CMP Associates Regulation Blog: Thirty Million Unemployed or Underemployed, Stagnating Real Wages, Theory and Reality of Economic History, Deflation and Unconventional Monetary Policy, American Taxpayer Relief Act of 2012 with United States Threatening Risk Premium on Government Debt, World Financial Turbulence and Economic Slowdown with Global Recession Risk: Part I

Thirty Million Unemployed or Underemployed, Stagnating Real Wages, Theory and Reality of Economic History, Deflation and Unconventional Monetary Policy, American Taxpayer Relief Act of 2012 with United States Threatening Risk Premium on Government Debt, World Financial Turbulence and Economic Slowdown with Global Recession Risk

Carlos M. Pelaez

Executive Summary

IA Thirty 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

IA5 Stagnating Real Wages

IB Collapse of United States Dynamism of Income Growth and Employment Creation

IIA Theory and Reality of Economic History, Deflation and Unconventional Monetary Policy

IIB American Taxpayer Relief Act of 2012 and United States Threatening Risk Premium on Government Debt

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

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

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during

Executive Summary

ESI Thirty Million Unemployed or Underemployed. Table ESI-1 consists of data and additional calculations using the BLS household survey, illustrating the possibility that the actual rate of unemployment could be 11.6 percent and the number of people in job stress could be around 29.5 million, which is 18.2 percent of the 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 Dec 2011, Nov 2012 and Dec 2012 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 (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). Table ESI-1b provides the yearly labor force participation rate from 1979 to 2012. The objective of Table ESI-1 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 Nov and Dec 2012 and Dec 2011 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 63.8 percent by Dec 2011 and was 63.5 percent in Nov 2012 and 63.4 percent in Dec 2012, 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: (1) there are an estimated 6.856 million unemployed in Dec 2012 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM); (2) the total number of unemployed is effectively 18.700 million (Total UEM) and not 11.844 million (UEM) of whom many have been unemployed long term; (3) the rate of unemployment is 11.6 percent (Total UEM%) and not 7.6 percent, not seasonally adjusted, or 7.8 percent seasonally adjusted; and (4) the number of people in job stress is close to 29.5 million by adding the 6.856 million leaving the labor force because they believe they could not find another job. The row “In Job Stress” in Table ESI-1 provides the number of people in job stress not seasonally adjusted at 29.5 million in Dec 2012, 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 ESI-1 shows that the number of people in job stress is equivalent to 18.2 percent of the labor force in Dec 2012. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 58.5 percent in Dec 2011, 58.8 percent in Nov 2012 and 58.5 percent in Dec 2012; the number employed (EMP) dropped from 144 million in 2006 to 143.060 million in Dec 2012 while population increased from 229.420 million in Sep 2006 to 244.350 million in Dec 2012 or by 14.930 million. The number employed in the US fell from 146.743 million in Oct 2007 to 143.060 million in Dec 2012, by 3.683 million, or 2.5 percent, while the noninstitutional population increased from 232.715 million in Oct 2007 to 244.350 million in Dec 2012, by 11.635 million or increase of 5.0 percent, using not seasonally adjusted data. What really matters for labor input in production and wellbeing is the number of people with jobs or the employment/population ratio, which has declined and does not show signs of increasing. There are several million fewer people working in 2012 than in 2006 and the number employed is not increasing while population increased 14.930 million. 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 17 million and does not show signs of increasing in an unusual recovery without hiring (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html).

Table ESI-1, US, Population, Labor Force and Unemployment, NSA

	2006	Dec 2011	Nov 2012	Dec 2012
POP	229	240,584	244,174	244,350
LF	151	153,373	154,953	154,904
PART%	66.2	63.8	63.5	63.4
EMP	144	140,681	143,549	143,060
EMP/POP%	62.9	58.5	58.8	58.5
UEM	7	12,692	11,404	11,844
UEM/LF Rate%	4.6	8.3	7.4	7.6
NLF	77	87,212	89,221	89,445
LF PART 66.2%		159,267	161,643	161,760
∆NLF UEM		5,894	6,690	6,856
Total UEM		18,586	18,094	18,700
Total UEM%		11.7	11.2	11.6
Part Time Economic Reasons		8,428	7,994	8,166
Marginally Attached to LF		2,540	2,505	2,614
In Job Stress		29,554	28,593	29,480
People in Job Stress as % Labor Force		18.6	17.7	18.2

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

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

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

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

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

Y = ∑_is_iy_i (1)

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

∆Y = ∑_i∆s_iy*_i+ ∑_i∆y_is*_i (2)

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

“The analysis in this paper and in others that we review do not provides 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 ESI-1b and Chart ESI-1 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 63.4 percent in Dec 2012. 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 ESI-1. 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 of their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors.

Table ESI-1b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2012

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

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

Chart ESI-1, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2012

Source: Bureau of Labor Statistics

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

Broader perspective is provided by Chart ESI-2 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 ESI-2, US, Civilian Population, Thousands, NSA, 1948-2012

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

The labor force of the United States in Chart ESI-3 has increased along a trend similar to that of the civilian noninstitutional population in Chart ESI-3. There is an evident stagnation of the civilian labor force in the final segment of Chart ESI-3 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 ESI-3, US, Labor Force, Thousands, NSA, 1947-2012

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

ESII Permanent Failure of United States Labor Markets. Total nonfarm payroll employment seasonally adjusted (SA) increased 155,000 in Dec 2012 and private payroll employment rose 168,000, as shown in Table ESII-1. The number of nonfarm jobs and private jobs created has been declining in 2012 from 275,000 in Jan 2012 to 45,000 in Jun, 132,000 in Sep, 137,000 in Oct, 161,000 in Nov and 155,000 in Dec 2012 for total nonfarm jobs and from 277,000 in Jan 2012 to 63,000 in Jun, 122,000 in Sep, 203,000 in Oct, 171,000 in Nov and 168,000 in Dec 2012 for private jobs. Average new nonfarm jobs in the quarter Dec 2011 to Feb 2012 were 252,333 per month, declining to average 130,100 per month in the ten months from Mar to Dec 2012. Average new private jobs in the quarter Dec 2011 to Feb 2012 were 255,000 per month, declining to average 137,200 per month in the ten months from Mar 2012 to Dec 2012. The US labor force stood at 154.088 million in Oct 2011 and at 155.779 million in Oct 2012, not seasonally adjusted, for increase of 1.691 million, or 140,917 per month. The US labor force stood at 153.683 million in Nov 2011 and 154.953 million in Nov 2012, not seasonally adjusted, for increase of 1.270 million or 105,833 per month. The US labor force stood at 153.373 million in Dec 2011 and 154.904 million in Dec 2012, not seasonally adjusted, for increase of 1.531 million or 127,583 per month. The average increase of 130,100 new nonfarm jobs per month in the US from Mar to Dec 2012 is insufficient even to absorb 127,583 new entrants per month into the labor force. The difference between the average increase of 137,200 new private nonfarm jobs per month in the US from Mar to Dec 2012 and the 127,583 average monthly increase in the labor force from Nov 2011 to Nov 2012 is 9,617 monthly new jobs net of absorption of new entrants in the labor force. There are 29.6 million in job stress in the US currently. The provision of 9,617 new jobs per month net of absorption of new entrants in the labor force would require 3078 months to provide jobs for the unemployed and underemployed (29.6 million divided by 9,617) or 256 years (3078 divided by 12). Net job creation of 9,617 jobs per month only adds 115,404 jobs in a year. The civilian labor force of the US in Dec 2012 not seasonally adjusted stood at 154.904 million with 11.844 million unemployed or effectively 18.700 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 8.7 years (1 million divided by product of 9,617 by 12, which is 115,404). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.745 million (0.05 times labor force of 154.904 million) for new net job creation of 4.099 million (11.844 million unemployed minus 7.745 million unemployed at rate of 5 percent) that at the current rate would take 35.5 years (4.099 million divided by 115,404). Under the calculation in this blog there are 18.700 million unemployed by including those who ceased searching because they believe there is no job for them. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 10.612 million jobs net of labor force growth that at the current rate would take 91.9 years (18.700 million minus 0.05(161.760 million) divided by 115,404, using LF PART 66.2% and Total UEM in Table ESI-1). 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 the US fell from 146.743 million in Oct 2007 to 143.060 million in Dec 2012, by 3.683 million, or 2.5 percent, while the noninstitutional population increased from 232.715 million in Oct 2007 to 244.350 million in Dec 2012, by 11.635 million or increase of 5.0 percent, using not seasonally adjusted data. There is actually not sufficient job creation to merely absorb 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. What is striking about the data in Table ESII-1 is that the numbers of monthly increases in jobs in 1983 and 1984 are several times higher than in 2010 to 2011 even with population higher by 35.4 percent and labor force higher by 38.1 percent in 2009 relative to 1983 nearly three decades ago and total number of jobs in payrolls rose by 39.5 million in 2010 relative to 1983 or by 43.8 percent. Growth at 2.2 percent has been mediocre in the thirteen quarters of expansion beginning in IIIQ2009 in comparison with 6.2 percent in earlier expansions (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html) and also in terms of what is required to reduce the job stress of at around 24 million persons but likely close to 30 million. Some of the job growth and contraction in 2010 in Table ESII-1 is caused by the hiring and subsequent layoff of temporary workers for the 2010 census.

Table ESII-1, US, Monthly Change in Jobs, Number SA

Month	1981	1982	1983	2008	2009	2010	Private
Jan	95	-327	225	41	-818	-40	-40
Feb	67	-6	-78	-84	-724	-35	-27
Mar	104	-129	173	-95	-799	189	141
Apr	74	-281	276	-208	-692	239	193
May	10	-45	277	-190	-361	516	84
Jun	196	-243	378	-198	-482	-167	92
Jul	112	-343	418	-210	-339	-58	92
Aug	-36	-158	-308	-274	-231	-51	128
Sep	-87	-181	1114	-432	-199	-27	115
Oct	-100	-277	271	-489	-202	220	196
Nov	-209	-124	352	-803	-42	121	134
Dec	-278	-14	356	-661	-171	120	140
			1984			2011	Private
Jan			447			110	119
Feb			479			220	257
Mar			275			246	261
Apr			363			251	264
May			308			54	108
Jun			379			84	102
Jul			312			96	175
Aug			241			85	52
Sep			311			202	216
Oct			286			112	139
Nov			349			157	178
Dec			127			223	234
			1985			2012	Private
Jan			266			275	277
Feb			124			259	254
Mar			346			143	147
Apr			195			68	85
May			274			87	116
Jun			145			45	63
Jul			189			181	163
Aug			193			192	134
Sep			204			132	122
Oct			187			137	203
Nov			209			161	171
Dec			168			155	168

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

ESIII Stagnating Real Wages. Calculations using BLS data of inflation-adjusted average hourly earnings are shown in Table ESIII-1. The final column of Table ESIII-1 (“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 lost 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 0.9 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 0.6 percent in the 12 months ending in Oct 2012. Real hourly earnings fell 1.3 percent in Oct 2012 and 0.1 percent in Dec 2012. Real hourly earnings are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html).

Table ESIII-1, US, Average Hourly Earnings Nominal and Inflation Adjusted, Dollars and % NSA

	AHE ALL	12 Month Nominal ∆%	∆% 12 Month CPI	12 Month Real ∆%
2007
Jan*	$20.70*	4.2*	2.1	2.1*
Feb*	$20.79*	4.1*	2.4	1.7*
Mar	$20.82	3.7	2.8	0.9
Apr	$21.05	3.3	2.6	0.7
May	$20.83	3.7	2.7	1.0
Jun	$20.82	3.8	2.7	1.1
Jul	$20.99	3.4	2.4	1.0
Aug	$20.85	3.5	2.0	1.5
Sep	$21.18	4.0	2.8	1.2
Oct	$21.07	2.7	3.5	-0.8
Nov	$21.13	3.3	4.3	-0.9
Dec	$21.37	3.7	4.1	-0.4
2010
Jan	$22.55	2.0	2.6	-0.6
Feb	$22.61	1.4	2.1	-0.7
Mar	$22.51	1.2	2.3	-1.1
Apr	$22.56	1.8	2.2	-0.4
May	$22.63	2.5	2.0	0.5
Jun	$22.37	1.7	1.1	0.6
Jul	$22.44	1.8	1.2	0.6
Aug	$22.58	1.7	1.1	0.6
Sep	$22.63	1.8	1.1	0.7
Oct	$22.73	1.9	1.2	0.7
Nov	$22.72	1.1	1.1	0.0
Dec	$22.79	1.7	1.5	0.2
2011
Jan	$23.20	2.9	1.6	1.3
Feb	$23.03	1.9	2.1	-0.2
Mar	$22.93	1.9	2.7	-0.8
Apr	$23.00	2.0	3.2	-1.2
May	$23.09	2.0	3.6	-1.5
Jun	$22.85	2.1	3.6	-1.4
Jul	$22.98	2.4	3.6	-1.2
Aug	$22.88	1.3	3.8	-2.4
Sep	$23.09	2.0	3.9	-1.8
Oct	$23.34	2.7	3.5	-0.8
Nov	$23.19	2.1	3.4	-1.3
Dec	$23.26	2.1	3.0	-0.9
2012
Jan	$23.61	1.8	2.9	-1.1
Feb	$23.45	1.8	2.9	-1.1
Mar	$23.41	2.1	2.7	-0.6
Apr	$23.64	2.8	2.3	0.5
May	$23.35	1.1	1.7	-0.6
Jun	$23.30	2.0	1.7	0.3
Jul	$23.52	2.3	1.4	0.9
Aug	$23.30	1.8	1.7	0.1
Sep	$23.70	2.6	2.0	0.6
Oct	$23.55	0.9	2.2	-1.3
Nov	$23.59	1.7	1.8	-0.1
Dec	$23.87	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/data/

Average hourly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are provided in Table ESIII-2. Average hourly earnings fell 0.5 percent after adjusting for inflation in the 12 months ending in Mar 2012 and gained 0.4 percent in the 12 months ending in Apr 2011 but then lost 0.6 percent in the 12 months ending in May 2012 with a gain of 0.3 percent in the 12 months ending in Jun 2012 and 1.0 percent in Jul 2012 followed by 0.1 percent in Aug 2012 and 0.6 percent in Sep 2012. Average hourly earnings adjusted by inflation fell 1.3 percent in the 12 months ending in Oct 2012 and were unchanged in the 12 months ending in Nov 2012. Table ESIII-2 confirms the trend of deterioration of purchasing power of average hourly earnings in 2011 and into 2012 with 12-month percentage declines in three of the first four months of 2012 (-1.0 percent in Jan, -1.1 percent in Feb and -0.5 percent in Mar), declines of 0.6 percent in May and 1.3 percent in Oct and increase in four (0.4 percent in May, 0.3 percent in Jun, 1.0 percent in Jul, 0.6 percent in Sep) and stagnation in two (0.1 percent in Aug and 0.0 percent in Nov). Those who still work bring back home a paycheck that buys fewer goods than a year earlier and savings in bank deposits do not pay anything because of financial repression (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html).

Table ESIII-2, US, Average Hourly Earnings of All Employees NSA in Constant Dollars of 1982-1984

Year	May	Jun	Jul	Aug	Sep	Oct	Nov
2006	9.92	9.88	9.97	9.88	10.03	10.17	10.15
2007	10.02	9.99	10.08	10.03	10.16	10.08	10.05
2008	9.91	9.84	9.77	9.83	9.94	10.06	10.37
2009	10.32	10.20	10.23	10.29	10.30	10.32	10.39
2010	10.37	10.26	10.29	10.34	10.36	10.39	10.38
2011	10.22	10.12	10.17	10.10	10.18	10.31	10.25
2012	10.16	10.15	10.27	10.11	10.24	10.18	10.25
∆% 12 Months	-0.6	0.3	1.0	0.1	0.6	-1.3	0.0

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

The deterioration of purchasing power of average hourly earnings of US workers is shown by Chart ESIII-1 of the US Bureau of Labor Statistics. Chart ESIII-1 plots average hourly earnings of all US employees in constant 1982-1984 dollars with evident decline from 2010 to 2012.

Chart ESIII-1, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Chart ESIII-2 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 now 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 and marginal gain in Sep 2012 with sharp decline in Oct 2012 and stagnation in Nov 2012.

Chart ESIII-2, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2012

Source: US Bureau of Labor Statistics

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

Average weekly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are provided in Table ESIII-3. 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, increased 0.9 percent in the 12 months ending in Oct, fell 0.7 percent in the 12 months ending in Nov and 0.3 in the 12 months ending in Dec 2011, declining 0.3 percent in the 12 months ending in Jan 2012 and 0.4 percent in the 12 months ending in Feb 2012. Average weekly earnings in constant dollars were flat in Mar 2012 relative to Mar 2011. Average weekly earnings in constant dollars increased 1.6 percent in Apr 2012 relative to Apr 2011 but fell 1.4 percent in May 2012 relative to May 2011, increasing 0.3 percent in the 12 months ending in Jun and 2.1 percent in Jul 2012. Real weekly earnings increased 0.4 percent in the 12 months ending in Aug 2012 and 2.1 percent in the 12 months ending in Sep 2012. Real weekly earnings fell 2.9 percent in the 12 months ending in Oct 2012 and fell 0.3 percent in the 12 months ending in Nov 2012. Table ESIII-3 confirms the trend of deterioration of purchasing power of average weekly earnings in 2011 and into 2012 with oscillations according to carry trades causing world inflation waves (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html). Those who still work bring back home a paycheck that buys fewer goods than a year earlier. The fractured US job market does not provide an opportunity for advancement as in past booms following recessions.

Table ESIII-3, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, NSA 2007-2012

Year	Jun	Jul	Aug	Sep	Oct	Nov
2006	341.91	347.97	341.76	346.19	354.88	349.12
2007	346.74	351.68	347.98	355.56	347.92	346.85
2008	343.40	337.06	340.18	341.83	345.95	358.83
2009	344.59	345.92	352.80	347.04	348.67	356.43
2010	349.97	352.02	358.90	353.27	356.47	355.12
2011	348.23	349.90	347.42	350.08	359.76	352.62
2012	349.28	357.26	348.93	357.44	349.20	351.46
∆% 12M	0.3	2.1	0.4	2.1	-2.9	-0.3

Source: US Bureau of Labor Statistics

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

Chart ESII-3 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.

Chart ESIII-3, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Chart ESIII-4 provides 12-month percentage changes of average weekly earnings of all employees in the US in constant dollars of 1982-1984. There is the same pattern of contraction during the global recession in 2008 and then again trend of deterioration in the recovery without hiring and inflation waves in 2011 and 2012 (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html).

Chart ESIII-4, US, Average Weekly Earnings of All Employees NSA in Constant Dollars of 1982-1984 12-Month Percent Change, NSA 2007-2012

Source: US Bureau of Labor Statistics

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

ESIV The Theory and Reality of Economic History, Deflation and Unconventional Monetary Policy. Unconventional monetary policy could be defined by continuous symmetric objectives of inflation and the rate of unemployment with policy impulses of highest magnitude. The central bank would operate policy such as to constantly maintain inflation around 2 percent and the rate of unemployment close to the natural rate (Friedman 1968, Phelps 1968) around 5 percent. There are lags in effect of monetary policy impulses, meaning that a policy impulse today may not have all the effects on income and prices until many months in the future (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). Unconventional monetary policy has evolved into a forecast growth mandate.

Charles Evans, President of the Federal Reserve Bank of Chicago, proposed an “economic state-contingent policy” or “7/3” approach (Evans 2012 Aug 27):

“I think the best way to provide forward guidance is by tying our policy actions to explicit measures of economic performance. There are many ways of doing this, including setting a target for the level of nominal GDP. But recognizing the difficult nature of that policy approach, I have a more modest proposal: I think the Fed should make it clear that the federal funds rate will not be increased until the unemployment rate falls below 7 percent. Knowing that rates would stay low until significant progress is made in reducing unemployment would reassure markets and the public that the Fed would not prematurely reduce its accommodation.

Based on the work I have seen, I do not expect that such policy would lead to a major problem with inflation. But I recognize that there is a chance that the models and other analysis supporting this approach could be wrong. Accordingly, I believe that the commitment to low rates should be dropped if the outlook for inflation over the medium term rises above 3 percent.

The economic conditionality in this 7/3 threshold policy would clarify our forward policy intentions greatly and provide a more meaningful guide on how long the federal funds rate will remain low. In addition, I would indicate that clear and steady progress toward stronger growth is essential.”

Evans (2012Nov27) modified the “7/3” approach to a “6.5/2.5” approach:

“I have reassessed my previous 7/3 proposal. I now think a threshold of 6-1/2 percent for the unemployment rate and an inflation safeguard of 2-1/2 percent, measured in terms of the outlook for total PCE (Personal Consumption Expenditures Price Index) inflation over the next two to three years, would be appropriate.”

The Federal Open Market Committee (FOMC) decided at its meeting on Dec 12, 2012 to implement the “6.5/2.5” approach (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm):

“To support continued progress toward maximum employment and price stability, the Committee expects that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the asset purchase program ends and the economic recovery strengthens. In particular, the Committee decided to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that this exceptionally low range for the federal funds rate will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee’s 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored.”

Unconventional monetary policy will remain in perpetuity, or QE∞, changing to a “growth mandate.” There are two reasons explaining unconventional monetary policy of QE∞: insufficiency of job creation to reduce unemployment/underemployment at current rates of job creation; and growth of GDP at 1.7 percent, which is well below 3.0 percent estimated by Lucas (2011May) from 1870 to 2010. Unconventional monetary policy interprets the dual mandate of low inflation and maximum employment as mainly a “growth mandate” of forcing economic growth in the US at a rate that generates full employment. A hurdle to this “growth mandate” is that the US economy grew at 6.2 percent on average during cyclical expansions in the postwar period while growth has been at only 2.2 percent on average in the cyclical expansion in the 13 quarters from IIIQ2009 to IIIQ2012 (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html). Zero interest rates and quantitative easing have not provided the impulse for growth and were not required in past successful cyclical expansions.

First, reduction of the unemployment rate to normal would take between 15 and 43.3 years depending on the definition (http://cmpassocregulationblog.blogspot.com/2012/12/twenty-eight-million-unemployed-or.html). The US labor force stood at 154.088 million in Oct 2011 and at 155.779 million in Oct 2012, not seasonally adjusted, for increase of 1.691 million, or 140,917 per month. The US labor force stood at 153.683 million in Nov 2011 and 154.953 million in Nov 2012, not seasonally adjusted, for increase of 1.270 million or 105,833 per month. The average increase of 125,778 new nonfarm jobs per month in the US from Mar to Oct 2012 is insufficient even to absorb 140,917 new entrants per month into the labor force. The difference between the average increase of 125,778 new nonfarm jobs per month in the US from Mar to Oct 2012 and the 105,833 average monthly increase in the labor force from Nov 2011 to Nov 2012 is 19,945 monthly new jobs net of absorption of new entrants in the labor force. There are 28.6 million in job stress in the US currently. The provision of 19,945 new jobs per month net of absorption of new entrants in the labor force would require 1434 months to provide jobs for the unemployed and underemployed (28.6 million divided by 19,945) or 119 years (1434 divided by 12). Net job creation of 19,945 jobs per month only adds 239,340 jobs in a year. The civilian labor force of the US in Nov 2012 not seasonally adjusted stood at 154.953 million with 11.404 million unemployed or effectively 18.094 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 4.2 years. Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.748 million for new net job creation of 3.656 million that at the current rate would take 15 years. Under the calculation in this blog there are 18.094 million unemployed by including those who ceased searching because they believe there is no job for them. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 10.346 million jobs net of labor force growth that at the current rate would take 43.2 years. These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply.

Second, calculations show that actual US GDP growth is around 1.7 percent per year that will perpetuate unemployment/underemployment (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html). This rate of 1.7 percent is well below trend growth of 3 percent per year from 1870 to 2010, which has been always recovered after events such as wars and recessions (Lucas 2011May). Weakness of growth is shown by the exceptional one-time contributions to growth from items that are not aggregate demand, 2.53 percentage points contributed by inventory change to growth of 4.1 percent in IVQ2011 and 0.64 percentage points contributed by expenditures in national defense together with 0.73 points of inventory accumulation to growth of 3.1 percent in IIIQ2012. Deducting inventory accumulation and one-time national defense expenditures adjusts IIIQ2012 growth to annual 1.73 percent. Cumulative growth of 2.0 percent in IQ2012, 1.3 percent in IIQ2012 and adjusted 1.73 percent in IIIQ2012 annualizes to 1.7 percent in the first three quarters of 2012 {([(1.02)^1/4(1.013)^1/4(1.0173^1/4]^4/3 -1)100 = 1.7%}. The actual rate required to reduce unemployment/underemployment to normal is even higher than 3 percent in historical trend.

In fact, it is evident to the public that this policy will be abandoned if inflation costs rise. There is concern of the production and employment costs of controlling future inflation. Even if there is no inflation QE∞ cannot be abandoned because of the fear of rising interest rates. The economy would operate in an inferior allocation of resources and suboptimal growth path, or interior point of the production possibilities frontier where the optimum of productive efficiency and wellbeing is attained, because of the distortion of risk/return decisions caused by perpetual financial repression. Not even a second-best allocation is feasible with the shocks to efficiency of financial repression in perpetuity.

It may be quite painful to exit QE∞ or use of the balance sheet of the central bank together with zero interest rates forever. 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 R_τ is expected revenue in the time horizon from τ =1 to T; C_τ 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 discount rates increase without bound, then V → 0, or

declines.

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, 10). According to a subsequent restatement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption decisions 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→∞. Equally, as r→∞, W→0. Monetary policy is constrained in a QE∞ trap with all adverse effects of financial repression and resource misallocation because an increase in interest rates causes contraction of wealth, which in the United States is concentrated in home ownership and stocks in own investment portfolios and pension funds that decline during interest rate increases.

Fear of deflation as had occurred during the Great Depression and in Japan was used as an argument for the first round of unconventional monetary policy with 1 percent interest rates from Jun 2003 to Jun 2004 and quantitative easing in the form of withdrawal of supply of 30-year securities by suspension of the auction of 30-year Treasury bonds with the intention of reducing mortgage rates (for fear of deflation see Pelaez and Pelaez, International Financial Architecture (2005), 18-28, and Pelaez and Pelaez, The Global Recession Risk (2007), 83-95). 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

If the forecast of the central bank is of recession and low inflation with controlled inflationary expectations, monetary policy should consist of lowering the short-term policy rate of the central bank, which in the US is the fed funds rate. The intended effect is to lower the real rate of interest (Svensson 2003LT, 146-7). The real rate of interest, r, is defined as the nominal rate, i, adjusted by expectations of inflation, π*, with all variables defined as proportions: (1+r) = (1+i)/(1+π*) (Fisher 1930). If i, the fed funds rate, is lowered by the Fed, the numerator of the right-hand side is lower such that if inflationary expectations, π*, remain unchanged, the left-hand (1+r) decreases, that is, the real rate of interest, r, declines. Expectations of lowering short-term real rates of interest by policy of the Federal Open Market Committee (FOMC) fixing a lower fed funds rate would lower long-term real rates of interest, inducing with a lag investment and consumption, or aggregate demand, that can lift the economy out of recession. Inflation also increases with a lag by higher aggregate demand and inflation expectations (Fisher 1933). This reasoning explains why the FOMC lowered the fed funds rate in Dec 2008 to 0 to 0.25 percent and left it unchanged.

The fear of the Fed is expected deflation or negative π*. In that case, (1+ π*) < 1, and (1+r) would increase because the right-hand side of the equation would be divided by a fraction. A simple numerical example explains the effect of deflation on the real rate of interest. Suppose that the nominal rate of interest or fed funds rate, i, is 0.25 percent, or in proportion 0.25/100 = 0.0025, such that (1+i) = 1.0025. Assume now that economic agents believe that inflation will remain at 1 percent for a long period, which means that π* = 1 percent, or in proportion 1/100 =0.01. The real rate of interest, using the equation, is (1+0.0025)/(1+0.01) = (1+r) = 0.99257, such that r = 0.99257 - 1 = -0.00743, which is a proportion equivalent to –(0.00743)100 = -0.743 percent. That is, Fed policy has created a negative real rate of interest of 0.743 percent with the objective of inducing aggregate demand by higher investment and consumption. This is true if expected inflation, π*, remains at 1 percent. Suppose now that expectations of deflation become generalized such that π* becomes -1 percent, that is, the public believes prices will fall at the rate of 1 percent in the foreseeable future. Then the real rate of interest becomes (1+0.0025) divided by (1-0.01) equal to (1.0025)/(0.99) = (1+r) = 1.01263, or r = (1.01263-1) = 0.01263, which results in positive real rate of interest of (0.01263)100 = 1.263 percent.

Irving Fisher also identified the impact of deflation on debts as an important cause of deepening contraction of income and employment during the Great Depression illustrated by an actual example (Fisher 1933, 346):

“By March, 1933, liquidation had reduced the debts about 20 percent, but had increased the dollar about 75 percent, so that the real debt, that is the debt measured in terms of commodities, was increased about 40 percent [100%-20%)X(100%+75%) =140%]. Unless some counteracting cause comes along to prevent the fall in the price level, such a depression as that of 1929-1933 (namely when the more the debtors pay the more they owe) tends to continue, going deeper, in a vicious spiral, for many years. There is then no tendency of the boat to stop tipping until it has capsized”

The nominal rate of interest must always be nonnegative, that is, i ≥ 0 (Hick 1937, 154-5):

“If the costs of holding money can be neglected, it will always be profitable to hold money rather than lend it out, if the rate of interest is not greater than zero. Consequently the rate of interest must always be positive. In an extreme case, the shortest short-term rate may perhaps be nearly zero. But if so, the long-term rate must lie above it, for the long rate has to allow for the risk that the short rate may rise during the currency of the loan, and it should be observed that the short rate can only rise, it cannot fall”

The interpretation by Hicks of the General Theory of Keynes is the special case in which at interest rates close to zero liquidity preference is infinitely or perfectly elastic, that is, the public holds infinitely large cash balances at that near zero interest rate because there is no opportunity cost of foregone interest. Increases in the money supply by the central bank would not decrease interest rates below their near zero level, which is called the liquidity trap. The only alternative public policy would consist of fiscal policy that would act similarly to an increase in investment, increasing employment without raising the interest rate.

An influential view on the policy required to steer the economy away from the liquidity trap is provided by Paul Krugman (1998). Suppose the central bank faces an increase in inflation. An important ingredient of the control of inflation is the central bank communicating to the public that it will maintain a sustained effort by all available policy measures and required doses until inflation is subdued and price stability is attained. If the public believes that the central bank will control inflation only until it declines to a more benign level but not sufficiently low level, current expectations will develop that inflation will be higher once the central bank abandons harsh measures. During deflation and recession the central bank has to convince the public that it will maintain zero interest rates and other required measures until the rate of inflation returns convincingly to a level consistent with expansion of the economy and stable prices. Krugman (1998, 161) summarizes the argument as:

“The ineffectuality of monetary policy in a liquidity trap is really the result of a looking-glass version of the standard credibility problem: monetary policy does not work because the public expects that whatever the central bank may do now, given the chance, it will revert to type and stabilize prices near their current level. If the central bank can credibly promise to be irresponsible—that is, convince the market that it will in fact allow prices to rise sufficiently—it can bootstrap the economy out of the trap”

This view is consistent with results of research by Christina Romer that “the rapid rates of growth of real output in the mid- and late 1930s were largely due to conventional aggregate demand stimulus, primarily in the form of monetary expansion. My calculations suggest that in the absence of these stimuli the economy would have remained depressed far longer and far more deeply than it actually did” (Romer 1992, 757-8, cited in Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 210-2). The average growth rate of the money supply in 1933-1937 was 10 percent per year and increased in the early 1940s. Romer calculates that GDP would have been much lower without this monetary expansion. The growth of “the money supply was primarily due to a gold inflow, which was in turn due to the devaluation in 1933 and to capital flight from Europe because of political instability after 1934” (Romer 1992, 759). Gold inflow coincided with the decline in real interest rates in 1933 that remained negative through the latter part of the 1930s, suggesting that they could have caused increases in spending that was sensitive to declines in interest rates. Bernanke finds dollar devaluation against gold to have been important in preventing further deflation in the 1930s (Bernanke 2002):

“There have been times when exchange rate policy has been an effective weapon against deflation. A striking example from US history is Franklin Roosevelt’s 40 percent devaluation of the dollar against gold in 1933-34, enforced by a program of gold purchases and domestic money creation. The devaluation and the rapid increase in money supply it permitted ended the US deflation remarkably quickly. Indeed, consumer price inflation in the United States, year on year, went from -10.3 percent in 1932 to -5.1 percent in 1933 to 3.4 percent in 1934. The economy grew strongly, and by the way, 1934 was one of the best years of the century for the stock market”

Fed policy is seeking what Irving Fisher proposed “that great depressions are curable and preventable through reflation and stabilization” (Fisher 1933, 350).

The President of the Federal Reserve Bank of Chicago argues that (Charles Evans 2010):

“I believe the US economy is best described as being in a bona fide liquidity trap. Highly plausible projections are 1 percent for core Personal Consumption Expenditures (PCE) inflation at the end of 2012 and 8 percent for the unemployment rate. For me, the Fed’s dual mandate misses are too large to shrug off, and there is currently no policy conflict between improving employment and inflation outcomes”

There are two types of monetary policies that could be used in this situation. First, the Fed could announce a price-level target to be attained within a reasonable time frame (Evans 2010):

“For example, if the slope of the price path is 2 percent and inflation has been underunning the path for some time, monetary policy would strive to catch up to the path. Inflation would be higher than 2 percent for a time until the path was reattained”

Optimum monetary policy with interest rates near zero could consist of “bringing the price level back up to a level even higher than would have prevailed had the disturbance never occurred” (Gauti Eggertsson and Michael Woodford 2003, 207). Bernanke (2003JPY) explains as follows:

“Failure by the central bank to meet its target in a given period leads to expectations of (and public demands for) increased effort in subsequent periods—greater quantities of assets purchased on the open market for example. So even if the central bank is reluctant to provide a time frame for meetings its objective, the structure of the price-level objective provides a means for the bank to commit to increasing its anti-deflationary efforts when its earlier efforts prove unsuccessful. As Eggertsson and Woodford show, the expectations that an increasing price level gap will give rise to intensified effort by the central bank should lead the public to believe that ultimately inflation will replace deflation, a belief that supports the central bank’s own objectives by lowering the current real rate of interest”

Second, the Fed could use its balance sheet to increase purchases of long-term securities together with credible commitment to maintain the policy until the dual mandates of maximum employment and price stability are attained.

The central bank could also be pursuing competitive devaluation of the national currency in the belief that it could increase inflation to a higher level and promote domestic growth and employment at the expense of growth and unemployment in the rest of the world. An essay by Chairman Bernanke in 1999 on Japanese monetary policy received attention in the press, stating that (Bernanke 2000, 165):

“Roosevelt’s specific policy actions were, I think, less important than his willingness to be aggressive and experiment—in short, to do whatever it took to get the country moving again. Many of his policies did not work as intended, but in the end FDR deserves great credit for having the courage to abandon failed paradigms and to do what needed to be done”

Quantitative easing has never been proposed by Chairman Bernanke or other economists as certain science without adverse effects. What has not been mentioned in the press is another suggestion to the Bank of Japan (BOJ) by Chairman Bernanke in the same essay that is very relevant to current events and the contentious issue of ongoing devaluation wars (2000, 161):

“Because the BOJ has a legal mandate to pursue price stability, it certainly could make a good argument that, with interest rates at zero, depreciation of the yen is the best available tool for achieving its mandated objective. The economic validity of the beggar-thy-neighbor thesis is doubtful, as depreciation creates trade—by raising home country income—as well as diverting it. Perhaps not all those who cite the beggar-thy-neighbor thesis are aware that it had its origins in the Great Depression, when it was used as an argument against the very devaluations that ultimately proved crucial to world economic recovery. A yen trading at 100 to the dollar is in no one’s interest”

Chairman Bernanke is referring to the argument by Joan Robinson based on the experience of the Great Depression that: “in times of general unemployment a game of beggar-my-neighbour is played between the nations, each one endeavouring to throw a larger share of the burden upon the others” (Robinson 1947, 156). Devaluation is one of the tools used in these policies (Robinson 1947, 157). Banking crises dominated the experience of the United States, but countries that recovered were those devaluing early such that competitive devaluations rescued many countries from a recession as strong as that in the US (see references to Ehsan Choudhri, Levis Kochin and Barry Eichengreen in Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 205-9; for the case of Brazil that devalued early in the Great Depression recovering with an increasing trade balance see Pelaez, 1968, 1968b, 1972; Brazil devalued and abandoned the gold standard during crises in the historical period as shown by Pelaez 1976, Pelaez and Suzigan 1981). Beggar-my-neighbor policies did work for individual countries but the criticism of Joan Robinson was that it was not optimal for the world as a whole.

Friedman (1969) finds that the optimal rule for the quantity of money is deflation at a rate that results in a zero nominal interest rate (see Ireland 2003 and Cole and Kocherlakota 1998). Atkeson and Kehoe (2004) argue that central bankers are not inclined to implement policies that could result in deflation because of the interpretation of the Great Depression as closely related to deflation. They use panel data on inflation and growth of real output for 17 countries over more than 100 years. The time-series data for each individual country are broken into five-year events with deflation measured as average negative inflation and depression as average negative growth rate of real output. Atkeson and Kehoe (2004) find that the Great Depression from 1929 to 1934 is the only case of association between deflation and depression without any evidence whatsoever of such relation in any other period. Their conclusion is (Atkeson and Kehoe 2004, 99): “Our finding thus suggests that policymakers’ fear of anticipated policy-induced deflation that would result from following, say, the Friedman rule is greatly overblown.” Their conclusion on the experience of Japan is (Atkeson and Kehoe 2004, 99):

“Since 1960, Japan’s average growth rates have basically fallen monotonically, and since 1970, its average inflation rates have too. Attributing this 40-year slowdown to monetary forces is a stretch. More reasonable, we think, is that much of the slowdown is the natural pattern for a country that was far behind the world leaders and had begun to catch up.”

In the sample of Atkeson and Kehoe (2004), there are only eight five-year periods besides the Great Depression with both inflation and depression. Deflation and depression is shown in 65 cases with 21 of depression without deflation. There is no depression in 65 of 73 five-year periods and there is no deflation in 29 episodes of depression. There is a remarkable result of no depression in 90 percent of deflation episodes. Excluding the Great Depression, there is virtually no relation of deflation and depression. Atkeson and Kehoe (2004, 102) find that the average growth rate of Japan of 1.41 percent in the 1990s is “dismal” when compared with 3.20 percent in the United States but is not “dismal” when compared with 1.61 percent for Italy and 1.84 percent for France, which are also catch-up countries in modern economic growth (see Atkeson and Kehoe 1998). The conclusion of Atkeson and Kehoe (2004), without use of controls, is that there is no association of deflation and depression in their dataset.

Benhabib and Spiegel (2009) use a dataset similar to that of Atkeson and Kehoe (2004) but allowing for nonlinearity and inflation volatility. They conclude that in cases of low and negative inflation an increase of average inflation of 1 percent is associated with an increase of 0.31 percent of average annual growth. The analysis of Benhabib and Spiegel (2009) leads to the significantly different conclusion that inflation and economic performance are strongly associated for low and negative inflation. There is no claim of causality by Atkeson and Kehoe (2004) and Benhabib and Spiegel (2009).

Chart ESIV-1 provides the consumer price index NSA from 1913 to 2012. The dominating characteristic is the increase in slope during the Great Inflation from the middle of the 1960s through the 1970s. There is long-term inflation in the US and no evidence of deflation risks

Chart ESIV-1, US, Consumer Price Index, All Items, NSA, 1913-2012

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

Table ESIV-1 provides annual percentage changes of United States consumer price inflation from 1914 to 2011. There have been only cases of annual declines of the CPI after World War II: -1.2 percent in 1949, -0.4 percent in 1955 and -0.4 percent in 2009. The decline of 0.4 percent in 2009 followed increase of 3.8 percent in 2008 and is explained by the reversal of speculative carry trades that were created in 2008 as monetary policy rates were driven to zero. The reversal occurred after misleading statement on toxic assets in banks in the proposal for TARP (Cochrane and Zingales 2009). The only persistent deflationary period since 1914 was during the Great Depression in the years from 1930 to 1933. Fear of deflation on the basis of that experience does not justify unconventional monetary policy of zero interest rates that has failed to stop deflation in Japan. Financial repression causes far more adverse effects on allocation of resources by distorting the calculus of risk/returns than alleged employment-creating effects or there would not be current recovery without jobs and hiring after zero interest rates since Dec 2008 and intended now forever in a self-imposed growth and employment mandate of monetary policy.

Table ESIV-1, US, Consumer Price Index, All Items, NSA, 12-Month Percentage Change 1914-2012

Year	Annual
1914	1.0
1915	1.0
1916	7.9
1917	17.4
1918	18.0
1919	14.6
1920	15.6
1921	-10.5
1922	-6.1
1923	1.8
1924	0.0
1925	2.3
1926	1.1
1927	-1.7
1928	-1.7
1929	0.0
1930	-2.3
1931	-9.0
1932	-9.9
1933	-5.1
1934	3.1
1935	2.2
1936	1.5
1937	3.6
1938	-2.1
1939	-1.4
1940	0.7
1941	5.0
1942	10.9
1943	6.1
1944	1.7
1945	2.3
1946	8.3
1947	14.4
1948	8.1
1949	-1.2
1950	1.3
1951	7.9
1952	1.9
1953	0.8
1954	0.7
1955	-0.4
1956	1.5
1957	3.3
1958	2.8
1959	0.7
1960	1.7
1961	1.0
1962	1.0
1963	1.3
1964	1.3
1965	1.6
1966	2.9
1967	3.1
1968	4.2
1969	5.5
1970	5.7
1971	4.4
1972	3.2
1973	6.2
1974	11.0
1975	9.1
1976	5.8
1977	6.5
1978	7.6
1979	11.3
1980	13.5
1981	10.3
1982	6.2
1983	3.2
1984	4.3
1985	3.6
1986	1.9
1987	3.6
1988	4.1
1989	4.8
1990	5.4
1991	4.2
1992	3.0
1993	3.0
1994	2.6
1995	2.8
1996	3.0
1997	2.3
1998	1.6
1999	2.2
2000	3.4
2001	2.8
2002	1.6
2003	2.3
2004	2.7
2005	3.4
2006	3.2
2007	2.8
2008	3.8
2009	-0.4
2010	1.6
2011	3.2

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

Chart ESIV-2 provides 12-month percentage changes of the US consumer price index from 1914 to 2012. There are actually three waves of inflation in the second half of the 1960s, in the mid 1970s and again in the late 1970s. The Great Inflation of the 1970s is analyzed in various comments of this blog (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 in Appendix I. Inflation rates then stabilized in the US in a range with only two episodes above 5 percent. There are isolated cases of deflation concentrated over extended periods only during the 1930s. There is no case in United States economic history for unconventional monetary policy because of fear of deflation. There are cases of long-term deflation without lost decades or depressions.

Chart ESIV-2, US, Consumer Price Index, All Items, NSA, 12-Month Percentage Change 1914-2012

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

Delfim Netto (1959) partly reprinted in Pelaez (1973) conducted two classical nonparametric tests (Mann 1945, Wallis and Moore 1941; see Kendall and Stuart 1968) with coffee-price data in the period of free markets from 1857 to 1906 with the following conclusions (Pelaez, 1976a, 280):

“First, the null hypothesis of no trend was accepted with high confidence; secondly, the null hypothesis of no oscillation was rejected also with high confidence. Consequently, in the nineteenth century international prices of coffee fluctuated but without long-run trend. This statistical fact refutes the extreme argument of structural weakness of the coffee trade.”

The conventional theory that the terms of trade of Brazil deteriorated over the long term is without reality (Pelaez 1976a, 280-281):

“Moreover, physical exports of coffee by Brazil increased at the high average rate of 3.5 per cent per year. Brazil's exchange receipts from coffee-exporting in sterling increased at the average rate of 3.5 per cent per year and receipts in domestic currency at 4.5 per cent per year. Great Britain supplied nearly all the imports of the coffee economy. In the period of the free coffee market, British export prices declined at the rate of 0.5 per cent per year. Thus, the income terms of trade of the coffee economy improved at the relatively satisfactory average rate of 4.0 per cent per year. This is only a lower bound of the rate of improvement of the terms of trade. While the quality of coffee remained relatively constant, the quality of manufactured products improved significantly during the fifty-year period considered. The trade data and the non-parametric tests refute conclusively the long-run hypothesis. The valid historical fact is that the tropical export economy of Brazil experienced an opportunity of absorbing rapidly increasing quantities of manufactures from the "workshop" countries. Therefore, the coffee trade constituted a golden opportunity for modernization in nineteenth-century Brazil.”

Imlah (1958) provides decline of British export prices at 0.5 percent in the nineteenth century and there were no lost decades, depressions or unconventional monetary policies in the highly dynamic economy of England that drove the world’s growth impulse. Inflation in the United Kingdom between 1857 and 1906 is measured by the composite price index of O’Donoghue and Goulding (2004) at minus 7.0 percent or average rate of decline of 0.2 percent per year.

Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:

“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated.Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”

Cameron (1961) analyzes the mechanism by which the Industrial Revolution in Great Britain spread throughout Europe and Cameron (1967) analyzes the financing by banks of the Industrial Revolution in Great Britain. O’Donoghue and Goulding (2004) provide consumer price inflation in England since 1750 and MacFarlane and Mortimer-Lee (1994) analyze inflation in England over 300 years. Lucas (2004) estimates world population and production since the year 1000 with sustained growth of per capita incomes beginning to accelerate for the first time in English-speaking countries and in particular in the Industrial Revolution in Great Britain. The conventional theory is unequal distribution of the gains from trade and technical progress between the industrialized countries and developing economies (Singer 1950, 478):

“Dismissing, then, changes in productivity as a governing factor in changing terms of trade, the following explanation presents itself: the fruits of technical progress may be distributed either to producers (in the form of rising incomes) or to consumers (in the form of lower prices). In the case of manufactured commodities produced in more developed countries, the former method, i.e., distribution to producers through higher incomes, was much more important relatively to the second method, while the second method prevailed more in the case of food and raw material production in the underdeveloped countries. Generalizing, we may say -that technical progress in manufacturing industries showed in a rise in incomes while technical progress in the production of food and raw materials in underdeveloped countries showed in a fall in prices”

Temin (1997, 79) uses a Ricardian trade model to discriminate between two views on the Industrial Revolution with an older view arguing broad-based increases in productivity and a new view concentration of productivity gains in cotton manufactures and iron:

“Productivity advances in British manufacturing should have lowered their prices relative to imports. They did. Albert Imlah [1958] correctly recognized this ‘severe deterioration’ in the net barter terms of trade as a signal of British success, not distress. It is no surprise that the price of cotton manufactures fell rapidly in response to productivity growth. But even the price of woolen manufactures, which were declining as a share of British exports, fell almost as rapidly as the price of exports as a whole. It follows, therefore, that the traditional ‘old-hat’ view of the Industrial Revolution is more accurate than the new, restricted image. Other British manufactures were not inefficient and stagnant, or at least, they were not all so backward. The spirit that motivated cotton manufactures extended also to activities as varied as hardware and haberdashery, arms, and apparel.”

Phyllis Deane (1968, 96) estimates growth of United Kingdom gross national product (GNP) at around 2 percent per year for several decades in the nineteenth century. The experience of the United Kingdom with deflation and economic growth is relevant and rich. Table IIA-3 uses yearly percentage changes of the composite index of prices of the United Kingdom of O’Donoghue and Goulding (2004). There are 73 declines of inflation in the 145 years from 1751 to 1896. Prices declined in 50.3 percent of 145 years. Some price declines were quite sharp and many occurred over several years. Table IIA-3 also provides yearly percentage changes of the UK composite price index of O’Donoghue and Goulding (2004) from 1929 to 1934. Deflation was much sharper in continuous years in earlier periods than during the Great Depression.

Table ESIV-2, United Kingdom, Negative Percentage Changes of Composite Price Index, 1751-1896, 1929-1934, Yearly ∆%

Year	∆%	Year	∆%	Year	∆%	Year	∆%
1751	-2.7	1797	-10.0	1834	-7.8	1877	-0.7
1753	-2.7	1798	-2.2	1841	-2.3	1878	-2.2
1755	-6.0	1802	-23.0	1842	-7.6	1879	-4.4
1758	-0.3	1803	-5.9	1843	-11.3	1881	-1.1
1759	-7.9	1806	-4.4	1844	-0.1	1883	-0.5
1760	-4.5	1807	-1.9	1848	-12.1	1884	-2.7
1761	-4.5	1811	-2.9	1849	-6.3	1885	-3.0
1768	-1.1	1814	-12.7	1850	-6.4	1886	-1.6
1769	-8.2	1815	-10.7	1851	-3.0	1887	-0.5
1770	-0.4	1816	-8.4	1857	-5.6	1893	-0.7
1773	-0.3	1819	-2.5	1858	-8.4	1894	-2.0
1775	-5.6	1820	-9.3	1859	-1.8	1895	-1.0
1776	-2.2	1821	-12.0	1862	-2.6	1896	-0.3
1777	-0.4	1822	-13.5	1863	-3.6	1929	-0.9
1779	-8.5	1826	-5.5	1864	-0.9	1930	-2.8
1780	-3.4	1827	-6.5	1868	-1.7	1931	-4.3
1785	-4.0	1828	-2.9	1869	-5.0	1932	-2.6
1787	-0.6	1830	-6.1	1874	-3.3	1933	-2.1
1789	-1.3	1832	-7.4	1875	-1.9	1934	0.0
1791	-0.1	1833	-6.1	1876	-0.3

Source:

O’Donoghue, Jim and Louise Goulding, 2004. Consumer Price Inflation since 1750. UK Office for National Statistics Economic Trends 604, Mar 2004, 38-46.

Nicholas Georgescu-Rogen (1960, 1) reprinted in Pelaez (1973) argues that “the agrarian economy has to this day remained a reality without theory.” The economic history of Latin America shares with the relation of deflation and unconventional monetary policy a more frustrating intellectual misfortune: theory without reality. MacFarlane and Mortimer-Lee (1994, 159) quote in a different context a phrase by Thomas Henry Huxley in the President’s Address to the British Association for the Advancement of Science on Sep 14, 1870 that is appropriate to these issues: “The great tragedy of science—the slaying of a beautiful hypothesis by an ugly fact.”

ESV American Taxpayer Relief Act of 2012 and United States Threatening Risk Premium on Government Debt. The United States Senate passed on Jan 1, 2013, H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf) subsequently passed in the United States House of Representatives and signed into law by the President. The Congressional Budget Office (CBO) analyzes the effects of the American Taxpayer Relief Act of 2012 (http://www.cbo.gov/publication/43829). The bulk of the effects originate in Title I—General Extensions. Table ESV-1 provides the estimates of effects of the General Extensions and the overall bill. The Treasury deficit of the United States increases by $3,971 billion from 2013 to 2022 or about $4 trillion. The alternative scenario of deficits and debts of CBO appears to be more relevant than the base scenario in which tax rates would increase and expenditures decline. The bulk of this section concentrates on United States unsustainable deficit/debt that may cause an increase in the risk premium of Treasury debt

Table ESV-1, Estimate by the Congressional Budget Office of Budget Effects of H.R.8, the American Taxpayer Relief Act of 2012, Passed by US Senate on January 1, 2013

	General Extensions	Total Changes in Revenues	Net Increase or (-) Decrease in Deficits
2013	-206,542	-279,840	329,644
2014	-266,004	-298,778	353,881
2015	-290,573	-274,707	311,008
2016	-315,761	-305,405	340,449
2017	-344,090	-336,613	371,139
2018	-372,728	-367,146	404,636
2019	-395,390	-393,146	415,743
2020	-425,716	-425,585	447,618
2021	-460,619	-460,509	482,553
2022	-496,647	-496,826	514,523
2013-2017	-1,422,970	-1,495,340	1,705,118
2013-2022	-3,575,062	-3,638,803	3,971,177

Source: Congressional Budget Office

http://www.cbo.gov/publication/43829

Table ESV-2 provides federal debt outstanding, held by government accounts and held by the public in millions of dollars for fiscal years from 2007 to 2012. Federal debt outstanding has increased 78.2 percent from fiscal year 2007 to fiscal year 2012 while federal debt held by the public has increased 122.8 percent and federal debt held by government accounts has increased 21.1 percent.

Table ESV-2, US, Federal Debt Outstanding, Held by Government Accounts and Held by the Public, Millions of Dollars

	Outstanding	Held by Government Accounts	Held by the Public
2012 Sep	16,090,640	4,791,850	11,298,790
Fiscal Years
2012	16,090,640	4,791,850	11,298,790
2011	14,815,328	4,658,307	10,157,021
2010	13,585,596	4,534,014	9,051,582
2009	11,933,031	4,355,291	7,577,739
2008	10,047,828	4,210,491	5,837,337
2007	9,030,612	3,958,417	5,072,195
∆% 2007-2012	78.2	21.1	122.8

Source: United States Treasury. 2012Dec. Treasury Bulletin. Washington, DC, Dec 2012. https://www.fms.treas.gov/bulletin/index.html

Table ESV-3 provides the maturity distribution and average length in months of marketable interest-bearing debt held by private investors from 2007 to Sep 2012. Total debt held by investors increased from $3635 billion in 2007 to $9040 billion in Sep 2012 or increase by 148.7 percent. There are two concerns with the maturity distribution of US debt. (1) Growth of debt is moving total debt to the point of saturation in investors’ portfolio. In a new environment of risk appetite and nonzero fed funds rates with economic growth at historical trend of around 3 percent, yields on risk financial assets are likely to increase. Placement of new debt may require increasing interest rates in an environment of continuing placement of debt by the US Treasury without strong fiscal constraints. (2) Refinancing of maturing debt is likely to occur in an environment of higher interest rates, exerting pressure on future fiscal budgets. In Sep 2012, $2897 billion or 32.1 percent of outstanding debt held by investors matures in less than a year and $3852 billion or 42.6 percent of total debt matures in one to five years. Debt maturing in five years or less adds to $6749 billion or 74.7 percent of total outstanding debt held by investors of $9040 billion. This historical episode may be remembered as one in which the US managed its government debt with short-dated instruments during record low long-dated yields and on the verge of fiscal pressures on all interest rates, which kind of maximizes over time interest payments on government debt by taxpayers that is precisely the opposite of the objective of sound debt management and taxpayer welfare.

Table ESV-3, Maturity Distribution and Average Length in Months of Marketable Interest-Bearing Public Debt Held by Private Investors, Billions of Dollars

End of Fiscal Year or Month	2007	2008	2009	2010	2011	2012	Sep 2012
Total*	3635	4745	6229	7676	7951	9040	9040
<1 Year	1176	2042	2605	2480	2504	2897	2897
1-5 Years	1310	1468	2075	2956	3085	3852	3852
5-10 Years	678	719	995	1529	1544	1488	1488
10-20 Years	292	352	351	341	309	271	271
>20 Years	178	163	204	371	510	533	533
Average Months	58	49	49	57	60	55	55

*Amount Outstanding Privately Held

Source: United States Treasury. 2012Dec. Treasury Bulletin. Washington, DC, Dec 2012. https://www.fms.treas.gov/bulletin/index.html

Table ESV-4 provides additional information required for understanding the deficit/debt situation of the United States. The table is divided into three parts: federal fiscal data for the years from 2009 to 2012; federal fiscal data for the years from 2005 to 2008; and Treasury debt held by the public from 2005 to 2012. Total revenues of the US from 2009 to 2012 accumulate to $9019 billion, or $9.0 trillion, while expenditures or outlays accumulate to $14,111 billion, or $14.1 trillion, with the deficit accumulating to $5092 billion, or $5.1 trillion. Revenues decreased 6.6 percent from $9653 billion in the four years from 2005 to 2008 to $9019 billion in the years from 2009 to 2012. Decreasing revenues were caused by the global recession from IVQ2007 (Dec) to IIQ2009 (Jun) and also by growth of only 2.2 percent on average in the cyclical expansion from IIIQ2009 to IIIQ2012, which is much lower than 6.2 percent on average in cyclical expansions since the 1950s (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html). Weakness of growth and employment creation is analyzed in IB Collapse of United States Dynamism of Income Growth and Employment Creation. There are 29.5 million people without jobs or underemployed that is equivalent to 18.2 percent of the US effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2012/12/twenty-eight-million-unemployed-or.html) and hiring is significantly below the earlier cyclical expansion before 2007 (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html). In contrast with the decline of revenue, outlays or expenditures increased 30.2 percent from $10,839 billion, or $10.8 trillion, in the four years from 2005 to 2008, to $14,111 billion, or $14.1 trillion, in the four years from 2009 to 2012. Increase in expenditures by 30.2 percent while revenue declined by 6.6 percent caused the increase in the federal deficit from $1186 billion in 2005-2008 to $5092 billion in 2009-2012. Federal revenue was 15.4 percent of GDP on average in the years from 2009 to 2012, which is well below 18.0 percent of GDP on average from 1970 to 2010. Federal outlays were 24.1 percent of GDP on average from 2009 to 2012, which is well above 21.9 percent of GDP on average from 1970 to 2010. The lower part of Table ESV-4 shows that debt held by the public swelled from $5803 billion in 2008 to $11,280 billion in 2012, by $5477 billion or 94.3 percent. Debt held by the public as percent of GDP or economic activity jumped from 40.5 percent in 2008 to 72.6 percent in 2012, which is well above the average of 37.0 percent from 1970 to 2010. The United States faces tough adjustment because growth is unlikely to recover, creating limits on what can be obtained by increasing revenues, while continuing stress of social programs restricts what can be obtained by reducing expenditures.

Table ESV-4, US, Treasury Budget and Debt Held by the Public, Billions of Dollars and Percent of GDP

	Receipts	Outlays	Deficit (-), Surplus (+)
$ Billions
2012	2,449	3,538	-1,089
Fiscal Year 2011	2,302	3,599	-1,297
Fiscal Year 2010	2,163	3,456	-1,293
Fiscal Year 2009	2,105	3,518	-1,413
Total 2009-2012	9,019	14,111	-5,092
Average % GDP 2009-2012	15.4	24.1	-8.7
Fiscal Year 2008	2,524	2,983	-459
Fiscal Year 2007	2,568	2,729	-161
Fiscal Year 2006	2,407	2,655	-248
Fiscal Year 2005	2,154	2,472	-318
Total 2005-2008	9,653	10,839	-1,186
Average % GDP 2005-2008	17.9	20.1	-2.2
Debt Held by the Public	Billions of Dollars	Percent of GDP
2005	4,592	36.9
2006	4,829	36.6
2007	5,035	36.3
2008	5,803	40.5
2009	7,545	54.1
2010	9,019	62.8
2011	10,128	67.7
2012	11,280	72.6

Source: http://www.fms.treas.gov/mts/index.html CBO (2012NovMBR). CBO (2011AugBEO); Office of Management and Budget. 2011. Historical Tables. Budget of the US Government Fiscal Year 2011. Washington, DC: OMB; CBO. 2011JanBEO. Budget and Economic Outlook. Washington, DC, Jan. CBO. 2012AugBEO. Budget and Economic Outlook. Washington, DC, Aug 22. CBO. 2012Jan31. Historical budget data. Washington, DC, Jan 31. CBO. 2012NovCDR. Choices for deficit reduction. Washington, DC. Nov.

The CBO (2012NovCDR, 4) uses different assumptions to calculate what would happen with the US budget and debt under an alternative fiscal scenario of no measures of fiscal tightening:

“The alternative fiscal scenario incorporates the assumptions that all expiring tax provisions (other than the payroll tax reduction), including those that expired at the end of December 2011, are instead extended; that the alternative minimum tax is indexed for inflation after 2011 (starting at the 2011 exemption amount); that Medicare’s payment rates for physicians’ services are held constant at their current level; and that the automatic enforcement procedures specified by the Budget Control Act of 2011 do not take effect. Outlays under that scenario also include the incremental interest costs associated with projected additional borrowing.”

Table ESV-5 provides the projections of the alternative fiscal scenario of the CBO under those assumptions. Debt as percent of GDP increases from 72.6 percent in 2012 to 89.7 percent in 2022.

Table ESV-5, US, Alternative Scenario CBO Projections of Federal Government Revenues, Outlays, Deficit and Debt as Percent of GDP

	Revenues % GDP	Outlays % GDP	Deficit % GDP	Debt GDP
2011	15.4	24.1	-8.7	67.7
2012	15.8	22.8	-7.0	72.6
2013	16.3	22.8	-6.5	78.6
2014	17.2	22.9	-5.6	82.3
2015	17.8	22.5	-4.6	82.5
2016	18.1	22.6	-4.5	82.5
2017	18.3	22.5	-4.2	82.5
2018	18.3	22.5	-4.2	82.9
2019	18.4	23.0	-4.6	84.1
2020	18.5	23.3	-4.8	85.7
2021	18.5	23.6	-5.1	87.5
2022	18.6	24.1	-5.5	89.7
Total 2013-2017	17.6	22.6	-5.0	NA
Total 2013-2022	18.1	23.0	-4.9	NA
Average 1971-2010	18.0	21.9	NA	37.0

Source: CBO (2012AugBEO). CBO (2012NovCDR).

IA Thirty Million Unemployed or Underemployed. The employment situation report of the Bureau of Labor Statistics (BLS) of the US Department of Labor released in the first Fri of every month is critical in the analysis of social and economic conditions in the US. The objective of this section is to analyze the report released on Jan 4, 2012, for Dec 2012 (http://www.bls.gov/news.release/pdf/empsit.pdf). The analysis of the employment situation of the US is divided into two subsections. IA Thirty Million Unemployed or Underemployed provides the key data on employment and job creation contained in the BLS report. These data are complemented by the BLS report on hiring, job openings and separations to be released on Thu Jan 10, 2013 (http://www.bls.gov/jlt/), which will be analyzed in this blog’s comment of Jan 13 with the latest report analyzed in the blog comment for Dec 16, 2012 (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html). IA5 Stagnating Real Wages analyzes wages and hours worked. IA1 Summary of the Employment Situation provides brief analysis of the employment situation. IA2 Number of People in Job Stress provides the calculation of people unemployed or underemployed in the US using the estimates of the BLS. IA3 Long-term and Cyclical Comparison of Employment provides the comparison with long-term and relevant cyclical experience in the US. IA4 Creation of Jobs analyzes the establishment survey of the BLS that provides job creation in nonfarm payrolls. Hourly and weekly earnings and hours worked are analyzed in the following section IA5 Stagnating Real Wages.

IA1 Summary of the Employment Situation. 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.”

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 155,000 in Dec 2012 and private payroll employment rose 168,000. The number of nonfarm jobs and private jobs created has been declining in 2012 from 275,000 in Jan 2012 to 45,000 in Jun, 132,000 in Sep, 137,000 in Oct, 161,000 in Nov and 155,000 in Dec 2012 for total nonfarm jobs and from 277,000 in Jan 2012 to 63,000 in Jun, 122,000 in Sep, 203,000 in Oct, 171,000 in Nov and 168,000 in Dec 2012 for private jobs. Average new nonfarm jobs in the quarter Dec 2011 to Feb 2012 were 252,333 per month, declining to average 130,100 per month in the ten months from Mar to Dec 2012. Average new private jobs in the quarter Dec 2011 to Feb 2012 were 255,000 per month, declining to average 137,200 per month in the ten months from Mar 2012 to Dec 2012. The US labor force stood at 154.088 million in Oct 2011 and at 155.779 million in Oct 2012, not seasonally adjusted, for increase of 1.691 million, or 140,917 per month. The US labor force stood at 153.683 million in Nov 2011 and 154.953 million in Nov 2012, not seasonally adjusted, for increase of 1.270 million or 105,833 per month. The US labor force stood at 153.373 million in Dec 2011 and 154.904 million in Dec 2012, not seasonally adjusted, for increase of 1.531 million or 127,583 per month. The average increase of 130,100 new nonfarm jobs per month in the US from Mar to Dec 2012 is insufficient even to absorb 127,583 new entrants per month into the labor force. The difference between the average increase of 137,200 new private nonfarm jobs per month in the US from Mar to Dec 2012 and the 127,583 average monthly increase in the labor force from Nov 2011 to Nov 2012 is 9,617 monthly new jobs net of absorption of new entrants in the labor force. There are 29.5 million in job stress in the US currently. The provision of 9,617 new jobs per month net of absorption of new entrants in the labor force would require 3067 months to provide jobs for the unemployed and underemployed (29.5 million divided by 9,617) or 256 years (3067 divided by 12). Net job creation of 9,617 jobs per month only adds 115,404 jobs in a year. The civilian labor force of the US in Dec 2012 not seasonally adjusted stood at 154.904 million with 11.844 million unemployed or effectively 18.700 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 8.7 years (1 million divided by product of 9,617 by 12, which is 115,404). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.745 million (0.05 times labor force of 154.904 million) for new net job creation of 4.099 million (11.844 million unemployed minus 7.745 million unemployed at rate of 5 percent) that at the current rate would take 35.5 years (4.099 million divided by 115,404). Under the calculation in this blog there are 18.700 million unemployed by including those who ceased searching because they believe there is no job for them. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 10.612 million jobs net of labor force growth that at the current rate would take 91.9 years (18.700 million minus 0.05(161.760 million) divided by 115,404, 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 the US fell from 146.743 million in Oct 2007 to 143.060 million in Dec 2012, by 3.683 million, or 2.5 percent, while the noninstitutional population increased from 232.715 million in Oct 2007 to 244.350 million in Dec 2012, by 11.635 million or increase of 5.0 percent, using not seasonally adjusted data. There is actually not sufficient job creation to merely absorb 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. Subsection IA4 Job Creation analyzes the types of jobs created, which are lower paying than earlier. Average hourly earnings in Dec 2012 were $23.73 seasonally adjusted (SA), increasing 2.6 percent not seasonally adjusted (NSA) relative to Nov 2011 and increasing 0.3 percent relative to Nov 2012 seasonally adjusted. In Nov 2012, average hourly earnings seasonally adjusted were $23.66, increasing 1.7 percent relative to Nov 2011 not seasonally adjusted and increasing 0.3 percent seasonally adjusted relative to Oct 2012. 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 Dec because the prices indexes of the BLS for Dec will only be released on Jan 16, 2013 (http://www.bls.gov/cpi/), which will be covered in this blog’s comment on Jan 20 together with world inflation. The second column provides changes in real wages for Nov 2012. Average hourly earnings adjusted for inflation or in constant dollars were unchanged in Nov 2012 relative to Nov 2011 but have been decreasing during many consecutive months. World inflation waves in bouts of risk aversion (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html) mask declining trend of real wages. The fractured labor market of the US is characterized by high levels of unemployment and underemployment together with falling real wages or wages adjusted for inflation in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html). The following section IA5 Stagnating Real Wages provides more detailed analysis. Average weekly hours of US workers not seasonally adjusted remained virtually unchanged at 34.5. Another headline number widely followed is the unemployment rate or number of people unemployed as percent of the labor force. The unemployment rate calculated in the household survey decreased from 7.9 percent in Oct 2012 to 7.8 percent in Nov 2012 but mostly because the labor force shrank by 257,000 as more people desist from seeking jobs because they believe none are available. The unchanged rate of unemployment of 7.8 percent in Dec 2012 is the result of increase of the number unemployed by 164,000 in the numerator of unemployment to labor force compensated by increase of the labor force by 192,000. 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 29.5 million in Dec 2012 and 28.6 million in Nov 2012. The final row in Table I-1 provides the number in job stress as percent of the actual labor force calculated at 18.2 percent in Dec 2012 and 17.7 percent in Nov 2012. Almost one in every five workers in the US is unemployed or underemployed. The combination of thirty million people in job stress, falling or stagnating real wages, collapse of hiring (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html), declining household net worth by one trillion dollars, household median income adjusted for inflation back to 1996 levels, real disposable income lower in IIIQ2012 by 0.4 percent relative to IVQ2007 (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html), federal deficits of $5.092 trillion in four years and debt/GDP of 72.6 percent in 2012 in the unsustainable path to 89.7 percent of GDP (http://cmpassocregulationblog.blogspot.com/2012/11/united-states-unsustainable-fiscal.html) and forty-eight million people in poverty and without health insurance (http://cmpassocregulationblog.blogspot.com/2012/09/collapse-of-united-states-creation-of.html) constitutes a socio-economic disaster.

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

	Dec 2012	Nov 2012
New Nonfarm Payroll Jobs	155,000	161,000
New Private Payroll Jobs	168,000	171,000
Average Hourly Earnings	$23.73 SA ∆% Dec 12/Dec 11 NSA: 2.6 ∆% Dec 12/Nov 12 SA: 0.3	Nov 12 $23.66 SA ∆% Nov 12/Nov 11 NSA: 1.7 ∆% Nov 12/Oct 12 SA: 0.3
Average Hourly Earnings in Constant Dollars	NA	∆% Nov 2012/Nov 2011: 0.0
Average Weekly Hours	34.5	34.4
Unemployment Rate Household Survey % of Labor Force SA	7.8	7.8
Number in Job Stress Unemployed and Underemployed Blog Calculation	29.5 million NSA	28.6 million NSA
In Job Stress as % Labor Force	18.2	17.7

Source: US Bureau of Labor Statistics http://www.bls.gov/data/ http://www.bls.gov/cps/ See Tables I-2, I-3, I-4, I-8, IB-1, IB-3 and IB-4.

IA2 Number of People in Job Stress. There are two approaches to calculating the number of people in job stress. The first approach consists of calculating the number of people in job stress unemployed or underemployed with the raw data of the employment situation report as in Table I-2. The data are seasonally adjusted (SA). The first three rows provide the labor force and unemployed in millions and the unemployment rate of unemployed as percent of the labor force. There is decrease in the number unemployed from 12.483 million in Aug 2012 to 12.082 million in Sep 2012 or decrease of 401,000, decrease to 12.248 million in Oct 2012 for decrease of 235,000 from Aug to Oct 2012 and further decrease to 12.042 million in Nov 2012 for decrease of 441,000 relative to Aug 2012. The number unemployed increased to 12.206 million in Dec 2012 by 164,000 relative to Nov 2012 but still decreased by 277,000 relative to Aug 2012. Thus, the rate of unemployment decreases from 8.1 percent in Aug 2012 to 7.8 percent in Sep, increasing to 7.9 percent in Oct 2012 but decreasing to 7.8 percent in Nov 2012 and 7.8 percent in Dec 2012. The labor force SA increased from 154.647 million in Aug 2012 to 155.056 million in Sep 2012 or by 409,000 and increased to 155.576 in Oct 2012 for increase of 929,000 relative to Aug 2012 but then decreased to 155.319 million in Nov 2012 for increase of 672,000 relative to Aug 2012 and to 155.511 in Dec 2012 for increase of 864,000. People have been dropping out of the labor force because they believe there are no jobs for them are actually unemployed but not counted as they stopped their job searches. The improvement of the rate of unemployment from 7.9 percent in Oct 2012 to 7.8 percent in Nov 2012 is largely because of the reduction of the labor force by 257,000. The unchanged rate of unemployment of 7.8 percent in Dec 2012 is the result of increase of the number unemployed by 164,000 in the numerator of unemployment to labor force compensated by increase of the labor force by 192,000. An important aspect of unemployment is its persistence for more than 27 weeks with 5.017 million in Oct or 40.9 percent of total unemployed, 4.784 million in Nov or 39.7 percent of total unemployed and 4.766 million in Dec or 39.1 percent of total 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 a full-time job” (http://www.bls.gov/news.release/pdf/empsit.pdf 2). The number of part-time for economic reasons increased from 8.043 million in Aug 2012 to 8.607 million in Sep 2012 or by 564,000 but decreased to 8.286 million in Oct 2012 or 243,000 more people employed part-time in Oct relative to Aug because they cannot find full-time employment. The number employed part-time for economic reasons fell to 8.138 million in Nov 2012 but fell to 7.918 million in Dec 2012 or fewer 125,000 relative to Aug 2012. Another category consists of people marginally attached to the labor force who have sought employment at some point but believe there may not be another job for them. 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 22.738 million in Dec is composed of 12.206 million unemployed (of whom 4.766 million, or 39.1 percent, unemployed for 27 weeks or more) compared with 12.042 million unemployed in Nov (of whom 4.784 million, or 39.7 percent, unemployed for 27 weeks or more), 7.918 million employed part-time for economic reasons in Dec (who suffered reductions in their work hours or could not find full-time employment) compared with 8.138 million in Nov and 2.614 million who were marginally attached to the labor force in Dec (who were not in the labor force but wanted and were available for work) compared with 2.505 million in Nov. The final row in Table I-2 provides the number in job stress as percent of the labor force: 14.6 percent in Dec, which is about equal to 14.6 percent in Nov and 14.8 percent in Oct.

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

2012	Dec 2012	Nov 2012	Oct 2012
Labor Force Millions	155.511	155.319	155.576
Unemployed Millions	12.206	12.042	12.248
Unemployment Rate (unemployed as % labor force)	7.8	7.8	7.9
Unemployed ≥27 weeks Millions	4.766	4.784	5.017
Unemployed ≥27 weeks %	39.1	39.7	40.9
Part Time for Economic Reasons Millions	7.918	8.138	8.286
Marginally Attached to Labor Force Millions	2.614	2.505	2.433
Job Stress Millions	22.738	22.685	22.967
In Job Stress as % Labor Force	14.6	14.6	14.8

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

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

Table I-3 repeats the data in Table I-2 but including Sep and additional data. What really matters is the number of people with jobs or the total employed. 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 58.6 percent. The employment to population ratio fell from an annual level of 63.1 percent in 2006 to 58.6 percent in 2012 with the lowest level at 58.4 percent in 2012.

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

	Dec 2012	Nov 2012	Oct 2012	Sep 2012
Labor Force	155.511	155.319	155.576	155.056
Unemployed	12.206	12.042	12.248	12.082
UNE Rate %	7.8	7.8	7.9	7.8
Part Time Economic Reasons	7.918	8.138	8.286	8.607
Marginally Attached to Labor Force	2.614	2.505	2.433	2.517
In Job Stress	22.738	22.685	22.967	23.206
In Job Stress % Labor Force	14.6	14.6	14.8	14.9
Employed	143.305	143.277	143.328	142.974
Employment % Population	58.6	58.7	58.7	58.7

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

The second approach is considered in the balance of this subsection. 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 2012. 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 2012 was 143.060 million (NSA) or 4.255 million fewer people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population increased from 231.958 million in Jul 2007 to 244.350 million in Dec 2012 or by 12.392 million.

Chart I-1, US, Employed, Thousands, SA, 2001-2012

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 2012. There was recovery in 2010 and 2011 but not sufficient to recover lost jobs. There are many people in the US who had jobs before the global recession who are not working now.

Chart I-2, US, Employed, 12-Month Percentage Change NSA, 2001-2012

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 grew from 142.828 million in Jan 2001 to 156.255 million in Jul 2009 but has declined to 153.905 million in Apr 2012, 154.998 million in May 2012, 156.385 million in Jun 2012, 156.526 million in Jul, 155.255 million in Aug 2012, 155.075 million Sep 2012, 155.779 million in Oct 2012, 154.953 million in Nov 2012 and 154.904 million in Dec 2012, all numbers not seasonally adjusted. Chart 1-3 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 154.904 million in Dec 2012 to the noninstitutional population of 244.350 million in Dec 2012 was 63.4 percent. The labor force of the US in Dec 2012 corresponding to 66.8 percent of participation in the population would be 163.226 million (0.668 x 244.350). The difference between the measured labor force in Dec 2012 of 154.904 million and the labor force with participation rate of 66.8 percent as in Jul 2007 of 163.226 million is 8.322 million. The level of the labor force in the US has stagnated and is 8.322 million lower than what it would have been had the same participation rate been maintained. There are millions of people who 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, 2001-2012

Source: 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.

Chart I-4, US, Civilian Labor Force, Thousands, NSA, 12-month Percentage Change, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-5 of the Bureau of Labor Statistics provides the labor force participation rate in the US or labor force as percent of the population. The labor force participation rate of the US fell from 66.8 percent in Jan 2001 to 63.4 percent NSA in Dec 2012, 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, 2001-2012

Source: 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 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, 11.742 million in Sep 2012, 11.741 million in Oct 2012, 11.404 million in Nov 2012 and 11.844 million in Dec 2012, all numbers not seasonally adjusted.

Chart I-6, US, Unemployed, Thousands, SA, 2001-2012

Source: 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.

Chart I-7, US, Unemployment Rate, SA, 2001-2012

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.

Chart I-8, US, Unemployed, 12-month Percentage Change, NSA, 2001-2012

Source: 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 9.103 million in Nov 2009, falling to 8.168 million in Dec 2011 but increasing to 8.220 million in Jan 2012 and 8.127 million in Feb 2012 but then falling to 7.918 million in Dec 2012. 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. The longer the period in part-time jobs the worst are the chances of finding another full-time job.

Chart I-9, US, Part-Time for Economic Reasons, Thousands, SA, 2001-2012

Source: 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 rate 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.

Chart I-10, US, Part-Time for Economic Reasons NSA 12-Month Percentage Change, 2001-2011

Source: 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 2009 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, 2.352 million in Mar 2012, 2.363 million in Apr 2012, 2.483 million in May 2012, 2.529 million in Jun 2012, 2.529 million in Jul 2012, 2.561 million in Aug 2012, 2.517 million in Sep 2012, 2.433 million in Oct 2012, 2.505 million in Nov 2012 and 2.614 million in Dec 2012.

Chart I-11, US, Marginally-Attached to the Labor Force, Thousands, NSA, 2001-2012

Source: 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 2012. 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.

Chart I-12, US, Marginally-Attached to the Labor Force 12-Month Percentage Change, NSA, 2001-2012

Source: 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 11.6 percent and the number of people in job stress could be around 29.5 million, which is 18.2 percent of the 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 Dec 2011, Nov 2012 and Dec 2012 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 (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). Table I-4b provides the yearly labor force participation rate from 1979 to 2012. 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 Nov and Dec 2012 and Dec 2011 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 63.8 percent by Dec 2011 and was 63.5 percent in Nov 2012 and 63.4 percent in Dec 2012, 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: (1) there are an estimated 6.856 million unemployed in Dec 2012 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM); (2) the total number of unemployed is effectively 18.700 million (Total UEM) and not 11.844 million (UEM) of whom many have been unemployed long term; (3) the rate of unemployment is 11.6 percent (Total UEM%) and not 7.6 percent, not seasonally adjusted, or 7.8 percent seasonally adjusted; and (4) the number of people in job stress is close to 29.5 million by adding the 6.856 million leaving the labor force because they believe they could not find another job. The row “In Job Stress” in Table I-4 provides the number of people in job stress not seasonally adjusted at 29.5 million in Dec 2012, 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 18.2 percent of the labor force in Dec 2012. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 58.5 percent in Dec 2011, 58.8 percent in Nov 2012 and 58.5 percent in Dec 2012; the number employed (EMP) dropped from 144 million in 2006 to 143.060 million in Dec 2012 while population increased from 229.420 million in Sep 2006 to 244.350 million in Dec 2012 or by 14.930 million. The number employed in the US fell from 146.743 million in Oct 2007 to 143.060 million in Dec 2012, by 3.683 million, or 2.5 percent, while the noninstitutional population increased from 232.715 million in Oct 2007 to 244.350 million in Dec 2012, by 11.635 million or increase of 5.0 percent, using not seasonally adjusted data. What really matters for labor input in production and wellbeing is the number of people with jobs or the employment/population ratio, which has declined and does not show signs of increasing. There are several million fewer people working in 2012 than in 2006 and the number employed is not increasing while population increased 14.930 million. 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 17 million and does not show signs of increasing in an unusual recovery without hiring (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html).

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

	2006	Dec 2011	Nov 2012	Dec 2012
POP	229	240,584	244,174	244,350
LF	151	153,373	154,953	154,904
PART%	66.2	63.8	63.5	63.4
EMP	144	140,681	143,549	143,060
EMP/POP%	62.9	58.5	58.8	58.5
UEM	7	12,692	11,404	11,844
UEM/LF Rate%	4.6	8.3	7.4	7.6
NLF	77	87,212	89,221	89,445
LF PART 66.2%		159,267	161,643	161,760
∆NLF UEM		5,894	6,690	6,856
Total UEM		18,586	18,094	18,700
Total UEM%		11.7	11.2	11.6
Part Time Economic Reasons		8,428	7,994	8,166
Marginally Attached to LF		2,540	2,505	2,614
In Job Stress		29,554	28,593	29,480
People in Job Stress as % Labor Force		18.6	17.7	18.2

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

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

Y = ∑_is_iy_i (1)

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

∆Y = ∑_i∆s_iy*_i+ ∑_i∆y_is*_i (2)

Table I-4b and Chart 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 63.4 percent in Dec 2012. 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 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 of their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors.

Table I-4b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2012

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

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

Chart 12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2012

Source: Bureau of Labor Statistics

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

Broader perspective is provided by Chart 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 12c, US, Civilian Population, Thousands, NSA, 1948-2012

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

The labor force of the United States in Chart 12d has increased along a trend similar to that of the civilian noninstitutional population in Chart 12c. There is an evident stagnation of the civilian labor force in the final segment of Chart 12c 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 12d, US, Labor Force, Thousands, NSA, 1947-2012

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 2012. 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 after 2007 is deeper and followed by a flatter curve of job creation. Economic growth is much lower in the current expansion at 2.2 percent relative to average 6.2 percent in expansions following earlier contractions.

Chart I-13, US, Employment Level, Thousands, SA, 1948-2012

Source: US Bureau of Labor Statistics

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

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

Chart I-14, US, Civilian Labor Force, SA, 1948-2012, Thousands

Source: US Bureau of Labor Statistics

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

Chart I-15 for the period from 1948 to 2012. The labor force participation rate is influenced by numerous factors such as the age of the population. There is no comparable episode in the postwar economy to the sharp collapse of the labor force participation rate in Chart I-15 during the contraction and subsequent expansion after 2007. Aging can reduce the labor force participation rate as many people retire but many may have decided to work longer as their wealth and savings have been significantly reduced. There is an important effect of many people just exiting the labor force because they believe there is no job available for them.

Chart I-15, US, Civilian Labor Force Participation Rate, SA, 1948-2012, %

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 2006 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, 1948-2012, 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 2012. 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.

Chart I-17, US, Unemployment Rate, SA, 1948-2012

Source: US Bureau of Labor Statistics

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

Chart I-18 provides the number unemployed for 27 weeks and over from 1948 to 2012. The number unemployed for 27 weeks and over jumped from 510,000 in Dec 1978 to 2.9 million in Jun 1983, by 2.4 million, or 480 percent. The number of unemployed 27 weeks or over jumped from 1.1 million in May 2007 to 6.6 million in Jun 2010, by 5.5 million, or 500 percent.

Chart I-18, US, Unemployed for 27 Weeks or More, 1948-2012, 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 58.5 NSA in Dec 2012. There is no comparable decline during an expansion in Chart I-19.

Chart I-19, US, Employment-Population Ratio, 1948-2012

Source: US Bureau of Labor Statistics

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

The number of people at work part-time for economic reasons because they cannot find full-time employment is provided in Chart I-20. The number of people at work part-time for economic reasons jumped from 3.7 million in Sep 2006 to a high of 9.4 million in Dec 2009 and 9.2 million in Jan 2011, or by 5.2 million, or 148.6 percent, all numbers not seasonally adjusted. Earlier increases in the 1980s and after the tough recession of 1991 were followed by rapid decrease that is still absent in the current expansion. The drop by 933,000 of seasonally-adjusted data from Sep to Dec 2011 while actual data without seasonal adjustment show decrease by 113,000 is not very credible.

Chart I-20, US, Part-Time for Economic Reasons, SA, 1955-2012, 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 26.7 percent cumulatively and fell 45.6 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). Data are available for the 1930s only on a yearly basis. US GDP fell 4.8 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1981 to IVQ1982 and 4.7 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first two years of the expansions in the 1980s and the current expansion. GDP grew at 4.5 percent in 1983 and 7.2 percent in 1984 while GDP grew at 2.4 percent in 2010, 1.8 percent in 2011 and at 2.0 percent in IQ2012 relative to IQ2011 and 1.5 percent in IIQ2012 relative to IQ2012. Growth in the first three quarters of 2012 accumulates to 1.59 percent, which is equivalent to 2.1 percent per year, decelerating from 2.4 percent annual growth in 2011. The US economy is growing in 2012 at the annual equivalent rate of 1.7 percent {([(1.02^1/4(1.013)^1/4(1.0173)^1/4]^4/3-1)100 = 1.7%} by excluding inventory accumulation of 0.73 percentage points and exceptional defense expenditures of 0.64 percentage points from growth 3.1 percent at SAAR in IIIQ2012 to obtain adjusted 1.73 percent SSAR. GDP grew at 4.1 percent in 1985 and 3.5 percent in 1986 while the forecasts of participants of the Federal Open Market Committee (FOMC) are in the range of 1.7 to 1.8 percent in 2012 and 2.3 to 3.0 percent in 2013 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20121212.pdf).

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

Year	GDP ∆%	Year	GDP ∆%	Year	GDP ∆%
1930	-8.6	1980	-0.3	2000	4.1
1931	-6.5	1981	2.5	2001	1.1
1932	-13.1	1982	-1.9	2002	1.8
1933	-1.3	1983	4.5	2003	2.5
1934	10.9	1984	7.2	2004	3.5
1935	8.9	1985	4.1	2005	3.1
1936	13.1	1986	3.5	2006	2.7
1937	5.1	1987	3.2	2007	1.9
1938	-3.4	1988	4.1	2008	-0.3
1930	8.1	1989	3.6	2009	-3.1
1940	8.8	1990	1.9	2010	2.4
1941	17.1	1991	-0.2	2011	1.8

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

Characteristics of the four cyclical contractions are provided 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 4.8 percent, which is almost equal to the decline of 4.7 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 26.7 percent cumulatively and fell 45.6 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). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

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

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	4	-2.5	-0.63
IIIQ1957 to IIQ1958	3	-3.1	-9.0
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.7	-0.67
IVQ2007 to IIQ2009	6	-4.7	-0.80

Sources: Business Cycle Reference Dates: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

Table I-7 shows the extraordinary contrast between the mediocre average annual equivalent growth rate of 2.2 percent of the US economy in the twelve quarters of the current cyclical expansion from IIIQ2009 to IIQ2012 and the average of 6.2 percent in the four earlier cyclical expansions. BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 percent decelerating to 1.8 percent annual growth in 2011 (http://www.bea.gov/iTable/index_nipa.cfm) and cumulative 1.59 percent in the first three quarters of 2012 {[(1.02)^1/4(1.013)^1/4(1.031)^1/4 – 1]100 = 1.59%}, which is equivalent to 2.1 percent per year {([(1.02)^1/4(1.013)^1/4(1.027)^1/4 ]^4/3 – 1)100 = 2.1%}. The US economy is growing in 2012 at the annual equivalent rate of 1.7 percent {([(1.02^1/4(1.013)^1/4(1.0173)^1/4]^4/3-1)100 = 1.7%} by excluding inventory accumulation of 0.73 percentage points and exceptional defense expenditures of 0.64 percentage points from growth 3.1 percent at SAAR in IIIQ2012 to obtain adjusted 1.73 percent SSAR. The expansion of IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 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	12.6	4.4
IIQ1958 to IIQ1959	5	10.2	8.1
IIQ1975 to IVQ1976	8	9.5	4.6
IQ1983 to IV1985	13	19.6	5.7
Average Four Above Expansions			6.2
IIIQ2009 to IIIQ2012	13	7.5	2.2

Sources: Business Cycle Reference Dates: US 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 facilitate the comparison of employment in the 1980s and 2000s. The long-term charts and tables from I-5 to I-7 in the discussion above confirm the view that the comparison of the current expansion should be with that in the 1980s because of similar dimensions. Chart I-21 provides the level of employment in the US between 1979 and 1989. Employment surged after the contraction and grew rapidly during the decade.

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

Source: US Bureau of Labor Statistics

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

The number employed in the US fell from 146.743 million in Oct 2007 to 143.060 million in Dec 2012, by 3.683 million, or 2.5 percent, while the noninstitutional population increased from 232.715 million in Oct 2007 to 244.350 million in Dec 2012, by 11.635 million or increase of 5.0 percent, using not seasonally adjusted data. Chart I-22 shows tepid recovery early in 2010 followed by near stagnation and marginal expansion.

Chart I-22, US, Employed, Thousands, 2001-2012

Source: US Bureau of Labor Statistics

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

There was a steady upward trend in growth of the civilian labor force between 1979 and 1989 as shown in Chart I-23. There were fluctuations but strong long-term dynamism over an entire decade.

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

Source: US Bureau of Labor Statistics

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

The civilian labor force in Chart I-24 grew steadily on an upward trend in the 2000s until it contracted together with the economy after 2007. There has not been recovery during the expansion but rather decline and marginal turn of the year into 2012 expansion.

Chart I-24, US, Civilian Labor Force, Thousands, 2001-2012

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

The rate of participation in the labor force declined after the recession of 2001 and stagnated 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 the expansion after 2009 with marginal expansion at the turn of the year into 2012 followed by trend of decline.

Chart I-26, US, Civilian Labor Force Participation Rate, 2001-2012, %

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 not seasonally adjusted during the first two years of expansion from the contraction. The number unemployed then fell to 6.667 million in Dec 1989 seasonally adjusted and 6.300 million not seasonally adjusted.

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

Source: US Bureau of Labor Statistics

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

Chart I-28 provides the number unemployed from 2001 to 2012. Using seasonally adjusted data, the number unemployed rose from 6.727 million in Oct 2006 to 15.382 million in Oct 2009, declining to 13.049 million in Dec 2011 and to 12.206 million in Dec 2012. 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.

Chart I-28, US, Unemployed Thousands 2001-2012

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

The rate of unemployment in the US seasonally adjusted jumped from 4.4 percent in May 2007 to 10.0 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009, as shown in Chart I-30. The rate of unemployment fluctuated at around 9.0 percent in 2011, declining to 7.8 percent in Dec 2012.

Chart I-30, US, Unemployment Rate, 2001-2012, %

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

The US employment-population ratio seasonally adjusted has fallen from 63.4 in Dec 2006 to 58.6 in Dec 2011 and 58.6 in Dec 2012, as shown in Chart I-32. 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 and 58.5 percent in Dec 2012.

Chart I-32, US, Employment Population Ratio, 2001-2012, %

Source: US Bureau of Labor Statistics

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

The number unemployed for 27 weeks or over peaked at 2.885 million in Jun 1983 as shown in Chart I-33. The number unemployed for 27 weeks or over fell sharply during the expansion to 1.393 million in Dec 1984 and continued to decline throughout the 1980s to 0.635 million in Dec 1989.

Chart I-33, US, Number Unemployed for 27 Weeks or More 1979-1989, 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 6.704 million in Apr 2010. The number of unemployed for 27 weeks remained at around 6 million during the expansion compared with somewhat above 1 million before the contraction, falling to 4.766 million in Dec 2012 seasonally adjusted and 4.618 million not seasonally adjusted.

Chart I-34, US, Number Unemployed for 27 Weeks or More, 2001-2012, 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 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.

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

Source: US Bureau of Labor Statistics

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

The number of people working part-time because they cannot find full-time employment, not seasonally adjusted, increased sharply during the contraction from 3.787 million in Apr 2006, not seasonally adjusted, to 9.354 million in Dec 2009, as shown in Chart I-36. The number of people working part-time because of failure to find an alternative occupation stagnated at a very high level during the expansion, declining to 8.166 million not seasonally adjusted in Dec 2012.

Chart I-36, US, Part-Time for Economic Reasons, 2001-2012, 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.

Chart I-37, US, Marginally Attached to the Labor Force, 2001-2012

Source: US Bureau of Labor Statistics

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

Total nonfarm payroll employment seasonally adjusted (SA) increased 155,000 in Dec 2012 and private payroll employment rose 168,000, as shown in Table I-8. The number of nonfarm jobs and private jobs created has been declining in 2012 from 275,000 in Jan 2012 to 45,000 in Jun, 132,000 in Sep, 137,000 in Oct, 161,000 in Nov and 155,000 in Dec 2012 for total nonfarm jobs and from 277,000 in Jan 2012 to 63,000 in Jun, 122,000 in Sep, 203,000 in Oct, 171,000 in Nov and 168,000 in Dec 2012 for private jobs. Average new nonfarm jobs in the quarter Dec 2011 to Feb 2012 were 252,333 per month, declining to average 130,100 per month in the ten months from Mar to Dec 2012. Average new private jobs in the quarter Dec 2011 to Feb 2012 were 255,000 per month, declining to average 137,200 per month in the ten months from Mar 2012 to Dec 2012. The US labor force stood at 154.088 million in Oct 2011 and at 155.779 million in Oct 2012, not seasonally adjusted, for increase of 1.691 million, or 140,917 per month. The US labor force stood at 153.683 million in Nov 2011 and 154.953 million in Nov 2012, not seasonally adjusted, for increase of 1.270 million or 105,833 per month. The US labor force stood at 153.373 million in Dec 2011 and 154.904 million in Dec 2012, not seasonally adjusted, for increase of 1.531 million or 127,583 per month. The average increase of 130,100 new nonfarm jobs per month in the US from Mar to Dec 2012 is insufficient even to absorb 127,583 new entrants per month into the labor force. The difference between the average increase of 137,200 new private nonfarm jobs per month in the US from Mar to Dec 2012 and the 127,583 average monthly increase in the labor force from Nov 2011 to Nov 2012 is 9,617 monthly new jobs net of absorption of new entrants in the labor force. There are 29.6 million in job stress in the US currently. The provision of 9,617 new jobs per month net of absorption of new entrants in the labor force would require 3078 months to provide jobs for the unemployed and underemployed (29.6 million divided by 9,617) or 256 years (3078 divided by 12). Net job creation of 9,617 jobs per month only adds 115,404 jobs in a year. The civilian labor force of the US in Dec 2012 not seasonally adjusted stood at 154.904 million with 11.844 million unemployed or effectively 18.700 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 8.7 years (1 million divided by product of 9,617 by 12, which is 115,404). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.745 million (0.05 times labor force of 154.904 million) for new net job creation of 4.099 million (11.844 million unemployed minus 7.745 million unemployed at rate of 5 percent) that at the current rate would take 35.5 years (4.099 million divided by 115,404). Under the calculation in this blog there are 18.700 million unemployed by including those who ceased searching because they believe there is no job for them. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 10.612 million jobs net of labor force growth that at the current rate would take 91.9 years (18.700 million minus 0.05(161.760 million) divided by 115,404, 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 the US fell from 146.743 million in Oct 2007 to 143.060 million in Dec 2012, by 3.683 million, or 2.5 percent, while the noninstitutional population increased from 232.715 million in Oct 2007 to 244.350 million in Dec 2012, by 11.635 million or increase of 5.0 percent, using not seasonally adjusted data. There is actually not sufficient job creation to merely absorb 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. 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 2011 even with population higher by 35.4 percent and labor force higher by 38.1 percent in 2009 relative to 1983 nearly three decades ago and total number of jobs in payrolls rose by 39.5 million in 2010 relative to 1983 or by 43.8 percent. Growth at 2.2 percent has been mediocre in the thirteen quarters of expansion beginning in IIIQ2009 in comparison with 6.2 percent in earlier expansions (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html) and also in terms of what is required to reduce the job stress of at around 24 million persons but likely close to 30 million. Some of the job growth and contraction in 2010 in Table I-8 is caused by the hiring and subsequent layoff of temporary workers for the 2010 census.

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

Month	1981	1982	1983	2008	2009	2010	Private
Jan	95	-327	225	41	-818	-40	-40
Feb	67	-6	-78	-84	-724	-35	-27
Mar	104	-129	173	-95	-799	189	141
Apr	74	-281	276	-208	-692	239	193
May	10	-45	277	-190	-361	516	84
Jun	196	-243	378	-198	-482	-167	92
Jul	112	-343	418	-210	-339	-58	92
Aug	-36	-158	-308	-274	-231	-51	128
Sep	-87	-181	1114	-432	-199	-27	115
Oct	-100	-277	271	-489	-202	220	196
Nov	-209	-124	352	-803	-42	121	134
Dec	-278	-14	356	-661	-171	120	140
			1984			2011	Private
Jan			447			110	119
Feb			479			220	257
Mar			275			246	261
Apr			363			251	264
May			308			54	108
Jun			379			84	102
Jul			312			96	175
Aug			241			85	52
Sep			311			202	216
Oct			286			112	139
Nov			349			157	178
Dec			127			223	234
			1985			2012	Private
Jan			266			275	277
Feb			124			259	254
Mar			346			143	147
Apr			195			68	85
May			274			87	116
Jun			145			45	63
Jul			189			181	163
Aug			193			192	134
Sep			204			132	122
Oct			187			137	203
Nov			209			161	171
Dec			168			155	168

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

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 2012. The sharp decline in total nonfarm jobs during the contraction after 2007 has been followed by initial stagnation and then inadequate growth in 2012.

Chart I-38, US, Total Nonfarm Payroll Jobs SA 2001-2012

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

Total nonfarm payroll jobs grew rapidly during the expansion in 1983 and 1984 as shown in Chart I-39. Nonfarm payroll jobs continued to grow at high rates during the remainder of the 1980s.

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

Source: US Bureau of Labor Statistics

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

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

Chart I-40, US, Total Private Payroll Jobs SA 2001-2012

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

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

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

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

IA4 Creation of Jobs. Types of jobs created, and not only the pace of job creation, may be important. Aspects of growth of payroll jobs from Nov 2011 to Nov 2012, not seasonally adjusted (NSA), are provided in Table I-9. Total nonfarm employment increased by 1,857,000 (row A, column Change), consisting of growth of total private employment by 1,916,000 (row B, column Change) and decrease by 59,000 of government employment (row C, column Change). Monthly average growth of private payroll employment has been 159,667, which is mediocre relative to 24 to 30 million in job stress, while total nonfarm employment has grown on average by only 154,750 per month, which barely keeps with 127,583 new entrants per month in the labor force. These monthly rates of job creation are insufficient to meet the demands of new entrants in the labor force and thus perpetuate unemployment and underemployment. Manufacturing employment increased by 167,000, at the monthly rate of 13,917 while private service providing employment grew by 1,695,000, at the monthly rate of 141,250. An important feature in Table I-9 is that jobs in professional and business services increased by 449,000 with temporary help services increasing by 115,000. 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 in a fractured job market. The segment leisure and hospitality added 340,000 jobs in 12 months. An important characteristic is that the loss of government jobs has stabilized in local government after heavy losses, 38,000 jobs lost in the past twelve months (row C3 Local), compensated partly by 20,000 jobs gained in state (row C2 State), while there is a higher number of employees in local government, 14.3 million relative to 5.2 million in state jobs and 2.8 million in federal jobs.

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

	Dec 2011	Dec 2012	Change
A Total Nonfarm	132,965	134,822	1,857
B Total Private	110,632	112,548	1,916
B1 Goods Producing	18,076	18,297	221
B1a Manufacturing	11,817	11,984	167
B2 Private service providing	92,556	94,251	1,695
B2a Wholesale Trade	5,580	5,669	89
B2b Retail Trade	15,231	15,434	203
B2c Transportation & Warehousing	4,435	4,469	34
B2d Financial Activities	7,707	7,793	86
B2e Professional and Business Services	17,698	18,147	449
B2e1 Temporary help services	2,506	2,621	115
B2f Health Care & Social Assistance	16,839	17,249	410
B2g Leisure & Hospitality	13,116	13,456	340
C Government	22,333	22,274	-59
C1 Federal	2,834	2,793	-41
C2 State	5,156	5,176	20
C3 Local	14,343	14,305	-38

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

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

Greater detail on the types of jobs created is provided in Table I-10 with data for Dec and Nov 2012. 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 155,000 SA total nonfarm jobs created in Dec relative to Nov actually correspond to decrease of 243,000 jobs NSA, as shown in row A. The 168,000 total private payroll jobs SA created in Dec relative to Nov actually correspond to decrease of 103,000 jobs NSA. Adjustment for seasonality isolates nonseasonal effects that suggest improvement from Nov 2012 to Dec 2012. The analysis of NSA job creation in the prior Table I-9 does show improvement over the 12 months ending in Dec 2012 that is not clouded by seasonal variations but significant reduction in 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 to even make a dent in about 30 million people unemployed or underemployed.

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

	Nov 2012 SA	Dec 2012 SA	∆	Nov 2012 NSA	Dec 2012 NSA	∆
A Total Nonfarm	133,866	134,021	155	135,065	134,822	-243
B Total Private	111,928	112,096	168	112,651	112,548	-103
B1 Goods Producing	18,330	18,389	59	18,448	18,297	-151
B1a Constr.	5,534	5,564	30	5,644	5,482	-162
B Mfg	11,963	11,988	25	11,969	11,984	15
B2 Private Service Providing	93,598	93,707	109	94,203	94,251	48
B2a Wholesale Trade	5,660	5,660	-0.1	5,675	5,669	-6
B2b Retail Trade	14,911	14,900	-11	15,346	15,434	88
B2c Couriers & Mess.	525	514	-11	548	550	2
B2d Health-care & Social Assistance	17,137	17,192	55	17,180	17,249	69
B2De Profess. & Business Services	18,046	18,065	19	18,177	18,147	-30
B2De1 Temp Help Services	2,550	2,550	-0.6	2,654	2,621	-33
B2f Leisure & Hospit.	13,753	13,784	31	13,497	13,456	-41

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

Source: US Bureau of Labor Statistics

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

Manufacturing jobs increased 25,000 in Dec 2012 relative to Nov 2012, seasonally adjusted but increased 15,000 in Dec 2012 relative to Nov 2012, not seasonally adjusted, as shown in Table I-10, because of the weaker economy and international trade. In the six months ending in Nov 2012, United States national industrial production accumulated increase of 0.3 percent at the annual equivalent rate of 0.6 percent, which is much lower than 2.5 percent growth in 12 months. Capacity utilization for total industry in the United States fell increased 0.7 percentage points in Nov to 78.4 percent from 77.7 percent in Oct, which is 1.9 percentage points lower than the long-run average from 1972 to 2011. Manufacturing increased 1.1 percent in Nov seasonally adjusted, increasing 2.5 percent not seasonally adjusted in 12 months, and increased 0.1 percent in the six months ending in Nov or at the annual equivalent rate of 0.2 percent (Section VA http://cmpassocregulationblog.blogspot.com/2012/12/united-states-commercial-banks-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2012/11/united-states-unsustainable-fiscal_18.html). Table I-13 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 86.3 percent in US national income in IIQ2012 and 86.4 percent in IIIQ2012. Most of US national income is in the form of services. In Dec 2012, there were 134.822 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 112.548 million NSA in Dec 2012 accounted for 82.9 percent of total nonfarm jobs of 135.822 million, of which 11.984 million, or 10.7 percent of total private jobs and 8.8 percent of total nonfarm jobs, were in manufacturing. Private service-producing jobs were 94.245 million NSA in Oct 2012, or 69.9 percent of total nonfarm jobs and 83.7 percent of total private-sector jobs. Manufacturing has share of 11.2 percent in US national income in IIQ2011 and 11.1 percent in IIIQ2012, 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-11, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total

	SAAR IIQ2012	% Total	SAAR IIIQ2012	% Total
National Income WCCA	13,833.6	100.0	13,969.4	100.0
Domestic Industries	13,586.3	98.2	13,726.2	98.3
Private Industries	11,933.2	86.3	12,067.6	86.4
Agriculture	131.7	0.9	138.7	1.0
Mining	208.3	1.5	203.2	1.5%
Utilities	214.6	1.6	216.8	1.6
Construction	583.7	4.2	592.7	4.2
Manufacturing	1548.1	11.2	1552.5	11.1
Durable Goods	894.3	6.5	895.6	6.4
Nondurable Goods	653.8	4.7	656.9	4.7
Wholesale Trade	853.5	6.2	837.9	6.0
Retail Trade	951.9	6.9	959.8	6.9
Transportation & WH	414.5	3.0	414.9	3.0
Information	499.1	3.6	499.6	3.6
Finance, Insurance, RE	2237.5	16.2	2324.6	16.6
Professional, BS	1971.7	14.3	1997.2	14.3
Education, Health Care	1378.1	10.0	1385.7	9.9
Arts, Entertainment	540.4	3.9	540.5	3.9
Other Services	400.0	2.9	403.6	2.9
Government	1653.0	11.9	1658.6	11.9
Rest of the World	247.3	1.8	243.1	1.7

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

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 months comparisons. Nonfarm jobs rose by 4.853 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 7.724 million in 2010 relative to 2007 and fell by 933,000 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.

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

Year	Total Nonfarm	Year	Total Nonfarm
1980	90,528	2000	131,785
1981	91,289	2001	131,826
1982	89,677	2002	130,341
1983	90,280	2003	129,999
1984	94,530	2004	131,435
1985	97,511	2005	133,703
1986	99,474	2006	136,086
1987	102,088	2007	137,598
1988	105,345	2008	136,790
1989	108,014	2009	130,807
1990	109,487	2010	129,874
1991	108,374	2011	131,359
1992	198,726	2012	133,238

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

IA5 Stagnating Real Wages. The wage bill is the product of average weekly hours times the earnings per hour. Table IA5-1 provides the estimates by the Bureau of Labor Statistics (BLS) of earnings per hour seasonally adjusted, increasing from $23.25/hour in Dec 2011 to $23.73/hour in Dec 2012, or by 2.1 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 70 percent of GDP. 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 and 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 $23.66 in Nov 2012 to $23.73 in Dec 2012. Average private weekly earnings increased $18.89 from $799.11 in Dec 2011 to $812.87 in Dec 2012 or 2.4 percent and increased from $813.90 in Nov 2012 to $818.69 in Dec 2012 or 0.6 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 $23.19 in Nov 2011 to $23.59 in Nov 2012 or by 1.7 percent (http://www.bls.gov/data/; see Table II-3 below). Data NSA are more suitable for comparison over a year. Average weekly hours NSA were 34.4 in Nov 2011 and 34.3 in Nov 2012 (http://www.bls.gov/data/; see Table II-2 below). The wage bill increased 1.4 percent in the 12 months ending in Nov 2012:

{[(wage bill in Nov 2012)/(wage bill in Nov 2011)]-1}100 =

{[($23.59x34.3)/($23.19x34.4)]-1]}100

= {[($809.13/$797.74)]-1}100 = 1.4%

CPI inflation was 1.8 percent in the 12 months ending in Nov 2012 (http://www.bls.gov/cpi/) for an inflation-adjusted wage-bill change of minus 0.3 percent :{[(1.014)/1.017)-1]100} (see Table IA5-5 below for Nov 2012). The wage bill for Dec 2012 before inflation adjustment increased 4.1 percent relative to the wage bill for Dec 2011:

{[(wage bill in Dec 2012)/(wage bill in Dec 2011)]-1}100 =

{[($23.87x34.9)/($23.26x34.4)]-1]}100

= {[($833.06/$800.14)]-1}100 = 4.1%

Average hourly earnings increased 1.7 percent from Dec 2011 to Nov 2012 {[($23.87/23.26) – 1]100 = 2.6%} while hours worked increased 1.5 percent {[(34.9/34.4) – 1]100 = 1.5%}. The increase of the wage bill is the product of the increase of hourly earnings of 2.6 percent and of hours worked of 1.5 percent {[(1.026x1.015) -1]100 = 4.1%}.

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 has reduced the rate of increase of the DJ UBS commodity index to 14.1 percent on Dec 7, 2012, relative to Jul 2, 2010 (see Table VI-4). Inflation has been rising in waves with carry trades driven by zero interest rates to commodity futures during periods of risk appetite with interruptions during risk aversion (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.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 IA5-1, US, Earnings per Hour and Average Weekly Hours SA

Earnings per Hour	Dec 2011	Oct 2012	Nov 2012	Dec 2012
Total Private	$23.25	$23.59	$23.66	$23.73
Goods Producing	$24.55	$24.77	$24.87	$24.95
Service Providing	$22.94	$23.31	$23.37	$23.44
Average Weekly Earnings
Total Private	$799.80	$809.14	$813.90	$818.69
Goods Producing	$986.91	$993.28	$999.77	$1,007.98
Service Providing	$763.90	$773.89	$778.22	$780.55
Average Weekly Hours
Total Private	34.4	34.3	34.4	34.5
Goods Producing	40.2	40.1	40.2	40.4
Service Providing	33.3	33.2	33.3	33.3

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

Table IA5-2 provides average weekly hours of all employees in the US from 2006 to 2012. Average weekly hours fell from 35.0 in Dec 2007 at the beginning of the contraction to 33.8 in Jun 2009, which was the last month of the contraction. Average weekly hours rose to 34.4 in Dec 2011 and oscillated to 34.9 in Dec 2012.

Table IA5-2, US, Average Weekly Hours of All Employees, NSA 2006-2012

Year	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
2006			34.2	34.6	34.3	34.6	34.9	34.6	34.5	34.9	34.4	34.6
2007	34.1	34.2	34.3	34.7	34.4	34.7	34.9	34.7	35.0	34.5	34.5	35.0
2008	34.2	34.2	34.8	34.4	34.4	34.9	34.5	34.6	34.4	34.4	34.6	34.1
2009	33.8	34.2	34.0	33.6	33.7	33.8	33.8	34.3	33.7	33.8	34.3	33.9
2010	33.7	33.6	33.8	34.0	34.4	34.1	34.2	34.7	34.1	34.3	34.2	34.2
2011	34.2	34.0	34.1	34.3	34.6	34.4	34.4	34.4	34.4	34.9	34.4	34.4
2012	34.5	34.2	34.3	34.7	34.3	34.4	34.8	34.5	34.9	34.3	34.3	34.9

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

Chart IB-1 provides average weekly hours monthly from Mar 2006 to Oct 2012. Average weekly hours remained relatively stable in the period before the contraction and fell sharply during the contraction as business could not support lower production with the same labor input. Average weekly hours rose rapidly during the expansion but have stabilized at a level below that prevailing before the contraction.

Chart IA5-1, US, Average Weekly Hours of All Employees, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Calculations using BLS data of inflation-adjusted average hourly earnings are shown in Table IA5-3. The final column of Table IA5-3 (“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 lost 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 0.9 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 0.6 percent in the 12 months ending in Oct 2012. Real hourly earnings fell 1.3 percent in Oct 2012 and 0.1 percent in Dec 2012. Real hourly earnings are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html).

Table IA5-3, US, Average Hourly Earnings Nominal and Inflation Adjusted, Dollars and % NSA

	AHE ALL	12 Month Nominal ∆%	∆% 12 Month CPI	12 Month Real ∆%
2007
Jan*	$20.70*	4.2*	2.1	2.1*
Feb*	$20.79*	4.1*	2.4	1.7*
Mar	$20.82	3.7	2.8	0.9
Apr	$21.05	3.3	2.6	0.7
May	$20.83	3.7	2.7	1.0
Jun	$20.82	3.8	2.7	1.1
Jul	$20.99	3.4	2.4	1.0
Aug	$20.85	3.5	2.0	1.5
Sep	$21.18	4.0	2.8	1.2
Oct	$21.07	2.7	3.5	-0.8
Nov	$21.13	3.3	4.3	-0.9
Dec	$21.37	3.7	4.1	-0.4
2010
Jan	$22.55	2.0	2.6	-0.6
Feb	$22.61	1.4	2.1	-0.7
Mar	$22.51	1.2	2.3	-1.1
Apr	$22.56	1.8	2.2	-0.4
May	$22.63	2.5	2.0	0.5
Jun	$22.37	1.7	1.1	0.6
Jul	$22.44	1.8	1.2	0.6
Aug	$22.58	1.7	1.1	0.6
Sep	$22.63	1.8	1.1	0.7
Oct	$22.73	1.9	1.2	0.7
Nov	$22.72	1.1	1.1	0.0
Dec	$22.79	1.7	1.5	0.2
2011
Jan	$23.20	2.9	1.6	1.3
Feb	$23.03	1.9	2.1	-0.2
Mar	$22.93	1.9	2.7	-0.8
Apr	$23.00	2.0	3.2	-1.2
May	$23.09	2.0	3.6	-1.5
Jun	$22.85	2.1	3.6	-1.4
Jul	$22.98	2.4	3.6	-1.2
Aug	$22.88	1.3	3.8	-2.4
Sep	$23.09	2.0	3.9	-1.8
Oct	$23.34	2.7	3.5	-0.8
Nov	$23.19	2.1	3.4	-1.3
Dec	$23.26	2.1	3.0	-0.9
2012
Jan	$23.61	1.8	2.9	-1.1
Feb	$23.45	1.8	2.9	-1.1
Mar	$23.41	2.1	2.7	-0.6
Apr	$23.64	2.8	2.3	0.5
May	$23.35	1.1	1.7	-0.6
Jun	$23.30	2.0	1.7	0.3
Jul	$23.52	2.3	1.4	0.9
Aug	$23.30	1.8	1.7	0.1
Sep	$23.70	2.6	2.0	0.6
Oct	$23.55	0.9	2.2	-1.3
Nov	$23.59	1.7	1.8	-0.1
Dec	$23.87	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/data/

Average hourly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are provided in Table IA5-4. Average hourly earnings fell 0.5 percent after adjusting for inflation in the 12 months ending in Mar 2012 and gained 0.4 percent in the 12 months ending in Apr 2011 but then lost 0.6 percent in the 12 months ending in May 2012 with a gain of 0.3 percent in the 12 months ending in Jun 2012 and 1.0 percent in Jul 2012 followed by 0.1 percent in Aug 2012 and 0.6 percent in Sep 2012. Average hourly earnings adjusted by inflation fell 1.3 percent in the 12 months ending in Oct 2012 and were unchanged in the 12 months ending in Nov 2012. Table IA5-4 confirms the trend of deterioration of purchasing power of average hourly earnings in 2011 and into 2012 with 12-month percentage declines in three of the first four months of 2012 (-1.0 percent in Jan, -1.1 percent in Feb and -0.5 percent in Mar), declines of 0.6 percent in May and 1.3 percent in Oct and increase in four (0.4 percent in May, 0.3 percent in Jun, 1.0 percent in Jul, 0.6 percent in Sep) and stagnation in two (0.1 percent in Aug and 0.0 percent in Nov). Those who still work bring back home a paycheck that buys fewer goods than a year earlier and savings in bank deposits do not pay anything because of financial repression (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html).

Table IA5-4, US, Average Hourly Earnings of All Employees NSA in Constant Dollars of 1982-1984

Year	May	Jun	Jul	Aug	Sep	Oct	Nov
2006	9.92	9.88	9.97	9.88	10.03	10.17	10.15
2007	10.02	9.99	10.08	10.03	10.16	10.08	10.05
2008	9.91	9.84	9.77	9.83	9.94	10.06	10.37
2009	10.32	10.20	10.23	10.29	10.30	10.32	10.39
2010	10.37	10.26	10.29	10.34	10.36	10.39	10.38
2011	10.22	10.12	10.17	10.10	10.18	10.31	10.25
2012	10.16	10.15	10.27	10.11	10.24	10.18	10.25
∆% 12 Months	-0.6	0.3	1.0	0.1	0.6	-1.3	0.0

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

The deterioration of purchasing power of average hourly earnings of US workers is shown by Chart IA5-2 of the US Bureau of Labor Statistics. Chart IA5-2 plots average hourly earnings of all US employees in constant 1982-1984 dollars with evident decline from 2010 to 2012.

Chart IA5-2, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Chart IA5-3 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 now 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 and marginal gain in Sep 2012 with sharp decline in Oct 2012 and stagnation in Nov 2012.

Chart IA5-3, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2012

Source: US Bureau of Labor Statistics

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

Average weekly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are provided in Table IA5-5. 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, increased 0.9 percent in the 12 months ending in Oct, fell 0.7 percent in the 12 months ending in Nov and 0.3 in the 12 months ending in Dec 2011, declining 0.3 percent in the 12 months ending in Jan 2012 and 0.4 percent in the 12 months ending in Feb 2012. Average weekly earnings in constant dollars were flat in Mar 2012 relative to Mar 2011. Average weekly earnings in constant dollars increased 1.6 percent in Apr 2012 relative to Apr 2011 but fell 1.4 percent in May 2012 relative to May 2011, increasing 0.3 percent in the 12 months ending in Jun and 2.1 percent in Jul 2012. Real weekly earnings increased 0.4 percent in the 12 months ending in Aug 2012 and 2.1 percent in the 12 months ending in Sep 2012. Real weekly earnings fell 2.9 percent in the 12 months ending in Oct 2012 and fell 0.3 percent in the 12 months ending in Nov 2012. Table IA5-5 confirms the trend of deterioration of purchasing power of average weekly earnings in 2011 and into 2012 with oscillations according to carry trades causing world inflation waves (http://cmpassocregulationblog.blogspot.com/2012/12/recovery-without-hiring-forecast-growth.html). Those who still work bring back home a paycheck that buys fewer goods than a year earlier. The fractured US job market does not provide an opportunity for advancement as in past booms following recessions.

Table IA5-5, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, NSA 2007-2012

Year	Jun	Jul	Aug	Sep	Oct	Nov
2006	341.91	347.97	341.76	346.19	354.88	349.12
2007	346.74	351.68	347.98	355.56	347.92	346.85
2008	343.40	337.06	340.18	341.83	345.95	358.83
2009	344.59	345.92	352.80	347.04	348.67	356.43
2010	349.97	352.02	358.90	353.27	356.47	355.12
2011	348.23	349.90	347.42	350.08	359.76	352.62
2012	349.28	357.26	348.93	357.44	349.20	351.46
∆% 12M	0.3	2.1	0.4	2.1	-2.9	-0.3

Source: US Bureau of Labor Statistics

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

Chart IA5-4 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.

Chart IA5-4, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Chart IA5-5, US, Average Weekly Earnings of All Employees NSA in Constant Dollars of 1982-1984 12-Month Percent Change, NSA 2007-2012

Source: US Bureau of Labor Statistics

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

IB Collapse of United States Dynamism of Income Growth and Employment Creation. There are four major approaches to the analysis of the depth of the financial crisis and global recession from IVQ2007 (Dec) to IIQ2009 (Jun) and the subpar recovery from IIIQ2009 (Jul) to the present IIIQ2012: (1) deeper contraction and slower recovery in recessions with financial crises; (2) counterfactual of avoiding deeper contraction by fiscal and monetary policies; (3) counterfactual that the financial crises and global recession would have been avoided had economic policies been different; and (4) evidence that growth rates are higher after deeper recessions with financial crises. 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). 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). Counterfactuals were used in the “new economic history” of the United States to measure the economy with or without railroads (Fishlow 1965, Fogel 1964) and also in analyzing slavery (Fogel and Engerman 1974). A critical counterfactual in economic history is how Britain surged ahead of France (North and Weingast 1989). These four approaches are discussed below in turn followed with comparison of the two recessions of the 1980s from IQ1980 (Jan) to IIIQ1980 (Jul) and from IIIQ1981 (Jul) to IVQ1982 (Nov) as dated by the National Bureau of Economic Research (NBER http://www.nber.org/cycles.html). These comparisons are not idle exercises, defining the interpretation of history and even possibly critical policies and institutional arrangements. There is active debate on these issues (Bordo 2012Oct 21 http://www.bloomberg.com/news/2012-10-21/why-this-u-s-recovery-is-weaker.html Reinhart and Rogoff, 2012Oct14 http://www.economics.harvard.edu/faculty/rogoff/files/Is_US_Different_RR_3.pdf Taylor 2012Oct 25 http://www.johnbtaylorsblog.blogspot.co.uk/2012/10/an-unusually-weak-recovery-as-usually.html, Wolf 2012Oct23 http://www.ft.com/intl/cms/s/0/791fc13a-1c57-11e2-a63b-00144feabdc0.html#axzz2AotsUk1q).

(1) Lower Growth Rates in Recessions with Financial Crises. A monumental effort of data gathering, calculation and analysis by Professors Carmen M. Reinhart and Kenneth Rogoff at Harvard University is highly relevant to banking crises, financial crash, debt crises and economic growth (Reinhart 2010CB; Reinhart and Rogoff 2011AF, 2011Jul14, 2011EJ, 2011CEPR, 2010FCDC, 2010GTD, 2009TD, 2009AFC, 2008TDPV; see also Reinhart and Reinhart 2011Feb, 2010AF and Reinhart and Sbrancia 2011). See http://cmpassocregulationblog.blogspot.com/2011/07/debt-and-financial-risk-aversion-and.html. The dataset of Reinhart and Rogoff (2010GTD, 1) is quite unique in breadth of countries and over time periods:

“Our results incorporate data on 44 countries spanning about 200 years. Taken together, the data incorporate over 3,700 annual observations covering a wide range of political systems, institutions, exchange rate and monetary arrangements and historic circumstances. We also employ more recent data on external debt, including debt owed by government and by private entities.”

Reinhart and Rogoff (2010GTD, 2011CEPR) classify the dataset of 2317 observations into 20 advanced economies and 24 emerging market economies. In each of the advanced and emerging categories, the data for countries is divided into buckets according to the ratio of gross central government debt to GDP: below 30, 30 to 60, 60 to 90 and higher than 90 (Reinhart and Rogoff 2010GTD, Table 1, 4). Median and average yearly percentage growth rates of GDP are calculated for each of the buckets for advanced economies. There does not appear to be any relation for debt/GDP ratios below 90. The highest growth rates are for debt/GDP ratios below 30: 3.7 percent for the average and 3.9 for the median. Growth is significantly lower for debt/GDP ratios above 90: 1.7 for the average and 1.9 percent for the median. GDP growth rates for the intermediate buckets are in a range around 3 percent: the highest 3.4 percent average is for the bucket 60 to 90 and 3.1 percent median for 30 to 60. There is even sharper contrast for the United States: 4.0 percent growth for debt/GDP ratio below 30; 3.4 percent growth for debt/GDP ratio of 30 to 60; 3.3 percent growth for debt/GDP ratio of 60 to 90; and minus 1.8 percent, contraction, of GDP for debt/GDP ratio above 90.

For the five countries with systemic financial crises—Iceland, Ireland, UK, Spain and the US—real average debt levels have increased by 75 percent between 2007 and 2009 (Reinhart and Rogoff 2010GTD, Figure 1). The cumulative increase in public debt in the three years after systemic banking crisis in a group of episodes after World War II is 86 percent (Reinhart and Rogoff 2011CEPR, Figure 2, 10).

An important concept is “this time is different syndrome,” which “is rooted in the firmly-held belief that financial crises are something that happens to other people in other countries at other times; crises do not happen here and now to us” (Reinhart and Rogoff 2010FCDC, 9). There is both an arrogance and ignorance in “this time is different” syndrome, as explained by Reinhart and Rogoff (2010FCDC, 34):

“The ignorance, of course, stems from the belief that financial crises happen to other people at other time in other places. Outside a small number of experts, few people fully appreciate the universality of financial crises. The arrogance is of those who believe they have figured out how to do things better and smarter so that the boom can long continue without a crisis.”

There is sober warning by Reinhart and Rogoff (2011CEPR, 42) on the basis of the momentous effort of their scholarly data gathering, calculation and analysis:

“Despite considerable deleveraging by the private financial sector, total debt remains near its historic high in 2008. Total public sector debt during the first quarter of 2010 is 117 percent of GDP. It has only been higher during a one-year sting at 119 percent in 1945. Perhaps soaring US debt levels will not prove to be a drag on growth in the decades to come. However, if history is any guide, that is a risky proposition and over-reliance on US exceptionalism may only be one more example of the “This Time is Different” syndrome.”

As both sides of the Atlantic economy maneuver around defaults the experience on debt and growth deserves significant emphasis in research and policy. The world economy is slowing with high levels of unemployment in advanced economies. Countries do not grow themselves out of unsustainable debts but rather through de facto defaults by means of financial repression and in some cases through inflation. The conclusion is that this time is not different.

Professor Alan M. Taylor (2012) at the University of Virginia analyzes own and collaborative research on 140 years of history with data from 14 advanced economies in the effort to elucidate experience anticipating, during and after financial crises. The conclusion is (Allan M. Taylor 2012, 8):

“Recessions might be painful, but they tend to be even more painful when combined with financial crises or (worse) global crises, and we already know that post-2008 experience will not overturn this conclusion. The impact on credit is also very strong: financial crises lead to strong setbacks in the rate of growth of loans as compared to what happens in normal recessions, and this effect is strong for global crises. Finally, inflation generally falls in recessions, but the downdraft is stronger in financial crisis times.”

Alan M. Taylor (2012) also finds that advanced economies entered the global recession with the largest financial sector in history. There was doubling after 1980 of the ratio of loans to GDP and tripling of the size of bank balance sheets. In contrast, in the period from 1950 to 1970 there was high investment, savings and growth in advanced economies with firm regulation of finance and controls of foreign capital flows.

(2) Counterfactual of the Global Recession. There is a difficult decision on when to withdraw the fiscal stimulus that could have adverse consequences on current growth and employment analyzed by Krugman (2011Jun18). CBO (2011JunLTBO, Chapter 2) considers the timing of withdrawal as well as the equally tough problems that result from not taking prompt action to prevent a possible debt crisis in the future. Krugman (2011Jun18) refers to Eggertsson and Krugman (2010) on the possible contractive effects of debt. The world does not become poorer as a result of debt because an individual’s asset is another’s liability. Past levels of credit may become unacceptable by credit tightening, such as during a financial crisis. Debtors are forced into deleveraging, which results in expenditure reduction, but there may not be compensatory effects by creditors who may not be in need of increasing expenditures. The economy could be pushed toward the lower bound of zero interest rates, or liquidity trap, remaining in that threshold of deflation and high unemployment.

Analysis of debt can lead to the solution of the timing of when to cease stimulus by fiscal spending (Krugman 2011Jun18). Excessive debt caused the financial crisis and global recession and it is difficult to understand how more debt can recover the economy. Krugman (2011Jun18) argues that the level of debt is not important because one individual’s asset is another individual’s liability. The distribution of debt is important when economic agents with high debt levels are encountering different constraints than economic agents with low debt levels. The opportunity for recovery may exist in borrowing by some agents that can adjust the adverse effects of past excessive borrowing by other agents. As Krugman (2011Jun18, 20) states:

“Suppose, in particular, that the government can borrow for a while, using the borrowed money to buy useful things like infrastructure. The true social cost of these things will be very low, because the spending will be putting resources that would otherwise be unemployed to work. And government spending will also make it easier for highly indebted players to pay down their debt; if the spending is sufficiently sustained, it can bring the debtors to the point where they’re no longer so severely balance-sheet constrained, and further deficit spending is no longer required to achieve full employment. Yes, private debt will in part have been replaced by public debt – but the point is that debt will have been shifted away from severely balance-sheet-constrained players, so that the economy’s problems will have been reduced even if the overall level of debt hasn’t fallen. The bottom line, then, is that the plausible-sounding argument that debt can’t cure debt is just wrong. On the contrary, it can – and the alternative is a prolonged period of economic weakness that actually makes the debt problem harder to resolve.”

Besides operational issues, the consideration of this argument would require specifying and measuring two types of gains and losses from this policy: (1) the benefits in terms of growth and employment currently; and (2) the costs of postponing the adjustment such as in the exercise by CBO (2011JunLTO, 28-31) in Table 11. It may be easier to analyze the costs and benefits than actual measurement.

An analytical and empirical approach is followed by Blinder and Zandi (2010), using the Moody’s Analytics model of the US economy with four different scenarios: (1) baseline with all policies used; (2) counterfactual including all fiscal stimulus policies but excluding financial stimulus policies; (3) counterfactual including all financial stimulus policies but excluding fiscal stimulus; and (4) a scenario excluding all policies. The scenario excluding all policies is an important reference or the counterfactual of what would have happened if the government had been entirely inactive. A salient feature of the work by Blinder and Zandi (2010) is the consideration of both fiscal and financial policies. There was probably more activity with financial policies than with fiscal policies. Financial policies included the Fed balance sheet, 11 facilities of direct credit to illiquid segments of financial markets, interest rate policy, the Financial Stability Plan including stress tests of banks, the Troubled Asset Relief Program (TARP) and others (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 157-67; Regulation of Banks and Finance (2009a), 224-7).

Blinder and Zandi (2010, 4) find that:

“In the scenario that excludes all the extraordinary policies, the downturn continues into 2011. Real GDP falls a stunning 7.4% in 2009 and another 3.7% in 2010 (see Table 3). The peak-to-trough decline in GDP is therefore close to 12%, compared to an actual decline of about 4%. By the time employment hits bottom, some 16.6 million jobs are lost in this scenario—about twice as many as actually were lost. The unemployment rate peaks at 16.5%, and although not determined in this analysis, it would not be surprising if the underemployment rate approached one-fourth of the labor force. The federal budget deficit surges to over $2 trillion in fiscal year 2010, $2.6 trillion in fiscal year 2011, and $2.25 trillion in FY 2012. Remember, this is with no policy response. With outright deflation in prices and wages in 2009-2011, this dark scenario constitutes a 1930s-like depression.”

The conclusion by Blinder and Zandi (2010) is that if the US had not taken massive fiscal and financial measures the economy could have suffered far more during a prolonged period. There are still a multitude of questions that cloud understanding of the impact of the recession and what would have happened without massive policy impulses. Some effects are quite difficult to measure. An important argument by Blinder and Zandi (2010) is that this evaluation of counterfactuals is relevant to the need of stimulus if economic conditions worsened again.

(3) Counterfactual of Policies Causing the Financial Crisis and Global Recession. 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 recessions 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; see http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html) and that 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).

The explanation of the sharp contraction of United States housing can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:

“On the maturity date T, the firm must either pay the promised payment of B to the debtholders or else the current equity will be valueless. Clearly, if at time T, V(T) > B, the firm should pay the bondholders because the value of equity will be V(T) – B > 0 whereas if they do not, the value of equity would be zero. If V(T) ≤ B, then the firm will not make the payment and default the firm to the bondholders because otherwise the equity holders would have to pay in additional money and the (formal) value of equity prior to such payments would be (V(T)- B) < 0.”

Pelaez and Pelaez (The Global Recession Risk (2007), 208-9) apply this analysis to the US housing market in 2005-2006 concluding:

“The house market [in 2006] is probably operating with low historical levels of individual equity. There is an application of structural models [Duffie and Singleton 2003] to the individual decisions on whether or not to continue paying a mortgage. The costs of sale would include realtor and legal fees. There could be a point where the expected net sale value of the real estate may be just lower than the value of the mortgage. At that point, there would be an incentive to default. The default vulnerability of securitization is unknown.”

There are multiple important determinants of the interest rate: “aggregate wealth, the distribution of wealth among investors, expected rate of return on physical investment, taxes, government policy and inflation” (Ingersoll 1987, 405). Aggregate wealth is a major driver of interest rates (Ibid, 406). Unconventional monetary policy, with zero fed funds rates and flattening of long-term yields by quantitative easing, causes uncontrollable effects on risk taking that can have profound undesirable effects on financial stability. Excessively aggressive and exotic monetary policy is the main culprit and not the inadequacy of financial management and risk controls.

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 (Ibid). According to a subsequent restatement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption decisions 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→∞.

Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment but the exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at close to zero interest rates, 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 to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4).

There are significant elements of the theory of bank financial fragility of Diamond and Dybvig (1983) and Diamond and Rajan (2000, 2001a, 2001b) that help to explain the financial fragility of banks during the credit/dollar crisis (see also Diamond 2007). The theory of Diamond and Dybvig (1983) as exposed by Diamond (2007) is that banks funding with demand deposits have a mismatch of liquidity (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 58-66). A run occurs when too many depositors attempt to withdraw cash at the same time. All that is needed is an expectation of failure of the bank. Three important functions of banks are providing evaluation, monitoring and liquidity transformation. Banks invest in human capital to evaluate projects of borrowers in deciding if they merit credit. The evaluation function reduces adverse selection or financing projects with low present value. Banks also provide important monitoring services of following the implementation of projects, avoiding moral hazard that funds be used for, say, real estate speculation instead of the original project of factory construction. The transformation function of banks involves both assets and liabilities of bank balance sheets. Banks convert an illiquid asset or loan for a project with cash flows in the distant future into a liquid liability in the form of demand deposits that can be withdrawn immediately.

In the theory of banking of Diamond and Rajan (2000, 2001a, 2001b), the bank creates liquidity by tying human assets to capital. The collection of skills of the relationship banker converts an illiquid project of an entrepreneur into liquid demand deposits that are immediately available for withdrawal. The deposit/capital structure is fragile because of the threat of bank runs. In these days of online banking, the run on Washington Mutual was through withdrawals online. A bank run can be triggered by the decline of the value of bank assets below the value of demand deposits.

Pelaez and Pelaez (Regulation of Banks and Finance 2009b, 60, 64-5) find immediate application of the theories of banking of Diamond, Dybvig and Rajan to the credit/dollar crisis after 2007. It is a credit crisis because the main issue was the deterioration of the credit portfolios of securitized banks as a result of default of subprime mortgages. It is a dollar crisis because of the weakening dollar resulting from relatively low interest rate policies of the US. It caused systemic effects that converted into a global recession not only because of the huge weight of the US economy in the world economy but also because the credit crisis transferred to the UK and Europe. Management skills or human capital of banks are illustrated by financial engineering of complex products. The increasing importance of human relative to inanimate capital (Rajan and Zingales 2000) is revolutionizing the theory of the firm (Zingales 2000) and corporate governance (Rajan and Zingales 2001). Finance is one of the most important examples of this transformation. Profits were derived from the charter in the original banking institution. Pricing and structuring financial instruments was revolutionized with option pricing formulas developed by Black and Scholes (1973) and Merton (1973, 1974, 1998) that permitted the development of complex products with fair pricing. The successful financial company must attract and retain finance professionals who have invested in human capital, which is a sunk cost to them and not of the institution where they work.

The complex financial products created for securitized banking with high investments in human capital are based on houses, which are as illiquid as the projects of entrepreneurs in the theory of banking. The liquidity fragility of the securitized bank is equivalent to that of the commercial bank in the theory of banking (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65). Banks created off-balance sheet structured investment vehicles (SIV) that issued commercial paper receiving AAA rating because of letters of liquidity guarantee by the banks. The commercial paper was converted into liquidity by its use as collateral in SRPs at the lowest rates and minimal haircuts because of the AAA rating of the guarantor bank. In the theory of banking, default can be triggered when the value of assets is perceived as lower than the value of the deposits. Commercial paper issued by SIVs, securitized mortgages and derivatives all obtained SRP liquidity on the basis of illiquid home mortgage loans at the bottom of the pyramid. The run on the securitized bank had a clear origin (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65):

“The increasing default of mortgages resulted in an increase in counterparty risk. Banks were hit by the liquidity demands of their counterparties. The liquidity shock extended to many segments of the financial markets—interbank loans, asset-backed commercial paper (ABCP), high-yield bonds and many others—when counterparties preferred lower returns of highly liquid safe havens, such as Treasury securities, than the risk of having to sell the collateral in SRPs at deep discounts or holding an illiquid asset. The price of an illiquid asset is near zero.”

Gorton and Metrick (2010H, 507) provide a revealing quote to the work in 1908 of Edwin R. A. Seligman, professor of political economy at Columbia University, founding member of the American Economic Association and one of its presidents and successful advocate of progressive income taxation. The intention of the quote is to bring forth the important argument that financial crises are explained in terms of “confidence” but as Professor Seligman states in reference to historical banking crises in the US the important task is to explain what caused the lack of confidence. It is instructive to repeat the more extended quote of Seligman (1908, xi) on the explanations of banking crises:

“The current explanations may be divided into two categories. Of these the first includes what might be termed the superficial theories. Thus it is commonly stated that the outbreak of a crisis is due to lack of confidence,--as if the lack of confidence was not in itself the very thing which needs to be explained. Of still slighter value is the attempt to associate a crisis with some particular governmental policy, or with some action of a country’s executive. Such puerile interpretations have commonly been confined to countries like the United States, where the political passions of democracy have had the fullest way. Thus the crisis of 1893 was ascribed by the Republicans to the impending Democratic tariff of 1894; and the crisis of 1907 has by some been termed the ‘[Theodore] Roosevelt panic,” utterly oblivious of the fact that from the time of President Jackson, who was held responsible for the troubles of 1837, every successive crisis had had its presidential scapegoat, and has been followed by a political revulsion. Opposed to these popular, but wholly unfounded interpretations, is the second class of explanations, which seek to burrow beneath the surface and to discover the more occult and fundamental causes of the periodicity of crises.”

Scholars ignore superficial explanations in the effort to seek good and truth. The problem of economic analysis of the credit/dollar crisis is the lack of a structural model with which to attempt empirical determination of causes (Gorton and Metrick 2010SB). There would still be doubts even with a well-specified structural model because samples of economic events do not typically permit separating causes and effects. There is also confusion is separating the why of the crisis and how it started and propagated, all of which are extremely important.

In true heritage of the principles of Seligman (1908), Gorton (2009EFM) discovers a prime causal driver of the credit/dollar crisis. The objective of subprime and Alt-A mortgages was to facilitate loans to populations with modest means so that they could acquire a home. These borrowers would not receive credit because of (1) lack of funds for down payments; (2) low credit rating and information; (3) lack of information on income; and (4) errors or lack of other information. Subprime mortgage “engineering” was based on the belief that both lender and borrower could benefit from increases in house prices over the short run. The initial mortgage would be refinanced in two or three years depending on the increase of the price of the house. According to Gorton (2009EFM, 13, 16):

“The outstanding amounts of Subprime and Alt-A [mortgages] combined amounted to about one quarter of the $6 trillion mortgage market in 2004-2007Q1. Over the period 2000-2007, the outstanding amount of agency mortgages doubled, but subprime grew 800%! Issuance in 2005 and 2006 of Subprime and Alt-A mortgages was almost 30% of the mortgage market. Since 2000 the Subprime and Alt-A segments of the market grew at the expense of the Agency (i.e., the government sponsored entities of Fannie Mae and Freddie Mac) share, which fell from almost 80% (by outstanding or issuance) to about half by issuance and 67% by outstanding amount. The lender’s option to rollover the mortgage after an initial period is implicit in the subprime mortgage. The key design features of a subprime mortgage are: (1) it is short term, making refinancing important; (2) there is a step-up mortgage rate that applies at the end of the first period, creating a strong incentive to refinance; and (3) there is a prepayment penalty, creating an incentive not to refinance early.”

The prime objective of successive administrations in the US during the past 20 years and actually since the times of Roosevelt in the 1930s has been to provide “affordable” financing for the “American dream” of home ownership. The US housing finance system is mixed with public, public/private and purely private entities. The Federal Home Loan Bank (FHLB) system was established by Congress in 1932 that also created the Federal Housing Administration in 1934 with the objective of insuring homes against default. In 1938, the government created the Federal National Mortgage Association, or Fannie Mae, to foster a market for FHA-insured mortgages. Government-insured mortgages were transferred from Fannie Mae to the Government National Mortgage Association, or Ginnie Mae, to permit Fannie Mae to become a publicly-owned company. Securitization of mortgages began in 1970 with the government charter to the Federal Home Loan Mortgage Corporation, or Freddie Mac, with the objective of bundling mortgages created by thrift institutions that would be marketed as bonds with guarantees by Freddie Mac (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 42-8). In the third quarter of 2008, total mortgages in the US were $12,057 billion of which 43.5 percent, or $5423 billion, were retained or guaranteed by Fannie Mae and Freddie Mac (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 45). In 1990, Fannie Mae and Freddie Mac had a share of only 25.4 percent of total mortgages in the US. Mortgages in the US increased from $6922 billion in 2002 to $12,088 billion in 2007, or by 74.6 percent, while the retained or guaranteed portfolio of Fannie and Freddie rose from $3180 billion in 2002 to $4934 billion in 2007, or by 55.2 percent.

According to Pinto (2008) in testimony to Congress:

“There are approximately 25 million subprime and Alt-A loans outstanding, with an unpaid principal amount of over $4.5 trillion, about half of them held or guaranteed by Fannie and Freddie. Their high risk activities were allowed to operate at 75:1 leverage ratio. While they may deny it, there can be no doubt that Fannie and Freddie now own or guarantee $1.6 trillion in subprime, Alt-A and other default prone loans and securities. This comprises over 1/3 of their risk portfolios and amounts to 34% of all the subprime loans and 60% of all Alt-A loans outstanding. These 10.5 million unsustainable, nonprime loans are experiencing a default rate 8 times the level of the GSEs’ 20 million traditional quality loans. The GSEs will be responsible for a large percentage of an estimated 8.8 million foreclosures expected over the next 4 years, accounting for the failure of about 1 in 6 home mortgages. Fannie and Freddie have subprimed America.”

In perceptive analysis of growth and macroeconomics in the past six decades, Rajan (2012FA) argues that “the West can’t borrow and spend its way to recovery.” The Keynesian paradigm is not applicable in current conditions. Advanced economies in the West could be divided into those that reformed regulatory structures to encourage productivity and others that retained older structures. In the period from 1950 to 2000, Cobet and Wilson (2002) find that US productivity, measured as output/hour, grew at the average yearly rate of 2.9 percent while Japan grew at 6.3 percent and Germany at 4.7 percent (see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). In the period from 1995 to 2000, output/hour grew at the average yearly rate of 4.6 percent in the US but at lower rates of 3.9 percent in Japan and 2.6 percent in Germany. Rajan (2012FA) argues that the differential in productivity growth was accomplished by deregulation in the US at the end of the 1970s and during the 1980s. In contrast, Europe did not engage in reform with the exception of Germany in the early 2000s that empowered the German economy with significant productivity advantage. At the same time, technology and globalization increased relative remunerations in highly-skilled, educated workers relative to those without skills for the new economy. It was then politically appealing to improve the fortunes of those left behind by the technological revolution by means of increasing cheap credit. As Rajan (2012FA) argues:

“In 1992, Congress passed the Federal Housing Enterprises Financial Safety and Soundness Act, partly to gain more control over Fannie Mae and Freddie Mac, the giant private mortgage agencies, and partly to promote affordable homeownership for low-income groups. Such policies helped money flow to lower-middle-class households and raised their spending—so much so that consumption inequality rose much less than income inequality in the years before the crisis. These policies were also politically popular. Unlike when it came to an expansion in government welfare transfers, few groups opposed expanding credit to the lower-middle class—not the politicians who wanted more growth and happy constituents, not the bankers and brokers who profited from the mortgage fees, not the borrowers who could now buy their dream houses with virtually no money down, and not the laissez-faire bank regulators who thought they could pick up the pieces if the housing market collapsed. The Federal Reserve abetted these shortsighted policies. In 2001, in response to the dot-com bust, the Fed cut short-term interest rates to the bone. Even though the overstretched corporations that were meant to be stimulated were not interested in investing, artificially low interest rates acted as a tremendous subsidy to the parts of the economy that relied on debt, such as housing and finance. This led to an expansion in housing construction (and related services, such as real estate brokerage and mortgage lending), which created jobs, especially for the unskilled. Progressive economists applauded this process, arguing that the housing boom would lift the economy out of the doldrums. But the Fed-supported bubble proved unsustainable. Many construction workers have lost their jobs and are now in deeper trouble than before, having also borrowed to buy unaffordable houses. Bankers obviously deserve a large share of the blame for the crisis. Some of the financial sector’s activities were clearly predatory, if not outright criminal. But the role that the politically induced expansion of credit played cannot be ignored; it is the main reason the usual checks and balances on financial risk taking broke down.”

In fact, Raghuram G. Rajan (2005) anticipated low liquidity in financial markets resulting from low interest rates before the financial crisis that caused distortions of risk/return decisions provoking the credit/dollar crisis and global recession from IVQ2007 to IIQ2009. Near zero interest rates of unconventional monetary policy induced excessive risks and low liquidity in financial decisions that were critical as a cause of the credit/dollar crisis after 2007. Rajan (2012FA) argues that it is not feasible to return to the employment and income levels before the credit/dollar crisis because of the bloated construction sector, financial system and government budgets.

(4) Historically Sharper Recoveries from Deeper Contractions and Financial Crises. Professor Michael D. Bordo (2012Sep27), at Rutgers University, is providing clear thought on the correct comparison of the current business cycles in the United States with those in United States history. There are two issues raised by Professor Bordo: (1) lumping together countries with different institutions, economic policies and financial systems; and (2) the conclusion that growth is mediocre after financial crises and deep recessions, which is repeated daily in the media, but that Bordo and Haubrich (2012DR) persuasively demonstrate to be inconsistent with United States experience.

Depriving economic history of institutions is perilous as is illustrated by the economic history of Brazil. Douglass C. North (1994) emphasized the key role of institutions in explaining economic history. Rondo E. Cameron (1961, 1967, 1972) applied institutional analysis to banking history. Friedman and Schwartz (1963) analyzed the relation of money, income and prices in the business cycle and related the monetary policy of an important institution, the Federal Reserve System, to the Great Depression. Bordo, Choudhri and Schwartz (1995) analyze the counterfactual of what would have been economic performance if the Fed had used during the Great Depression the Friedman (1960) monetary policy rule of constant growth of money(for analysis of the Great Depression see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 198-217). Alan Meltzer (2004, 2010a,b) analyzed the Federal Reserve System over its history. The reader would be intrigued by Figure 5 in Reinhart and Rogoff (2010FCDC, 15) in which Brazil is classified in external default for seven years between 1828 and 1834 but not again until 64 years later in 1989, above the 50 years of incidence for “serial default”. This void has been filled in scholarly research on nineteenth-century Brazil by William R. Summerhill, Jr. (2007SC, 2007IR). There are important conclusions by Summerhill on the exceptional sample of institutional change or actually lack of change, public finance and financial repression in Brazil between 1822 an 1899, combining tools of economics, political science and history. During seven continuous decades, Brazil did not miss a single interest payment with government borrowing without repudiation of debt or default. What is really surprising is that Brazil borrowed by means of long-term bonds and even more surprising interest rates fell over time. The external debt of Brazil in 1870 was ₤41,275,961 and the domestic debt in the internal market was ₤25,708,711, or 62.3 percent of the total (Summerhill 2007IR, 73).

The experience of Brazil differed from that of Latin America (Summerhill 2007IR). During the six decades when Brazil borrowed without difficulty, Latin American countries becoming independent after 1820 engaged in total defaults, suffering hardship in borrowing abroad. The countries that borrowed again fell again in default during the nineteenth century. Venezuela defaulted in four occasions. Mexico defaulted in 1827, rescheduling its debt eight different times and servicing the debt sporadically. About 44 percent of Latin America’s sovereign debt was in default in 1855 and approximately 86 percent of total government loans defaulted in London originated in Spanish American borrowing countries.

External economies of commitment to secure private rights in sovereign credit would encourage development of private financial institutions, as postulated in classic work by North and Weingast (1989), Summerhill 2007IR, 22). This is how banking institutions critical to the Industrial Revolution were developed in England (Cameron 1967). The obstacle in Brazil found by Summerhill (2007IR) is that sovereign debt credibility was combined with financial repression. There was a break in Brazil of the chain of effects from protecting public borrowing, as in North and Weingast (1989), to development of private financial institutions. According to Pelaez 1976, 283) following Cameron:

“The banking law of 1860 placed severe restrictions on two basic modern economic institutions—the corporation and the commercial bank. The growth of the volume of bank credit was one of the most significant factors of financial intermediation and economic growth in the major trading countries of the gold standard group. But Brazil placed strong restrictions on the development of banking and intermediation functions, preventing the channeling of coffee savings into domestic industry at an earlier date.”

Brazil actually abandoned the gold standard during multiple financial crises in the nineteenth century, as it should have to protect domestic economic activity. Pelaez (1975, 447) finds similar experience in the first half of nineteenth-century Brazil:

“Brazil’s experience is particularly interesting in that in the period 1808-1851 there were three types of monetary systems. Between 1808 and 1829, there was only one government-related Bank of Brazil, enjoying a perfect monopoly of banking services. No new banks were established in the 1830s after the liquidation of the Bank of Brazil in 1829. During the coffee boom in the late 1830s and 1840s, a system of banks of issue, patterned after similar institutions in the industrial countries [Cameron 1967], supplied the financial services required in the first stage of modernization of the export economy.”

Financial crises in the advanced economies were transmitted to nineteenth-century Brazil by the arrival of a ship (Pelaez and Suzigan 1981). The explanation of those crises and the economy of Brazil requires knowledge and roles of institutions, economic policies and the financial system chosen by Brazil, in agreement with Bordo (2012Sep27).

The departing theoretical framework of Bordo and Haubrich (2012DR) is the plucking model of Friedman (1964, 1988). Friedman (1988, 1) recalls “I was led to the model in the course of investigating the direction of influence between money and income. Did the common cyclical fluctuation in money and income reflect primarily the influence of money on income or of income on money?” Friedman (1964, 1988) finds useful for this purpose to analyze the relation between expansions and contractions. Analyzing the business cycle in the United States between 1870 and 1961, Friedman (1964, 15) found that “a large contraction in output tends to be followed on the average by a large business expansion; a mild contraction, by a mild expansion.” The depth of the contraction opens up more room in the movement toward full employment (Friedman 1964, 17):

“Output is viewed as bumping along the ceiling of maximum feasible output except that every now and then it is plucked down by a cyclical contraction. Given institutional rigidities and prices, the contraction takes in considerable measure the form of a decline in output. Since there is no physical limit to the decline short of zero output, the size of the decline in output can vary widely. When subsequent recovery sets in, it tends to return output to the ceiling; it cannot go beyond, so there is an upper limit to output and the amplitude of the expansion tends to be correlated with the amplitude of the contraction.”

Kim and Nelson (1999) test the asymmetric plucking model of Friedman (1964, 1988) relative to a symmetric model using reference cycles of the NBER and find evidence supporting the Friedman model. Bordo and Haubrich (2012DR) analyze 27 cycles beginning in 1872, using various measures of financial crises while considering different regulatory and monetary regimes. The revealing conclusion of Bordo and Haubrich (2012DR, 2) is that:

“Our analysis of the data shows that steep expansions tend to follow deep contractions, though this depends heavily on when the recovery is measured. In contrast to much conventional wisdom, the stylized fact that deep contractions breed strong recoveries is particularly true when there is a financial crisis. In fact, on average, it is cycles without a financial crisis that show the weakest relation between contraction depth and recovery strength. For many configurations, the evidence for a robust bounce-back is stronger for cycles with financial crises than those without.”

The average rate of growth of real GDP in expansions after recessions with financial crises was 8 percent but only 6.9 percent on average for recessions without financial crises (Bordo 2012Sep27). Real GDP declined 12 percent in the Panic of 1907 and increased 13 percent in the recovery, consistent with the plucking model of Friedman (Bordo 2012Sep27). Bordo (2012Sep27) finds two probable explanations for the weak recovery during the current economic cycle: (1) collapse of United States housing; and (2) uncertainty originating in fiscal policy, regulation and structural changes. There are serious doubts if monetary policy is adequate to recover the economy under these conditions.

Lucas (2011May) estimates US economic growth in the long-term at 3 percent per year and about 2 percent per year in per capita terms. There are displacements from this trend caused by events such as wars and recessions but the economy then returns to trend. Historical US GDP data exhibit remarkable growth: Lucas (2011May) estimates an increase of US real income per person by a factor of 12 in the period from 1870 to 2010. The explanation by Lucas (2011May) of this remarkable growth experience is that government provided stability and education while elements of “free-market capitalism” were an important driver of long-term growth and prosperity. The analysis is sharpened by comparison with the long-term growth experience of G7 countries (US, UK, France, Germany, Canada, Italy and Japan) and Spain from 1870 to 2010. Countries benefitted from “common civilization” and “technology” to “catch up” with the early growth leaders of the US and UK, eventually growing at a faster rate. Significant part of this catch up occurred after World War II. Lucas (2011May) finds that the catch up stalled in the 1970s. The analysis of Lucas (2011May) is that the 20-40 percent gap that developed originated in differences in relative taxation and regulation that discouraged savings and work incentives in comparison with the US. A larger welfare and regulatory state, according to Lucas (2011May), could be the cause of the 20-40 percent gap. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Long-term economic growth and prosperity are measured by the key indicators of growth of real income per capita, or what is earned per person after inflation. A refined concept would include real disposable income per capita, or what is earned per person after inflation and taxes.

Table IB-1 provides the data required for broader comparison of the cyclical expansions of IQ1983 to IVQ1985 and the current one from 2009 to 2012. First, in the 13 quarters from IQ1983 to IVQ1985, GDP increased 19.6 percent at the annual equivalent rate of 5.7 percent; real disposable personal income (RDPI) increased 14.5 percent at the annual equivalent rate of 4.3 percent; RDPI per capita increased 11.5 percent at the annual equivalent rate of 3.4 percent; and population increased 2.7 percent at the annual equivalent rate of 0.8 percent. Second, in the 13 quarters of the current cyclical expansion from IIIQ2009 to IIIQ2012, GDP increased 7.4 percent at the annual equivalent rate of 2.2 percent. In the 12 quarters of cyclical expansion real disposable personal income (RDPI) increased 5.4 percent at the annual equivalent rate of 1.6 percent; RDPI per capita increased 3.0 percent at the annual equivalent rate of 0.9 percent; and population increased 2.3 percent at the annual equivalent rate of 0.7 percent. Third, since the beginning of the recession in IVQ2007 to IIIQ2012, GDP increased 2.5 percent, or barely above the level before the recession. Since the beginning of the recession in IVQ2007 to IIIQ2012, real disposable personal income increased 3.4 percent at the annual equivalent rate of 0.7 percent; population increased 3.9 percent at the annual equivalent rate of 0.8 percent; and real disposable personal income per capita is 0.4 percent lower than the level before the recession. Real disposable personal income is the actual take home pay after inflation and taxes and real disposable income per capita is what is left per inhabitant. The current cyclical expansion is the worst in the period after World War II in terms of growth of economic activity and income. The United States grew during its history at high rates of per capita income that made its economy the largest in the world. That dynamism is disappearing. Bordo (2012 Sep27) and Bordo and Haubrich (2012DR) provide strong evidence that recoveries have been faster after deeper recessions and recessions with financial crises, casting serious doubts on the conventional explanation of weak growth during the current expansion allegedly because of the depth of the contraction from IVQ2007 to IIQ2009 of 4.7 percent and the financial crisis.

Table IB-1, US, GDP, Real Disposable Personal Income, Real Disposable Income per Capita and Population in 1983-85 and 2007-2011, %

	# Quarters	∆%	∆% Annual Equivalent
IQ1983 to IVQ1985	13
GDP		19.6	5.7
RDPI		14.5	4.3
RDPI Per Capita		11.5	3.4
Population		2.7	0.8
IIIQ2009 to IIIQ2012	13
GDP		7.5	2.2
RDPI		5.4	1.6
RDPI per Capita		3.0	0.9
Population		2.3	0.7
IVQ2007 to IIIQ2012	20
GDP		2.5	0.5
RDPI		3.4	0.7
RDPI per Capita		-0.4
Population		3.9	0.8

RDPI: Real Disposable Personal Income

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

There are seven basic facts illustrating the current economic disaster of the United States: (1) GDP maintained trend growth in the entire business cycle from IQ1980 to IV1985, including contractions and expansions, but is well below trend in the entire business cycle from IVQ2007 to IIQ2012, including contractions and expansions; (2) per capita real disposable income exceeded trend growth in the 1980s but is substantially below trend in IIQ2012; (3) the number of employed persons increased in the 1980s but declined into IIQ2012; (4) the number of full-time employed persons increased in the 1980s but declined into IIIQ2012; (5) the number unemployed, unemployment rate and number employed part-time for economic reasons fell in the recovery from the recessions of the 1980s but not substantially in the recovery after IIQ2009; (6) wealth of households and nonprofit organizations soared in the 1980s but declined into IIIQ2012; and (7) gross private domestic investment increased sharply from IQ1980 to IVQ1985 but gross private domestic investment and private fixed investment have fallen sharply from IVQ2007 to IIIQ2007. There is a critical issue of whether the United States economy will be able in the future to attain again the level of activity and prosperity of projected trend growth. Growth at trend during the entire business cycles built the largest economy in the world but there may be an adverse, permanent weakness in United States economic performance and prosperity. Table IB-2 provides data for analysis of these five basic facts. The six blocks of Table IB-2 are separated initially after individual discussion of each one followed by the full Table IB-2.

1. Trend Growth.

i. As shown in Table IB-2, actual GDP grew cumulatively 17.7 percent from IQ1980 to IVQ1985, which is relatively close to what trend growth would have been at 18.5 percent. Rapid growth at 5.7 percent annual rate on average per quarter during the expansion from IQ1983 to IVQ1985 erased the loss of GDP of 4.8 percent during the contraction and maintained trend growth at 3 percent over the entire cycle.

ii. In contrast, cumulative growth from IVQ2007 to IIIQ2012 was 2.5 percent while trend growth would have been 15.1 percent. GDP in IIIQ2012 at seasonally adjusted annual rate is estimated at $13,652.5 by the Bureau of Economic Analysis (BEA) (http://www.bea.gov/iTable/index_nipa.cfm) and would have been $15,338.2 billion, or $1,685.7 billion higher, had the economy grown at trend over the entire business cycle as it happened during the 1980s and throughout most of US history. There is $1.7 trillion of foregone GDP that would have been created as it occurred during past cyclical expansions, which explains why employment has not rebounded to even higher than before. There would not be recovery of full employment even with growth of 3 percent per year beginning immediately because the opportunity was lost to grow faster during the expansion from IIIQ2009 to IIIQ2012 after the recession from IVQ2007 to IIQ2009. The United States has acquired a heavy social burden of unemployment and underemployment of 28.6 million people or 17.7 percent of the effective labor force (Section I, Table I-4 http://cmpassocregulationblog.blogspot.com/2012/12/twenty-eight-million-unemployed-or.html) that will not be significantly diminished even with return to growth of GDP of 3 percent per year because of growth of the labor force by new entrants. The US labor force grew from 142.583 million in 2000 to 153.124 million in 2007 or by 7.4 percent at the average yearly rate of 1.0 percent per year. The civilian noninstitutional population increased from 212.577 million in 2000 to 231.867 million in 2007 or 9.1 percent at the average yearly rate of 1.3 percent per year (data from http://www.bls.gov/data/). Data for the past five years cloud accuracy because of the number of people discouraged from seeking employment. The noninstitutional population of the United States increased from 231.867 million in 2007 to 239.618 million in 2011 or by 3.3 percent while the labor force increased from 153.124 million in 2007 to 153.617 million in 2011 or by 0.3 percent (data from http://www.bls.gov/data/). People ceased to seek jobs because they do not believe that there is a job available for them (http://cmpassocregulationblog.blogspot.com/2012/12/twenty-eight-million-unemployed-or.html ).

Period IQ1980 to IVQ1985
GDP SAAR USD Billions
IQ1980	5,903.4
IVQ1985	6,950.0
∆% IQ1980 to IVQ1985	17.7
∆% Trend Growth IQ1980 to IVQ1985	18.5

Period IVQ2007 to IIIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIIQ2012	13,652.5
∆% IVQ2007 to IIIQ2012 Actual	2.5
∆% IVQ2007 to IIIQ2012 Trend	15.1

2. Decline of Per Capita Real Disposable Income

i. In the entire business cycle from IQ1980 to IVQ1985, as shown in Table IB-2 trend growth of per capita real disposable income, or what is left per person after inflation and taxes, grew cumulatively 14.5 percent, which is close to what would have been trend growth of 12.1 percent.

ii. In contrast, in the entire business cycle from IVQ2007 to IIIQ2012, per capita real disposable income fell 0.4 percent while trend growth would have been 10.4 percent. Income available after inflation and taxes is lower than before the contraction after 13 consecutive quarters of GDP growth at mediocre rates relative to those prevailing during historical cyclical expansions.

Period IQ1980 to IVQ1985

Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD	18,938
Real Disposable Personal Income per Capita IVQ1985 Chained 2005 USD	21,687
∆% IQ1980 to IVQ1985	14.5
∆% Trend Growth	12.1

Period IVQ2007 to IIIQ2012

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIIQ2012 Chained 2005 USD	32,691
∆% IVQ2007 to IIIQ2012	-0.4
∆% Trend Growth	10.4

3. Number of Employed Persons

i. As shown in Table IB-2, the number of employed persons increased over the entire business cycle from 98.527 million not seasonally adjusted (NSA) in IQ1980 to 107.819 million NSA in IVQ1985 or by 9.4 percent.

ii. In contrast, during the entire business cycle the number employed fell from 146.334 million in IVQ2007 to 143.202 million in IIIQ2012 or by 2.1 percent. There are 28.6 million persons unemployed or underemployed, which is 17.7 percent of the effective labor force (Section I, Table I-4 http://cmpassocregulationblog.blogspot.com/2012/12/twenty-eight-million-unemployed-or.html).

Period IQ1980 to IVQ1985

Employed Millions IQ1980 NSA End of Quarter	98.527
Employed Millions IV1985 NSA End of Quarter	107.819
∆% Employed IQ1980 to IV1985	9.4

Period IVQ2007 to IIIQ2012

Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIIQ2012 NSA End of Quarter	143.333
∆% Employed IVQ2007 to IIIQ2012	-2.1

4. Number of Full-Time Employed Persons

i. As shown in Table IB-2, during the entire business cycle in the 1980s, including contractions and expansion, the number of employed full-time rose from 81.280 million NSA in IQ1980 to 88.757 million NSA in IVQ1985 or 9.2 percent.

ii. In contrast, during the entire current business cycle, including contraction and expansion, the number of persons employed full-time fell from 121.042 million in IVQ2007 to 115.678 million in IIIQ2012 or by minus 4.4 percent.

Period IQ1980 to IVQ1985

Employed Full-time Millions IQ1980 NSA End of Quarter	81.280
Employed Full-time Millions IV1985 NSA End of Quarter	88.757
∆% Full-time Employed IQ1980 to IV1985	9.2

Period IVQ2007 to IIIQ2012

Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIIQ2012 NSA End of Quarter	115.678
∆% Full-time Employed IVQ2007 to IIIQ2012	-4.4

5. Unemployed, Unemployment Rate and Employed Part-time for Economic Reasons.

i. As shown in Table IIB-2 and in the following block, in the cycle from IQ1980 to IVQ1985: (a) the rate of unemployment was virtually the same at 6.7 percent in IQ1985 relative to 6.6 percent in IQ1980; (b) the number unemployed increased from 6.983 million in IQ1980 to 7.717 million in IVQ1985 or 10.5 percent; and (c) the number employed part-time for economic reasons increased 49.1 percent from 3.624 million in IQ1980 to 5.402 million in IVQ1985.

ii. In contrast, in the economic cycle from IVQ2007 to IIIQ2012: (a) the rate of unemployment increased from 4.8 percent in IVQ2007 to 7.6 percent in IIIQ2012; (b) the number unemployed increased 59.3 percent from 7.371 million in IVQ2007 to 11.742 million in IIIQ2012; (c) the number employed part-time for economic reasons increased 70.7 percent from 4.750 million in IVQ2007 to 8.110 million in IIIQ2012; and (d) U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA increased from 8.7 percent in IVQ2007 to 14.2 percent in IIIQ2012.

Period IQ1980 to IVQ1985

Unemployment Rate IQ1980 NSA End of Quarter	6.6
Unemployment Rate IV1985 NSA End of Quarter	6.7
Unemployed IQ1980 Millions End of Quarter	6.983
Unemployed IV 1985 Millions End of Quarter	7.717
Employed Part-time Economic Reasons Millions IQ1980 End of Quarter	3.624
Employed Part-time Economic Reasons Millions IVQ1985 End of Quarter	5.402
∆%	49.1

Period IVQ2007 to IIIQ2012

Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIIQ2012 NSA End of Quarter	7.6
Unemployed IVQ2007 Millions End of Quarter	7.371
Unemployed IIIQ2009 Millions End of Quarter	11.742
∆%	59.3
Employed Part-time Economic Reasons IVQ2007 Millions End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIIQ2009 End of Quarter	8.110
∆%	70.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007	8.7
IIIQ2012	14.2

6. Wealth of Households and Nonprofit Organizations.

i. The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and also from IVQ1979) to IVQ1985 and from IVQ2007 to IIIQ2012 is provided in the following block and in Table IB-2. Net worth of households and nonprofit organizations increased from $8,326.4 billion in IVQ1979 to $14,395.2 billion in IVQ1985 or 72.9 percent or 69.3 percent from $8,502.9 billion in IQ1980. The starting quarter does not bias the results. The US consumer price index not seasonally adjusted increased from 76.7 in Dec 1979 to 109.3 in Dec 1985 or 42.5 percent or 36.5 percent from 80.1 in Mar 1980 (using consumer price index data from the US Bureau of Labor Statistics at http://www.bls.gov/cpi/data.htm). In terms of purchasing power measured by the consumer price index, real wealth of households and nonprofit organizations increased 21.3 percent in constant purchasing power from IVQ1979 to IVQ1985 or 24.0 percent from IQ1980.

ii. In contrast, as shown in Table IB-2, net worth of households and nonprofit organizations fell from $66,000.6 billion in IVQ2007 to $64,768.8 billion in IIIQ2012 by $1,231.8 billion or 1.9 percent. The US consumer price index was 210.036 in Dec 2007 and 231.407 in Sep 2012 for increase of 10.2 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 10.9 percent in Sep 2012 after 13 consecutive quarters of expansion from IIIQ2009 to IIIQ2012 relative to IVQ2007 when the recession began. The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. The average growth rate from IIIQ2009 to IIQ2012 has been 2.2 percent, which is substantially lower than the average of 6.2 percent in cyclical expansions after World War II and 5.7 percent in the expansion from IQ1983 to IVQ1985 (http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions. US wealth of households and nonprofit organizations grew from IVQ1945 at $710,125.9 million to IIIQ2009 at $64,768,835.3 million or increase of 9,020.8 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 231.407 in Sep 2012 or 1,171.5 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 67 years with inflation adjusted increase of 617.3 percent. The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIQ2009 caused sharp contraction of US household and nonprofit net worth. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 67 years when US GDP grew at 2.2 percent on average in 13 quarters between IIIQ2009 and IIIQ2012 in contrast with average 5.7 percent from IQ1983 to IVQ1985 and average 6.2 percent during cyclical expansions in those 67 years.

Period IQ1980 to IVQ1985
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ1979	8,326.4
IVQ1985	14,395.2
∆ USD Billions	+6,068.8
Period IVQ2007 to IIQ2012
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ2007	66,000.6
IIIQ2012	64,768.8
∆ USD Billions	-1,231.8

7. Gross Private Domestic Investment.

i. The comparison of gross private domestic investment in the entire economic cycles from IQ1980 to IV1985 and from IVQ2007 to IIQ2012 is provides in the following block and in Table IB-2. Gross private domestic investment increased from $778.3 billion in IQ1980 to $965.9 billion in IVQ1985 or by 24.1 percent.

ii In the current cycle, gross private domestic investment decreased from $2,123.6 billion in IVQ2007 to $1,928.8 billion in IIIQ2012, or decline by 9.2 percent. Private fixed investment fell from $2,111.5 billion in IVQ2007 to $1844.8 billion in IIIQ2012, or decline by 12.6 percent.

Period IQ1980 to IVQ1985
Gross Private Domestic Investment USD 2005 Billions
IQ1980	778.3
IVQ1985	965.9
∆%	24.1
Period IVQ2007 to IIIQ2012
Gross Private Domestic Investment USD Billions
IVQ2007	2,123.6
IIIQ2012	1,928.8
∆%	-9.2
Private Fixed Investment USD 2005 Billions
IVQ2007	2,111.5
IIIQ2012	1,844.8
∆%	-12.6

Table IB-2, US, GDP and Real Disposable Personal Income per Capita Actual and Trend Growth and Employment, 1980-1985 and 2007-2012, SAAR USD Billions, Millions of Persons and ∆%


Period IQ1980 to IVQ1985
GDP SAAR USD Billions
IQ1980	5,903.4
IVQ1985	6,950.0
∆% IQ1980 to IVQ1985	17.7
∆% Trend Growth IQ1980 to IVQ1985	18.5
Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD	18,938
Real Disposable Personal Income per Capita IVQ1985 Chained 2005 USD	21,687
∆% IQ1980 to IVQ1985	14.5
∆% Trend Growth	12.1
Employed Millions IQ1980 NSA End of Quarter	98.527
Employed Millions IV1985 NSA End of Quarter	107.819
∆% Employed IQ1980 to IV1985	9.4
Employed Full-time Millions IQ1980 NSA End of Quarter	81.280
Employed Full-time Millions IV1985 NSA End of Quarter	88.757
∆% Full-time Employed IQ1980 to IV1985	9.2
Unemployment Rate IQ1980 NSA End of Quarter	6.6
Unemployment Rate IV1985 NSA End of Quarter	6.7
Unemployed IQ1980 Millions NSA End of Quarter	6.983
Unemployed IV 1985 Millions NSA End of Quarter	7.717
∆%	11.9
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 NSA End of Quarter	8.394
∆%	76.7
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ1979	8,326.4
IVQ1985	14,395.2
∆ USD Billions	+6,068.8
Gross Private Domestic Investment USD 2005 Billions
IQ1980	778.3
IVQ1985	965.9
∆%	24.1
Period IVQ2007 to IIIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIIQ2012	13,652.5
∆% IVQ2007 to IIIQ2012	2.5
∆% IVQ2007 to IIIQ2012 Trend Growth	15.1
Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIIQ2012 Chained 2005 USD	32,691
∆% IVQ2007 to IIIQ2012	-0.4
∆% Trend Growth	10.4
Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIIQ2012 NSA End of Quarter	143.333
∆% Employed IVQ2007 to IIIQ2012	-2.1
Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIIQ2012 NSA End of Quarter	115.678
∆% Full-time Employed IVQ2007 to IIIQ2012	-4.4
Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIIQ2012 NSA End of Quarter	7.6
Unemployed IVQ2007 Millions NSA End of Quarter	7.371
Unemployed IIIQ2012 Millions NSA End of Quarter	11.742
∆%	59.3
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIIQ2009 NSA End of Quarter	8.110
∆%	70.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007	8.7
IIIQ2012	14.2
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ2007	66,000.6
IIIQ2012	64,768.8
∆ USD Billions	-1,231.8
Gross Private Domestic Investment USD Billions
IVQ2007	2,123.6
IIIQ2012	1,928.8
∆%	-9.2
Private Fixed Investment USD 2005 Billions
IVQ2007	2,111.5
IIIQ2012	1,844.8
∆%	-12.6

Note: GDP trend growth used is 3.0 percent per year and GDP per capita is 2.0 percent per year as estimated by Lucas (2011May) on data from 1870 to 2010.

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm US Bureau of Labor Statistics http://www.bls.gov/data/. Board of Governors of the Federal Reserve System. 2012Sep20. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System.

IIA The Theory and Reality of Economic History, Deflation and Unconventional Monetary Policy. Unconventional monetary policy could be defined by continuous symmetric objectives of inflation and the rate of unemployment with policy impulses of highest magnitude. The central bank would operate policy such as to constantly maintain inflation around 2 percent and the rate of unemployment close to the natural rate (Friedman 1968, Phelps 1968) around 5 percent. There are lags in effect of monetary policy impulses, meaning that a policy impulse today may not have all the effects on income and prices until many months in the future (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). Unconventional monetary policy has evolved into a forecast growth mandate.

Charles Evans, President of the Federal Reserve Bank of Chicago, proposed an “economic state-contingent policy” or “7/3” approach (Evans 2012 Aug 27):

Evans (2012Nov27) modified the “7/3” approach to a “6.5/2.5” approach:

The Federal Open Market Committee (FOMC) decided at its meeting on Dec 12, 2012 to implement the “6.5/2.5” approach (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm):

declines.

W = Y/r (1)

The nominal rate of interest must always be nonnegative, that is, i ≥ 0 (Hick 1937, 154-5):

Fed policy is seeking what Irving Fisher proposed “that great depressions are curable and preventable through reflation and stabilization” (Fisher 1933, 350).

The President of the Federal Reserve Bank of Chicago argues that (Charles Evans 2010):

There are two types of monetary policies that could be used in this situation. First, the Fed could announce a price-level target to be attained within a reasonable time frame (Evans 2010):

Chart IIA-1 provides the consumer price index NSA from 1913 to 2012. The dominating characteristic is the increase in slope during the Great Inflation from the middle of the 1960s through the 1970s. There is long-term inflation in the US and no evidence of deflation risks

Chart IIA-1, US, Consumer Price Index, All Items, NSA, 1913-2012

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

Table IIA-1 provides annual percentage changes of United States consumer price inflation from 1914 to 2011. There have been only cases of annual declines of the CPI after World War II: -1.2 percent in 1949, -0.4 percent in 1955 and -0.4 percent in 2009. The decline of 0.4 percent in 2009 followed increase of 3.8 percent in 2008 and is explained by the reversal of speculative carry trades that were created in 2008 as monetary policy rates were driven to zero. The reversal occurred after misleading statement on toxic assets in banks in the proposal for TARP (Cochrane and Zingales 2009). The only persistent deflationary period since 1914 was during the Great Depression in the years from 1930 to 1933. Fear of deflation on the basis of that experience does not justify unconventional monetary policy of zero interest rates that has failed to stop deflation in Japan. Financial repression causes far more adverse effects on allocation of resources by distorting the calculus of risk/returns than alleged employment-creating effects or there would not be current recovery without jobs and hiring after zero interest rates since Dec 2008 and intended now forever in a self-imposed growth and employment mandate of monetary policy

Table IIA-1, US, Consumer Price Index, All Items, NSA, 12-Month Percentage Change 1914-2012

Year	Annual
1914	1.0
1915	1.0
1916	7.9
1917	17.4
1918	18.0
1919	14.6
1920	15.6
1921	-10.5
1922	-6.1
1923	1.8
1924	0.0
1925	2.3
1926	1.1
1927	-1.7
1928	-1.7
1929	0.0
1930	-2.3
1931	-9.0
1932	-9.9
1933	-5.1
1934	3.1
1935	2.2
1936	1.5
1937	3.6
1938	-2.1
1939	-1.4
1940	0.7
1941	5.0
1942	10.9
1943	6.1
1944	1.7
1945	2.3
1946	8.3
1947	14.4
1948	8.1
1949	-1.2
1950	1.3
1951	7.9
1952	1.9
1953	0.8
1954	0.7
1955	-0.4
1956	1.5
1957	3.3
1958	2.8
1959	0.7
1960	1.7
1961	1.0
1962	1.0
1963	1.3
1964	1.3
1965	1.6
1966	2.9
1967	3.1
1968	4.2
1969	5.5
1970	5.7
1971	4.4
1972	3.2
1973	6.2
1974	11.0
1975	9.1
1976	5.8
1977	6.5
1978	7.6
1979	11.3
1980	13.5
1981	10.3
1982	6.2
1983	3.2
1984	4.3
1985	3.6
1986	1.9
1987	3.6
1988	4.1
1989	4.8
1990	5.4
1991	4.2
1992	3.0
1993	3.0
1994	2.6
1995	2.8
1996	3.0
1997	2.3
1998	1.6
1999	2.2
2000	3.4
2001	2.8
2002	1.6
2003	2.3
2004	2.7
2005	3.4
2006	3.2
2007	2.8
2008	3.8
2009	-0.4
2010	1.6
2011	3.2

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

Chart IIA-2 provides 12-month percentage changes of the US consumer price index from 1914 to 2012. There are actually three waves of inflation in the second half of the 1960s, in the mid 1970s and again in the late 1970s. The Great Inflation of the 1970s is analyzed in various comments of this blog (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 in Appendix I. Inflation rates then stabilized in the US in a range with only two episodes above 5 percent. There are isolated cases of deflation concentrated over extended periods only during the 1930s. There is no case in United States economic history for unconventional monetary policy because of fear of deflation. There are cases of long-term deflation without lost decades or depressions.

Chart IIA-2, US, Consumer Price Index, All Items, NSA, 12-Month Percentage Change 1914-2012

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

The conventional theory that the terms of trade of Brazil deteriorated over the long term is without reality (Pelaez 1976a, 280-281):

Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:

Phyllis Deane (1968, 96) estimates growth of United Kingdom gross national product (GNP) at around 2 percent per year for several decades in the nineteenth century. The experience of the United Kingdom with deflation and economic growth is relevant and rich. Table IIA-2 uses yearly percentage changes of the composite index of prices of the United Kingdom of O’Donoghue and Goulding (2004). There are 73 declines of inflation in the 145 years from 1751 to 1896. Prices declined in 50.3 percent of 145 years. Some price declines were quite sharp and many occurred over several years. Table IIA-3 also provides yearly percentage changes of the UK composite price index of O’Donoghue and Goulding (2004) from 1929 to 1934. Deflation was much sharper in continuous years in earlier periods than during the Great Depression.

Table IIA-2, United Kingdom, Negative Percentage Changes of Composite Price Index, 1751-1896, 1929-1934, Yearly ∆%

Year	∆%	Year	∆%	Year	∆%	Year	∆%
1751	-2.7	1797	-10.0	1834	-7.8	1877	-0.7
1753	-2.7	1798	-2.2	1841	-2.3	1878	-2.2
1755	-6.0	1802	-23.0	1842	-7.6	1879	-4.4
1758	-0.3	1803	-5.9	1843	-11.3	1881	-1.1
1759	-7.9	1806	-4.4	1844	-0.1	1883	-0.5
1760	-4.5	1807	-1.9	1848	-12.1	1884	-2.7
1761	-4.5	1811	-2.9	1849	-6.3	1885	-3.0
1768	-1.1	1814	-12.7	1850	-6.4	1886	-1.6
1769	-8.2	1815	-10.7	1851	-3.0	1887	-0.5
1770	-0.4	1816	-8.4	1857	-5.6	1893	-0.7
1773	-0.3	1819	-2.5	1858	-8.4	1894	-2.0
1775	-5.6	1820	-9.3	1859	-1.8	1895	-1.0
1776	-2.2	1821	-12.0	1862	-2.6	1896	-0.3
1777	-0.4	1822	-13.5	1863	-3.6	1929	-0.9
1779	-8.5	1826	-5.5	1864	-0.9	1930	-2.8
1780	-3.4	1827	-6.5	1868	-1.7	1931	-4.3
1785	-4.0	1828	-2.9	1869	-5.0	1932	-2.6
1787	-0.6	1830	-6.1	1874	-3.3	1933	-2.1
1789	-1.3	1832	-7.4	1875	-1.9	1934	0.0
1791	-0.1	1833	-6.1	1876	-0.3

Source:

O’Donoghue, Jim and Louise Goulding, 2004. Consumer Price Inflation since 1750. UK Office for National Statistics Economic Trends 604, Mar 2004, 38-46.

CMP Associates Regulation Blog

Followers

Blog Archive

About Me

Sunday, January 6, 2013

No comments:

Post a Comment