Sunday, September 4, 2016

Interest Rates and Valuations of Risk Financial Assets, Twenty-four Million Unemployed or Underemployed, Job Creation, Stagnating Real Wages, Stagnating Real Disposable Income per Capita, Financial Repression, Rules, Discretionary Authorities and Slow Productivity Growth, World Cyclical Slow Growth and Global Recession Risk: Part II

 

Interest Rates and Valuations of Risk Financial Assets, Twenty-four Million Unemployed or Underemployed, Job Creation, Stagnating Real Wages, Stagnating Real Disposable Income per Capita, Financial Repression, Rules, Discretionary Authorities and Slow Productivity Growth, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

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

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 Stagnating Real Disposable Income and Consumption Expenditures

IB1 Stagnating Real Disposable Income and Consumption Expenditures

IB2 Financial Repression

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 151,000 in Aug 2016 and private payroll employment increased 126,000. The average monthly number of nonfarm jobs created from Aug 2014 to Aug 2015 was 238,167 using seasonally adjusted data, while the average number of nonfarm jobs created from Aug 2015 to Aug 2016 was 203,917, or decrease by 14.4 percent. The average number of private jobs created in the US from Aug 2014 to Aug 2015 was 223,083, using seasonally adjusted data, while the average from Aug 2015 to Aug 2016 was 190,250, or decrease by 14.7 percent. This blog calculates the effective labor force of the US at 166.226 million in Aug 2015 and 168.051 million in Aug 2016 (Table I-4), for growth of 1.825 million at average 152,083 per month. The difference between the average increase of 190.250 new private nonfarm jobs per month in the US from Aug 2015 to Aug 2016 and the 152,083 average monthly increase in the labor force from Aug 2015 to Aug 2016 is 38,167 monthly new jobs net of absorption of new entrants in the labor force. There are 23.923 million in job stress in the US currently. Creation of 38,167 new jobs per month net of absorption of new entrants in the labor force would require 627 months to provide jobs for the unemployed and underemployed (23.923 million divided by 38,167) or 52 years (627 divided by 12). The civilian labor force of the US in Aug 2016 not seasonally adjusted stood at 159.800 million with 7.996 million unemployed or effectively 16.247 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 168.051 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 2.2 years (1 million divided by product of 38,167 by 12, which is 458,004). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.990 million (0.05 times labor force of 159.800 million). New net job creation would be 0.006 million (7.996 million unemployed minus 7.990 million unemployed at rate of 5 percent) that at the current rate would take 0.01 years (0.006 million divided by 458,004). Under the calculation in this blog, there are 16.247 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 168.051 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 7.063 million jobs net of labor force growth that at the current rate would take 17.1 years (16.247 million minus 0.05(168.051 million) = 7.844 million divided by 458,004 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 Aug 2016 was 151.804 million (NSA) or 4.489 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 253.854 million in Aug 2016 or by 21.896 million. The number employed increased 3.0 percent from Jul 2007 to Aug 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.4 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 Aug 2016 would result in 161.197 million jobs (0.635 multiplied by noninstitutional civilian population of 253.854 million). There are effectively 9.393 million fewer jobs in Aug 2016 than in Jul 2007, or 161.197 million minus 151.804 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/2016/08/rising-valuations-of-risk-financial.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 Aug 2016 were $25.73 seasonally adjusted (SA), increasing 1.9 percent not seasonally adjusted (NSA) relative to Aug 2015 and increasing 0.1 percent relative to Jul 2016 seasonally adjusted. In Jul 2016, average hourly earnings seasonally adjusted were $25.70, increasing 2.8 percent relative to Jul 2015 not seasonally adjusted and increasing 0.3 percent seasonally adjusted relative to Jun 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 Aug 2016 because the prices indexes of the BLS for Jul 2016 will only be released on Sep 16, 2016 (http://www.bls.gov/cpi/), which will be covered in this blog’s comment on Sep 18, 2016, together with world inflation. The second column provides changes in real wages for Jul 2016. Average hourly earnings adjusted for inflation or in constant dollars increased 1.9 percent in Jul 2016 relative to Jul 2015 but have been decreasing/stagnating during multiple months. World inflation waves in bouts of risk aversion (http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.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 http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html). The following section IB Stagnating Real Wages provides more detailed analysis. Average weekly hours of US workers seasonally adjusted remained virtually unchanged, decreasing from 34.4 in Jul to 34.3 in Aug, which is substantial less additional work on a labor force of 159.463 million SA in Aug 2016. Another headline number widely followed is the unemployment rate or number of people unemployed as percent of the labor force. The unemployment rate calculated in the household survey did not change from 4.9 percent in Jul 2016 to 4.9 percent in Aug 2016, 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 23.9 million in Aug 2016 and 23.6 million in Jul 2016. The final row in Table I-1 provides the number in job stress as percent of the actual labor force calculated at 14.2 percent in Aug 2016 and 14.0 percent in Jul 2016. 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

 

Aug 2016

July 2016

New Nonfarm Payroll Jobs

151,000

275,000

New Private Payroll Jobs

126,000

225,000

Average Hourly Earnings

Aug 16 $25.73 SA

∆% Aug 16/Aug 15 NSA: 1.9

∆% Aug 16/Jul 16 SA: 0.1

Jul 16 $25.70 SA

∆% Jul 16/Jun 15 NSA: 2.8

∆% Jul 16/Jun 16 SA: 0.3

Average Hourly Earnings in Constant Dollars

 

∆% Jul 2016/Jul 2015 NSA: 1.9

Average Weekly Hours

34.3 SA

34.4 NSA

34.4 SA

34.4 NSA

Unemployment Rate Household Survey % of Labor Force SA

4.9

4.9

Number in Job Stress Unemployed and Underemployed Blog Calculation

23.9 million NSA

23.6 million NSA

In Job Stress as % Labor Force

14.2 NSA

14.0 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 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.”

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 decrease in the number unemployed from 7.783 million in Jun 2016 to 7.770 million in Jul 2016 and increase to 7.849 million in Aug 2016. The rate of unemployment did not change from 4.9 percent in Jun 2016 to 4.9 percent in Jul 2016 and did not change to 4.9 percent in Aug 2016. An important aspect of unemployment is its persistence for more than 27 weeks with 2.006 million in Aug 2016, corresponding to 25.6 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 5.843 million in Jun 2016 to 5.940 million in Jul 2016 and increased to 6.053 million in Aug 2016. 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 15.615 million in Aug 2016 consists of:

· 7.849 million unemployed (of whom 2.006 million, or 25.6 percent, unemployed for 27 weeks or more) compared with 7.770 million unemployed in Jul 2016 (of whom 2.020 million, or 26.0 percent, unemployed for 27 weeks or more).

· 6.053 million employed part-time for economic reasons in Aug 2016 (who suffered reductions in their work hours or could not find full-time employment) compared with 5.940 million in Jul 2016

· 1.713 million who were marginally attached to the labor force in Aug 2016 (who were not in the labor force but wanted and were available for work) compared with 1.950 million in Jul 2016

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

 

Aug 2016

Jul 2016

Jun 2016

Labor Force Millions

159.463

159.287

158.880

Unemployed
Millions

7.849

7.770

7.783

Unemployment Rate (unemployed as % labor force)

4.9

4.9

4.9

Unemployed ≥27 weeks
Millions

2.006

2.020

1.979

Unemployed ≥27 weeks %

25.6

26.0

25.4

Part Time for Economic Reasons
Millions

6.053

5.940

5.843

Marginally
Attached to Labor Force
Millions

1.713

1.950

1.779

Job Stress
Millions

15.615

15.660

15.405

In Job Stress as % Labor Force

9.8

9.8

9.7

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

Source: US Bureau of Labor Statistics

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

Table I-3 repeats the data in Table I-2 but including May 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 May 2015, 59.6 in Jun 2016, 59.7 in Jul 2016 and 59.7 in Aug 2016. 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 59.3 in 2015.

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

 

Aug 2016

Jul 2016

Jun 2016

May 2016

Labor Force

159.463

159.287

158.880

158.466

Participation Rate

62.8

62.8

62.7

62.6

Unemployed

7.849

7.770

7.783

7.436

UNE Rate %

4.9

4.9

4.9

4.7

Part Time Economic Reasons

6.053

5.940

5.843

6.430

Marginally Attached to Labor Force

1.713

1.950

1.779

1.713

In Job Stress

15,615

15.660

15.405

15.579

In Job Stress % Labor Force

9.8

9.8

9.7

9.8

Employed

151.614

151.517

151.097

151.030

Employment % Population

59.7

59.7

59.6

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 2016. 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 Aug 2016 was 151.804 million (NSA) or 4.489 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 253.854 million in Aug 2016 or by 21.896 million. The number employed increased 3.0 percent from Jul 2007 to Aug 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.4 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 Aug 2016 would result in 161.197 million jobs (0.635 multiplied by noninstitutional civilian population of 253.854 million). There are effectively 9.393 million fewer jobs in Aug 2016 than in Jul 2007, or 161.197 million minus 151.804 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.

clip_image001

Chart I-1, US, Employed, Thousands, SA, 2001-2016

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.

clip_image002

Chart I-2, US, Employed, 12-Month Percentage Change NSA, 2001-2016

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 2.3 percent higher at 159.800 million in Aug 2016 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 159.800 million in Aug 2016 to the noninstitutional population of 253.854 million in Aug 2016 was 62.9 percent. The labor force of the US in Aug 2016 corresponding to 66.8 percent of participation in the population would be 169.574 million (0.668 x 253.854). The difference between the measured labor force in Aug 2016 of 159.800 million and the labor force in Aug 2016 with participation rate of 66.8 percent (as in Jul 2007) of 169.574 million is 9.774 million. The level of the labor force in the US has stagnated and is 9.774 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.

clip_image003

Chart I-3, US, Civilian Labor Force, Thousands, SA, 2001-2016

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.

clip_image004

Chart I-4, US, Civilian Labor Force, Thousands, NSA, 12-month Percentage Change, 2001-2016

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 62.9 percent NSA in Aug 2016, 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.

clip_image005

Chart I-5, Civilian Labor Force Participation Rate, Percent of Population in Labor Force SA, 2001-2016

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 7.996 million in Aug 2016, all numbers not seasonally adjusted.

clip_image006

Chart I-6, US, Unemployed, Thousands, SA, 2001-2016

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 5.0 percent in Aug 2016.

clip_image007

Chart I-7, US, Unemployment Rate, SA, 2001-2016

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. The level of unemployment fell 2.0 percent in Aug 2016 relative to a year earlier.

clip_image008

Chart I-8, US, Unemployed, 12-month Percentage Change, NSA, 2001-2016

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 8.267 million in Jan 2012 and 8.214 million in Feb 2012 but then falling to 7.922 million in Dec 2012 and increasing to 8.093 million in Jul 2013. The number employed part-time for economic reasons seasonally adjusted reached 7.763 million in Dec 2013 and 6.786 million in Dec 2014. The number employed part-time for economic reasons seasonally adjusted reached 6.053 million in Aug 2016. 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 5.963 million in Aug 2016. The longer the period in part-time jobs the lower are the chances of finding another full-time job.

clip_image009

Chart I-9, US, Part-Time for Economic Reasons, Thousands, SA, 2001-2016

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 fell 6.3 percent in Aug 2016 relative to a year earlier.

clip_image010

Chart I-10, US, Part-Time for Economic Reasons NSA 12-Month Percentage Change, 2001-2016

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 1.713 million in Aug 2016.

clip_image011

Chart I-11, US, Marginally Attached to the Labor Force, Thousands, NSA, 2001-2016

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 2016. 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 fell 5.5 percent in the 12 months ending in Aug 2016.

clip_image012

Chart I-12, US, Marginally Attached to the Labor Force 12-Month Percentage Change, NSA, 2001-2016

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 9.2 percent and the number of people in job stress could be around 23.9 million, which is 14.2 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 Aug 2015, Jul 2016 and Aug 2016 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 2016. 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 Aug 2015, Jul 2016 and Aug 2016 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 Aug 2015 and was 63.4 percent in Jul 2016 and 62.9 percent in Aug 2016, 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 8.251 million unemployed in Aug 2016 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 16.247 million (Total UEM) and not 7.996 million (UEM) of whom many have been unemployed long term
  • the rate of unemployment is 9.7 percent (Total UEM%) and not 5.0 percent, not seasonally adjusted, or 4.9 percent seasonally adjusted
  • the number of people in job stress is close to 23.9 million by adding the 8.251 million leaving the labor force because they believe they could not find another job, corresponding to 14.2 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 23.923 million in Aug 2016, 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 14.2 percent of the labor force in Aug 2016. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 59.4 percent in Aug 2015, 60.1 percent in Jul 2016 and 59.8 percent in Aug 2016. The number employed in Aug 2016 was 151.804 million (NSA) or 4.489 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 253.854 million in Aug 2016 or by 21.896 million. The number employed increased 3.0 percent from Jul 2007 to Aug 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.4 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 Aug 2016 would result in 161.197 million jobs (0.635 multiplied by noninstitutional civilian population of 253.854 million). There are effectively 9.393 million fewer jobs in Aug 2016 than in Jul 2007, or 161.197 million minus 151.804 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 (http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.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 28 quarters from IIIQ2009 to IIQ2016. 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 IIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp2q16_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 (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.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 IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2709.3 billion than actual $16,570.2 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.2 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/fluctuating-valuations-of-risk.html). US GDP in IIQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,570.2 billion in IIQ2016 or 10.5 percent at the average annual equivalent rate of 1.2 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 Jul 1919 to Jul 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 140.6556 in Jul 2016. The actual index NSA in Jul 2016 is 101.8529, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.3674 in Jul 2016. The output of manufacturing at 101.8529 in Jul 2016 is 21.3 percent below trend under this alternative calculation.

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

 

2006

Aug 2015

Jul 2016

Aug 2016

POP

229

251,096

253,620

253,854

LF

151

157,390

160,705

159,800

PART%

66.2

62.7

63.4

62.9

EMP

144

149,228

152,437

151,804

EMP/POP%

62.9

59.4

60.1

59.8

UEM

7

8,162

8,267

7,996

UEM/LF Rate%

4.6

5.2

5.1

5.0

NLF

77

92,706

92,916

94,054

LF PART 66.2%

 

166,226

167,896

168,051

NLF UEM

 

8,836

7,191

8,251

Total UEM

 

16,998

15,458

16,247

Total UEM%

 

10.2

9.2

9.7

Part Time Economic Reasons

 

6,361

6,157

5,963

Marginally Attached to LF

 

1,812

1,950

1,713

In Job Stress

 

25,171

23,565

23,923

People in Job Stress as % Labor Force

 

15.1

14.0

14.2

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 and 62.4 percent in Dec 2015. The civilian labor force participation rate was 62.9 percent in Aug 2016. 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 (http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.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, 1979-2016

Year

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Nov

Dec

Annual

1979

62.9

63.0

63.2

62.9

62.9

64.5

64.9

64.5

63.8

63.8

63.7

1980

63.3

63.2

63.2

63.2

63.5

64.6

65.1

64.5

63.7

63.4

63.8

1981

63.2

63.2

63.5

63.6

63.9

64.6

65.0

64.6

63.8

63.4

63.9

1982

63.0

63.2

63.4

63.3

63.9

64.8

65.3

64.9

64.1

63.8

64.0

1983

63.3

63.2

63.3

63.2

63.4

65.1

65.4

65.1

64.1

63.8

64.0

1984

63.3

63.4

63.6

63.7

64.3

65.5

65.9

65.2

64.4

64.3

64.4

1985

64.0

64.0

64.4

64.3

64.6

65.5

65.9

65.4

64.9

64.6

64.8

1986

64.2

64.4

64.6

64.6

65.0

66.3

66.6

66.1

65.4

65.0

65.3

1987

64.7

64.8

65.0

64.9

65.6

66.3

66.8

66.5

65.7

65.5

65.6

1988

65.1

65.2

65.2

65.3

65.5

66.7

67.1

66.8

66.2

65.9

65.9

1989

65.8

65.6

65.7

65.9

66.2

67.4

67.7

67.2

66.7

66.3

66.5

1990

66.0

66.0

66.2

66.1

66.5

67.4

67.7

67.1

66.3

66.1

66.5

1991

65.5

65.7

65.9

66.0

66.0

67.2

67.3

66.6

66.0

65.8

66.2

1992

65.7

65.8

66.0

66.0

66.4

67.6

67.9

67.2

66.2

66.1

66.4

1993

65.6

65.8

65.8

65.6

66.3

67.3

67.5

67.0

66.3

66.2

66.3

1994

66.0

66.2

66.1

66.0

66.5

67.2

67.5

67.2

66.7

66.5

66.6

1995

66.1

66.2

66.4

66.4

66.4

67.2

67.7

67.1

66.5

66.2

66.6

1996

65.8

66.1

66.4

66.2

66.7

67.4

67.9

67.2

67.0

66.7

66.8

1997

66.4

66.5

66.9

66.7

67.0

67.8

68.1

67.6

67.1

67.0

67.1

1998

66.6

66.7

67.0

66.6

67.0

67.7

67.9

67.3

67.1

67.0

67.1

1999

66.7

66.8

66.9

66.7

67.0

67.7

67.9

67.3

67.0

67.0

67.1

2000

66.8

67.0

67.1

67.0

67.0

67.7

67.6

67.2

66.9

67.0

67.1

2001

66.8

66.8

67.0

66.7

66.6

67.2

67.4

66.8

66.6

66.6

66.8

2002

66.2

66.6

66.6

66.4

66.5

67.1

67.2

66.8

66.3

66.2

66.6

2003

66.1

66.2

66.2

66.2

66.2

67.0

66.8

66.3

66.1

65.8

66.2

2004

65.7

65.7

65.8

65.7

65.8

66.5

66.8

66.2

66.1

65.8

66.0

2005

65.4

65.6

65.6

65.8

66.0

66.5

66.8

66.5

66.1

65.9

66.0

2006

65.5

65.7

65.8

65.8

66.0

66.7

66.9

66.5

66.4

66.3

66.2

2007

65.9

65.8

65.9

65.7

65.8

66.6

66.8

66.1

66.1

65.9

66.0

2008

65.7

65.5

65.7

65.7

66.0

66.6

66.8

66.4

65.8

65.7

66.0

2009

65.4

65.5

65.4

65.4

65.5

66.2

66.2

65.6

64.9

64.4

65.4

2010

64.6

64.6

64.8

64.9

64.8

65.1

65.3

65.0

64.4

64.1

64.7

2011

63.9

63.9

64.0

63.9

64.1

64.5

64.6

64.3

63.9

63.8

64.1

2012

63.4

63.6

63.6

63.4

63.8

64.3

64.3

63.7

63.5

63.4

63.7

2013

63.3

63.2

63.1

63.1

63.5

64.0

64.0

63.4

62.9

62.6

63.2

2014

62.5

62.7

62.9

62.6

62.9

63.4

63.5

63.0

62.8

62.5

62.9

2015

62.5

62.5

62.5

62.6

63.0

63.1

63.2

62.7

62.5

62.4

62.7

2016

62.3

62.7

62.8

62.7

62.7

63.2

63.4

62.9

     

Source: US Bureau of Labor Statistics

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

clip_image013

Chart I-12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2016

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.

clip_image014

Chart I-12c, US, Civilian Noninstitutional Population, Thousands, NSA, 1948-2016

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.

clip_image015

Chart I-12d, US, Labor Force, Thousands, NSA, 1948-2016

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 2016. 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.

clip_image016

Chart I-12E, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1948-2016

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 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. 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 28 quarters from IIIQ2009 to IIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the first estimate of GDP for IIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp2q16_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.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 IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2704.4 billion than actual $16,575.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/07/fluctuating-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html). US GDP in IIQ2016 is 14.0 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,575.1 billion in IIQ2016 or 10.6 percent at the average annual equivalent rate of 1.2 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Jun 1919 to Jun 2016. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.4587 in Jun 2016. The actual index NSA in Jun 2016 is 105.6646, which is 25.3 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.1203 in Jun 2016. The output of manufacturing at 105.6646 in Jun 2016 is 18.2 percent below trend under this alternative calculation.

clip_image017

Chart I-13, US, Employment Level, Thousands, SA, 1948-2016

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.

clip_image018

Chart I-14, US, Civilian Labor Force, SA, 1948-2016, Thousands

Source: US Bureau of Labor Statistics

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

Chart I-15 for the period from 1948 to 2016. 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.

clip_image019

Chart I-15, US, Civilian Labor Force Participation Rate, SA, 1948-2016, %

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.

clip_image020

Chart I-16, US, Unemployed, SA, 1948-2016, 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 2016. 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 5.0 percent in Aug 2016.

clip_image021

Chart I-17, US, Unemployment Rate, SA, 1948-2016

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.

clip_image022

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 59.8 NSA in Aug 2016. There is no comparable decline followed by stabilization during a cyclical expansion in Chart I-19.

clip_image023

Chart I-19, US, Employment-Population Ratio, 1948-2016

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.

clip_image024

Chart I-20, US, Part-Time for Economic Reasons, NSA, 1955-2016, 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. Actual annual equivalent GDP growth in the four quarters of 2012, twelve quarters from IQ2013 to IVQ2015, IQ2016 and IIQ2016 is 2.0 percent and 1.2 percent in the four quarters ending in IIQ2016. 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 2.0 percent in 2016 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20160615.pdf) with less reliable forecast of 1.9 to 2.2 percent in 2017 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20160615.pdf). Growth of GDP in the expansion from IIIQ2009 to IIQ2016 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

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

Characteristics of the four cyclical contractions are in Table I-5 with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.7 percent, which is almost equal to the decline of 4.2 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

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

 

Number of Quarters

Cumulative Percentage Contraction

Average Percentage Rate

IIQ1953 to IIQ1954

3

-2.4

-0.8

IIIQ1957 to IIQ1958

3

-3.0

-1.0

IVQ1973 to IQ1975

5

-3.1

-0.6

IQ1980 to IIIQ1980

2

-2.2

-1.1

IIIQ1981 to IVQ1982

4

-2.5

-0.64

IVQ2007 to IIQ27009

6

-4.2

-0.72

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

Table I-7 shows the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the twenty-eight quarters of the current cyclical expansion from IIIQ2009 to IIQ2016. 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 IQ1093 to IVQ1989

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 and 2.6 percent in 2015 (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 and at 7.8 percent from IQ1983 to IVQ1983. GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the four quarters of 2012, the four quarters of 2013, the four quarters of 2014, the four quarters of Q2015, IQ2016 and IIQ2016 accumulated to 9.1 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IIQ2016 of $16,575.1 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/18: {[($16,575.1/$15,190.3)4/18 -1]100 = 2.0 percent}.

Table I-7 shows that GDP grew 15.5 percent in the first twenty-seven quarters of expansion from IIIQ2009 to IIQ2016 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

13

15

16

17

18

19

20

21

22

23

24

25

26

27

28

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

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

First Four Quarters IQ1983 to IVQ1983

4

7.8

 

Average First Four Quarters in Four Expansions*

 

7.7

 

IIIQ2009 to IIQ2016

28

15.5

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.

clip_image025

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 Aug 2016 was 151.804 million (NSA) or 4.489 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 253.854 million in Aug 2016 or by 21.896 million. The number employed increased 3.0 percent from Jul 2007 to Aug 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.4 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 Aug 2016 would result in 161.197 million jobs (0.635 multiplied by noninstitutional civilian population of 253.854 million). There are effectively 9.393 million fewer jobs in Aug 2016 than in Jul 2007, or 161.197 million minus 151.804 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.

clip_image001[1]

Chart I-22, US, Employed, Thousands, 2001-2016

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.

clip_image026

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 2013-2016. 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 2.3 percent higher at 159.800 million in Aug 2016 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 159.800 million in Aug 2016 to the noninstitutional population of 253.854 million in Aug 2016 was 62.9 percent. The labor force of the US in Aug 2016 corresponding to 66.8 percent of participation in the population would be 169.574 million (0.668 x 253.854). The difference between the measured labor force in Aug 2016 of 159.800 million and the labor force in Aug 2016 with participation rate of 66.8 percent (as in Jul 2007) of 169.574 million is 9.774 million. The level of the labor force in the US has stagnated and is 9.774 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.

clip_image003[1]

Chart I-24, US, Civilian Labor Force, Thousands, 2001-2016

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.

clip_image027

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.

clip_image005[1]

Chart I-26, US, Civilian Labor Force Participation Rate, 2001-2016, %

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.

clip_image028

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 2016. 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, 8.704 million in Dec 2014 and 7.904 million in Dec 2015. The number unemployed SA stood at 7.849 million in Aug 2016. 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 7,996 million in Aug 2016.

clip_image006[1]

Chart I-28, US, Unemployed Thousands 2001-2016

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.

clip_image029

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 4.9 percent in Aug 2016.

clip_image007[1]

Chart I-30, US, Unemployment Rate, 2001-2016, %

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.

clip_image030

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, 58.6 in Dec 2012, 58.6 in Dec 2013, 59.2 in Dec 2014 and 59.5 in Dec 2015, as shown in Chart I-32. The employment-population ratio reached 59.7 in Aug 2016. 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 59.8 percent in Aug 2016.

clip_image031

Chart I-32, US, Employment Population Ratio, 2001-2016, %

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.

clip_image032

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 remained at around 6 million during the expansion compared with somewhat above 1 million before the contraction, falling to 2.006 million in Aug 2016 seasonally adjusted and 1.996 million not seasonally adjusted.

clip_image033

Chart I-34, US, Number Unemployed for 27 Weeks or More, 2001-2016, 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.

clip_image034

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 5.963 million not seasonally adjusted in Aug 2016.

clip_image009[1]

Chart I-36, US, Part-Time for Economic Reasons, 2001-2016, Thousands

Source: US Bureau of Labor Statistics

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 1.713 million in Aug 2016.

clip_image011[1]

Chart I-37, US, Marginally Attached to the Labor Force, 2001-2016

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 2015. The civilian noninstitutional population grew by 44.0 percent from 174.215 million in 1983 to 250.801 million in 2015 and labor force higher by 40.9 percent, growing from 111.550 million in 1983 to 157.130 million in 2015. Total nonfarm payroll employment seasonally adjusted (SA) increased 151,000 in Aug 2016 and private payroll employment increased 126,000. The average monthly number of nonfarm jobs created from Aug 2014 to Aug 2015 was 238,167 using seasonally adjusted data, while the average number of nonfarm jobs created from Aug 2015 to Aug 2016 was 203,917, or decrease by 14.4 percent. The average number of private jobs created in the US from Aug 2014 to Aug 2015 was 223,083, using seasonally adjusted data, while the average from Aug 2015 to Aug 2016 was 190,250, or decrease by 14.7 percent. This blog calculates the effective labor force of the US at 166.226 million in Aug 2015 and 168.051 million in Aug 2016 (Table I-4), for growth of 1.825 million at average 152,083 per month. The difference between the average increase of 190.250 new private nonfarm jobs per month in the US from Aug 2015 to Aug 2016 and the 152,083 average monthly increase in the labor force from Aug 2015 to Aug 2016 is 38,167 monthly new jobs net of absorption of new entrants in the labor force. There are 23.923 million in job stress in the US currently. Creation of 38,167 new jobs per month net of absorption of new entrants in the labor force would require 627 months to provide jobs for the unemployed and underemployed (23.923 million divided by 38,167) or 52 years (627 divided by 12). The civilian labor force of the US in Aug 2016 not seasonally adjusted stood at 159.800 million with 7.996 million unemployed or effectively 16.247 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 168.051 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 2.2 years (1 million divided by product of 38,167 by 12, which is 458,004). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.990 million (0.05 times labor force of 159.800 million). New net job creation would be 0.006 million (7.996 million unemployed minus 7.990 million unemployed at rate of 5 percent) that at the current rate would take 0.01 years (0.006 million divided by 458,004). Under the calculation in this blog, there are 16.247 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 168.051 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 7.063 million jobs net of labor force growth that at the current rate would take 17.1 years (16.247 million minus 0.05(168.051 million) = 7.844 million divided by 458,004 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 Aug 2016 was 151.804 million (NSA) or 4.489 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 253.854 million in Aug 2016 or by 21.896 million. The number employed increased 3.0 percent from Jul 2007 to Aug 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.4 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 Aug 2016 would result in 161.197 million jobs (0.635 multiplied by noninstitutional civilian population of 253.854 million). There are effectively 9.393 million fewer jobs in Aug 2016 than in Jul 2007, or 161.197 million minus 151.804 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/2016/08/rising-valuations-of-risk-financial.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 IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2709.3 billion than actual $16,570.2 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.2 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/fluctuating-valuations-of-risk.html). US GDP in IIQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,570.2 billion in IIQ2016 or 10.5 percent at the average annual equivalent rate of 1.2 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 Jul 1919 to Jul 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 140.6556 in Jul 2016. The actual index NSA in Jul 2016 is 101.8529, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.3674 in Jul 2016. The output of manufacturing at 101.8529 in Jul 2016 is 21.3 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

19

-791

28

19

Feb

68

-5

-75

-86

-703

-69

-54

Mar

105

-130

172

-78

-823

163

121

Apr

73

-280

276

-210

-686

243

192

May

10

-45

277

-185

-351

522

95

Jun

197

-243

379

-165

-470

-133

123

Jul

112

-342

418

-209

-329

-70

101

Aug

-36

-158

-308

-266

-212

-34

115

Sep

-87

-181

1115

-452

-219

-52

121

Oct

-99

-277

271

-473

-200

257

207

Nov

-209

-123

353

-769

-7

123

133

Dec

-278

-14

356

-695

-279

88

109

     

1984

   

2011

Private

Jan

   

446

   

42

50

Feb

   

481

   

188

231

Mar

   

275

   

225

248

Apr

   

363

   

346

354

May

   

308

   

73

128

Jun

   

379

   

235

200

Jul

   

313

   

70

185

Aug

   

242

   

107

139

Sep

   

310

   

246

280

Oct

   

286

   

202

187

Nov

   

349

   

146

173

Dec

   

128

   

207

224

     

1985

   

2012

Private

Jan

   

266

   

338

347

Feb

   

124

   

257

261

Mar

   

346

   

239

237

Apr

   

196

   

75

90

May

   

274

   

115

130

Jun

   

146

   

87

72

Jul

   

190

   

143

160

Aug

   

193

   

190

174

Sep

   

203

   

181

180

Oct

   

188

   

132

164

Nov

   

209

   

149

171

Dec

   

167

   

243

233

     

1986

   

2013

Private

Jan

   

125

   

190

203

Feb

   

107

   

311

297

Mar

   

94

   

135

150

Apr

   

187

   

192

193

May

   

127

   

218

225

Jun

   

-94

   

146

173

Jul

   

318

   

140

162

Aug

   

114

   

269

242

Sep

   

347

   

185

179

Oct

   

186

   

189

203

Nov

   

186

   

291

280

Dec

   

205

   

45

71

     

1987

   

2014

Private

Jan

   

172

   

187

197

Feb

   

232

   

168

158

Mar

   

249

   

272

261

Apr

   

338

   

310

282

May

   

226

   

213

215

Jun

   

172

   

306

267

Jul

   

347

   

232

244

Aug

   

171

   

218

231

Sep

   

228

   

286

237

Oct

   

492

   

200

190

Nov

   

232

   

331

324

Dec

   

294

   

292

279

     

1988

   

2015

Private

Jan

   

94

   

221

214

Feb

   

453

   

265

252

Mar

   

276

   

84

90

Apr

   

245

   

251

241

May

   

229

   

273

256

Jun

   

363

   

228

226

Jul

   

222

   

277

245

Aug

   

124

   

150

123

Sep

   

339

   

149

162

Oct

   

268

   

295

304

Nov

   

339

   

280

279

Dec

   

290

   

271

259

     

1989

   

2016

Private

Jan

   

262

   

168

155

Feb

   

258

   

233

222

Mar

   

193

   

186

167

Apr

   

173

   

144

147

May

   

118

   

24

-1

Jun

   

116

   

271

238

Jul

   

40

   

275

225

Aug

   

49

   

151

126

Sep

   

250

       

Oct

   

111

       

Nov

   

277

       

Dec

   

96

       

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 2013-2016 while population growth continued.

clip_image035

Chart I-38, US, Total Nonfarm Payroll Jobs SA 2001-2016

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.

clip_image036

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.

clip_image037

Chart I-40, US, Total Private Payroll Jobs SA 2001-2016

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.

clip_image038

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 Aug 2015 to Aug 2016, not seasonally adjusted (NSA), are in Table I-9. Total nonfarm employment increased by 2,451,000 (row A, column Change), consisting of growth of total private employment by 2,266,000 (row B, column Change) and increase by 185,000 of government employment (row C, column Change). Monthly average growth of private payroll employment has been 188,833, which is mediocre relative to 24 to 30 million in job stress, while total nonfarm employment has grown on average by only 204,250 per month, which does not significantly reduce job stress with 152,083 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 decreased by 38,000, at the monthly rate of minus 3167 while private service providing employment grew by 2,246,000, at the monthly average rate of 187,167. An important feature in Table I-9 is that jobs in professional and business services increased 365,000 with temporary help services increasing 33,000. 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 425,000 jobs in 12 months. An important characteristic is that the loss of government jobs has stabilized in federal government with increase of 38,000 jobs while states increased 14,000 jobs and local government added 133,000 jobs. Local government provides the bulk of government jobs, 13.502 million, while federal government provides 2.804 million and states’ government 4.823 million.

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

 

Aug 2015

Aug 2016

Change

A Total Nonfarm

141,973

144,424

2,451

B Total Private

121,029

123,295

2,266

B1 Goods Producing

19,957

19,977

20

B1a

Manufacturing

12,409

12,371

-38

B2 Private service providing

101,072

103,318

2,246

B2a Wholesale Trade

5,908

5,953

45

B2b Retail Trade

15,669

15,954

285

B2c Transportation & Warehousing

4,818

4,871

53

B2d Financial Activities

8,208

8,379

171

B2e Professional and Business Services

19,883

20,248

365

B2e1 Temporary help services

2,914

2,947

33

B2f Health Care & Social Assistance

18,646

19,199

553

B2g Leisure & Hospitality

15,802

16,235

433

C Government

20,944

21,129

185

C1 Federal

2,766

2,804

38

C2 State

4,809

4,823

14

C3 Local

13,369

13,502

133

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 Jul 2016 and

Aug 2016. 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 151,000 SA total nonfarm jobs created in Aug 2016 relative to Jul 2016 actually correspond to increase of 224,000 jobs NSA, as shown in row A. Most of this difference in Jan 2016 is due to the necessary benchmark and seasonal adjustments in the beginning of every year. The 126,000 total private payroll jobs SA created in Aug 2016 relative to Jul 2016 actually correspond to increase of 33,000 jobs NSA. The analysis of NSA job creation in the prior Table I-9 does show improvement over the 12 months ending in Jul 2016 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

 

Jul               2016 SA

Aug   2016 SA

Jul   2016 NSA

Aug   2016 NSA

A Total Nonfarm

144,447

144,598

151

144,200

144,424

224

B Total Private

122,259

122,385

126

123,262

123,295

33

B1 Goods Producing

19,624

19,600

-24

19,978

19,977

-1

B1a Constr.

6,646

6,640

-6

6,915

6,917

2

B Mfg

12,295

12,281

-14

12,370

12,371

1

B2 Private Service Providing

102,635

102,785

150

103,284

103,318

34

B2a Wholesale Trade

5,922

5,926

4

5,957

5,953

-4

B2b Retail Trade

15,953

15,968

15

15,976

15,954

-22

B2c Couriers     & Mess.

623

627

4

592

602

10

B2d Health-care & Social Assistance

19,193

19,229

36

19,147

19,199

52

B2De Profess. & Business Services

20,262

20,284

22

20,376

20,428

52

B2De1 Temp Help Services

2,920

2,917

-3

2,888

2,947

59

B2f Leisure & Hospit.

15,547

15,576

29

16,265

16,235

-30

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 38,000 from Aug 2015 to
Aug 2016 or at the average monthly rate of minus 3167. There are effects of the weaker economy and international trade together with the yearly adjustment of labor statistics.  Industrial production increased 0.7 percent in Jul 2016 and increased 0.4 percent in Jun 2016 after decreasing 0.2 percent in May 2016, with all data seasonally adjusted. 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.”

Manufacturing fell 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increased 16.0 percent from the trough in Apr 2009 to Dec 2015. Manufacturing grew 16.5 percent from the trough in Apr 2009 to Jul 2016. Manufacturing in Jul 2016 is lower by 9.5 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 IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2709.3 billion than actual $16,570.2 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.2 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/fluctuating-valuations-of-risk.html). US GDP in IIQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,570.2 billion in IIQ2016 or 10.5 percent at the average annual equivalent rate of 1.2 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 Jul 1919 to Jul 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 140.6556 in Jul 2016. The actual index NSA in Jul 2016 is 101.8529, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.3674 in Jul 2016. The output of manufacturing at 101.8529 in Jul 2016 is 21.3 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 IQ2016. Most of US national income is in the form of services. In Aug 2016, there were 144.424 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 123.295 million NSA in Aug 2016 accounted for 85.4 percent of total nonfarm jobs of 144.424 million, of which 12.371 million, or 10.0 percent of total private jobs and 8.6 percent of total nonfarm jobs, were in manufacturing. Private service-providing jobs were 103.318 million NSA in Aug 2016, or 71.5 percent of total nonfarm jobs and 83.8 percent of total private-sector jobs. Manufacturing has share of 10.5 percent in US national income in IQ2016 and durable goods 6.1 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 IQ2016

% Total

SAAR
IIQ2016

% Total

National Income WCCA

15,758.8

100.0

15,871.5

100.0

Domestic Industries

15,586.3

98.9

15,675.5

98.8

Private Industries

13,741.8

87.2

13,821.1

87.1

Agriculture

128.0

0.8

   

Mining

190.1

1.2

   

Utilities

165.9

1.1

   

Construction

760.4

4.8

   

Manufacturing

1652.8

10.5

   

Durable Goods

969.0

6.1

   

Nondurable Goods

683.8

4.3

   

Wholesale Trade

948.6

6.0

   

Retail Trade

1111.4

7.1

   

Transportation & WH

498.4

3.2

   

Information

569.7

3.6

   

Finance, Insurance, RE

2778.7

17.6

   

Professional & Business Services

2199.4

14.0

   

Education, Health Care

1604.4

10.2

   

Arts, Entertainment

669.6

4.2

   

Other Services

464.3

2.9

   

Government

1844.5

11.7

1854.4

11.7

Rest of the World

172.5

1.1

196.0

1.2

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.

clip_image039

Chart I-42, US, Output of Durable Manufacturing, 1972-2016

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 141,865 million in 2015, by 3.866 million or 2.8 percent. The US noninstitutional population or in condition to work increased from 231.867 million in 2007 to 250,801 million in 2015, by 18.934 million or 8.2 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 2015 corresponding to the ratio of 59.5 of nonfarm jobs/noninstitutional population would be 149.227 million (0.595x250.801). The difference between actual nonfarm jobs of 141.865 million in 2015 and nonfarm jobs of 149.227 million that are equivalent to 59.5 percent of the noninstitutional population as in 2007 is 7.362 million fewer jobs. 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 IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2709.3 billion than actual $16,570.2 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.2 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/fluctuating-valuations-of-risk.html). US GDP in IIQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,570.2 billion in IIQ2016 or 10.5 percent at the average annual equivalent rate of 1.2 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 Jul 1919 to Jul 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 140.6556 in Jul 2016. The actual index NSA in Jul 2016 is 101.8529, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.3674 in Jul 2016. The output of manufacturing at 101.8529 in Jul 2016 is 21.3 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

141,865

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

Chart I-43 provides annual nonfarm jobs from 2000 to 2015. Cyclically slow growth in the expansion since IIIQ2009 has not been sufficient to recover nonfarm jobs. Because of population growth, there are 7.362 million fewer nonfarm jobs in the US in 2015 than in 2007.

clip_image040

Chart I-43, US, Annual Nonfarm Jobs, NSA, Thousands, 2000-2015

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.

clip_image041

Chart I-44, US, Annual Nonfarm Jobs, NSA, Thousands, 1980-1995

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: 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 $25.12/hour in Aug 2015 to $25.73/hour in Aug 2016, or by 2.4 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 68.8 percent of GDP (Table I-10 at http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft_31.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), (Section II 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 0.1 percent from $25.70 in Jul 2016 to $25.73 in Aug 2016. Average private weekly earnings increased $13.39 from $869.15 in Aug 2015 to $882.54 in Aug 2016 or 1.5 percent and decreased $1.54 from $884.08 in Jul 2016 to $882.54 in Aug 2016 or minus 0.2 percent. The inflation-adjusted wage bill can only be calculated for Jul, 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 $24.84 in Jul 2015 to $25.54 in Jul 2016 or by 2.8 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 34.5 in Jul 2015 and 34.4 in Jul 2016 (http://www.bls.gov/data/; see Table IB-2 below). The wage bill increased 2.5 percent in the 12 months ending in Jul 2016:

{[(wage bill in Jul 2016)/(wage bill in Jul 2015)]-1}100 =

{[($25.54x34.4)/($24.84x34.5)]-1]}100

= {[($878.58)/($856.98]-1}100 = 2.5%

CPI inflation was 0.8 percent in the 12 months ending in Jul 2016 (http://www.bls.gov/cpi/) for an inflation-adjusted wage-bill change of 2.2 percent :{[(1.025/1.008)-1]100 = 1.7%} (see Table IB-5 below for Jul 2016 with minor rounding difference). The wage bill for Aug 2016 before inflation adjustment decreased 0.1 percent relative to the wage bill for Aug 2015:

{[(wage bill in Aug 2015)/(wage bill in Aug 2015)]-1}100 =

{[($25.53x34.4)/($25.05x35.1)]-1]}100

= {[$878.23)/$879.26]-1}100 = -0.1%

Average hourly earnings increased 1.9 percent from Aug 2015 to Aug 2016 {[($25.53/$25.05) – 1]100 = 1.9%} while hours worked decreased 2.0 percent {[(34.4/35.1) – 1]100 = -2.0%}. The increase of the wage bill is the product of the increase of hourly earnings of 1.9 percent and increase of hours worked of minus 2.0 percent {[(1.019x0.980) -1]100 = -0.1%} 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 (http://cmpassocregulationblog.blogspot.com/2016/08/interest-rate-policy-uncertainty-and.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

Aug 2015

Jun 2016

Jul 2016

Aug 2016

Total Private

$25.12

$25.62

$25.70

$25.73

Goods Producing

$26.33

$26.90

$26.95

$26.96

Service Providing

$24.83

$25.32

$25.41

$25.45

Average Weekly Earnings

       

Total Private

$869.15

$881.33

$884.08

$882.54

Goods Producing

$1,063.73

$1,081.38

$1,086.09

$1,078.40

Service Providing

$829.32

$843.16

$846.15

$844.94

Average Weekly Hours

       

Total Private

34.6

34.4

34.4

34.3

Goods Producing

40.4

40.2

40.3

40.0

Service Providing

33.4

33.3

33.3

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 34.4 in Aug 2016. 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 2006-2016

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

34.9

34.3

34.3

34.8

34.5

2013

34.0

34.2

34.3

34.3

34.3

34.9

34.4

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

         

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart IB-1, US, Average Weekly Hours of All Employees, SA 2006-2016

Source: US Bureau of Labor Statistics

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

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.

clip_image042

Chart IB-1, US, Average Weekly Hours of All Employees, SA 2006-2016

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 1.2 percent in Feb 2012 and 0.6 percent in Mar 2012. There was a gain of 0.6 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 1.3 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 fell 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 0.5 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 2.0 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 2.5 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 1.4 percent in the 12 months ending in Jun 2015 and increased 2.0 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 2.3 percent in the 12 months ending in Sep 2015. Real hourly earnings increased 2.4 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 1.9 percent in the 12 months ending in Dec 2015 and increased 1.2 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 are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (http://cmpassocregulationblog.blogspot.com/2016/08/interest-rate-policy-uncertainty-and.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.html) originating in weak economic growth (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.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

$20.76

3.4

2.8

0.6

Apr

$20.99

3.0

2.6

0.4

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

$21.31

3.4

4.1

-0.7

2010

       

Jan

$22.51

2.1

2.6

-0.5

Feb

$22.57

1.5

2.1

-0.6

Mar

$22.49

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

1.8

1.2

0.6

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

$23.00

1.9

2.1

-0.2

Mar

$22.90

1.8

2.7

-0.9

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

1.7

2.9

-1.2

Mar

$23.39

2.1

2.7

-0.6

Apr

$23.62

2.9

2.3

0.6

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

$23.59

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

$23.91

2.2

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

$23.93

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

$24.17

2.1

1.2

0.9

Oct

$24.05

2.3

1.0

1.3

Nov

$24.12

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

$24.31

2.1

2.1

0.0

Jun

$24.42

2.0

2.1

-0.1

Jul

$24.31

2.1

2.0

0.1

Aug

$24.33

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

$24.79

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

$25.06

2.0

0.0

2.0

Mar

$25.05

2.2

-0.1

2.3

Apr

$24.95

2.3

-0.2

2.5

May

$24.89

2.4

0.0

2.4

Jun

$24.78

1.5

0.1

1.4

Jul

$24.84

2.2

0.2

2.0

Aug

$25.05

3.0

0.2

2.8

Sep

$25.07

2.3

0.0

2.3

Oct

$25.16

2.6

0.2

2.4

Nov

$25.39

2.4

0.5

1.9

Dec

$25.22

2.6

0.7

1.9

2016

       

Jan

$25.52

2.6

1.4

1.2

Feb

$25.51

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

$25.54

2.8

0.8

2.0

Aug

$25.53

1.9

   

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 0.6 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 0.2 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 1.1 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 1.3 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 changed 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 1.4 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 2.0 percent in the 12 months ending in Feb 2015. Real hourly earnings increased 2.3 percent in the 12 months ending in Mar 2015 and increased 2.5 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 2.1 percent in the 12 months ending in Jul 2015 and increased 2.7 percent in the 12 months ending in Aug 2015. Real hourly earnings increased 2.4 percent in the 12 months ending in Sep 2015. Real hourly earnings increased 2.4 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 1.1 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 0.8 percent in the 12 months ending in Mar 2016. Real hourly earnings increased 1.4 percent in the 12 months ending in Apr 2016 and increased 2.1 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 1.9 percent in the 12 months ending in Jul 2016. Real hourly earnings are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (http://cmpassocregulationblog.blogspot.com/2016/07/oscillating-valuations-of-risk.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2016/07/oscillating-valuations-of-risk.html) originating in weak economic growth (http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.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

Feb

Mar

Apr

May

Jun

Jul

Dec

2006

 

10.05

10.11

9.91

9.88

9.97

10.21

2007

10.21

10.11

10.16

9.99

9.97

10.05

10.15

2008

10.09

10.08

9.98

9.88

9.82

9.75

10.45

2009

10.48

10.45

10.38

10.31

10.18

10.22

10.36

2010

10.41

10.33

10.33

10.36

10.25

10.28

10.38

2011

10.39

10.25

10.21

10.21

10.11

10.15

10.29

2012

10.28

10.20

10.27

10.15

10.14

10.25

10.39

∆%12M

-1.1

-0.5

0.6

-0.6

0.3

1.0

1.0

2013

10.30

10.24

10.29

10.22

10.25

10.19

10.43

∆%12M

0.2

0.4

0.2

0.7

1.1

-0.6

0.4

2014

10.47

10.37

10.29

10.22

10.25

10.20

10.47

∆%12M

1.7

1.3

0.0

0.0

0.0

0.1

0.4

2015

10.68

10.61

10.55

10.47

10.38

10.41

10.66

∆%12M

2.0

2.3

2.5

2.4

1.3

2.1

1.8

2016

10.76

10.70

10.70

10.69

10.55

10.61

 

∆%12M

0.7

0.8

1.4

2.1

1.6

1.9

 

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 $10.34 in 2009 and $10.35 in 2010 to $10.24 in 2011 and $10.24 again in 2012 or loss of 1.1 percent (data in http://www.bls.gov/data/). Annual real hourly earnings increased 0.5 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 4.7 percent from 2007 to 2015 at the rate of 0.6 percent per year. Annual real hourly earnings increased 2.1 percent from 2009 to 2015 at the rate of 0.4 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 (http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.html), stagnating/declining real wages and 23.9 million unemployed or underemployed (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html) because of mediocre economic growth (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.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.

clip_image043

Chart IB-2, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2016

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 and Jan-Jul 2016.

clip_image044

Chart IB-3, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2016

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 2.1 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 0.7 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 1.4 percent in the 12 months ending in Jul 2013. Real weekly earnings increased 0.8 percent in the 12 months ending in Aug 2013, 0.9 percent in the 12 months ending in Sep 2013 and 1.6 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 0.4 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 2.6 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 2.5 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 0.2 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 1.8 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 1.2 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 0.6 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 2.7 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. 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/2016/07/oscillating-valuations-of-risk.html). On an annual basis, average weekly earnings in constant 1982-1984 dollars increased from $347.19 in 2007 to $354.30 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 $352.96 in 2010 fell 0.4 percent to $351.68 in 2012. Annual average weekly earnings increased from $347.19 in 2007 to $356.94 in 2014 or by 2.8 at the average rate of 0.4 percent. Annual average weekly earnings in constant increased from $347.19 in 2007 to $364.78 in 2015 by 5.1 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 23.6 million unemployed or underemployed (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html) in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.html) because of mediocre economic growth (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.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 2007-2016

Year

Feb

Mar

Apr

May

Jun

Jul

2007

347.19

345.74

350.37

342.59

343.92

349.84

2008

343.22

348.71

341.17

337.84

341.61

334.32

2009

356.19

354.13

347.66

346.28

343.10

345.45

2010

349.89

349.29

351.37

356.33

349.50

351.55

2011

353.35

349.44

349.14

353.10

346.61

349.30

2012

351.52

348.72

355.19

347.04

348.83

355.63

∆%12M

-0.5

-0.2

1.7

-1.7

0.6

1.8

2013

352.21

351.29

352.84

350.44

357.66

350.63

∆%12M

0.2

0.7

-0.7

1.0

2.5

-1.4

2014

360.14

359.79

354.05

351.52

357.58

352.03

∆%12M

2.3

2.4

0.3

0.3

0.0

0.4

2015

369.41

368.14

362.76

360.05

358.25

359.09

∆%12M

2.6

2.3

2.5

2.4

0.2

2.0

2016

366.87

366.08

367.00

369.86

362.79

365.09

∆%12M

-0.7

-0.6

1.2

2.7

1.3

1.7

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 2012-2016. The increase in the final segment is mostly because of collapse of commodity prices in reversals of carry trade exposures. 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.

clip_image045

Chart IB-4, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2016

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. (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).

clip_image046

Chart IB-5, US, Average Weekly Earnings of All Employees NSA in Constant Dollars of 1982-1984 12-Month Percent Change, NSA 2007-2016

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

   II IB Stagnating Real Disposable Income and Consumption Expenditures. The Bureau of Economic Analysis (BEA) provides important revisions and enhancements of data on personal income and outlays since 1929 (http://www.bea.gov/iTable/index_nipa.cfm). There are waves of changes in personal income and expenditures in Table IB-1 that correspond somewhat to inflation waves observed worldwide (http://cmpassocregulationblog.blogspot.com/2016/08/interest-rate-policy-uncertainty-and.html) because of the influence through price indexes. There are wide fluctuations in Nov and Dec 2012 by the rush to realize income of all forms in anticipation of tax increases beginning in Jan 2013. There is major distortion in Jan 2013 because of higher contributions in payrolls to government social insurance that caused sharp reduction in personal income and disposable personal income. The Bureau of Economic Analysis (BEA) explains as follows (page 3 http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

“The February and January [2013] changes in disposable personal income (DPI) mainly reflected the effect of special factors in January, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to November and to December [2012] in anticipation of changes in individual tax rates.”

In the first wave in Jan-Apr 2011 with relaxed risk aversion, nominal personal income (NPI) increased at the annual equivalent rate of 7.7 percent, nominal disposable personal income (NDPI) at 5.2 percent and nominal personal consumption expenditures (NPCE) at 5.9 percent. Real disposable income (RDPI) increased at the annual equivalent rate of 1.2 percent and real personal consumption expenditures (RPCE) rose at annual equivalent 1.5 percent. In the second wave in May-Aug 2011 under risk aversion, NPI rose at annual equivalent 4.9 percent, NPDI at 4.9 percent and NPCE at 3.7 percent. RDPI increased at 1.8 percent annual equivalent and RPCE at 0.9 percent annual equivalent. With mixed shocks of risk aversion in the third wave from Sep to Dec 2011, NPI rose at 2.4 percent annual equivalent, NDPI at 2.4 percent and NPCE at 2.1 percent. RDPI increased at 1.5 percent annual equivalent and RPCE at 1.5 percent annual equivalent. In the fourth wave from Jan to Mar 2012, NPI increased at 8.3 percent annual equivalent, NDPI at 9.6 percent and NPCE at 4.3 percent. Real disposable income (RDPI) is more dynamic in the revisions, growing at 4.9 percent annual equivalent and RPCE at 2.1 percent. The policy of repressing savings with zero interest rates stimulated growth of nominal consumption (NPCE) at the annual equivalent rate of 4.3 percent and real consumption (RPCE) at 2.1 percent. In the fifth wave in Apr-Jul 2012, NPI increased at annual equivalent 1.2 percent, NDPI at 1.2 percent and RDPI at 0.9 percent. Financial repression failed to stimulate consumption with NPCE growing at 1.2 percent annual equivalent and RPCE at 0.9 percent. In the sixth wave in Aug-Oct 2012, in another wave of carry trades into commodity futures, NPI increased at 8.3 percent annual equivalent and NDPI increased at 7.9 percent while real disposable income (RDPI) increased at 3.7 percent annual equivalent. NPCE increased at 4.1 percent and RPCE changed at 0.0 percent. Data for Nov-Dec 2012 have illusory increases: “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf). In the seventh wave, anticipations of tax increases in Jan 2013 caused exceptional income gains that increased personal income to annual equivalent 25.3 percent in Nov-Dec 2012, nominal disposable income at 25.3 percent and real disposable personal income at 26.0 percent with likely effects on nominal personal consumption that increased at 2.4 percent and real personal consumption at 3.0 percent with subdued prices. The numbers in parentheses show that without the exceptional effects NDPI (nominal disposable personal income) increased at 5.5 percent and RDPI (real disposable personal income) at 8.7 percent. In the eighth wave, nominal personal income fell 5.2 percent in Jan 2013 or at the annual equivalent rate of decline of 47.3 percent; nominal disposable personal income fell 6.1 percent or at the annual equivalent rate of decline of 53.0 percent; real disposable income fell 6.2 percent or at the annual rate of decline of 53.6 percent; nominal personal consumption expenditures increased 0.3 percent or at the annual equivalent rate of 3.7 percent; and real personal consumption expenditures increased 0.2 percent or at the annual equivalent rate of 2.4 percent. The savings rate fell significantly from 11.0 percent in Dec 2012 to 4.9 percent in Jan 2013. The Bureau of Economic Analysis explains as follows (http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0113.pdf 3):

“Contributions for government social insurance -- a subtraction in calculating personal income -- increased $126.7 billion in January, compared with an increase of $6.3 billion in December. The

January estimate reflected increases in both employer and employee contributions for government social insurance. The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base; together, these changes added $12.8 billion to January. As noted above, employer contributions were boosted $5.9 billion in January, so the total contribution of special factors to the January change in contributions for government social insurance was $132.8 billion”

Further explanation is provided by the Bureau of Economic Analysis (http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf 2-3):

“Contributions for government social insurance -- a subtraction in calculating personal income --increased $6.4 billion in February, compared with an increase of $126.8 billion in January. The

January estimate reflected increases in both employer and employee contributions for government social insurance. The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base; together, these changes added $12.9 billion to January. Employer contributions were boosted $5.9 billion in January, which reflected increases in the social security taxable wage base (from $110,100 to $113,700), in the tax rates paid by employers to state unemployment insurance, and in employer contributions for the federal unemployment tax and for pension guaranty. The total contribution of special factors to the January change in contributions for government social insurance was $132.9 billion. The January change in disposable personal income (DPI) mainly reflected the effect of special factors, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to December in anticipation of changes in individual tax rates. Excluding these special factors and others, which are discussed more fully below, DPI increased $46.8 billion in February, or 0.4 percent, after increasing $15.8 billion, or 0.1 percent, in January.”

The increase was provided in the “fiscal cliff” law H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf). In the ninth wave in Feb-Mar 2013, nominal personal income increased at 3.0 percent and nominal disposable income at 2.4 percent annual equivalent, while real disposable income increased at 0.6 percent annual equivalent. Nominal personal consumption expenditures grew at 1.8 percent annual equivalent and real personal consumption expenditures at 0.0 percent annual equivalent. The savings rate collapsed from 7.8 percent in Oct 2012, 8.8 percent in Nov 2012 and 11.0 percent in Dec 2012 to 4.9 percent in Jan 2013, 4.7 percent in Feb 2013 and 4.8 percent in Mar 2013. In the tenth wave from Apr to Sep 2013, personal income grew at 4.1 percent annual equivalent, nominal disposable income increased at annual equivalent 3.7 percent and nominal personal consumption expenditures at 2.8 percent. Real disposable income grew at 2.6 percent annual equivalent and real personal consumption expenditures at 2.0 percent. In the eleventh wave, nominal personal income fell at 1.2 percent annual equivalent in Oct 2013, nominal disposable income at 1.2 percent and real disposable income at 3.5 percent. Nominal personal consumption expenditures increased at 4.9 percent annual equivalent and real personal consumption expenditures at 2.4 percent. In the twelfth wave, nominal personal income increased at 6.2 percent annual equivalent in Nov 2013, nominal disposable income at 4.9 percent and nominal personal consumption expenditures at 8.7 percent. Real disposable income increased at annual equivalent 3.7 percent and real personal consumption expenditures at 6.2 percent. In the thirteenth wave, nominal personal income increased at 4.9 percent annual equivalent in Dec 2013 and nominal disposable income at 3.7 percent while real disposable income increased at 1.2 percent annual equivalent. Nominal personal consumption expenditures increased at 2.4 percent annual equivalent and 0.0 percent for real personal consumption expenditures. In the fourteenth wave, nominal personal income increased at 8.3 percent annual equivalent in Jan-Mar 2014, nominal disposable income at 8.3 percent and nominal consumption expenditures at 5.3 percent. Real disposable personal income increased at 6.6 percent and real personal consumption expenditures at 2.8 percent. In the fifteenth wave, nominal personal income increased at 5.9 percent in annual equivalent in Apr-Aug 2014 and nominal disposable income at 5.7 percent. Real disposable income increased at 4.7 percent in annual equivalent in Apr-Aug 2014. Nominal personal consumption increased at 5.2 percent annual equivalent in Apr-Aug 2014 and real personal consumption expenditures increased at 3.7 percent. In the sixteenth wave, nominal personal income increased at 4.0 percent annual equivalent in Sep-Dec 2014, nominal disposable income at 3.7 percent and nominal personal consumption at 3.0 percent. Real disposable income increased at 3.7 percent in Sep-Dec 2014 and real personal consumption expenditure at 3.7 percent. In the seventeenth wave, nominal personal income increased at 1.8 percent annual equivalent in Jan-Feb 2015 and nominal disposable income fell at 0.6 percent while nominal personal consumption expenditures increased at 0.6 percent. Real disposable income increased at 1.8 percent and real personal consumption expenditures at 1.8 percent. In the eighteenth wave, nominal personal income (NPI) increased at 6.2 percent and nominal disposable personal income (NDPI) increased at 5.7 percent annual equivalent in Mar-Jun 2015. Real disposable income (RDPI) increased at 4.1 percent. Nominal consumption expenditures (NPCE) increased at 5.3 percent and real personal consumption expenditures (RPCE) increased at 3.7 percent. In the nineteenth wave, nominal personal income (NPI) increased at 4.1 percent in Jun-Aug 2015 and nominal disposable personal income (NDPI) at 4.5 percent. Real disposable income (RDPI) increased at 3.2 percent, nominal personal consumption expenditures (NPCE) at 3.2 percent and real personal consumption expenditures (RPCE) at 2.0 percent. In the twentieth wave, nominal personal income (NPI) increased at 3.4 percent annual equivalent in Sep-Dec 2015, nominal disposable personal income (NDPI) at 3.4 percent and nominal personal consumption expenditures (NPCE) at 2.7 percent. Real disposable personal income grew at 3.3 percent annual equivalent and real personal consumption expenditures at 2.4 percent. In the twenty-first wave, nominal personal income fell at 0.6 percent annual equivalent in Jan-Feb 2016. Nominal disposable personal income increased at 0.6 percent and nominal personal consumption expenditures at 1.8 percent. Real disposable personal income increased at 0.6 percent and real personal consumption expenditures at 1.8 percent. In the twenty-second wave, nominal personal income increased at 5.5 percent in Mar-Apr 2016. Nominal disposable income increased at 5.5 percent and real disposable income grew at 2.4 percent. Nominal personal consumption expenditures grew at 6.2 percent and real personal consumption expenditures increased at 4.3 percent. In the twenty-third wave, nominal personal income increased at 4.1 percent in May-Jul 2016 and nominal disposable income at 4.1 percent while nominal consumption expenditures increased at 4.1 percent. Real disposable income increased at 2.8 percent and real consumption expenditures at 3.7 percent.

The United States economy has grown at the average yearly rate of 3 percent per year and 2 percent per year in per capita terms from 1870 to 2010, as measured by Lucas (2011May). An important characteristic of the economic cycle in the US has been rapid growth in the initial phase of expansion after recessions. 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. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 28 quarters from IIIQ2009 to IIQ2016. 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 IIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp2q16_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 (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.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 IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2709.3 billion than actual $16,570.2 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.2 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/fluctuating-valuations-of-risk.html). US GDP in IIQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,570.2 billion in IIQ2016 or 10.5 percent at the average annual equivalent rate of 1.2 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 Jul 1919 to Jul 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 140.6556 in Jul 2016. The actual index NSA in Jul 2016 is 101.8529, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.3674 in Jul 2016. The output of manufacturing at 101.8529 in Jul 2016 is 21.3 percent below trend under this alternative calculation.

Table IB-1, US, Percentage Change from Prior Month Seasonally Adjusted of Personal Income, Disposable Income and Personal Consumption Expenditures %

 

NPI

NDPI

RDPI

NPCE

RPCE

2016

         

Jul 2016

0.4

0.4

0.4

0.3

0.3

Jun

0.3

0.3

0.2

0.5

0.4

May

0.3

0.3

0.1

0.3

0.2

AE ∆% May-Jul

4.1

4.1

2.8

4.5

3.7

Apr

0.6

0.6

0.2

1.0

0.7

Mar

0.3

0.3

0.2

0.0

0.0

AE ∆% Mar-Apr

5.5

5.5

2.4

6.2

4.3

Feb

-0.1

-0.1

0.0

0.2

0.3

Jan

0.0

0.2

0.1

0.1

-0.1

AE ∆% Jan-Feb

-0.6

0.6

0.6

1.8

1.2

2015

         

Dec

0.3

0.4

0.5

0.2

0.3

Nov

0.2

0.2

0.1

0.3

0.2

Oct

0.4

0.3

0.3

0.1

0.0

Sep

0.2

0.2

0.2

0.3

0.3

AE ∆% Sep-Dec

3.4

3.4

3.3

2.7

2.4

Aug

0.3

0.3

0.3

0.2

0.2

Jul

0.3

0.4

0.2

0.4

0.3

Jun

0.4

0.4

0.3

0.2

0.0

AE ∆% Jun-Aug

4.1

4.5

3.2

3.2

2.0

May

0.6

0.6

0.4

0.6

0.4

Apr

0.7

0.7

0.6

0.2

0.1

Mar

0.2

0.1

0.0

0.5

0.4

AE ∆% Mar-Jun

6.2

5.7

4.1

5.3

3.7

Feb

0.3

0.3

0.2

0.3

0.1

Jan

0.0

-0.4

0.1

-0.2

0.2

AE ∆% Jan-Feb

1.8

-0.6

1.8

0.6

1.8

2014

         

Dec

0.1

0.1

0.3

-0.1

0.1

Nov

0.4

0.3

0.4

0.4

0.5

Oct

0.5

0.5

0.4

0.6

0.6

Sep

0.3

0.3

0.1

0.1

0.0

AE ∆% Sep-Dec

4.0

3.7

3.7

3.0

3.7

Aug

0.5

0.4

0.5

0.7

0.7

Jul

0.4

0.3

0.2

0.2

0.1

Jun

0.6

0.6

0.5

0.5

0.5

May

0.5

0.5

0.4

0.3

0.1

Apr

0.4

0.5

0.3

0.4

0.1

AE ∆% Apr-Aug

5.9

5.7

4.7

5.2

3.7

Mar

0.7

0.8

0.6

0.7

0.5

Feb

0.6

0.6

0.6

0.6

0.5

Jan

0.7

0.6

0.4

0.0

-0.3

AE ∆% Jan-Mar

8.3

8.3

6.6

5.3

2.8

2013

         

Dec

0.4

0.3

0.1

0.2

0.0

AE ∆% Dec

4.9

3.7

1.2

2.4

0.0

Nov

0.5

0.4

0.3

0.7

0.5

AE ∆% Nov

6.2

4.9

3.7

8.7

6.2

Oct

-0.1

-0.1

-0.3

0.4

0.2

AE ∆% Oct

-1.2

-1.2

-3.5

4.9

2.4

Sep

0.4

0.4

0.3

0.5

0.4

Aug

0.4

0.4

0.3

0.2

0.1

Jul

0.0

0.0

-0.1

0.2

0.1

Jun

0.4

0.4

0.2

0.4

0.2

May

0.7

0.6

0.6

0.2

0.2

Apr

0.1

0.0

0.0

-0.1

0.0

AE ∆% Apr-Sep

4.1

3.7

2.6

2.8

2.0

Mar

0.1

0.0

0.1

-0.2

-0.1

Feb

0.4

0.4

0.0

0.5

0.1

AE ∆% Feb-Mar

3.0

2.4

0.6

1.8

0.0

Jan

-5.2

-6.1 (0.1)a

-6.2

0.3

0.2

AE ∆% Jan

-47.3

-53.0 (3.7)a

-53.6

3.7

2.4

2012

         

∆% Jan-Dec 2012***

8.5

8.6

6.8

3.3

2.3

Dec

2.6

2.6 (0.3)*

2.6 (0.5)*

0.2

0.2

Nov

1.2

1.2 (0.6)*

1.3 (0.9)*

0.2

0.3

AE ∆% Nov-Dec

25.3

25.3 (5.5)*

26.0 (8.7)*

2.4

3.0

Oct

0.9

0.9

0.6

0.1

-0.2

Sep

0.9

0.8

0.5

0.7

0.4

Aug

0.2

0.2

-0.2

0.2

-0.2

AE ∆% Aug-Oct

8.3

7.9

3.7

4.1

0.0

Jul

-0.2

-0.2

-0.3

0.3

0.3

Jun

0.2

0.2

0.2

-0.1

-0.1

May

0.0

0.0

0.1

-0.1

0.0

Apr

0.4

0.4

0.3

0.3

0.1

AE ∆% Apr-Jul

1.2

1.2

0.9

1.2

0.9

Mar

0.5

0.5

0.3

0.1

-0.1

Feb

0.8

0.8

0.6

0.6

0.4

Jan

0.7

1.0

0.7

0.7

0.4

AE ∆% Jan-Mar

8.3

9.6

4.9

4.3

2.1

2011

         

∆% Jan-Dec 2011*

5.1

4.1

1.6

3.7

1.8

Dec

0.8

0.8

0.8

0.0

0.0

Nov

0.0

0.0

-0.1

0.0

-0.1

Oct

0.1

0.1

0.1

0.3

0.3

Sep

-0.1

-0.1

-0.3

0.4

0.3

AE ∆% Sep-Dec

2.4

2.4

1.5

2.1

1.5

Aug

0.2

0.2

-0.1

0.2

-0.1

Jul

0.6

0.6

0.4

0.5

0.3

Jun

0.5

0.5

0.4

0.2

0.2

May

0.3

0.3

-0.1

0.3

-0.1

AE ∆% May-Aug

4.9

4.9

1.8

3.7

0.9

Apr

0.2

0.2

-0.3

0.4

0.0

Mar

0.2

0.2

-0.1

0.7

0.3

Feb

0.5

0.6

0.3

0.4

0.1

Jan

1.6

0.7

0.5

0.4

0.1

AE ∆% Jan-Apr

7.7

5.2

1.2

5.9

1.5

2010

         

∆% Jan-Dec 2010**

5.2

4.3

2.9

4.4

2.9

Dec

0.9

0.9

0.7

0.3

0.1

Nov

0.5

0.5

0.3

0.5

0.4

Oct

0.5

0.5

0.2

0.7

0.5

IVQ2010∆%

1.9

1.9

1.2

1.5

1.0

IVQ2010 AE ∆%

7.9

7.9

4.9

6.2

4.1

Notes: *Excluding exceptional income gains in Nov and Dec 2012 because of anticipated tax increases in Jan 2013 ((page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf). a Excluding employee contributions for government social insurance (pages 1-2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0113.pdf )Excluding NPI: current dollars personal income; NDPI: current dollars disposable personal income; RDPI: chained (2005) dollars DPI; NPCE: current dollars personal consumption expenditures; RPCE: chained (2005) dollars PCE; AE: annual equivalent; IVQ2010: fourth quarter 2010; A: annual equivalent

Percentage change month to month seasonally adjusted

*∆% Dec 2011/Dec 2010 **∆% Dec 2010/Dec 2009 *** ∆% Dec 2012/Dec 2011

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

The rates of growth of real disposable income decline in the final quarter of 2013 because of the increases in the last two months of 2012 in anticipation of the tax increases of the “fiscal cliff” episode. The increase was provided in the “fiscal cliff” law H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf).

The 12-month rate of increase of real disposable income fell to minus 1.3 percent in Oct 2013 and minus 2.4 percent in Nov 2013 partly because of the much higher level in late 2012 in anticipation of incomes to avoid increases in taxes in 2013. Real disposable income fell 4.8 percent in the 12 months ending in Dec 2013 primarily because of the much higher level in late 2012 in anticipation of income to avoid increases in taxes in 2013. Real disposable income increased 1.9 percent in the 12 months ending in Jan 2014, partly because of the low level in Jan 2013 after anticipation of incomes in late 2012 in avoiding the fiscal cliff episode. Real disposable income increased 2.7 percent in the 12 months ending in Jul 2016.

RPCE growth decelerated less sharply from close to 3 percent in IVQ 2010 to 3.0 percent in Jul 2016. Subdued growth of RPCE could affect revenues of business. Growth rates of personal consumption have weakened. Goods and especially durable goods have been driving growth of PCE as shown by the much higher 12-month rates of growth of real goods PCE (RPCEG) and durable goods real PCE (RPCEGD) than services real PCE (RPCES). Growth of consumption of goods and, in particular, of consumer durable goods drives the faster expansion of the economy while growth of consumption of services is much more moderate. The 12-month rates of growth of RPCEGD have fallen from around 10 percent and even higher in several months from Sep 2010 to Feb 2011 to the range of 3.2 to 7.3 percent from Jul 2015 to Jul 2016. RPCEG growth rates have fallen from around 5 percent late in 2010 and early Jan-Feb 2011 to the range of 2.4 to 4.4 percent from Jul 2015 to Jul 2016. In Jun 2016, RPCEG increased 3.8 percent in 12 months and RPCEGD 6.3 percent while RPCES increased 2.6 percent. There are limits to sustained growth based on financial repression in an environment of weak labor markets and real labor remuneration.

Table IB-2, Real Disposable Personal Income and Real Personal Consumption Expenditures

Percentage Change from the Same Month a Year Earlier %

 

RDPI

RPCE

RPCEG

RPCEGD

RPCES

2016

         

Jul

2.7

3.0

3.8

6.3

2.6

Jun

2.6

2.9

3.8

5.4

2.5

May

2.6

2.5

3.2

3.9

2.2

Apr

2.8

2.8

4.0

5.2

2.2

Mar

3.2

2.2

2.4

3.2

2.0

Feb

2.9

2.6

3.3

5.5

2.2

Jan

3.1

2.4

3.1

4.1

2.0

2015

         

Dec

3.0

2.6

3.5

5.5

2.2

Nov

2.9

2.4

3.2

5.3

2.0

Oct

3.2

2.6

3.3

5.6

2.3

Sep

3.3

3.2

4.3

6.8

2.6

Aug

3.3

2.9

3.5

5.6

2.5

Jul

3.4

3.4

4.4

7.3

2.9

Jun

3.4

3.2

3.8

6.2

2.9

May

3.6

3.6

4.7

8.0

3.1

Apr

3.7

3.4

3.8

7.5

3.2

Mar

3.3

3.4

4.2

7.0

3.0

Feb

4.0

3.5

4.1

7.6

3.3

Jan

4.4

4.0

5.9

11.1

3.1

2014

         

Dec

4.7

3.5

4.7

9.4

2.9

Nov

4.5

3.5

4.7

8.5

2.8

Oct

4.4

3.5

4.5

8.0

3.0

Sep

3.7

3.2

4.0

8.0

2.8

Aug

3.8

3.6

5.3

8.5

2.7

Jul

3.6

2.9

3.8

6.7

2.4

Jun

3.3

2.9

4.2

7.0

2.3

May

3.1

2.6

3.7

6.7

2.1

Apr

3.3

2.7

4.1

6.0

2.0

Mar

3.0

2.6

4.2

7.3

1.7

Feb

2.5

1.9

2.6

3.3

1.6

Jan

1.9

1.5

1.1

1.2

1.7

2013

         

Dec

-4.8

1.9

2.9

3.1

1.4

Nov

-2.4

2.2

3.8

5.8

1.3

Oct

-1.3

1.9

3.7

6.8

1.0

Sep

-0.5

1.5

2.9

4.5

0.8

Aug

-0.3

1.5

2.8

6.6

0.9

Jul

-0.8

1.3

3.4

7.0

0.2

Jun

-1.0

1.5

3.5

7.5

0.5

May

-1.0

1.2

3.0

6.5

0.3

Apr

-1.5

1.0

2.5

6.1

0.2

Mar

-1.2

1.1

2.4

5.6

0.5

Feb

-1.1

1.1

3.0

7.2

0.1

Jan

-0.5

1.4

3.4

7.8

0.3

2012

         

Dec

6.8

1.6

3.6

8.7

0.6

Nov

4.9

1.4

2.8

7.7

0.7

Oct

3.4

1.0

1.9

5.2

0.5

Sep

2.9

1.4

3.4

8.5

0.4

Aug

2.1

1.3

3.4

8.5

0.3

Jul

2.2

1.4

2.8

7.5

0.7

Jun

2.9

1.4

2.5

8.3

0.8

May

3.1

1.7

3.1

7.9

1.0

Apr

3.0

1.6

2.5

7.0

1.2

Mar

2.4

1.4

2.3

5.9

1.0

Feb

2.0

1.8

2.5

7.1

1.5

Jan

1.8

1.5

1.9

5.9

1.3

Dec 2011

1.6

1.2

1.4

5.0

1.1

Dec 2010

2.9

2.9

4.7

8.4

2.1

Notes: RDPI: real disposable personal income; RPCE: real personal consumption expenditures (PCE); RPCEG: real PCE goods; RPCEGD: RPCEG durable goods; RPCES: RPCE services

Numbers are percentage changes from the same month a year earlier

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

Chart IB-1 shows US real personal consumption expenditures (RPCE) between 1999 and 2016. There is an evident drop in RPCE during the global recession in 2007 to 2009 but the slope is flatter during the current recovery than in the period before 2007.

clip_image047

Chart IB-1, US, Real Personal Consumption Expenditures, Quarterly Seasonally Adjusted at Annual Rates 1999-2016

Source: US Bureau of Economic Analysis

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

Percent changes from the prior period in seasonally adjusted annual equivalent quarterly rates (SAAR) of real personal consumption expenditures (RPCE) are in Chart IB-2 from 1995 to 2016. The average rate could be visualized as a horizontal line. Although there are not yet sufficient observations, it appears from Chart IB-2 that the average rate of growth of RPCE was higher before the recession than during the past twenty-eight quarters of expansion that began in IIIQ2009.

clip_image048

Chart IB-2, Percent Change from Prior Period in Real Personal Consumption Expenditures, Quarterly Seasonally Adjusted at Annual Rates 1995-2016

Source: US Bureau of Economic Analysis

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

Personal income and its disposition are in Table IB-3. The latest estimates and revisions have changed movements in eight forms. (1) Increase in Jul 2016 of personal income by $71.7 billion or 0.4 percent and increase of disposable income of $60.1 billion or 0.4 percent with increase of wages and salaries of 0.5 percent. (2) Increase of personal income of $506.0 billion or 3.3 percent from Jul 2015 to Jul 2016 and increase of disposable income of $483.8 billion or 3.6 percent. Wages and salaries increased $2319.3 billion or 4.1 percent. (3) Increase of personal income of $599.7 billion from Dec 2014 to Dec 2015 or 4.0 percent and increase of disposable income of $482.4 billion or 3.6 percent. Wages and salaries increased $411.7 billion or 5.4 percent. (4) Increase of personal income of $844.1 billion from Dec 2013 to Dec 2014 or 5.9 percent while disposable income increased $712.4 billion or 5.7 percent. Wages and salaries increased $406.0 billion or 5.6 percent. (5) Decrease of personal income of $329.0 billion from Dec 2012 to Dec 2013 or by 2.2 percent and decrease of disposable income of $442.5 billion or by 3.4 percent. Wages and salaries increased $60.7 billion from Dec 2012 to Dec 2013 or by 0.8 percent. Large part of these declines occurred because of the comparison of high levels in late 2012 in anticipation of tax increases in 2013. (6) In 2012, personal income increased $1150.5 billion or 8.5 percent while wages and salaries increased 7.5 percent and disposable income 8.6 percent. Significant part of these gains occurred in Dec 2012 in anticipation of incomes because of tax increases beginning in Jan 2013. (7) Increase of $656.0 billion of personal income in 2011 or by 5.1 percent with increase of wages and salaries of 2.7 percent and disposable income of 4.1 percent. (8) Increase of the rate of savings as percent of disposable income from 5.9 percent in Dec 2010 to 6.4 percent in Dec 2011 and 11.0 percent in Dec 2012, decreasing to 4.7 percent in Dec 2013. The savings rate increased to 5.7 percent in Dec 2014, 6.1 percent in Dec 2015, 5.5 in Jun 2016 and 5.7 percent in Jul 2016.

Table IB-3, US, Personal Income and its Disposition, Seasonally Adjusted at Annual Rates USD Billions

 

Personal
Income

Wages &
Salaries

Personal
Taxes

DPI

Savings
Rate %

Jul 2016

16,023.4

8,184.6

1,963.4

14,059.9

5.7

Jun

15,951.7

8,141.3

1,951.9

13,999.8

5.5

Change Jul 2016/     

Jun 2016

71.7 ∆% 0.4

43.3 ∆%

0.5

11.5 ∆% 0.6

60.1 ∆% 0.4

 

Jul 2015

15,517.4

7,865.3

1,941.3

13,576.1

5.8

Change Jul 2016/     

Jul 2015

506.0 ∆% 3.3

319.3 ∆% 4.1

22.1 ∆% 1.1

483.8 ∆% 3.6

 

Dec 2015

15,737.7

8,063.0

1,966.6

13,771.1

6.1

Change Dec 2015/Dec 2014

599.7 ∆%

4.0

411.7 ∆%

5.4

117.4 ∆%

6.3

482.4 ∆%

3.6

 

Dec 2014

15,138.0

7,651.3

1,849.2

13,288.7

5.7

Change Dec 2014/Dec 2013

844.1 ∆% 5.9

406.0 ∆% 5.6

131.6 ∆% 7.7

712.4 ∆% 5.7

 

Dec 2013

14,293.9

7,245.3

1,717.6

12,576.3

4.7

Dec 2012

14,622.9

7,184.6

1,604.1

13,018.8

11.0

Change Dec 2013/ Dec 2012

-329.0 ∆% -2.2

60.7 ∆% 0.8

113.5 ∆%

7.3

-442.5 ∆% -3.4

 

Change Dec 2012/ Dec 2011

1150.5 ∆% 8.5

501.7 ∆% 7.5

120.3 ∆% 8.1

1030.2 ∆% 8.6

 

Dec 2011

13,472.4

6,682.9

1,483.8

11,988.6

6.4

Dec 2010

12,816.4

6,506.0

1,301.9

11,514.5

5.9

Change Dec 2011/ Dec 2010

656.0 ∆%

5.1

176.9  ∆% 2.7

181.9     ∆% 14.0

474.1    ∆% 4.1

 

Source: US Bureau of Economic Analysis

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

The Bureau of Economic Analysis (BEA) provides a wealth of revisions and enhancements of US personal income and outlays since 1929 (http://www.bea.gov/iTable/index_nipa.cfm). Table IB-4 provides growth rates of real disposable income and real disposable income per capita in the long-term and selected periods. Real disposable income consists of after-tax income adjusted for inflation. Real disposable income per capita is income per person after taxes and inflation. There is remarkable long-term trend of growth of real disposable income of 3.2 percent per year on average from 1929 to 2015 and 2.0 percent in real disposable income per capita. Real disposable income increased at the average yearly rate of 3.7 percent from 1947 to 1999 and real disposable income per capita at 2.3 percent. These rates of increase broadly accompany rates of growth of GDP. Institutional arrangements in the United States provided the environment for growth of output and income after taxes, inflation and population growth. There is significant break of growth by much lower 2.4 percent for real disposable income on average from 1999 to 2015 and 1.5 percent in real disposable per capita income. Real disposable income grew at 3.5 percent from 1980 to 1989 and real disposable per capita income at 2.6 percent. In contrast, real disposable income grew at only 1.7 percent on average from 2006 to 2015 and real disposable income per capita at 0.9 percent. Real disposable income grew at 1.7 percent from 2007 to 2015 and real disposable income per capita at 0.8 percent. The United States has interrupted its long-term and cyclical dynamism of output, income and employment growth. Recovery of this dynamism could prove to be a major challenge. Cyclical uncommonly slow growth explains weakness in the current whole cycle instead of the allegation of secular stagnation.

Table IB-4, Average Annual Growth Rates of Real Disposable Income (RDPI) and Real Disposable Income per Capita (RDPIPC), Percent per Year 

RDPI Average ∆%

 

     1929-2015

3.2

     1947-1999

3.7

     1999-2015

2.4

     1999-2006

3.2

     1980-1989

3.5

     2006-2015

1.7

2007-2015

1.7

RDPIPC Average ∆%

 

     1929-2015

2.0

     1947-1999

2.3

     1999-2015

1.5

     1999-2006

2.2

     1980-1989

2.6

     2006-2015

0.9

2007-2015

0.8

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

Chart IB-3 provides personal income in the US between 1980 and 1989. These data are not adjusted for inflation that was still high in the 1980s in the exit from the Great Inflation of the 1960s and 1970s (see http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I The Great Inflation; see Taylor 1993, 1997, 1998LB, 1999, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB and http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html http://cmpassocregulationblog.blogspot.com/2014/07/financial-irrational-exuberance.html http://cmpassocregulationblog.blogspot.com/2014/07/world-inflation-waves-united-states.html). Personal income grew steadily during the 1980s after recovery from two recessions from Jan IQ1980 to Jul IIIQ1980 and from Jul IIIQ1981 to Nov IVQ1982.

clip_image049

Chart IB-3, US, Personal Income, Billion Dollars, Quarterly Seasonally Adjusted at Annual Rates, 1980-1989

Source: US Bureau of Economic Analysis

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

A different evolution of personal income is shown in Chart IB-4. Personal income also fell during the recession from Dec IVQ2007 to Jun IIQ2009 (http://www.nber.org/cycles.html). Growth of personal income during the expansion has been tepid even with the new revisions. In IVQ2012, nominal disposable personal income grew at the SAAR of 13.3 percent and real disposable personal income at 10.9 percent (Table 2.1 http://bea.gov/iTable/index_nipa.cfm). The BEA explains as follows: “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf pages 1-2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0113.pdf). The Bureau of Economic Analysis explains as (http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf 2-3): “The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base.”

The increase was provided in the “fiscal cliff” law H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf).

In IQ2013, personal income fell at the SAAR of minus 11.0 percent; real personal income excluding current transfer receipts at minus 11.9 percent; and real disposable personal income at minus 15.9 percent (Table 14 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf).The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

“The February and January changes in disposable personal income (DPI) mainly reflected the effect of special factors in January, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to November and to December in anticipation of changes in individual tax rates.”

In IIIQ2014, personal income grew at 4.5 percent, real personal income excluding current transfers at 2.8 percent, nominal disposable income at 3.9 percent and real disposable personal income at 2.7 percent (Table 14 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf). In IVQ2014, personal income grew at 5.0 percent in nominal terms and at 6.0 percent in real terms excluding current transfers while nominal disposable income grew at 4.2 percent in nominal terms and at 4.7 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf). In IQ2015, nominal personal income grew at 2.1 percent and at 2.7 percent in real terms excluding current transfer receipts while nominal disposable income grew at 0.3 percent and at 2.0 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIQ2015, nominal personal income grew at 5.8 percent and at 3.9 percent in real terms excluding current transfer receipts while nominal disposable income grew at 5.8 percent and real disposable income grew at 3.9 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIIQ2015, nominal personal income grew at 4.1 percent and 3.2 percent excluding transfer receipts while nominal disposable income grew at 4.4 percent and real disposable income grew at 3.3 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IVQ2015, nominal personal income grew at 3.5 percent and 3.3 percent excluding transfer receipts while nominal disposable income grew at 3.4 percent and real disposable income at 3.0 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IQ2016, personal income grew at 1.3 percent and at 0.2 percent excluding transfer receipts while nominal disposable income grew at 2.4 percent and real disposable income grew at 2.1 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIQ2016, personal income grew at 4.1 percent and at 2.3 percent excluding transfer receipts while nominal disposable income grew at 4.3 percent and real disposable income grew at 2.3 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf).

clip_image050

Chart IB-4, US, Personal Income, Current Billions of Dollars, Quarterly Seasonally Adjusted at Annual Rates, 2007-2016

Source: US Bureau of Economic Analysis

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

Real or inflation-adjusted disposable personal income is in Chart IB-5 from 1980 to 1989. Real disposable income after allowing for taxes and inflation grew steadily at high rates during the entire decade.

clip_image051

Chart IB-5, US, Real Disposable Income, Billions of Chained 2009 Dollars, Quarterly Seasonally Adjusted at Annual Rates 1980-1989

Source: US Bureau of Economic Analysis

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

Chart IB-6 provides real disposable income from 2007 to 2016. In IVQ2012, nominal disposable personal income grew at the SAAR of 13.3 percent and real disposable personal income at 10.9 percent (Table 2.1 http://bea.gov/iTable/index_nipa.cfm). The BEA explains as follows: “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf pages 1-2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0113.pdf). The Bureau of Economic Analysis explains as (http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf 2-3): “The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base.”

The increase was provided in the “fiscal cliff” law H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf). In IQ2013, personal income fell at the SAAR of minus 11.0 percent; real personal income excluding current transfer receipts at minus 11.9 percent; and real disposable personal income at minus 15.9 percent (Table 14 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf).The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

“The February and January changes in disposable personal income (DPI) mainly reflected the effect of special factors in January, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to November and to December in anticipation of changes in individual tax rates.”

In IIIQ2014, personal income grew at 4.5 percent, real personal income excluding current transfers at 2.8 percent, nominal disposable income at 3.9 percent and real disposable personal income at 2.7 percent (Table 14 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf). In IVQ2014, personal income grew at 5.0 percent in nominal terms and at 6.0 percent in real terms excluding current transfers while nominal disposable income grew at 4.2 percent in nominal terms and at 4.7 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf). In IQ2015, nominal personal income grew at 2.1 percent and at 2.7 percent in real terms excluding current transfer receipts while nominal disposable income grew at 0.3 percent and at 2.0 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIQ2015, nominal personal income grew at 5.8 percent and at 3.9 percent in real terms excluding current transfer receipts while nominal disposable income grew at 5.8 percent and real disposable income grew at 3.9 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIIQ2015, nominal personal income grew at 4.1 percent and 3.2 percent excluding transfer receipts while nominal disposable income grew at 4.4 percent and real disposable income grew at 3.3 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IVQ2015, nominal personal income grew at 3.5 percent and 3.3 percent excluding transfer receipts while nominal disposable income grew at 3.4 percent and real disposable income at 3.0 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IQ2016, personal income grew at 1.3 percent and at 0.2 percent excluding transfer receipts while nominal disposable income grew at 2.4 percent and real disposable income grew at 2.1 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIQ2016, personal income grew at 4.1 percent and at 2.3 percent excluding transfer receipts while nominal disposable income grew at 4.3 percent and real disposable income grew at 2.3 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf).

clip_image052

Chart IB-6, US, Real Disposable Income, Billions of Chained 2009 Dollars, Quarterly Seasonally Adjusted at Annual Rates, 2007-2016

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

Chart IB-7 provides percentage quarterly changes in real disposable income from the preceding period at seasonally adjusted annual rates from 1980 to 1989. Rates of changes were high during the decade with few negative changes.

clip_image053

Chart IB-7, US, Real Disposable Income Percentage Change from Preceding Period at Quarterly Seasonally-Adjusted Annual Rates, 1980-1989

Source: US Bureau of Economic Analysis

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

Chart IB-8 provides percentage quarterly changes in real disposable income from the preceding period at seasonally adjusted annual rates from 2007 to 2016. There has been a period of positive rates followed by decline of rates and then negative and low rates in 2011. Recovery in 2012 has not reproduced the dynamism of the brief early phase of expansion. In IVQ2012, nominal disposable personal income grew at the SAAR of 13.3 percent and real disposable personal income at 10.9 percent (Table 2.1 http://bea.gov/iTable/index_nipa.cfm). The BEA explains as follows: “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf pages 1-2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0113.pdf). The Bureau of Economic Analysis explains as (http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf 2-3): “The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base.”

The increase was provided in the “fiscal cliff” law H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf). In IQ2013, personal income fell at the SAAR of minus 11.0 percent; real personal income excluding current transfer receipts at minus 11.9 percent; and real disposable personal income at minus 15.9 percent (Table 14 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf).The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

“The February and January changes in disposable personal income (DPI) mainly reflected the effect of special factors in January, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to November and to December in anticipation of changes in individual tax rates.”

In IIIQ2014, personal income grew at 4.5 percent, real personal income excluding current transfers at 2.8 percent, nominal disposable income at 3.9 percent and real disposable personal income at 2.7 percent (Table 14 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf). In IVQ2014, personal income grew at 5.0 percent in nominal terms and at 6.0 percent in real terms excluding current transfers while nominal disposable income grew at 4.2 percent in nominal terms and at 4.7 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0616.pdf). In IQ2015, nominal personal income grew at 2.1 percent and at 2.7 percent in real terms excluding current transfer receipts while nominal disposable income grew at 0.3 percent and at 2.0 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIQ2015, nominal personal income grew at 5.8 percent and at 3.9 percent in real terms excluding current transfer receipts while nominal disposable income grew at 5.8 percent and real disposable income grew at 3.9 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIIQ2015, nominal personal income grew at 4.1 percent and 3.2 percent excluding transfer receipts while nominal disposable income grew at 4.4 percent and real disposable income grew at 3.3 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IVQ2015, nominal personal income grew at 3.5 percent and 3.3 percent excluding transfer receipts while nominal disposable income grew at 3.4 percent and real disposable income at 3.0 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IQ2016, personal income grew at 1.3 percent and at 0.2 percent excluding transfer receipts while nominal disposable income grew at 2.4 percent and real disposable income grew at 2.1 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). In IIQ2016, personal income grew at 4.1 percent and at 2.3 percent excluding transfer receipts while nominal disposable income grew at 4.3 percent and real disposable income grew at 2.3 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf).

clip_image054

Chart, IB-8, US, Real Disposable Income, Percentage Change from Preceding Period at Seasonally-Adjusted Annual Rates, 2007-2016

Source: US Bureau of Economic Analysis

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

The Bureau of Economic Analysis (BEA) estimates US personal income in Jul 2016 at the seasonally adjusted annual rate of $16,023.4 billion, as shown in Table IB-3 above (see Table 1 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). The major portion of personal income is compensation of employees of $10,099.4 billion, or 63.0 percent of the total. Wages and salaries are $8,146.6 billion, of which $6,871.7 billion by private industries and supplements to wages and salaries of $1,914.8 billion (contributions to social insurance are $586.1 billion). In Jan 1990 (at the comparable month after the 28th quarter of cyclical expansion), US personal income was $4,782.4 billion at SAAR (http://www.bea.gov/iTable/index_nipa.cfm). Compensation of employees was $3,250.9 billion, or 68.0 percent of the total. Wages and salaries were $2,661.7 billion of which $2,159.0 billion by private industries. Supplements to wages and salaries were $589.2 billion with employer contributions to pension and insurance funds of $387.8 billion and $201.3 billion to government social insurance. Chart IB-9 provides US wages and salaries by private industries in the 1980s. Growth was robust after the interruption of the recessions.

clip_image055

Chart IB-9, US, Wages and Salaries, Private Industries, Quarterly, Seasonally Adjusted at Annual Rates Billions of Dollars, 1980-1989

Source: US Bureau of Economic Analysis

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

The Bureau of Economic Analysis (BEA) estimates US personal income in Jul 2016 at the seasonally adjusted annual rate of $16,023.4 billion, as shown in Table IB-3 above (see Table 1 at http://www.bea.gov/newsreleases/national/pi/2016/pdf/pi0716.pdf). The major portion of personal income is compensation of employees of $10,099.4 billion, or 63.0 percent of the total. Wages and salaries are $8,146.6 billion, of which $6,871.7 billion by private industries and supplements to wages and salaries of $1,914.8 billion (contributions to social insurance are $586.1 billion). Chart IB-10 provides US wages and salaries by private industries from 2007 to 2016. Growth was mediocre in the weak expansion phase after IIIQ2009.

clip_image056

Chart IB-10, US, Wage and Salary Disbursement, Private Industries, Quarterly, Seasonally Adjusted at Annual Rates, Billions of Dollars 2007-2016

Source: US Bureau of Economic Analysis

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

Chart IB-11 provides finer detail with monthly wages and salaries of private industries from 2007 to 2016. Anticipations of income in late 2012 to avoid tax increases in 2013 cloud comparisons.

clip_image057

Chart IB-11, US, Wages and Salaries, Private Industries, Monthly, Seasonally Adjusted at Annual Rates, Billions of Dollars 2007-2016

Source: US Bureau of Economic Analysis

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

Chart IB-12 provides monthly real disposable personal income per capita from 1980 to 1989. This is the ultimate measure of wellbeing in receiving income by obtaining the value per inhabitant. The measure cannot adjust for the distribution of income. Real disposable personal income per capita grew rapidly during the expansion after 1983 and continued growing during the rest of the decade.

clip_image058

Chart IB-12, US, Real Disposable Per Capita Income, Monthly, Seasonally Adjusted at Annual Rates, Chained 2009 Dollars 1980-1989

Source: US Bureau of Economic Analysis

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

Table IB-5 provides the comparison between the cycle of the 1980s and the current cycle. Real per capita disposable income (RDPI-PC) increased 26.3 percent from Dec 1979 to Jan 1990. In the comparable period in the current cycle from Dec 2007 to Jul 2016, real per capita disposable income increased 9.2 percent.

Table IB-5, Percentage Changes of Real Disposable Personal Income Per Capita

Month

RDPI-PC ∆% 12/79

RDPI-PC ∆% YOY

Month

RDPI-PC ∆% 12/07

RDPI-PC ∆% YOY

11/1982

2.4

0.7

6/2009

-0.6

-2.4

12/1982

2.9

1.3

9/2009

-1.3

-0.6

12/1983

7.8

4.8

6/2010

-0.4

0.2

12/1987

20.4

2.7

6/2014

4.2

2.6

1/1988

20.6

2.6

7/2014

4.3

2.8

2/1988

21.2

2.6

8/2014

4.7

3.0

3/1988

21.6

2.9

9/2014

4.8

2.9

4/1988

21.9

7.4

10/2014

5.2

3.6

5/1988

22.0

3.3

11/2014

5.5

3.7

6/1988

22.3

3.9

12/2014

5.8

3.9

7/1988

22.7

4.0

1/2015

5.8

3.6

8/1988

23.0

3.8

2/2015

5.9

3.2

9/1988

23.1

4.0

3/2015

5.8

2.5

10/1988

23.6

3.9

4/2015

6.4

2.9

11/1988

23.6

3.5

5/2015

6.7

2.8

12/1988

24.2

3.2

6/2015

6.9

2.6

1/1989

24.7

3.4

7/2015

7.1

2.6

2/1989

25.0

3.2

8/2015

7.3

2.5

3/1989

25.6

3.3

9/2015

7.5

2.5

4/1989

24.8

2.4

10/2015

7.7

2.4

5/1989

24.1

1.8

11/2015

7.8

2.1

6/1989

24.4

1.6

12/2015

8.2

2.3

7/1989

24.7

1.6

1/2016

8.2

2.3

8/1989

24.9

1.6

2/2016

8.2

2.1

9/1989

25.1

1.7

3/2016

8.4

2.4

10/1989

25.6

1.6

4/2016

8.6

2.0

11/1989

25.6

1.6

5/2016

8.6

1.8

12/1989

25.6

1.1

6/2016

8.8

1.8

1/1990

26.3

1.3

7/2016

9.2

2.0

RDPI: Real Disposable Personal Income; RDPI-PC, Real Disposable Personal Income Per Capita

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

National Bureau of Economic Research

http://www.nber.org/cycles.html

Chart IB-13 provides monthly real disposable personal income per capita from 2007 to 2016. There was initial recovery from the drop during the global recession followed by relative cyclical weakness

clip_image059

Chart IB-13, US, Real Disposable Per Capita Income, Monthly, Seasonally Adjusted at Annual Rates, Chained 2009 Dollars 2007-2016

Source: US Bureau of Economic Analysis

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

Table IB-6 provides data for analysis of the current cycle. Real disposable income (RDPI) increased 16.8 percent from Dec 2007 to Jul 2016 (column RDPI ∆% 12/07). In the same period, real disposable income per capita increased 9.2 percent (column RDPI-PC ∆% 12/07). The annual equivalent rate of increase of real disposable income per capita is 1.0 percent, only a fraction of 2.0 percent on average from 1929 to 2015, and 1.8 percent for real disposable income, much lower than 3.2 percent on average from 1929 to 2015.

Table IB-6, Percentage Changes of Real Disposable Personal Income and Real Disposable Personal Income Per Capita

Month

RDPI
∆% 12/07

RDPI ∆% Month

RDPI ∆% YOY

RDPI-PC ∆% 12/07

RDPI-PC ∆% Month

RDPI-PC ∆% YOY

6/09

0.8

-1.7

-1.5

-0.6

-1.8

-2.4

9/09

0.3

0.1

0.3

-1.3

0.1

-0.6

6/10

1.8

0.0

1.0

-0.4

0.0

0.2

12/10

3.3

0.7

2.9

0.7

0.6

2.1

6/11

4.1

0.4

2.3

1.2

0.4

1.5

12/11

5.0

0.8

1.6

1.6

0.7

0.8

6/12

7.2

0.2

2.9

3.4

0.2

2.2

10/12

7.9

0.6

3.4

3.7

0.5

2.7

11/12

9.3

1.3

4.9

5.0

1.3

4.1

12/12

12.1

2.6

6.8

7.7

2.5

6.0

6/13

6.2

0.2

-1.0

1.6

0.2

-1.7

12/13

6.8

0.1

-4.8

1.8

0.0

-5.5

1/14

7.2

0.4

1.9

2.1

0.3

1.2

2/14

7.8

0.6

2.5

2.6

0.5

1.8

3/14

8.5

0.6

3.0

3.2

0.5

2.3

4/14

8.8

0.3

3.3

3.4

0.2

2.5

5/14

9.2

0.4

3.1

3.8

0.4

2.3

6/14

9.7

0.5

3.3

4.2

0.4

2.6

7/14

9.9

0.2

3.6

4.3

0.1

2.8

8/14

10.4

0.5

3.8

4.7

0.4

3.0

9/14

10.6

0.1

3.7

4.8

0.1

2.9

10/14

11.1

0.4

4.4

5.2

0.4

3.6

11/14

11.5

0.4

4.5

5.5

0.3

3.7

12/14

11.8

0.3

4.7

5.8

0.2

3.9

1/15

11.9

0.1

4.4

5.8

0.0

3.6

2/15

12.1

0.2

4.0

5.9

0.1

3.2

3/15

12.1

0.0

3.3

5.8

-0.1

2.5

4/15

12.7

0.6

3.7

6.4

0.5

2.9

5/15

13.1

0.4

3.6

6.7

0.3

2.8

6/15

13.4

0.3

3.4

6.9

0.2

2.6

7/15

13.7

0.2

3.4

7.1

0.2

2.6

8/15

14.1

0.3

3.3

7.3

0.2

2.5

9/15

14.3

0.2

3.3

7.5

0.1

2.5

10/15

14.6

0.3

3.2

7.7

0.2

2.4

11/15

14.7

0.1

2.9

7.8

0.1

2.1

12/15

15.3

0.5

3.0

8.2

0.4

2.3

1/16

15.4

0.1

3.1

8.2

0.0

2.3

2/16

15.4

0.0

2.9

8.2

0.0

2.1

3/16

15.6

0.2

3.2

8.4

0.2

2.4

4/16

15.9

0.2

2.8

8.6

0.2

2.0

5/16

16.1

0.1

2.6

8.6

0.1

1.8

6/16

16.3

0.2

2.6

8.8

0.2

1.8

7/16

16.8

0.4

2.7

9.2

0.4

2.0

RDPI: Real Disposable Personal Income; RDPI-PC, Real Disposable Personal Income Per Capita

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

National Bureau of Economic Research

http://www.nber.org/cycles.html

IA2 Financial Repression. McKinnon (1973) and Shaw (1974) argue that legal restrictions on financial institutions can be detrimental to economic development. “Financial repression” is the term used in the economic literature for these restrictions (see Pelaez and Pelaez, Globalization and the State, Vol. II (2008b), 81-6; for historical analysis see the landmark exhaustive research by Summerhill (2015) and earlier research by Pelaez (1975)). Theory and evidence support the role of financial institutions in efficiency and growth (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 22-6, Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 37-44). Excessive official regulation frustrates financial development required for growth (Haber 2011). Emphasis on disclosure can reduce bank fragility and corruption, empowering investors to enforce sound governance (Barth, Caprio and Levine 2006). Banking was important in facilitating economic growth in historical periods (Cameron 1961, 1967, 1972; Cameron et al. 1992). Banking is also important currently because small- and medium-size business may have no other form of financing than banks in contrast with many options for larger and more mature companies that have access to capital markets. Calomiris and Haber (2014) find that broad voting rights and institutions restricting coalitions of bankers and populists ensure stable banking systems and access to credit. Summerhill (2015) contributes momentous solid facts and analysis with an ideal method combining economic theory, econometrics, international comparisons, data reconstruction and exhaustive archival research. Summerhill (2015) finds that Brazil committed to service of sovereign foreign and internal debt. Contrary to conventional wisdom, Brazil generated primary fiscal surpluses during most of the Empire until 1889 (Summerhill 2015, 37-8, Figure 2.1). Econometric tests by Summerhill (2015, 19-44) show that Brazil’s sovereign debt was sustainable. Sovereign credibility in the North-Weingast (1989) sense spread to financial development that provided the capital for modernization in England and parts of Europe (see Cameron 1961, 1967). Summerhill (2015, 3, 194-6, Figure 7.1) finds that “Brazil’s annual cost of capital in London fell from a peak of 13.9 percent in 1829 to only 5.12 percent in 1889. Average rates on secured loans in the private sector in Rio, however, remained well above 12 percent through 1850.” Financial development would have financed diversification of economic activities, increasing productivity and wages and ensuring economic growth. Brazil restricted creation of limited liability enterprises (Summerhill 2015, 151-82) that prevented raising capital with issue of stocks and corporate bonds. Cameron (1961) analyzed how the industrial revolution in England spread to France and then to the rest of Europe. The Société Générale de Crédit Mobilier of Émile and Isaac Péreire provided the “mobilization of credit” for the new economic activities (Cameron 1961). Summerhill (2015, 151-9) provides facts and analysis demonstrating that regulation prevented the creation of a similar vehicle for financing modernization by Irineu Evangelista de Souza, the legendary Visconde de Mauá. Regulation also prevented the use of negotiable bearing notes of the Caisse Générale of Jacques Lafitte (Cameron 1961, 118-9). The government also restricted establishment and independent operation of banks (Summerhill 2015, 183-214). Summerhill (2005, 198-9) measures concentration in banking that provided economic rents or a social loss. The facts and analysis of Summerhill (2015) provide convincing evidence in support of the economic theory of regulation, which postulates that regulated entities capture the process of regulation to promote their self-interest. There appears to be a case that excessively centralized government can result in regulation favoring private instead of public interests with adverse effects on economic activity. The contribution of Summerhill (2015) explains why Brazil did not benefit from trade as an engine of growth—as did regions of recent settlement in the vision of nineteenth-century trade and development of Ragnar Nurkse (1959)—partly because of restrictions on financing and incorporation. Interest rate ceilings on deposits and loans have been commonly used. The Banking Act of 1933 imposed prohibition of payment of interest on demand deposits and ceilings on interest rates on time deposits. These measures were justified by arguments that the banking panic of the 1930s was caused by competitive rates on bank deposits that led banks to engage in high-risk loans (Friedman, 1970, 18; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 74-5). The objective of policy was to prevent unsound loans in banks. Savings and loan institutions complained of unfair competition from commercial banks that led to continuing controls with the objective of directing savings toward residential construction. Friedman (1970, 15) argues that controls were passive during periods when rates implied on demand deposit were zero or lower and when Regulation Q ceilings on time deposits were above market rates on time deposits. The Great Inflation or stagflation of the 1960s and 1970s changed the relevance of Regulation Q.

Most regulatory actions trigger compensatory measures by the private sector that result in outcomes that are different from those intended by regulation (Kydland and Prescott 1977). Banks offered services to their customers and loans at rates lower than market rates to compensate for the prohibition to pay interest on demand deposits (Friedman 1970, 24). The prohibition of interest on demand deposits was eventually lifted in recent times. In the second half of the 1960s, already in the beginning of the Great Inflation (DeLong 1997), market rates rose above the ceilings of Regulation Q because of higher inflation. Nobody desires savings allocated to time or savings deposits that pay less than expected inflation. This is a fact currently with near zero interest rates, ¼ to ½ percent, and consumer price inflation of 0.8 percent in the 12 months ending in Jul 2016 (http://www.bls.gov/cpi/) but rising during waves of carry trades from zero interest rates to commodity futures exposures (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). Funding problems motivated compensatory measures by banks. Money-center banks developed the large certificate of deposit (CD) to accommodate increasing volumes of loan demand by customers. As Friedman (1970, 25) finds:

“Large negotiable CD’s were particularly hard hit by the interest rate ceiling because they are deposits of financially sophisticated individuals and institutions who have many alternatives. As already noted, they declined from a peak of $24 billion in mid-December, 1968, to less than $12 billion in early October, 1969.”

Banks created different liabilities to compensate for the decline in CDs. As Friedman (1970, 25; 1969) explains:

“The most important single replacement was almost surely ‘liabilities of US banks to foreign branches.’ Prevented from paying a market interest rate on liabilities of home offices in the United States (except to foreign official institutions that are exempt from Regulation Q), the major US banks discovered that they could do so by using the Euro-dollar market. Their European branches could accept time deposits, either on book account or as negotiable CD’s at whatever rate was required to attract them and match them on the asset side of their balance sheet with ‘due from head office.’ The head office could substitute the liability ‘due to foreign branches’ for the liability ‘due on CDs.”

Friedman (1970, 26-7) predicted the future:

“The banks have been forced into costly structural readjustments, the European banking system has been given an unnecessary competitive advantage, and London has been artificially strengthened as a financial center at the expense of New York.”

In short, Depression regulation exported the US financial system to London and offshore centers. What is vividly relevant currently from this experience is the argument by Friedman (1970, 27) that the controls affected the most people with lower incomes and wealth who were forced into accepting controlled-rates on their savings that were lower than those that would be obtained under freer markets. As Friedman (1970, 27) argues:

“These are the people who have the fewest alternative ways to invest their limited assets and are least sophisticated about the alternatives.”

Chart IB-14 of the Bureau of Economic Analysis (BEA) provides quarterly savings as percent of disposable income or the US savings rate from 1980 to 2016. There was a long-term downward sloping trend from 12 percent in the early 1980s to 1.9 percent in Jul 2005. The savings rate then rose during the contraction and in the expansion. In 2011 and into 2012 the savings rate declined as consumption is financed with savings in part because of the disincentive or frustration of receiving a few pennies for every $10,000 of deposits in a bank. The savings rate increased in the final segment of Chart IB-14 in 2012 because of the “fiscal cliff” episode followed by another decline because of the pain of the opportunity cost of zero remuneration for hard-earned savings. There are multiple recent oscillations during expectations of increase or “liftoff” of the fed funds rate in the United States followed by “shallow” monetary policy.

clip_image060

Chart IB-14, US, Personal Savings as a Percentage of Disposable Personal Income, Quarterly, 1980-2016

Source: US Bureau of Economic Analysis

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

Chart IB-14A provides the US personal savings rate, or personal savings as percent of disposable personal income, on an annual basis from 1929 to 2015. The US savings rate shows decline from around 10 percent in the 1960s to around 5 percent currently.

clip_image061

Chart IB-14A, US, Personal Savings as a Percentage of Disposable Personal Income, Annual, 1929-2015

Source: US Bureau of Economic Analysis

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

Table IB-7 provides personal savings as percent of disposable income and annual change of real disposable personal income in selected years since 1930. Savings fell from 4.4 percent of disposable personal income in 1930 to minus 0.8 percent in 1933 while real disposable income contracted 6.3 percent in 1930 and 2.9 percent in 1933. Savings as percent of disposable personal income swelled during World War II to 27.9 percent in 1944 with increase of real disposable income of 3.1 percent. Savings as percent of personal disposable income fell steadily over decades from 11.5 percent in 1982 to 2.6 percent in 2005. Savings as percent of disposable personal income was 5.0 percent in 2013 while real disposable income fell 1.4 percent. The savings rate was 5.6 percent of GDP in 2014 with growth of real disposable income of 3.5 percent. The savings rate was 5.8 percent in 2015 with growth of real disposable income of 3.5 percent. The average ratio of savings as percent of disposable income fell from 9.3 percent in 1980 to 1989 to 5.5 percent on average from 2007 to 2015. Real disposable income grew on average at 3.5 percent from 1980 to 1989 and at 1.7 percent on average from 2007 to 2015.

Table IB-7, US, Personal Savings as Percent of Disposable Personal Income, Annual, Selected Years 1929-1913

 

Personal Savings as Percent of Disposable Personal Income

Annual Change of Real Disposable Personal Income

1930

4.4

-6.3

1933

-0.8

-2.9

1944

27.9

3.1

1947

6.3

-4.1

1954

10.3

1.4

1958

11.4

1.1

1960

10.0

2.6

1970

12.6

4.6

1975

13.0

2.5

1982

11.5

2.1

1989

7.8

3.0

1992

8.9

4.3

2002

5.0

3.1

2003

4.8

2.7

2004

4.5

3.6

2005

2.6

1.5

2006

3.3

4.0

2007

2.9

2.1

2008

4.9

1.5

2009

6.1

-0.4

2010

5.6

1.0

2011

6.0

2.5

2012

7.6

3.2

2013

5.0

-1.4

2014

5.6

3.5

2015

5.8

3.5

Average Savings Ratio

   

1980-1989

9.3

 

2007-2015

5.5

 

Average Yearly ∆% Real Disposable Income

   

1980-1989

 

3.5

2007-2015

 

1.7

Source: US Bureau of Economic Analysis

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

Chart IB-15 of the US Bureau of Economic Analysis provides personal savings as percent of personal disposable income, or savings ratio, from Jan 2007 to Jul 2016.

clip_image062

Chart IB-15, US, Personal Savings as a Percentage of Disposable Income, Monthly 2007-2016

Source: US Bureau of Economic Analysis

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

Table IB-8 provides the savings ratio and changes in real disposable income in selected years. The uncertainties caused by the global recession resulted in sharp increase in the savings ratio that peaked at 7.9 percent in May 2008 (http://www.bea.gov/iTable/index_nipa.cfm). The second peak occurred at 8.1 percent in May 2009. There was another rising trend until 5.9 percent in Jun 2010 and then steady downward trend until 5.6 percent in Nov 2011. This was followed by an upward trend with 7.6 percent in Jun 2012 but decline to 7.1 percent in Aug 2012 followed by jump to 11.0 percent in Dec 2012. Swelling realization of income in Oct-Dec 2012 in anticipation of tax increases in Jan 2013 caused the jump of the savings rate to 11.0 percent in Dec 2012. The BEA explains as “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf). There was a reverse effect in Jan 2013 with decline of the savings rate to 4.9 percent. Real disposable personal income fell 6.2 percent and real disposable per capita income fell from $38,639 in Dec 2012 to $36,216 in Jan 2013 or by 6.3 percent (http://www.bea.gov/iTable/index_nipa.cfm), which is explained by the Bureau of Economic Analysis as follows (page 3 http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf):

“Contributions for government social insurance -- a subtraction in calculating personal income --increased $6.4 billion in February, compared with an increase of $126.8 billion in January. The

January estimate reflected increases in both employer and employee contributions for government social insurance. The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base; together, these changes added $12.9 billion to January. Employer contributions were boosted $5.9 billion in January, which reflected increases in the social security taxable wage base (from $110,100 to $113,700), in the tax rates paid by employers to state unemployment insurance, and in employer contributions for the federal unemployment tax and for pension guaranty. The total contribution of special factors to the January change in contributions for government social insurance was $132.9 billion.”

Table IB-8, US, Savings Ratio and Real Disposable Income, % and ∆%

 

Personal Saving as % Disposable Income

RDPI ∆% 12/07

RDPI ∆% Month

RDPI ∆% YOY

May 2008

7.9

5.1

4.8

5.7

May 2009

8.1

2.5

1.6

-2.5

Jun 2010

5.9

1.8

0.0

1.0

Nov 2011

5.6

4.2

-0.1

1.5

Jun 2012

7.6

7.2

0.2

2.9

Aug 2012

7.1

6.7

-0.2

2.1

Dec 2012

11.0

12.1

2.6

6.8

Jan 2013

4.9

5.2

-6.2

-0.5

Feb 2013

4.7

5.1

0.0

-1.1

Mar 2013

4.8

5.2

0.1

-1.2

Apr 2013

4.9

5.3

0.0

-1.5

May 2013

5.3

5.9

0.6

-1.0

Jun 2013

5.4

6.2

0.2

-1.0

Jul 2013

5.2

6.1

-0.1

-0.8

Aug 2013

5.4

6.4

0.3

-0.3

Sep 2013

5.3

6.7

0.3

-0.5

Oct 2013

4.8

6.4

-0.3

-1.3

Nov 2013

4.6

6.7

0.3

-2.4

Dec 2013

4.7

6.8

0.1

-4.8

Jan 2014

5.3

7.2

0.4

1.9

Feb 2014

5.3

7.8

0.6

2.5

Mar 2014

5.4

8.5

0.6

3.0

Apr 2014

5.5

8.8

0.3

3.3

May 2014

5.7

9.2

0.4

3.1

Jun 2014

5.8

9.7

0.5

3.3

Jul 2014

5.9

9.9

0.2

3.6

Aug 2014

5.6

10.4

0.5

3.8

Sep 2014

5.7

10.6

0.1

3.7

Oct 2014

5.6

11.1

0.4

4.4

Nov 2014

5.5

11.5

0.4

4.5

Dec 2014

5.7

11.8

0.3

4.7

Jan 2015

5.6

11.9

0.1

4.4

Feb 2015

5.7

12.1

0.2

4.0

Mar 2015

5.3

12.1

0.0

3.3

Apr 2015

5.7

12.7

0.6

3.7

May 2015

5.7

13.1

0.4

3.6

Jun 2015

5.8

13.4

0.3

3.4

Jul 2015

5.8

13.7

0.2

3.4

Aug 2015

5.9

14.1

0.3

3.3

Sep 2015

5.9

14.3

0.2

3.3

Oct 2015

6.1

14.6

0.3

3.2

Nov 2015

6.0

14.7

0.1

2.9

Dec 2015

6.1

15.3

0.5

3.0

Jan 2016

6.2

15.4

0.1

3.1

Feb 2016

6.0

15.4

0.0

2.9

Mar 2016

6.2

15.6

0.2

3.2

Apr 2016

5.8

15.9

0.2

2.8

May 2016

5.8

16.1

0.1

2.6

Jun 2016

5.5

16.3

0.2

2.6

Jul 2016

5.7

16.8

0.4

2.7

Source: US Bureau of Economic Analysis

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

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

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