Sunday, January 7, 2018

Twenty-Three Million Unemployed or Underemployed in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Job Creation, Cyclically Stagnating Real Wages, Unconventional Monetary Policy and Valuations of Risk Financial Assets, United States Net International Investment Position, World Cyclical Slow Growth and Global Recession Risk: Part I

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Twenty-Three Million Unemployed or Underemployed in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Job Creation, Cyclically Stagnating Real Wages, Unconventional Monetary Policy and Valuations of Risk Financial Assets, United States Net International Investment Position, World Cyclical Slow Growth and Global Recession Risk

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018

I Twenty-Three Million Unemployed or Underemployed

IA1 Summary of the Employment Situation

IA2 Number of People in Job Stress

IA3 Long-term and Cyclical Comparison of Employment

IA4 Job Creation

IB Stagnating Real Wages

IIA Unconventional Monetary Policy and Valuations of Risk Financial Assets

II United States Net International Investment Position

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

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

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

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

IA1 Summary of the Employment Situation. Table I-1 provides summary statistics of the employment situation report of the BLS. The first four rows provide the data from the establishment report of creation of nonfarm payroll jobs and remuneration of workers (for analysis of the differences in employment between the establishment report and the household survey see Abraham, Haltiwanger, Sandusky and Spletzer 2009). Total nonfarm payroll employment seasonally adjusted (SA) increased 148,000 in Dec 2017 and private payroll employment increased 146,000. The Bureau of Labor Statistics states (https://www.bls.gov/news.release/empsit.nr0.htm): “Our analysis suggests that the net effect of these hurricanes [Harvey and Irma] was to reduce the estimate of total nonfarm payroll employment for September. There was no discernible effect on the national unemployment rate. No changes were made to either the establishment or household survey estimation procedures for the September figures.” The average monthly number of nonfarm jobs created from Dec 2015 to Dec 2016 was 186,667 using seasonally adjusted data, while the average number of nonfarm jobs created from Dec 2016 to Dec 2017 was 171,250, or decrease by 8.3 percent. The average number of private jobs created in the US from Dec 2015 to Dec 2016 was 169,917, using seasonally adjusted data, while the average from Dec 2016 to Dec 2017 was 167,750, or decrease by 1.3 percent. This blog calculates the effective labor force of the US at 169,544 million in Dec 2017 and 168,639 million in Dec 2016 (Table I-4), for growth of 0.905 million at average 75,417 per month. The difference between the average increase of 167,750 new private nonfarm jobs per month in the US from Dec 2016 to Dec 2017 and the 75,417-average monthly increase in the labor force from Dec 2016 to Dec 2017 is 92,333 monthly new jobs net of absorption of new entrants in the labor force. There are 22.625 million in job stress in the US currently. Creation of 92,333 new jobs per month net of absorption of new entrants in the labor force would require 245 months to provide jobs for the unemployed and underemployed (22.625 million divided by 92,333) or 20 years (245 divided by 12). The civilian labor force of the US in Dec 2017 not seasonally adjusted stood at 159.880 million with 6.278 million unemployed or effectively 15.942 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 169.544 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 0.903 years (1 million divided by product of 92,333 by 12, which is 1,107,996). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.994 million (0.05 times labor force of 159.880 million). New net job creation would be minus 1.716 million (6.278 million unemployed minus 7.994 million unemployed at rate of 5 percent) that at the current rate would take 0.0 years (-1.716 million divided by 1.108). Under the calculation in this blog, there are 15.942 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 169.544 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 7.465 million jobs net of labor force growth that at the current rate would take 6.7 years (15.942 million minus 0.05(169.544 million) = 7.465 million divided by 1.107996 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 Dec 2017 was 153.602 million (NSA) or 6.287 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 256.109 million in Dec 2017 or by 24.151 million. The number employed increased 4.3 percent from Jul 2007 to Dec 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 10.4 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employed as percent of population of 231.958 million). The same ratio in Dec 2017 would result in 162.629 million jobs (0.635 multiplied by noninstitutional civilian population of 256.109 million). There are effectively 9.027 million fewer jobs in Dec 2017 than in Jul 2007, or 162.629 million minus 153.602 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

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

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (https://cmpassocregulationblog.blogspot.com/2017/11/recovery-without-hiring-ten-million.html). The proper explanation is not in secular stagnation but in cyclically slow growth. Secular stagnation is merely another case of theory without reality with dubious policy proposals. Subsection IA4 Job Creation analyzes the types of jobs created, which are lower paying than earlier. Average hourly earnings in Nov 2017 were $26.55 seasonally adjusted (SA), increasing 2.4 percent not seasonally adjusted (NSA) relative to Nov 2016 and increasing 0.2 percent relative to Oct 2017 seasonally adjusted. In Oct 2017, average hourly earnings seasonally adjusted were $26.50, increasing 2.3 percent relative to Oct 2016 not seasonally adjusted and decreasing 0.1 percent seasonally adjusted relative to Sep 2017. These are nominal changes in workers’ wages. The following row “average hourly earnings in constant dollars” provides hourly wages in constant dollars calculated by the BLS or what is called “real wages” adjusted for inflation. Data are not available for Nov 2017 because the prices indexes of the BLS for Nov 2017 will only be released on Dec 13, 2017 (http://www.bls.gov/cpi/), which will be covered in this blog’s comment on Dec 17, 2017, together with world inflation. The second column provides changes in real wages for Oct 2017. Average hourly earnings adjusted for inflation or in constant dollars increased 0.3 percent in Oct 2017 relative to Oct 2016 but have been decreasing/stagnating during multiple months. World inflation waves in bouts of risk aversion (https://cmpassocregulationblog.blogspot.com/2017/11/dollar-devaluation-and-decline-of.html) mask declining trend of real wages. The fractured labor market of the US is characterized by high levels of unemployment and underemployment together with cyclically stagnating real wages or wages adjusted for inflation (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html). The following section IB Stagnating Real Wages provides more detailed analysis. Average weekly hours of US workers seasonally adjusted remained virtually unchanged, increasing from 34.4 in Oct 2017 to 34.5 in Nov 2017, which could be substantial additional work on a labor force of 160.529 million SA in Nov 2017. Another headline number widely followed is the unemployment rate or number of people unemployed as percent of the labor force. The unemployment rate calculated in the household survey did not change from 4.1 percent in Oct 2017 to 4.1 percent in Nov 2017, seasonally adjusted. This blog provides with every employment situation report the number of people in the US in job stress or unemployed plus underemployed calculated without seasonal adjustment (NSA) at 21.4 million in Nov 2017 and 21.2 million in Oct 2017. The final row in Table I-1 provides the number in job stress as percent of the actual labor force calculated at 12.6 percent in Nov 2017 and 12.5 percent in Oct 2017. Almost one in every five to ten workers in the US is unemployed or underemployed.

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

and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/exchange-rate-conflicts-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/imf-view-squeeze-of-economic-activity.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html)

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

Dec 2017

Nov 2017

New Nonfarm Payroll Jobs

148

252

New Private Payroll Jobs

146

239

Average Hourly Earnings

Dec 17 $26.63 SA

∆% Dec 17/Dec 16 NSA: 2.6

∆% Dec 17/Nov 17 SA: 0.3

Nov 17 $26.54 SA

∆% Nov 17/Oct 16 NSA: 2.4

∆% Nov 17/Oct 17 SA: 0.1

Average Hourly Earnings in Constant Dollars

∆% Nov 17/Nov 16 NSA: 0.2

Average Weekly Hours

34.5 SA

34.5 NSA

34.5 SA

34.4 NSA

Unemployment Rate Household Survey % of Labor Force SA

4.1

4.1

Number in Job Stress Unemployed and Underemployed Blog Calculation

22.6

21.4 Million NSA

In Job Stress as % Labor Force

13.3

12.6

Source: US Bureau of Labor Statistics

http://www.bls.gov/

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

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

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

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

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

December 2014.

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

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

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

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

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

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

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

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

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

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

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

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

The Bureau of Labor Statistics (BLS) revised household data for seasonal adjustment in the release for Dec 2017 (https://www.bls.gov/news.release/pdf/empsit.pdf): “Seasonally adjusted household survey data have been revised using updated seasonal adjustment factors, a procedure done at the end of each calendar year. Seasonally adjusted estimates back to January 2013 were subject to revision. The unemployment rates for January 2017 through November 2017 (as originally published and as revised) appear in table A on page 6, along with additional information about the revisions.”

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

IA2 Number of People in Job Stress. There are two approaches to calculating the number of people in job stress. The first approach consists of calculating the number of people in job stress unemployed or underemployed with the raw data of the employment situation report as in Table I-2. The data are seasonally adjusted (SA). The first three rows provide the labor force and unemployed in millions and the unemployment rate of unemployed as percent of the labor force. There is increase in the number unemployed from 6.524 million in Oct 2017 to 6.616 million in Nov 2017 and decrease to 6.576 million in Dec 2017. The rate of unemployment did not change from 4.1 percent in Oct 2017 to 4.1 percent in Nov 2017 and did not change to 4.1 percent in Dec 2017. An important aspect of unemployment is its persistence for more than 27 weeks with 1.515 million in Dec 2017, corresponding to 23.0 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 decreased from 4.880 million in Oct 2017 to 4.851 million in Nov 2017 and increased to 4.915 million in Dec 2017. Another important fact is the marginally attached to the labor force. The BLS explains as follows: “these individuals were not in the labor force, wanted and were available for work, and had looked for a job sometime in the prior 12 months. They were not counted as unemployed because they had not searched for work in the 4 weeks preceding the survey” (http://www.bls.gov/news.release/pdf/empsit.pdf 2). The number in job stress unemployed or underemployed of 13.114 million in Dec. 2017 consists of:

· 6.576 million unemployed (of whom 1.515 million, or 23.0 percent, unemployed for 27 weeks or more) compared with 6.616 million unemployed in Nov 2017 (of whom 1.593 million, or 24.1 percent, unemployed for 27 weeks or more).

· 4.915 million employed part-time for economic reasons in Dec 2017 (who suffered reductions in their work hours or could not find full-time employment) compared with 4.851 million in Nov 2017

· 1.623 million who were marginally attached to the labor force in Dec 2017 (who were not in the labor force but wanted and were available for work) compared with 1.481 million in Nov 2017

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

Dec 2017

Nov 2017

Oct 2017

Labor Force Millions

160.597

160.533

160.371

Unemployed
Millions

6.576

6.616

6.524

Unemployment Rate (unemployed as % labor force)

4.1

4.1

4.1

Unemployed ≥27 weeks
Millions

1.515

1.593

1.645

Unemployed ≥27 weeks %

23.0

24.1

25.2

Part Time for Economic Reasons
Millions

4.915

4.851

4.880

Marginally
Attached to Labor Force
Millions

1.623

1.481

1.535

Job Stress
Millions

13.114

12.948

12.939

In Job Stress as % Labor Force

8.2

8.1

8.1

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Table I-3 repeats the data in Table I-2 but including Jul 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 60.4 in Sep 2017, 60.2 in Oct 2017, 60.1 in Nov 2017 and 60.1 in Dec 2017. The employment to population ratio fell from an annual level of 63.1 percent in 2006 to 58.6 percent in 2012, 58.6 percent in 2013 and 59.0 in 2014 with the lowest level at 58.4 percent in 2011. The employment population ratio NSA reached 59.4 in Dec 2015, 59.6 in Dec 2016 and 60.0 in Dec 2917.

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

Dec 2017

Nov 2017

Oct 2017

Sep 2017

Labor Force

160.597

160.533

160.371

161.082

Participation Rate

62.7

62.7

62.7

63.0

Unemployed

6.576

6.616

6.524

6.759

UNE Rate %

4.1

4.1

4.1

4.2

Part Time Economic Reasons

4.915

4.851

4.880

5.148

Marginally Attached to Labor Force

1.623

1.481

1.535

1.569

In Job Stress

13.114

12.948

12.939

13.476

In Job Stress % Labor Force

8.2

8.1

8.1

8.4

Employed

154.021

153.917

153.846

154.324

Employment % Population

60.1

60.1

60.2

60.4

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

Source: US Bureau of Labor Statistics

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

The balance of this section considers the second approach. Charts I-1 to I-12 explain the reasons for considering another approach to calculating job stress in the US. Chart I-1 of the Bureau of Labor Statistics provides the level of employment in the US from 2001 to 2017. There was a big drop of the number of people employed from 147.315 million at the peak in Jul 2007 (NSA) to 136.809 million at the trough in Jan 2010 (NSA) with 10.506 million fewer people employed. Recovery has been anemic compared with the shallow recession of 2001 that was followed by nearly vertical growth in jobs. The number employed in Dec 2017 was 153.602 million (NSA) or 6.287 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 256.109 million in Dec 2017 or by 24.151 million. The number employed increased 4.3 percent from Jul 2007 to Dec 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 10.4 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employed as percent of population of 231.958 million). The same ratio in Dec 2017 would result in 162.629 million jobs (0.635 multiplied by noninstitutional civilian population of 256.109 million). There are effectively 9.027 million fewer jobs in Dec 2017 than in Jul 2007, or 162.629 million minus 153.602 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

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

Source: Bureau of Labor Statistics

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

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

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

Source: Bureau of Labor Statistics

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

The foundation of the second approach derives from Chart I-3 of the Bureau of Labor Statistics providing the level of the civilian labor force in the US. The civilian labor force consists of people who are available and willing to work and who have searched for employment recently. The labor force of the US NSA grew 9.4 percent from 142.828 million in Jan 2001 to 156.255 million in Jul 2009. The civilian labor force is 2.6 percent higher at 160.320 million in Dec 2017 than in Jul 2009, all numbers not seasonally adjusted. Chart I-3 shows the flattening of the curve of expansion of the labor force and its decline in 2010 and 2011. The ratio of the labor force of 154.871 million in Jul 2007 to the noninstitutional population of 231.958 million in Jul 2007 was 66.8 percent while the ratio of the labor force of 159.880 million in Dec 2017 to the noninstitutional population of 256.109 million in Dec 2017 was 62.4 percent. The labor force of the US in Dec 2017 corresponding to 66.8 percent of participation in the population would be 171.081 million (0.668 x 256.109). The difference between the measured labor force in Dec 2017 of 159.880 million and the labor force in Dec 2017 with participation rate of 66.8 percent (as in Jul 2007) of 171.081 million is 11.201 million. The level of the labor force in the US has stagnated and is 11.201 million lower than what it would have been had the same participation rate been maintained. Millions of people have abandoned their search for employment because they believe there are no jobs available for them. The key issue is whether the decline in participation of the population in the labor force is the result of people giving up on finding another job.

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

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

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

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

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

Chart I-5 of the Bureau of Labor Statistics provides the labor force participation rate in the US or labor force as percent of the population. The labor force participation rate of the US fell from 66.8 percent in Jan 2001 to 62.4 percent NSA in Dec 2017, all numbers not seasonally adjusted. The annual labor force participation rate for 1979 was 63.7 percent and also 63.7 percent in Nov 1980 during sharp economic contraction. This comparison is further elaborated below. Chart I-5 shows an evident downward trend beginning with the global recession that has continued throughout the recovery beginning in IIIQ2009. The critical issue is whether people left the workforce of the US because they believe there is no longer a job for them.

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

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

Chart I-6 of the Bureau of Labor Statistics provides the level of unemployed in the US. The number unemployed rose from the trough of 6.272 million NSA in Oct 2006 to the peak of 16.147 million in Jan 2010, declining to 13.400 million in Jul 2012, 12.696 million in Aug 2012 and 11.741 million in Sep 2012. The level unemployed fell to 11.741 million in Oct 2012, 11.404 million in Nov 2012, 11.844 million in Dec 2012, 13.181 million in Jan 2013, 12.500 million in Feb 2013 and 9.984 million in Dec 2013. The level of unemployment reached 6.278 million in Dec 2017, all numbers not seasonally adjusted.

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

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

Chart I-7 of the Bureau of Labor Statistics provides the rate of unemployment in the US or unemployed as percent of the labor force. The rate of unemployment of the US rose from 4.7 percent in Jan 2001 to 6.5 percent in Jun 2003, declining to 4.1 percent in Oct 2006. The rate of unemployment jumped to 10.6 percent in Jan 2010 and declined to 7.6 percent in Dec 2012 but increased to 8.5 percent in Jan 2013 and 8.1 percent in Feb 2013, falling back to 7.3 percent in May 2013 and 7.8 percent in Jun 2013, all numbers not seasonally adjusted. The rate of unemployment not seasonally adjusted stabilized at 7.7 percent in Jul 2013 and fell to 6.5 percent in Dec 2013 and 5.4 percent in Dec 2014. The rate of unemployment NSA decreased to 4.8 percent in Dec 2015 and 4.5 percent in Dec 2016, reaching 3.9 percent in Dec 2017.

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

Source: Bureau of Labor Statistics

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

Chart I-8 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of unemployed. There was a jump of 81.8 percent in Apr 2009 with subsequent decline and negative rates since 2010. On an annual basis, the level of unemployed rose 59.8 percent in 2009 and 26.1 percent in 2008 with increase of 3.9 percent in 2010, decline of 7.3 percent in 2011 and decrease of 9.0 percent in 2012. The annual level of unemployment decreased 8.4 percent in 2013 and fell 16.1 percent in 2014. The annual level of unemployment fell 13.7 percent in 2015 and fell 6.6 percent in 2016, decreasing 9.9 percent in 2017. The level of unemployment decreased 12.4 percent in Dec 2017 relative to a year earlier.

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

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

Chart I-9 of the Bureau of Labor Statistics provides the number of people in part-time occupations because of economic reasons, that is, because they cannot find full-time employment. The number underemployed in part-time occupations not seasonally adjusted rose from 3.732 million in Jan 2001 to 5.270 million in Jan 2004, falling to 3.787 million in Apr 2006. The number underemployed seasonally adjusted jumped to 9.114 million in Nov 2009, falling to 8.171 million in Dec 2011 but increasing to 8.305 million in Jan 2012 and 8.238 million in Feb 2012 but then falling to 7.943 million in Dec 2012 and increasing to 8.083 million in Jul 2013. The number employed part-time for economic reasons seasonally adjusted reached 4.915 million in Dec 2017. Without seasonal adjustment, the number employed part-time for economic reasons reached 9.354 million in Dec 2009, declining to 8.918 million in Jan 2012 and 8.166 million in Dec 2012 but increasing to 8.324 million in Jul 2013. The number employed part-time for economic reasons NSA stood at 7.990 million in Dec 2013, 6.970 million in Dec 2014 and 6.179 million in Dec 2015. The number employed part-time for economic reasons NSA stood at 5.707 million in Dec 2016. The number employed part-time for economic reasons reached 5.060 million in Dec 2017. The longer the period in part-time jobs the lower are the chances of finding another full-time job.

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

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

Chart I-10 of the Bureau of Labor Statistics repeats the behavior of unemployment. The 12-month percentage change of the level of people at work part-time for economic reasons jumped 84.7 percent in Mar 2009 and declined subsequently. The declines have been insufficient to reduce significantly the number of people who cannot shift from part-time to full-time employment. On an annual basis, the number of part-time for economic reasons increased 33.5 percent in 2008 and 51.7 percent in 2009, declining 0.4 percent in 2010, 3.5 percent in 2011 and 5.1 percent in 2012. The annual number of part-time for economic reasons decreased 2.3 percent in 2013 and fell 9.1 percent in 2014. The annual number of part-time for economic reasons fell 11.7 percent in 2015 and fell 6.7 percent in 2016. The number of part-time for economic reasons decreased 7.6 percent in Dec 2016 relative to a year earlier. The level of part-time for economic reason fell 11.3 percent in Dec 2017 relative to a year earlier.

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

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

Chart I-11 of the Bureau of Labor Statistics provides the same pattern of the number marginally attached to the labor force jumping to significantly higher levels during the global recession and remaining at historically high levels. The number marginally attached to the labor force not seasonally adjusted increased from 1.295 million in Jan 2001 to 1.691 million in Feb 2004. The number of marginally attached to the labor force fell to 1.299 million in Sep 2006 and increased to 2.609 million in Dec 2010 and 2.800 million in Jan 2011. The number marginally attached to the labor force was 2.540 million in Dec 2011, increasing to 2.809 million in Jan 2012, falling to 2.608 million in Feb 2012. The number marginally attached to the labor force fell to 2.352 million in Mar 2012, 2.363 million in Apr 2012, 2.423 million in May 2012, 2.483 million in Jun 2012, 2.529 million in Jul 2012 and 2.561 million in Aug 2012. The number marginally attached to the labor force fell to 2.517 million in Sep 2012, 2.433 million in Oct 2012, 2.505 million in Nov 2012 and 2.427 million in in Dec 2013. The number marginally attached to the labor force reached 2.260 million in Dec 2014 and 1.833 million in Dec 2015. The number marginally attached to the labor force stood at 1.684 million in Dec 2016. The level marginally attached to the labor force reached 1.623 million Dec 2017.

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

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

Chart I-12 provides 12-month percentage changes of the marginally attached to the labor force from 2001 to 2017. There was a jump of 56.1 percent in May 2009 during the global recession followed by declines in percentage changes but insufficient negative changes. On an annual basis, the number of marginally attached to the labor force increased in four consecutive years: 15.7 percent in 2008, 37.9 percent in 2009, 11.7 percent in 2010 and 3.5 percent in 2011. The number marginally attached to the labor force fell 2.2 percent on annual basis in 2012 but increased 2.9 percent in the 12 months ending in Dec 2012, fell 13.0 percent in the 12 months ending in Jan 2013, falling 10.7 percent in the 12 months ending in May 2013. The number marginally attached to the labor force increased 4.0 percent in the 12 months ending in Jun 2013 and fell 4.5 percent in the 12 months ending in Jul 2013 and 8.6 percent in the 12 months ending in Aug 2013. The annual number of marginally attached to the labor force fell 6.2 percent in 2013 and fell 6.5 percent in 2014. The annual number of marginally attached to the labor force fell 11.4 percent in 2015. The number marginally attached to the labor force fell 7.2 percent in the 12 months ending in Dec 2013 and fell 6.9 percent in the 12 months ending in Dec 2014. The number marginally attached to the labor force fell 18.9 percent in the 12 months ending in Dec 2015 and decreased 8.1 percent in the 12 months ending in Dec 2016. The level of marginally attached to the labor force decreased 3.6 percent in the 12 months ending in Dec 2017.

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

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

Table I-4 consists of data and additional calculations using the BLS household survey, illustrating the possibility that the actual rate of unemployment could be 9.0 percent and the number of people in job stress could be around 21.4 million, which is 12.6 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 Nov 2016, Oct 2017 and Nov 2017 are in thousands, not seasonally adjusted. The average yearly participation rate of the population in the labor force was in the range of 66.0 percent minimum to 67.1 percent maximum between 2000 and 2006 with the average of 66.4 percent (http://www.bls.gov/data/). Table I-4b provides the yearly labor force participation rate from 1979 to 2017. The objective of Table I-4 is to assess how many people could have left the labor force because they do not think they can find another job. Row “LF PART 66.2 %” applies the participation rate of 2006, almost equal to the rates for 2000 to 2006, to the noninstitutional civilian population in Dec 2016, Nov 2017 and Dec 2017 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 62.4 percent by Dec 2016 and was 62.7 percent in Nov 2017 and 62.4 percent in Dec 2017, suggesting that many people simply gave up on finding another job. Row “∆ NLF UEM” calculates the number of people not counted in the labor force because they could have given up on finding another job by subtracting from the labor force with participation rate of 66.2 percent (row “LF PART 66.2%”) the labor force estimated in the household survey (row “LF”). Total unemployed (row “Total UEM”) is obtained by adding unemployed in row “∆NLF UEM” to the unemployed of the household survey in row “UEM.” The row “Total UEM%” is the effective total unemployed “Total UEM” as percent of the effective labor force in row “LF PART 66.2%.” The results are that:

  • there are an estimated 9.664 million unemployed in Dec 2017 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM), that is, they dropped out of their job searches
  • the total number of unemployed is effectively 15.942 million (Total UEM) and not 6.278 million (UEM) of whom many have been unemployed long term
  • the rate of unemployment is 9.4 percent (Total UEM%) and not 3.9 percent, not seasonally adjusted, or 4.1 percent seasonally adjusted
  • the number of people in job stress is close to 22.6 million by adding the 9.664 million leaving the labor force because they believe they could not find another job, corresponding to 13.3 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 22.625 million in Dec 2017, adding the total number of unemployed (“Total UEM”), plus those involuntarily in part-time jobs because they cannot find anything else (“Part Time Economic Reasons”) and the marginally attached to the labor force (“Marginally attached to LF”). The final row of Table I-4 shows that the number of people in job stress is equivalent to 13.3 percent of the labor force in Dec 2017. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 59.6 percent in Dec 2016, 60.2 percent in Nov 2017 and 60.0 percent in Dec 2017. The number employed in Dec 2017 was 153.602 million (NSA) or 6.287 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 256.109 million in Dec 2017 or by 24.151 million. The number employed increased 4.3 percent from Jul 2007 to Dec 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 10.4 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employed as percent of population of 231.958 million). The same ratio in Dec 2017 would result in 162.629 million jobs (0.635 multiplied by noninstitutional civilian population of 256.109 million). There are effectively 9.027 million fewer jobs in Dec 2017 than in Jul 2007, or 162.629 million minus 153.602 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (https://cmpassocregulationblog.blogspot.com/2017/12/fomc-increases-interest-rates-with.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 2.2 percent on average in the cyclical expansion in the 33 quarters from IIIQ2009 to IIIQ2017. 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 IIIQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp3q17_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 dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2835.2 billion than actual $17,163.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.3 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,163.9 billion in IIIQ2017 or 14.5 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 146.5098 in Nov 2017. The actual index NSA in Nov 2017 is 104.6305, which is 28.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Nov 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.7256 in Nov 2017. The output of manufacturing at 104.6305 in Nov 2017 is 20.6 percent below trend under this alternative calculation.

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

2006

Dec 2016

Nov 2017

Dec 2017

POP

229

254,742

255,949

256,109

LF

151

158,968

160,466

159,880

PART%

66.2

62.4

62.7

62.4

EMP

144

151,798

154,180

153,602

EMP/POP%

62.9

59.6

60.2

60.0

UEM

7

7,170

6,286

6,278

UEM/LF Rate%

4.6

4.5

3.9

3.9

NLF

77

95,774

95,483

96,230

LF PART 66.2%

168,639

169,438

169,544

∆NLF UEM

9,671

8,972

9,664

Total UEM

16,841

15,258

15,942

Total UEM%

10.0

9.0

9.4

Part Time Economic Reasons

5,707

4,642

5,060

Marginally Attached to LF

1,684

1,481

1,623

In Job Stress

24,232

21,381

22,625

People in Job Stress as % Labor Force

14.4

12.6

13.3

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

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

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

Source: US Bureau of Labor Statistics

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

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

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

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

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

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

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

Y = ∑isiyi (1)

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

∆Y = ∑i∆siy*i + ∑i∆yis*i (2)

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

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

Table I-4b and Chart I-12-b provide the US labor force participation rate or percentage of the labor force in population. It is not likely that simple demographic trends caused the sharp decline during the global recession and failure to recover earlier levels. The civilian labor force participation rate dropped from the peak of 66.9 percent in Jul 2006 to 62.6 percent in Dec 2013, 62.5 percent in Dec 2014, 62.4 percent in Dec 2015 and 62.4 in Dec 2016. The civilian labor force participation rate reached 62.4 in Dec 2017. The civilian labor force participation rate was 63.7 percent on an annual basis in 1979 and 63.4 percent in Dec 1980 and Dec 1981, reaching even 62.9 percent in both Apr and May 1979. The civilian labor force participation rate jumped with the recovery to 64.8 percent on an annual basis in 1985 and 65.9 percent in Jul 1985. Structural factors cannot explain these sudden changes vividly shown visually in the final segment of Chart I-12b. Seniors would like to delay their retiring especially because of the adversities of financial repression on their savings. Labor force statistics are capturing the disillusion of potential workers with their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors. The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (https://cmpassocregulationblog.blogspot.com/2017/12/fomc-increases-interest-rates-with.html). “Secular stagnation” would be a process over many years and not from one year to another. This is merely another case of theory without reality with dubious policy proposals.

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

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

Year

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

1979

64.5

64.9

64.5

63.8

64.0

63.8

63.8

63.7

1980

64.6

65.1

64.5

63.6

63.9

63.7

63.4

63.8

1981

64.6

65.0

64.6

63.5

64.0

63.8

63.4

63.9

1982

64.8

65.3

64.9

64.0

64.1

64.1

63.8

64.0

1983

65.1

65.4

65.1

64.3

64.1

64.1

63.8

64.0

1984

65.5

65.9

65.2

64.4

64.6

64.4

64.3

64.4

1985

65.5

65.9

65.4

64.9

65.1

64.9

64.6

64.8

1986

66.3

66.6

66.1

65.3

65.5

65.4

65.0

65.3

1987

66.3

66.8

66.5

65.5

65.9

65.7

65.5

65.6

1988

66.7

67.1

66.8

65.9

66.1

66.2

65.9

65.9

1989

67.4

67.7

67.2

66.3

66.6

66.7

66.3

66.5

1990

67.4

67.7

67.1

66.4

66.5

66.3

66.1

66.5

1991

67.2

67.3

66.6

66.1

66.1

66.0

65.8

66.2

1992

67.6

67.9

67.2

66.3

66.2

66.2

66.1

66.4

1993

67.3

67.5

67.0

66.1

66.4

66.3

66.2

66.3

1994

67.2

67.5

67.2

66.5

66.8

66.7

66.5

66.6

1995

67.2

67.7

67.1

66.5

66.7

66.5

66.2

66.6

1996

67.4

67.9

67.2

66.8

67.1

67.0

66.7

66.8

1997

67.8

68.1

67.6

67.0

67.1

67.1

67.0

67.1

1998

67.7

67.9

67.3

67.0

67.1

67.1

67.0

67.1

1999

67.7

67.9

67.3

66.8

67.0

67.0

67.0

67.1

2000

67.7

67.6

67.2

66.7

66.9

66.9

67.0

67.1

2001

67.2

67.4

66.8

66.6

66.7

66.6

66.6

66.8

2002

67.1

67.2

66.8

66.6

66.6

66.3

66.2

66.6

2003

67.0

66.8

66.3

65.9

66.1

66.1

65.8

66.2

2004

66.5

66.8

66.2

65.7

66.0

66.1

65.8

66.0

2005

66.5

66.8

66.5

66.1

66.2

66.1

65.9

66.0

2006

66.7

66.9

66.5

66.1

66.4

66.4

66.3

66.2

2007

66.6

66.8

66.1

66.0

66.0

66.1

65.9

66.0

2008

66.6

66.8

66.4

65.9

66.1

65.8

65.7

66.0

2009

66.2

66.2

65.6

65.0

64.9

64.9

64.4

65.4

2010

65.1

65.3

65.0

64.6

64.4

64.4

64.1

64.7

2011

64.5

64.6

64.3

64.2

64.1

63.9

63.8

64.1

2012

64.3

64.3

63.7

63.6

63.8

63.5

63.4

63.7

2013

64.0

64.0

63.4

63.2

62.9

62.9

62.6

63.2

2014

63.4

63.5

63.0

62.8

63.0

62.8

62.5

62.9

2015

63.1

63.2

62.7

62.3

62.5

62.5

62.4

62.7

2016

63.2

63.4

62.9

62.8

62.8

62.6

62.4

62.8

2017

63.3

63.5

63.0

63.0

62.7

62.7

62.4

62.9

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

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

Source: Bureau of Labor Statistics

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

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

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

Sources: US Bureau of Labor Statistics

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

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

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

Sources: US Bureau of Labor Statistics

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

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

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

Sources: US Bureau of Labor Statistics

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

IA3 Long-term and Cyclical Comparison of Employment. There is initial discussion here of long-term employment trends followed by cyclical comparison. Growth and employment creation have been mediocre in the expansion beginning in Jul IIIQ2009 from the contraction between Dec IVQ2007 and Jun IIQ2009 (http://www.nber.org/cycles.html). A series of charts from the database of the Bureau of Labor Statistics (BLS) provides significant insight. Chart I-13 provides the monthly employment level of the US from 1948 to 2017. The number of people employed has trebled. There are multiple contractions throughout the more than six decades but followed by resumption of the strong upward trend. The contraction of employment after 2007 is sharp and followed by a flatter curve of job creation. The United States missed this opportunity of high growth in the initial phase of recovery that historically eliminated unemployment and underemployment created during the contraction. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 33 quarters from IIIQ2009 to IIIQ2017. 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 IIIQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp3q17_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 dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2835.2 billion than actual $17,163.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.3 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,163.9 billion in IIIQ2017 or 14.5 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 146.5098 in Nov 2017. The actual index NSA in Nov 2017 is 104.6305, which is 28.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Nov 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.7256 in Nov 2017. The output of manufacturing at 104.6305 in Nov 2017 is 20.6 percent below trend under this alternative calculation.

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

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

Chart I-17 provides the rate of unemployment of the US from 1948 to 2017. The peak of the series is 10.8 percent in both Nov and Dec 1982. The second highest rates are 10.0 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009 SA. The unadjusted rate of unemployment NSA reached 3.9 percent in Dec 2017.

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

Source: US Bureau of Labor Statistics

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

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

Chart I-18, US, Unemployed for 27 Weeks or More, SA, 1948-2017, Thousands

Source: US Bureau of Labor Statistics

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

The employment-population ratio in Chart I-19 is an important indicator of wellbeing in labor markets, measuring the number of people with jobs. The US employment-population ratio fell from 63.5 in Dec 2006 to 58.6 in Jul 2011 and stands at 59.6 NSA in Dec 2016. The employment population ration reached 60.0 NSA in Dec 2017. There is no comparable decline followed by stabilization during a cyclical expansion in Chart I-19.

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

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

Table I-5 provides percentage change of real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Data are available for the 1930s only on a yearly basis. US GDP fell 4.7 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1982 and 4.2 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. In contrast, GDP grew 2.5 percent in 2010, 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.6 percent in 2014 and 2.9 percent in 2015. GDP grew 1.5 percent in 2016. Actual annual equivalent GDP growth in the twenty-three quarters from IQ2012 to III2017 is 2.1 percent and 2.3 percent in the four quarters ending in IIIQ2017. 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 2.2 to 2.6 percent in 2018 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20171213.pdf) with less reliable forecast of 1.9 to 2.3 percent in 2019 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20171213.pdf). Growth of GDP in the expansion from IIIQ2009 to IIIQ2017 has been at average 2.2 percent in annual equivalent.

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

Year

GDP ∆%

Year

GDP ∆%

Year

GDP ∆%

1930

-8.5

1980

-0.2

2000

4.1

1931

-6.4

1981

2.6

2001

1.0

1932

-12.9

1982

-1.9

2002

1.8

1933

-1.3

1983

4.6

2003

2.8

1934

10.8

1984

7.3

2004

3.8

1935

8.9

1985

4.2

2005

3.3

1936

12.9

1986

3.5

2006

2.7

1937

5.1

1987

3.5

2007

1.8

1938

-3.3

1988

4.2

2008

-0.3

1939

8.0

1989

3.7

2009

-2.8

1940

8.8

1990

1.9

2010

2.5

1941

17.7

1991

-0.1

2011

1.6

1942

18.9

1992

3.6

2012

2.2

1943

17.0

1993

2.7

2013

1.7

1944

8.0

1994

4.0

2014

2.6

1945

-1.0

1995

2.7

2015

2.9

1946

-11.6

1996

3.8

2016

1.5

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

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

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

Number of Quarters

Cumulative Percentage Contraction

Average Percentage Rate

IIQ1953 to IIQ1954

3

-2.4

-0.8

IIIQ1957 to IIQ1958

3

-3.0

-1.0

IVQ1973 to IQ1975

5

-3.1

-0.6

IQ1980 to IIIQ1980

2

-2.2

-1.1

IIIQ1981 to IVQ1982

4

-2.5

-0.64

IVQ2007 to IIQ2009

6

-4.2

-0.72

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

Table I-7 shows the mediocre average annual equivalent growth rate of 2.2 percent of the US economy in the thirty-three quarters of the current cyclical expansion from IIIQ2009 to IIIQ2017. In sharp contrast, the average growth rate of GDP was:

  • 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986
  • 5.4 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986
  • 5.2 percent in the first sixteen quarters of expansion from IQ1983 to IVQ1986
  • 5.0 percent in the first seventeen quarters of expansion from IQ1983 to IQ1987
  • 5.0 percent in the first eighteen quarters of expansion from IQ1983 to IIQ1987
  • 4.9 percent in the first nineteen quarters of expansion from IQ1983 to IIIQ1987
  • 5.0 percent in the first twenty quarters of expansion from IQ1983 to IVQ1987
  • 4.9 percent in the first twenty-first quarters of expansion from IQ1983 to IQ1988
  • 4.9 percent in the first twenty-two quarters of expansion from IQ1983 to IIQ1988
  • 4.8 percent in the first twenty-three quarters of expansion from IQ1983 to IIIQ1988
  • 4.8 percent in the first twenty-four quarters of expansion from IQ1983 to IVQ1988
  • 4.8 percent in the first twenty-five quarters of expansion from IQ1983 to IQ1989
  • 4.7 percent in the first twenty-six quarters of expansion from IQ1983 to IIQ1989
  • 4.7 percent in the first twenty-seven quarters of expansion from IQ1983 to IIIQ1989
  • 4.5 percent in the first twenty-eight quarters of expansion from IQ1983 to IVQ1989
  • 4.5 percent in the first twenty-nine quarters of expansion from IQ1983 to IQ1990
  • 4.4 percent in the first thirty quarters of expansion from IQ1983 to IIQ1990
  • 4.3 percent in the first thirty-one quarters of expansion from IQ1983 to IIIQ1990
  • 4.0 percent in the first thirty-two quarters of expansion from IQ1983 to IVQ1990
  • 3.8 percent in the first thirty-three quarters of expansion from IQ1983 to IQ1991

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 relative to historical experience with annual growth of 2.5 percent in 2010 decelerating to 1.6 percent annual growth in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.6 percent in 2014, 2.9 percent in 2015 and 1.5 percent in 2016 (http://www.bea.gov/iTable/index_nipa.cfm).  The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988. 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989. 4.5 percent from IQ1983 to IVQ1989, 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990. 4.0 percent from IQ1983 to IVQ1990. 3.8 percent from IQ1983 to IQ1991 and at 7.8 percent from IQ1983 to IVQ1983. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the twenty-three quarters from 2012 to 2017 accumulated to 13.0 percent. This growth is equivalent to 2.1 percent per year, obtained by dividing GDP in IIIQ2017 of $17,163.9 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/23: {[($17,163.9/$15,190.3)4/23 -1]100 = 2.1 percent}.

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

Number
of
Quarters

Cumulative Growth

∆%

Average Annual Equivalent Growth Rate

IIIQ 1954 to IQ1957

11

12.8

4.5

First Four Quarters IIIQ1954 to IIQ1955

4

7.8

IIQ1958 to IIQ1959

5

10.0

7.9

First Four Quarters

IIIQ1958 to IIQ1959

4

9.2

IIQ1975 to IVQ1976

8

8.3

4.1

First Four Quarters IIIQ1975 to IIQ1976

4

6.1

IQ1983-IQ1986

IQ1983-IIIQ1986

IQ1983-IVQ1986

IQ1983-IQ1987

IQ1983-IIQ1987

IQ1983 to IIIQ1987

IQ1983 to IVQ1987

IQ1983 to IQ1988

IQ1983 to IIQ1988

IQ1983 to IIIQ1988

IQ1983 to IVQ1988

IQ1983 to IQ1989

IQ1983 to IIQ1989

IQ1983 to IIIQ1989

IQ1983 to IVQ1989

IQ1983 to IQ1990

IQ1983 to IIQ1990

IQ1983 to IIIQ1990

IQ1983 to IVQ1990

IQ1983 to IQ1991

13

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

19.9

21.6

22.3

23.1

24.5

25.6

27.7

28.4

30.1

30.9

32.6

34.0

35.0

36.0

36.3

37.8

38.3

38.4

37.2

36.5

5.7

5.4

5.2

5.0

5.0

4.9

5.0

4.9

4.9

4.8

4.8

4.8

4.7

4.7

4.5

4.5

4.4

4.3

4.0

3.8

First Four Quarters IQ1983 to IVQ1983

4

7.8

Average First Four Quarters in Four Expansions*

7.7

IIIQ2009 to IIIQ2017

33

19.6

2.2

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 1990. Employment surged after the contraction and grew rapidly during the decade. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the decline of employment in 1990.

Chart I-21, US, Employed, Thousands, 1979-1990

Source: US Bureau of Labor Statistics

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

Chart I-22 provides the level of employment in the US from 2001 to 2016. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs. Recovery has been anemic compared with the shallow recession of 2001 that was followed by nearly vertical growth in jobs. The number employed in Dec 2017 was 153.602 million (NSA) or 6.287 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 256.109 million in Dec 2017 or by 24.151 million. The number employed increased 4.3 percent from Jul 2007 to Dec 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 10.4 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employed as percent of population of 231.958 million). The same ratio in Dec 2017 would result in 162.629 million jobs (0.635 multiplied by noninstitutional civilian population of 256.109 million). There are effectively 9.027 million fewer jobs in Dec 2017 than in Jul 2007, or 162.629 million minus 153.602 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

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

Source: US Bureau of Labor Statistics

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

The US civilian labor force in Chart I-23 grew with few interruptions from 1979 to 1990. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the flattening of the curve in 1990.

Chart I-23, US, Civilian Labor Force, Thousands, 1979-1990

Source: US Bureau of Labor Statistics

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

The civilian labor force in Chart I-24 grew steadily on an upward trend in the 2000s until it contracted together with the economy after 2007. There has not been recovery during the expansion but rather decline and marginal turn of the year 2011 into expansion in 2012 followed by stability and oscillation into 2013-2017. There is substantial underperformance relative to trend before the global recession. The civilian labor force consists of people who are available and willing to work and who have searched for employment recently. The labor force of the US NSA grew 9.4 percent from 142.828 million in Jan 2001 to 156.255 million in Jul 2009. The civilian labor force is 2.6 percent higher at 160.320 million in Dec 2017 than in Jul 2009, all numbers not seasonally adjusted. Chart I-3 shows the flattening of the curve of expansion of the labor force and its decline in 2010 and 2011. The ratio of the labor force of 154.871 million in Jul 2007 to the noninstitutional population of 231.958 million in Jul 2007 was 66.8 percent while the ratio of the labor force of 159.880 million in Dec 2017 to the noninstitutional population of 256.109 million in Dec 2017 was 62.4 percent. The labor force of the US in Dec 2017 corresponding to 66.8 percent of participation in the population would be 171.081 million (0.668 x 256.109). The difference between the measured labor force in Dec 2017 of 159.880 million and the labor force in Dec 2017 with participation rate of 66.8 percent (as in Jul 2007) of 171.081 million is 11.201 million. The level of the labor force in the US has stagnated and is 11.201 million lower than what it would have been had the same participation rate been maintained. Millions of people have abandoned their search for employment because they believe there are no jobs available for them. The key issue is whether the decline in participation of the population in the labor force is the result of people giving up on finding another job.

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

Source: US Bureau of Labor Statistics

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

The rate of participation of the labor force in population stagnated during the stagflation and conquest of inflation in the late 1970s and early 1980s, as shown in Chart I-25. Recovery was vigorous during the expansion and lasted through the remainder of the decade. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the flattening/decline of the curve in 1990.

Chart I-25, US, Civilian Labor Force Participation Rate, 1979-1990, %

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

Chart I-27 provides the number unemployed during the 1980s. The number unemployed peaked at 12.051 million in Dec 1982 seasonally adjusted and 12.517 in Jan 1983 million not seasonally adjusted, declining to 8.358 million in Dec 1984 seasonally adjusted and 7.978 million in Dec 1984 not seasonally adjusted during the first two years of expansion from the contraction. The number unemployed then fell to 6.667 million in Dec 1989 seasonally adjusted and 6.300 million not seasonally adjusted. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the increase of the curve in 1990 with 7.525 million unemployed NSA and 7.901 million SA.

Chart I-27, US, Unemployed Thousands 1979-1990

Source: US Bureau of Labor Statistics

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

Chart I-28 provides the number unemployed from 2001 to 2017. Using seasonally adjusted data, the number unemployed rose from 6.727 million in Oct 2006 to 15.352 million in Oct 2009, declining to 13.093 million in Dec 2011, 8.718 million in Dec 2014 and 7.927 million in Dec 2015. The number unemployed SA stood at 7.529 million in Dec 2016. The level of unemployment SA was 6.576 million in Dec 2017. Using data not seasonally adjusted, the number unemployed rose from 6.272 million in Oct 2006 to 16.147 million in Jan 2010, declining to 11.844 million in Dec 2012, increasing to 13.181 million in Jan 2013 and declining to 9.984 million in Dec 2013. The level of unemployment fell from 10.855 million in Jan 2014 to 8.331 million in Dec 2014. The level of unemployment was 7.542 million in Dec 2015 and 7.170 million in Dec 2016. The level of unemployment was 6.278 million in Dec 2017.

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

Source: US Bureau of Labor St

atistics

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

The rate of unemployment peaked at 10.8 percent in both Nov and Dec 1982 seasonally adjusted, as shown in Chart I-29. The rate of unemployment dropped sharply during the expansion after 1984 and continued to decline during the rest of the decade to 5.4 percent in Dec 1989. Using not seasonally adjusted data, the rate of unemployment peaked at 11.4 percent in Jan 1983, declining to 7.0 percent in Dec 1984 and 5.1 percent in Dec 1989. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the increase of the curve in Dec 1990 with 6.0 percent unemployed NSA and 6.2 percent SA.

Chart I-29, US, Unemployment Rate, 1979-1990, %

Source: US Bureau of Labor Statistics

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

The rate of unemployment in the US seasonally adjusted jumped from 4.4 percent in May 2007 to 10.0 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009, as shown in Chart I-30. The rate of unemployment fluctuated at around 9.0 percent in 2011, declining to 7.9 percent in Dec 2012 and 6.7 percent in Dec 2013. The rate of unemployed eased to 5.6 percent in Dec 2014 and 5.0 percent in Dec 2015. The rate of unemployment SA stood at 4.7 percent in Dec 2016. The rate of unemployment SA reached 4.1 percent in Dec 2017.

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

Source: US Bureau of Labor Statistics

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

The employment population ratio seasonally adjusted fell from around 60.1 in Dec 1979 to 57.1 in both Feb and Mar 1983, as shown in Chart I-31. The employment population ratio seasonally adjusted rose back to 59.9 in Dec 1984 and reached 63.0 later in the decade in Dec 1989. Using not seasonally adjusted data, the employment population ratio dropped from 60.4 percent in Oct 1979 to 56.1 percent in Jan 1983, increasing to 59.8 in Dec 1984 and to 62.9 percent in Dec 1989. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the increase of the curve in Dec 1990 with 62.2 NSA and 62.2 percent SA.

Chart I-31, US, Employment Population Ratio, 1979-1990, %

Source: US Bureau of Labor Statistics

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

The US employment-population ratio seasonally adjusted has fallen from 63.4 in Dec 2006 to 58.6 in Dec 2011, 58.7 in Dec 2012, 58.7 in Dec 2013, 59.2 in Dec 2014 and 59.6 in Dec 2015, as shown in Chart I-32. The employment-population ratio reached 59.7 in Dec 2016. The employment population ratio stood at 60.1 in Dec

2017. The employment population-ratio has stagnated during the expansion. Using not seasonally adjusted data, the employment population ratio fell from 63.6 percent in Jul 2006 to 57.6 percent in Jan 2011, 58.5 percent in Dec 2012, 58.5 percent in Dec 2013 and 59.1 in Dec 2014. The employment population ratio reached 59.4 percent in Dec 2015 and 59.6 percent in Dec 2016. The employment population ratio stood at 60.0 in Dec 2017.

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

Source: US Bureau of Labor Statistics

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

The number unemployed 27 weeks or more rose in Chart I-33 rose from 492,000 NSA in Oct 1979 to 2.978 million in Mar 1983. The level unemployed 27 weeks or more NSA fell to 566,000 in Aug 1989. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the increase of the curve in Dec 1990 with 774,000 NSA and 831,000 SA.

Chart I-33, US, Number Unemployed for 27 Weeks or More 1979-1990, SA, Thousands

Source: US Bureau of Labor Statistics

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

The number unemployed for 27 weeks or over, seasonally adjusted, increased sharply during the contraction as shown in Chart I-34 from 1.131 million in Nov 2006 to 6.800 million in Apr 2010 seasonally adjusted. The number of unemployed for 27 weeks or over remained at around 6 million during the expansion compared with somewhat above 1 million before the contraction, falling to 1.869 million in Dec 2016 seasonally adjusted and 1.769 million not seasonally adjusted. The level unemployed for 27 weeks or over reached 1.515 million SA in Dec 2017 and 1.420 million NSA.

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

Source: US Bureau of Labor Statistics

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

The number of persons working part-time for economic reasons because they cannot find full-time work peaked during the contraction at 6.857 million SA in Oct 1982, as shown in Chart I-35. The number of persons at work part-time for economic reasons fell sharply during the expansion to 5.797 million in Dec 1984 and continued to fall throughout the decade to 4.817 million in Dec 1989 SA and 4.709 million NSA. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the increase of the curve in Dec 1990 with 5.615 million NSA and 5.699 million SA.

Chart I-35, US, Part-Time for Economic Reasons, 1979-1990, Thousands

Source: US Bureau of Labor Statistics

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

The number of people working part-time because they cannot find full-time employment, not seasonally adjusted, increased sharply during the contraction from 3.787 million in Apr 2006, not seasonally adjusted, to 9.354 million in Dec 2009, as shown in Chart I-36. The number of people working part-time because of failure to find an alternative occupation stagnated at a very high level during the expansion, declining to 5.060 million not seasonally adjusted in Dec 2017.

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

Source: US Bureau of Labor Statistics

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

The number marginally attached to the labor force in Chart I-37 jumped from 1.252 million in Dec 2006 to 2.800 million in Jan 2011, remaining at a high level of 2.540 million in Dec 2011, 2.809 million in Jan 2012 and 2.614 million in Dec 2012. The number marginally attached to the labor force eased to 2.427 million in Dec 2013, 2.260 million in Dec 2014 and 1.833 million in Dec 2015. The level of marginally attached to the labor force reached 1.684 million in Dec 2016. The number of marginally attached to the labor force stood at 1.623 million in Dec 2017.

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

Source: US Bureau of Labor Statistics

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

IA4 Job Creation. What is striking about the data in Table I-8 is that the numbers of monthly increases in jobs in 1983 and 1984 are several times higher than in 2010 to 2016. The civilian noninstitutional population grew by 45.5 percent from 174.215 million in 1983 to 253.538 million in 2016 and labor force higher by 42.7 percent, growing from 111.550 million in 1983 to 159.187 million in 2016. Total nonfarm payroll employment seasonally adjusted (SA) increased 148,000 in Dec 2017 and private payroll employment increased 146,000. The Bureau of Labor Statistics states (https://www.bls.gov/news.release/empsit.nr0.htm): “Our analysis suggests that the net effect of these hurricanes [Harvey and Irma] was to reduce the estimate of total nonfarm payroll employment for September. There was no discernible effect on the national unemployment rate. No changes were made to either the establishment or household survey estimation procedures for the September figures.” The average monthly number of nonfarm jobs created from Dec 2015 to Dec 2016 was 186,667 using seasonally adjusted data, while the average number of nonfarm jobs created from Dec 2016 to Dec 2017 was 171,250, or decrease by 8.3 percent. The average number of private jobs created in the US from Dec 2015 to Dec 2016 was 169,917, using seasonally adjusted data, while the average from Dec 2016 to Dec 2017 was 167,750, or decrease by 1.3 percent. This blog calculates the effective labor force of the US at 169,544 million in Dec 2017 and 168,639 million in Dec 2016 (Table I-4), for growth of 0.905 million at average 75,417 per month. The difference between the average increase of 167,750 new private nonfarm jobs per month in the US from Dec 2016 to Dec 2017 and the 75,417-average monthly increase in the labor force from Dec 2016 to Dec 2017 is 92,333 monthly new jobs net of absorption of new entrants in the labor force. There are 22.625 million in job stress in the US currently. Creation of 92,333 new jobs per month net of absorption of new entrants in the labor force would require 245 months to provide jobs for the unemployed and underemployed (22.625 million divided by 92,333) or 20 years (245 divided by 12). The civilian labor force of the US in Dec 2017 not seasonally adjusted stood at 159.880 million with 6.278 million unemployed or effectively 15.942 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 169.544 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 0.903 years (1 million divided by product of 92,333 by 12, which is 1,107,996). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.994 million (0.05 times labor force of 159.880 million). New net job creation would be minus 1.716 million (6.278 million unemployed minus 7.994 million unemployed at rate of 5 percent) that at the current rate would take 0.0 years (-1.716 million divided by 1.108). Under the calculation in this blog, there are 15.942 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 169.544 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 7.465 million jobs net of labor force growth that at the current rate would take 6.7 years (15.942 million minus 0.05(169.544 million) = 7.465 million divided by 1.107996 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 Dec 2017 was 153.602 million (NSA) or 6.287 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 256.109 million in Dec 2017 or by 24.151 million. The number employed increased 4.3 percent from Jul 2007 to Dec 2017 while the noninstitutional civilian population of ages of 16 years and over, or those available for work, increased 10.4 percent. The ratio of employment to population in Jul 2007 was 63.5 percent (147.315 million employed as percent of population of 231.958 million). The same ratio in Dec 2017 would result in 162.629 million jobs (0.635 multiplied by noninstitutional civilian population of 256.109 million). There are effectively 9.027 million fewer jobs in Dec 2017 than in Jul 2007, or 162.629 million minus 153.602 million. There is actually not sufficient job creation in merely absorbing new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.

There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

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

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (https://cmpassocregulationblog.blogspot.com/2017/12/fomc-increases-interest-rates-with.html). The proper explanation is not in secular stagnation but in cyclically slow growth. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 33 quarters from IIIQ2009 to IIIQ2017. 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 IIIQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp3q17_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 dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2835.2 billion than actual $17,163.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.3 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,163.9 billion in IIIQ2017 or 14.5 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 146.5098 in Nov 2017. The actual index NSA in Nov 2017 is 104.6305, which is 28.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Nov 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.7256 in Nov 2017. The output of manufacturing at 104.6305 in Nov 2017 is 20.6 percent below trend under this alternative calculation.

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

Month

1981

1982

1983

2008

2009

2010

Private

Jan

94

-326

224

17

-793

23

14

Feb

68

-5

-75

-84

-702

-68

-53

Mar

105

-130

172

-78

-823

164

122

Apr

73

-280

276

-210

-687

243

192

May

10

-45

277

-186

-349

524

97

Jun

197

-243

379

-162

-471

-137

119

Jul

112

-342

418

-213

-329

-68

103

Aug

-36

-158

-308

-267

-213

-36

113

Sep

-87

-181

1115

-450

-220

-52

121

Oct

-99

-277

271

-474

-204

262

212

Nov

-209

-123

353

-766

-2

119

129

Dec

-278

-14

356

-694

-275

87

108

1984

2011

Private

Jan

446

43

51

Feb

481

189

232

Mar

275

225

248

Apr

363

346

354

May

308

77

132

Jun

379

225

190

Jul

313

69

184

Aug

242

110

142

Sep

310

248

282

Oct

286

209

194

Nov

349

141

168

Dec

128

209

226

1985

2012

Private

Jan

266

358

366

Feb

124

237

236

Mar

346

233

237

Apr

196

78

90

May

274

115

135

Jun

146

76

57

Jul

190

143

160

Aug

193

177

174

Sep

203

203

194

Oct

188

146

168

Nov

209

132

152

Dec

167

244

240

1986

2013

Private

Jan

125

211

226

Feb

107

286

267

Mar

94

130

152

Apr

187

197

195

May

127

226

242

Jun

-94

162

179

Jul

318

122

146

Aug

114

261

242

Sep

347

190

184

Oct

186

212

214

Nov

186

258

250

Dec

205

47

73

1987

2014

Private

Jan

172

190

204

Feb

232

151

139

Mar

249

272

261

Apr

338

329

299

May

226

246

252

Jun

172

304

259

Jul

347

202

226

Aug

171

230

238

Sep

228

280

237

Oct

492

227

214

Nov

232

312

302

Dec

294

255

240

1988

2015

Private

Jan

94

234

227

Feb

453

238

222

Mar

276

86

97

Apr

245

262

235

May

229

344

324

Jun

363

206

195

Jul

222

254

239

Aug

124

157

115

Sep

339

100

116

Oct

268

321

314

Nov

339

272

260

Dec

290

239

217

1989

2016

Private

Jan

262

126

110

Feb

258

237

221

Mar

193

225

189

Apr

173

153

158

May

118

43

17

Jun

116

297

269

Jul

40

291

249

Aug

49

176

143

Sep

250

249

223

Oct

111

124

132

Nov

277

164

178

Dec

96

155

150

1990

2017

Private

Jan

336

216

204

Feb

248

232

222

Mar

215

50

59

Apr

39

207

194

May

152

145

153

Jun

22

210

207

Jul

-31

138

133

Aug

-216

208

184

Sep

-90

38

50

Oct

-160

211

222

Nov

-149

252

239

Dec

-56

148

146

Source: US Bureau of Labor Statistics

http://www.bls.gov/

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

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

Source: US Bureau of Labor Statistics

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

Chart I-39 provides total nonfarm jobs SA from 1979 to 1990. Recovery is strong throughout the decade with the economy growing at trend over the entire economic cycle. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the decline of the curve in 1990.

Chart I-39, US, Total Nonfarm Payroll Jobs SA 1979-1990

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

In contrast, growth of private payroll jobs in the US recovered vigorously during the expansion in 1983 through 1985, as shown in Chart I-41. Rapid growth of creation of private jobs continued throughout the 1980s. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The third recession explains the decline of the curve in 1990.

Chart I-41, US, Total Private Payroll Jobs SA 1979-1990

Source: US Bureau of Labor Statistics

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

Types of jobs created, and not only the pace of job creation, may be important. Aspects of growth of payroll jobs from Dec 2016 to Dec 2017, not seasonally adjusted (NSA), are in Table I-9. Total nonfarm employment increased by 2,188,000 (row A, column Change), consisting of growth of total private employment by 2,132,000 (row B, column Change) and increase by 56,000 of government employment (row C, column Change). Monthly average growth of private payroll employment has been 177,667, which is mediocre relative to 22 to 30 million in job stress, while total nonfarm employment has grown on average by only 182,333 per month, which does not significantly reduce job stress with 75,417 new entrants per month in the labor force. These monthly rates of job creation net of the demands of new entrants in the labor force perpetuate unemployment and underemployment. Manufacturing employment increased 198,000, at the monthly rate of 16,500 while private service providing employment grew by 1,623,000, at the monthly average rate of 135,250. An important feature in Table I-9 is that jobs in professional and business services increased 521,000 with temporary help services increasing 121,000. 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 309,000 jobs in 12 months. An important characteristic is that the loss of government jobs has stabilized in federal government with decrease of 18,000 jobs while states decreased 13,000 jobs and local government added 87,000 jobs. Local government provides the bulk of government jobs, 14.696 million, while federal government provides 2.819 million and states’ government 5.177 million.

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

Dec 2016

Dec 2017

Change

A Total Nonfarm

146,158

148,346

2,188

B Total Private

123,522

125,654

2,132

B1 Goods Producing

19,670

20,179

509

B1a

Manufacturing

12,341

12,539

198

B2 Private service providing

103,852

105,475

1,623

B2a Wholesale Trade

5,893

5,964

71

B2b Retail Trade

16,376

16,346

-30

B2c Transportation & Warehousing

5,265

5,358

93

B2d Financial Activities

8,373

8,505

132

B2e Professional and Business Services

20,521

21,042

521

B2e1 Temporary help services

3,093

3,214

121

B2f Health Care & Social Assistance

19,324

19,707

383

B2g Leisure & Hospitality

15,394

15,703

309

C Government

22,636

22,692

56

C1 Federal

2,837

2,819

-18

C2 State

5,190

5,177

-13

C3 Local

14,609

14,696

87

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Greater detail on the types of jobs created is provided in Table I-10 with data for Nov 2017 and

Dec 2017. Strong seasonal effects are shown by the significant difference between seasonally adjusted (SA) and not-seasonally-adjusted (NSA) data. The purpose of adjusting for seasonality is to isolate nonseasonal effects. The 148,000 SA total nonfarm jobs created in Dec 2017 relative to Nov 2017 actually correspond to decrease of 180 thousand jobs NSA, as shown in row A. Most of this difference in Jan 2017 is due to the necessary benchmark and seasonal adjustments in the beginning of every year. The 146,000 total private payroll jobs SA created in Dec 2017 relative to Nov 2017 actually correspond to decrease of 62 thousand jobs NSA. The analysis of NSA job creation in the prior Table I-9 does show improvement over the 12 months ending in Dec 2017 that is not clouded by seasonal variations but is inadequate number of jobs created. In fact, the 12-month rate of job creation without seasonal adjustment is stronger indication of marginal improvement in the US job market but that is insufficient in even making a dent in about 30 million people unemployed or underemployed. Benchmark and seasonal adjustments affect comparability of data over time.

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

Nov 2017

Dec

2017

∆

Nov 2017

Dec 2017

∆

A Total Nonfarm

147,232

147,380

148

148,526

148,346

-180

B Total Private

124,893

125,039

146

125,716

125,654

-62

B1 Goods Producing

20,204

20,259

55

20,299

20,179

-120

B1a Constr.

6963

6993

30

7057

6910

-147

B Mfg

12,514

12,539

25

12,507

12,539

32

B2 Private Service Providing

104,689

104,780

91

105,417

105,475

58

B2a Wholesale Trade

5949

5959

10

5961

5964

3

B2b Retail Trade

15,835

15,815

-20

16,287

16,346

59

B2c Couriers     & Mess.

676

678

2

732

874

142

B2d Health-care & Social Assistance

19,611

19,640

29

19,664

19,707

43

B2De Profess. & Business Services

20,924

20,943

19

21,125

21,042

-83

B2De1 Temp Help Services

3,090

3,097

7

3,232

3,214

-18

B2f Leisure & Hospit.

16,021

16,050

29

15,738

15,703

-35

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Manufacturing jobs not seasonally adjusted increased 198,000 from Dec 2016 to
Dec 2017 or at the average monthly rate of 16,500. Industrial production increased 0.2 percent in Nov 2017 and increased 1.2 percent in Oct 2017 after increasing 0.3 percent in Sep 2017, with all data seasonally adjusted. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 31, 2017 (https://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] On net, the revisions were small, and the contour of total IP is little changed. Total IP is still reported to have moved up about 22 percent from the end of the recession in mid-2009 through late 2014, to have declined in 2015, and to have moved sideways in 2016. The most notable difference between the current and the previous estimates is that total IP is now reported to have decreased about 2 3/4 percent in 2015, whereas it previously showed a decline of about 1 3/4 percent.[2] The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2015 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

Capacity for total industry is now reported to have expanded about 1 percent in 2015, a lower rate of increase than was reported earlier. Capacity was little changed in 2016 and is expected to increase 1 percent in 2017. Compared with prior reports, the rates of change in 2016 and 2017 are now a little smaller. In the fourth quarter of 2016, capacity utilization for total industry stood at 75.8 percent, a rate 0.4 percentage point higher than previously published but still 4.1 percentage points below its long-run (1972–2016) average. Relative to earlier estimates, the utilization rates in recent years are now a little higher.” Manufacturing decreased 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increased 15.5 percent from the trough in Apr 2009 to Dec 2016. Manufacturing grew 19.7 percent from the trough in Apr 2009 to Nov 2017. Manufacturing in Nov 2017 is lower by 7.1 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 IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2835.2 billion than actual $17,163.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.3 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,163.9 billion in IIIQ2017 or 14.5 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 146.5098 in Nov 2017. The actual index NSA in Nov 2017 is 104.6305, which is 28.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Nov 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.7256 in Nov 2017. The output of manufacturing at 104.6305 in Nov 2017 is 20.6 percent below trend under this alternative calculation. Table I-13 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 87.0 percent in IIIQ2017. Most of US national income is in the form of services. In Dec 2017, there were 148.346 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 125.654 million NSA in Dec 2017 accounted for 84.7 percent of total nonfarm jobs of 148.346 million, of which 12.539 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 105.475 million NSA in Dec 2017, or 71.1 percent of total nonfarm jobs and 83.9 percent of total private-sector jobs. Manufacturing has share of 10.2 percent in US national income in IIIQ2017 and durable goods 5.9 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 IIQ2017

% Total

SAAR IIIQ2017

% Total

National Income WCCA

16,398.1

100.0

16,592.2

100.0

Domestic Industries

16,195.7

98.8

16,363.9

98.6

Private Industries

14,275.0

87.1

14,430.8

87.0

Agriculture

125.5

0.8

122.3

0.7

Mining

155.4

0.9

142.0

0.9

Utilities

196.5

1.2

195.8

1.2

Construction

817.1

5.0

847.6

5.1

Manufacturing

1657.0

10.1

1694.9

10.2

Durable Goods

977.3

6.0

986.9

5.9

Nondurable Goods

679.7

4.1

708.0

4.3

Wholesale Trade

933.0

5.7

939.7

5.7

Retail Trade

1141.6

7.0

1146.8

6.9

Transportation & WH

521.5

3.2

511.7

3.1

Information

618.9

3.8

621.8

3.7

Finance, Insurance, RE

2881.9

17.6

2947.1

17.8

Professional & Business Services

2352.4

14.3

2373.4

14.3

Education, Health Care

1671.8

10.2

1671.1

10.1

Arts, Entertainment

720.7

4.4

731.2

4.4

Other Services

481.5

2.9

485.4

2.9

Government

1920.7

11.7

1933.1

11.7

Rest of the World

202.4

1.2

228.3

1.4

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

Source: US Bureau of Economic Analysis

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

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

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

Source: Board of Governors of the Federal Reserve

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

The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). Table I-12 provides total annual level nonfarm employment in the US for the 1980s and the 2000s, which is different from 12-month comparisons. Nonfarm jobs rose by 4.859 million from 1982 to 1984, or 5.4 percent, and continued rapid growth in the rest of the decade. In contrast, nonfarm jobs are down by 7.638 million in 2010 relative to 2007 and fell by 952,000 in 2010 relative to 2009 even after six quarters of GDP growth. Monetary and fiscal stimuli have failed in increasing growth to rates required for mitigating job stress. The initial growth impulse reflects a flatter growth curve in the current expansion. Nonfarm jobs declined from 137.999 million in 2007 to 136.381 million in 2013, by 1.618 million or 1.2 percent. Nonfarm jobs increased from 137.999 million in 2007 to 144,306 million in 2016, by 6.308 million or 4.6 percent. The US noninstitutional population or in condition to work increased from 231.867 million in 2007 to 253.538 million in 2016, by 21,671 million or 9.3 percent. The ratio of nonfarm jobs of 137.999 million in 2007 to the noninstitutional population of 231.867 was 59.5. Nonfarm jobs in 2016 corresponding to the ratio of 59.5 of nonfarm jobs/noninstitutional population would be 150.855 million (0.595x253.538). The difference between actual nonfarm jobs of 144.306 million in 2016 and nonfarm jobs of 150.855 million that are equivalent to 59.5 percent of the noninstitutional population as in 2007 is 6.549 million fewer jobs. The proper explanation for this loss of work opportunities is not in secular stagnation but in cyclically slow growth. The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). The proper explanation for this loss of work opportunities is not in secular stagnation but in cyclically slow growth. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2835.2 billion than actual $17,163.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.3 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,163.9 billion in IIIQ2017 or 14.5 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 146.5098 in Nov 2017. The actual index NSA in Nov 2017 is 104.6305, which is 28.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Nov 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.7256 in Nov 2017. The output of manufacturing at 104.6305 in Nov 2017 is 20.6 percent below trend under this alternative calculation.

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

Year

Total Nonfarm

Year

Total Nonfarm

1980

90,533

2000

132,024

1981

91,297

2001

132,087

1982

89,689

2002

130,649

1983

90,295

2003

130,347

1984

94,548

2004

131,787

1985

97,532

2005

134,051

1986

99,500

2006

136,453

1987

102,116

2007

137,999

1988

105,378

2008

137,242

1989

108,051

2009

131,313

1990

109,527

2010

130,361

1991

108,427

2011

131,932

1992

108,802

2012

134,175

1993

110,935

2013

136,381

1994

114,398

2014

138,958

1995

117,407

2015

141,843

1996

119,836

2016

144,306

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

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

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

Source: US Bureau of Labor Statistics

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

Chart I-44 provides annual nonfarm jobs in the US from 1980 to 1996. 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-41, US, Total Private Payroll Jobs SA 1979-1990

Source: US Bureau of Labor Statistics

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

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

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

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

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

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

Total Nonfarm Jobs

Total Private Jobs

06/1981 #

92,288

75,969

11/1982 #

89,482

73,260

Change #

-2,806

-2,709

Change ∆%

-3.0

-3.6

12/1982 #

89,383

73,185

05/1984 #

94,471

78,049

Change #

5,088

4,864

Change ∆%

5.7

6.6

11/2007 #

139,090

116,291

05/2009 #

131,626

108,601

Change %

-7,464

-7,690

Change ∆%

-5.4

-6.6

12/2009 #

130,178

107,338

05/2011 #

131,753

108,494

Change #

1,575

1,156

Change ∆%

1.2

1.1

05/1983 #

90,005

73,667

05/1984 #

94,471

78,049

Change #

4,466

4,382

Change ∆%

4.9

5.9

05/2010 #

130,801

107,405

05/2011 #

131,753

109,203

Change #

952

1,798

Change ∆%

0.7

1.7

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

6,409*

6,337**

Difference in Jobs that Would Have Been Created

5,457 =
6,409-952

4,539 =
6,337-1,798

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

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

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

IB Stagnating Real Wages. The wage bill is the product of average weekly hours times the earnings per hour. Table IB-1 provides the estimates by the Bureau of Labor Statistics (BLS) of earnings per hour seasonally adjusted, increasing from $25.98/hour in Dec 2016 to $26.63/hour in Dec 2017, or by 2.5 percent. There has been disappointment about the pace of wage increases because of rising food and energy costs that inhibit consumption and thus sales and similar concern about growth of consumption that accounts for about 68.9 percent of GDP (Table I-10 at https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html). Growth of consumption by decreasing savings by means of controlling interest rates in what is called financial repression may not be lasting and sound for personal finances (See Pelaez and Pelaez, Globalization and the State, Vol. II (2008c), 81-6, Pelaez (1975), https://cmpassocregulationblog.blogspot.com/2017/12/dollar-devaluation-cyclically.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html and earlier https://cmpassocregulationblog.blogspot.com/2017/10/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/twenty-two-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/08/data-dependent-monetary-policy-with.html and earlier https://cmpassocregulationblog.blogspot.com/2017/07/rising-yields-twenty-two-million.html and earlier https://cmpassocregulationblog.blogspot.com/2017/06/twenty-two-million-unemployed-or.html https://cmpassocregulationblog.blogspot.com/2017/05/twenty-two-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/04/twenty-three-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/12/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/closely-monitoring-global-economic-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/dollar-revaluation-and-decreasing.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/dollar-revaluation-constraining.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/11/live-possibility-of-interest-rates.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/labor-market-uncertainty-and-interest.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html http://cmpassocregulationblog.blogspot.com/2015/08/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/dollar-devaluation-and-carry-trade.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/global-competitive-devaluation-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2015/02/job-creation-and-monetary-policy-twenty.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/valuations-of-risk-financial-assets.html http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/geopolitical-and-financial-risks.html and earlier http://cmpassocregulationblog.blogspot.com/2014/08/fluctuating-financial-valuations.html http://cmpassocregulationblog.blogspot.com/2014/06/financial-indecision-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/06/financial-instability-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-uncertainty-mediocre-cyclical.html

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

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

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

http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states.html http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html http://cmpassocregulationblog.blogspot.com/2012/09/collapse-of-united-states-dynamism-of.html http://cmpassocregulationblog.blogspot.com/2012/07/recovery-without-jobs-stagnating-real.html http://cmpassocregulationblog.blogspot.com/2012/06/mediocre-recovery-without-jobs.html http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-economic-growth-falling-real.html http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html http://cmpassocregulationblog.blogspot.com/2012/01/mediocre-economic-growth-financial.html http://cmpassocregulationblog.blogspot.com/2011/12/slow-growth-falling-real-disposable.html http://cmpassocregulationblog.blogspot.com/2011/11/us-growth-standstill-falling-real.html http://cmpassocregulationblog.blogspot.com/2011/10/slow-growth-driven-by-reducing-savings.html). Average hourly earnings seasonally adjusted increased 0.3 percent from $26.54 in Nov 2017 to $26.63 in Dec 2017. Average private weekly earnings increased $25.03 from $893.71 in Dec 2016 to $918.74 in Dec 2017 or 2.8 percent and increased $3.11 from $915.63 in Nov 2017 to $918.74 in Dec 2017 or 0.3 percent. The inflation-adjusted wage bill can only be calculated for Nov, which is the most recent month for which there are estimates of the consumer price index. Earnings per hour (not-seasonally-adjusted (NSA)) rose from $25.87 in Nov 2016 to $26.48 in Nov 2017 or by 2.4 percent (http://www.bls.gov/data/; see Table IB-3 below). Data NSA are more suitable for comparison over a year. Average weekly hours NSA were 34.3 in

Nov 2016 and 34.4 in Nov 2017 (http://www.bls.gov/data/; see Table IB-2 below). The wage bill increased 2.7 percent in the 12 months ending in Nov 2017:

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

{[($26.48x34.4)/($25.87x34.3)]-1]}100

= {[($910.91)/($887.34)]-1}100 = 2.7%

CPI inflation was 2.2 percent in the 12 months ending in Nov 2017 (http://www.bls.gov/cpi/) for an inflation-adjusted wage-bill change of 0.5 percent: {[(1.027/1.022)-1]100 = 0.5%} (see Table IB-5 below for Nov 2017 with minor rounding difference). The wage bill for Dec 2017 before inflation adjustment increased 3.2 percent relative to the wage bill for Dec 2016:

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

{[($26.58x34.5)/($25.90x34.3)]-1]}100

= {[$917.01)/$888.37]-1}100 = 3.2%}

Average hourly earnings increased 2.6 percent from Dec 2016 to Dec 2017 {[($26.58/$25.90) – 1]100 = 2.6%} while hours worked increased 0.6 percent {[(34.5/34.3) – 1]100 = 0.6%}. 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 0.6 percent {[(1.026x1.006) -1]100 = 3.2 %} with small rounding error. Energy and food price increases are similar to a “silent tax” that is highly regressive, harming the most those with lowest incomes. There are concerns that the wage bill would deteriorate in purchasing power because of renewed raw materials shocks in the form of increases in prices of commodities such as the 31.1 percent steady increase in the DJ-UBS Commodity Index from Jul 2, 2010 to Sep 2, 2011. The charts of four commodity price indexes by Bloomberg show steady increase since Jul 2, 2010 that was interrupted briefly only in Nov 2010 with the sovereign issues in Europe triggered by Ireland; in Mar 2011 by the earthquake and tsunami in Japan; and in the beginning of May 2011 by the decline in oil prices and sovereign risk difficulties in Europe (http://www.bloomberg.com/markets/commodities/futures/). Renewed risk aversion because of the sovereign risks in Europe had reduced the rate of increase of the DJ UBS commodity index to 10.2 percent on May 2, 2014, relative to Jul 2, 2010 (see Table VI-4) but there has been a shift in investor preferences into equities. Inflation has been rising in waves with carry trades driven by zero interest rates to commodity futures during periods of risk appetite with interruptions during risk aversion (https://cmpassocregulationblog.blogspot.com/2017/12/fomc-increases-interest-rates-with.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

Dec 2016

Oct 2017

Nov 2017

Dec 2017

Total Private

$25.98

$26.51

$26.54

$26.63

Goods Producing

$27.24

$27.77

$27.76

$27.81

Service Providing

$25.68

$26.21

$26.26

$26.35

Average Weekly Earnings

Total Private

$893.71

$911.94

$915.63

$918.74

Goods Producing

$1,095.05

$1,121.91

$1,124.28

$1,126.31

Service Providing

$855.14

$872.79

$874.46

$880.09

Average Weekly Hours

Total Private

34.4

34.4

34.5

34.5

Goods Producing

40.2

40.4

40.5

40.5

Service Providing

33.3

33.2

33.3

33.4

Source: US Bureau of Labor Statistics

http://www.bls.gov/

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

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

Year

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

2006

34.5

34.7

34.5

34.3

34.7

34.3

34.4

2007

34.5

34.8

34.5

34.8

34.3

34.3

34.8

34.4

2008

34.8

34.3

34.5

34.2

34.2

34.4

33.9

34.3

2009

33.7

33.8

34.3

33.7

33.8

34.2

33.8

33.8

2010

34.1

34.2

34.7

34.1

34.3

34.2

34.2

34.1

2011

34.3

34.4

34.4

34.4

34.8

34.3

34.4

34.3

2012

34.4

34.7

34.5

34.8

34.3

34.3

34.8

34.5

2013

34.9

34.3

34.5

34.9

34.4

34.4

34.7

34.4

2014

34.9

34.5

34.6

34.5

34.5

34.9

34.6

34.5

2015

34.5

34.5

35.1

34.3

34.5

34.8

34.5

34.5

2016

34.4

34.4

34.4

34.4

34.8

34.3

34.3

34.4

2017

34.5

34.8

34.5

34.3

34.8

34.4

34.5

34.4

Source: US Bureau of Labor Statistics

http://www.bls.gov/

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

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

Source: US Bureau of Labor Statistics

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

Calculations of inflation-adjusted average hourly earnings using BLS data are in Table IB-3. The final column of Table IB-3 (“12-Month Real ∆%”) provides inflation-adjusted average hourly earnings of all employees in the US. Average hourly earnings rose above inflation throughout the first nine months of 2007 just before the global recession that began in the final quarter of 2007 when average hourly earnings began to lose to inflation. In contrast, average hourly earnings of all US workers have risen less than inflation in four months in 2010 and in all but the first month in 2011 and the loss accelerated at 1.8 percent in Sep 2011, declining to a real loss of 1.1 percent in Feb 2012 and 0.6 percent in Mar 2012. There was a gain of 0.5 percent in Apr 2012 in inflation-adjusted average hourly earnings but another fall of 0.6 percent in May 2012 followed by increases of 0.3 percent in Jun and 1.0 percent in Jul 2012. Real hourly earnings stagnated in the 12 months ending in Aug 2012 with increase of only 0.1 percent, and increased 0.7 percent in the 12 months ending in Sep 2012. Real hourly earnings fell 1.3 percent in Oct 2012 and gained 1.0 percent in Dec 2012 but declined 0.2 percent in Jan 2013 and stagnated at change of 0.2 percent in Feb 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Mar 2013 and 0.2 percent in Apr 2013, increasing 0.7 percent in May 2013. In Jun 2013, real hourly earnings increased 1.0 percent relative to Jun 2012. Real hourly earnings fell 0.6 percent in the 12 months ending in Jul 2013 and increased 0.8 percent in the 12 months ending in Aug 2013. Real hourly earnings increased 1.2 percent in the 12 months ending in Oct 2013 and 1.0 percent in Nov 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Dec 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Jan 2014 and 1.7 percent in the 12 months ending in Feb 2014. Real hourly earnings increased 1.3 percent in the 12 months ending in Mar 2014. Real hourly earnings changed 0.0 percent in the 12 months ending in Apr 2014. Real hourly earnings stagnated at 0.0 percent in the 12 months ending in May 2014. Real hourly earnings changed 0.0 percent in the 12 months ending in Jun 2014. Real hourly earnings increased 0.1 percent in the 12 months ending in Jul 2014 and increased 0.5 percent in the 12 months ending in Aug 2014. Real hourly earnings fell 0.3 percent in the 12 months ending in Sep 2014 and increased 0.3 percent in the 12 months ending in Oct 2014. Real hourly earnings increased 1.5 percent in the 12 months ending in Nov 2014. Real hourly earnings increased 0.4 percent in the 12 months ending in Dec 2014 and increased 2.3 percent in the 12 months ending in Jan 2015. Real hourly earnings increased 1.9 percent in the 12 months ending in Feb 2015 and 2.3 percent in the 12 months ending in Mar 2015. Real hourly earnings increased 2.4 percent in the 12 months ending in Apr 2015 and increased 2.4 percent in the 12 months ending in May 2015. Real hourly earnings increased 1.3 percent in the 12 months ending in Jun 2015 and increased 1.9 percent in the 12 months ending in Jul 2015. Real hourly earnings increased 2.8 percent in the 12 months ending in Aug 2015 and increased 2.2 percent in the 12 months ending in Sep 2015. Real hourly earnings increased 2.3 percent in the 12 months ending in Oct 2015 and increased 1.9 percent in the 12 months ending in Nov 2015. Real hourly earnings increased 1.8 percent in the 12 months ending in Dec 2015 and increased 1.1 percent in the 12 months ending in Jan 2016. Real hourly earnings increased 0.8 percent in the 12 months ending in Feb 2016 and increased 0.9 percent in the 12 months ending in Mar 2016. Real hourly earnings increased 1.5 percent in the 12 months ending in Apr 2016 and increased 2.2 percent in the 12 months ending in May 2016. Real hourly earnings increased 1.6 percent in the 12 months ending in Jun 2016 and increased 2.0 percent in the 12 months ending in Jul 2016. Real hourly earnings increased 0.8 percent in the 12 months ending in Aug 2016 and increased 1.3 percent in the 12 months ending in Sep 2016. Real hourly earnings increased 2.0 percent in the 12 months ending in Oct 2016 and increased 0.2 percent in the 12 months ending in Nov 2016. Real hourly earnings increased 0.6 percent in the 12 months ending in Dec 2016 and increased 0.8 percent in the 12 months ending in Jan 2017. Real hourly earnings increased 0.1 percent in the 12 months ending in Feb 2017 and increased 0.2 percent in the 12 months ending in Mar 2017. Real hourly earnings increased 1.0 percent in the 12 months ending in Apr 2017 and decreased 0.1 percent in the 12 months ending in May 2017. Real hourly earnings increased 0.9 percent in the 12 months ending in Jun 2017 and increased 1.6 percent in the 12 months ending in Jul 2017. Real hourly earnings increased 0.7 percent in the 12 months ending in Aug 2017 and increased 0.7 percent in the 12 months ending in Sep 2017. Real hourly earnings increased 0.3 percent in the 12 months ending in Oct 2017 and increased 0.2 percent in the 12 months ending in Nov 2017. Real hourly earnings are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (https://cmpassocregulationblog.blogspot.com/2017/12/fomc-increases-interest-rates-with.html) and in part because of the collapse of hiring (https://cmpassocregulationblog.blogspot.com/2017/12/fomc-increases-interest-rates-with.html) originating in weak economic growth (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available in the release for Jan 2016 and subsequent releases.

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

AHE ALL

12 Month-
Nominal
∆%

∆% 12 Month CPI

12-Month
Real ∆%

2007

Jan*

$20.69*

4.2*

2.1

2.1*

Feb*

$20.78*

4.1*

2.4

1.7*

Mar

$20.75

3.4

2.8

0.6

Apr

$20.99

3.1

2.6

0.5

May

$20.77

3.5

2.7

0.8

Jun

$20.77

3.6

2.7

0.9

Jul

$20.94

3.3

2.4

0.9

Aug

$20.80

3.3

2.0

1.3

Sep

$21.13

3.8

2.8

1.0

Oct

$21.01

2.4

3.5

-1.1

Nov

$21.07

3.1

4.3

-1.2

Dec

$21.30

3.4

4.1

-0.7

2010

Jan

$22.51

2.1

2.6

-0.5

Feb

$22.57

1.6

2.1

-0.5

Mar

$22.48

1.2

2.3

-1.1

Apr

$22.53

1.8

2.2

-0.4

May

$22.60

2.5

2.0

0.5

Jun

$22.34

1.7

1.1

0.6

Jul

$22.41

1.9

1.2

0.7

Aug

$22.55

1.8

1.1

0.7

Sep

$22.60

1.8

1.1

0.7

Oct

$22.70

1.9

1.2

0.7

Nov

$22.69

1.1

1.1

0.0

Dec

$22.76

1.7

1.5

0.2

2011

Jan

$23.16

2.9

1.6

1.3

Feb

$22.99

1.9

2.1

-0.2

Mar

$22.90

1.9

2.7

-0.8

Apr

$22.96

1.9

3.2

-1.3

May

$23.06

2.0

3.6

-1.5

Jun

$22.81

2.1

3.6

-1.4

Jul

$22.94

2.4

3.6

-1.2

Aug

$22.85

1.3

3.8

-2.4

Sep

$23.05

2.0

3.9

-1.8

Oct

$23.30

2.6

3.5

-0.9

Nov

$23.15

2.0

3.4

-1.4

Dec

$23.22

2.0

3.0

-1.0

2012

Jan

$23.56

1.7

2.9

-1.2

Feb

$23.40

1.8

2.9

-1.1

Mar

$23.39

2.1

2.7

-0.6

Apr

$23.61

2.8

2.3

0.5

May

$23.32

1.1

1.7

-0.6

Jun

$23.27

2.0

1.7

0.3

Jul

$23.48

2.4

1.4

1.0

Aug

$23.26

1.8

1.7

0.1

Sep

$23.67

2.7

2.0

0.7

Oct

$23.52

0.9

2.2

-1.3

Nov

$23.58

1.9

1.8

0.1

Dec

$23.85

2.7

1.7

1.0

2013

Jan

$23.88

1.4

1.6

-0.2

Feb

$23.90

2.1

2.0

0.2

Mar

$23.84

1.9

1.5

0.4

Apr

$23.92

1.3

1.1

0.2

May

$23.80

2.1

1.4

0.7

Jun

$23.92

2.8

1.8

1.0

Jul

$23.81

1.4

2.0

-0.6

Aug

$23.80

2.3

1.5

0.8

Sep

$24.16

2.1

1.2

0.9

Oct

$24.04

2.2

1.0

1.2

Nov

$24.11

2.2

1.2

1.0

Dec

$24.30

1.9

1.5

0.4

2014

Jan

$24.35

2.0

1.6

0.4

Feb

$24.58

2.8

1.1

1.7

Mar

$24.50

2.8

1.5

1.3

Apr

$24.40

2.0

2.0

0.0

May

$24.30

2.1

2.1

0.0

Jun

$24.42

2.1

2.1

0.0

Jul

$24.31

2.1

2.0

0.1

Aug

$24.32

2.2

1.7

0.5

Sep

$24.50

1.4

1.7

-0.3

Oct

$24.52

2.0

1.7

0.3

Nov

$24.78

2.8

1.3

1.5

Dec

$24.59

1.2

0.8

0.4

2015

Jan

$24.88

2.2

-0.1

2.3

Feb

$25.05

1.9

0.0

1.9

Mar

$25.04

2.2

-0.1

2.3

Apr

$24.94

2.2

-0.2

2.4

May

$24.88

2.4

0.0

2.4

Jun

$24.77

1.4

0.1

1.3

Jul

$24.83

2.1

0.2

1.9

Aug

$25.04

3.0

0.2

2.8

Sep

$25.05

2.2

0.0

2.2

Oct

$25.14

2.5

0.2

2.3

Nov

$25.38

2.4

0.5

1.9

Dec

$25.21

2.5

0.7

1.8

2016

Jan

$25.50

2.5

1.4

1.1

Feb

$25.49

1.8

1.0

0.8

Mar

$25.49

1.8

0.9

0.9

Apr

$25.60

2.6

1.1

1.5

May

$25.68

3.2

1.0

2.2

Jun

$25.42

2.6

1.0

1.6

Jul

$25.53

2.8

0.8

2.0

Aug

$25.52

1.9

1.1

0.8

Sep

$25.74

2.8

1.5

1.3

Oct

$26.04

3.6

1.6

2.0

Nov

$25.87

1.9

1.7

0.2

Dec

$25.90

2.7

2.1

0.6

2017

Jan

$26.34

3.3

2.5

0.8

Feb

$26.20

2.8

2.7

0.1

Mar

$26.15

2.6

2.4

0.2

Apr

$26.43

3.2

2.2

1.0

May

$26.15

1.8

1.9

-0.1

Jun

$26.05

2.5

1.6

0.9

Jul

$26.37

3.3

1.7

1.6

Aug

$26.19

2.6

1.9

0.7

Sep

$26.48

2.9

2.2

0.7

Oct

$26.64

2.3

2.0

0.3

Nov

$26.48

2.4

2.2

0.2

Dec

$26.58

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

http://www.bls.gov/

Calculations of inflation-adjusted average hourly earnings by the BLS are in Table IB-4. Average hourly earnings rose above inflation throughout the first nine months of 2007 just before the global recession that began in the final quarter of 2007 when average hourly earnings began to lose to inflation. In contrast, average hourly earnings of all US workers have risen less than inflation in five months in 2010 and in all but the first month in 2011 and the loss accelerated at 1.8 percent in Sep 2011, declining to a real loss of 1.1 percent in Feb 2012 and 0.5 percent in Mar 2012. There was a gain of 0.5 percent in Apr 2012 in inflation-adjusted average hourly earnings but another fall of 0.6 percent in May 2012 followed by increases of 0.3 percent in Jun and 1.0 percent in Jul 2012. Real hourly earnings stagnated in the 12 months ending in Aug 2012 with increase of only 0.1 percent, and increased 0.7 percent in the 12 months ending in Sep 2012. Real hourly earnings fell 1.2 percent in Oct 2012 and gained 1.0 percent in Dec 2012 but declined 0.2 percent in Jan 2013 and stagnated at change of 0.1 percent in Feb 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Mar 2013 and 0.3 percent in Apr 2013, increasing 0.7 percent in May 2013. In Jun 2013, real hourly earnings increased 1.0 percent relative to Jun 2012. Real hourly earnings fell 0.6 percent in the 12 months ending in Jul 2013 and increased 0.8 percent in the 12 months ending in Aug 2013. Real hourly earnings increased 1.2 percent in the 12 months ending in Oct 2013 and 1.0 percent in Nov 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Dec 2013. Real hourly earnings increased 0.4 percent in the 12 months ending in Jan 2014 and 1.7 percent in the 12 months ending in Feb 2014. Real hourly earnings increased 1.3 percent in the 12 months ending in Mar 2014. Real hourly changed 0.0 percent in the 12 months ending in Apr 2014. Real hourly decreased 0.1 percent in the 12 months ending in May 2014. Real hourly earnings increased 0.1 percent in the 12 months ending in Jun 2014. Real hourly earnings increased 0.1 percent in the 12 months ending in Jul 2014 and increased 0.4 percent in the 12 months ending in Aug 2014. Real hourly earnings fell 0.3 percent in the 12 months ending in Sep 2014 and increased 0.4 percent in the 12 months ending in Oct 2014. Real hourly earnings increased 1.5 percent in the 12 months ending in Nov 2014 and 0.4 percent in the 12 months ending in Dec 2014. Real hourly earnings increased 2.3 percent in the 12 months ending in Jan 2015 and increased 1.9 percent in the 12 months ending in Feb 2015. Real hourly earnings increased 2.2 percent in the 12 months ending in Mar 2015 and increased 2.4 percent in the 12 months ending in Apr 2015. Real hourly earnings increased 2.4 percent in the 12 months ending in May 2015 and 1.3 percent in the 12 months ending in Jun 2015. Real hourly earnings increased 2.0 percent in the 12 months ending in Jul 2015 and increased 2.8 percent in the 12 months ending in Aug 2015. Real hourly earnings increased 2.3 percent in the 12 months ending in Sep 2015. Real hourly earnings increased 2.3 percent in the 12 months ending in Oct 2015 and increased 1.9 percent in the 12 months ending in Nov 2015. Average hourly earnings increased 1.8 percent in the 12 months ending in Dec 2015 and increased 1.0 percent in the 12 months ending in Jan 2016. Real hourly earnings increased 0.7 percent in the 12 months ending in Feb 2016 and increased 0.9 percent in the 12 months ending in Mar 2016. Real hourly earnings increased 1.5 percent in the 12 months ending in Apr 2016 and increased 2.2 percent in the 12 months ending in May 2016. Real hourly earnings increased 1.6 percent in the 12 months ending in Jun 2016 and increased 2.0 percent in the 12 months ending in Jul 2016. Real hourly earnings increased 0.9 percent in the 12 months ending in Aug 2016 and increased 1.2 percent in the 12 months ending in Sep 2016. Real hourly earnings increased 1.9 percent in the 12 months ending in Oct 2016 and increased 0.3 percent in the 12 months ending in Nov 2016. Real hourly earnings increased 0.7 percent in the 12 months ending in Dec 2016 and increased 0.8 percent in the 12 months ending in Jan 2017.

Real hourly earnings increased 0.1 percent in the 12 months ending in Feb 2017 and increased 0.3 percent in the 12 months ending in Mar 2017. Real hourly earnings increased 1.0 percent in the 12 months ending in Apr 2017 and changed 0.0 percent in the 12 months ending in May 2017. Real hourly earnings increased 0.8 percent in the 12 months ending in Jun 2017 and increased 1.5 percent in the 12 months ending in Jul 2017. Real hourly earnings increased 0.7 percent in the 12 months ending in Aug 2017 and increased 0.7 percent in the 12 months ending in Sep 2017. Real hourly earnings increased 0.3 percent in the 12 months ending in Oct 2017 and increased 0.2 percent in the 12 months ending in Nov 2017. Real hourly earnings of US workers are crawling in a fractured labor market. The economic welfare or wellbeing of United States workers deteriorated in a recovery without hiring (https://cmpassocregulationblog.blogspot.com/2017/12/fomc-increases-interest-rates-with.html), stagnating/declining real wages and 22.6 million unemployed or underemployed (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html) because of mediocre economic growth (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.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

Jul

Aug

Sep

Oct

Nov

Dec

2006

9.97

9.87

10.03

10.16

10.14

10.21

2007

10.05

10.00

10.13

10.06

10.02

10.14

2008

9.75

9.81

9.91

10.03

10.34

10.45

2009

10.22

10.27

10.28

10.30

10.37

10.36

2010

10.28

10.33

10.35

10.38

10.37

10.38

2011

10.15

10.09

10.16

10.29

10.23

10.29

2012

10.25

10.10

10.23

10.17

10.24

10.39

∆%12M

1.0

0.1

0.7

-1.2

0.1

1.0

2013

10.19

10.18

10.32

10.29

10.34

10.43

∆%12M

-0.6

0.8

0.9

1.2

1.0

0.4

2014

10.20

10.22

10.29

10.33

10.49

10.47

∆%12M

0.1

0.4

-0.3

0.4

1.5

0.4

2015

10.40

10.51

10.53

10.57

10.69

10.66

∆%12M

2.0

2.8

2.3

2.3

1.9

1.8

2016

10.61

10.60

10.66

10.77

10.72

10.73

∆%12M

2.0

0.9

1.2

1.9

0.3

0.7

2017

10.77

10.67

10.73

10.80

10.74

∆%12M

1.5

0.7

0.7

0.3

0.2

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart IB-2 of the US Bureau of Labor Statistics plots average hourly earnings of all US employees in constant 1982-1984 dollars with evident decline from annual earnings of $10.33 in 2009 and $10.35 in 2010 to $10.24 in 2011 and $10.23 in 2012 or loss of 1.0 percent (data in http://www.bls.gov/data/). Annual real hourly earnings increased 0.6 percent in 2013 relative to 2012 and increased 0.5 percent in 2014 relative to 2013. Annual real hourly earnings increased 2.1 percent in 2015 relative to 2014. Annual real hourly earnings increased 1.2 percent in 2016 relative to 2015. Annual real hourly earnings increased 5.9 percent from 2007 to 2016 at the rate of 0.6 percent per year. Annual real hourly earnings increased 3.5 percent from 2009 to 2016 at the rate of 0.5 percent per year and increased 6.8 percent from 2008 to 2016 at the rate of 0.8 percent per year. Real hourly earnings of US workers are crawling in a fractured labor market. The economic welfare or wellbeing of United States workers deteriorated in a recovery without hiring (https://cmpassocregulationblog.blogspot.com/2017/12/fomc-increases-interest-rates-with.html), stagnating/declining real wages and 22.6 million unemployed or underemployed (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html) because of mediocre economic growth (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html). The BLS is revising the data from 2006 to 2009 (http://www.bls.gov/ces/#notices) now available for the release of Jan 2016 and subsequent releases.

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

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

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

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

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

Average weekly earnings of the dataset of the US Bureau of Labor Statistics (BLS) are in Table IB-5. Average weekly earnings fell 3.2 percent after adjusting for inflation in the 12 months ending in Aug 2011, decreased 0.9 percent in the 12 months ending in Sep 2011 and increased 0.6 percent in the 12 months ending in Oct 2011. Average weekly earnings fell 1.0 percent in the 12 months ending in Nov 2011 and fell 0.3 percent in the 12 months ending in Dec 2011. Average weekly earnings declined 0.3 percent in the 12 months ending in Jan 2012 and fell 0.5 percent in the 12 months ending in Feb 2012. Average weekly earnings in constant dollars were virtually flat in Mar 2012 relative to Mar 2011, decreasing 0.2 percent. Average weekly earnings in constant dollars increased 1.7 percent in Apr 2012 relative to Apr 2011 but fell 1.7 percent in May 2012 relative to May 2011, increasing 0.6 percent in the 12 months ending in Jun 2012 and 1.8 percent in the 12 months ending in Jul 2012. Real weekly earnings increased 0.4 percent in the 12 months ending in Aug 2012 and 1.9 percent in the 12 months ending in Sep 2012. Real weekly earnings fell 2.6 percent in the 12 months ending in Oct 2012 and increased 0.1 percent in the 12 months ending in Nov 2012 and 2.1 percent in the 12 months ending in Dec 2012. Real weekly earnings fell 1.7 percent in the 12 months ending in Jan 2013 and virtually stagnated with gain of 0.2 percent in the 12 months ending in Feb 2013, increasing 0.7 percent in the 12 months ending in Mar 2013. Real weekly earnings fell 0.6 percent in the 12 months ending in Apr 2013 and increased 1.0 percent in the 12 months ending in May 2013. Average weekly earnings increased 2.5 percent in the 12 months ending in Jun 2013 and fell 1.7 percent in the 12 months ending in Jul 2013. Real weekly earnings increased 0.8 percent in the 12 months ending in Aug 2013, 1.2 percent in the 12 months ending in Sep 2013 and 1.5 percent in the 12 months ending in Oct 2013. Average weekly earnings increased 1.3 percent in the 12 months ending in Nov 2013 and increased 0.1 percent in the 12 months ending in Dec 2013. Average weekly earnings increased 0.4 percent in the 12 months ending in Jan 2014 and 2.3 percent in the 12 months ending in Feb 2014. Average weekly earnings increased 2.4 percent in the 12 months ending in Mar 2014 and 0.3 percent in the 12 months ending in Apr 2014. Average weekly earnings in constant dollars increased 0.3 percent in the 12 months ending in May 2014 and changed 0.0 percent in the 12 months ending in Jun 2014. Real average weekly earnings increased 0.7 percent in the 12 months ending in Jul 2014 and 0.8 percent in the 12 months ending in Aug 2014. Real weekly earnings decreased 1.4 percent in the 12 months ending in Sep 2014 and increased 0.6 percent in the 12 months ending in Oct 2014. Average weekly earnings increased 2.9 percent in the 12 months ending in Nov 2014 and increased 0.1 percent in the 12 months ending in Dec 2014. Average weekly earnings increased 2.9 percent in the 12 months ending in Jan 2015 and increased 2.5 percent in the 12 months ending in Feb 2015. Average weekly earnings adjusted for inflation increased 2.3 percent in the 12 months ending in Mar 2015 and increased 2.4 percent in the 12 months ending in Apr 2015. Average weekly earnings adjusted for inflation increased 2.4 percent in the 12 months ending in May 2015 and increased 0.1 percent in the 12 months ending in Jun 2015. Average weekly earnings increased 2.0 percent in the 12 months ending in Jul 2015 and 4.2 percent in the 12 months ending in Aug 2015. Average weekly earnings adjusted for inflation increased 1.7 percent in the 12 months ending in Sep 2015 and increased 2.4 percent in the 12 months ending in Oct 2015. Average weekly earnings adjusted for inflation increased 1.6 percent in the 12 months ending in Nov 2015 and increased 1.5 percent in the 12 months ending in Dec 2015. Average weekly earnings increased 1.1 percent in the 12 months ending in Jan 2016. Average weekly earnings contracted 0.7 percent in the 12 months ending in Feb 2015 and contracted 0.5 percent in the 12 months ending in Mar 2016. Average weekly earnings increased 1.2 percent in the 12 months ending in Apr 2016 and increased 2.8 percent in the 12 months ending in May 2016. Average weekly earnings increased 1.3 percent in the 12 months ending in Jun 2016 and increased 1.7 percent in the 12 months ending in Jul 2016. Average weekly earnings decreased 1.2 percent in the 12 months ending in Aug 2016 and increased 1.6 percent in the 12 months ending in Sep 2016. Average weekly earnings increased 2.8 percent in the 12 months ending in Oct 2016 and decreased 1.2 percent in the 12 months ending in Nov 2016. Average weekly earnings increased 0.1 percent in the 12 months ending in Dec 2016 and increased 1.4 percent in the 12 months ending in Jan 2017. Average weekly earnings changed 0.0 percent in the 12 months ending in Feb 2017. Average weekly earnings decreased 0.1 percent in the 12 months ending in Mar 2017 and increased 1.9 percent in the 12 months ending in Apr 2017. Average weekly earnings decreased 0.9 percent in the 12 months ending in May 2017 and increased 1.1 percent in the 12 months ending in Jun 2017. Average weekly earnings increased 2.7 percent in the 12 months ending in Jul 2017 and increased 1.0 percent in the 12 months ending in Aug 2017. Average weekly earnings increased 0.3 percent in the 12 months ending in Sep 2017 and increased 0.3 percent in the 12 months ending in Oct 2017. Average weekly earnings increased 0.4 percent in the 12 months ending in Nov 2017. Table I-5 confirms the trend of deterioration of purchasing power of average weekly earnings in 2011 and into 2013 with oscillations according to carry trades causing world inflation waves (ttps://cmpassocregulationblog.blogspot.com/2017/10/world-inflation-waves-long-term-and.html). On an annual basis, average weekly earnings in constant 1982-1984 dollars increased from $347.17 in 2007 to $354.15 in 2013, by 2.0 percent or at the average rate of 0.3 percent per year (data in http://www.bls.gov/data/). Annual average weekly earnings in constant dollars of $352.95 in 2010 fell 0.4 percent to $351.67 in 2011. Annual average weekly earnings increased from $347.17 in 2007 to $356.90 in 2014 or by 2.8 at the average rate of 0.4 percent. Annual average weekly earnings in constant dollars increased from $347.17 in 2007 to $364.62 in 2015 by 5.0 percent at the average rate of 0.6 percent per year. Annual average weekly earnings in constant dollar increased from $347.17 in 2007 to $367.30 in 2016 by 5.8 percent at the average rate of 0.6 percent per year. Those who still work bring back home a paycheck that buys fewer high-quality goods than a year earlier. The fractured US job market does not provide an opportunity for advancement as in past booms following recessions because of poor job creation with 22.6 million unemployed or underemployed (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html) because of mediocre economic growth (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.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.

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

Year

Sep

Oct

Nov

Dec

2006

344.02

352.68

347.94

351.16

2007

352.69

344.91

343.85

352.91

2008

338.90

342.99

355.78

354.11

2009

346.41

348.20

354.76

350.29

2010

352.80

356.00

354.66

355.14

2011

349.47

358.11

350.99

353.95

2012

355.96

348.76

351.31

361.49

∆%12M

1.9

-2.6

0.1

2.1

2013

360.10

354.10

355.85

361.82

∆%12M

1.2

1.5

1.3

0.1

2014

355.10

356.29

366.21

362.34

∆%12M

-1.4

0.6

2.9

0.1

2015

361.10

364.67

372.14

367.72

∆%12M

1.7

2.4

1.6

1.5

2016

366.76

374.88

367.65

367.96

∆%12M

1.6

2.8

-1.2

0.1

2017

367.99

375.84

369.28

∆%12M

0.3

0.3

0.4

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

tistics http://www.bls.gov/

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

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

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

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

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

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

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

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

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

IA Unconventional Monetary Policy and Valuations of Risk Financial Assets. Unconventional monetary policy since 2003 has consisted of near zero nominal interest rates, negative real rates of interest, massive purchases of securities for the balance sheet of the Fed and intervention in allocation of credit. Professor John B. Taylor (2016Dec 7, 2016Dec20), in Testimony to the Subcommittee on Monetary Policy and Trade Committee on Financial Services, on Dec 7, 2016, analyzes the adverse effects of unconventional monetary policy:

“My research and that of others over the years shows that these policies were not effective, and may have been counterproductive. Economic growth was consistently below the Fed’s forecasts with the policies, and was much weaker than in earlier U.S. recoveries from deep recessions. Job growth has been insufficient to raise the percentage of the population that is working above pre-recession levels. There is a growing consensus that the extra low interest rates and unconventional monetary policy have reached diminishing or negative returns. Many have argued that these policies widen the income distribution, adversely affect savers, and increase the volatility of the dollar exchange rate. Experienced market participants have expressed concerns about bubbles, imbalances, and distortions caused by the policies. The unconventional policies have also raised public policy concerns about the Fed being transformed into a multipurpose institution, intervening in particular sectors and allocating credit, areas where Congress may have a role, but not a limited-purpose independent agency of government.”

A counterfactual consists of theory and measurements of what would have occurred otherwise if economic policies or institutional arrangements had been different. This task is quite difficult because economic data are observed with all effects as they actually occurred while the counterfactual attempts to evaluate how data would differ had policies and institutional arrangements been different (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008b), 125, 136; Pelaez 1979, 26-8). Counterfactual data are unobserved and must be calculated using theory and measurement methods. The measurement of costs and benefits of projects or applied welfare economics (Harberger 1971, 1997) specifies and attempts to measure projects such as what would be economic welfare with or without a bridge or whether markets would be more or less competitive in the absence of antitrust and regulation laws (Winston 2006). The “new economic history” of the United States used counterfactuals to measure the economy with or without railroads (Fishlow 1965, Fogel 1964) and in analyzing slavery (Fogel and Engerman 1974). A critical counterfactual in economic history is how Britain surged ahead of France (North and Weingast 1989). There is similarly path-breaking research on railroads in Latin America by Coastworth (1981) and Summerhill (1997, 1998, 2003). Coastworth (2006, 176) argues that: “We already have so many history books that tells us so much about what really occurred in the past, that what we need now are books about what did not happen—but might have, or perhaps even should have happened: Counterfactual History, that is, history that is contrary to fact.”

The counterfactual of avoidance of deeper and more prolonged contraction by fiscal and monetary policies is not the critical issue. As Professor John B. Taylor (2012Oct25) argues, the critically important counterfactual is that the financial crisis and global recession would have not occurred in the first place if different economic policies had been followed. The counterfactual intends to verify that a combination of housing policies and discretionary monetary policies instead of rules (Taylor 1993) caused, deepened and prolonged the financial crisis (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/; see http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). The experience resembles that of the Great Inflation of the 1960s and 1970s with stop-and-go growth/inflation that coined the term stagflation (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I).

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 2.2 percent on average in the cyclical expansion in the 33 quarters from IIIQ2009 to IIIQ2017. 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 IIIQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp3q17_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 dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2835.2 billion than actual $17,163.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.3 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,163.9 billion in IIIQ2017 or 14.5 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 146.5098 in Nov 2017. The actual index NSA in Nov 2017 is 104.6305, which is 28.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Nov 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.7256 in Nov 2017. The output of manufacturing at 104.6305 in Nov 2017 is 20.6 percent below trend under this alternative calculation.

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

and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/exchange-rate-conflicts-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/imf-view-squeeze-of-economic-activity.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html)

Valuations of risk financial assets have reached extremely high levels in markets with fluctuating volumes. For example, the DJIA has increased 105.3 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Jan 13, 2016; S&P 500 has gained 122.4 percent and DAX 105.1 percent. The overwhelming risk factor is the unsustainable Treasury deficit/debt of the United States (http://cmpassocregulationblog.blogspot.com/2017/01/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/12/rising-yields-and-dollar-revaluation.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/unresolved-us-balance-of-payments.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-reducing.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/weakening-equities-and-dollar.html). A competing event is the high level of valuations of risk financial assets (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/01/unconventional-monetary-policy-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/peaking-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/theory-and-reality-of-secular.html). Matt Jarzemsky, writing on “Dow industrials set record,” on Mar 5, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324156204578275560657416332.html), analyzes that the DJIA broke the closing high of 14,164.53 set on Oct 9, 2007, and subsequently also broke the intraday high of 14,198.10 reached on Oct 11, 2007. The DJIA closed at 19,885.73 on Jan 13, 2017, which is higher by 40.4 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 40.1 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial assets have been approaching or exceeding historical highs.

The financial crisis and global recession were caused by interest rate and housing subsidies and affordability policies that encouraged high leverage and risks, low liquidity and unsound credit (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). Several past comments of this blog elaborate on these arguments, among which: 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

Table VI-1 shows the phenomenal impulse to valuations of risk financial assets originating in the initial shock of near zero interest rates in 2003-2004 with the fed funds rate at 1 percent, in fear of deflation that never materialized, and quantitative easing in the form of suspension of the auction of 30-year Treasury bonds to lower mortgage rates. World financial markets were dominated by monetary and housing policies in the US. Between 2002 and 2008, the DJ UBS Commodity Index rose 165.5 percent largely because of unconventional monetary policy encouraging carry trades from low US interest rates to long leveraged positions in commodities, exchange rates and other risk financial assets. The charts of risk financial assets show sharp increase in valuations leading to the financial crisis and then profound drops that are captured in Table VI-1 by percentage changes of peaks and troughs. The first round of quantitative easing and near zero interest rates depreciated the dollar relative to the euro by 39.3 percent between 2003 and 2008, with revaluation of the dollar by 25.1 percent from 2008 to 2010 in the flight to dollar-denominated assets in fear of world financial risks. The dollar devalued 0.9 percent by Fri Jan 5, 2018. Dollar devaluation is a major vehicle of monetary policy in reducing the output gap that is implemented in the probably erroneous belief that devaluation will not accelerate inflation, misallocating resources toward less productive economic activities and disrupting financial markets. The last row of Table VI-1 shows CPI inflation in the US rising from 1.9 percent in 2003 to 4.1 percent in 2007 even as monetary policy increased the fed funds rate from 1 percent in Jun 2004 to 5.25 percent in Jun 2006.

Table VI-1, Volatility of Assets

DJIA

10/08/02-10/01/07

10/01/07-3/4/09

3/4/09- 4/6/10

∆%

87.8

-51.2

60.3

NYSE Financial

1/15/04- 6/13/07

6/13/07- 3/4/09

3/4/09- 4/16/07

∆%

42.3

-75.9

121.1

Shanghai Composite

6/10/05- 10/15/07

10/15/07- 10/30/08

10/30/08- 7/30/09

∆%

444.2

-70.8

85.3

STOXX EUROPE 50

3/10/03- 7/25/07

7/25/07- 3/9/09

3/9/09- 4/21/10

∆%

93.5

-57.9

64.3

UBS Com.

1/23/02- 7/1/08

7/1/08- 2/23/09

2/23/09- 1/6/10

∆%

165.5

-56.4

41.4

10-Year Treasury

6/10/03

6/12/07

12/31/08

4/5/10

%

3.112

5.297

2.247

3.986

USD/EUR

6/26/03

7/14/08

6/07/10

01/05/2018

Rate

1.1423

1.5914

1.192

1.2032

CNY/USD

01/03
2000

07/21
2005

7/15
2008

01/05/

2018

Rate

8.2798

8.2765

6.8211

6.4891

New House

1963

1977

2005

2009

Sales 1000s

560

819

1283

375

New House

2000

2007

2009

2010

Median Price $1000

169

247

217

222

2003

2005

2007

2010

CPI

2.3

3.4

2.8

1.6

Sources: http://professional.wsj.com/mdc/page/marketsdata.html?mod=WSJ_hps_marketdata

http://www.census.gov/const/www/newressalesindex_excel.html

http://federalreserve.gov/releases/h10/Hist/dat00_eu.htm

There are collateral effects of unconventional monetary policy. Chart VIII-1 of the Board of Governors of the Federal Reserve System provides the rate on the overnight fed funds rate and the yields of the 10-year constant maturity Treasury and the Baa seasoned corporate bond. Table VIII-3 provides the data for selected points in Chart VIII-1. There are two important economic and financial events, illustrating the ease of inducing carry trade with extremely low interest rates and the resulting financial crash and recession of abandoning extremely low interest rates.

  • The Federal Open Market Committee (FOMC) lowered the target of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85). Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment. The exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV). The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever-increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity by the penalty in the form of low interest rates and unsound credit decisions. The put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4). The FOMC implemented increments of 25 basis points of the fed funds target from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006, as shown in Chart VIII-1. The gradual exit from the first round of unconventional monetary policy from 1.00 percent in Jun 2004 (http://www.federalreserve.gov/boarddocs/press/monetary/2004/20040630/default.htm) to 5.25 percent in Jun 2006 (http://www.federalreserve.gov/newsevents/press/monetary/20060629a.htm) caused the financial crisis and global recession.
  • On Dec 16, 2008, the policy determining committee of the Fed decided (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm): “The Federal Open Market Committee decided today to establish a target range for the federal funds rate of 0 to 1/4 percent.” Policymakers emphasize frequently that there are tools to exit unconventional monetary policy at the right time. At the confirmation hearing on nomination for Chair of the Board of Governors of the Federal Reserve System, Vice Chair Yellen (2013Nov14 http://www.federalreserve.gov/newsevents/testimony/yellen20131114a.htm), states that: “The Federal Reserve is using its monetary policy tools to promote a more robust recovery. A strong recovery will ultimately enable the Fed to reduce its monetary accommodation and reliance on unconventional policy tools such as asset purchases. I believe that supporting the recovery today is the surest path to returning to a more normal approach to monetary policy.” Perception of withdrawal of $2671 billion, or $2.7 trillion, of bank reserves (http://www.federalreserve.gov/releases/h41/current/h41.htm#h41tab1), would cause Himalayan increase in interest rates that would provoke another recession. There is no painless gradual or sudden exit from zero interest rates because reversal of exposures created on the commitment of zero interest rates forever.

In his classic restatement of the Keynesian demand function in terms of “liquidity preference as behavior toward risk,” James Tobin (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/1981/tobin-bio.html) identifies the risks of low interest rates in terms of portfolio allocation (Tobin 1958, 86):

“The assumption that investors expect on balance no change in the rate of interest has been adopted for the theoretical reasons explained in section 2.6 rather than for reasons of realism. Clearly investors do form expectations of changes in interest rates and differ from each other in their expectations. For the purposes of dynamic theory and of analysis of specific market situations, the theories of sections 2 and 3 are complementary rather than competitive. The formal apparatus of section 3 will serve just as well for a non-zero expected capital gain or loss as for a zero expected value of g. Stickiness of interest rate expectations would mean that the expected value of g is a function of the rate of interest r, going down when r goes down and rising when r goes up. In addition to the rotation of the opportunity locus due to a change in r itself, there would be a further rotation in the same direction due to the accompanying change in the expected capital gain or loss. At low interest rates expectation of capital loss may push the opportunity locus into the negative quadrant, so that the optimal position is clearly no consols, all cash. At the other extreme, expectation of capital gain at high interest rates would increase sharply the slope of the opportunity locus and the frequency of no cash, all consols positions, like that of Figure 3.3. The stickier the investor's expectations, the more sensitive his demand for cash will be to changes in the rate of interest (emphasis added).”

Tobin (1969) provides more elegant, complete analysis of portfolio allocation in a general equilibrium model. The major point is equally clear in a portfolio consisting of only cash balances and a perpetuity or consol. Let g be the capital gain, r the rate of interest on the consol and re the expected rate of interest. The rates are expressed as proportions. The price of the consol is the inverse of the interest rate, (1+re). Thus, g = [(r/re) – 1]. The critical analysis of Tobin is that at extremely low interest rates there is only expectation of interest rate increases, that is, dre>0, such that there is expectation of capital losses on the consol, dg<0. Investors move into positions combining only cash and no consols. Valuations of risk financial assets would collapse in reversal of long positions in carry trades with short exposures in a flight to cash. There is no exit from a central bank created liquidity trap without risks of financial crash and another global recession. The net worth of the economy depends on interest rates. In theory, “income is generally defined as the amount a consumer unit could consume (or believe that it could) while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is a flow that is obtained by applying a rate of return, r, to a stock of wealth, W, or Y = rW (Friedman 1957). According to a subsequent statement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption is the long-run expected yield from wealth r*W. This yield was named permanent income: Y* = r*W” (Darby 1974, 229), where * denotes permanent. The simplified relation of income and wealth can be restated as:

W = Y/r (1)

Equation (1) shows that as r goes to zero, r→0, W grows without bound, W→∞. Unconventional monetary policy lowers interest rates to increase the present value of cash flows derived from projects of firms, creating the impression of long-term increase in net worth. An attempt to reverse unconventional monetary policy necessarily causes increases in interest rates, creating the opposite perception of declining net worth. As r→∞, W = Y/r →0. There is no exit from unconventional monetary policy without increasing interest rates with resulting pain of financial crisis and adverse effects on production, investment and employment.

Dan Strumpf and Pedro Nicolaci da Costa, writing on “Fed’s Yellen: Stock Valuations ‘Generally are Quite High,’” on May 6, 2015, published in the Wall Street Journal (http://www.wsj.com/articles/feds-yellen-cites-progress-on-bank-regulation-1430918155?tesla=y ), quote Chair Yellen at open conversation with Christine Lagarde, Managing Director of the IMF, finding “equity-market valuations” as “quite high” with “potential dangers” in bond valuations. The DJIA fell 0.5 percent on May 6, 2015, after the comments and then increased 0.5 percent on May 7, 2015 and 1.5 percent on May 8, 2015.

Fri May 1

Mon 4

Tue 5

Wed 6

Thu 7

Fri 8

DJIA

18024.06

-0.3%

1.0%

18070.40

0.3%

0.3%

17928.20

-0.5%

-0.8%

17841.98

-1.0%

-0.5%

17924.06

-0.6%

0.5%

18191.11

0.9%

1.5%

There are two approaches in theory considered by Bordo (2012Nov20) and Bordo and Lane (2013). The first approach is in the classical works of Milton Friedman and Anna Jacobson Schwartz (1963a, 1987) and Karl Brunner and Allan H. Meltzer (1973). There is a similar approach in Tobin (1969). Friedman and Schwartz (1963a, 66) trace the effects of expansionary monetary policy into increasing initially financial asset prices: “It seems plausible that both nonbank and bank holders of redundant balances will turn first to securities comparable to those they have sold, say, fixed-interest coupon, low-risk obligations. But as they seek to purchase these they will tend to bid up the prices of those issues. Hence they, and also other holders not involved in the initial central bank open-market transactions, will look farther afield: the banks, to their loans; the nonbank holders, to other categories of securities-higher risk fixed-coupon obligations, equities, real property, and so forth.”

The second approach is by the Austrian School arguing that increases in asset prices can become bubbles if monetary policy allows their financing with bank credit. Professor Michael D. Bordo provides clear thought and empirical evidence on the role of “expansionary monetary policy” in inflating asset prices (Bordo2012Nov20, Bordo and Lane 2013). Bordo and Lane (2013) provide revealing narrative of historical episodes of expansionary monetary policy. Bordo and Lane (2013) conclude that policies of depressing interest rates below the target rate or growth of money above the target influences higher asset prices, using a panel of 18 OECD countries from 1920 to 2011. Bordo (2012Nov20) concludes: “that expansionary money is a significant trigger” and “central banks should follow stable monetary policies…based on well understood and credible monetary rules.” Taylor (2007, 2009) explains the housing boom and financial crisis in terms of expansionary monetary policy. Professor Martin Feldstein (2016), at Harvard University, writing on “A Federal Reserve oblivious to its effects on financial markets,” on Jan 13, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/a-federal-reserve-oblivious-to-its-effect-on-financial-markets-1452729166), analyzes how unconventional monetary policy drove values of risk financial assets to high levels. Quantitative easing and zero interest rates distorted calculation of risks with resulting vulnerabilities in financial markets.

Another hurdle of exit from zero interest rates is “competitive easing” that Professor Raghuram Rajan, governor of the Reserve Bank of India, characterizes as disguised “competitive devaluation” (http://www.centralbanking.com/central-banking-journal/interview/2358995/raghuram-rajan-on-the-dangers-of-asset-prices-policy-spillovers-and-finance-in-india). The fed has been considering increasing interest rates. The European Central Bank (ECB) announced, on Mar 5, 2015, the beginning on Mar 9, 2015 of its quantitative easing program denominated as Public Sector Purchase Program (PSPP), consisting of “combined monthly purchases of EUR 60 bn [billion] in public and private sector securities” (http://www.ecb.europa.eu/mopo/liq/html/pspp.en.html). Expectation of increasing interest rates in the US together with euro rates close to zero or negative cause revaluation of the dollar (or devaluation of the euro and of most currencies worldwide). US corporations suffer currency translation losses of their foreign transactions and investments (http://www.fasb.org/jsp/FASB/Pronouncement_C/SummaryPage&cid=900000010318) while the US becomes less competitive in world trade (Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), Government Intervention in Globalization (2008c)). The DJIA fell 1.5 percent on Mar 6, 2015 and the dollar revalued 2.2 percent from Mar 5 to Mar 6, 2015. The euro has devalued 32.2 percent relative to the dollar from the high on Jul 15, 2008 to Jan 5, 2018.

Fri 27 Feb

Mon 3/2

Tue 3/3

Wed 3/4

Thu 3/5

Fri 3/6

USD/ EUR

1.1197

1.6%

0.0%

1.1185

0.1%

0.1%

1.1176

0.2%

0.1%

1.1081

1.0%

0.9%

1.1030

1.5%

0.5%

1.0843

3.2%

1.7%

Chair Yellen explained the removal of the word “patience” from the advanced guidance at the press conference following the FOMC meeting on Mar 18, 2015 (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20150318.pdf):

“In other words, just because we removed the word “patient” from the statement doesn’t mean we are going to be impatient. Moreover, even after the initial increase in the target funds rate, our policy is likely to remain highly accommodative to support continued progress toward our objectives of maximum employment and 2 percent inflation.”

Exchange rate volatility is increasing in response of “impatience” in financial markets with monetary policy guidance and measures:

Fri Mar 6

Mon 9

Tue 10

Wed 11

Thu 12

Fri 13

USD/ EUR

1.0843

3.2%

1.7%

1.0853

-0.1%

-0.1%

1.0700

1.3%

1.4%

1.0548

2.7%

1.4%

1.0637

1.9%

-0.8%

1.0497

3.2%

1.3%

Fri Mar 13

Mon 16

Tue 17

Wed 18

Thu 19

Fri 20

USD/ EUR

1.0497

3.2%

1.3%

1.0570

-0.7%

-0.7%

1.0598

-1.0%

-0.3%

1.0864

-3.5%

-2.5%

1.0661

-1.6%

1.9%

1.0821

-3.1%

-1.5%

Fri Apr 24

Mon 27

Tue 28

Wed 29

Thu 30

May Fri 1

USD/ EUR

1.0874

-0.6%

-0.4%

1.0891

-0.2%

-0.2%

1.0983

-1.0%

-0.8%

1.1130

-2.4%

-1.3%

1.1223

-3.2%

-0.8%

1.1199

-3.0%

0.2%

In a speech at Brown University on May 22, 2015, Chair Yellen stated (http://www.federalreserve.gov/newsevents/speech/yellen20150522a.htm):

“For this reason, if the economy continues to improve as I expect, I think it will be appropriate at some point this year to take the initial step to raise the federal funds rate target and begin the process of normalizing monetary policy. To support taking this step, however, I will need to see continued improvement in labor market conditions, and I will need to be reasonably confident that inflation will move back to 2 percent over the medium term. After we begin raising the federal funds rate, I anticipate that the pace of normalization is likely to be gradual. The various headwinds that are still restraining the economy, as I said, will likely take some time to fully abate, and the pace of that improvement is highly uncertain.”

The US dollar appreciated 3.8 percent relative to the euro in the week of May 22, 2015:

Fri May 15

Mon 18

Tue 19

Wed 20

Thu 21

Fri 22

USD/ EUR

1.1449

-2.2%

-0.3%

1.1317

1.2%

1.2%

1.1150

2.6%

1.5%

1.1096

3.1%

0.5%

1.1113

2.9%

-0.2%

1.1015

3.8%

0.9%

The Managing Director of the International Monetary Fund (IMF), Christine Lagarde, warned on Jun 4, 2015, that: (http://blog-imfdirect.imf.org/2015/06/04/u-s-economy-returning-to-growth-but-pockets-of-vulnerability/):

“The Fed’s first rate increase in almost 9 years is being carefully prepared and telegraphed. Nevertheless, regardless of the timing, higher US policy rates could still result in significant market volatility with financial stability consequences that go well beyond US borders. I weighing these risks, we think there is a case for waiting to raise rates until there are more tangible signs of wage or price inflation than are currently evident. Even after the first rate increase, a gradual rise in the federal fund rates will likely be appropriate.”

The President of the European Central Bank (ECB), Mario Draghi, warned on Jun 3, 2015 that (http://www.ecb.europa.eu/press/pressconf/2015/html/is150603.en.html):

“But certainly one lesson is that we should get used to periods of higher volatility. At very low levels of interest rates, asset prices tend to show higher volatility…the Governing Council was unanimous in its assessment that we should look through these developments and maintain a steady monetary policy stance.”

The Chair of the Board of Governors of the Federal Reserve System, Janet L. Yellen, stated on Jul 10, 2015 that (http://www.federalreserve.gov/newsevents/speech/yellen20150710a.htm):

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

There is essentially the same view in the Testimony of Chair Yellen in delivering the Semiannual Monetary Policy Report to the Congress on Jul 15, 2015 (http://www.federalreserve.gov/newsevents/testimony/yellen20150715a.htm).

At the press conference after the meeting of the FOMC on Sep 17, 2015, Chair Yellen states (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20150917.pdf 4):

“The outlook abroad appears to have become more uncertain of late, and heightened concerns about growth in China and other emerging market economies have led to notable volatility in financial markets. Developments since our July meeting, including the drop in equity prices, the further appreciation of the dollar, and a widening in risk spreads, have tightened overall financial conditions to some extent. These developments may restrain U.S. economic activity somewhat and are likely to put further downward pressure on inflation in the near term. Given the significant economic and financial interconnections between the United States and the rest of the world, the situation abroad bears close watching.”

Some equity markets fell on Fri Sep 18, 2015:

Fri Sep 11

Mon 14

Tue 15

Wed 16

Thu 17

Fri 18

DJIA

16433.09

2.1%

0.6%

16370.96

-0.4%

-0.4%

16599.85

1.0%

1.4%

16739.95

1.9%

0.8%

16674.74

1.5%

-0.4%

16384.58

-0.3%

-1.7%

Nikkei 225

18264.22

2.7%

-0.2%

17965.70

-1.6%

-1.6%

18026.48

-1.3%

0.3%

18171.60

-0.5%

0.8%

18432.27

0.9%

1.4%

18070.21

-1.1%

-2.0%

DAX

10123.56

0.9%

-0.9%

10131.74

0.1%

0.1%

10188.13

0.6%

0.6%

10227.21

1.0%

0.4%

10229.58

1.0%

0.0%

9916.16

-2.0%

-3.1%

Frank H. Knight (1963, 233), in Risk, uncertainty and profit, distinguishes between measurable risk and unmeasurable uncertainty. Chair Yellen, in a lecture on “Inflation dynamics and monetary policy,” on Sep 24, 2015 (http://www.federalreserve.gov/newsevents/speech/yellen20150924a.htm), states that (emphasis added):

· “The economic outlook, of course, is highly uncertain”

· “Considerable uncertainties also surround the outlook for economic activity”

· “Given the highly uncertain nature of the outlook…”

Is there a “science” or even “art” of central banking under this extreme uncertainty in which policy does not generate higher volatility of money, income, prices and values of financial assets?

Lingling Wei, writing on Oct 23, 2015, on China’s central bank moves to spur economic growth,” published in the Wall Street Journal (http://www.wsj.com/articles/chinas-central-bank-cuts-rates-1445601495), analyzes the reduction by the People’s Bank of China (http://www.pbc.gov.cn/ http://www.pbc.gov.cn/english/130437/index.html) of borrowing and lending rates of banks by 50 basis points and reserve requirements of banks by 50 basis points. Paul Vigna, writing on Oct 23, 2015, on “Stocks rally out of correction territory on latest central bank boost,” published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2015/10/23/stocks-rally-out-of-correction-territory-on-latest-central-bank-boost/), analyzes the rally in financial markets following the statement on Oct 22, 2015, by the President of the European Central Bank (ECB) Mario Draghi of consideration of new quantitative measures in Dec 2015 (https://www.youtube.com/watch?v=0814riKW25k&rel=0) and the reduction of bank lending/deposit rates and reserve requirements of banks by the People’s Bank of China on Oct 23, 2015. The dollar revalued 2.8 percent from Oct 21 to Oct 23, 2015, following the intended easing of the European Central Bank. The DJIA rose 2.8 percent from Oct 21 to Oct 23 and the DAX index of German equities rose 5.4 percent from Oct 21 to Oct 23, 2015.

Fri Oct 16

Mon 19

Tue 20

Wed 21

Thu 22

Fri 23

USD/ EUR

1.1350

0.1%

0.3%

1.1327

0.2%

0.2%

1.1348

0.0%

-0.2%

1.1340

0.1%

0.1%

1.1110

2.1%

2.0%

1.1018

2.9%

0.8%

DJIA

17215.97

0.8%

0.4%

17230.54

0.1%

0.1%

17217.11

0.0%

-0.1%

17168.61

-0.3%

-0.3%

17489.16

1.6%

1.9%

17646.70

2.5%

0.9%

Dow Global

2421.58

0.3%

0.6%

2414.33

-0.3%

-0.3%

2411.03

-0.4%

-0.1%

2411.27

-0.4%

0.0%

2434.79

0.5%

1.0%

2458.13

1.5%

1.0%

DJ Asia Pacific

1402.31

1.1%

0.3%

1398.80

-0.3%

-0.3%

1395.06

-0.5%

-0.3%

1402.68

0.0%

0.5%

1396.03

-0.4%

-0.5%

1415.50

0.9%

1.4%

Nikkei 225

18291.80

-0.8%

1.1%

18131.23

-0.9%

-0.9%

18207.15

-0.5%

0.4%

18554.28

1.4%

1.9%

18435.87

0.8%

-0.6%

18825.30

2.9%

2.1%

Shanghai

3391.35

6.5%

1.6%

3386.70

-0.1%

-0.1%

3425.33

1.0%

1.1%

3320.68

-2.1%

-3.1%

3368.74

-0.7%

1.4%

3412.43

0.6%

1.3%

DAX

10104.43

0.1%

0.4%

10164.31

0.6%

0.6%

10147.68

0.4%

-0.2%

10238.10

1.3%

0.9%

10491.97

3.8%

2.5%

10794.54

6.8%

2.9%

Ben Leubsdorf, writing on “Fed’s Yellen: December is “Live Possibility” for First Rate Increase,” on Nov 4, 2015, published in the Wall Street Journal (http://www.wsj.com/articles/feds-yellen-december-is-live-possibility-for-first-rate-increase-1446654282) quotes Chair Yellen that a rate increase in “December would be a live possibility.” The remark of Chair Yellen was during a hearing on supervision and regulation before the Committee on Financial Services, US House of Representatives (http://www.federalreserve.gov/newsevents/testimony/yellen20151104a.htm) and a day before the release of the employment situation report for Oct 2015 (Section I). The dollar revalued 2.4 percent during the week. The euro has devalued 32.2 percent relative to the dollar from the high on Jul 15, 2008 to Jan 5, 2018.

Fri Oct 30

Mon 2

Tue 3

Wed 4

Thu 5

Fri 6

USD/ EUR

1.1007

0.1%

-0.3%

1.1016

-0.1%

-0.1%

1.0965

0.4%

0.5%

1.0867

1.3%

0.9%

1.0884

1.1%

-0.2%

1.0742

2.4%

1.3%

The release on Nov 18, 2015 of the minutes of the FOMC (Federal Open Market Committee) meeting held on Oct 28, 2015 (http://www.federalreserve.gov/monetarypolicy/fomcminutes20151028.htm) states:

“Most participants anticipated that, based on their assessment of the current economic situation and their outlook for economic activity, the labor market, and inflation, these conditions [for interest rate increase] could well be met by the time of the next meeting. Nonetheless, they emphasized that the actual decision would depend on the implications for the medium-term economic outlook of the data received over the upcoming intermeeting period… It was noted that beginning the normalization process relatively soon would make it more likely that the policy trajectory after liftoff could be shallow.”

Markets could have interpreted a symbolic increase in the fed funds rate at the meeting of the FOMC on Dec 15-16, 2015 (http://www.federalreserve.gov/monetarypolicy/fomccalendars.htm) followed by “shallow” increases, explaining the sharp increase in stock market values and appreciation of the dollar after the release of the minutes on Nov 18, 2015:

Fri Nov 13

Mon 16

Tue 17

Wed 18

Thu 19

Fri 20

USD/ EUR

1.0774

-0.3%

0.4%

1.0686

0.8%

0.8%

1.0644

1.2%

0.4%

1.0660

1.1%

-0.2%

1.0735

0.4%

-0.7%

1.0647

1.2%

0.8%

DJIA

17245.24

-3.7%

-1.2%

17483.01

1.4%

1.4%

17489.50

1.4%

0.0%

17737.16

2.9%

1.4%

17732.75

2.8%

0.0%

17823.81

3.4%

0.5%

DAX

10708.40

-2.5%

-0.7%

10713.23

0.0%

0.0%

10971.04

2.5%

2.4%

10959.95

2.3%

-0.1%

11085.44

3.5%

1.1%

11119.83

3.8%

0.3%

In testimony before The Joint Economic Committee of Congress on Dec 3, 2015 (http://www.federalreserve.gov/newsevents/testimony/yellen20151203a.htm), Chair Yellen reiterated that the FOMC (Federal Open Market Committee) “anticipates that even after employment and inflation are near mandate-consistent levels, economic condition may, for some time, warrant keeping the target federal funds rate below the Committee views as normal in the longer run.” Todd Buell and Katy Burne, writing on “Draghi says ECB could step up stimulus efforts if necessary,” on Dec 4, 2015, published in the Wall Street Journal (http://www.wsj.com/articles/draghi-says-ecb-could-step-up-stimulus-efforts-if-necessary-1449252934), analyze that the President of the European Central Bank (ECB), Mario Draghi, reassured financial markets that the ECB will increase stimulus if required to raise inflation the euro area to targets. The USD depreciated 3.1 percent on Thu Dec 3, 2015 after weaker than expected measures by the European Central Bank. DJIA fell 1.4 percent on Dec 3 and increased 2.1 percent on Dec 4. DAX fell 3.6 percent on Dec 3.

Fri Nov 27

Mon 30

Tue 1

Wed 2

Thu 3

Fri 4

USD/ EUR

1.0594

0.5%

0.2%

1.0565

0.3%

0.3%

1.0634

-0.4%

-0.7%

1.0616

-0.2%

0.2%

1.0941

-3.3%

-3.1%

1.0885

-2.7%

0.5%

DJIA

17798.49

-0.1%

-0.1%

17719.92

-0.4%

-0.4%

17888.35

0.5%

1.0%

17729.68

-0.4%

-0.9%

17477.67

-1.8%

-1.4%

17847.63

0.3%

2.1%

DAX

11293.76

1.6%

-0.2%

11382.23

0.8%

0.8%

11261.24

-0.3%

-1.1%

11190.02

-0.9%

-0.6%

10789.24

-4.5%

-3.6%

10752.10

-4.8%

-0.3%

At the press conference following the meeting of the FOMC on Dec 16, 2015, Chair Yellen states (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20151216.pdf page 8):

“And we recognize that monetary policy operates with lags. We would like to be able to move in a prudent, and as we've emphasized, gradual manner. It's been a long time since the Federal Reserve has raised interest rates, and I think it's prudent to be able to watch what the impact is on financial conditions and spending in the economy and moving in a timely fashion enables us to do this.”

The implication of this statement is that the state of the art is not accurate in analyzing the effects of monetary policy on financial markets and economic activity. The US dollar appreciated and equities fluctuated:

Fri Dec 11

Mon 14

Tue 15

Wed 16

Thu 17

Fri 18

USD/ EUR

1.0991

-1.0%

-0.4%

1.0993

0.0%

0.0%

1.0932

0.5%

0.6%

1.0913

0.7%

0.2%

1.0827

1.5%

0.8%

1.0868

1.1%

-0.4%

DJIA

17265.21

-3.3%

-1.8%

17368.50

0.6%

0.6%

17524.91

1.5%

0.9%

17749.09

2.8%

1.3%

17495.84

1.3%

-1.4%

17128.55

-0.8%

-2.1%

DAX

10340.06

-3.8%

-2.4%

10139.34

-1.9%

-1.9%

10450.38

-1.1%

3.1%

10469.26

1.2%

0.2%

10738.12

3.8%

2.6%

10608.19

2.6%

-1.2%

On January 29, 2016, the Policy Board of the Bank of Japan introduced a new policy to attain the “price stability target of 2 percent at the earliest possible time” (https://www.boj.or.jp/en/announcements/release_2016/k160129a.pdf). The new framework consists of three dimensions: quantity, quality and interest rate. The interest rate dimension consists of rates paid to current accounts that financial institutions hold at the Bank of Japan of three tiers zero, positive and minus 0.1 percent. The quantitative dimension consists of increasing the monetary base at the annual rate of 80 trillion yen. The qualitative dimension consists of purchases by the Bank of Japan of Japanese government bonds (JGBs), exchange traded funds (ETFs) and Japan real estate investment trusts (J-REITS). The yen devalued sharply relative to the dollar and world equity markets soared after the new policy announced on Jan 29, 2016:

Fri 22

Mon 25

Tue 26

Wed 27

Thu 28

Fri 29

JPY/ USD

118.77

-1.5%

-0.9%

118.30

0.4%

0.4%

118.42

0.3%

-0.1%

118.68

0.1%

-0.2%

118.82

0.0%

-0.1%

121.13

-2.0%

-1.9%

DJIA

16093.51

0.7%

1.3%

15885.22

-1.3%

-1.3%

16167.23

0.5%

1.8%

15944.46

-0.9%

-1.4%

16069.64

-0.1%

0.8%

16466.30

2.3%

2.5%

Nikkei

16958.53

-1.1%

5.9%

17110.91

0.9%

0.9%

16708.90

-1.5%

-2.3%

17163.92

1.2%

2.7%

17041.45

0.5%

-0.7%

17518.30

3.3%

2.8%

Shanghai

2916.56

0.5%

1.3

2938.51

0.8%

0.8%

2749.79

-5.7%

-6.4%

2735.56

-6.2%

-0.5%

2655.66

-8.9%

-2.9%

2737.60

-6.1%

3.1%

DAX

9764.88

2.3%

2.0%

9736.15

-0.3%

-0.3%

9822.75

0.6%

0.9%

9880.82

1.2%

0.6%

9639.59

-1.3%

-2.4%

9798.11

0.3%

1.6%

In testimony on the Semiannual Monetary Policy Report to the Congress on Feb 10-11, 2016, Chair Yellen (http://www.federalreserve.gov/newsevents/testimony/yellen20160210a.htm) states: “U.S. real gross domestic product is estimated to have increased about 1-3/4 percent in 2015. Over the course of the year, subdued foreign growth and the appreciation of the dollar restrained net exports. In the fourth quarter of last year, growth in the gross domestic product is reported to have slowed more sharply, to an annual rate of just 3/4 percent; again, growth was held back by weak net exports as well as by a negative contribution from inventory investment.”

Jon Hilsenrath, writing on “Yellen Says Fed Should Be Prepared to Use Negative Rates if Needed,” on Feb 11, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/yellen-reiterates-concerns-about-risks-to-economy-in-senate-testimony-1455203865), analyzes the statement of Chair Yellen in Congress that the FOMC (Federal Open Market Committee) is considering negative interest rates on bank reserves. The Wall Street Journal provides yields of two and ten-year sovereign bonds with negative interest rates on shorter maturities where central banks pay negative interest rates on excess bank reserves:

Sovereign Yields 2/12/16

Japan

Germany

USA

2 Year

-0.168

-0.498

0.694

10 Year

0.076

0.262

1.744

On Mar 10, 2016, the European Central Bank (ECB) announced (1) reduction of the refinancing rate by 5 basis points to 0.00 percent; decrease the marginal lending rate to 0.25 percent; reduction of the deposit facility rate to 0,40 percent; increase of the monthly purchase of assets to €80 billion; include nonbank corporate bonds in assets eligible for purchases; and new long-term refinancing operations (https://www.ecb.europa.eu/press/pr/date/2016/html/pr160310.en.html). The President of the ECB, Mario Draghi, stated in the press conference (https://www.ecb.europa.eu/press/pressconf/2016/html/is160310.en.html): “How low can we go? Let me say that rates will stay low, very low, for a long period of time, and well past the horizon of our purchases…We don’t anticipate that it will be necessary to reduce rates further. Of course, new facts can change the situation and the outlook.”

The dollar devalued relative to the euro and open stock markets traded lower after the announcement on Mar 10, 2016, but stocks rebounded on Mar 11:

Fri 4

Mon 7

Tue 8

Wed 9

Thu10

Fri 11

USD/ EUR

1.1006

-0.7%

-0.4%

1.1012

-0.1%

-0.1%

1.1013

-0.1%

0.0%

1.0999

0.1%

0.1%

1.1182

-1.6%

-1.7%

1.1151

-1.3%

0.3%

DJIA

17006.77

2.2%

0.4%

17073.95

0.4%

0.4%

16964.10

-0.3%

-0.6%

17000.36

0.0%

0.2%

16995.13

-0.1%

0.0%

17213.31

1.2%

1.3%

DAX

9824.17

3.3%

0.7%

9778.93

-0.5%

0.5%

9692.82

-1.3%

-0.9%

9723.09

-1.0%

0.3%

9498.15

-3.3%

-2.3%

9831.13

0.1%

3.5%

At the press conference after the FOMC meeting on Sep 21, 2016, Chair Yellen states (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20160921.pdf ): “However, the economic outlook is inherently uncertain.” In the address to the Jackson Hole symposium on Aug 26, 2016, Chair Yellen states: “I believe the case for an increase in in federal funds rate has strengthened in recent months…And, as ever, the economic outlook is uncertain, and so monetary policy is not on a preset course” (http://www.federalreserve.gov/newsevents/speech/yellen20160826a.htm). In a speech at the World Affairs Council of Philadelphia, on Jun 6, 2016 (http://www.federalreserve.gov/newsevents/speech/yellen20160606a.htm), Chair Yellen finds that “there is considerable uncertainty about the economic outlook.” There are fifteen references to this uncertainty in the text of 18 pages double-spaced. In the Semiannual Monetary Policy Report to the Congress on Jun 21, 2016, Chair Yellen states (http://www.federalreserve.gov/newsevents/testimony/yellen20160621a.htm), “Of course, considerable uncertainty about the economic outlook remains.” Frank H. Knight (1963, 233), in Risk, uncertainty and profit, distinguishes between measurable risk and unmeasurable uncertainty. Is there a “science” or even “art” of central banking under this extreme uncertainty in which policy does not generate higher volatility of money, income, prices and values of financial assets?

What is truly important is the fixing of the overnight fed funds at 1 to 1 ¼ percent with gradual consideration of further rate increases with all measures depending on “incoming data” (https://www.federalreserve.gov/newsevents/pressreleases/monetary20170920a.htm): “In determining the timing and size of future adjustments to the target range for the federal funds rate, the Committee will assess realized and expected economic conditions relative to its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial and international developments. The Committee will carefully monitor actual and expected inflation developments relative to its symmetric inflation goal. The Committee expects that economic conditions will evolve in a manner that will warrant gradual increases in the federal funds rate; the federal funds rate is likely to remain, for some time, below levels that are expected to prevail in the longer run. However, the actual path of the federal funds rate will depend on the economic outlook as informed by incoming data” (emphasis added).

The decisions of the FOMC (Federal Open Market Committee) depend on incoming data. There are unexpected swings in valuations of risk financial assets by “carry trades” from interest rates below inflation to exposures in stocks, commodities and their derivatives. Another issue is the unexpected “data surprises” such as the sharp decline in 12 months rates of increase of real disposable income, or what is left after taxes and inflation, and the price indicator of the FOMC, prices of personal consumption expenditures (PCE) excluding food and energy. There is no science or art of monetary policy that can deal with this uncertainty.

Real Disposable Personal Income

Real Personal Consumption Expenditures

Prices of Personal Consumption Expenditures

PCE Prices Excluding Food and Energy

∆%12M

∆%12M

∆%12M

∆%12M

6/2017

6/2017

6/2017

6/2017

1.2

2.4

1.4

1.5

Chart VIII-1, Fed Funds Rate and Yields of  Ten-year Treasury Constant Maturity and Baa Seasoned Corporate Bond, Jan 2, 2001 to Oct 6, 2016 

Source: Board of Governors of the Federal Reserve System

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

Chart VIII-1A, Fed Funds Rate and Yield of Ten-year Treasury Constant Maturity, Jan 2, 2001 to Jan 4, 2018

Source: Board of Governors of the Federal Reserve System

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

Table VIII-3, Selected Data Points in Chart VIII-1, % per Year

Fed Funds Overnight Rate

10-Year Treasury Constant Maturity

Seasoned Baa Corporate Bond

1/2/2001

6.67

4.92

7.91

10/1/2002

1.85

3.72

7.46

7/3/2003

0.96

3.67

6.39

6/22/2004

1.00

4.72

6.77

6/28/2006

5.06

5.25

6.94

9/17/2008

2.80

3.41

7.25

10/26/2008

0.09

2.16

8.00

10/31/2008

0.22

4.01

9.54

4/6/2009

0.14

2.95

8.63

4/5/2010

0.20

4.01

6.44

2/4/2011

0.17

3.68

6.25

7/25/2012

0.15

1.43

4.73

5/1/13

0.14

1.66

4.48

9/5/13

0.089

2.98

5.53

11/21/2013

0.09

2.79

5.44

11/26/13

0.09

2.74

5.34 (11/26/13)

12/5/13

0.09

2.88

5.47

12/11/13

0.09

2.89

5.42

12/18/13

0.09

2.94

5.36

12/26/13

0.08

3.00

5.37

1/1/2014

0.08

3.00

5.34

1/8/2014

0.07

2.97

5.28

1/15/2014

0.07

2.86

5.18

1/22/2014

0.07

2.79

5.11

1/30/2014

0.07

2.72

5.08

2/6/2014

0.07

2.73

5.13

2/13/2014

0.06

2.73

5.12

2/20/14

0.07

2.76

5.15

2/27/14

0.07

2.65

5.01

3/6/14

0.08

2.74

5.11

3/13/14

0.08

2.66

5.05

3/20/14

0.08

2.79

5.13

3/27/14

0.08

2.69

4.95

4/3/14

0.08

2.80

5.04

4/10/14

0.08

2.65

4.89

4/17/14

0.09

2.73

4.89

4/24/14

0.10

2.70

4.84

5/1/14

0.09

2.63

4.77

5/8/14

0.08

2.61

4.79

5/15/14

0.09

2.50

4.72

5/22/14

0.09

2.56

4.81

5/29/14

0.09

2.45

4.69

6/05/14

0.09

2.59

4.83

6/12/14

0.09

2.58

4.79

6/19/14

0.10

2.64

4.83

6/26/14

0.10

2.53

4.71

7/2/14

0.10

2.64

4.84

7/10/14

0.09

2.55

4.75

7/17/14

0.09

2.47

4.69

7/24/14

0.09

2.52

4.72

7/31/14

0.08

2.58

4.75

8/7/14

0.09

2.43

4.71

8/14/14

0.09

2.40

4.69

8/21/14

0.09

2.41

4.69

8/28/14

0.09

2.34

4.57

9/04/14

0.09

2.45

4.70

9/11/14

0.09

2.54

4.79

9/18/14

0.09

2.63

4.91

9/25/14

0.09

2.52

4.79

10/02/14

0.09

2.44

4.76

10/09/14

0.08

2.34

4.68

10/16/14

0.09

2.17

4.64

10/23/14

0.09

2.29

4.71

11/13/14

0.09

2.35

4.82

11/20/14

0.10

2.34

4.86

11/26/14

0.10

2.24

4.73

12/04/14

0.12

2.25

4.78

12/11/14

0.12

2.19

4.72

12/18/14

0.13

2.22

4.78

12/23/14

0.13

2.26

4.79

12/30/14

0.06

2.20

4.69

1/8/15

0.12

2.03

4.57

1/15/15

0.12

1.77

4.42

1/22/15

0.12

1.90

4.49

1/29/15

0.11

1.77

4.35

2/05/15

0.12

1.83

4.43

2/12/15

0.12

1.99

4.53

2/19/15

0.12

2.11

4.64

2/26/15

0.11

2.03

4.47

3/5/215

0.11

2.11

4.58

3/12/15

0.11

2.10

4.56

3/19/15

0.12

1.98

4.48

3/26/15

0.11

2.01

4.56

4/03/15

0.12

1.92

4.47

4/9/15

0.12

1.97

4.50

4/16/15

0.13

1.90

4.45

4/23/15

0.13

1.96

4.50

5/1/15

0.08

2.05

4.65

5/7/15

0.13

2.18

4.82

5/14/15

0.13

2.23

4.97

5/21/15

0.12

2.19

4.94

5/28/15

0.12

2.13

4.88

6/04/15

0.13

2.31

5.03

6/11/15

0.13

2.39

5.10

6/18/15

0.14

2.35

5.17

6/25/15

0.13

2.40

5.20

7/1/15

0.13

2.43

5.26

7/9/15

0.13

2.32

5.20

7/16/15

0.14

2.36

5.24

7/23/15

0.13

2.28

5.13

7/30/15

0.14

2.28

5.16

8/06/15

0.14

2.23

5.15

8/20/15

0.15

2.09

5.13

8/27/15

0.14

2.18

5.33

9/03/15

0.14

2.18

5.35

9/10/15

0.14

2.23

5.35

9/17/15

0.14

2.21

5.39

9/25/15

0.14

2.13

5.29

10/01/15

0.13

2.05

5.36

10/08/15

0.13

2.12

5.40

10/15/15

0.13

2.04

5.33

10/22/15

0.12

2.04

5.30

10/29/15

0.12

2.19

5.40

11/05/15

0.12

2.26

5.44

11/12/15

0.12

2.32

5.51

11/19/15

0.12

2.24

5.44

11/25/15

0.12

2.23

5.44

12/03/15

0.13

2.33

5.51

12/10/15

0.14

2.24

5.43

12/17/15

0.37

2.24

5.45

12/23/15

0.36

2.27

5.53

12/30/15

0.35

2.31

5.54

1/07/2016

0.36

2.16

5.44

01/14/16

0.36

2.10

5.46

01/20/16

0.37

2.01

5.41

01/29/16

0.38

2.00

5.48

02/04/16

0.38

1.87

5.40

02/11/16

0.38

1.63

5.26

02/18/16

0.38

1.75

5.37

02/25/16

0.37

1.71

5.27

03/03/16

0.37

1.83

5.30

03/10/16

0.36

1.93

5.23

03/17/16

0.37

1.91

5.11

03/24/16

0.37

1.91

4.97

03/31/16

0.25

1.78

4.90

04/07/16

0.37

1.70

4.76

04/14/16

0.37

1.80

4.79

04/21/16

0.37

1.88

4.79

04/28/16

0.37

1.84

4.73

05/05/16

0.37

1.76

4.62

05/12/16

0.37

1.75

4.66

05/19/16

0.37

1.85

4.70

05/26/16

0.37

1.83

4.69

06/02/16

0.37

1.81

4.64

06/09/16

0.37

1.68

4.53

06/16/16

0.38

1.57

4.47

06/23/16

0.39

1.74

4.60

06/30/16

0.36

1.49

4.41

07/07/16

0.40

1.40

4.19

07/14/16

0.40

1.53

4.23

07/21/16

0.40

1.57

4.25

07/28/16

0.40

1.52

4.20

08/04/16

0.40

1.51

4.27

08/11/16

0.40

1.57

4.27

08/18/16

0.40

1.53

4.23

08/25/16

0.40

1.58

4.21

09/01/16

0.40

1.57

4.19

09/08/16

0.40

1.61

4.28

09/15/16

0.40

1.71

4.43

09/22/16

0.40

1.63

4.32

09/29/16

0.40

1.56

4.23

10/06/16

0.40

1.75

4.36

10/13/16

0.40

1.75

NA*

10/20/16

0.41

1.76

NA*

10/27/16

0.41

1.85

NA*

11/03/16

0.41

1.82

NA*

11/09/16

0.41

2.07

NA*

11/17/16

0.41

2.29

NA*

11/23/16

0.40

2.36

NA*

12/01/16

0.40

2.45

NA*

12/08/16

0.41

2.40

NA*

12/15/16

0.66

2.60

NA*

12/22/16

0.66

2.55

NA*

12/29/16

0.66

2.49

NA*

01/05/17

0.66

2.37

NA*

01/12/17

0.66

2.36

NA*

01/19/17

0.66

2.42

NA*

01/26/17

0.66

2.51

NA*

02/02/17

0.66

2.48

NA*

02/09/17

0.66

2.40

NA*

02/16/17

0.66

2.45

NA*

02/23/17

0.66

2.38

NA*

03/02/17

0.66

2.49

NA*

03/09/17

0.66

2.60

NA*

03/16/17

0.91

2.53

NA*

03/23/17

0.91

2.41

NA*

03/30/17

0.91

2.42

NA*

04/06/17

0.91

2.34

NA*

04/13/17

0.91

2.24

NA*

04/21/17

0.91

2.24

NA*

04/27/17

0.91

2.30

NA*

05/04/17

0.91

2.36

NA*

05/11/17

0.91

2.39

NA*

05/18/17

0.91

2.23

NA*

05/25/17

0.91

2.25

NA*

06/01/17

0.90

2.21

NA*

06/08/17

0.91

2.19

NA*

06/15/17

1.16

2.16

NA*

06/22/17

1.16

2.15

NA*

06/29/17

1.16

2.27

NA*

07/06/17

1.16

2.37

NA*

07/13/17

1.16

2.35

NA*

07/20/17

1.16

2.27

NA*

07/27/17

1.16

2.32

NA*

08/03/17

1.16

2.24

NA*

08/10/17

1.16

2.20

NA*

08/17/17

1.16

2.19

NA*

08/24/17

1.16

2.19

NA*

08/31/17

1.07

2.12

NA*

09/07/17

1.16

2.05

NA*

09/14/17

1.16

2.20

NA*

09/21/17

1.16

2.27

NA*

09/28/17

1.16

2.31

NA*

10/05/17

1.16

2.35

NA*

10/12/17

1.16

2.33

NA*

10/19/17

1.16

2.33

NA*

10/26/17

1.16

2.46

NA*

11/02/17

1.16

2.35

NA*

11/09/17

1.16

2.32

NA*

11/16/17

1.16

2.37

NA*

11/22/17

1.16

2.32

NA*

11/30/17

1.16

2.42

NA*

12/07/17

1.16

2.37

NA*

12/14/17

1.41

2.35

NA*

12/21/17

1.42

2.48

NA*

12/28/17

1.42

2.43

NA*

01/04/18

1.42

2.46

NA*

*Note: The Board of Governors of the Federal Reserve System discontinued the publication of the BAA bond yield.

Source: Board of Governors of the Federal Reserve System

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

Chart VIII-2 of the Board of Governors of the Federal Reserve System provides the rate of US dollars (USD) per euro (EUR), USD/EUR. The rate depreciated from USD 1.0486/EUR on Dec 29, 2016 to USD 1.2022/EUR on Dec 29, 2017 or 14.6 percent. The euro has devalued 32.2 percent relative to the dollar from the high on Jul 15, 2008 to Jan 5, 2018. US corporations with foreign transactions and net worth experience losses in their balance sheets in converting revenues from depreciated currencies to the dollar. Corporate profits increased at $53.9 billion in IVQ2016. Corporate profits fell at $46.2 billion in IQ2017. Corporate profits increased at $14.4 billion in IIQ2017. Corporate profits increased $90.3 billion in IIIQ2017. Profits after tax with IVA and CCA increased at $71.6 billion in IVQ2016. Profits after tax with IVA and CCA fell at $43.0 billion in IQ2017. After tax profits increased at $1.1 billion in IIQ2017. Profits after tax with IVA and CCA increased at $94.4 billion in IIIQ2017. Net dividends increased at $2.8 billion in IVQ2016. Net dividends increased at $9.0 billion in IQ2017. Net dividends increased at $6.1 billion in IIQ2017. Net dividends increased at $4.4 billion in IIIQ2017. Undistributed corporate profits increased at $68.9 billion in IVQ2016. Undistributed profits fell at $52.0 billion in IQ2017. Undistributed profits decreased at $5.0 billion in IIQ2017. Undistributed profits increased at $90.0 billion in IIIQ2017. Undistributed corporate profits swelled 389.3 percent from $107.7 billion in IQ2007 to $527.0 billion in IIIQ2017 and changed signs from minus $55.9 billion in current dollars in IVQ2007. Uncertainty originating in fiscal, regulatory and monetary policy causes wide swings in expectations and decisions by the private sector with adverse effects on investment, real economic activity and employment. There is increase in corporate profits from devaluing the dollar with unconventional monetary policy of zero interest rates and decrease of corporate profits in revaluing the dollar with attempts at “normalization” or increases in interest rates. Conflicts arise while other central banks differ in their adjustment process. The current account deficit of the US not seasonally adjusted decreased from $126.0 billion in IIIQ2016 to $112.8 billion in IIIQ2017. The current account deficit seasonally adjusted at annual rate increased from 2.4 percent of GDP in IIIQ2016 to 2.6 percent of GDP in IIQ2017, decreasing to 2.1 percent of GDP in IIIQ2017. The absolute value of the net international investment position increases from minus $8.0 trillion in IIIQ2016 to minus $8.3 trillion in IVQ2016. The absolute value of the net international investment position decreases to minus $8.1 trillion in IQ2017 and decreases to minus $8.0 trillion in IIQ2017. The absolute value of the net international investment position decreased to $7.8 trillion in IIIQ2017. The BEA explains as follows (https://www.bea.gov/newsreleases/international/intinv/2017/pdf/intinv217.pdf):

“The U.S. net international investment position increased to -$7,768.7 billion (preliminary) at the end of the third quarter of 2017 from -$8,004.1 billion (revised) at the end of the second quarter, according to statistics released today by the Bureau of Economic Analysis (BEA). The $235.4 billion increase reflected a $1,001.2 billion increase in U.S. assets and a $765.8 billion increase in U.S. liabilities (table 1).”

The BEA explains further (https://www.bea.gov/newsreleases/international/intinv/2017/pdf/intinv317.pdf): “

“The $235.4 billion increase in the net investment position reflected net financial transactions of –$87.4 billion and net other changes in position, such as price and exchange-rate changes, of $322.8 billion (table A).

The net investment position increased 2.9 percent in the third quarter, compared with an increase of 1.1 percent in the second quarter, and an average quarterly decrease of 5.3 percent from the first quarter of 2011 through the first quarter of 2017.

U.S. assets increased $1,001.2 billion to $26,854.9 billion at the end of the third quarter, mostly reflecting increases in portfolio investment and direct investment assets that were partly offset by a decrease in financial derivatives.

· Assets excluding financial derivatives increased $1,227.5 billion to $25,149.7 billion. The increase resulted from other changes in position of $869.2 billion and financial transactions of $358.2 billion. Other changes in position mostly reflected foreign equity price increases that raised the equity value of portfolio investment and direct investment assets, and the appreciation of major foreign currencies against the U.S. dollar that raised the value of foreign-currency-denominated assets in dollar terms. Financial transactions mostly reflected net acquisition of portfolio investment assets.

· Financial derivatives decreased $226.2 billion to $1,705.1 billion, mostly in single-currency interest rate contracts.”

U.S. liabilities increased $765.8 billion to $34,623.6 billion at the end of the third quarter, mostly reflecting increases in portfolio investment and direct investment liabilities that were partly offset by a decrease in financial derivatives.

· Liabilities excluding financial derivatives increased $988.8 billion to $32,952.3 billion. The increase resulted from other changes in position of $524.6 billion and financial transactions of $464.2 billion (table A). Other changes in position mostly reflected U.S. equity price increases that raised the equity value of portfolio investment and direct investment liabilities. Financial transactions mostly reflected net incurrence of portfolio investment liabilities.

· Financial derivatives decreased $223.0 billion to $1,671.3 billion, mostly in single-currency interest rate contracts.”

Chart VIII-2, Exchange Rate of US Dollars (USD) per Euro (EUR), Dec 29, 2016 to Dec 29, 2017

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H10/default.htm

Chart VIII-3 of the Board of Governors of the Federal Reserve System provides the yield of the 10-year Treasury constant maturity note from 2.35 percent on Oct 5, 2017 to 2.46 percent on Jan 4, 2018. There is turbulence in financial markets originating in a combination of intentions of normalizing or increasing US policy fed funds rate, quantitative easing in Europe and Japan and increasing perception of financial/economic risks.

Chart VIII-3, Yield of Ten-year Constant Maturity Treasury, Oct 5, 2017 to Jan 4, 2018

Source: Board of Governors of the Federal Reserve System

Percentage changes of risk financial assets from the last day of the year relative to the last day of the earlier year are in Table I-1 from 2007 to 2017. Some of the highest increases in valuations of risk financial assets are in 2017 with exception of 2013. DJIA increased 25.1 percent and S&P increased 19.4 percent while NYSE Financial gained 18.3 percent. Dow Global increased 21.9 percent. NIKKEI Average increased 19.1 percent while Shanghai Composite increased 6.6 percent. The US dollar depreciated 14.1 percent relative to the euro and the ten-year Treasury yield decreased to 2.411 percent. There is somewhat less strong performance in 2016. DJIA increased 13.4 percent and S&P 500 increased 9.5 percent. NYSE Financial increased 10.4 percent and Dow Global increased 8.4 percent. Shanghai Composite decreased 12.3 percent. DAX increased 6.9 percent. The US dollar appreciated 3.1 percent relative to the euro. There is mixed performance in 2015 with declines of 2.2 for DJIA, 0.7 percent for S&P 500, 6.0 percent for NYSE Financial, 6.6 percent for Dow Global and 2.5 percent for Dow Asia Pacific. There were increases of 9.1 percent for the Nikkei Average, 9.4 percent for Shanghai Composite and 9.6 percent for DAX of Germany. The US dollar appreciated 10.2 percent relative to the euro. Calendar year 2014 was satisfactory for most equity indexes but not as excellent as 2013. Shanghai Composite outperformed all equity indexes in Table I-1 in 2014 with increase of 52.9 percent after falling 6.7 percent in 2013. The second highest increase is 11.4 percent for the Standard and Poor’s 500 (S&P 500). DAX of Germany gained 2.7 percent. NYSE Financial increased 5.6 percent and Dow Global gained 0.6 percent. Dow Asia Pacific decreased 1.6 percent while the Dow Jones Industrial Average (DJIA) increased 7.5 percent. The USD appreciated 12.0 percent relative to the EUR. Equities also outperformed in calendar year 2012. DAX gained 29.1 percent and NYSE Financial 25.9 percent. Equities soared in 2013. The Nikkei Average increased 56.7 percent. DJIA gained 26.5 percent and S&P 500 29.6 percent. DAX of Germany increased 25.5 percent. The dollar depreciated 4.2 percent relative to the euro. DJ UBS Commodities index fell 9.6 percent. Equities enjoyed a good year in 2012. Nikkei Average gained 22.9 percent in 2012. S&P increased 13.4 percent and DJIA 7.3 percent. Shanghai Composite increased 3.2 percent. Dow Global increased 10.7 percent and Dow Asia Pacific 13.1 percent. DJ UBS Commodities fell 1.8 percent. The only gain for a major equity index in Table I-1 for 2011 is 5.5 percent for the DJIA. S&P 500 is better than other equity markets by remaining flat for 2011. Except for a drop of 8.4 percent of the European equity index STOXX 50, all declines of equity markets in 2011 are in excess of 10 percent. China’s Shanghai Composite lost 21.7 percent. The equity index of Germany DAX fell 14.7 percent. The DJ UBS Commodities Index dropped 13.4 percent. Robin Wigglesworth, writing on Dec 30, 2011, on “$6.3tn wiped off markets in 2011,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/483069d8-32f3-11e1-8e0d-00144feabdc0.html#axzz1i2BE7OPa), provides an estimate of $6.3 trillion erased from equity markets globally in 2011. The Bureau of Economic Analysis (BEA) estimates US nominal GDP in 2011 at $15,517.9 billion (http://www.bea.gov/iTable/index_nipa.cfm). The loss in equity markets worldwide in 2011 of $6.3 trillion is equivalent to about 40.6 percent of US GDP or economic activity in 2011. Table I-1 also provides the exchange rate of number of US dollars (USD) required in buying a unit of euro (EUR), USD/EUR. The dollar appreciated 3.1 percent on the last day of trading in 2011 relative to the last day of trading in 2010, suggesting risk aversion. Depreciation of the dollar by 1.8 percent in 2012 and 4.2 percent in 2013 suggests more favorable environment of risk appetite for carry trades from zero interest rates into risk financial assets. The final row of Table I-1 provides the yield of the ten-year Treasury, decreasing to 2.172 percent in 2014 and 2.269 percent in 2015. The yield of the ten-year Treasury increased to 3.030 percent in 2013, which is the highest since 3.292 percent in 2010 and 3.844 percent in 2009. The yield at year-end 2007 was 4.077 percent.

Table I-1, Percentage Change of Year-end Values of Financial Assets Relative to Earlier Year-end Values 2007-2017 and Year-end Yield of 10-Year Treasury Note

∆%

2015

2014

2013

2012

2011

2010

2009

2008

2007

DJIA

-2.2

7.5

26.5

7.3

5.5

11.0

18.8

-33.8

6.4

S&P

500

-0.7

11.4

29.6

13.4

0.0

12.8

23.5

-38.5

3.5

NYSE

Fin

-6.0

5.6

24.2

25.9

-18.1

5.0

22.7

-53.6

-13.1

Dow Global

-6.6

0.6

24.5

10.7

-13.6

5.2

30.0

-45.4

30.5

Dow Asia-Pacific

-2.5

-1.6

10.2

13.1

-17.6

16.0

36.4

-44.2

14.0

Nikkei Av

9.1

7.1

56.7

22.9

-17.3

-3.0

19.0

-42.1

-11.1

Shanghai

9.4

52.9

-6.7

3.2

-21.7

-14.3

80.0

-65.4

96.7

DAX

9.6

2.7

25.5

29.1

-14.7

16.1

23.8

-40.4

22.3

USD/

EUR*

10.2

12.0

-4.2

-1.8

3.1

6.6

-2.5

4.3

-10.6

DJ UBS** Com

NA

NA

-9.6

-1.1

-13.4

16.7

18.7

-36.6

11.2

Year-end Yield 10-Year Treasury %

2.269

2.172

3.030

1.758

2.027

3.292

3.844

2.157

4.077

∆%

2016

2017

DJIA

13.4

25.1

S&P 500

9.5

19.4

NYSE Financial

10.4

18.3

Dow Global

8.4

21.9

Dow Asia Pacific

2.4

NA

Nikkei Average

0.4

19.1

Shanghai Composite

-12.3

6.6

DAX

6.9

12.5

USD/EUR*

3.1

-14.1

DJ UBS Commodities**

NA

NA

Year-end Yield 10 Year Treasury

2.447

2.411

*Negative sign is dollar devaluation; positive sign is dollar appreciation

**DJ UBS available only for 2013 and earlier years

Sources: http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata

The other yearly percentage changes in Table I-2 are also revealing wide fluctuations in valuations of risk financial assets. To be sure, economic conditions and perceptions of the future do influence valuations of risk financial assets. It is also valid to contend that unconventional monetary policy magnifies fluctuations in these valuations by inducing carry trades from zero interest rates to exposures with high leverage in risk financial assets such as equities, emerging equities, currencies, high-yield structured products and commodities futures and options. In fact, one of the alleged channels of transmission of unconventional monetary policy is through higher consumption induced by increases in wealth resulting from higher valuations of stock markets. Bernanke (2010WP) and Yellen (2011AS) reveal the emphasis of monetary policy on the impact of the rise of stock market valuations in stimulating consumption by wealth effects on household confidence. Unconventional monetary policy could also result in magnification of values of risk financial assets beyond actual discounted future cash flows, creating financial instability. Separating all these effects in practice may be quite difficult because they are observed simultaneously. Conclusive evidence would require contrasting what actually happened with the counterfactual of what would have happened in the absence of unconventional monetary policy and other effects (on counterfactuals see Pelaez and Pelaez, Globalization and the State Vol I (2008a), 125, 136, Harberger (1971, 1997), Fishlow 1965, Fogel 1964, Fogel and Engerman 1974, North and Weingast 1989, Coastworth 1981, 2006, Summerhill 1997, 1998, 2003, Pelaez 1979, 26-7). There is no certainty or evidence that unconventional policies attain their intended effects without risks of costly side effects. Yearly fluctuations of financial assets in Table I-1 are quite wide. In 2007, for example, Table I-1 shows that the equity index Dow Global increased 30.5 percent while DAX gained 22.3 percent and the Shanghai Composite jumped 96.7 percent. The DJIA gained only 6.4 percent as recession began in IVQ2007. The flight to government obligations in 2008 (Cochrane and Zingales 2009, Cochrane 2011Jan) was equivalent to the astronomical declines of world equity markets and commodities. The flight from risk is also in evidence in the appreciation of the dollar by 4.3 percent in 2008 with unwinding carry trades and with renewed carry trades in the depreciation of the dollar by 2.5 percent in 2009. Recovery still continued in 2010 with shocks of the European debt crisis in the spring and in Nov 2010. The flight from risk exposures dominated declines of valuations of risk financial assets in 2011.

Table I-2 is designed to provide a comparison of valuations of risk financial assets at the end of 2017 relative to valuations at the end of every year from 2007 to 2016. There were increases in major indexes in 2017: 25.1 percent for DJIA, 19.4 percent for S&P 500, 18.3 percent for NYSE Financial and 21.9 percent for Dow Global. There are increases in major indexes: 19.1 percent for Nikkei and 12.5 percent for DAX of Germany. Shanghai Composite increased 12.5 percent. The DJIA index is 38.7 percent higher at the end of 2017 relative to the valuation at the end of 2014, 86.4 percent above the valuation at the end of 2007 and 98.3 percent higher relative to the valuation at the end of 2006. DJIA is higher by 181.7 percent at the end of 2017 relative to the depressed valuation at the end of 2008. Several indexes are still lower at the end of 2017 relative to the values at the end of 2007 with exception of gains of 86.4 for DJIA, 82.1 percent for S&P 500, 48.1 percent for Nikkei Average and 60.1 percent for DAX. Some equity indexes are higher at the end of 2017 relative to the end of 2006: DJIA by 98.3 percent, S&P by 88.5 percent, Dow Global by 44.2 percent, Nikkei Average by 32.2percent, Shanghai Composite by 23.6 percent and DAX by 95.8 percent. The USD is 17.8 stronger at the end of 2017 relative to 2007 and 9.0 percent stronger relative to 2006. Zero interest rates do not devalue the dollar during prolonged bouts of relative risk aversion and portfolio reallocations. Low valuations of risk financial assets are intimately related to risk aversion in international financial markets because of the European debt crisis, weakness and unemployment in advanced economies, fiscal imbalances and cycally slowing growth worldwide.

Table I-2, Percentage Change of Year-end 2017 Values of Financial Assets Relative to Year-end Values 2007-2017

∆% 17/

14

∆% 17/

13

∆% 17/ 12

∆% 17/ 11

∆% 17/

10

∆% 17/

09

∆% 17/

08

∆% 17/

07

DJIA

38.7

49.1

88.6

102.3

113.5

137.0

181.7

86.4

S&P 500

29.9

44.6

87.5

112.6

112.6

139.8

196.0

82.1

NYSE Fin

22.8

29.6

61.0

102.7

66.1

74.5

114.0

-0.8

Dow Global

23.4

24.2

54.6

71.2

47.9

55.5

102.2

10.5

Nikkei Av

30.5

39.7

119.0

169.2

122.6

115.9

157.0

48.7

Shanghai

2.2

56.3

45.7

50.4

17.8

0.9

81.6

-37.1

DAX

31.7

35.2

69.7

119.0

86.8

116.8

168.5

60.1

USD/EUR*

0.8

12.7

9.0

7.4

10.2

16.2

14.1

17.8

∆% 17/15

∆% 17/16

DJIA

41.9

25.1

S&P 500

30.8

19.4

NYSE Fin

30.6

18.3

Dow Global

32.1

21.9

Nikkei Average

19.6

19.1

Shanghai Composite

-6.6

6.6

DAX

20.2

12.5

USD/EUR*

-10.5

-14.1

*Negative sign is dollar devaluation; positive sign is dollar appreciation

Sources: http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata

There are references to adverse periods as “lost decades.” There is a more prolonged and adverse period in Table V-3A: the lost economic cycle of the Global Recession with economic growth underperforming below trend worldwide. Economic contractions were relatively high but not comparable to the decline of GDP during the Great Depression. In fact, during the Great Depression in the four years of 1930 to 1933, US 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. The contraction of GDP in the current cycle of the Global Recession was much lower, 4.2 percent (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html and earlier https://cmpassocregulationblog.blogspot.com/2017/10/dollar-revaluation-and-increase-of.html). Contractions were deeper in Japan, 8.7 percent, the euro area (19 members), 5.8 percent, Germany, 6.9 percent and the UK 6.1 percent. The contraction in France was 4.0 percent. There is adversity in low rates of growth during the expansion that did not compensate for the contraction such that for the whole cycle performance is disappointingly low. As a result, GDP is substantially below what it would have been in trend growth in all countries and regions in the world. 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 2.2 percent on average in the cyclical expansion in the 33 quarters from IIIQ2009 to IIIQ2017. 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 IIIQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp3q17_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 dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states_23.html and earlier https://cmpassocregulationblog.blogspot.com/2017/12/mediocre-cyclical-united-states.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). 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 IIIQ2017 would have accumulated to 33.4 percent. GDP in IIIQ2017 would be $19,999.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2835.2 billion than actual $17,163.9 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.3 percent of the effective labor force (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/12/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/11/unchanged-fomc-policy-rate-gradual.html). US GDP in IIIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,163.9 billion in IIIQ2017 or 14.5 percent at the average annual equivalent rate of 1.4 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Nov 1919 to Nov 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 146.5098 in Nov 2017. The actual index NSA in Nov 2017 is 104.6305, which is 28.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Nov 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.7256 in Nov 2017. The output of manufacturing at 104.6305 in Nov 2017 is 20.6 percent below trend under this alternative calculation.

Table V-3A, Cycle 2007-2017, Percentage Contraction, Average Growth Rate in Expansion, Average Growth Rate in Whole Cycle and GDP Percent Below Trend

Contraction ∆%

Expansion AV ∆%

Whole Cycle AV ∆%

Below Trend Percent

USA

4.2

2.2

1.4

14.2

Japan

8.7

1.7

0.5

NA

Euro Area (19)

5.8

1.3

0.5

15.5

France

4.0

1.3

0.7

10.1

Germany

6.9

2.1

1.1

NA

UK

6.1

2.0

1.0

14.5

Note: AV: Average. Expansion and Whole Cycle AV ∆% calculated with quarterly growth, seasonally adjusted and quarterly adjusted when applicable, rates and converted into annual equivalent.

Data reported periodically in this blog.

Source: Country Statistical Agencies http://www.census.gov/aboutus/stat_int.html

The carry trade from zero interest rates to leveraged positions in risk financial assets had proved strongest for commodity exposures but US equities have regained leadership. The DJIA has increased 161.1 percent since the trough of the sovereign debt crisis in Europe on Jul 16, 2010 to Jan 5, 2018; S&P 500 has gained 168.3 percent and DAX 134.9 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 01/05/18” in Table VI-4 had double digit gains relative to the trough around Jul 2, 2010 followed by negative performance but now some valuations of equity indexes show varying behavior. China’s Shanghai Composite is 42.3 percent above the trough. Japan’s Nikkei Average is 168.7 percent above the trough. Dow Global is 86.4 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 40.7 percent above the trough. NYSE Financial Index is 96.7 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 134.9 percent above the trough. Japan’s Nikkei Average is 168.7 percent above the trough on Aug 31, 2010 and 108.1 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 23,714.53 on Jan 5, 2018 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 131.3 percent higher than 10,254.43 on Mar 11, 2011, on the date of the Tōhoku or Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar depreciated 0.9 percent relative to the euro. The dollar devalued before the new bout of sovereign risk issues in Europe. The column “∆% week to 01/05/18” in Table VI-4 shows

increase of 2.6 percent for China’s Shanghai Composite. The Nikkei increased 4.2 percent. NYSE Financial increased 1.5 percent in the week. Dow Global increased 2.9 percent in the week of Jan 5, 2018. The DJIA increased 2.3 percent and S&P 500 increased 2.6 percent. DAX of Germany increased 3.1 percent. STOXX 50 increased 1.7 percent. The USD depreciated 0.2 percent. There are still high uncertainties on European sovereign risks and banking soundness, US and world growth slowdown and China’s growth tradeoffs. Sovereign problems in the “periphery” of Europe and fears of slower growth in Asia and the US cause risk aversion with trading caution instead of more aggressive risk exposures. There is a fundamental change in Table VI-4 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 01/05/18” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Jan 5, 2018. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 01/05/18” but also relative to the peak in column “∆% Peak to 01/05/18.” There are now several equity indexes above the peak in Table VI-4: DJIA 125.8 percent, S&P 500 125.3 percent, DAX 110.4 percent, Dow Global 52.1 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 56.6 percent, Nikkei Average 108.1 percent and STOXX 50 19.2 percent. Shanghai Composite is 7.2 percent above the peak. The Shanghai Composite increased 71.8 percent from March 12, 2014, to Jan 5, 2018. The US dollar strengthened 20.5 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010.

Sharp and continuing strengthening of the dollar, with recent oscillation of dollar devaluation, is affecting balance sheets of US corporations with foreign operations (http://www.fasb.org/jsp/FASB/Pronouncement_C/SummaryPage&cid=900000010318). Recently, the dollar is depreciating. The Federal Open Market Committee (FOMC) is following “financial and international developments” as part of the process of framing interest rate policy (http://www.federalreserve.gov/newsevents/press/monetary/20150128a.htm). Kate Linebaugh, writing on “Corporate profits set to shrink for fourth consecutive quarter,” on Jul 17, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/corporate-profits-set-to-shrink-for-fourth-consecutive-quarter-1468799278), quotes forecasts of Thomson Reuters of 4.7 decline of adjusted earnings per share in the S&P 500 index in IIQ2016 relative to a year earlier. That would be the fourth consecutive quarterly decline. Theo Francis and Kate Linebaugh, writing on “US corporate profits on pace for third straight decline,” on Apr 28, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/u-s-corporate-profits-on-pace-for-third-straight-decline-1461872242), analyze three consecutive quarters of decline of corporate earnings and revenue in companies in S&P 500. They quote Thomson Reuters on expected decline of earnings of 6.1 percent in IQ2016 based on 55 percent of reporting companies. Weakness of economic activity shows in decline of revenues in IQ2016 of 1.4 percent, increasing 1.7 percent excluding energy, and contraction of profits of 0.5 percent. Justin Lahart, writing on “S&P 500 Earnings: far worse than advertised,” on Feb 24, 2016, published in the Wall Street Journal (http://www.wsj.com/articles/s-p-500-earnings-far-worse-than-advertised-1456344483), analyzes S&P 500 earnings in 2015. Under data provided by companies, earnings increased 0.4 percent in 2015 relative to 2014 but under GAAP (Generally Accepted Accounting Principles), earnings fell 12.7 percent, which is the worst decrease since 2008. Theo Francis e Kate Linebaugh, writing on Oct 25, 2015, on “US Companies Warn of Slowing Economy, published in the Wall Street Journal (http://www.wsj.com/articles/u-s-companies-warn-of-slowing-economy-1445818298) analyze the first contraction of earnings and revenue of big US companies. Production, sales and employment are slowing in a large variety of companies with some contracting. Corporate profits also suffer from revaluation of the dollar that constrains translation of foreign profits into dollar balance sheets. Francis and Linebaugh quote Thomson Reuters that analysts expect decline of earnings per share of 2.8 percent in IIIQ2015 relative to IIIQ2014 based on reports by one third of companies in the S&P 500. Sales would decline 4.0% in a third quarter for the first joint decline of earnings per share and revenue in the same quarter since IIIQ2009. Dollar revaluation also constrains corporate results.

Inyoung Hwang, writing on “Fed optimism spurs record bets against stock volatility,” on Aug 21, 2014, published in Bloomberg.com (http://www.bloomberg.com/news/2014-08-21/fed-optimism-spurs-record-bets-against-stock-voalitlity.html), informs that the S&P 500 is trading at 16.6 times estimated earnings, which is higher than the five-year average of 14.3 Tom Lauricella, writing on Mar 31, 2014, on “Stock investors see hints of a stronger quarter,” published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304157204579473513864900656?mod=WSJ_smq0314_LeadStory&mg=reno64-wsj), finds views of stronger earnings among many money managers with positive factors for equity markets in continuing low interest rates and US economic growth. There is important information in the Quarterly Markets review of the Wall Street Journal (http://online.wsj.com/public/page/quarterly-markets-review-03312014.html) for IQ2014. Alexandra Scaggs, writing on “Tepid profits, roaring stocks,” on May 16, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323398204578487460105747412.html), analyzes stabilization of earnings growth: 70 percent of 458 reporting companies in the S&P 500 stock index reported earnings above forecasts but sales fell 0.2 percent relative to forecasts of increase of 0.5 percent. Paul Vigna, writing on “Earnings are a margin story but for how long,” on May 17, 2013, published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2013/05/17/earnings-are-a-margin-story-but-for-how-long/), analyzes that corporate profits increase with stagnating sales while companies manage costs tightly. More than 90 percent of S&P components reported moderate increase of earnings of 3.7 percent in IQ2013 relative to IQ2012 with decline of sales of 0.2 percent. Earnings and sales have been in declining trend. In IVQ2009, growth of earnings reached 104 percent and sales jumped 13 percent. Net margins reached 8.92 percent in IQ2013, which is almost the same at 8.95 percent in IIIQ2006. Operating margins are 9.58 percent. There is concern by market participants that reversion of margins to the mean could exert pressure on earnings unless there is more accelerated growth of sales. Vigna (op. cit.) finds sales growth limited by weak economic growth. Kate Linebaugh, writing on “Falling revenue dings stocks,” on Oct 20, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444592704578066933466076070.html?mod=WSJPRO_hpp_LEFTTopStories), identifies a key financial vulnerability: falling revenues across markets for United States reporting companies. Global economic slowdown is reducing corporate sales and squeezing corporate strategies. Linebaugh quotes data from Thomson Reuters that 100 companies of the S&P 500 index have reported declining revenue only 1 percent higher in Jun-Sep 2012 relative to Jun-Sep 2011 but about 60 percent of the companies are reporting lower sales than expected by analysts with expectation that revenue for the S&P 500 will be lower in Jun-Sep 2012 for the entities represented in the index. Results of US companies are likely repeated worldwide. Future company cash flows derive from investment projects. In IQ1980, real gross private domestic investment in the US was $951.6 billion of chained 2009 dollars, growing to $1,137.1 billion in IQ1991 or 19.5 percent. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). Real gross private domestic investment in the US increased 14.3 percent from $2605.2 billion in IVQ2007 to $2,976.5 billion in IIIQ2017. Real private fixed investment increased 12.7 percent from $2,586.3 billion of chained 2009 dollars in IVQ2007 to $2,915.8 billion in IIIQ2017. Private fixed investment fell relative to IVQ2007 in all quarters preceding IQ2014 and increased 0.4 percent in IIIQ2016, increasing 0.3 percent in IIQ2016 and falling 0.1 percent in IQ2016. Private fixed investment increased 0.4 percent in IVQ2016. Private fixed investment increased 2.0 percent in IQ2017 and increased 0.8 percent in IIQ2017. Private fixed investment increased 0.6 percent in IIIQ2017. Growth of real private investment is mediocre for all but four quarters from IIQ2011 to IQ2012. The investment decision of United States corporations is fractured in the current economic cycle in preference of cash.

There are three aspects. First, there is fluctuation in corporate profits. Corporate profits increased at $53.9 billion in IVQ2016. Corporate profits fell at $46.2 billion in IQ2017. Corporate profits increased at $14.4 billion in IIQ2017. Corporate profits increased $90.3 billion in IIIQ2017. Profits after tax with IVA and CCA increased at $71.6 billion in IVQ2016. Profits after tax with IVA and CCA fell at $43.0 billion in IQ2017. After tax profits increased at $1.1 billion in IIQ2017. Profits after tax with IVA and CCA increased at $94.4 billion in IIIQ2017. Net dividends increased at $2.8 billion in IVQ2016. Net dividends increased at $9.0 billion in IQ2017. Net dividends increased at $6.1 billion in IIQ2017. Net dividends increased at $4.4 billion in IIIQ2017. Undistributed corporate profits increased at $68.9 billion in IVQ2016. Undistributed profits fell at $52.0 billion in IQ2017. Undistributed profits decreased at $5.0 billion in IIQ2017. Undistributed profits increased at $90.0 billion in IIIQ2017. Undistributed corporate profits swelled 389.3 percent from $107.7 billion in IQ2007 to $527.0 billion in IIIQ2017 and changed signs from minus $55.9 billion in current dollars in IVQ2007. Uncertainty originating in fiscal, regulatory and monetary policy causes wide swings in expectations and decisions by the private sector with adverse effects on investment, real economic activity and employment. Second, sharp and continuing strengthening of the dollar, with recent depreciation at the margin, is affecting balance sheets of US corporations with foreign operations (http://www.fasb.org/jsp/FASB/Pronouncement_C/SummaryPage&cid=900000010318) and the overall US economy. The bottom part of Table IA1-9 provides the breakdown of corporate profits with IVA and CCA in domestic industries and the rest of the world. Corporate profits with IVA and CCA increased at $53.9 billion in IVQ2016. Profits from domestic industries increased at $6.7 billion and profits from nonfinancial business decreased at $20.5 billion. Profits from the rest of the world increased at $47.3 billion. Corporate profits with IVA and CCA decreased at $46.2 billion in IQ2017. Profits from domestic industries decreased at $36.9 billion and profits from nonfinancial business increased at $3.8 billion. Profits from the rest of the world decreased at $9.3 billion. Corporate profits with IVA and CCA increased at $14.4 billion in IIQ2017. Profits from domestic industries increased at $25.2 billion and profits from nonfinancial business increased at $59.1 billion. Profits from the rest of the world decreased at $10.8 billion. Corporate profits with IVA and CCA increased at $90.3 billion in IIIQ2017. Profits from domestic industries increased at $58.2 billion and profits from nonfinancial business increased at $10.4 billion. Profits from the rest of the world increased at $32.0 billion. Total corporate profits with IVA and CCA were $2213.7 billion in IIIQ2017 of which $1766.1 billion from domestic industries, or 79.8 percent of the total, and $447.5 billion, or 20.2 percent, from the rest of the world. Nonfinancial corporate profits of $1276.7 billion account for 57.7 percent of the total. Third, there is reduction in the use of corporate cash for investment. Vipal Monga, David Benoit and Theo Francis, writing on “Companies send more cash back to shareholders,” published on May 26, 2015 in the Wall Street Journal (http://www.wsj.com/articles/companies-send-more-cash-back-to-shareholders-1432693805?tesla=y), use data of a study by Capital IQ conducted for the Wall Street Journal. This study shows that companies in the S&P 500 reduced investment in plant and equipment to median 29 percent of operating cash flow in 2013 from 33 percent in 2003 while increasing dividends and buybacks to median 36 percent in 2013 from 18 percent in 2003.

The basic valuation equation that is also used in capital budgeting postulates that the value of stocks or of an investment project is given by:

Where Rτ is expected revenue in the time horizon from τ =1 to T; Cτ denotes costs; and ρ is an appropriate rate of discount. In words, the value today of a stock or investment project is the net revenue, or revenue less costs, in the investment period from τ =1 to T discounted to the present by an appropriate rate of discount. In the current weak economy, revenues have been increasing more slowly than anticipated in investment plans. An increase in interest rates would affect discount rates used in calculations of present value, resulting in frustration of investment decisions. If V represents value of the stock or investment project, as ρ → ∞, meaning that interest rates increase without bound, then V → 0, or

declines. Equally, decline in expected revenue from the stock or project, Rτ, causes decline in valuation.

An intriguing issue is the difference in performance of valuations of risk financial assets and economic growth and employment. Paul A. Samuelson (http://www.nobelprize.org/nobel_prizes/economics/laureates/1970/samuelson-bio.html) popularized the view of the elusive relation between stock markets and economic activity in an often-quoted phrase “the stock market has predicted nine of the last five recessions.” In the presence of zero interest rates forever, valuations of risk financial assets are likely to differ from the performance of the overall economy. The interrelations of financial and economic variables prove difficult to analyze and measure.

Appendix on the Monetary History of Brazil. According to an influential school of thought, the interrelation of growth and inflation in Latin America is complex, preventing analysis of whether inflation promotes or restricts economic growth (Seers 1962, 191). In this view, there are multiple structural factors of inflation. Successful economic policy requires a development program that ameliorates structural weaknesses. Policy measures in developed countries are not transferable to developing economies.

In extensive research and analysis, Kahil (1973) finds no evidence of the role of structural factors in Brazilian inflation from 1947 to 1963. In fact, Kahil (1973, 329) concludes:

“The immediate causes of the persistent and often violent rise in prices, with which Brazil was plagued from the last month of 1948 to the early months of 1964, are pretty obvious: large and generally growing public deficits, together with too rapid an expansion of bank credit in the first years and, later, exaggerated and more and more frequent increases in the legal minimum wages.”

Kahil (1973, 334) analyzes the impact of inflation on the economy and society of Brazil:

“The real incomes of the various social classes alternately suffered increasingly frequent and sharp fluctuations: no sooner had a group succeeded in its struggle to restore its real income to some previous peak than it witnessed its erosion with accelerated speed; and it soon became apparent to all that the success of any important group in raising its real income, through government actions or by other means, was achieved only by reducing theirs. Social harmony, the general climate of euphoria, and also enthusiasm for government policies, which had tended to prevail until the last months of 1958, gave way in the following years of galloping inflation to intense political and social conflict and to profound disillusionment with public policies. By 1963 when inflation reached its runaway stage, the economy had ceased to grow, industry and transport were convulsed by innumerable strikes, and peasants were invading land in the countryside; and the situation further worsened in the first months of 1964.”

Professor Nathiel H. Leff (1975) at Columbia University identified another important contribution of Kahil (1975, Chapter IV “The supply of capital,” 127-185) of key current relevance to current proposals to promote economic growth and employment by raising inflation targets:

“Contrary to the assertions of some earlier writers on this topic, Kahil concludes that inflation did not lead to accelerated capital formation in Brazil.”

In econometric analysis of Brazil’s inflation from 1947 to 1980, Barbosa (1987) concludes:

“The most important result, based on the empirical evidence presented here, is that in the long run inflation is a monetary phenomenon. It follows that the most challenging task for Brazilian society in the near future is to shape a monetary-fiscal constitution that precludes financing much of the budget deficits through the inflation tax.”

Experience with continuing fiscal deficits and money creation tend to show accelerating inflation. Table III-10 provides average yearly rates of growth of two definitions of the money stock, M1, and M2 that adds also interest-paying deposits. The data were part of a research project on the monetary history of Brazil using the NBER framework of Friedman and Schwartz (1963, 1970) and Cagan (1965) as well as the institutional framework of Rondo E. Cameron (1967, 1972) who inspired the research (Pelaez 1974, 1975, 1976a,b, 1977, 1979, Pelaez and Suzigan 1978, 1981). The data were also used to test the correct specification of money and income following Sims (1972; see also Williams et al. 1976) as well as another test of orthogonality of money demand and supply using covariance analysis. Sims (1972, 541) finds that: “If and only if causality runs one way from current and past values of some list of exogenous variables to a given endogenous variable, then in a regression of the endogenous variable on past, current, and future values of the exogenous variables, the future values of the exogenous variables should have zero coefficients.” The objective of research was to verify the quantity theory of money of Friedman and Schwartz (1963, 1970) for the economy of Brazil from 1862 to 1976. The Granger-Sims test postulates that causality runs from money into nominal income if and only if in a regression of nominal income on past, current and future values of money, future coefficients are zero. The results show that the Sims F coefficients are zero for the regressions of nominal income on money and 38 for the coefficients of money on income (Pelaez and Suzigan 1978, Pelaez 1979, 106). There also covariance tests verifying orthogonality of money demand and money supply and orthogonality of base money and the money multiplier. The quantity theory of money explains money, income and prices in the historical period of Brazil 1862 to 1976. There are two important conclusions.

  • Models of Keynesian multipliers in historical Brazil are inconsistent with these findings
  • Pelaez (1979, 121) concludes following Friedman that for the case of Brazil “in historical perspective, it appears that a system of rules, instead of authorities, would have best promoted the interests of the Nation.”

Hill (2007, 763) develops “a simple parametric recursion for VAR coefficients that, for trivariate processes with one scalar auxiliary variable, always allows for sequential linear parametric conditions for non-causality up to horizon h ≥ 1. An empirical analysis of the money-income relationship reveals significant evidence in favor of linear causation of money to income, either directly when we control for cointegration, or indirectly after a delay of 1-3 months in models of first differences.” Shikida, Araujo Jr. and Figueiredo (2014) apply Hill (2007) to the historical experience of Brazil. They conclude that base money influences nominal output but not real output. Their results are consistent with the unpleasant monetarist arithmetic of Sargent and Wallace (1981) that uses base money instead of the stock of money. Because of restrictions on banking and finance (Summerhill 2015, Pelaez 1975), base money should have been more important in influencing nominal income in historical Brazil. It is still valid to conclude that monetary policy rules instead of discretionary authorities would have best promoted national interests in historical Brazil.

The average yearly rates of inflation are high for almost any period in 1861-1970, even when prices were declining at 1 percent in 19th century England, and accelerated to 27.1 percent in 1945-1970. There may be concern in an uncontrolled deficit monetized by sharp increases in base money. The Fed may have desired to control inflation at 2 percent after lowering the fed funds rate to 1 percent in 2003 but inflation rose to 4.1 percent in 2007. There is not “one hundred percent” confidence in controlling inflation because of the lags in effects of monetary policy impulses and the equally important lags in realization of the need for action and taking of action and also the inability to forecast any economic variable. Romer and Romer (2004) find that a one percentage point tightening of monetary policy is associated with a 4.3 percent decline in industrial production. There is no change in inflation in the first 22 months after monetary policy tightening when it begins to decline steadily, with decrease by 6 percent after 48 months (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 102). Even if there were one hundred percent confidence in reducing inflation by monetary policy, it could take a prolonged period with adverse effects on economic activity. Certainty does not occur in economic policy, which is characterized by costs that cannot be anticipated.

Table III-10, Brazil, Yearly Growth Rates of M1, M2, Nominal Income (Y), Real Income (y), Real Income per Capita (y/n) and Prices (P)

M1

M2

Y

y

y/N

P

1861-1970

9.3

6.2

10.2

4.6

2.4

5.8

1861-1900

5.4

5.9

5.9

4.4

2.6

1.6

1861-1913

4.7

4.7

5.3

4.4

2.4

0.1

1861-1929

5.5

5.6

6.4

4.3

2.3

2.1

1900-1970

13.9

13.9

15.2

4.9

2.6

10.3

1900-1929

8.9

8.9

10.8

4.2

2.1

6.6

1900-1945

8.6

9.1

9.2

4.3

2.2

4.9

1920-1970

17.8

17.3

19.4

5.3

2.8

14.1

1920-1945

8.3

8.7

7.5

4.3

2.2

3.2

1920-1929

5.4

6.9

11.1

5.3

3.3

5.8

1929-1939

8.9

8.1

11.7

6.3

4.1

5.4

1945-1970

30.3

29.2

33.2

6.1

3.1

27.1

Note: growth rates are obtained by regressions of the natural logarithms on time. M1 and M2 definitions of the money stock; Y nominal GDP; y real GDP; y/N real GDP per capita; P prices.

Source: See Pelaez and Suzigan (1978), 143; M1 and M2 from Pelaez and Suzigan (1981); money income and real income from Contador and Haddad (1975) and Haddad (1974); prices by the exchange rate adjusted by British wholesale prices until 1906 and then from Villela and Suzigan (1973); national accounts after 1947 from Fundação Getúlio Vargas.

Chart III-1 shows in semi-logarithmic scale from 1861 to 1970 in descending order two definitions of income velocity, money income, M1, M2, an indicator of prices and real income.

Chart III-1, Brazil, Money, Income and Prices 1861-1970.

Source: © Carlos Manuel Pelaez and Wilson Suzigan. 1981. História Monetária do Brasil Segunda Edição. Coleção Temas Brasileiros. Brasília: Universidade de Brasília, 21.

Table III-11 provides yearly percentage changes of GDP, GDP per capita, base money, prices and the current account in millions of dollars during the acceleration of inflation after 1947. There was an explosion of base money or the issue of money and three waves of inflation identified by Kahil (1973). Inflation accelerated together with issue of money and political instability from 1960 to 1964. There must be a role for expectations in inflation but there is not much sound knowledge and measurement as Rajan (2012May8) argues. There have been inflation waves documented in periodic comments in this blog (http://cmpassocregulationblog.blogspot.com/2016/12/of-course-economic-outlook-is-highly.html and earlier http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html). The risk is ignition of adverse expectations at the crest of one of worldwide inflation waves. Lack of credibility of the commitment by the FOMC to contain inflation could ignite such perverse expectations. Deficit financing of economic growth can lead to inflation and financial instability.

Table III-11, Brazil, GDP, GDP per Capita, Base Money, Prices and Current Account of the Balance of Payments, ∆% and USD Millions, 1947-1971

GDP

∆%

GDP per Capita

∆%

Base Money

∆%

Prices

∆%

Current
Account BOP

USD Millions

1947

2.4

0.1

-1.4

14.0

162

1948

7.4

4.9

4.6

7.6

-24

1949

6.6

4.2

14.5

4.0

-74

1950

6.5

4.0

23.0

10.0

52

1951

5.9

2.9

15.3

21.9

-291

1952

8.7

5.6

17.7

10.2

-615

1953

2.5

-0.5

15.5

12.1

16

1954

10.1

6.9

23.4

31.0

-203

1955

6.9

3.8

18.0

14.0

17

1956

3.2

0.2

16.9

21.6

194

1957

8.1

4.9

30.5

13.9

-180

1958

7.7

4.6

26.1

10.4

-253

1959

5.6

2.5

32.3

37.7

-154

1960

9.7

6.5

42.4

27.6

-410

1961

10.3

7.1

54.4

36.1

115

1962

5.3

2.2

66.4

54.1

-346

1963

1.6

-1.4

78.4

75.2

-244

1964

2.9

-0.1

82.5

89.7

40

1965

2.7

-0.6

67.6

62.0

331

1966

4.4

1.5

25.8

37.9

153

1967

4.9

2.0

33.9

28.7

-245

1968

11.2

8.1

31.4

25.2

32

1969

9.9

6.9

22.4

18.2

549

1970

8.9

5.8

20.2

20.7

545

1971

13.3

10.2

29.8

22.0

530

Sources: Fundação Getúlio Vargas, Banco Central do Brasil and Pelaez and Suzigan (1981). Carlos Manuel Pelaez, História Econômica do Brasil: Um Elo entre a Teoria e a Realidade Econômica. São Paulo: Editora Atlas, 1979, 94.

II B. United States Net International Investment Position. The current account of the US balance of payments is in Table VI-3A for IIIQ2016 and IIIQ2017. The Bureau of Economic Analysis analyzes as follows (https://www.bea.gov/newsreleases/international/transactions/2017/pdf/trans317.pdf):

“The U.S. current-account deficit decreased to $100.6 billion (preliminary) in the third quarter of 2017 from $124.4 billion (revised) in the second quarter of 2017, according to statistics released by the Bureau of Economic Analysis (BEA). The deficit decreased to 2.1 percent of current-dollar gross domestic product (GDP) from 2.6 percent in the second quarter. The $23.8 billion decrease in the current-account deficit reflected decreases in the deficits on secondary income and goods and increases in the surpluses on primary income and services.”

The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US not seasonally adjusted decreased from $126.0 billion in IIIQ2016 to $112.8 billion in IIIQ2017. The current account deficit seasonally adjusted at annual rate increased from 2.4 percent of GDP in IIIQ2016 to 2.6 percent of GDP in IIQ2017, decreasing to 2.1 percent of GDP in IIIQ2017. 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). There is still a major challenge in the combined deficits in current account and in federal budgets.

Table VI-3A, US, Balance of Payments, Millions of Dollars NSA

IIIQ2016

IIIQ2017

Difference

Goods Balance

-203,022

-211,273

-8,251

X Goods

364,117

382,172

5.0 ∆%

M Goods

-567,139

-593,444

4.6 ∆%

Services Balance

66,707

64,279

-2,428

X Services

197,136

200,710

1.8 ∆%

M Services

-130,429

-136,431

4.6 ∆%

Balance Goods and Services

-136,315

-146,994

-10,679

Exports of Goods and Services and Income Receipts

802,389

861,331

Imports of Goods and Services and Income Payments

-928,421

-974,147

Current Account Balance

-126,032

-112,816

-13,216

% GDP

IIIQ2016

IIIQ2017

IIQ2017

2.4

2.1

2.6

X: exports; M: imports

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

Source: Bureau of Economic Analysis

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

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

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

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

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

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

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

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

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

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

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

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

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

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

(Mt + Bt)/Pt = Et∫(1/Rt, t+τ)st+τdτ (4)

Equation (4) expresses the monetary, Mt, and debt, Bt, liabilities of the government, divided by the price level, Pt, in terms of the expected value discounted by the ex-post rate on government debt, Rt, t+τ, of the future primary surpluses st+τ, which are equal to Tt+τ – Gt+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 Rt, t+τ. The second equation of Cochrane (2011Jan, 5) is:

MtV(it, ·) = PtYt (5)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Table VI-3B 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.”

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

85

130

115

168

211

Secondary Income

-91

-102

-104

-104

-107

Current Account

-711

-681

-373

-431

-445

NGDP

14478

14719

14419

14964

15518

Current Account % GDP

-4.9

-4.6

-2.6

-2.9

-2.9

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

2559

2742

2283

2625

2983

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

2016

Goods &
Services

-537

-462

-490

-500

-505

Primary Income

207

206

210

181

173

Secondary Income

-97

-94

-94

-115

-120

Current Account

-426

-350

-374

-434

-452

NGDP

16155

16692

17428

18121

18625

Current Account % GDP

-2.6

-2.1

-2.1

-2.4

-2.4

NIIP

-4518

-5373

-6980

-7493

-8318

US Owned Assets Abroad

22562

24145

24832

23352

23849

Foreign Owned Assets in US

27080

29517

31813

30846

32168

NIIP % GDP

-28.0

-32.2

-40.1

-41.3

-44.7

Exports
Goods,
Services and
Income

3096

3212

3333

3173

3157

NIIP %
Exports
Goods,
Services and
Income

-146

-167

-209

-236

-263

DIA MV

5969

7121

7189

6999

7375

DIUS MV

4662

5815

6370

6701

7569

Fiscal Balance

-1087

-680

-485

-439

-585

Fiscal Balance % GDP

-6.8

-4.1

-2.8

-2.4

-3.2

Federal   Debt

11281

11983

12780

13117

14168

Federal Debt % GDP

70.4

72.6

74.2

73.3

77.0

Federal Outlays

3537

3455

3506

3688

3853

∆%

-1.8

-2.3

1.5

5.2

4.5

% GDP

22.1

20.9

20.4

20.6

20.9

Federal Revenue

2450

2775

3022

3250

3268

∆%

6.4

13.3

8.9

7.6

0.5

% GDP

15.3

16.8

17.5

18.2

17.8

Sources:

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

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

https://www.cbo.gov/about/products/budget_economic_data#3

https://www.cbo.gov/about/products/budget-economic-data#2

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

The most recent CBO long-term budget on Mar 27, 2017, projects US federal debt at 150.0 percent of GDP in 2047 (Congressional Budget Office, The 2017 Long-term Budget Outlook. Washington, DC, Mar 30, 2017 https://www.cbo.gov/publication/52480).

Table VI-3C provides quarterly estimates NSA of the external imbalance of the United States. The current account deficit seasonally adjusted at 2.4 percent in IIIQ2016 stabilizes to 2.4 percent of GDP in IVQ2016. The deficit does not change to 2.4 percent in IQ2017 and increases to 2.6 percent in IIQ2017. The current account deficits decreased to 2.1 percent in IIIQ2017. The absolute value of the net international investment position increases from minus $8.0 trillion in IIIQ2016 to minus $8.3 trillion in IVQ2016. The absolute value of the net international investment position decreases to minus $8.1 trillion in IQ2017 and decreases to minus $8.0 trillion in IIQ2017. The absolute value of the net international investment position decreased to $7.8 trillion in IIIQ2017. The BEA explains as follows (https://www.bea.gov/newsreleases/international/intinv/2017/pdf/intinv217.pdf):

“The U.S. net international investment position increased to -$7,768.7 billion (preliminary) at the end of the third quarter of 2017 from -$8,004.1 billion (revised) at the end of the second quarter, according to statistics released today by the Bureau of Economic Analysis (BEA). The $235.4 billion increase reflected a $1,001.2 billion increase in U.S. assets and a $765.8 billion increase in U.S. liabilities (table 1).”

The BEA explains further (https://www.bea.gov/newsreleases/international/intinv/2017/pdf/intinv317.pdf): “

“The $235.4 billion increase in the net investment position reflected net financial transactions of –$87.4 billion and net other changes in position, such as price and exchange-rate changes, of $322.8 billion (table A).

The net investment position increased 2.9 percent in the third quarter, compared with an increase of 1.1 percent in the second quarter, and an average quarterly decrease of 5.3 percent from the first quarter of 2011 through the first quarter of 2017.

U.S. assets increased $1,001.2 billion to $26,854.9 billion at the end of the third quarter, mostly reflecting increases in portfolio investment and direct investment assets that were partly offset by a decrease in financial derivatives.

· Assets excluding financial derivatives increased $1,227.5 billion to $25,149.7 billion. The increase resulted from other changes in position of $869.2 billion and financial transactions of $358.2 billion. Other changes in position mostly reflected foreign equity price increases that raised the equity value of portfolio investment and direct investment assets, and the appreciation of major foreign currencies against the U.S. dollar that raised the value of foreign-currency-denominated assets in dollar terms. Financial transactions mostly reflected net acquisition of portfolio investment assets.

· Financial derivatives decreased $226.2 billion to $1,705.1 billion, mostly in single-currency interest rate contracts.”

U.S. liabilities increased $765.8 billion to $34,623.6 billion at the end of the third quarter, mostly reflecting increases in portfolio investment and direct investment liabilities that were partly offset by a decrease in financial derivatives.

· Liabilities excluding financial derivatives increased $988.8 billion to $32,952.3 billion. The increase resulted from other changes in position of $524.6 billion and financial transactions of $464.2 billion (table A). Other changes in position mostly reflected U.S. equity price increases that raised the equity value of portfolio investment and direct investment liabilities. Financial transactions mostly reflected net incurrence of portfolio investment liabilities.

· Financial derivatives decreased $223.0 billion to $1,671.3 billion, mostly in single-currency interest rate contracts.”

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

IIIQ2016

IVQ2016

IQ2017

IIQ2017

IIIQ2017

Goods &
Services

-136

-132

-113

-155

-147

Primary

Income

43

51

49

51

58

Secondary Income

-32

-31

-26

-31

-24

Current Account

-126

-112

-90

-134

-113

Current Account % GDP

-2.4

-2.4

-2.4

-2.6

-2.1

NIIP

-8036

-8318

-8092

-8004

-7769

US Owned Assets Abroad

24839

23849

24933

25853

26855

Foreign Owned Assets in US

-32875

-32168

-33025

-33857

-34623

DIA MV

7392

7375

7895

8125

8581

DIA MV Equity

6147

6172

6609

6909

7355

DIUS MV

7424

7569

7952

8135

8453

DIUS MV Equity

5607

5784

6153

6341

6630

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

Chart VI-3C of the US Bureau of Economic Analysis provides the quarterly and annual US net international investment position (NIIP) NSA in billion dollars. The NIIP deteriorated in 2008, improving in 2009-2011 followed by deterioration after 2012. There is improvement in 2017.

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

Source: Bureau of Economic Analysis

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

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018.

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