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 7.920 million in Apr 2016 to 7.436 million in May 2016 and increase to 7.783 million in Jun 2016. The rate of unemployment decreased from 5.0 percent in Apr 2016 to 4.7 percent in May 2016 and increased to 4.9 percent in Jun 2016. An important aspect of unemployment is its persistence for more than 27 weeks with 1.979 million in Jun 2016, corresponding to 25.4 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 5.962 million in Apr 2016 to 6.430 million in May 2016 and decreased to 5.843 million in Jun 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 15.809 million in Jun 2016 consists of:

· 7.783 million unemployed (of whom 1.979 million, or 25.4 percent, unemployed for 27 weeks or more) compared with 7.436 million unemployed in May 2016 (of whom 1.885 million, or 25.3 percent, unemployed for 27 weeks or more),

· 5.843 million employed part-time for economic reasons in Jun 2016 (who suffered reductions in their work hours or could not find full-time employment) compared with 6.430 million in May 2016

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

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

2014	Jun 2016	May 2016	Apr 2016
Labor Force Millions	158.880	158.466	158.924
Unemployed Millions	7.783	7.436	7.920
Unemployment Rate (unemployed as % labor force)	4.9	4.7	5.0
Unemployed ≥27 weeks Millions	1.979	1.885	2.063
Unemployed ≥27 weeks %	25.4	25.3	26.0
Part Time for Economic Reasons Millions	5.843	6.430	5.962
Marginally Attached to Labor Force Millions	1.779	1.713	1.715
Job Stress Millions	15.809	15.579	15.597
In Job Stress as % Labor Force	9.9	9.8	9.8

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 Mar 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 59.9 in Mar 2015, 59.7 in Apr 2016, 59.7 in May 2016 and 59.6 in Jun 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

	Jun 2016	May 2016	Apr 2016	Mar 2016
Labor Force	158.880	158.466	158.924	159.286
Participation Rate	62.7	62.6	62.8	63.0
Unemployed	7.783	7.436	7.920	7.966
UNE Rate %	4.9	4.7	5.0	5.0
Part Time Economic Reasons	5.843	6.430	5.962	6.123
Marginally Attached to Labor Force	1.779	1.713	1.715	1.720
In Job Stress	15.606	15.579	15,597	15.809
In Job Stress % Labor Force	9.8	9.8	9.8	9.9
Employed	151.097	151.030	151.004	151.320
Employment % Population	59.6	59.7	59.7	59.9

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 Jun 2016 was 151.990 million (NSA) or 4.675 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 253.397 million in Jun 2016 or by 21.439 million. The number employed increased 3.2 percent from Jul 2007 to Jun 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.2 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 Jun 2016 would result in 160.907 million jobs (0.635 multiplied by noninstitutional civilian population of 253.397 million). There are effectively 8.917 million fewer jobs in Jun 2016 than in Jul 2007, or 160.907 million minus 151.990 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 2.5 percent higher at 160.135 million in Jun 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 160.135 million in Jun 2016 to the noninstitutional population of 253.397 million in Jun 2016 was 63.2 percent. The labor force of the US in Jun 2016 corresponding to 66.8 percent of participation in the population would be 169.269 million (0.668 x 253.397). The difference between the measured labor force in Jun 2016 of 160.135 million and the labor force in Jun 2016 with participation rate of 66.8 percent (as in Jul 2007) of 169.269 million is 9.134 million. The level of the labor force in the US has stagnated and is 9.134 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 63.2 percent NSA in Jun 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 8.144 million in Jun 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 5.1 percent in Jun 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 5.7 percent in Jun 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 5.843 million in Jun 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 6.119 million in Jun 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 9.7 percent in Jun 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 1.779 million in Jun 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 7.1 percent in the 12 months ending in Jun 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 9.4 percent and the number of people in job stress could be around 23.7 million, which is 14.1 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 Jun 2015, May 2016 and Jun 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 Jun 2015, May 2016 and Jun 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 63.1 percent by Jun 2015 and was 62.7 percent in May 2016 and 63.2 percent in Jun 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 7.614 million unemployed in Jun 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 15.758 million (Total UEM) and not 8.144 million (UEM) of whom many have been unemployed long term
the rate of unemployment is 9.4 percent (Total UEM%) and not 5.1 percent, not seasonally adjusted, or 4.9 percent seasonally adjusted
the number of people in job stress is close to 23.7 million by adding the 7.614 million leaving the labor force because they believe they could not find another job, corresponding to 14.1 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 23.959 million in May 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 14.1 percent of the labor force in Jun 2016. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 59.7 percent in Jun 2015, 59.9 percent in May 2016 and 60.0 percent in Jun 2016. The number employed in Jun 2016 was 151.990 million (NSA) or 4.675 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 253.397 million in Jun 2016 or by 21.439 million. The number employed increased 3.2 percent from Jul 2007 to Jun 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.2 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 Jun 2016 would result in 160.907 million jobs (0.635 multiplied by noninstitutional civilian population of 253.397 million). There are effectively 8.917 million fewer jobs in Jun 2016 than in Jul 2007, or 160.907 million minus 151.990 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/2016/06/considerable-uncertainty-about-economic.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 27 quarters from IIIQ2009 to IQ2016. 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 third estimate of GDP for IQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp1q16_3rd.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/financial-asset-values-rebound-from.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.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 IQ2016 would have accumulated to 27.6 percent. GDP in IQ2016 would be $19,129.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2614.9 billion than actual $16,514.6 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.7 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.1 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html). US GDP in IQ2016 is 13.7 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,514.6 billion in IQ2016 or 10.2 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 May 1919 to May 2016. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0886 in May 2016. The actual index NSA in May 2016 is 103.0898, which is 26.9 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 128.9038 in May 2016. The output of manufacturing at 103.0898 in May 2016 is 20.0 percent below trend under this alternative calculation.

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

	2006	Jun 2015	May 2016	Jun 2016
POP	229	250,663	253,174	253,397
LF	151	158,283	158,800	160,135
PART%	66.2	63.1	62.7	63.2
EMP	144	149,645	151,594	151,990
EMP/POP%	62.9	59.7	59.9	60.0
UEM	7	8,638	7,207	8,144
UEM/LF Rate%	4.6	5.5	4.5	5.1
NLF	77	92,380	94,374	93,262
LF PART 66.2%		165,939	167,601	167,749
∆NLF UEM		7,656	8,801	7,614
Total UEM		16,294	16,008	15,758
Total UEM%		9.8	9.6	9.4
Part Time Economic Reasons		6,776	6,238	6,119
Marginally Attached to LF		1,914	1,713	1,779
In Job Stress		24,984	23,959	23,656
People in Job Stress as % Labor Force		15.1	14.3	14.1

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 63.2 percent in Jun 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/2016/06/considerable-uncertainty-about-economic.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	Sep	Oct	Nov	Dec	Annual
1979	62.9	63.0	63.2	62.9	62.9	64.5	63.8	64.0	63.8	63.8	63.7
1980	63.3	63.2	63.2	63.2	63.5	64.6	63.6	63.9	63.7	63.4	63.8
1981	63.2	63.2	63.5	63.6	63.9	64.6	63.5	64.0	63.8	63.4	63.9
1982	63.0	63.2	63.4	63.3	63.9	64.8	64.0	64.1	64.1	63.8	64.0
1983	63.3	63.2	63.3	63.2	63.4	65.1	64.3	64.1	64.1	63.8	64.0
1984	63.3	63.4	63.6	63.7	64.3	65.5	64.4	64.6	64.4	64.3	64.4
1985	64.0	64.0	64.4	64.3	64.6	65.5	64.9	65.1	64.9	64.6	64.8
1986	64.2	64.4	64.6	64.6	65.0	66.3	65.3	65.5	65.4	65.0	65.3
1987	64.7	64.8	65.0	64.9	65.6	66.3	65.5	65.9	65.7	65.5	65.6
1988	65.1	65.2	65.2	65.3	65.5	66.7	65.9	66.1	66.2	65.9	65.9
1989	65.8	65.6	65.7	65.9	66.2	67.4	66.3	66.6	66.7	66.3	66.5
1990	66.0	66.0	66.2	66.1	66.5	67.4	66.4	66.5	66.3	66.1	66.5
1991	65.5	65.7	65.9	66.0	66.0	67.2	66.1	66.1	66.0	65.8	66.2
1992	65.7	65.8	66.0	66.0	66.4	67.6	66.3	66.2	66.2	66.1	66.4
1993	65.6	65.8	65.8	65.6	66.3	67.3	66.1	66.4	66.3	66.2	66.3
1994	66.0	66.2	66.1	66.0	66.5	67.2	66.5	66.8	66.7	66.5	66.6
1995	66.1	66.2	66.4	66.4	66.4	67.2	66.5	66.7	66.5	66.2	66.6
1996	65.8	66.1	66.4	66.2	66.7	67.4	66.8	67.1	67.0	66.7	66.8
1997	66.4	66.5	66.9	66.7	67.0	67.8	67.0	67.1	67.1	67.0	67.1
1998	66.6	66.7	67.0	66.6	67.0	67.7	67.0	67.1	67.1	67.0	67.1
1999	66.7	66.8	66.9	66.7	67.0	67.7	66.8	67.0	67.0	67.0	67.1
2000	66.8	67.0	67.1	67.0	67.0	67.7	66.7	66.9	66.9	67.0	67.1
2001	66.8	66.8	67.0	66.7	66.6	67.2	66.6	66.7	66.6	66.6	66.8
2002	66.2	66.6	66.6	66.4	66.5	67.1	66.6	66.6	66.3	66.2	66.6
2003	66.1	66.2	66.2	66.2	66.2	67.0	65.9	66.1	66.1	65.8	66.2
2004	65.7	65.7	65.8	65.7	65.8	66.5	65.7	66.0	66.1	65.8	66.0
2005	65.4	65.6	65.6	65.8	66.0	66.5	66.1	66.2	66.1	65.9	66.0
2006	65.5	65.7	65.8	65.8	66.0	66.7	66.1	66.4	66.4	66.3	66.2
2007	65.9	65.8	65.9	65.7	65.8	66.6	66.0	66.0	66.1	65.9	66.0
2008	65.7	65.5	65.7	65.7	66.0	66.6	65.9	66.1	65.8	65.7	66.0
2009	65.4	65.5	65.4	65.4	65.5	66.2	65.0	64.9	64.9	64.4	65.4
2010	64.6	64.6	64.8	64.9	64.8	65.1	64.6	64.4	64.4	64.1	64.7
2011	63.9	63.9	64.0	63.9	64.1	64.5	64.2	64.1	63.9	63.8	64.1
2012	63.4	63.6	63.6	63.4	63.8	64.3	63.6	63.8	63.5	63.4	63.7
2013	63.3	63.2	63.1	63.1	63.5	64.0	63.2	62.9	62.9	62.6	63.2
2014	62.5	62.7	62.9	62.6	62.9	63.4	62.8	63.0	62.8	62.5	62.9
2015	62.5	62.5	62.5	62.6	63.0	63.1	62.3	62.5	62.5	62.4	62.7
2016	62.3	62.7	62.8	62.7	62.7	63.2

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. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 27 quarters from IIIQ2009 to IQ2016. 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 IQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp1q16_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/2016/05/appropriate-for-fed-to-increase.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/05/economic-activity-appears-to-have.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 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/05/economic-activity-appears-to-have.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 IQ2016 would have accumulated to 27.6 percent. GDP in IQ2016 would be $19,129.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2624.4 billion than actual $16,505.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.0 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.3 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-monetary.html). US GDP in IQ2016 is 13.7 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,505.1 billion in IQ2016 or 10.1 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 Apr 1919 to Apr 2016. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 140.7011 in Apr 2016. The actual index NSA in Apr 2016 is 103.8348, which is 26.2 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 128.6874 in Apr 2016. The output of manufacturing at 103.8348 in Apr 2016 is 19.3 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 5.1 percent in Jun 2016.

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

Source: US Bureau of Labor Statistics

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 60.0 NSA in Jun 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, 1.5 percent in 2013, 2.4 percent in 2014 and 2.4 percent in 2015. Actual annual equivalent GDP growth in the four quarters of 2012, twelve quarters from IQ2013 to IVQ2015 and IQ2016 is 2.0 percent and 2.0 percent in the four quarters ending in IQ2016. GDP grew at 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. The forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 2.1 to 2.3 percent in 2016 (https://www.federalreserve.gov/monetarypolicy/fomcprojtabl20160316.htm) with less reliable forecast of 2.0 to 2.3 percent in 2017 (https://www.federalreserve.gov/monetarypolicy/fomcprojtabl20160316.htm). Growth of GDP in the expansion from IIIQ2009 to IQ2016 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	1.5
1944	8.0	1994	4.0	2014	2.4
1945	-1.0	1995	2.7	2015	2.4

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

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

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

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	3	-2.4	-0.8
IIIQ1957 to IIQ1958	3	-3.0	-1.0
IVQ1973 to IQ1975	5	-3.1	-0.6
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.5	-0.64
IVQ2007 to 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-seven quarters of the current cyclical expansion from IIIQ2009 to IQ2016. 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

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, 1.5 percent in 2013, 2.4 percent in 2014 and 2.4 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 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 and IQ2016 accumulated to 8.7 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IQ2016 of $16,514.6 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/17: {[($16,514.6/$15,190.3)^4/17 -1]100 = 2.0 percent}.

Table I-5 shows that GDP grew 15.0 percent in the first twenty-seven quarters of expansion from IIIQ2009 to IQ2016 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	13 15 16 17 18 19 20 21 22 23 24 25 26 27	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	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
First Four Quarters IQ1983 to IVQ1983	4	7.8
Average First Four Quarters in Four Expansions*		7.7
IIIQ2009 to IQ2016	27	15.0	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 Jun 2016 was 151.990 million (NSA) or 4.675 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 253.397 million in Jun 2016 or by 21.439 million. The number employed increased 3.2 percent from Jul 2007 to Jun 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.2 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 Jun 2016 would result in 160.907 million jobs (0.635 multiplied by noninstitutional civilian population of 253.397 million). There are effectively 8.917 million fewer jobs in Jun 2016 than in Jul 2007, or 160.907 million minus 151.990 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 2.5 percent higher at 160.135 million in Jun 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 160.135 million in Jun 2016 to the noninstitutional population of 253.397 million in Jun 2016 was 63.2 percent. The labor force of the US in Jun 2016 corresponding to 66.8 percent of participation in the population would be 169.269 million (0.668 x 253.397). The difference between the measured labor force in Jun 2016 of 160.135 million and the labor force in Jun 2016 with participation rate of 66.8 percent (as in Jul 2007) of 169.269 million is 9.134 million. The level of the labor force in the US has stagnated and is 9.134 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 in Dec 1984 million 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 7.783 million in Junn 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 8.144 million in Jun 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 Jun 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 59.6 in Jun 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 60.0 percent in Jun 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 1.979 million in Jun 2016 seasonally adjusted and 1.904 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 6.119 million not seasonally adjusted in Jun 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 1.779 million in Jun 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 287,000 in Jun 2016 and private payroll employment increased 265,000. The average monthly number of nonfarm jobs created from Jun 2014 to Jun 2015 was 240,083 using seasonally adjusted data, while the average number of nonfarm jobs created from Jun 2015 to Jun 2016 was 204,250, or decrease by 14.9 percent. The average number of private jobs created in the US from Jun 2014 to Jun 2015 was 232,000, using seasonally adjusted data, while the average from Jun 2015 to Jun 2016 was 193,500, or decrease by 16.6 percent. This blog calculates the effective labor force of the US at 167.749 million in Jun 2015 and 165.939 million in Jun 2016 (Table I-4), for growth of 1.810 million at average 150,833 per month. The difference between the average increase of 193,500 new private nonfarm jobs per month in the US from Jun 2015 to Jun 2016 and the 150,833 average monthly increase in the labor force from Jun 2015 to Jun 2016 is 42,667 monthly new jobs net of absorption of new entrants in the labor force. There are 23.656 million in job stress in the US currently. Creation of 42,667 new jobs per month net of absorption of new entrants in the labor force would require 554 months to provide jobs for the unemployed and underemployed (23.656 million divided by 42,667) or 46 years (554 divided by 12). The civilian labor force of the US in Jun 2016 not seasonally adjusted stood at 160.135 million with 8.144 million unemployed or effectively 15.758 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 167.749 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 1.95 years (1 million divided by product of 42,667 by 12, which is 512,004). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 8.007 million (0.05 times labor force of 160.135 million). New net job creation would be 0.137 million (8.144 million unemployed minus 8.007 million unemployed at rate of 5 percent) that at the current rate would take 0.3 years (0.137 million divided by 512,004). Under the calculation in this blog, there are 15.758 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 167.749 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 7.628 million jobs net of labor force growth that at the current rate would take 14.4 years (15.758 million minus 0.05(167.749 million) = 7.371 million divided by 512,004 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 Jun 2016 was 151.990 million (NSA) or 4.675 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 253.397 million in Jun 2016 or by 21.439 million. The number employed increased 3.2 percent from Jul 2007 to Jun 2016 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 9.2 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 Jun 2016 would result in 160.907 million jobs (0.635 multiplied by noninstitutional civilian population of 253.397 million). There are effectively 8.917 million fewer jobs in Jun 2016 than in Jul 2007, or 160.907 million minus 151.990 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			11	-6
Jun			116			287	265
Jul			40
Aug			49
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 Jun 2015 to Jun 2016, not seasonally adjusted (NSA), are in Table I-9. Total nonfarm employment increased by 2,522,000 (row A, column Change), consisting of growth of total private employment by 2,405,000 (row B, column Change) and increase by 117,000 of government employment (row C, column Change). Monthly average growth of private payroll employment has been 200,417, which is mediocre relative to 24 to 30 million in job stress, while total nonfarm employment has grown on average by only 210,167 per month, which does not significantly reduce job stress with 150,833 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 33,000, at the monthly rate of minus 2750 while private service providing employment grew by 2,342,000, at the monthly average rate of 195,167. An important feature in Table I-9 is that jobs in professional and business services increased 533,000 with temporary help services increasing 22,000. 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 444,000 jobs in 12 months. An important characteristic is that the loss of government jobs has stabilized in federal government with increase of 30,000 jobs while states increased 3,000 jobs and local government added 84,000 jobs. Local government provides the bulk of government jobs, 14.396 million, while federal government provides 2.794 million and states’ government 4.858 million.

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

	Jun 2015	Jun 2016	Change
A Total Nonfarm	142,717	145,239	2,522
B Total Private	120,786	123,191	2,405
B1 Goods Producing	19,853	19,916	63
B1a Manufacturing	12,407	12,374	-33
B2 Private service providing	100,933	103,275	2,342
B2a Wholesale Trade	5,911	5,965	54
B2b Retail Trade	15,644	15,963	319
B2c Transportation & Warehousing	4,839	4,879	40
B2d Financial Activities	8,168	8,337	169
B2e Professional and Business Services	19,797	20,330	533
B2e1 Temporary help services	2,901	2,923	22
B2f Health Care & Social Assistance	18,572	19,170	598
B2g Leisure & Hospitality	15,742	16,186	444
C Government	21,931	22,048	117
C1 Federal	2,764	2,794	30
C2 State	4,855	4,858	3
C3 Local	14,312	14,396	84

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 May 2016 and

Jun 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 287,000 SA total nonfarm jobs created in Jun 2016 relative to May 2016 actually correspond to increase of 682,000 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 265,000 total private payroll jobs SA created in Jun 2016 relative to May 2016 actually correspond to increase of 1,086,000 jobs NSA. The analysis of NSA job creation in the prior Table I-9 does show improvement over the 12 months ending in Jun 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

	May 2016 SA	Jun 2016 SA	∆	May 2016 NSA	Jun 2016 NSA	∆
A Total Nonfarm	143,888	144,175	287	144,557	145,239	682
B Total Private	121,791	122,056	265	122,105	123,191	1086
B1 Goods Producing	19,622	19,631	9	19,644	19,916	272
B1a Constr.	6,643	6,643	0	6,699	6,850	151
B Mfg	12,282	12,296	14	12,256	12,374	118
B2 Private Service Providing	102,169	102,425	256	102,461	103,275	814
B2a Wholesale Trade	5,921	5,925	4	5,934	5,965	31
B2b Retail Trade	15,922	15,952	30	15,854	15,963	109
B2c Couriers & Mess.	617	618	1	588	596	8
B2d Health-care & Social Assistance	19,094	19,152	58	19,119	19,170	51
B2De Profess. & Business Services	20,120	20,158	38	20,137	20,330	193
B2De1 Temp Help Services	2,887	2,902	15	2,884	2,923	39
B2f Leisure & Hospit.	15,443	15,502	59	15,711	16,186	475

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

Source: US Bureau of Labor Statistics

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

Manufacturing jobs not seasonally adjusted decreased 33,000 from Jun 2015 to
Jun 2016 or at the average monthly rate of minus 2750. There are effects of the weaker economy and international trade together with the yearly adjustment of labor statistics. Industrial production decreased 0.4 percent in May 2016 and increased 0.6 percent in Apr 2016 after decreasing 1.0 percent in Mar 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 17.9 percent from the trough in Apr 2009 to May 2016. Manufacturing in May 2016 is lower by 8.4 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 IQ2016 would have accumulated to 27.6 percent. GDP in IQ2016 would be $19,129.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2614.9 billion than actual $16,514.6 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.7 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.1 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html). US GDP in IQ2016 is 13.7 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,514.6 billion in IQ2016 or 10.2 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 May 1919 to May 2016. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0886 in May 2016. The actual index NSA in May 2016 is 103.0898, which is 26.9 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 128.9038 in May 2016. The output of manufacturing at 103.0898 in May 2016 is 20.0 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 87.6 percent in IQ2016. Most of US national income is in the form of services. In Jun 2016, there were 145.239 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 123.191 million NSA in Jun 2016 accounted for 84.8 percent of total nonfarm jobs of 145.239 million, of which 12.374 million, or 10.0 percent of total private jobs and 8.5 percent of total nonfarm jobs, were in manufacturing. Private service-providing jobs were 103.275 million NSA in Jun 2016, or 71.1 percent of total nonfarm jobs and 83.8 percent of total private-sector jobs. Manufacturing has share of 10.8 percent in US national income in IQ2016 and durable goods 6.3 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 IVQ2015	% Total	SAAR IQ2016	% Total
National Income WCCA	15,949.3	100.0	16,047.3	100.0
Domestic Industries	15,756.7	98.8	15,893.5	99.0
Private Industries	13,940.7	87.4	14,062.9	87.6
Agriculture	156.2	1.0	146.6	0.9
Mining	239.6	1.5	233.4	1.5
Utilities	178.9	1.1	178.8	1.1
Construction	755.0	4.7	767.7	4.8
Manufacturing	1733.7	10.9	1730.7	10.8
Durable Goods	1015.8	6.4	1013.8	6.3
Nondurable Goods	718.0	4.5	716.9	4.5
Wholesale Trade	972.5	6.1	976.7	6.1
Retail Trade	1096.6	6.9	1104.0	6.9
Transportation & WH	527.7	3.3	522.9	3.3
Information	609.7	3.8	617.4	3.8
Finance, Insurance, RE	2779.1	17.4	2843.6	17.7
Professional & Business Services	2159.8	13.5	2170.6	13.5
Education, Health Care	1596.3	10.0	1621.8	10.1
Arts, Entertainment	675.8	4.2	683.8	4.3
Other Services	459.7	2.9	465.0	2.9
Government	1816.0	11.4	1830.6	11.4
Rest of the World	192.7	1.2	153.9	1.0

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

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

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

The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). Table I-12 provides total annual level nonfarm employment in the US for the 1980s and the 2000s, which is different from 12-month comparisons. Nonfarm jobs rose by 4.859 million from 1982 to 1984, or 5.4 percent, and continued rapid growth in the rest of the decade. In contrast, nonfarm jobs are down by 7.638 million in 2010 relative to 2007 and fell by 952,000 in 2010 relative to 2009 even after six quarters of GDP growth. Monetary and fiscal stimuli have failed in increasing growth to rates required for mitigating job stress. The initial growth impulse reflects a flatter growth curve in the current expansion. Nonfarm jobs declined from 137.999 million in 2007 to 136.381 million in 2013, by 1.618 million or 1.2 percent. Nonfarm jobs increased from 137.999 million in 2007 to 141,865 million in 2015, by 3.866 million or 2.8 percent. The US noninstitutional population or in condition to work increased from 231.867 million in 2007 to 250,801 million in 2015, by 18.934 million or 8.2 percent. The ratio of nonfarm jobs of 137.999 million in 2007 to the noninstitutional population of 231.867 was 59.5. Nonfarm jobs in 2015 corresponding to the ratio of 59.5 of nonfarm jobs/noninstitutional population would be 149.227 million (0.595x250.801). The difference between actual nonfarm jobs of 141.865 million in 2015 and nonfarm jobs of 149.227 million that are equivalent to 59.5 percent of the noninstitutional population as in 2007 is 7.362 million fewer jobs. The proper explanation for this loss of work opportunities is not in secular stagnation but in cyclically slow growth. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IQ2016 would have accumulated to 27.6 percent. GDP in IQ2016 would be $19,129.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2614.9 billion than actual $16,514.6 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.7 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.1 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html). US GDP in IQ2016 is 13.7 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,514.6 billion in IQ2016 or 10.2 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 May 1919 to May 2016. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0886 in May 2016. The actual index NSA in May 2016 is 103.0898, which is 26.9 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 128.9038 in May 2016. The output of manufacturing at 103.0898 in May 2016 is 20.0 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 May 2016)/(wage bill in May 2015)]-1}100 =

{[($25.68x34.6)/($24.89x34.4)]-1]}100

= {[($888.53)/($856.22]-1}100 = 3.8%

CPI inflation was 1.0 percent in the 12 months ending in May 2016 (http://www.bls.gov/cpi/) for an inflation-adjusted wage-bill change of 2.7 percent :{[(1.038/1.01)-1]100 = 2.7%} (see Table IB-5 below for Apr 2016 with minor rounding difference). The wage bill for Jun 2016 before inflation adjustment increased 2.3 percent relative to the wage bill for Jun 2015:

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

{[($25.42x34.4)/($24.78x34.5)]-1]}100

= {[$874.45)/$854.91]-1}100 = 2.3%

Average hourly earnings increased 2.6 percent from Jun 2015 to Jun 2016 {[($25.42/$24.78) – 1]100 = 2.6%} while hours worked decreased 0.9 percent {[(34.4/34.5) – 1]100 = -0.3%}. The increase of the wage bill is the product of the increase of hourly earnings of 2.6 percent and increase of hours worked of minus 0.3 percent {[(1.026x0.997) -1]100 = 2.3%} 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/2016/06/fomc-projections-world-inflation-waves.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	Jun 2015	Apr 2016	May 2016	Jun 2016
Total Private	$24.96	$25.53	$25.59	$25.61
Goods Producing	$26.09	$26.81	$26.92	$26.90
Service Providing	$24.69	$25.23	$25.28	$25.31
Average Weekly Earnings
Total Private	$861.12	$878.23	$880.30	$880.98
Goods Producing	$1,051.43	$1,080.44	$1,084.88	$1,084.07
Service Providing	$824.65	$840.16	$841.82	$842.82
Average Weekly Hours
Total Private	34.5	34.4	34.4	34.4
Goods Producing	40.3	40.3	40.3	40.3
Service Providing	33.4	33.3	33.3	33.3

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 Jun 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

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 are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2016/06/considerable-uncertainty-about-economic.html) originating in weak economic growth (http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.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

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 are oscillating in in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2016/06/considerable-uncertainty-about-economic.html) originating in weak economic growth (http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available in the release for Jan 2016 and subsequent releases.

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

Year	Jan	Feb	Mar	Apr	May	Nov	Dec
2006			10.05	10.11	9.91	10.14	10.21
2007	10.22	10.21	10.11	10.16	9.99	10.02	10.15
2008	10.09	10.09	10.08	9.98	9.88	10.34	10.45
2009	10.44	10.48	10.45	10.38	10.31	10.38	10.36
2010	10.39	10.41	10.33	10.33	10.36	10.37	10.38
2011	10.52	10.39	10.25	10.21	10.21	10.23	10.29
2012	10.39	10.28	10.20	10.27	10.15	10.25	10.39
∆%12M	-1.2	-1.1	-0.5	0.6	-0.6	0.2	1.0
2013	10.37	10.30	10.24	10.29	10.22	10.35	10.43
∆%12M	-0.2	0.2	0.4	0.2	0.7	1.0	0.4
2014	10.41	10.47	10.37	10.29	10.22	10.50	10.47
∆%12M	0.4	1.7	1.3	0.0	0.0	1.4	0.4
2015	10.65	10.68	10.61	10.55	10.47	10.70	10.66
∆%12M	2.3	2.0	2.3	2.5	2.4	1.9	1.8
2016	10.77	10.76	10.70	10.70	10.69
∆%12M	1.1	0.7	0.8	1.4	2.1

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/2016/06/considerable-uncertainty-about-economic.html), stagnating/declining real wages and 23.7 million unemployed or underemployed (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html) because of mediocre economic growth (http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.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-May 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 2.4 percent in the 12 months ending in Apr 2015. Average weekly earnings adjusted for inflation increased 2.4 percent in the 12 months ending in May 2015 and increased 0.2 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. 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/2016/06/fomc-projections-world-inflation-waves.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 23.7 million unemployed or underemployed (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html) in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2016/06/considerable-uncertainty-about-economic.html) because of mediocre economic growth (http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.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	Jan	Feb	Mar	Apr	May	Dec
2007	346.51	347.19	345.74	350.37	342.59	353.08
2008	342.93	343.22	348.71	341.17	337.84	354.11
2009	350.89	356.19	354.13	347.66	346.28	350.29
2010	350.09	349.89	349.29	351.37	356.33	355.14
2011	359.67	353.35	349.44	349.14	353.10	353.95
2012	358.60	351.52	348.72	355.19	347.04	361.49
∆%12M	-0.3	-0.5	-0.2	1.7	-1.7	2.1
2013	352.58	352.21	351.29	352.84	350.44	361.82
∆%12M	-1.7	0.2	0.7	-0.7	1.0	0.1
2014	353.93	360.14	359.79	354.05	351.52	362.34
∆%12M	0.4	2.3	2.4	0.3	0.3	0.1
2015	364.09	369.41	368.14	362.76	360.05	367.86
∆%12M	2.9	2.6	2.3	2.5	2.4	1.5
2016	368.39	366.87	366.08	367.00	369.86
∆%12M	1.2	-0.7	-0.6	1.2	2.7

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 United States Balance of Payments Current Account. The current account of the US balance of payments is in Table IIA2-1 for IQ2015 and IQ2016. The Bureau of Economic Analysis analyzes as follows (http://www.bea.gov/newsreleases/international/transactions/2016/pdf/trans116.pdf):

“The U.S. current-account deficit—a net measure of transactions between the United States and the rest of the world in goods, services, primary income, and secondary income—increased to $124.7 billion (preliminary) in the first quarter of 2016 from $113.4 billion (revised) in the fourth quarter of 2015, according to statistics released by the Bureau of Economic Analysis (BEA). The deficit increased to 2.7 percent of current-dollar gross domestic product (GDP) from 2.5 percent in the fourth quarter.

The $11.3 billion increase reflected a $9.6 billion decrease in the surplus on primary income to $37.5 billion and a $4.0 billion increase in the deficit on secondary income to $40.3 billion. These changes were partly offset by a $2.0 billion decrease in the deficit on goods to $186.4 billion and a $0.4 billion increase in the surplus on services to $64.6 billion.”

The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US not seasonally adjusted increased from $92.1 billion in IQ2015 to $103.1 billion in IQ2016. The current account deficit seasonally adjusted at annual rate decreased from 2.6 percent of GDP in IQ2015 to 2.5 percent of GDP in IVQ2015, increasing to 2.7 percent of GDP in IQ2016. The ratio of the current account deficit to GDP has stabilized below 3 percent of GDP compared with much higher percentages before the recession but is combined now with much higher imbalance in the Treasury budget (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71).

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

	IQ2015	IQ2016	Difference
Goods Balance	-173,428	-169,044	-4,384
X Goods	375,070	348,639	-7.0 ∆%
M Goods	-548,498	-517,683	-5.6 ∆%
Services Balance	70,311	69,299	-1,012
X Services	185,005	185,944	0.5 ∆%
M Services	-114,694	-116,645	1.7 ∆%
Balance Goods and Services	-103,117	-99,745	-3,372
Exports of Goods and Services and Income Receipts	783,881	757,604
Imports of Goods and Services and Income Payments	-876,027	-860,739
Current Account Balance	-92,146	-103,135	10,989
% GDP	IQ2015	IQ2016	IVQ2015
	2.6	2.7	2.5

X: exports; M: imports

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

Source: Bureau of Economic Analysis

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

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

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

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

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

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

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

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

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

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

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

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

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

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

(M_t + B_t)/P_t = E_t∫(1/R_t_{, t+τ})s_t_+τdτ (4)

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

M_tV(i_t, ·) = P_tY_t (5)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The most recent CBO long-term budget on Jun 16, 2015, projects US federal debt at 103 percent of GDP in 2040 (CBO (2015Jun15). The 2015 long-term budget outlook. Washington, DC, Congressional Budget Office, Jun 16).

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

	2007	2008	2009	2010	2011
Goods & Services	-705	-709	-384	-495	-549
Primary Income	101	146	124	178	221
Secondary Income	-114	-128	-124	-125	-133
Current Account	-719	-691	-384	-442	-460
NGDP	14478	14719	14419	14964	15518
Current Account % GDP	-5.0	-4.7	-2.7	-3.0	-3.0
NIIP	-1279	-3995	-2628	-2512	-4455
US Owned Assets Abroad	20705	19423	19426	21767	22209
Foreign Owned Assets in US	21984	23418	22054	24279	26664
NIIP % GDP	-8.8	-27.1	-18.2	-16.8	-28.7
Exports Goods, Services and Income	2569	2751	2286	2631	2988
NIIP % Exports Goods, Services and Income	-50	-145	-115	-95	-149
DIA MV	5858	3707	4945	5486	5215
DIUS MV	4134	3091	3619	4099	4199
Fiscal Balance	-161	-459	-1413	-1294	-1300
Fiscal Balance % GDP	-1.1	-3.1	-9.8	-8.7	-8.5
Federal Debt	5035	5803	7545	9019	10128
Federal Debt % GDP	35.2	39.3	52.3	60.9	65.9
Federal Outlays	2729	2983	3518	3457	3603
∆%	2.8	9.3	17.9	-1.7	4.2
% GDP	19.1	20.2	24.4	23.4	23.4
Federal Revenue	2568	2524	2105	2163	2303
∆%	6.7	-1.7	-16.6	2.7	6.5
% GDP	17.9	17.1	14.6	14.6	15.0

	2012	2013	2014	2015
Goods & Services	-538	-462	-490	-500
Primary Income	216	219	224	182
Secondary Income	-126	-124	-126	-145
Current Account	-447	-366	-392	-463
NGDP	16155	16663	17348	17947
Current Account % GDP	-2.8	-2.2	-2.3	2.6
NIIP	-4518	-5373	-7046	-7281
US Owned Assets Abroad	22562	24145	24718	23341
Foreign Owned Assets in US	27080	29517	31764	30621
NIIP % GDP	-28.0	-32.2	-40.6	-40.6
Exports Goods, Services and Income	3097	3215	3339	3173
NIIP % Exports Goods, Services and Income	-146	-167	-211	-229
DIA MV	5969	7121	7133	6978
DIUS MV	4662	5815	6350	6544
Fiscal Balance	-1087	-680	-485	-438
Fiscal Balance % GDP	-6.8	-4.1	-2.8	-2.5
Federal Debt	11281	11983	12780	13117
Federal Debt % GDP	70.4	72.6	74.4	73.6
Federal Outlays	3537	3455	3506	3688
∆%	-1.8	-2.3	1.5	5.2
% GDP	22.1	20.9	20.4	20.7
Federal Revenue	2450	2775	3022	3250
∆%	6.4	13.3	8.9	7.6
% GDP	15.3	16.8	17.6	18.2

Sources:

Notes: NGDP: nominal GDP or in current dollars; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value. There are minor discrepancies in the decimal point of percentages of GDP between the balance of payments data and federal debt, outlays, revenue and deficits in which the original number of the CBO source is maintained. See Bureau of Economic Analysis, US International Economic Accounts: Concepts and Methods. 2014. Washington, DC: BEA, Department of Commerce, Jun 2014 http://www.bea.gov/international/concepts_methods.htm These discrepancies do not alter conclusions. Budget http://www.cbo.gov/ https://www.cbo.gov/about/products/budget_economic_data#3 https://www.cbo.gov/about/products/budget_economic_data#2 Balance of Payments and NIIP http://www.bea.gov/international/index.htm#bop Gross Domestic Product, Bureau of Economic Analysis (BEA) http://www.bea.gov/iTable/index_nipa.cfm

Table VI-3C provides quarterly estimates NSA of the external imbalance of the United States. The current account deficit seasonally adjusted decreases from 2.6 percent of GDP in IQ2015 to 2.5 percent in IIQ2015. The current account deficit increases to 2.7 percent of GDP in IIIQ2015. The deficit decreases to 2.5 percent in IVQ2015 and increases to 2.7 percent to IQ2016. The net international investment position decreases from minus $6.8 trillion in IQ2015 to minus $6.7 trillion in IIQ2015, increasing at minus $7.2 trillion in IIIQ2015. The net international investment position increases to minus $7.3 trillion in IVQ2015 and increases to minus $7.5 trillion in IVQ2015. The BEA explains as follows (http://www.bea.gov/newsreleases/international/intinv/2016/pdf/intinv116.pdf):

“The U.S. net international investment position at the end of the first quarter of 2016 was −$7,525.6 billion (preliminary) as the value of U.S. liabilities exceeded the value of U.S. assets. At the end of the fourth quarter of 2015, the net investment position was −$7,280.6 billion. The U.S. net international investment position was −$7,280.6 billion (revised) at the end of 2015 compared with −$7,046.1 billion (revised) at the end of 2014 (table 2). The $234.5 billion decrease in the net investment position was mostly due to net financial transactions—net U.S. acquisition of assets excluding financial derivatives less net U.S. incurrence of liabilities excluding financial derivatives plus net transactions in financial derivatives. Other changes in position, which include price changes, exchange-rate changes, and changes in volume and valuation n.i.e., also contributed to the decrease.”

The BEA explains further (http://www.bea.gov/newsreleases/international/intinv/2016/pdf/intinv116.pdf): “U.S. assets decreased $1,376.8 billion to $23,340.8 billion at the end of 2015. Financial derivatives with a gross positive fair value decreased $818.8 billion, and assets excluding financial derivatives decreased $558.0 billion. The decrease in assets excluding financial derivatives reflected exchange rate changes of −$1,141.5 billion that were partly offset by financial transactions of $225.4 billion, price changes of $220.4 billion, and changes in volume and valuation n.i.e. of $137.7 billion. Net exchange-rate changes of −$1,051.5 billion reflected the depreciation of major foreign currencies against the U.S. dollar that lowered the dollar value of U.S. assets significantly more than the decline in the dollar value of U.S. liabilities.”

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

	IQ2015	IIQ2015	IIIQ2015	IVQ2015	IQ2016
Goods & Services	-103	-131	-139	-127	-100
Primary Income	48	44	43	48	38
Secondary Income	-37	-31	-41	-36	-41
Current Account	-92	-119	-137	-114	-103
Current Account % GDP	-2.6	-2.5	-2.7	-2.5	-2.7
NIIP	-6838	-6701	-7240	-7281	-7526
US Owned Assets Abroad	25495	24696	23478	23341	24083
Foreign Owned Assets in US	-32333	-31397	-30718	-30621	-31609
DIA MV	7332	7384	6785	6978	7012
DIA MV Equity	6195	6213	5640	5811	5833
DIUS MV	6536	6589	6260	6544	6638
DIUS MV Equity	5022	5024	4682	4979	5045

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

IIA United States International Trade. Table IIA-1 provides the trade balance of the US and monthly growth of exports and imports seasonally adjusted with the latest release and revisions (http://www.census.gov/foreign-trade/). Because of heavy dependence on imported oil, fluctuations in the US trade account originate largely in fluctuations of commodity futures prices caused by carry trades from zero interest rates into commodity futures exposures in a process similar to world inflation waves (http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html). The Census Bureau revised data for 2016, 2015, 2014 and 2013. Exports decreased 0.2 percent in May 2016 while imports increased 1.6 percent. The trade deficit increased from $37,383 million in Apr 2016 to $41,144 million in May 2016. The trade deficit deteriorated to $48,189 million in Mar 2015. The trade deficit improved to $40,885 million in Apr 2015 and $40,170 million in May 2015. The trade deficit deteriorated to $42,973 million in Jun 2015 and improved to $39,900 million in Jul 2015, deteriorating to $44,639 million in Aug 2015. The trade deficit improved to $41,072 million in Sep 2015, deteriorating to $41,600 million in Oct 2015 and improving to $41,122 million in Nov 2015. The trade deficit deteriorated to $44,028 million in Feb 2016, improving to $35,536 million in Mar 2016. The trade deficit deteriorated to $37,383 million in Apr 2016, deteriorating to $41,144 million in May 2016.

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

	Trade Balance	Exports	Month ∆%	Imports	Month ∆%
May 2016	-41,144	182,354	-0.2	223,498	1.6
Apr	-37,383	182,668	1.4	220,051	2.0
Mar	-35,536	180,174	-1.1	215,709	-4.6
Feb	-44,028	182,159	1.3	226,187	1.8
Jan	-42,308	179,771	-1.8	222,079	-1.1
Dec 2015	-41,487	183,074	-0.3	224,561	-0.1
Nov	-41,122	183,576	-1.1	224,698	-1.1
Oct	-41,600	185,587	-1.0	227,186	-0.6
Sep	-41,072	187,550	0.5	228,622	-1.1
Aug	-44,639	186,620	-1.8	231,259	0.5
Jul	-39,900	190,106	-0.1	230,006	-1.4
Jun	-42,973	190,347	0.0	233,320	1.2
May	-40,170	190,361	-0.7	230,531	-0.9
Apr	-40,885	191,675	0.6	232,560	-2.5
Mar	-48,189	190,448	0.3	238,637	5.5
Feb	-36,268	189,852	-1.1	226,121	-3.4
Jan	-42,057	191,968	-2.8	234,024	-3.0
Jan-Dec 2015	-500,361	2,261,163	-4.9	2,761,525	-3.7

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

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

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

	Balance	∆%	Exports	∆%	Imports	∆%
1960	4,608	(X)	19,626	(X)	15,018	(X)
1961	5,476	18.8	20,190	2.9	14,714	-2.0
1962	4,583	-16.3	20,973	3.9	16,390	11.4
1963	5,289	15.4	22,427	6.9	17,138	4.6
1964	7,006	32.5	25,690	14.5	18,684	9.0
1965	5,333	-23.9	26,699	3.9	21,366	14.4
1966	3,837	-28.1	29,379	10.0	25,542	19.5
1967	4,122	7.4	30,934	5.3	26,812	5.0
1968	837	-79.7	34,063	10.1	33,226	23.9
1969	1,289	54.0	37,332	9.6	36,043	8.5
1970	3,224	150.1	43,176	15.7	39,952	10.8
1971	-1,476	-145.8	44,087	2.1	45,563	14.0
1972	-5,729	288.1	49,854	13.1	55,583	22.0
1973	2,389	-141.7	71,865	44.2	69,476	25.0
1974	-3,884	-262.6	99,437	38.4	103,321	48.7
1975	9,551	-345.9	108,856	9.5	99,305	-3.9
1976	-7,820	-181.9	116,794	7.3	124,614	25.5
1977	-28,352	262.6	123,182	5.5	151,534	21.6
1978	-30,205	6.5	145,847	18.4	176,052	16.2
1979	-23,922	-20.8	186,363	27.8	210,285	19.4
1980	-19,696	-17.7	225,566	21.0	245,262	16.6
1981	-22,267	13.1	238,715	5.8	260,982	6.4
1982	-27,510	23.5	216,442	-9.3	243,952	-6.5
1983	-52,409	90.5	205,639	-5.0	258,048	5.8
1984	-106,702	103.6	223,976	8.9	330,678	28.1
1985	-117,711	10.3	218,815	-2.3	336,526	1.8
1986	-138,279	17.5	227,159	3.8	365,438	8.6
1987	-152,119	10.0	254,122	11.9	406,241	11.2
1988	-118,526	-22.1	322,426	26.9	440,952	8.5
1989	-109,399	-7.7	363,812	12.8	473,211	7.3
1990	-101,719	-7.0	393,592	8.2	495,311	4.7
1991	-66,723	-34.4	421,730	7.1	488,453	-1.4
1992	-84,501	26.6	448,164	6.3	532,665	9.1
1993	-115,568	36.8	465,091	3.8	580,659	9.0
1994	-150,630	30.3	512,626	10.2	663,256	14.2
1995	-158,801	5.4	584,742	14.1	743,543	12.1
1996	-170,214	7.2	625,075	6.9	795,289	7.0
1997	-180,522	6.1	689,182	10.3	869,704	9.4
1998	-229,758	27.3	682,138	-1.0	911,896	4.9
1999	-328,821	43.1	695,797	2.0	1,024,618	12.4
2000	-436,104	32.6	781,918	12.4	1,218,022	18.9
2001	-411,899	-5.6	729,100	-6.8	1,140,999	-6.3
2002	-468,263	13.7	693,103	-4.9	1,161,366	1.8
2003	-532,350	13.7	724,771	4.6	1,257,121	8.2
2004	-654,830	23.0	814,875	12.4	1,469,704	16.9
2005	-772,373	18.0	901,082	10.6	1,673,455	13.9
2006	-827,971	7.2	1,025,967	13.9	1,853,938	10.8
2007	-808,763	-2.3	1,148,199	11.9	1,956,962	5.6
2008	-816,199	0.9	1,287,442	12.1	2,103,641	7.5
2009	-503,582	-38.3	1,056,043	-18.0	1,559,625	-25.9
2010	-635,362	26.2	1,278,495	21.1	1,913,857	22.7
2011	-725,447	14.2	1,482,508	16.0	2,207,954	15.4
2012	-730,446	0.7	1,545,821	4.3	2,276,267	3.1
2013	-689,470	-5.6	1,578,517	2.1	2,267,987	-0.4
2014	-735,194	6.6	1,621,172	2.7	2,356,366	3.9
2015	-745,660	1.4	1,502,572	-7.3	2,248,232	-4.6

Source: US Census Bureau, Foreign Trade Division

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

Chart IIA-1 of the US Census Bureau of the Department of Commerce shows that the trade deficit (gap between exports and imports) fell during the economic contraction after 2007 but has grown again during the expansion. The low average rate of growth of GDP of 2.1 percent during the expansion beginning since IIIQ2009 does not deteriorate further the trade balance. Higher rates of growth may cause sharper deterioration.

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

Source: US Census Bureau

Table IIA-2B provides the US international trade balance, exports and imports of goods and services on an annual basis from 1992 to 2015. The trade balance deteriorated sharply over the long term. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US not seasonally adjusted increased from $92.1 billion in IQ2015 to $103.1 billion in IQ2016 (http://www.bea.gov/international/index.htm). The current account deficit seasonally adjusted at annual rate decreased from 2.6 percent of GDP in IQ2015 to 2.5 percent of GDP in IVQ2015 and increasing to 2.7 percent of GDP in IQ2016 (http://www.bea.gov/international/index.htm http://www.bea.gov/iTable/index_nipa.cfm). The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71). The last row of Table IIA-2B shows marginal improvement of the trade deficit from $548,625 million in 2011 to lower $536,773 million in 2012 with exports growing 4.3 percent and imports 3.0 percent. The trade balance improved further to deficit of $461,876 million in 2013 with growth of exports of 3.4 percent while imports virtually stagnated. The trade deficit deteriorated in 2014 to $490,176 million with growth of exports of 3.6 percent and of imports of 4.0 percent. The trade deficit deteriorated in 2015 to $500,361 million with decrease of exports of 4.9 percent and decrease of imports of 3.7 percent. Growth and commodity shocks under alternating inflation waves (http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html) have deteriorated the trade deficit from the low of $383,774 million in 2009.

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

	Balance	Exports	∆%	Imports	∆%
1960	3,508	25,940	NA	22,432	NA
1961	4,195	26,403	1.8	22,208	-1.0
1962	3,370	27,722	5.0	24,352	9.7
1963	4,210	29,620	6.8	25,410	4.3
1964	6,022	33,341	12.6	27,319	7.5
1965	4,664	35,285	5.8	30,621	12.1
1966	2,939	38,926	10.3	35,987	17.5
1967	2,604	41,333	6.2	38,729	7.6
1968	250	45,543	10.2	45,293	16.9
1969	91	49,220	8.1	49,129	8.5
1970	2,254	56,640	15.1	54,386	10.7
1971	-1,302	59,677	5.4	60,979	12.1
1972	-5,443	67,222	12.6	72,665	19.2
1973	1,900	91,242	35.7	89,342	23.0
1974	-4,293	120,897	32.5	125,190	40.1
1975	12,404	132,585	9.7	120,181	-4.0
1976	-6,082	142,716	7.6	148,798	23.8
1977	-27,246	152,301	6.7	179,547	20.7
1978	-29,763	178,428	17.2	208,191	16.0
1979	-24,565	224,131	25.6	248,696	19.5
1980	-19,407	271,834	21.3	291,241	17.1
1981	-16,172	294,398	8.3	310,570	6.6
1982	-24,156	275,236	-6.5	299,391	-3.6
1983	-57,767	266,106	-3.3	323,874	8.2
1984	-109,072	291,094	9.4	400,166	23.6
1985	-121,880	289,070	-0.7	410,950	2.7
1986	-138,538	310,033	7.3	448,572	9.2
1987	-151,684	348,869	12.5	500,552	11.6
1988	-114,566	431,149	23.6	545,715	9.0
1989	-93,141	487,003	13.0	580,144	6.3
1990	-80,864	535,233	9.9	616,097	6.2
1991	-31,135	578,344	8.1	609,479	-1.1
1992	-39,212	616,882	6.7	656,094	7.6
1993	-70,311	642,863	4.2	713,174	8.7
1994	-98,493	703,254	9.4	801,747	12.4
1995	-96,384	794,387	13.0	890,771	11.1
1996	-104,065	851,602	7.2	955,667	7.3
1997	-108,273	934,453	9.7	1,042,726	9.1
1998	-166,140	933,174	-0.1	1,099,314	5.4
1999	-258,617	969,867	3.9	1,228,485	11.8
2000	-372,517	1,075,321	10.9	1,447,837	17.9
2001	-361,511	1,005,654	-6.5	1,367,165	-5.6
2002	-418,955	978,706	-2.7	1,397,660	2.2
2003	-493,890	1,020,418	4.3	1,514,308	8.3
2004	-609,883	1,161,549	13.8	1,771,433	17.0
2005	-714,245	1,286,022	10.7	2,000,267	12.9
2006	-761,716	1,457,642	13.3	2,219,358	11.0
2007	-705,375	1,653,548	13.4	2,358,922	6.3
2008	-708,726	1,841,612	11.4	2,550,339	8.1
2009	-383,774	1,583,053	-14.0	1,966,827	-22.9
2010	-494,658	1,853,606	17.1	2,348,263	19.4
2011	-548,625	2,127,021	14.8	2,675,646	13.9
2012	-536,773	2,218,989	4.3	2,755,762	3.0
2013	-461,876	2,293,457	3.4	2,755,334	0.0
2014	-490,176	2,376,577	3.6	2,866,754	4.0
2015	-500,361	2,261,163	-4.9	2,761,525	-3.7

Source: US Census Bureau

Chart IIA-2 of the US Census Bureau provides the US trade account in goods and services SA from Jan 1992 to May 2016. There is long-term trend of deterioration of the US trade deficit shown vividly by Chart IIA-2. The global recession from IVQ2007 to IIQ2009 reversed the trend of deterioration. Deterioration resumed together with incomplete recovery and was influenced significantly by the carry trade from zero interest rates to commodity futures exposures (these arguments are elaborated in Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4 http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html). Earlier research focused on the long-term external imbalance of the US in the form of trade and current account deficits (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). US external imbalances have not been fully resolved and tend to widen together with improving world economic activity and commodity price shocks. There are additional effects for revaluation of the dollar with the Fed orienting interest rate increases while the European Central Bank and the Bank of Japan determine negative nominal interest rates.

Chart IIA-2, US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-Feb 2016

Source: US Census Bureau

Chart IIA-3 of the US Census Bureau provides US exports SA from Jan 1992 to May 2016. There was sharp acceleration from 2003 to 2007 during worldwide economic boom and increasing inflation. Exports fell sharply during the financial crisis and global recession from IVQ2007 to IIQ2009. Growth picked up again together with world trade and inflation but stalled in the final segment with less rapid global growth and inflation.

Chart IIA-3, US, Exports SA, Monthly, Millions of Dollars Jan 1992-Feb 2016

Source: US Census Bureau

Chart IIA-4 of the US Census Bureau provides US imports SA from Jan 1992 to May 2016. Growth was stronger between 2003 and 2007 with worldwide economic boom and inflation. There was sharp drop during the financial crisis and global recession. There is stalling import levels in the final segment resulting from weaker world economic growth and diminishing inflation because of risk aversion and portfolio reallocations from commodity exposures to equities.

Chart IIA-4, US, Imports SA, Monthly, Millions of Dollars Jan 1992-Feb 2016

Source: US Census Bureau

There is improvement of the US trade balance in goods in Table IIA-3 from deficit of $62,336 million in May 2015 to deficit of $62,244 million in May 2016. The nonpetroleum deficit increased by $3462 million while the petroleum deficit shrank by $3293 million. Total exports of goods decreased 6.1 percent in May 2016 relative to a year earlier while total imports decreased 4.2 percent. Nonpetroleum exports decreased 5.7 percent from May 2015 to May 2016 while nonpetroleum imports decreased 1.9 percent. Petroleum imports fell 28.7 percent.

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

	May 2016	May 2015	∆%
Total Balance	-62,244	-62,336
Petroleum	-2,866	-6,159
Non Petroleum	-58,196	-54,734
Total Exports	119,816	127,614	-6.1
Petroleum	8,236	9,433	-12.7
Non Petroleum	110,908	117,645	-5.7
Total Imports	182,060	189,951	-4.2
Petroleum	11,122	15,593	-28.7
Non Petroleum	169,104	172,379	-1.9

Details may not add because of rounding and seasonal adjustment

Source: US Census Bureau

US exports and imports of goods not seasonally adjusted in Jan-May 2016 and Jan-May 2015 are in Table IIA-4. The rate of growth of exports was minus 6.9 percent and minus 5.2 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that decreased 12.6 percent and of mineral fuels that decreased 21.4 percent both because prices of raw materials and commodities increase and fall recurrently as a result of shocks of risk aversion and portfolio reallocations. The US exports an insignificant but growing amount of crude oil, decreasing 21.0 percent in cumulative Jan-May 2016 relative to a year earlier. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports decreased 7.5 percent while manufactured imports decreased 3.2 percent. Significant part of the US trade imbalance originates in imports of mineral fuels decreasing 36.4 percent and petroleum decreasing 36.6 percent with wide oscillations in oil prices. The limited hedge in exports of agricultural commodities and mineral fuels compared with substantial imports of mineral fuels and crude oil results in waves of deterioration of the terms of trade of the US, or export prices relative to import prices, originating in commodity price increases caused by carry trades from zero interest rates. These waves are similar to those in worldwide inflation.

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

	Jan-May 2016 $ Millions	Jan-May 2015 $ Millions	∆%
Exports	586,114	629,344	-6.9
Manufactured	431,454	466,488	-7.5
Agricultural Commodities	50,439	57,712	-12.6
Mineral Fuels	35,598	45,263	-21.4
Petroleum	29,272	37,046	-21.0
Imports	870,671	918,903	-5.2
Manufactured	763,401	788,907	-3.2
Agricultural Commodities	49,209	49,072	0.3
Mineral Fuels	53,809	84,624	-36.4
Petroleum	49,442	78,002	-36.6

Source: US Census Bureau