CMP Associates Regulation Blog

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

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

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.

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

Source: Bureau of Labor Statistics

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

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

Source: Bureau of Labor Statistics

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.

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.

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.

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.

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.

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

Source: Bureau of Labor Statistics

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.

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.

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.

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.

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.

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

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 s_i of a demographic group in an industry i and unemployment rate y_i of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):

Y = ∑_is_iy_i (1)

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

∆Y = ∑_i∆s_iy*_i+ ∑_i∆y_is*_i (2)

The first term in (2) captures changes in the demographic and industrial composition of the economy ∆s_i 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 ∆y_i, 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

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

Source: Bureau of Labor Statistics

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

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

Sources: US Bureau of Labor Statistics

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

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

Sources: US Bureau of Labor Statistics

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.

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

Sources: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

Chart I-16, US, Unemployed, SA, 1948-2016, Thousands

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

Chart I-20, US, Part-Time for Economic Reasons, NSA, 1955-2016, Thousands

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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.

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

Source: US Bureau of Labor Statistics

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:

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

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.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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

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

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.federalreserve.gov/releases/g17/Current/default.htm

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

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

Source: Board of Governors of the Federal Reserve

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.

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.

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/

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

{[(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

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

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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

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://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

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.

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.

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.

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, 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

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). ^aExcluding 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.

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

Source: US Bureau of Economic Analysis

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.

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

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

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.

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

Source: US Bureau of Economic Analysis

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).

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

Source: US Bureau of Economic Analysis

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.

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

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):

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

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.

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

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):

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

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 28^th 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.

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

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

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.

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

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.

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.nber.org/cycles.html

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

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

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.nber.org/cycles.html

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

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.

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

Source: US Bureau of Economic Analysis

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.

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

Source: US Bureau of Economic Analysis

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

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.

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

Source: US Bureau of Economic Analysis

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

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