Nov 2016, with all data seasonally adjusted, as shown in Table I-1. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Apr 1, 2016 (http://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] Total IP is now reported to have increased about 2 1/2 percent per year, on average, from 2011 through 2014 before falling 1 1/2 percent in 2015.[2] Relative to earlier reports, the current rates of change are lower, especially for 2014 and 2015. Total IP is now estimated to have returned to its pre-recession peak in November 2014, six months later than previously estimated. Capacity for total industry is now reported to have increased about 2 percent in 2014 and 2015 after having increased only 1 percent in 2013. Compared with the previously reported estimates, the gain in 2015 is 1/2 percentage point higher, and the gain in 2013 is 1/2 percentage point lower. Industrial capacity is expected to increase 1/2 percent in 2016.”

The report of the Board of Governors of the Federal Reserve System states (https://www.federalreserve.gov/releases/g17/Current/default.htm):

“Industrial production decreased 0.3 percent in January following a 0.6 percent increase in December. In January, manufacturing output moved up 0.2 percent, and mining output jumped 2.8 percent. The index for utilities fell 5.7 percent, largely because unseasonably warm weather reduced the demand for heating. At 104.6 percent of its 2012 average, total industrial production in January was at about the same level as it was a year earlier. Capacity utilization for the industrial sector fell 0.3 percentage point in January to 75.3 percent, a rate that is 4.6 percentage points below its long-run (1972–2016) average.” In the six months ending in Jan 2017, United States national industrial production accumulated change of 0.0 percent at the annual equivalent rate of 0.0 percent, which is equal to growth of 0.0 percent in the 12 months ending in Jan 2017. Excluding growth of 0.6 percent in Dec 2016, growth in the remaining five months from Aug to Jan 2017 accumulated to minus 0.6 percent or minus 1.4 percent annual equivalent. Industrial production declined in four of the past six months and increased 0.3 percent in one month and 0.6 percent in another month. Industrial production grew at annual equivalent 0.4 percent in the most recent quarter from Nov 2016 to Jan 2017 and decreased at 0.4 percent in the prior quarter Aug 2016 to Oct 2016. Business equipment accumulated change of 0.0 percent in the six months from Aug 2016 to Jan 2017, at the annual equivalent rate of 0.0 percent, which is lower than growth of 1.2 percent in the 12 months ending in Jan 2017. The Fed analyzes capacity utilization of total industry in its report (https://www.federalreserve.gov/releases/g17/Current/default.htm): “Capacity utilization for the industrial sector fell 0.3 percentage point in January to 75.3 percent, a rate that is 4.6 percentage points below its long-run (1972–2016) average.” United States industry apparently decelerated to a lower growth rate followed by possible acceleration and weakening growth in past months. Manufacturing declined 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increased 16.4 percent from the trough in Apr 2009 to Dec 2016. Manufacturing grew 16.2 percent from the trough in Apr 2009 to Jan 2017. Manufacturing in Jan 2017 is lower by 9.8 percent relative to the peak in Jun 2007. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 25.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 15.0 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Jan 1919 to Jan 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.7575 in Jan 2017. The actual index NSA in Jan 2017 is 101.5620, which is 28.9 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Jan 2017. Using trend growth of 2.0 percent per year, the index would increase to 129.5532 in Jan 2017. The output of manufacturing at 101.5620 in Jan 2017 is 21.6 percent below trend under this alternative calculation.

Table I-13 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 87.2 percent in IIIQ2016. Most of US national income is in the form of services. In Feb 2017, there were 144.271 million nonfarm jobs NSA in the US, according to estimates of the establishment survey of the Bureau of Labor Statistics (BLS) (http://www.bls.gov/news.release/empsit.nr0.htm Table B-1). Total private jobs of 121.650 million NSA in Feb 2017 accounted for 84.3 percent of total nonfarm jobs of 144.271 million, of which 12.301 million, or 10.1 percent of total private jobs and 8.5 percent of total nonfarm jobs, were in manufacturing. Private service-providing jobs were 102.204 million NSA in Feb 2017, or 70.8 percent of total nonfarm jobs and 84.0 percent of total private-sector jobs. Manufacturing has share of 10.4 percent in US national income in IIIQ2016 and durable goods 6.0 percent, as shown in Table I-13. Most income in the US originates in services. Subsidies and similar measures designed to increase manufacturing jobs will not increase economic growth and employment and may actually reduce growth by diverting resources away from currently employment-creating activities because of the drain of taxation.

Table I-13, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total

 

SAAR
IIQ2016

% Total

SAAR IIIQ2016

% Total

National Income WCCA

15,905.5

100.0

16,173.7

100.0

Domestic Industries

15,697.6

98.7

15,969.7

98.7

Private Industries

13,843.4

87.0

14,095.4

87.2

Agriculture

123.9

0.8

122.0

0.8

Mining

187.7

1.2

187.7

1.2

Utilities

164.9

1.0

172.0

1.1

Construction

765.2

4.8

771.3

4.8

Manufacturing

1658.4

10.4

1676.5

10.4

Durable Goods

972.8

6.1

977.4

6.0

Nondurable Goods

685.6

4.3

699.2

4.3

Wholesale Trade

920.7

5.8

957.9

5.9

Retail Trade

1118.6

7.0

1136.2

7.0

Transportation & WH

495.7

3.1

505.7

3.1

Information

578.8

3.6

596.0

3.7

Finance, Insurance, RE

2807.8

17.7

2862.6

17.7

Professional & Business Services

2246.5

14.1

2293.6

14.2

Education, Health Care

1633.0

10.3

1651.7

10.2

Arts, Entertainment

675.1

4.2

688.0

4.3

Other Services

467.1

2.9

474.2

2.9

Government

1854.3

11.7

1874.3

11.6

Rest of the World

207.8

1.3

204.0

1.3

Notes: SSAR: Seasonally-Adjusted Annual Rate; WCCA: Without Capital Consumption Adjustment by Industry; WH: Warehousing; RE, includes rental and leasing: Real Estate; Art, Entertainment includes recreation, accommodation and food services; BS: business services

Source: US Bureau of Economic Analysis

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

Chart I-42 provides output of durable manufacturing from 1972 to 2016. Output fell sharply during the global recession, recovering at relatively high pace. Output is lower than extrapolation of trend.

 

Chart I-42, US, Output of Durable Manufacturing, 1972-2017

Source: Board of Governors of the Federal Reserve

http://www.federalreserve.gov/releases/g17/Current/default.htm

The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). Table I-12 provides total annual level nonfarm employment in the US for the 1980s and the 2000s, which is different from 12-month comparisons. Nonfarm jobs rose by 4.859 million from 1982 to 1984, or 5.4 percent, and continued rapid growth in the rest of the decade. In contrast, nonfarm jobs are down by 7.638 million in 2010 relative to 2007 and fell by 952,000 in 2010 relative to 2009 even after six quarters of GDP growth. Monetary and fiscal stimuli have failed in increasing growth to rates required for mitigating job stress. The initial growth impulse reflects a flatter growth curve in the current expansion. Nonfarm jobs declined from 137.999 million in 2007 to 136.381 million in 2013, by 1.618 million or 1.2 percent. Nonfarm jobs increased from 137.999 million in 2007 to 144,306 million in 2016, by 6.308 million or 4.6 percent. The US noninstitutional population or in condition to work increased from 231.867 million in 2007 to 253.538 million in 2016, by 21,671 million or 9.3 percent. The ratio of nonfarm jobs of 137.999 million in 2007 to the noninstitutional population of 231.867 was 59.5. Nonfarm jobs in 2016 corresponding to the ratio of 59.5 of nonfarm jobs/noninstitutional population would be 150.855 million (0.595x253.538). The difference between actual nonfarm jobs of 144.306 million in 2016 and nonfarm jobs of 150.855 million that are equivalent to 59.5 percent of the noninstitutional population as in 2007 is 6.549 million fewer jobs. The proper explanation for this loss of work opportunities is not in secular stagnation but in cyclically slow growth. The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). The proper explanation for this loss of work opportunities is not in secular stagnation but in cyclically slow growth. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Jan 1919 to Jan 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.7575 in Jan 2017. The actual index NSA in Jan 2017 is 101.5620, which is 28.9 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Jan 2017. Using trend growth of 2.0 percent per year, the index would increase to 129.5532 in Jan 2017. The output of manufacturing at 101.5620 in Jan 2017 is 21.6 percent below trend under this alternative calculation.

Table I-12, US, Total Nonfarm Employment in Thousands

Year

Total Nonfarm

Year

Total Nonfarm

1980

90,533

2000

132,024

1981

91,297

2001

132,087

1982

89,689

2002

130,649

1983

90,295

2003

130,347

1984

94,548

2004

131,787

1985

97,532

2005

134,051

1986

99,500

2006

136,453

1987

102,116

2007

137,999

1988

105,378

2008

137,242

1989

108,051

2009

131,313

1990

109,527

2010

130,361

1991

108,427

2011

131,932

1992

108,802

2012

134,175

1993

110,935

2013

136,381

1994

114,398

2014

139,958

1995

117,407

2015

141,843

1996

119,836

2016

144,306

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

Chart I-43 provides annual nonfarm jobs from 2000 to 2016. Cyclically slow growth in the expansion since IIIQ2009 has not been sufficient to recover nonfarm jobs. Because of population growth, there are 6.549 million fewer nonfarm jobs in the US in 2016 than in 2007.

 

Chart I-43, US, Annual Nonfarm Jobs, NSA, Thousands, 2000-2016

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

Chart I-44 provides annual nonfarm jobs in the US from 1980 to 1995. Much more rapid cyclical growth as in other expansions historically allowed steady and rapid growth of nonfarm job opportunities even with similarly dynamic population growth.

 

Chart I-44, US, Annual Nonfarm Jobs, NSA, Thousands, 1980-1996

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

The highest average yearly percentage of unemployed to the labor force since 1940 was 14.6 percent in 1940 followed by 9.9 percent in 1941, 8.5 percent in 1975, 9.7 percent in 1982 and 9.6 percent in 1983 (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). The rate of unemployment remained at high levels in the 1930s, rising from 3.2 percent in 1929 to 22.9 percent in 1932 in one estimate and 23.6 percent in another with real wages increasing by 16.4 percent (Margo 1993, 43; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 214-5). There are alternative estimates of 17.2 percent or 9.5 percent for 1940 with real wages increasing by 44 percent. Employment declined sharply during the 1930s. The number of hours worked remained in 1939 at 29 percent below the level of 1929 (Cole and Ohanian 1999). Private hours worked fell in 1939 to 25 percent of the level in 1929. The policy of encouraging collusion through the National Industrial Recovery Act (NIRA), to maintain high prices, together with the National Labor Relations Act (NLRA), to maintain high wages, prevented the US economy from recovering employment levels until Roosevelt abandoned these policies toward the end of the 1930s (for review of the literature analyzing the Great Depression see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 198-217).

The Bureau of Labor Statistics (BLS) makes yearly revisions of its establishment survey (Harris 2011BA):

“With the release of data for January 2011, the Bureau of Labor Statistics (BLS) introduced its annual revision of national estimates of employment, hours, and earnings from the Current Employment Statistics (CES) monthly survey of nonfarm establishments.  Each year, the CES survey realigns its sample-based estimates to incorporate universe counts of employment—a process known as benchmarking.  Comprehensive counts of employment, or benchmarks, are derived primarily from unemployment insurance (UI) tax reports that nearly all employers are required to file with State Workforce Agencies.”

The number of not seasonally adjusted total private jobs in the US in Dec 2010 is 108.464 million, declining to 106.079 million in Jan 2011, or by 2.385 million, because of the adjustment of a different benchmark and not actual job losses. The not seasonally adjusted number of total private jobs in Dec 1984 is 80.250 million, declining to 78.704 million in Jan 1985, or by 1.546 million for the similar adjustment. Table I-13 attempts to measure job losses and gains in the recessions and expansions of 1981-1985 and 2007-2011. The final ten rows provide job creation from May 1983 to May 1984 and from May 2010 to May 2011, that is, at equivalent stages of the recovery from two comparable strong recessions. The row “Change ∆%” for May 1983 to May 1984 shows an increase of total nonfarm jobs by 4.9 percent and of 5.9 percent for total private jobs. The row “Change ∆%” for May 2010 to May 2011 shows an increase of total nonfarm jobs by 0.7 percent and of 1.7 percent for total private jobs. The last two rows of Table 7 provide a calculation of the number of jobs that would have been created from May 2010 to May 2011 if the rate of job creation had been the same as from May 1983 to May 1984. If total nonfarm jobs had grown between May 2010 and May 2011 by 4.9 percent, as between May 1983 and May 1984, 6.409 million jobs would have been created in the past 12 months for a difference of 5.457 million more total nonfarm jobs relative to 0.952 million jobs actually created. If total private jobs had grown between May 2010 and May 2011 by 5.9 percent as between May 1983 and May 1984, 6.337 million private jobs would have been created for a difference of 4.539 million more total private jobs relative to 1.798 million jobs actually created.

Table I-13, US, Total Nonfarm and Total Private Jobs Destroyed and Subsequently Created in Two Recessions IIIQ1981-IVQ1982 and IVQ2007-IIQ2009, Thousands and Percent

 

Total Nonfarm Jobs

Total Private Jobs

06/1981 #

92,288

75,969

11/1982 #

89,482

73,260

Change #

-2,806

-2,709

Change ∆%

-3.0

-3.6

12/1982 #

89,383

73,185

05/1984 #

94,471

78,049

Change #

5,088

4,864

Change ∆%

5.7

6.6

11/2007 #

139,090

116,291

05/2009 #

131,626

108,601

Change %

-7,464

-7,690

Change ∆%

-5.4

-6.6

12/2009 #

130,178

107,338

05/2011 #

131,753

108,494

Change #

1,575

1,156

Change ∆%

1.2

1.1

05/1983 #

90,005

73,667

05/1984 #

94,471

78,049

Change #

4,466

4,382

Change ∆%

4.9

5.9

05/2010 #

130,801

107,405

05/2011 #

131,753

109,203

Change #

952

1,798

Change ∆%

0.7

1.7

Change # by ∆% as in 05/1984 to 05/1985

6,409*

6,337**

Difference in Jobs that Would Have Been Created

5,457 =
6,409-952

4,539 =
6,337-1,798

*[(130,801x1.049)-130,801] = 6,409 thousand

**[(107,405)x1.059 – 107,405] = 6,337 thousand

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

IB Stagnating Real Wages. The wage bill is the product of average weekly hours times the earnings per hour. Table IB-1 provides the estimates by the Bureau of Labor Statistics (BLS) of earnings per hour seasonally adjusted, increasing from $25.38/hour in Feb 2016 to $26.09/hour in Feb 2017, or by 2.8 percent. There has been disappointment about the pace of wage increases because of rising food and energy costs that inhibit consumption and thus sales and similar concern about growth of consumption that accounts for about 68.9 percent of GDP (Table I-10 at https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html). Growth of consumption by decreasing savings by means of controlling interest rates in what is called financial repression may not be lasting and sound for personal finances (See Pelaez and Pelaez, Globalization and the State, Vol. II (2008c), 81-6, Pelaez (1975), https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/closely-monitoring-global-economic-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/dollar-revaluation-and-decreasing.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/dollar-revaluation-constraining.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/11/live-possibility-of-interest-rates.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/labor-market-uncertainty-and-interest.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html http://cmpassocregulationblog.blogspot.com/2015/08/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/dollar-devaluation-and-carry-trade.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/global-competitive-devaluation-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2015/02/job-creation-and-monetary-policy-twenty.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/valuations-of-risk-financial-assets.html http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/geopolitical-and-financial-risks.html and earlier http://cmpassocregulationblog.blogspot.com/2014/08/fluctuating-financial-valuations.html http://cmpassocregulationblog.blogspot.com/2014/06/financial-indecision-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/06/financial-instability-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-uncertainty-mediocre-cyclical.html

http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/collapse-of-united-states-dynamism-of.html http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html

http://cmpassocregulationblog.blogspot.com/2013/09/increasing-interest-rate-risk.html http://cmpassocregulationblog.blogspot.com/2013/08/risks-of-steepening-yield-curve-and.html http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html

http://cmpassocregulationblog.blogspot.com/2013/06/mediocre-united-states-economic-growth.html

http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states.html http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html http://cmpassocregulationblog.blogspot.com/2012/09/collapse-of-united-states-dynamism-of.html http://cmpassocregulationblog.blogspot.com/2012/07/recovery-without-jobs-stagnating-real.html http://cmpassocregulationblog.blogspot.com/2012/06/mediocre-recovery-without-jobs.html http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-economic-growth-falling-real.html http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html http://cmpassocregulationblog.blogspot.com/2012/01/mediocre-economic-growth-financial.html http://cmpassocregulationblog.blogspot.com/2011/12/slow-growth-falling-real-disposable.html http://cmpassocregulationblog.blogspot.com/2011/11/us-growth-standstill-falling-real.html http://cmpassocregulationblog.blogspot.com/2011/10/slow-growth-driven-by-reducing-savings.html). Average hourly earnings seasonally adjusted increased 2.8 percent from $25.38 in Feb 2016 to $26.09 in Feb 2017. Average private weekly earnings increased $21.89 from $875.61 in Feb 2016 to $897.50 in Feb 2017 or 2.5 percent and increased $2.07 from $895.43 in Jan 2017 to $897.50 in Feb 2017 or 0.2 percent. The inflation-adjusted wage bill can only be calculated for Jan, which is the most recent month for which there are estimates of the consumer price index. Earnings per hour (not-seasonally-adjusted (NSA)) rose from $25.50 in Jan 2016 to $26.35 in Jan 2017 or by 3.3 percent (http://www.bls.gov/data/; see Table IB-3 below). Data NSA are more suitable for comparison over a year. Average weekly hours NSA were 34.2 in Jan 2016 and 34.4 in Jan 2017 (http://www.bls.gov/data/; see Table IB-2 below). The wage bill increased 3.9 percent in the 12 months ending in Jan 2017:

{[(wage bill in Jan 2017)/(wage bill in Jan 2016)]-1}100 =

{[($26.35x34.4)/($25.50x34.2)]-1]}100

= {[($906.44)/($872.10)]-1}100 = 3.9%

CPI inflation was 2.5 percent in the 12 months ending in Jan 2017 (http://www.bls.gov/cpi/) for an inflation-adjusted wage-bill change of 1.4 percent :{[(1.039/1.025)-1]100 = 1.4%} (see Table IB-5 below for Dec 2016 with minor rounding difference). The wage bill for Feb 2017 before inflation adjustment increased 2.8 percent relative to the wage bill for Feb 2016:

{[(wage bill in Feb 2017)/(wage bill in Feb 2016)]-1}100 =

{[($26.20x34.1)/($25.49x34.1)]-1]}100

= {[$893.42)/$869.21]-1}100 = 2.8%}

Average hourly earnings increased 2.8 percent from Feb 2016 to Feb 2017 {[($26.20/$25.49) – 1]100 = 2.8%} while hours worked changed 0.0 percent {[(34.1/34.1) – 1]100 = 0.0%}. The increase of the wage bill is the product of the increase of hourly earnings of 2.8 percent and change of hours worked of 0.0 percent {[(1.028x1.00) -1]100 =2.8%} with small rounding error. Energy and food price increases are similar to a “silent tax” that is highly regressive, harming the most those with lowest incomes. There are concerns that the wage bill would deteriorate in purchasing power because of renewed raw materials shocks in the form of increases in prices of commodities such as the 31.1 percent steady increase in the DJ-UBS Commodity Index from Jul 2, 2010 to Sep 2, 2011. The charts of four commodity price indexes by Bloomberg show steady increase since Jul 2, 2010 that was interrupted briefly only in Nov 2010 with the sovereign issues in Europe triggered by Ireland; in Mar 2011 by the earthquake and tsunami in Japan; and in the beginning of May 2011 by the decline in oil prices and sovereign risk difficulties in Europe (http://www.bloomberg.com/markets/commodities/futures/). Renewed risk aversion because of the sovereign risks in Europe had reduced the rate of increase of the DJ UBS commodity index to 10.2 percent on May 2, 2014, relative to Jul 2, 2010 (see Table VI-4) but there has been a shift in investor preferences into equities. Inflation has been rising in waves with carry trades driven by zero interest rates to commodity futures during periods of risk appetite with interruptions during risk aversion (https://cmpassocregulationblog.blogspot.com/2017/02/world-inflation-waves-united-states.html). Inflation-adjusted wages fall sharply during carry trades from zero interest rates to long positions in commodity futures during periods of risk appetite.

Table IB-1, US, Earnings per Hour and Average Weekly Hours SA

Earnings per Hour

Feb 2016

Dec 2016

Jan 2017

Feb 2017

Total Private

$25.38

$25.98

$26.03

$26.09

Goods Producing

$26.54

$27.24

$27.30

$27.30

Service Providing

$25.10

$25.68

$25.73

$25.81

Average Weekly Earnings

       

Total Private

$875.61

$893.71

$895.43

$897.50

Goods Producing

$1,069.56

$1,095.05

$1,097.46

$1,100.19

Service Providing

$835.83

$855.14

$854.24

$856.89

Average Weekly Hours

       

Total Private

34.5

34.4

34.4

34.4

Goods Producing

40.3

40.2

40.2

40.3

Service Providing

33.3

33.3

33.2

33.2

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Average weekly hours in Table IB-2 fell from 34.8 in Dec 2007 at the beginning of the contraction to 33.7 in Jun 2009, which was the last month of the contraction. Average weekly hours rose to 34.4 in Dec 2011 and oscillated to 34.8 in Dec 2012 and 34.7 in Dec 2013. Average weekly hours of all employees decreased to 34.6 in Dec 2014 and 34.5 in Dec 2015. Average weekly hours stood at 34.3 in Dec 2016. Average weekly hours reached 34.1 in Feb 2017. The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available in the release for Jan 2016 and subsequent months.

Table IB-2, US, Average Weekly Hours of All Employees, NSA 2006-2017

Year

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

2006

   

34.0

34.4

34.1

34.5

34.7

34.5

34.3

34.7

34.3

34.4

 

2007

33.9

34.0

34.2

34.5

34.3

34.5

34.8

34.5

34.8

34.3

34.3

34.8

34.4

2008

34.0

34.0

34.6

34.2

34.2

34.8

34.3

34.5

34.2

34.2

34.4

33.9

34.3

2009

33.6

34.0

33.9

33.5

33.6

33.7

33.8

34.3

33.7

33.8

34.2

33.8

33.8

2010

33.7

33.6

33.8

34.0

34.4

34.1

34.2

34.7

34.1

34.3

34.2

34.2

34.1

2011

34.2

34.0

34.1

34.2

34.6

34.3

34.4

34.4

34.4

34.8

34.3

34.4

34.3

2012

34.5

34.2

34.2

34.6

34.2

34.4

34.7

34.5

34.8

34.3

34.3

34.8

34.5

2013

34.0

34.2

34.3

34.3

34.3

34.9

34.3

34.5

34.9

34.4

34.4

34.7

34.4

2014

34.0

34.4

34.7

34.4

34.4

34.9

34.5

34.6

34.5

34.5

34.9

34.6

34.5

2015

34.2

34.6

34.7

34.4

34.4

34.5

34.5

35.1

34.3

34.5

34.8

34.5

34.5

2016

34.2

34.1

34.2

34.3

34.6

34.4

34.4

34.4

34.4

34.8

34.3

34.3

34.4

2017

34.4

34.1

                     

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart IB-1 provides average weekly hours of all employees seasonally adjusted. There was sharp contract during the global recession. Hours returned to levels before the contraction.

 

Chart IB-1, US, Average Weekly Hours of All Employees, SA 2006-2017

Source: US Bureau of Labor Statistics

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

Calculations of inflation-adjusted average hourly earnings using BLS data are in Table IB-3. The final column of Table IB-3 (“12-Month Real ∆%”) provides inflation-adjusted average hourly earnings of all employees in the US. Average hourly earnings rose above inflation throughout the first nine months of 2007 just before the global recession that began in the final quarter of 2007 when average hourly earnings began to lose to inflation. In contrast, average hourly earnings of all US workers have risen less than inflation in four months in 2010 and in all but the first month in 2011 and the loss accelerated at 1.8 percent in Sep 2011, declining to a real loss of 1.1 percent in Feb 2012 and 0.6 percent in Mar 2012. There was a gain of 0.5 percent in Apr 2012 in inflation-adjusted average hourly earnings but another fall of 0.6 percent in May 2012 followed by increases of 0.3 percent in Jun and 1.0 percent in Jul 2012. Real hourly earnings stagnated in the 12 months ending in Aug 2012 with increase of only 0.1 percent, and increased 0.7 percent in the 12 months ending in Sep 2012. Real hourly earnings fell 1.3 percent in Oct 2012 and gained 1.0 percent in Dec 2012 but declined 0.2 percent in Jan 2013 and stagnated at change of 0.2 percent in Feb 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Mar 2013 and 0.2 percent in Apr 2013, increasing 0.7 percent in May 2013. In Jun 2013, real hourly earnings increased 1.0 percent relative to Jun 2012. Real hourly earnings fell 0.6 percent in the 12 months ending in Jul 2013 and increased 0.8 percent in the 12 months ending in Aug 2013. Real hourly earnings increased 1.2 percent in the 12 months ending in Oct 2013 and 1.0 percent in Nov 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Dec 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Jan 2014 and 1.7 percent in the 12 months ending in Feb 2014. Real hourly earnings increased 1.3 percent in the 12 months ending in Mar 2014. Real hourly earnings changed 0.0 percent in the 12 months ending in Apr 2014. Real hourly earnings stagnated at 0.0 percent in the 12 months ending in May 2014. Real hourly earnings changed 0.0 percent in the 12 months ending in Jun 2014. Real hourly earnings increased 0.1 percent in the 12 months ending in Jul 2014 and increased 0.5 percent in the 12 months ending in Aug 2014. Real hourly earnings fell 0.3 percent in the 12 months ending in Sep 2014 and increased 0.3 percent in the 12 months ending in Oct 2014. Real hourly earnings increased 1.5 percent in the 12 months ending in Nov 2014. Real hourly earnings increased 0.4 percent in the 12 months ending in Dec 2014 and increased 2.3 percent in the 12 months ending in Jan 2015. Real hourly earnings increased 1.9 percent in the 12 months ending in Feb 2015 and 2.3 percent in the 12 months ending in Mar 2015. Real hourly earnings increased 2.4 percent in the 12 months ending in Apr 2015 and increased 2.4 percent in the 12 months ending in May 2015. Real hourly earnings increased 1.3 percent in the 12 months ending in Jun 2015 and increased 1.9 percent in the 12 months ending in Jul 2015. Real hourly earnings increased 2.8 percent in the 12 months ending in Aug 2015 and increased 2.2 percent in the 12 months ending in Sep 2015. Real hourly earnings increased 2.3 percent in the 12 months ending in Oct 2015 and increased 1.9 percent in the 12 months ending in Nov 2015. Real hourly earnings increased 1.8 percent in the 12 months ending in Dec 2015 and increased 1.1 percent in the 12 months ending in Jan 2016. Real hourly earnings increased 0.8 percent in the 12 months ending in Feb 2016 and increased 0.9 percent in the 12 months ending in Mar 2016. Real hourly earnings increased 1.5 percent in the 12 months ending in Apr 2016 and increased 2.2 percent in the 12 months ending in May 2016. Real hourly earnings increased 1.6 percent in the 12 months ending in Jun 2016 and increased 2.0 percent in the 12 months ending in Jul 2016. Real hourly earnings increased 0.8 percent in the 12 months ending in Aug 2016 and increased 1.3 percent in the 12 months ending in Sep 2016. Real hourly earnings increased 2.0 percent in the 12 months ending in Oct 2016 and increased 0.2 percent in the 12 months ending in Nov 2016. Real hourly earnings increased 0.6 percent in the 12 months ending in Dec 2016 and increased 0.8 percent in the 12 months ending in Jan 2017. Real hourly earnings are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (https://cmpassocregulationblog.blogspot.com/2017/02/world-inflation-waves-united-states.html) and in part because of the collapse of hiring (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html) originating in weak economic growth (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available in the release for Jan 2016 and subsequent releases.

Table IB-3, US, Average Hourly Earnings Nominal and Inflation Adjusted, Dollars and % NSA

 

AHE ALL

12 Month-
Nominal
∆%

∆% 12 Month CPI

12-Month
Real ∆%

2007

       

Jan*

$20.69*

4.2*

2.1

2.1*

Feb*

$20.78*

4.1*

2.4

1.7*

Mar

$20.75

3.4

2.8

0.6

Apr

$20.99

3.1

2.6

0.5

May

$20.77

3.5

2.7

0.8

Jun

$20.77

3.6

2.7

0.9

Jul

$20.94

3.3

2.4

0.9

Aug

$20.80

3.3

2.0

1.3

Sep

$21.13

3.8

2.8

1.0

Oct

$21.01

2.4

3.5

-1.1

Nov

$21.07

3.1

4.3

-1.2

Dec

$21.30

3.4

4.1

-0.7

2010

       

Jan

$22.51

2.1

2.6

-0.5

Feb

$22.57

1.6

2.1

-0.5

Mar

$22.48

1.2

2.3

-1.1

Apr

$22.53

1.8

2.2

-0.4

May

$22.60

2.5

2.0

0.5

Jun

$22.34

1.7

1.1

0.6

Jul

$22.41

1.9

1.2

0.7

Aug

$22.55

1.8

1.1

0.7

Sep

$22.60

1.8

1.1

0.7

Oct

$22.70

1.9

1.2

0.7

Nov

$22.69

1.1

1.1

0.0

Dec

$22.76

1.7

1.5

0.2

2011

       

Jan

$23.16

2.9

1.6

1.3

Feb

$22.99

1.9

2.1

-0.2

Mar

$22.90

1.9

2.7

-0.8

Apr

$22.96

1.9

3.2

-1.3

May

$23.06

2.0

3.6

-1.5

Jun

$22.81

2.1

3.6

-1.4

Jul

$22.94

2.4

3.6

-1.2

Aug

$22.85

1.3

3.8

-2.4

Sep

$23.05

2.0

3.9

-1.8

Oct

$23.30

2.6

3.5

-0.9

Nov

$23.15

2.0

3.4

-1.4

Dec

$23.22

2.0

3.0

-1.0

2012

       

Jan

$23.56

1.7

2.9

-1.2

Feb

$23.40

1.8

2.9

-1.1

Mar

$23.39

2.1

2.7

-0.6

Apr

$23.61

2.8

2.3

0.5

May

$23.32

1.1

1.7

-0.6

Jun

$23.27

2.0

1.7

0.3

Jul

$23.48

2.4

1.4

1.0

Aug

$23.26

1.8

1.7

0.1

Sep

$23.67

2.7

2.0

0.7

Oct

$23.52

0.9

2.2

-1.3

Nov

$23.58

1.9

1.8

0.1

Dec

$23.85

2.7

1.7

1.0

2013

       

Jan

$23.88

1.4

1.6

-0.2

Feb

$23.90

2.1

2.0

0.2

Mar

$23.84

1.9

1.5

0.4

Apr

$23.92

1.3

1.1

0.2

May

$23.80

2.1

1.4

0.7

Jun

$23.92

2.8

1.8

1.0

Jul

$23.81

1.4

2.0

-0.6

Aug

$23.80

2.3

1.5

0.8

Sep

$24.16

2.1

1.2

0.9

Oct

$24.04

2.2

1.0

1.2

Nov

$24.11

2.2

1.2

1.0

Dec

$24.30

1.9

1.5

0.4

2014

       

Jan

$24.35

2.0

1.6

0.4

Feb

$24.58

2.8

1.1

1.7

Mar

$24.50

2.8

1.5

1.3

Apr

$24.40

2.0

2.0

0.0

May

$24.30

2.1

2.1

0.0

Jun

$24.42

2.1

2.1

0.0

Jul

$24.31

2.1

2.0

0.1

Aug

$24.32

2.2

1.7

0.5

Sep

$24.50

1.4

1.7

-0.3

Oct

$24.52

2.0

1.7

0.3

Nov

$24.78

2.8

1.3

1.5

Dec

$24.59

1.2

0.8

0.4

2015

       

Jan

$24.88

2.2

-0.1

2.3

Feb

$25.05

1.9

0.0

1.9

Mar

$25.04

2.2

-0.1

2.3

Apr

$24.94

2.2

-0.2

2.4

May

$24.88

2.4

0.0

2.4

Jun

$24.77

1.4

0.1

1.3

Jul

$24.83

2.1

0.2

1.9

Aug

$25.04

3.0

0.2

2.8

Sep

$25.05

2.2

0.0

2.2

Oct

$25.14

2.5

0.2

2.3

Nov

$25.38

2.4

0.5

1.9

Dec

$25.21

2.5

0.7

1.8

2016

       

Jan

$25.50

2.5

1.4

1.1

Feb

$25.49

1.8

1.0

0.8

Mar

$25.49

1.8

0.9

0.9

Apr

$25.60

2.6

1.1

1.5

May

$25.68

3.2

1.0

2.2

Jun

$25.42

2.6

1.0

1.6

Jul

$25.53

2.8

0.8

2.0

Aug

$25.52

1.9

1.1

0.8

Sep

$25.74

2.8

1.5

1.3

Oct

$26.04

3.6

1.6

2.0

Nov

$25.87

1.9

1.7

0.2

Dec

$25.90

2.7

2.1

0.6

2017

       

Jan

$26.35

3.3

2.5

0.8

Feb

$26.20

2.8

   

Note: AHE ALL: average hourly earnings of all employees; CPI: consumer price index; Real: adjusted by CPI inflation; NA: not available

*AHE of production and nonsupervisory employees because of unavailability of data for all employees for Jan-Feb 2006

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Calculations of inflation-adjusted average hourly earnings by the BLS are in Table IB-4. Average hourly earnings rose above inflation throughout the first nine months of 2007 just before the global recession that began in the final quarter of 2007 when average hourly earnings began to lose to inflation. In contrast, average hourly earnings of all US workers have risen less than inflation in five months in 2010 and in all but the first month in 2011 and the loss accelerated at 1.8 percent in Sep 2011, declining to a real loss of 1.1 percent in Feb 2012 and 0.5 percent in Mar 2012. There was a gain of 0.5 percent in Apr 2012 in inflation-adjusted average hourly earnings but another fall of 0.6 percent in May 2012 followed by increases of 0.3 percent in Jun and 1.0 percent in Jul 2012. Real hourly earnings stagnated in the 12 months ending in Aug 2012 with increase of only 0.1 percent, and increased 0.7 percent in the 12 months ending in Sep 2012. Real hourly earnings fell 1.2 percent in Oct 2012 and gained 1.0 percent in Dec 2012 but declined 0.2 percent in Jan 2013 and stagnated at change of 0.1 percent in Feb 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Mar 2013 and 0.3 percent in Apr 2013, increasing 0.7 percent in May 2013. In Jun 2013, real hourly earnings increased 1.0 percent relative to Jun 2012. Real hourly earnings fell 0.6 percent in the 12 months ending in Jul 2013 and increased 0.8 percent in the 12 months ending in Aug 2013. Real hourly earnings increased 1.2 percent in the 12 months ending in Oct 2013 and 1.0 percent in Nov 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Dec 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Jan 2014 and 1.7 percent in the 12 months ending in Feb 2014. Real hourly earnings increased 1.3 percent in the 12 months ending in Mar 2014. Real hourly changed 0.0 percent in the 12 months ending in Apr 2014. Real hourly decreased 0.1 percent in the 12 months ending in May 2014. Real hourly earnings increased 0.1 percent in the 12 months ending in Jun 2014. Real hourly earnings increased 0.1 percent in the 12 months ending in Jul 2014 and increased 0.4 percent in the 12 months ending in Aug 2014. Real hourly earnings fell 0.3 percent in the 12 months ending in Sep 2014 and increased 0.4 percent in the 12 months ending in Oct 2014. Real hourly earnings increased 1.5 percent in the 12 months ending in Nov 2014 and 0.4 percent in the 12 months ending in Dec 2014. Real hourly earnings increased 2.3 percent in the 12 months ending in Jan 2015 and increased 1.9 percent in the 12 months ending in Feb 2015. Real hourly earnings increased 2.2 percent in the 12 months ending in Mar 2015 and increased 2.4 percent in the 12 months ending in Apr 2015. Real hourly earnings increased 2.4 percent in the 12 months ending in May 2015 and 1.3 percent in the 12 months ending in Jun 2015. Real hourly earnings increased 2.0 percent in the 12 months ending in Jul 2015 and increased 2.8 percent in the 12 months ending in Aug 2015. Real hourly earnings increased 2.3 percent in the 12 months ending in Sep 2015. Real hourly earnings increased 2.3 percent in the 12 months ending in Oct 2015 and increased 1.9 percent in the 12 months ending in Nov 2015. Average hourly earnings increased 1.8 percent in the 12 months ending in Dec 2015 and increased 1.0 percent in the 12 months ending in Jan 2016. Real hourly earnings increased 0.7 percent in the 12 months ending in Feb 2016 and increased 0.9 percent in the 12 months ending in Mar 2016. Real hourly earnings increased 1.5 percent in the 12 months ending in Apr 2016 and increased 2.2 percent in the 12 months ending in May 2016. Real hourly earnings increased 1.6 percent in the 12 months ending in Jun 2016 and increased 2.0 percent in the 12 months ending in Jul 2016. Real hourly earnings increased 0.9 percent in the 12 months ending in Aug 2016 and increased 1.2 percent in the 12 months ending in Sep 2016. Real hourly earnings increased 1.9 percent in the 12 months ending in Oct 2016 and increased 0.3 percent in the 12 months ending in Nov 2016. Real hourly earnings increased 0.7 percent in the 12 months ending in Dec 2016 and increased 0.8 percent in the 12 months ending in Jan 2017. Real hourly earnings are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (https://cmpassocregulationblog.blogspot.com/2017/02/world-inflation-waves-united-states.html) and in part because of the collapse of hiring (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html) originating in weak economic growth (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available in the release for Jan 2016 and subsequent releases.

Table IB-4, US, Average Hourly Earnings of All Employees NSA in Constant Dollars of 1982-1984

Year

Jan

Aug

Sep

Oct

Nov

Dec

2006

 

9.87

10.03

10.16

10.14

10.21

2007

10.22

10.00

10.13

10.06

10.02

10.14

2008

10.09

9.81

9.91

10.03

10.34

10.45

2009

10.44

10.27

10.28

10.30

10.37

10.36

2010

10.39

10.33

10.35

10.38

10.37

10.38

2011

10.52

10.09

10.16

10.29

10.23

10.29

2012

10.39

10.10

10.23

10.17

10.24

10.39

∆%12M

-1.2

0.1

0.7

-1.2

0.1

1.0

2013

10.37

10.18

10.32

10.29

10.34

10.43

∆%12M

-0.2

0.8

0.9

1.2

1.0

0.4

2014

10.41

10.22

10.29

10.33

10.49

10.47

∆%12M

0.4

0.4

-0.3

0.4

1.5

0.4

2015

10.65

10.51

10.53

10.57

10.69

10.66

∆%12M

2.3

2.8

2.3

2.3

1.9

1.8

2016

10.76

10.60

10.66

10.77

10.72

10.73

∆%12M

1.0

0.9

1.2

1.9

0.3

0.7

2017

10.85

         

∆%12M

0.8

         

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart IB-2 of the US Bureau of Labor Statistics plots average hourly earnings of all US employees in constant 1982-1984 dollars with evident decline from annual earnings of $10.33 in 2009 and $10.35 in 2010 to $10.24 in 2011 and $10.23 in 2012 or loss of 1.0 percent (data in http://www.bls.gov/data/). Annual real hourly earnings increased 0.6 percent in 2013 relative to 2012 and increased 0.5 percent in 2014 relative to 2013. Annual real hourly earnings increased 2.1 percent in 2015 relative to 2014. Annual real hourly earnings increased 1.2 percent in 2016 relative to 2015. Annual real hourly earnings increased 5.9 percent from 2007 to 2016 at the rate of 0.6 percent per year. Annual real hourly earnings increased 3.5 percent from 2009 to 2016 at the rate of 0.5 percent per year and increased 6.8 percent from 2008 to 2016 at the rate of 0.8 percent per year. Real hourly earnings of US workers are crawling in a fractured labor market. The economic welfare or wellbeing of United States workers deteriorated in a recovery without hiring (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html), stagnating/declining real wages and 24.2 million unemployed or underemployed (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html) because of mediocre economic growth (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html).

The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available for the release of Jan 2016 and subsequent releases.

 

Chart IB-2, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2017

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

Chart IB-3 provides 12-month percentage changes of average hourly earnings of all employees in constant dollars of 1982-1984, that is, adjusted for inflation. There was sharp contraction of inflation-adjusted average hourly earnings of US employees during parts of 2007 and 2008. Rates of change in 12 months became positive in parts of 2009 and 2010 but then became negative again in 2011 and into 2012 with temporary increase in Apr 2012 that was reversed in May with another gain in Jun and Jul 2012 followed by stagnation in Aug 2012. There was marginal gain in Sep 2012 with sharp decline in Oct 2012, stagnation in Nov 2012, increase in Dec 2012 and renewed decrease in Jan 2013 with near stagnation in Feb 2013 followed by mild increase in Mar-Apr 2013. Hourly earnings adjusted for inflation increased in Jun 2013 and fell in Jul 2013, increasing in Aug-Dec 2013 and Jan-Mar 2014. Average hourly earnings stagnated in Apr-May 2014 and rebounded mildly in Jul 2014, increasing in Aug 2014 and Sep 2014. Average hourly earnings adjusted for inflation increased in Oct-Dec 2014, Jan-Dec 2015, Jan-Dec 2016 and Jan 2017.

 

Chart IB-3, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2017

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

Average weekly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are in Table IB-5. Average weekly earnings fell 3.2 percent after adjusting for inflation in the 12 months ending in Aug 2011, decreased 0.9 percent in the 12 months ending in Sep 2011 and increased 0.6 percent in the 12 months ending in Oct 2011. Average weekly earnings fell 1.0 percent in the 12 months ending in Nov 2011 and fell 0.3 percent in the 12 months ending in Dec 2011. Average weekly earnings declined 0.3 percent in the 12 months ending in Jan 2012 and fell 0.5 percent in the 12 months ending in Feb 2012. Average weekly earnings in constant dollars were virtually flat in Mar 2012 relative to Mar 2011, decreasing 0.2 percent. Average weekly earnings in constant dollars increased 1.7 percent in Apr 2012 relative to Apr 2011 but fell 1.7 percent in May 2012 relative to May 2011, increasing 0.6 percent in the 12 months ending in Jun 2012 and 1.8 percent in the 12 months ending in Jul 2012. Real weekly earnings increased 0.4 percent in the 12 months ending in Aug 2012 and 1.9 percent in the 12 months ending in Sep 2012. Real weekly earnings fell 2.6 percent in the 12 months ending in Oct 2012 and increased 0.1 percent in the 12 months ending in Nov 2012 and 2.1 percent in the 12 months ending in Dec 2012. Real weekly earnings fell 1.7 percent in the 12 months ending in Jan 2013 and virtually stagnated with gain of 0.2 percent in the 12 months ending in Feb 2013, increasing 0.7 percent in the 12 months ending in Mar 2013. Real weekly earnings fell 0.6 percent in the 12 months ending in Apr 2013 and increased 1.0 percent in the 12 months ending in May 2013. Average weekly earnings increased 2.5 percent in the 12 months ending in Jun 2013 and fell 1.7 percent in the 12 months ending in Jul 2013. Real weekly earnings increased 0.8 percent in the 12 months ending in Aug 2013, 1.2 percent in the 12 months ending in Sep 2013 and 1.5 percent in the 12 months ending in Oct 2013. Average weekly earnings increased 1.3 percent in the 12 months ending in Nov 2013 and increased 0.1 percent in the 12 months ending in Dec 2013. Average weekly earnings increased 0.4 percent in the 12 months ending in Jan 2014 and 2.3 percent in the 12 months ending in Feb 2014. Average weekly earnings increased 2.4 percent in the 12 months ending in Mar 2014 and 0.3 percent in the 12 months ending in Apr 2014. Average weekly earnings in constant dollars increased 0.3 percent in the 12 months ending in May 2014 and changed 0.0 percent in the 12 months ending in Jun 2014. Real average weekly earnings increased 0.7 percent in the 12 months ending in Jul 2014 and 0.8 percent in the 12 months ending in Aug 2014. Real weekly earnings decreased 1.4 percent in the 12 months ending in Sep 2014 and increased 0.6 percent in the 12 months ending in Oct 2014. Average weekly earnings increased 2.9 percent in the 12 months ending in Nov 2014 and increased 0.1 percent in the 12 months ending in Dec 2014. Average weekly earnings increased 2.9 percent in the 12 months ending in Jan 2015 and increased 2.5 percent in the 12 months ending in Feb 2015. Average weekly earnings adjusted for inflation increased 2.3 percent in the 12 months ending in Mar 2015 and increased 2.4 percent in the 12 months ending in Apr 2015. Average weekly earnings adjusted for inflation increased 2.4 percent in the 12 months ending in May 2015 and increased 0.1 percent in the 12 months ending in Jun 2015. Average weekly earnings increased 2.0 percent in the 12 months ending in Jul 2015 and 4.2 percent in the 12 months ending in Aug 2015. Average weekly earnings adjusted for inflation increased 1.7 percent in the 12 months ending in Sep 2015 and increased 2.4 percent in the 12 months ending in Oct 2015. Average weekly earnings adjusted for inflation increased 1.6 percent in the 12 months ending in Nov 2015 and increased 1.5 percent in the 12 months ending in Dec 2015. Average weekly earnings increased 1.1 percent in the 12 months ending in Jan 2016. Average weekly earnings contracted 0.7 percent in the 12 months ending in Feb 2015 and contracted 0.5 percent in the 12 months ending in Mar 2016. Average weekly earnings increased 1.2 percent in the 12 months ending in Apr 2016 and increased 2.8 percent in the 12 months ending in May 2016. Average weekly earnings increased 1.3 percent in the 12 months ending in Jun 2016 and increased 1.7 percent in the 12 months ending in Jul 2016. Average weekly earnings decreased 1.2 percent in the 12 months ending in Aug 2016 and increased 1.6 percent in the 12 months ending in Sep 2016. Average weekly earnings increased 2.8 percent in the 12 months ending in Oct 2016 and decreased 1.2 percent in the 12 months ending in Nov 2016. Average weekly earnings increased 0.1 percent in the 12 months ending in Dec 2016 and increased 1.4 percent in the 12 months ending in Jan 2017. Table I-5 confirms the trend of deterioration of purchasing power of average weekly earnings in 2011 and into 2013 with oscillations according to carry trades causing world inflation waves (http://cmpassocregulationblog.blogspot.com/2017/01/world-inflation-waves-united-states.html). On an annual basis, average weekly earnings in constant 1982-1984 dollars increased from $347.17 in 2007 to $354.15 in 2013, by 2.0 percent or at the average rate of 0.3 percent per year (data in http://www.bls.gov/data/). Annual average weekly earnings in constant dollars of $352.95 in 2010 fell 0.4 percent to $351.67 in 2012. Annual average weekly earnings increased from $347.17 in 2007 to $356.90 in 2014 or by 2.8 at the average rate of 0.4 percent. Annual average weekly earnings in constant increased from $347.17 in 2007 to $364.62 in 2015 by 5.0 percent at the average rate of 0.6 percent per year. Annual average weekly earnings in constant increased from $347.17 in 2007 to $367.30 in 2016 by 5.8 percent at the average rate of 0.6 percent per year. Those who still work bring back home a paycheck that buys fewer high-quality goods than a year earlier. The fractured US job market does not provide an opportunity for advancement as in past booms following recessions because of poor job creation with 24.2 million unemployed or underemployed (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html) in a recovery without hiring (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html) because of mediocre economic growth (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) available in the release for Jan 2016 and subsequent releases.

Table IB-5, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, NSA 2007-2017

Year

Jan

Aug

Sep

Oct

Nov

Dec

2006

 

340.60

344.02

352.68

347.94

351.16

2007

346.51

345.14

352.69

344.91

343.85

352.91

2008

342.93

338.41

338.90

342.99

355.78

354.11

2009

350.89

352.16

346.41

348.20

354.76

350.29

2010

350.09

358.43

352.80

356.00

354.66

355.14

2011

359.67

346.97

349.47

358.11

350.99

353.95

2012

358.60

348.33

355.96

348.76

351.31

361.49

∆%12M

-0.3

0.4

1.9

-2.6

0.1

2.1

2013

352.58

351.08

360.10

354.10

355.85

361.82

∆%12M

-1.7

0.8

1.2

1.5

1.3

0.1

2014

353.93

353.78

355.10

356.29

366.21

362.34

∆%12M

0.4

0.8

-1.4

0.6

2.9

0.1

2015

364.09

368.80

361.10

364.67

372.14

367.72

∆%12M

2.9

4.2

1.7

2.4

1.6

1.5

2016

368.11

364.50

366.76

374.88

367.65

367.96

∆%12M

1.1

-1.2

1.6

2.8

-1.2

0.1

2017

373.27

         

∆%12M

1.4

         

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

Chart IB-4 provides average weekly earnings of all employees in constant dollars of 1982-1984. The same pattern emerges of sharp decline during the contraction, followed by recovery in the expansion and continuing fall with oscillations caused by carry trades from zero interest rates into commodity futures from 2010 to 2011 and into 2012-2017. The increase in the final segment is mostly because of collapse of commodity prices in reversals of carry trade exposures followed by reversal of carry trades and new decreases/stability. The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) available for the release of Jan 2016 and subsequent releases.

 

Chart IB-4, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2017

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

Chart IB-5 provides 12-month percentage changes of average weekly earnings of all employees in the US in constant dollars of 1982-1984. The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) available for the release of Jan 2016 and subsequent releases. There is the same pattern of contraction during the global recession in 2008 and then again weakness in the recovery without hiring and inflation waves. (https://cmpassocregulationblog.blogspot.com/2017/02/world-inflation-waves-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/world-inflation-waves-united-states.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/12/of-course-economic-outlook-is-highly.html and earlier http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/dollar-revaluation-world-inflation.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-volatility-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/interest-rate-policy-uncertainty-and.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/oscillating-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/most-fomc-participants-judged-that-if.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/contracting-united-states-industrial.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/monetary-policy-and-competitive.html and earlier http://cmpassocregulationblog.blogspot.com/2016/02/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/uncertainty-of-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-interest-rates-with-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-liftoff-followed-by.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/interest-rate-policy-quagmire-world.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-increase-on-hold-because.html http://cmpassocregulationblog.blogspot.com/2015/08/global-decline-of-values-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html http://cmpassocregulationblog.blogspot.com/2015/05/interest-rate-policy-and-dollar.html http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html http://cmpassocregulationblog.blogspot.com/2015/03/dollar-revaluation-and-financial-risk.html http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html http://cmpassocregulationblog.blogspot.com/2015/01/competitive-currency-conflicts-world.html http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html http://cmpassocregulationblog.blogspot.com/2014/10/financial-oscillations-world-inflation.html http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html http://cmpassocregulationblog.blogspot.com/2014/08/monetary-policy-world-inflation-waves.html http://cmpassocregulationblog.blogspot.com/2014/07/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2014/06/valuation-risks-world-inflation-waves.html http://cmpassocregulationblog.blogspot.com/2014/05/world-inflation-waves-squeeze-of.html http://cmpassocregulationblog.blogspot.com/2014/04/imf-view-world-inflation-waves-squeeze.html http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html http://cmpassocregulationblog.blogspot.com/2014/01/world-inflation-waves-interest-rate.html http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html

http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-zero-interest-rates-world.html http://cmpassocregulationblog.blogspot.com/2013/10/world-inflation-waves-regional-economic.html http://cmpassocregulationblog.blogspot.com/2013/08/duration-dumping-and-peaking-valuations.html http://cmpassocregulationblog.blogspot.com/2013/07/tapering-quantitative-easing-policy-and.html

http://cmpassocregulationblog.blogspot.com/2013/06/paring-quantitative-easing-policy-and.html http://cmpassocregulationblog.blogspot.com/2013/05/word-inflation-waves-squeeze-of.html http://cmpassocregulationblog.blogspot.com/2013/04/world-inflation-waves-squeeze-of.html http://cmpassocregulationblog.blogspot.com/2013/04/recovery-without-hiring-ten-million.html http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html http://cmpassocregulationblog.blogspot.com/2013/02/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html http://cmpassocregulationblog.blogspot.com/2012/11/united-states-unsustainable-fiscal.html http://cmpassocregulationblog.blogspot.com/2012/09/recovery-without-hiring-world-inflation.html http://cmpassocregulationblog.blogspot.com/2012_09_01_archive.html http://cmpassocregulationblog.blogspot.com/2012/07/world-inflation-waves-financial.html http://cmpassocregulationblog.blogspot.com/2012/06/destruction-of-three-trillion-dollars.html http://cmpassocregulationblog.blogspot.com/2012/05/world-inflation-waves-monetary-policy.html http://cmpassocregulationblog.blogspot.com/2012/06/recovery-without-hiring-continuance-of.html http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html http://cmpassocregulationblog.blogspot.com/2012/03/global-financial-and-economic-risk.html http://cmpassocregulationblog.blogspot.com/2012/02/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/01/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/01/recovery-without-hiring-united-states.html

http://cmpassocregulationblog.blogspot.com/2012/09/recovery-without-hiring-world-inflation.html http://cmpassocregulationblog.blogspot.com/2012_09_01_archive.html http://cmpassocregulationblog.blogspot.com/2012/07/world-inflation-waves-financial.html http://cmpassocregulationblog.blogspot.com/2012/05/world-inflation-waves-monetary-policy.html http://cmpassocregulationblog.blogspot.com/2012/06/recovery-without-hiring-continuance-of.html http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html http://cmpassocregulationblog.blogspot.com/2012/03/global-financial-and-economic-risk.html http://cmpassocregulationblog.blogspot.com/2012/02/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/01/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/01/recovery-without-hiring-united-states.html).

 

Chart IB-5, US, Average Weekly Earnings of All Employees NSA in Constant Dollars of 1982-1984 12-Month Percent Change, NSA 2007-2017

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

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 (https://cmpassocregulationblog.blogspot.com/2017/02/world-inflation-waves-united-states.html). The Census Bureau revised data for 2016, 2015, 2014 and 2013. Exports increased 0.6 percent in Jan 2017 while imports increased 2.3 percent. The trade deficit increased from $44,259 million in Dec 2016 to $48,492 million in Jan 2017. The trade deficit deteriorated to $48,189 million in Mar 2015. The trade deficit improved to $40,885 million in Apr 2015 and $40,170 million in May 2015. The trade deficit deteriorated to $42,973 million in Jun 2015 and improved to $39,900 million in Jul 2015, deteriorating to $44,639 million in Aug 2015. The trade deficit improved to $41,072 million in Sep 2015, deteriorating to $41,600 million in Oct 2015 and improving to $41,122 million in Nov 2015. The trade deficit deteriorated to $45,588 million in Mar 2016, improving to $37,259 million in Mar 2016. The trade deficit deteriorated to $38,544 million in Apr 2016, deteriorating to $42,189 million in May 2016 and $45,073 million in Jun 2016. The trade deficit improved to $39,691 million in Jul 2016, deteriorating to $40,513 million in Aug 2016. The trade deficit improved to $36,026 million in Sep 2016, deteriorating to $42,577 million in Oct 2016. The trade deficit deteriorated to $45,484 million in Nov 2016, improving to $44,259 million in Dec 2016. The trade deficit deteriorated to $48,492 million in Jan 2017.

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

 

Trade Balance

Exports

Month ∆%

Imports

Month ∆%

Jan 2017

-48,492

192,094

0.6

240,586

2.3

Dec 2016

-44,259

191,014

2.7

235,273

1.5

Nov

-45,484

185,995

-0.2

231,478

1.1

Oct

-42,577

186,398

-2.0

228,975

1.2

Sep

-36,026

190,210

1.0

226,236

-1.1

Aug

-40,513

188,326

0.9

228,839

1.2

Jul

39,691

186,444

2.0

226,134

-0.7

Jun

-45,073

182,723

0.8

227,796

1.9

May

-42,189

181,297

-0.2

223,485

1.5

Apr

-38,544

181,570

1.7

220,115

2.0

Mar

-37,259

178,543

-1.2

215,802

-4.7

Feb

-45,588

180,747

1.1

226,336

1.9

Jan

-43,356

178,813

-2.3

222,170

-1.1

Dec 2015

-41,487

183,074

-0.3

224,561

-0.1

Nov

-41,122

183,576

-1.1

224,698

-1.1

Oct

-41,600

185,587

-1.0

227,186

-0.6

Sep

-41,072

187,550

0.5

228,622

-1.1

Aug

-44,639

186,620

-1.8

231,259

0.5

Jul

-39,900

190,106

-0.1

230,006

-1.4

Jun

-42,973

190,347

0.0

233,320

1.2

May

-40,170

190,361

-0.7

230,531

-0.9

Apr

-40,885

191,675

0.6

232,560

-2.5

Mar

-48,189

190,448

0.3

238,637

5.5

Feb

-36,268

189,852

-1.1

226,121

-3.4

Jan

-42,057

191,968

-2.8

234,024

-3.0

Jan-Dec 2016

-500,560

2,212,079

-2.2

2,712,639

-1.8

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

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

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

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

 

Balance

∆%

Exports

∆%

Imports

∆%

1960

4,608

(X)

19,626

(X)

15,018

(X)

1961

5,476

18.8

20,190

2.9

14,714

-2.0

1962

4,583

-16.3

20,973

3.9

16,390

11.4

1963

5,289

15.4

22,427

6.9

17,138

4.6

1964

7,006

32.5

25,690

14.5

18,684

9.0

1965

5,333

-23.9

26,699

3.9

21,366

14.4

1966

3,837

-28.1

29,379

10.0

25,542

19.5

1967

4,122

7.4

30,934

5.3

26,812

5.0

1968

837

-79.7

34,063

10.1

33,226

23.9

1969

1,289

54.0

37,332

9.6

36,043

8.5

1970

3,224

150.1

43,176

15.7

39,952

10.8

1971

-1,476

-145.8

44,087

2.1

45,563

14.0

1972

-5,729

288.1

49,854

13.1

55,583

22.0

1973

2,389

-141.7

71,865

44.2

69,476

25.0

1974

-3,884

-262.6

99,437

38.4

103,321

48.7

1975

9,551

-345.9

108,856

9.5

99,305

-3.9

1976

-7,820

-181.9

116,794

7.3

124,614

25.5

1977

-28,352

262.6

123,182

5.5

151,534

21.6

1978

-30,205

6.5

145,847

18.4

176,052

16.2

1979

-23,922

-20.8

186,363

27.8

210,285

19.4

1980

-19,696

-17.7

225,566

21.0

245,262

16.6

1981

-22,267

13.1

238,715

5.8

260,982

6.4

1982

-27,510

23.5

216,442

-9.3

243,952

-6.5

1983

-52,409

90.5

205,639

-5.0

258,048

5.8

1984

-106,702

103.6

223,976

8.9

330,678

28.1

1985

-117,711

10.3

218,815

-2.3

336,526

1.8

1986

-138,279

17.5

227,159

3.8

365,438

8.6

1987

-152,119

10.0

254,122

11.9

406,241

11.2

1988

-118,526

-22.1

322,426

26.9

440,952

8.5

1989

-109,399

-7.7

363,812

12.8

473,211

7.3

1990

-101,719

-7.0

393,592

8.2

495,311

4.7

1991

-66,723

-34.4

421,730

7.1

488,453

-1.4

1992

-84,501

26.6

448,164

6.3

532,665

9.1

1993

-115,568

36.8

465,091

3.8

580,659

9.0

1994

-150,630

30.3

512,626

10.2

663,256

14.2

1995

-158,801

5.4

584,742

14.1

743,543

12.1

1996

-170,214

7.2

625,075

6.9

795,289

7.0

1997

-180,522

6.1

689,182

10.3

869,704

9.4

1998

-229,758

27.3

682,138

-1.0

911,896

4.9

1999

-328,821

43.1

695,797

2.0

1,024,618

12.4

2000

-436,104

32.6

781,918

12.4

1,218,022

18.9

2001

-411,899

-5.6

729,100

-6.8

1,140,999

-6.3

2002

-468,263

13.7

693,103

-4.9

1,161,366

1.8

2003

-532,350

13.7

724,771

4.6

1,257,121

8.2

2004

-654,830

23.0

814,875

12.4

1,469,704

16.9

2005

-772,373

18.0

901,082

10.6

1,673,455

13.9

2006

-827,971

7.2

1,025,967

13.9

1,853,938

10.8

2007

-808,763

-2.3

1,148,199

11.9

1,956,962

5.6

2008

-816,199

0.9

1,287,442

12.1

2,103,641

7.5

2009

-503,582

-38.3

1,056,043

-18.0

1,559,625

-25.9

2010

-635,362

26.2

1,278,495

21.1

1,913,857

22.7

2011

-725,447

14.2

1,482,508

16.0

2,207,954

15.4

2012

-730,446

0.7

1,545,821

4.3

2,276,267

3.1

2013

-689,470

-5.6

1,578,517

2.1

2,267,987

-0.4

2014

-735,194

6.6

1,621,172

2.7

2,356,366

3.9

2015

-745,660

1.4

1,502,572

-7.3

2,248,232

-4.6

2016

-734,316

-1.5

1,454,624

-3.2

2,188,940

-2.6

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 2.1 percent during the expansion beginning since IIIQ2009 does not deteriorate further the trade balance. Higher rates of growth may cause sharper deterioration.

 

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

Source: US Census Bureau

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 2016. The trade balance deteriorated sharply over the long term. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US not seasonally adjusted decreased from $137.2 billion in IIIQ2015 to $133.2 billion in IIIQ2016 (http://www.bea.gov/international/index.htm). The current account deficit seasonally adjusted at annual rate increased from 2.7 percent of GDP in IIIQ2015 to 2.6 percent of GDP in IIQ2016, decreasing to 2.4 percent of GDP in IIIQ2016 (http://www.bea.gov/international/index.htm http://www.bea.gov/iTable/index_nipa.cfm). The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71). The final rows of Table IIA-2B show marginal improvement of the trade deficit from $548,625 million in 2011 to lower $536,773 million in 2012 with exports growing 4.3 percent and imports 3.0 percent. The trade balance improved further to deficit of $461,876 million in 2013 with growth of exports of 3.4 percent while imports virtually stagnated. The trade deficit deteriorated in 2014 to $490,176 million in 2014 with growth of exports of 3.6 percent and of imports of 4.0 percent. The trade deficit deteriorated in 2015 to $500,361 million with decrease of exports of 4.9 percent and decrease of imports of 3.7 percent. The trade deficit deteriorated in 2016 to $502,252 million with decrease of exports of 2.3 percent and decrease of imports of 1.8 percent. Growth and commodity shocks under alternating inflation waves (https://cmpassocregulationblog.blogspot.com/2017/02/world-inflation-waves-united-states.html) have deteriorated the trade deficit from the low of $383,774 million in 2009.

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

 

Balance

Exports

∆%

Imports

∆%

1960

3,508

25,940

NA

22,432

NA

1961

4,195

26,403

1.8

22,208

-1.0

1962

3,370

27,722

5.0

24,352

9.7

1963

4,210

29,620

6.8

25,410

4.3

1964

6,022

33,341

12.6

27,319

7.5

1965

4,664

35,285

5.8

30,621

12.1

1966

2,939

38,926

10.3

35,987

17.5

1967

2,604

41,333

6.2

38,729

7.6

1968

250

45,543

10.2

45,293

16.9

1969

91

49,220

8.1

49,129

8.5

1970

2,254

56,640

15.1

54,386

10.7

1971

-1,302

59,677

5.4

60,979

12.1

1972

-5,443

67,222

12.6

72,665

19.2

1973

1,900

91,242

35.7

89,342

23.0

1974

-4,293

120,897

32.5

125,190

40.1

1975

12,404

132,585

9.7

120,181

-4.0

1976

-6,082

142,716

7.6

148,798

23.8

1977

-27,246

152,301

6.7

179,547

20.7

1978

-29,763

178,428

17.2

208,191

16.0

1979

-24,565

224,131

25.6

248,696

19.5

1980

-19,407

271,834

21.3

291,241

17.1

1981

-16,172

294,398

8.3

310,570

6.6

1982

-24,156

275,236

-6.5

299,391

-3.6

1983

-57,767

266,106

-3.3

323,874

8.2

1984

-109,072

291,094

9.4

400,166

23.6

1985

-121,880

289,070

-0.7

410,950

2.7

1986

-138,538

310,033

7.3

448,572

9.2

1987

-151,684

348,869

12.5

500,552

11.6

1988

-114,566

431,149

23.6

545,715

9.0

1989

-93,141

487,003

13.0

580,144

6.3

1990

-80,864

535,233

9.9

616,097

6.2

1991

-31,135

578,344

8.1

609,479

-1.1

1992

-39,212

616,882

6.7

656,094

7.6

1993

-70,311

642,863

4.2

713,174

8.7

1994

-98,493

703,254

9.4

801,747

12.4

1995

-96,384

794,387

13.0

890,771

11.1

1996

-104,065

851,602

7.2

955,667

7.3

1997

-108,273

934,453

9.7

1,042,726

9.1

1998

-166,140

933,174

-0.1

1,099,314

5.4

1999

-258,617

969,867

3.9

1,228,485

11.8

2000

-372,517

1,075,321

10.9

1,447,837

17.9

2001

-361,511

1,005,654

-6.5

1,367,165

-5.6

2002

-418,955

978,706

-2.7

1,397,660

2.2

2003

-493,890

1,020,418

4.3

1,514,308

8.3

2004

-609,883

1,161,549

13.8

1,771,433

17.0

2005

-714,245

1,286,022

10.7

2,000,267

12.9

2006

-761,716

1,457,642

13.3

2,219,358

11.0

2007

-705,375

1,653,548

13.4

2,358,922

6.3

2008

-708,726

1,841,612

11.4

2,550,339

8.1

2009

-383,774

1,583,053

-14.0

1,966,827

-22.9

2010

-494,658

1,853,606

17.1

2,348,263

19.4

2011

-548,625

2,127,021

14.8

2,675,646

13.9

2012

-536,773

2,218,989

4.3

2,755,762

3.0

2013

-461,876

2,293,457

3.4

2,755,334

0.0

2014

-490,176

2,376,577

3.6

2,866,754

4.0

2015

-500,361

2,261,163

-4.9

2,761,525

-3.7

2016

-502,252

2,209,418

-2.3

2,711,671

-1.8

Source: US Census Bureau

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

Chart IIA-2 of the US Census Bureau provides the US trade account in goods and services SA from Jan 1992 to Jan 2017. There is long-term trend of deterioration of the US trade deficit shown vividly by Chart IIA-2. The global recession from IVQ2007 to IIQ2009 reversed the trend of deterioration. Deterioration resumed together with incomplete recovery and was influenced significantly by the carry trade from zero interest rates to commodity futures exposures (these arguments are elaborated in Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4 http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html). Earlier research focused on the long-term external imbalance of the US in the form of trade and current account deficits (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). US external imbalances have not been fully resolved and tend to widen together with improving world economic activity and commodity price shocks. There are additional effects for revaluation of the dollar with the Fed orienting interest rate increases while the European Central Bank and the Bank of Japan determine negative nominal interest rates.

 

Chart IIA-2, US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-Jan 2017

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 Jan 2017. There was sharp acceleration from 2003 to 2007 during worldwide economic boom and increasing inflation. Exports fell sharply during the financial crisis and global recession from IVQ2007 to IIQ2009. Growth picked up again together with world trade and inflation but stalled in the final segment with less rapid global growth and inflation.

 

Chart IIA-3, US, Exports SA, Monthly, Millions of Dollars Jan 1992-Jan 2017

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 Jan 2017. Growth was stronger between 2003 and 2007 with worldwide economic boom and inflation. There was sharp drop during the financial crisis and global recession. There is stalling import levels in the final segment resulting from weaker world economic growth and diminishing inflation because of risk aversion and portfolio reallocations from commodity exposures to equities.

 

Chart IIA-4, US, Imports SA, Monthly, Millions of Dollars Jan 1992-Jan 2017

Source: US Census Bureau

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

There is deterioration of the US trade balance in goods in Table IIA-3 from deficit of $64,071 million in Jan 2016 to deficit of $69,684 million in Jan 2017. The nonpetroleum deficit increased by $3153 million while the petroleum deficit increased $2738 million. Total exports of goods increased 9.4 percent in Jan 2017 relative to a year earlier while total imports increased 9.2 percent. Nonpetroleum exports increased 7.0 percent from Jan 2016 to Jan 2017 while nonpetroleum imports increased 6.5 percent. Petroleum imports increased 48.1 percent.

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

 

Jan 2017

Jan 2016

∆%

Total Balance

-69,684

-64,071

 

Petroleum

-7,557

-4,819

 

Non Petroleum

-61,282

-58,129

 

Total Exports

127,954

116,977

9.4

Petroleum

9,317

6,575

41.7

Non Petroleum

117,625

109,908

7.0

Total Imports

197,638

181,048

9.2

Petroleum

16,874

11,394

48.1

Non Petroleum

178,906

168,037

6.5

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 2017 and Jan 2016 are in Table IIA-4. The rate of growth of exports was minus 3.2 percent and minus 2.6 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that increased 22.3 percent and of mineral fuels that increased 53.6 percent both because prices of raw materials and commodities increase and fall recurrently as a result of shocks of risk aversion and portfolio reallocations. The US exports an insignificant but growing amount of crude oil, increasing 37.0 percent in cumulative Jan 2017 relative to a year earlier. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports increased 4.9 percent while manufactured imports increased 9.6 percent. Significant part of the US trade imbalance originates in imports of mineral fuels decreasing 51.0 percent and petroleum increasing 52.8 percent with wide oscillations in oil prices. The limited hedge in exports of agricultural commodities and mineral fuels compared with substantial imports of mineral fuels and crude oil results in waves of deterioration of the terms of trade of the US, or export prices relative to import prices, originating in commodity price increases caused by carry trades from zero interest rates. These waves are similar to those in worldwide inflation.

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

 

Jan 2017 $ Millions

Jan 2016 $ Millions

∆%

Exports

117,711

108,273

8.7

Manufactured

83,085

79,230

4.9

Agricultural
Commodities

12,350

10,099

22.3

Mineral Fuels

10,321

6,719

53.6

Petroleum

7,552

5,513

37.0

Imports

185,841

165,873

12.0

Manufactured

158,622

144,666

9.6

Agricultural
Commodities

10,080

10,099

-0.2

Mineral Fuels

17,077

11,312

51.0

Petroleum

15,713

10,281

52.8

Source: US Census Bureau

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

The current account of the US balance of payments is in Table VI-3A for IIIQ2015 and IIIQ2016. The Bureau of Economic Analysis analyzes as follows (https://www.bea.gov/newsreleases/international/transactions/2016/pdf/trans316.pdf):

“The U.S. current account deficit decreased to $113.0 billion (preliminary) in the third quarter of 2016 from $118.3 billion (revised) in the second quarter of 2016, according to statistics released by the Bureau of Economic Analysis (BEA). The deficit decreased to 2.4 percent of current-dollar gross domestic product (GDP) from 2.6 percent in the second quarter.

The $5.3 billion decrease in the current account deficit reflected a $9.0 billion decrease in the deficit on goods that was partly offset by changes in the balances on secondary income, primary income, and services.”

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 $137.2 billion in IIIQ2015 to $133.2 billion in IIIQ2016. The current account deficit seasonally adjusted at annual rate increased from 2.7 percent of GDP in IIIQ2015 to 2.6 percent of GDP in IIQ2016, decreasing to 2.4 percent of GDP in IIIQ2016. 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 VI-3A, US, Balance of Payments, Millions of Dollars NSA

 

IIIQ2015

IIIQ2016

Difference

Goods Balance

-207,992

-201,707

6,285

X Goods

373,337

365,767

-2.0 ∆%

M Goods

-581,329

-567,474

-2.4 ∆%

Services Balance

68,913

66,231

-2,682

X Services

194,854

196,008

0.6 ∆%

M Services

-125,941

-129,777

3.0 ∆%

Balance Goods and Services

-139,079

-135,476

3,603

Exports of Goods and Services and Income Receipts

798,193

799,083

 

Imports of Goods and Services and Income Payments

-935,400

-932,272

 

Current Account Balance

-137,207

-133,188

-4,019

% GDP

IIIQ2015

IIIQ2016

IIQ2016

 

2.7

2.4

2.6

X: exports; M: imports

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

Source: Bureau of Economic Analysis

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

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

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

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

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

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

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

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

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

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

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

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

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

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

(Mt + Bt)/Pt = Et∫(1/Rt, t+τ)stdτ (4)

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

MtV(it, ·) = PtYt (5)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Table IIA2-3 provides data on the US fiscal and balance of payments imbalances incorporating all revisions and methods. In 2007, the federal deficit of the US was $161 billion corresponding to 1.1 percent of GDP while the Congressional Budget Office estimates the federal deficit in 2012 at $1087 billion or 6.8 percent of GDP. The estimate of the deficit for 2013 is $680 billion or 4.1 percent of GDP. The combined record federal deficits of the US from 2009 to 2012 are $5094 billion or 31.6 percent of the estimate of GDP for fiscal year 2012 implicit in the CBO (CBO 2013Sep11) estimate of debt/GDP. The deficits from 2009 to 2012 exceed one trillion dollars per year, adding to $5.094 trillion in four years, using the fiscal year deficit of $1087 billion for fiscal year 2012, which is the worst fiscal performance since World War II. Federal debt in 2007 was $5035 billion, slightly less than the combined deficits from 2009 to 2012 of $5094 billion. Federal debt in 2012 was 70.4 percent of GDP (CBO 2015Jan26) and 72.6 percent of GDP in 2013 (http://www.cbo.gov/). This situation may worsen in the future (CBO 2013Sep17):

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

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

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

The most recent CBO long-term budget on Jul 12, 2016, projects US federal debt at 141.1 percent of GDP in 2046 (Congressional Budget Office, The 2016 long-term budget outlook. Washington, DC, Jul 12 https://www.cbo.gov/publication/51580).

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

 

2007

2008

2009

2010

2011

Goods &
Services

-705

-709

-384

-495

-549

Primary Income

101

146

124

178

221

Secondary Income

-114

-128

-124

-125

-133

Current Account

-719

-691

-384

-442

-460

NGDP

14478

14719

14419

14964

15518

Current Account % GDP

-5.0

-4.7

-2.7

-3.0

-3.0

NIIP

-1279

-3995

-2628

-2512

-4455

US Owned Assets Abroad

20705

19423

19426

21767

22209

Foreign Owned Assets in US

21984

23418

22054

24279

26664

NIIP % GDP

-8.8

-27.1

-18.2

-16.8

-28.7

Exports
Goods,
Services and
Income

2569

2751

2286

2631

2988

NIIP %
Exports
Goods,
Services and
Income

-50

-145

-115

-95

-149

DIA MV

5858

3707

4945

5486

5215

DIUS MV

4134

3091

3619

4099

4199

Fiscal Balance

-161

-459

-1413

-1294

-1300

Fiscal Balance % GDP

-1.1

-3.1

-9.8

-8.7

-8.5

Federal   Debt

5035

5803

7545

9019

10128

Federal Debt % GDP

35.2

39.3

52.3

60.9

65.9

Federal Outlays

2729

2983

3518

3457

3603

∆%

2.8

9.3

17.9

-1.7

4.2

% GDP

19.1

20.2

24.4

23.4

23.4

Federal Revenue

2568

2524

2105

2163

2303

∆%

6.7

-1.7

-16.6

2.7

6.5

% GDP

17.9

17.1

14.6

14.6

15.0

 

2012

2013

2014

2015

Goods &
Services

-538

-462

-490

-500

Primary Income

216

219

224

182

Secondary Income

-126

-124

-126

-145

Current Account

-447

-366

-392

-463

NGDP

16155

16692

17393

18037

Current Account % GDP

-2.8

-2.2

-2.3

-2.6

NIIP

-4518

-5373

-7046

-7281

US Owned Assets Abroad

22562

24145

24718

23341

Foreign Owned Assets in US

27080

29517

31764

30621

NIIP % GDP

-28.0

-32.2

-40.5

-40.4

Exports
Goods,
Services and
Income

3097

3215

3339

3173

NIIP %
Exports
Goods,
Services and
Income

-146

-167

-211

-229

DIA MV

5969

7121

7133

6978

DIUS MV

4662

5815

6350

6544

Fiscal Balance

-1087

-680

-485

-438

Fiscal Balance % GDP

-6.8

-4.1

-2.8

-2.5

Federal   Debt

11281

11983

12780

13117

Federal Debt % GDP

70.4

72.6

74.4

73.6

Federal Outlays

3537

3455

3506

3688

∆%

-1.8

-2.3

1.5

5.2

% GDP

22.1

20.9

20.4

20.7

Federal Revenue

2450

2775

3022

3250

∆%

6.4

13.3

8.9

7.6

% GDP

15.3

16.8

17.6

18.2

Sources: 

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

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

https://www.cbo.gov/about/products/budget_economic_data#3 https://www.cbo.gov/about/products/budget_economic_data#2 Balance of Payments and NIIP http://www.bea.gov/international/index.htm#bop Gross Domestic Product, Bureau of Economic Analysis (BEA) http://www.bea.gov/iTable/index_nipa.cfm

Table VI-3C provides quarterly estimates NSA of the external imbalance of the United States. The current account deficit seasonally adjusted decreases from 2.7 percent of GDP in IIIQ2015 to 2.5 percent in IVQ2015. The current account deficit increases to 2.9 percent of GDP in IQ2016. The deficit decreases to 2.6 percent in IIQ2016 and decreases to 2.4 percent in IIIQ2016. The net international investment position increases from minus $7.2 trillion in IIIQ2015 to minus $7.3 trillion in IVQ2015, increasing at minus $7.6 trillion in IQ2016. The net international investment position increases to minus $8.0 trillion in IIQ2016 and decreases to minus $7.8 trillion in IIIQ2016. The BEA explains as follows (https://www.bea.gov/newsreleases/international/intinv/2016/pdf/intinv316.pdf):

“The U.S. net international investment position increased to −$7,781.1 billion (preliminary) at the end of the third quarter of 2016 from −$8,026.9 billion (revised) at the end of the second quarter, according to statistics released today by the Bureau of Economic Analysis (BEA). The $245.8 billion increase in the net investment position reflected a $346.2 billion increase in U.S. assets and a $100.5 billion increase in U.S. liabilities. The net investment position increased 3.1 percent in the third quarter, compared with a decrease of 5.9 percent in the second quarter and an average quarterly decrease of 6.0 percent from the first quarter of 2011 through the first quarter of 2016.”

The BEA explains further (https://www.bea.gov/newsreleases/international/intinv/2016/pdf/intinv316.pdf): “U.S. assets increased $346.2 billion to $24,861.2 billion at the end of the third quarter, reflecting an increase in assets excluding financial derivatives that was partly offset by a decrease in financial derivatives. Assets excluding financial derivatives increased $794.9 billion to $22,086.1 billion, mostly reflecting increases in portfolio investment and direct investment assets due to increases in foreign equity prices. Financial derivatives decreased $448.7 billion to $2,775.1 billion, mostly in single-currency interest rate contracts and in foreign exchange contracts. U.S. liabilities increased $100.5 billion to $32,642.3 billion at the end of the third quarter, reflecting an increase in liabilities excluding financial derivatives that was partly offset by a decrease in financial derivatives. Liabilities excluding financial derivatives increased $546.3 billion to $29,922.5 billion, reflecting increases in portfolio investment and direct investment liabilities due to financial transactions and increases in U.S. equity prices. Financial derivatives decreased $445.8 billion to $2,719.9 billion, mostly in single-currency interest rate contracts and in foreign exchange contracts.”

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

 

IIIQ2015

IVQ2015

IQ2016

IIQ2016

IIIQ2016

Goods &
Services

-139

-127

-103

-134

-135

Primary

Income

43

48

34

42

44

Secondary Income

-41

-36

-41

-36

-42

Current Account

-137

-114

-110

-127

-133

Current Account % GDP

-2.7

-2.5

-2.9

-2.6

-2.4

NIIP

-7240

-7281

-7582

-8027

-7781

US Owned Assets Abroad

23478

23341

24062

24515

24861

Foreign Owned Assets in US

-30718

-30621

-31644

-32542

-32642

DIA MV

6785

6978

6993

6964

7384

DIA MV Equity

5640

5811

5838

5797

6161

DIUS MV

6260

6544

6665

6955

7194

DIUS MV Equity

4682

4979

5070

5272

5498

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

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

 

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

Source: Bureau of Economic Analysis

http://www.bea.gov/newsreleases/international/intinv/intinvnewsrelease.htm

Chart VI-10 of the Board of Governors of the Federal Reserve System provides the overnight Fed funds rate on business days from Jul 1, 1954 at 1.13 percent through Jan 10, 1979, at 9.91 percent per year, to Mar 9, 2017, at 0.66 percent per year. US recessions are in shaded areas according to the reference dates of the NBER (http://www.nber.org/cycles.html). In the Fed effort to control the “Great Inflation” of the 1970s (http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I The Great Inflation; see Taylor 1993, 1997, 1998LB, 1999, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB and http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html), the fed funds rate increased from 8.34 percent on Jan 3, 1979 to a high in Chart VI-10 of 22.36 percent per year on Jul 22, 1981 with collateral adverse effects in the form of impaired savings and loans associations in the United States, emerging market debt and money-center banks (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 72-7; Pelaez 1986, 1987). Another episode in Chart VI-10 is the increase in the fed funds rate from 3.15 percent on Jan 3, 1994, to 6.56 percent on Dec 21, 1994, which also had collateral effects in impairing emerging market debt in Mexico and Argentina and bank balance sheets in a world bust of fixed income markets during pursuit by central banks of non-existing inflation (Pelaez and Pelaez, International Financial Architecture (2005), 113-5). Another interesting policy impulse is the reduction of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of equally non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85), followed by increments of 25 basis points from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006 in Chart VI-10. Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment but the exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).

The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever-increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4). A final episode in Chart VI-10 is the reduction of the fed funds rate from 5.41 percent on Aug 9, 2007, to 2.97 percent on October 7, 2008, to 0.12 percent on Dec 5, 2008 and close to zero throughout a long period with the final point at 0.66 percent on Mar 9, 2017. Evidently, this behavior of policy would not have occurred had there been theory, measurements and forecasts to avoid these violent oscillations that are clearly detrimental to economic growth and prosperity without inflation. The Chair of the Board of Governors of the Federal Reserve System, Janet L. Yellen, stated on Jul 10, 2015 that (http://www.federalreserve.gov/newsevents/speech/yellen20150710a.htm):

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

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

It is a forecast mandate because of the lags in effect of monetary policy impulses on income and prices (Romer and Romer 2004). The intention is to reduce unemployment close to the “natural rate” (Friedman 1968, Phelps 1968) of around 5 percent and inflation at or below 2.0 percent. If forecasts were reasonably accurate, there would not be policy errors. A commonly analyzed risk of zero interest rates is the occurrence of unintended inflation that could precipitate an increase in interest rates similar to the Himalayan rise of the fed funds rate from 9.91 percent on Jan 10, 1979, at the beginning in Chart VI-10, to 22.36 percent on Jul 22, 1981. There is a less commonly analyzed risk of the development of a risk premium on Treasury securities because of the unsustainable Treasury deficit/debt of the United States (http://cmpassocregulationblog.blogspot.com/2017/01/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/unresolved-us-balance-of-payments.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-reducing.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/weakening-equities-and-dollar.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/monetary-policy-designed-on-measurable.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html

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

 

Chart VI-10, US, Fed Funds Rate, Business Days, Jul 1, 1954 to Mar 9, 2017, Percent per Year

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/h15/

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

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

1994

FF

30Y

30P

10Y

10P

MOR

CPI

Jan

3.00

6.29

100

5.75

100

7.06

2.52

Feb

3.25

6.49

97.37

5.97

98.36

7.15

2.51

Mar

3.50

6.91

92.19

6.48

94.69

7.68

2.51

Apr

3.75

7.27

88.10

6.97

91.32

8.32

2.36

May

4.25

7.41

86.59

7.18

88.93

8.60

2.29

Jun

4.25

7.40

86.69

7.10

90.45

8.40

2.49

Jul

4.25

7.58

84.81

7.30

89.14

8.61

2.77

Aug

4.75

7.49

85.74

7.24

89.53

8.51

2.69

Sep

4.75

7.71

83.49

7.46

88.10

8.64

2.96

Oct

4.75

7.94

81.23

7.74

86.33

8.93

2.61

Nov

5.50

8.08

79.90

7.96

84.96

9.17

2.67

Dec

6.00

7.87

81.91

7.81

85.89

9.20

2.67

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

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

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

 

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

Source: Board of Governors of the Federal Reserve System

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

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

 

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

Source: Bureau of Labor Statistics

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

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

 

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

Source: Bureau of Labor Statistics

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

  The Congressional Budget Office (CBO 2014BEOFeb4) estimates potential GDP, potential labor force and potential labor productivity provided in Table IB-3. The CBO estimates average rate of growth of potential GDP from 1950 to 2014 at 3.3 percent per year. The projected path is significantly lower at 2.1 percent per year from 2015 to 2025. The legacy of the economic cycle expansion from IIIQ2009 to IVQ2016 at 2.1 percent on average is in contrast with 4.4 percent on average in the expansion from IQ1983 to IIQ1990 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). Subpar economic growth may perpetuate unemployment and underemployment estimated at 24.2 million or 14.4 percent of the effective labor force in Feb 2017 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html) with much lower hiring than in the period before the current cycle (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/unconventional-monetary-policy-and.html).

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

 

Potential GDP

Potential Labor Force

Potential Labor Productivity*

Average Annual ∆%

     

1950-1973

4.0

1.6

2.4

1974-1981

3.2

2.5

0.7

1982-1990

3.2

1.6

1.6

1991-2001

3.2

1.2

2.0

2002-2007

2.5

1.0

1.5

2008-2015

1.5

0.5

0.9

Total 1950-2015

3.2

1.5

1.7

Projected Average Annual ∆%

     

2016-2020

1.7

0.4

1.3

2021-2026

2.0

0.5

1.4

2016-2026

1.8

0.5

1.4

*Ratio of potential GDP to potential labor force

Source: CBO (2014BEOFeb4), CBO, Key assumptions in projecting potential GDP—February 2014 baseline. Washington, DC, Congressional Budget Office, Feb 4, 2014. CBO, The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015. Aug 2016

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

 

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

Source: Congressional Budget Office

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

Chart IB-1 of the Congressional Budget Office (CBO 2013BEOFeb5) provides actual and potential GDP of the United States from 2000 to 2011 and projected to 2024. Lucas (2011May) estimates trend of United States real GDP of 3.0 percent from 1870 to 2010 and 2.2 percent for per capita GDP. The United States successfully returned to trend growth of GDP by higher rates of growth during cyclical expansion as analyzed by Bordo (2012Sep27, 2012Oct21) and Bordo and Haubrich (2012DR). Growth in expansions following deeper contractions and financial crises was much higher in agreement with the plucking model of Friedman (1964, 1988). The unusual weakness of growth at 2.1 percent on average from IIIQ2009 to IVQ2016 during the current economic expansion in contrast with 4.4 percent on average in the cyclical expansion from IQ1983 to IIQ1990 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html) cannot be explained by the contraction of 4.2 percent of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 24.2 million or 14.4 percent of the labor force as estimated for Feb 2017 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). There is no exit from unemployment/underemployment and stagnating real wages because of the collapse of hiring (https://cmpassocregulationblog.blogspot.com/2017/02/recovery-without-hiring-ten-million.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/unconventional-monetary-policy-and.html). The US economy and labor markets collapsed without recovery. Abrupt collapse of economic conditions can be explained only with cyclic factors (Lazear and Spletzer 2012Jul22) and not by secular stagnation (Hansen 1938, 1939, 1941 with early dissent by Simons 1942).

 

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

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

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

 

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

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

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

 

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

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

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

 

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

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

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

 

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

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

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

 

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

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

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

 

Chart IIA2-6, US, Real GDP, 1960-2015, Billions of Chained 2009 Dollars

Source: Bureau of Economic Analysis

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

Chart IIA-7 provides the US current account deficit on a quarterly basis from 1980 to IQ1983. The deficit is at a lower level because of growth below potential not only in the US but worldwide. The combination of high government debt and deficit with external imbalance restricts potential prosperity in the US.

 

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

Source: Bureau of Economic Analysis

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

Risk aversion channels funds toward US long-term and short-term securities that finance the US balance of payments and fiscal deficits benefitting from risk flight to US dollar denominated assets. There are now temporary interruptions because of fear of rising interest rates that erode prices of US government securities because of mixed signals on monetary policy and exit from the Fed balance sheet of four trillion dollars of securities held outright. Net foreign purchases of US long-term securities (row C in Table VA-4) weakened from $15.9 billion in Nov 2016 to minus $29.4 billion in Dec 2016. Foreign residents’ purchases minus sales of US long-term securities (row A in Table VA-4) in Nov 2016 of $17.0 billion weakened to $13.9 billion in Dec 2016. Net US (residents) purchases of long-term foreign securities (row B in Table VA-4) weakened from $17.5 billion in Nov 2016 to $1.1 billion in Dec 2016. Other transactions (row C2 in Table VA-4) changed from minus $18.5 billion in Nov 2016 to minus $16.6 billion in Dec 2016. In Dec 2016,

C = A + B + C2 = -$13.9 billion + $1.1 billion -$16.6 billion = -$29.4 billion

There are minor rounding errors. There is weakening demand in Table VA-4 in Dec 2016 in A1 private purchases by residents overseas of US long-term securities of minus $32.0 billion of which weakening in A11 Treasury securities of $40.4 billion, weakening in A12 of $12.5 billion in agency securities, weakening of $5.4 billion of corporate bonds and weakening of minus $9.5 billion in equities. Worldwide risk aversion causes flight into US Treasury obligations with significant oscillations. Official purchases of securities in row A2 increased $18.1 billion with increase of Treasury securities of $18.6 billion in Dec 2016. Official purchases of agency securities increased $1.2 billion in Dec 2016. Row D shows increase in Dec 2016 of $33.5 billion in purchases of short-term dollar denominated obligations. Foreign private holdings of US Treasury bills increased $8.3 billion (row D11) with foreign official holdings increasing $2.8 billion while the category “other” increased $22.4 billion. Foreign private holdings of US Treasury bills increased $8.3 billion in what could be arbitrage of duration exposures and international risks. Risk aversion of default losses in foreign securities dominates decisions to accept zero interest rates in Treasury securities with no perception of principal losses. In the case of long-term securities, investors prefer to sacrifice inflation and possible duration risk to avoid principal losses with significant oscillations in risk perceptions.

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

 

Dec 2015 12 Months

Dec 2016 12 Months

Nov 2016

Dec 2016

A Foreign Purchases less Sales of
US LT Securities

155.6

68.4

17.0

-13.9

A1 Private

368.0

356.8

15.9

-32.0

A11 Treasury

205.6

-4.7

0.7

-40.4

A12 Agency

123.2

253.2

13.2

12.5

A13 Corporate Bonds

137.9

124.4

7.8

5.4

A14 Equities

-98.7

-16.0

-5.9

-9.5

A2 Official

-212.4

-288.3

1.1

18.1

A21 Treasury

-225.9

-338.0

-0.9

18.6

A22 Agency

33.5

49.5

3.0

1.2

A23 Corporate Bonds

-3.8

-5.3

-1.1

-1.1

A24 Equities

-16.2

5.4

0.1

-0.5

B Net US Purchases of LT Foreign Securities

161.9

187.1

17.5

1.1

B1 Foreign Bonds

276.1

258.8

17.1

19.2

B2 Foreign Equities

-114.2

-71.6

0.4

-18.2

C1 Net Transactions

317.5

255.5

34.4

-12.9

C2 Other

-277.5

-272.4

-18.5

-16.6

C Net Foreign Purchases of US LT Securities

40.0

-16.9

15.9

-29.4

D Increase in Foreign Holdings of Dollar Denominated Short-term 

71.0

35.2

1.7

33.5

D1 US Treasury Bills

53.1

-54.8

0.2

11.1

D11 Private

51.7

-16.5

-0.3

8.3

D12 Official

1.4

-38.3

0.4

2.8

D2 Other

17.9

89.9

1.5

22.4

C1 = A + B; C = C1+C2

A = A1 + A2

A1 = A11 + A12 + A13 + A14

A2 = A21 + A22 + A23 + A24

B = B1 + B2

D = D1 + D2

Sources: United States Treasury

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

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

Table VA-2 provides major foreign holders of US Treasury securities. China is the second largest holder with $1058.4 billion in Dec 2016, increasing 0.9 percent from $1049.3 billion in Nov 2016 while decreasing $187.7 billion from Dec 2015 or 15.1 percent. The United States Treasury estimates US government debt held by private investors at $11,184 billion in Sep 2016. China’s holding of US Treasury securities represent 9.5 percent of US government marketable interest-bearing debt held by private investors (http://www.fms.treas.gov/bulletin/index.html). Min Zeng, writing on “China plays a big role as US Treasury yields fall,” on Jul 16, 2014, published in the Wall Street Journal (http://online.wsj.com/articles/china-plays-a-big-role-as-u-s-treasury-yields-fall-1405545034?tesla=y&mg=reno64-wsj), finds that acceleration in purchases of US Treasury securities by China has been an important factor in the decline of Treasury yields in 2014. Japan decreased its holdings from $1122.4 billion in Dec 2015 to $1090.8 billion in Dec 2016 or 2.8 percent. The combined holdings of China and Japan in Dec 2016 add to $2149.2 billion, which is equivalent to 19.2 percent of US government marketable interest-bearing securities held by investors of $11,184 billion in Sep 2016 (http://www.fms.treas.gov/bulletin/index.html). Total foreign holdings of Treasury securities decreased from $6146.2 billion in Dec 2015 to $6003.9 billion in Dec 2016, or 2.3 percent. The US continues to finance its fiscal and balance of payments deficits with foreign savings (see Pelaez and Pelaez, The Global Recession Risk (2007)). A point of saturation of holdings of US Treasury debt may be reached as foreign holders evaluate the threat of reduction of principal by dollar devaluation and reduction of prices by increases in yield, including possibly risk premium. Shultz et al (2012) find that the Fed financed three-quarters of the US deficit in fiscal year 2011, with foreign governments financing significant part of the remainder of the US deficit while the Fed owns one in six dollars of US national debt. Concentrations of debt in few holders are perilous because of sudden exodus in fear of devaluation and yield increases and the limit of refinancing old debt and placing new debt. In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):

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

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

 

Dec 2016

Nov 2016

Dec 2015

Total

6003.9

5944.7

6146.2

Japan

1090.8

1108.6

1122.4

China

1058.4

1049.3

1246.1

Ireland

288.2

275.2

264.4

Cayman Islands

263.5

260.6

249.8

Brazil

259.2

258.3

254.8

Switzerland

229.3

229.5

231.7

Luxembourg

223.4

221.0

199.6

United Kingdom

217.1

212.0

207.1

Hong Kong

191.4

185.5

200.1

Taiwan

189.3

183.1

178.7

Belgium

120.4

113.5

121.7

India

118.2

118.7

116.8

Foreign Official Holdings

3814.1

3770.5

4093.6

A. Treasury Bills

298.4

295.6

336.7

B. Treasury Bonds and Notes

3515.8

3474.9

3757.0

Source: United States Treasury

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

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

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

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 second estimate for IVQ2016 and revision of the estimates for IIIQ2016 and IIQ2016 together with data for nonfarm business sector productivity and unit labor costs in seasonally adjusted annual equivalent (SAAE) rate and the percentage change from the same quarter a year earlier. Reflecting increase in output at 2.4 percent and increase at 1.0 percent in hours worked, nonfarm business sector labor productivity increased at the SAAE rate of 1.3 percent in IVQ2016, as shown in column 2 “IVQ2016 SAEE.” The increase of labor productivity from IVQ2015 to IVQ2016 was 1.0 percent, reflecting increases in output of 2.2 percent and of hours worked of 1.2 percent, as shown in column 3 “IVQ2016 YoY.” Hours worked decreased from 1.7 percent in IIQ2016 at SAAE to 0.8 percent in IIIQ2016 and decreased to 1.0 percent in IVQ2016 while output growth increased from 1.6 percent in IIQ2016 at SAAE to 4.2 percent in IIIQ2016, decreasing to 2.4 percent in IVQ2016. The BLS defines unit labor costs as (http://www.bls.gov/news.release/pdf/prod2.pdf 1): “BLS calculates 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 1.7 percent in IVQ2016 and increased 2.0 percent in IVQ2016 relative to IVQ2015. Hourly compensation increased at the SAAE rate of 3.0 percent in IVQ2016, which deflating by the estimated consumer price increase SAAE rate in IVQ2016 results in decrease of real hourly compensation at 0.4 percent. Real hourly compensation increased 1.2 percent in IVQ2016 relative to IVQ2015.

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

 

IVQ 2016 SAAE

IVQ 2016 YoY

III 2016 SAAE

III 2016 YOY

IIQ
2016
SAAE

IIQ
2016
YoY

Productivity

1.3

1.0

3.3

0.1

-0.1

-0.2

Output

2.4

2.2

4.2

1.8

1.6

1.2

Hours

1.0

1.2

0.8

1.7

1.7

1.5

Hourly
Comp.

3.0

3.0

4.1

3.2

6.1

2.8

Real Hourly Comp.

-0.4

1.2

2.4

2.0

3.5

1.7

Unit Labor Costs

1.7

2.0

0.7

3.0

6.2

3.1

Unit Nonlabor Payments

2.0

0.7

1.6

-1.4

-2.8

-1.5

Implicit Price Deflator

1.8

1.5

1.1

1.1

2.3

1.1

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

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). Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). 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 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). Professor Edward P. Lazear (2017Feb27), writing in the Wall Street Journal, on Feb 27, 2017 (https://www.wsj.com/articles/how-trump-can-hit-3-growthmaybe-1488239746), finds that productivity growth was 7 percent between 2009 and 2016 at annual equivalent 1 percent. Lazear measures productivity growth at 2.3 percent per year from 2001 to 2008. The Bureau of Labor Statistics important report on productivity and costs released on Mar 8, 2017 (http://www.bls.gov/lpc/) supports the argument of decline of productivity growth in the US analyzed by Prescott and Ohanian (2014Feb) and Lazear (2017Feb27). 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 2017. The estimates incorporate the yearly revision of the US national accounts (http://www.bea.gov/national/an1.htm#2016annualupdate). The data confirm the argument of Prescott and Ohanian (2014Feb) and Lazear (2017Feb27): productivity increased cumulatively 3.2 percent from 2011 to 2016 at the average annual rate of 0.5 percent. The situation is direr by excluding growth of 0.9 percent in 2012, which leaves an average of 0.4 percent for 2011-2016. Average productivity growth for the entire economic cycle from 2007 to 2016 is only 1.2 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 2010 consisted of reducing labor hours.

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

 

2016 ∆%

2015 ∆%

2014 ∆%

2013 ∆%

2012   ∆%

2011    ∆%

Productivity

0.2

0.9

0.8

0.3

0.9

0.1

Real Hourly Compensation

1.6

2.8

1.1

-0.3

0.5

-0.9

Unit Labor Costs

2.6

2.0

2.0

0.9

1.7

2.1

 

2010 ∆%

2009 ∆%

2008 ∆%

2007∆%

Productivity

3.3

3.1

0.8

1.6

Real Hourly Compensation

0.3

1.4

-1.0

1.4

Unit Labor Costs

-1.3

-2.0

2.0

2.7

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 2016. The annual average jumped from 2.7 percent in 2001 to 4.4 percent in 2002. Nonfarm business productivity increased at the SAAE rate of 9.3 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 4.5 percent in IVQ2013 and contracted at 3.7 percent in IQ2014. Productivity increased at 1.7 percent in IIQ2014 and at 4.1 percent in IIIQ2014. Productivity contracted at 1.4 percent in IVQ2014 and increased at 1.2 percent in IQ2015. Productivity grew at 1.0 percent in IIQ2015 and increased at 1.8 percent in IIIQ2015. Productivity contracted at 2.0 percent in IVQ2015 and contracted at 0.6 percent in IQ2016. Productivity contracted at 0.1 percent in IIQ2016 and expanded at 3.3 percent in IIIQ2016. Productivity grew at 1.3 percent in IVQ2016.

Table II-3, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2016

Year

Qtr1

Qtr2

Qtr3

Qtr4

Annual

1999

4.5

1.2

3.6

6.6

3.7

2000

-1.9

8.2

-0.2

4.1

3.0

2001

-1.6

7.0

2.1

5.2

2.7

2002

9.3

0.3

3.1

-0.7

4.4

2003

4.2

5.5

9.0

3.9

3.7

2004

-0.1

3.8

1.4

1.3

3.1

2005

4.5

-0.4

3.0

0.1

2.1

2006

2.4

-0.3

-1.8

3.0

0.9

2007

0.4

2.5

4.9

1.7

1.6

2008

-3.8

4.0

1.0

-2.5

0.8

2009

3.1

7.9

5.9

4.9

3.1

2010

2.1

1.4

2.0

1.6

3.3

2011

-3.3

1.3

-0.7

2.8

0.1

2012

0.6

2.3

-0.7

-1.8

0.9

2013

0.9

-0.7

1.7

4.5

0.3

2014

-3.7

1.7

4.1

-1.4

0.8

2015

1.2

1.0

1.8

-2.0

0.9

2016

-0.6

-0.1

3.3

1.3

0.2

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 2016. 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 2016 have been more frequent and sharper.

 

Chart II-1, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2016

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 at 8.9 percent in IQ2012 followed by decrease at 0.1 percent in IIQ2012, increase at 1.1 percent in IIIQ2012 and increase at 13.2 percent in IVQ2012. Unit labor costs decreased at 9.7 percent in IQ2013 and increased at 6.5 percent in IIQ2013. Unit labor costs decreased at 0.5 percent in IIIQ2013 and decreased at 1.9 percent in IVQ2013. Unit labor costs increased at 10.2 percent in IQ2014 and at minus 3.7 percent in IIQ2014. Unit labor costs decreased at 0.2 percent in IIIQ2014 and increased at 5.2 percent in IVQ2014. Unit labor costs increased at 0.7 percent in IQ2015 and increased at 3.5 percent in IIQ2015. Unit labor costs increased at 0.8 percent in IIIQ2015 and increased at 5.7 percent in IVQ2015. Unit labor costs decreased at 0.3 percent in IQ2016 and increased at 6.2 percent in IIQ2016. Unit labor costs increased at 0.7 percent in IIIQ2016 and increased at 1.7 percent in IVQ2016.

Table II-4, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2016

Year

Qtr1

Qtr2

Qtr3

Qtr4

Annual

1999

2.9

0.3

0.0

1.6

0.9

2000

17.4

-6.8

8.2

-1.7

4.0

2001

11.4

-5.4

-1.7

-1.4

1.6

2002

-6.6

3.3

-1.1

1.7

-2.0

2003

-1.5

1.6

-2.6

1.5

0.1

2004

-0.5

3.9

5.6

0.5

1.4

2005

-1.3

2.6

2.0

2.3

1.6

2006

6.1

0.5

2.3

4.0

3.0

2007

9.8

-2.7

-3.2

2.6

2.7

2008

8.3

-3.6

2.4

7.1

2.0

2009

-12.3

2.1

-3.0

-2.3

-2.0

2010

-4.8

3.2

-0.2

0.2

-1.3

2011

11.0

-3.5

3.3

-7.7

2.1

2012

8.9

-0.1

1.1

13.2

1.7

2013

-9.7

6.5

-0.5

-1.9

0.9

2014

10.2

-3.7

-0.2

5.2

2.0

2015

0.7

3.5

0.8

5.7

2.0

2016

-0.3

6.2

0.7

1.7

2.6

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

Chart II-2 provides change of unit labor costs at SAAE from 1999 to 2016. There are multiple oscillations recently with negative changes alternating with positive changes.

 

Chart II-2, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2016

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 6.6 percent in IIQ2011 and 6.8 percent in IVQ2011. Real hourly compensation increased at 6.9 percent in IQ2012, increasing at 1.5 percent in IIQ2012, declining at 1.3 percent in IIIQ2012 and increasing at 8.1 percent in IVQ2012. Real hourly compensation fell at 0.9 percent in 2011 and increased at 0.5 percent in 2012. Real hourly compensation fell at 10.4 percent in IQ2013 and increased at 6.3 percent in IIQ2013, falling at 1.0 percent in IIIQ2013. Real hourly compensation increased at 0.7 percent in IVQ2013 and at 3.8 percent in IQ2014. Real hourly compensation decreased at 4.0 percent in IIQ2014. Real hourly compensation increased at 3.0 percent in IIIQ2014. The annual rate of increase of real hourly compensation for 2013 is minus 0.3 percent. Real hourly compensation increased at 4.1 percent in IVQ2014. The annual rate of increase of real hourly compensation in 2014 is 1.1 percent. Real hourly compensation increased at 4.9 percent in IQ2015 and increased at 2.1 percent in IIQ2015. Real hourly compensation increased at 1.3 percent in IIIQ2015 and increased at 2.7 percent in IVQ2015. Real hourly compensation increased at 2.8 percent in 2015. Real hourly compensation decreased at 0.7 percent in IQ2016 and increased at 3.5 percent in IIQ2016. Real hourly compensation increased at 2.4 percent in IIIQ2016 and decreased at 0.4 percent in IVQ2016. Real hourly compensation increased 1.6 percent in 2016.

Table II-5, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate 1999-2016

Year

Qtr1

Qtr2

Qtr3

Qtr4

Annual

1999

5.9

-1.4

0.5

5.1

2.5

2000

10.6

-2.2

4.1

-0.6

3.5

2001

5.4

-1.5

-0.7

4.2

1.4

2002

0.6

0.4

-0.2

-1.5

0.7

2003

-1.4

7.9

3.0

4.0

1.5

2004

-3.9

4.6

4.4

-2.5

1.8

2005

1.2

-0.6

-1.1

-1.2

0.3

2006

6.2

-3.3

-3.3

8.9

0.6

2007

5.9

-4.6

-1.0

-0.6

1.4

2008

-0.2

-4.7

-2.6

14.5

-1.0

2009

-7.1

7.8

-0.7

-0.6

1.4

2010

-3.4

4.8

0.6

-1.4

0.3

2011

2.9

-6.6

-0.1

-6.8

-0.9

2012

6.9

1.5

-1.3

8.1

0.5

2013

-10.4

6.3

-1.0

0.7

-0.3

2014

3.8

-4.0

3.0

4.1

1.1

2015

4.9

2.1

1.3

2.7

2.8

2016

-0.7

3.5

2.4

-0.4

1.6

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.

 

Chart II-3, US, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate 1999-2016

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.

 

Chart II-4, US, Nonfarm Business Output per Hour, Percent Change from Same Quarter a Year Earlier 1999-2016

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.

 

Chart II-5, US, Nonfarm Business Unit Labor Costs, Percent Change from Same Quarter a Year Earlier 1999-2016

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.

 

Chart II-6, US, Nonfarm Business Real Hourly Compensation, Percent Change from Same Quarter a Year Earlier 1999-2016

2005=100

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). Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). 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 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). Professor Edward P. Lazear (2017Feb27), writing in the Wall Street Journal, on Feb 27, 2017 (https://www.wsj.com/articles/how-trump-can-hit-3-growthmaybe-1488239746), finds that productivity growth was 7 percent between 2009 and 20016 at annual equivalent 1 percent. Lazear measures productivity growth at 2.3 percent per year from 2001 to 2008. The Bureau of Labor Statistics important report on productivity and costs released on Mar 8, 2017 (http://www.bls.gov/lpc/) supports the argument of decline of productivity growth in the US analyzed by Prescott and Ohanian (2014Feb) and Lazear (2017Feb27). 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 2017. The estimates incorporate the yearly revision of the US national accounts (http://www.bea.gov/national/an1.htm#2016annualupdate). The data confirm the argument of Prescott and Ohanian (2014Feb) and Lazear (2017Feb27): productivity increased cumulatively 3.2 percent from 2011 to 2016 at the average annual rate of 0.5 percent. The situation is direr by excluding growth of 0.9 percent in 2012, which leaves an average of 0.4 percent for 2011-2016. Average productivity growth for the entire economic cycle from 2007 to 2016 is only 1.2 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 2010 consisted of 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 2016. 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.

 

Chart II-7, US, Nonfarm Business Labor Productivity, Output per Hour, 1947-2016, 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 2016. 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 2016 of productivity growth at average 0.5 percent per year.

Table II-6, US, Productivity and Costs, Annual Percentage Changes 2007-2016

 

2016

2015

2014

2013

2012

Productivity

0.2

0.9

0.8

0.3

0.9

Output

1.7

3.1

3.0

2.0

3.1

Hours Worked

1.5

2.1

2.2

1.7

2.2

Employment

1.8

2.2

2.0

1.8

2.0

Average Weekly Hours Worked

-0.3

-0.1

0.2

-0.1

0.2

Unit Labor Costs

2.6

2.0

2.0

0.9

1.7

Hourly Compensation

2.9

2.9

2.8

1.2

2.6

Consumer Price Inflation

1.6

0.1

3.2

1.5

2.1

Real Hourly Compensation

1.6

2.8

1.1

-0.3

0.5

Non-labor Payments

0.9

2.7

4.4

4.4

5.3

Output per Job

-0.1

0.8

1.0

0.2

1.1

 

2011

2010

2009

2008

2007

Productivity

0.1

3.3

3.1

0.8

1.6

Output

2.2

3.2

-4.3

-1.3

2.3

Hours Worked

2.1

-0.1

-7.2

-2.1

0.7

Employment

1.6

-1.2

-5.7

-1.5

0.9

Average Weekly Hours Worked

0.5

1.1

-1.6

-0.6

-0.2

Unit Labor Costs

2.1

-1.3

-2.0

2.0

2.7

Hourly Compensation

2.2

1.9

1.0

2.8

4.3

Consumer Price Inflation

3.2

1.6

-0.4

3.8

2.8

Real Hourly Compensation

-0.9

0.3

1.4

-1.0

1.4

Non-labor Payments

3.7

7.5

0.0

-0.4

3.4

Output per Job

0.6

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 from 2.1 percent per year on average from 1947 to 2016 to 1.2 percent per year on average in the whole cycle from 2007 to 2016. 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 2016 to 1.4 percent from 2007 to 2016. Output grew at 3.7 percent per year on average from 1947 to 2007. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Jan 1919 to Jan 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 142.7575 in Jan 2017. The actual index NSA in Jan 2017 is 101.5620, which is 28.9 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Jan 2017. Using trend growth of 2.0 percent per year, the index would increase to 129.5532 in Jan 2017. The output of manufacturing at 101.5620 in Jan 2017 is 21.6 percent below trend under this alternative calculation.

Table II-7, US, Productivity and Costs, Average Annual Percentage Changes 2007-2016 and 1947-2016

 

Average Annual Percentage Rate 2007-2016

Average Annual Percentage Rate 1947-2007

Average Annual Percentage Rate  1947-2016

Productivity

1.2

2.3

2.1

Output

1.4

3.7

3.4

Hours

0.2

1.4

1.2

Employment

0.3

1.6

1.5

Average Weekly Hours

-0.7*

-14.4*

-15.0*

Hourly Compensation

2.3

5.4

5.0

Consumer Price Inflation

1.6

3.8

3.5

Real Hourly Compensation

0.6

1.7

1.6

Unit Labor Costs

1.1

3.0

2.8

Unit Non-labor Payments

1.7

3.5

3.2

Output per Job

1.1

2.0

1.9

* 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.

 

Chart II-8, US, Nonfarm Business, Unit Labor Costs, 1947-2016, 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.

 

Chart II-9, US, Nonfarm Business, Real Hourly Compensation, 1947-2016, Index 2009=100

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

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

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