CMP Associates Regulation Blog

Chart I-1 shows the annual level of total nonfarm hiring (HNF) that collapsed during the global recession after 2007 in contrast with milder decline in the shallow recession of 2001. Nonfarm hiring has not recovered, remaining at a depressed level.

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2013

Source: US Bureau of Labor Statistics

Chart I-2 shows the ratio or rate of nonfarm hiring to employment (RNF) that also fell much more in the recession of 2007 to 2009 than in the shallow recession of 2001. Recovery is weak in the current environment of cyclical slow growth.

Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2015

Source: US Bureau of Labor Statistics

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table I-2. There were much milder declines in 2002 of 6.6 percent and 2.6 percent in 2003 followed by strong rebounds of 5.8 percent in 2004 and 4.5 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 1.9 in 2007, 11.8 in 2008 and 16.1 percent in 2009. On a yearly basis, nonfarm hiring grew 6.1 percent in 2010 relative to 2009, 3.2 percent in 2011, 4.1 percent in 2012 and 3.5 percent in 2013. The relatively large length of 18 quarters of the current expansion reduces the likelihood of significant recovery of hiring levels in the United States because lower rates of growth and hiring in the final phase of expansions.

Table I-2, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2002-2013

Year	Annual ∆%
2002	-6.6
2003	-2.6
2004	5.8
2005	4.5
2006	0.6
2007	-1.9
2008	-11.8
2009	-16.1
2010	6.1
2011	3.2
2012	4.1
2013	3.5

Source: US Bureau of Labor Statistics

Total private hiring (HP) yearly data are provided in Chart I-4. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2013.

Chart I-4, US, Total Nonfarm Hiring Level, Annual, 12-Month ∆%, 2001-2013

Source: Bureau of Labor Statistics

Chart I-5 plots the rate of total private hiring relative to employment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.

Chart I-5, US, Total Private Hiring, Annual, 2001-2013

Source: Bureau of Labor Statistics

Chart I-5A plots the rate of total private hiring relative to employment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.

Chart I-5A, US, Rate Total Private Hiring Level, Annual, 2001-2013

Source: Bureau of Labor Statistics

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Jan in the years from 2001 to 2014 in Table I-3. Hiring numbers are in thousands. There is moderate recovery in HNF from 3949 thousand (or 3.9 million) in Jan 2009 to 3744 thousand in Jan 2010, 3765 thousand in Jan 2011, 4112 thousand in Jan 2012, 4223 thousand in Jan 2013 and 4383 thousand in Jan 2014 for cumulative gain of 11.0 percent. HP rose from 3655 thousand in Jan 2009 to 3488 thousand in Jan 2010, 3512 thousand in Jan 2011, 3853 thousand in Jan 2012, 3970 thousand in Jan 2013 and 4127 thousand in Jan 2014 for cumulative gain of 12.9 percent. HNF has fallen from 5058 thousand in Jan 2006 to 4383 thousand in Jan 2014 or by 13.3 percent. HP has fallen from 4790 thousand in Jan 2006 to 4127 thousand in Jan 2014 or by 13.8 percent. The civilian noninstitutional population of the US, or individuals in condition to work, rose from 228.815 million in 2006 to 245.679 million in 2013 or by 16.864 million and the civilian labor force from 151.428 million in 2006 to 155.389 million in 2013 or by 3.961 million (http://www.bls.gov/data/). The number of nonfarm hires in the US fell from 63.327 million in 2006 to 54.191 million in 2013 or by 9.136 million and the number of private hires fell from 59.128 million in 2006 to 50.718 million in 2013 or by 8.410 million (http://www.bls.gov/jlt/). Private hiring of 59.128 million in 2006 was equivalent to 25.8 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 50.718 million in 2013 or 20.6 percent of the civilian noninstitutional population of 245.679 million in 2013. The percentage of hiring in civilian noninstitutional population of 25.8 percent in 2006 would correspond to 63.385 million of hiring in 2013, which would be 12.667 million higher than actual 50.718 million in 2013. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html) explains the fact that there are many million fewer hires in the US than before the global recession. The labor market continues to be fractured, failing to provide an opportunity to exit from unemployment/underemployment or to find an opportunity for advancement away from declining inflation-adjusted earnings.

Table I-3, US, Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US in

Thousands and in Percentage of Total Employment Not Seasonally Adjusted

	HNF	Rate RNF	HP	Rate HP
2001 Jan	5853	4.5	5525	5.0
2002 Jan	4941	3.8	4654	4.3
2003 Jan	5015	3.9	4712	4.4
2004 Jan	4789	3.7	4542	4.2
2005 Jan	5092	3.9	4791	4.4
2006 Jan	5058	3.8	4790	4.3
2007 Jan	5014	3.7	4705	4.2
2008 Jan	4698	3.4	4433	3.9
2009 Jan	3949	3.0	3655	3.3
2010 Jan	3744	2.9	3488	3.3
2011 Jan	3765	2.9	3512	3.3
2012 Jan	4112	3.1	3853	3.5
2013 Jan	4223	3.2	3970	3.6
2014 Jan	4383	3.2	4127	3.6

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

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2014. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4841 in May 2010 until it surpassed it with 4975 in Jun 2011 but declined to 3084 in Dec 2012. Nonfarm hiring fell to 3012 in Dec 2011 from 3810 in Nov and to revised 3614 in Feb 2012, increasing to 4220 in Mar 2012, 3084 in Dec 2012 and 4223 in Jan 2013 and declining to 3699 in Feb 2013. Nonfarm hires not seasonally adjusted increased to 4165 in Nov 2013 and 3271 in Dec 2013. Nonfarm hires reached 4383 in Jan 2014. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Oct 2011 was 4237 thousand, increasing to revised 4446 thousand in Feb 2012, or 4.9 percent, moving to 4343 in Dec 2012 for cumulative increase of 2.0 percent from 4256 in Dec 2011 and 4578 in Dec 2013 for increase of 5.4 percent relative to 4343 in Dec 2012. The number of hires not seasonally adjusted was 4975 in Jun 2011, falling to 3012 in Dec 2011 but increasing to 4112 in Jan 2012 and declining to 3084 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 39.5 percent from 4975 in Jun 2011 to 3012 in Dec 2011 and fell 38.7 percent from 5035 in Jun 2012 to 3084 in Dec 2012 in a yearly-repeated seasonal pattern. The number of nonfarm hires not seasonally adjusted fell from 5095 in Jun 2013 to 3271 in Dec 2013, or decline of 35.8 percent, showing strong seasonality.

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2014 Month SA

Source: Bureau of Labor Statistics

Similar behavior occurs in the rate of nonfarm hiring in Chart I-7. Recovery in early 2010 was followed by decline and stabilization at a lower level but with stability in monthly SA estimates of 3.2 in Aug 2011 to 3.2 in Jan 2012, increasing to 3.3 in May 2012 and falling to 3.2 in Jun 2012. The rate stabilized at 3.2 in Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.2 in Dec 2012 and 3.3 in Dec 2013. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.3 in Dec 2011, climbing to 3.7 in Jun 2012 but falling to 2.3 in Dec 2012. The rate of nonfarm hires not seasonally adjusted fell from 3.7 in Jun 2013 to 2.4 in Dec 2013. Rates of nonfarm hiring NSA were in the range of 2.7 (Dec) to 4.4 (Jun) in 2006.

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2014

Source: Bureau of Labor Statistics

There is only milder improvement in total private hiring shown in Chart I-8. Hiring private (HP) rose in 2010 with stability and renewed increase in 2011 followed by almost stationary series in 2012. The number of private hiring seasonally adjusted fell from 4057 thousand in Sep 2011 to 3962 in Dec 2011 or by 2.3 percent, decreasing to 3998 in Jan 2012 or decline by 1.5 percent relative to the level in Sep 2011. The rate fell to 3959 in Sep 2012 or lower by 2.4 percent relative to Sep 2011, moving to 4061 in Dec 2012 for increase of 1.6 percent relative to 3998 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4600 in Jun 2011 to 2833 in Dec 2011 or by 38.4 percent, reaching 3853 in Jan 2012 or decline of 16.2 percent relative to Jun 2011 and moving to 2911 in Dec 2012 or 37.1 percent lower relative to 4629 in Jun 2012. Hires fell from 4706 in Jun 2013 to 3098 in Dec 2013. Companies do not hire in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5567 in Jun 2006 to 3568 in Dec 2006 or by 35.9 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Jul 2006, private hiring NSA was 5501, declining to 4326 in Jul 2011 or by 21.4 percent and to 4354 in Jul 2012 or lower by 20.9 percent relative to Jul 2006. Private hiring NSA fell from 4790 in Jan 2006 to 4127 in Jan 2014 or 13.8 percent. Private hiring fell from 5501 in Jul 2006 to 4632 in Jul 2013 or 15.8 percent. The conclusion is that private hiring in the US is around 20 percent below the hiring before the global recession while the noninstitutional population of the United States has grown from 228.815 million in 2006 to 245.679 million in 2013, by 16.864 million or 7.4 percent. The main problem in recovery of the US labor market has been the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-8, US, Total Private Hiring Month SA 2001-2014

Source: Bureau of Labor Statistics

Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data did not rise significantly above the peak in 2010. The rate seasonally adjusted fell from 3.7 in Sep 2011 to 3.6 in Dec 2011 and reached 3.6 in Dec 2012 and 3.7 in Dec 2013. The rate not seasonally adjusted (NSA) fell from 3.7 in Sep 2011 to 2.5 in Dec 2011, increasing to 3.8 in Oct 2012 but falling to 2.6 in Dec 2012 and 3.4 in Mar 2013. The NSA rate of private hiring fell from 4.8 in Jul 2006 to 3.4 in Aug 2009 but recovery was insufficient to only 3.8 in Aug 2012, 2.5 in Dec 2012 and 2.6 in Dec 2013. The rate of private hires fell from 4.8 in Jul 2006 to 4.0 in Jul 2013. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp4q13_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth on trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,107.4 billion than actual $15,932.9 billion. There are about two trillion dollars of GDP less than on trend, explaining the 29.1 million unemployed or underemployed equivalent to actual unemployment of 17.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,932.9 billion in IVQ2013 or 6.2 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation.

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2014

Source: Bureau of Labor Statistics

The JOLTS report of the Bureau of Labor Statistics also provides total nonfarm job openings (TNF JOB), TNF JOB rate and TNF LD (layoffs and discharges) shown in Table I-4 for the month of Jan from 2001 to 2014. The final column provides annual TNF LD for the years from 2001 to 2013. Nonfarm job openings (TNF JOB) fell from a peak of 4462 in Jan 2006 to 4121 in Jan 2014 or by 7.6 percent while the rate dropped from 3.2 to 3.0. Nonfarm layoffs and discharges (TNF LD) rose from 2237 in Jan 2006 to 3203 in Jan 2009 or by 43.2 percent. The annual data show layoffs and discharges rising from 20.9 million in 2006 to 26.4 million in 2009 or by 26.3 percent. Business pruned payroll jobs to survive the global recession but there has not been hiring because of the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp4q13_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth on trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,107.4 billion than actual $15,932.9 billion. There are about two trillion dollars of GDP less than on trend, explaining the 29.1 million unemployed or underemployed equivalent to actual unemployment of 17.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,932.9 billion in IVQ2013 or 6.2 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation.

Table I-4, US, Total Nonfarm Job Openings and Total Nonfarm Layoffs and Discharges, Thousands NSA

	TNF JOB	TNF JOB Rate	TNF LD	TNF LD Annual
Jan 2001	5594	4.1	2868	24138
Jan 2002	3855	2.9	2472	22706
Jan 2003	3940	3.0	2605	23490
Jan 2004	3604	2.7	2481	22668
Jan 2005	3775	2.8	2465	22243
Jan 2006	4462	3.2	2237	20896
Jan 2007	4711	3.4	2149	21958
Jan 2008	4372	3.1	2346	24028
Jan 2009	2838	2.1	3203	26444
Jan 2010	2762	2.1	2399	21829
Jan 2011	2994	2.3	2177	20805
Jan 2012	3721	2.8	2087	20892
Jan 2013	3836	2.8	2012	19964
Jan 2014	4121	3.0	2200

Notes: TNF JOB: Total Nonfarm Job Openings; LD: Layoffs and Discharges

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

Chart I-10 shows monthly job openings rising from the trough in 2009 to a high in the beginning of 2010. Job openings then stabilized into 2011 but have surpassed the peak of 3080 seasonally adjusted in Apr 2010 with 3646 seasonally adjusted in Dec 2012, which is higher by 18.4 percent relative to Apr 2010 but lower by 2.9 percent relative to 3755 in Nov 2012 and lower by 4.7 percent than 3827 in Mar 2012. Nonfarm job openings increased from 3646 in Dec 2012 to 3914 in Dec 2013 or by 7.4 percent. The high of job openings not seasonally adjusted was 3428 in Apr 2010 that was surpassed by 3661 in Jul 2011, increasing to 3939 in Oct 2012 but declining to 3152 in Dec 2012 and decreasing to 3387 in Dec 2013. The level of job openings not seasonally adjusted fell to 3152 in Dec 2012 or by 21.3 percent relative to 4005 in Apr 2012. There is here again the strong seasonality of year-end labor data. Job openings fell from 4209 in Apr 2013 to 3387 in Dec 2013, showing strong seasonal effects. The level of job openings of 4121 in Jan 2014 NSA is lower by 7.6 percent relative to 4462 in Jan 2006. The main problem in recovery of the US labor market has been the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-10, US Job Openings, Thousands NSA, 2001-2014

Source: US Bureau of Labor Statistics

The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted increasedd from 2.2 in Jan 2011 to 2.36 in Dec 2011, 2.6 in Dec 2012 and 2.8 in Dec 2013. The rate seasonally adjusted stood at 2.8 in Jan 2014. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 3.0 in Apr 2013 and 2.6 in Nov 2013. The rate of job openings NSA fell from 3.3 in Jul 2007 to 1.8 in Nov-Dec 2009, recovering insufficiently to 3.0 in Jan 2014. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp4q13_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth on trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,107.4 billion than actual $15,932.9 billion. There are about two trillion dollars of GDP less than on trend, explaining the 29.1 million unemployed or underemployed equivalent to actual unemployment of 17.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,932.9 billion in IVQ2013 or 6.2 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation.

Chart I-11, US, Rate of Job Openings, NSA, 2001-2014

Source: US Bureau of Labor Statistics

Total separations are shown in Chart I-12. Separations are much lower in 2012-14 than before the global recession but hiring has not recovered.

Chart I-12, US, Total Nonfarm Separations, Month Thousands SA, 2001-2014

Source: US Bureau of Labor Statistics

Annual total separations are shown in Chart I-13. Separations are much lower in 2011-2013 than before the global recession but without recovery in hiring.

Chart I-13, US, Total Separations, Annual, Thousands, 2001-2013

Source: US Bureau of Labor Statistics

Table I-5 provides total nonfarm total separations from 2001 to 2013. Separations fell from 61.1 million in 2006 to 47.8 million in 2010 or by 13.3 million and 48.2 million in 2011 or by 12.9 million. Total separations increased from 48.2 million in 2011 to 51.8 million in 2013 or by 3.6 million.

Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2013

Year	Annual
2001	64472
2002	59003
2003	56970
2004	58238
2005	60494
2006	61117
2007	60838
2008	58227
2009	51127
2010	47750
2011	48220
2012	50070
2013	51837

Source: US Bureau of Labor Statistics

Monthly data of layoffs and discharges reach a peak in early 2009, as shown in Chart I-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business. Weak rates of growth of GDP (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html) frustrated employment recovery. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly Thousands SA, 2011-2014

Source: US Bureau of Labor Statistics

Layoffs and discharges in Chart I-15 rose sharply to a peak in 2009. There was pronounced drop into 2010 and 2011 with mild increase into 2012 and renewed decline into 2013.

Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2012

Source: US Bureau of Labor Statistics

Table I-6 provides annual nonfarm layoffs and discharges from 2001 to 2013. Layoffs and discharges peaked at 26.4 million in 2009 and then fell to 20.8 million in 2011, by 5.6 million, or 21.2 percent. Total nonfarm layoffs and discharges increased mildly to 20.9 million in 2012, falling to 19.9 million in 2013.

Table I-6, US, Total Nonfarm Layoffs and Discharges, Thousands, 2001-2013

Year	Annual
2001	24138
2002	22706
2003	23490
2004	22668
2005	22243
2006	20896
2007	21958
2008	24028
2009	26444
2010	21829
2011	20805
2012	20892
2013	19964

Source: US Bureau of Labor Statistics

IA2 Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table I-7. The most comprehensive measure is U6 that consists of total unemployed plus total employed part time for economic reasons plus all marginally attached workers as percent of the labor force. U6 not seasonally annualized has risen from 8.2 percent in 2006 to 13.1 percent in Feb 2014.

Table I-7, US, Alternative Measures of Labor Underutilization NSA %

	U1	U2	U3	U4	U5	U6
2014
Feb	3.6	3.9	7.0	7.5	8.4	13.1
Jan	3.5	4.0	7.0	7.5	8.6	13.5
2013
Dec	3.5	3.5	6.5	7.0	7.9	13.0
Nov	3.7	3.5	6.6	7.1	7.9	12.7
Oct	3.7	3.6	7.0	7.4	8.3	13.2
Sep	3.7	3.5	7.0	7.5	8.4	13.1
Aug	3.7	3.8	7.3	7.9	8.7	13.6
Jul	3.7	3.8	7.7	8.3	9.1	14.3
Jun	3.9	3.8	7.8	8.4	9.3	14.6
May	4.1	3.7	7.3	7.7	8.5	13.4
Apr	4.3	3.9	7.1	7.6	8.5	13.4
Mar	4.3	4.3	7.6	8.1	9.0	13.9
Feb	4.3	4.6	8.1	8.6	9.6	14.9
Jan	4.3	4.9	8.5	9.0	9.9	15.4
2012
Dec	4.2	4.3	7.6	8.3	9.2	14.4
Nov	4.2	3.9	7.4	7.9	8.8	13.9
Oct	4.3	3.9	7.5	8.0	9.0	13.9
Sep	4.2	4.0	7.6	8.0	9.0	14.2
Aug	4.3	4.4	8.2	8.7	9.7	14.6
Jul	4.3	4.6	8.6	9.1	10.0	15.2
Jun	4.5	4.4	8.4	8.9	9.9	15.1
May	4.7	4.3	7.9	8.4	9.3	14.3
Apr	4.8	4.3	7.7	8.3	9.1	14.1
Mar	4.9	4.8	8.4	8.9	9.7	14.8
Feb	4.9	5.1	8.7	9.3	10.2	15.6
Jan	4.9	5.4	8.8	9.4	10.5	16.2
2011
Dec	4.8	5.0	8.3	8.8	9.8	15.2
Nov	4.9	4.7	8.2	8.9	9.7	15.0
Oct	5.0	4.8	8.5	9.1	10.0	15.3
Sep	5.2	5.0	8.8	9.4	10.2	15.7
Aug	5.2	5.1	9.1	9.6	10.6	16.1
Jul	5.2	5.2	9.3	10.0	10.9	16.3
Jun	5.1	5.1	9.3	9.9	10.9	16.4
May	5.5	5.1	8.7	9.2	10.0	15.4
Apr	5.5	5.2	8.7	9.2	10.1	15.5
Mar	5.7	5.8	9.2	9.7	10.6	16.2
Feb	5.6	6.0	9.5	10.1	11.1	16.7
Jan	5.6	6.2	9.8	10.4	11.4	17.3
Dec 2010	5.4	5.9	9.1	9.9	10.7	16.6
Annual
2013	3.9	3.9	7.4	7.9	8.8	13.8
2012	4.5	4.4	8.1	8.6	9.5	14.7
2011	5.3	5.3	8.9	9.5	10.4	15.9
2010	5.7	6.0	9.6	10.3	11.1	16.7
2009	4.7	5.9	9.3	9.7	10.5	16.2
2008	2.1	3.1	5.8	6.1	6.8	10.5
2007	1.5	2.3	4.6	4.9	5.5	8.3
2006	1.5	2.2	4.6	4.9	5.5	8.2
2005	1.8	2.5	5.1	5.4	6.1	8.9
2004	2.1	2.8	5.5	5.8	6.5	9.6
2003	2.3	3.3	6.0	6.3	7.0	10.1
2002	2.0	3.2	5.8	6.0	6.7	9.6
2001	1.2	2.4	4.7	4.9	5.6	8.1
2000	0.9	1.8	4.0	4.2	4.8	7.0

Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers

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

Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.1 percent in Aug 2011 to 16.3 percent in Sep 2011 and then fell to 14.5 percent in Mar 2012, reaching 12.6 percent in Feb 2014. Unemployment is an incomplete measure of the stress in US job markets. A different calculation in this blog is provided by using the participation rate in the labor force before the global recession. This calculation shows 29.1 million in job stress of unemployment/underemployment in Feb 2013, not seasonally adjusted, corresponding to 17.8 percent of the labor force (Table I-4 http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html).

Table I-8, US, Alternative Measures of Labor Underutilization SA %

	U1	U2	U3	U4	U5	U6
Feb 2014	3.5	3.5	6.7	7.2	8.1	12.6
Jan	3.4	3.5	6.6	7.1	8.1	12.7
Dec 2013	3.6	3.5	6.7	7.2	8.1	13.1
Nov	3.7	3.7	7.0	7.4	8.2	13.1
Oct	3.8	4.0	7.2	7.7	8.6	13.7
Sep	3.8	3.7	7.2	7.7	8.6	13.6
Aug	3.8	3.8	7.2	7.8	8.6	13.6
Jul	3.9	3.8	7.3	7.9	8.7	13.9
Jun	4.0	3.9	7.5	8.1	9.0	14.2
May	4.0	3.9	7.5	8.0	8.8	13.8
Apr	4.1	4.1	7.5	8.0	8.9	13.9
Mar	4.1	4.1	7.5	8.0	8.9	13.8
Feb	4.2	4.2	7.7	8.3	9.3	14.3
Jan	4.2	4.3	7.9	8.4	9.3	14.4
Dec 2012	4.3	4.2	7.9	8.5	9.4	14.4
Nov	4.2	4.1	7.8	8.3	9.2	14.4
Oct	4.4	4.2	7.8	8.3	9.2	14.4
Sep	4.3	4.2	7.8	8.3	9.3	14.7
Aug	4.4	4.5	8.1	8.6	9.6	14.7
Jul	4.5	4.6	8.2	8.7	9.7	14.9
Jun	4.6	4.6	8.2	8.7	9.6	14.8
May	4.6	4.5	8.2	8.7	9.6	14.8
Apr	4.6	4.4	8.2	8.7	9.5	14.6
Mar	4.7	4.6	8.2	8.7	9.6	14.5
Feb	4.8	4.6	8.3	8.9	9.8	15.0
Jan	4.8	4.7	8.2	8.8	9.8	15.1
Dec 2011	4.9	4.9	8.5	9.1	10.0	15.2
Nov	5.0	5.0	8.6	9.3	10.2	15.6
Oct	5.1	5.1	8.8	9.4	10.3	15.9
Sep	5.4	5.2	9.0	9.6	10.5	16.3
Aug	5.3	5.2	9.0	9.6	10.5	16.1
Jul	5.3	5.3	9.0	9.7	10.6	16.0
Jun	5.3	5.3	9.1	9.7	10.7	16.1
May	5.3	5.4	9.0	9.5	10.3	15.8
Apr	5.2	5.4	9.1	9.7	10.5	16.1
Mar	5.3	5.4	9.0	9.5	10.4	15.9
Feb	5.4	5.5	9.0	9.6	10.6	16.0
Jan	5.5	5.5	9.1	9.7	10.7	16.1

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

Chart I-16 provides U6 on a monthly basis from 2001 to 2014. There was a steep climb from 2007 into 2009 and then this measure of unemployment and underemployment stabilized at that high level but declined into 2012. The low of U6 SA was 8.0 percent in Mar 2007 and the peak was 17.1 percent in Apr 2010. The low NSA was 7.6 percent in Oct 2006 and the peak was 18.0 percent in Jan 2010.

Chart I-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed Part-Time for Economic Reasons, Month, SA, 2001-2014

Source: US Bureau of Labor Statistics

Chart I-17 provides the number employed part-time for economic reasons or who cannot find full-time employment. There are sharp declines at the end of 2009, 2010 and 2011 but an increase in 2012 followed by stability in 2013-2014.

Chart I-17, US, Working Part-time for Economic Reasons

Thousands, Month SA 2001-2014

Sources: US Bureau of Labor Statistics

ICA3 Ten Million Fewer Full-time Jobs. There is strong seasonality in US labor markets around the end of the year. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.068 million in Sep 2011 to 7.780 million in Mar 2012, seasonally adjusted, or decline of 1.288 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.572 million in Sep 2012 for increase of 527,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.231 million in Oct 2012 or by 341,000 again in one month, further declining to 8.164 million in Nov 2012 for another major one-month decline of 67,000 and 7.929 million in Dec 2012 or fewer 235,000 in just one month. The number employed part-time for economic reasons increased to 7.983 million in Jan 2013 or 54,000 more than in Dec 2012 and to 7,991 million in Feb 2013, declining to 7.917 million in May 2013 but increasing to 8.194 million in Jun 2013. The number employed part-time for economic reasons fell to 7.898 million in Aug 2013 for decline of 282,000 in one month from 8.180 million in Jul 2013. The number employed part-time for economic reasons increased 16,000 from 7.898 million in Aug 2013 to 7.914 million in Sep 2013. The number part-time for economic reasons rose to 8.016 million in Oct 2013, falling by 293,000 to 7.723 million in Nov 2013. The number part-time for economic reasons increased to 7.771 million in Dec 2013, decreasing to 7.257 million in Jan 2014. The number employed part-time for economic reasons fell from 7.257 million in Jan 2014 to 7.186 million in Feb 2014. There is an increase of 186,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 119,000 from Aug 2012 to Nov 2012. The number employed full-time increased from 112.906 million in Oct 2011 to 115.114 million in Mar 2012 or 2.208 million but then fell to 114.279 million in May 2012 or 0.835 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.626 million in Aug 2012 to 115.531 million in Oct 2012 or increase of 0.905 million full-time jobs in two months and further to 115.821 million in Jan 2013 or increase of 1.195 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.785 million in Feb 2013, increasing to 116.288 million in May 2013 and 116.087 million in Jun 2013. Then number of full-time jobs increased to 116.156 million in Jul 2013, 116.301 million in Aug 2013 and 116.883 million in Sep 2013. The number of full-time jobs fell to 116.306 million in Oct 2013 and increased to 116.951 in Nov 2013. The level of full-time jobs fell to 117.278 million in Dec 2013, increasing to 117.656 million in Jan 2014 and 117.819 million in Feb 2014. Benchmark and seasonality-factors adjustments at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.051 million and to 7.694 million in Apr 2012 or 1.224 million fewer relative to Jan 2012. In Aug 2012, the number employed part-time for economic reasons reached 7.842 million NSA or 148,000 more than in Apr 2012. The number employed part-time for economic reasons increased from 7.842 million in Aug 2012 to 8.110 million in Sep 2012 or by 3.4 percent. The number part-time for economic reasons fell from 8.110 million in Sep 2012 to 7.870 million in Oct 2012 or by 240.000 in one month. The number employed part-time for economic reasons NSA increased to 8.628 million in Jan 2013 or 758,000 more than in Oct 2012. The number employed part-time for economic reasons fell to 8.298 million in Feb 2013, which is lower by 330,000 relative to 8.628 million in Jan 2013 but higher by 428,000 relative to 7.870 million in Oct 2012. The number employed part time for economic reasons fell to 7.734 million in Mar 2013 or 564,000 less than in Feb 2013 and fell to 7.709 million in Apr 2013. The number employed part-time for economic reasons reached 7.618 million in May 2013. The number employed part-time for economic reasons jumped from 7.618 million in May 2013 to 8.440 million in Jun 2013 or 822,000 in one month. The number employed part-time for economic reasons fell to 8.324 million in Jul 2013 and 7.690 million in Aug 2013. The number employed part-time for economic reasons NSA fell to 7.522 million in Sep 2013, increasing to 7.700 million in Oct 2013. The number employed part-time for economic reasons fell to 7.563 million in Nov 2013 and increased to 7.990 million in Dec 2013. The number employed part-time for economic reasons fell to 7.771 million in Jan 2014 and 7.397 million in Feb 2014. The number employed full time without seasonal adjustment fell from 113.138 million in Nov 2011 to 113.050 million in Dec 2011 or by 88,000 and fell further to 111.879 in Jan 2012 for cumulative decrease of 1.259 million. The number employed full-time not seasonally adjusted fell from 113.138 million in Nov 2011 to 112.587 million in Feb 2012 or by 551.000 but increased to 116.214 million in Aug 2012 or 3.076 million more full-time jobs than in Nov 2011. The number employed full-time not seasonally adjusted decreased from 116.214 million in Aug 2012 to 115.678 million in Sep 2012 for loss of 536,000 full-time jobs and rose to 116.045 million in Oct 2012 or by 367,000 full-time jobs in one month relative to Sep 2012. The number employed full-time NSA fell from 116.045 million in Oct 2012 to 115.515 million in Nov 2012 or decline of 530.000 in one month. The number employed full-time fell from 115.515 in Nov 2012 to 115.079 million in Dec 2012 or decline by 436,000 in one month. The number employed full time fell from 115.079 million in Dec 2012 to 113.868 million in Jan 2013 or decline of 1.211 million in one month. The number of full time jobs increased to 114.191 in Feb 2012 or by 323,000 in one month and increased to 114.796 million in Mar 2013 for cumulative increase from Jan by 928,000 full-time jobs but decrease of 283,000 from Dec 2012. The number employed full time reached 117.400 million in Jun 2013 and increased to 117.688 in Jul 2013 or by 288,000. The number employed full-time reached 117.868 million in Aug 2013 for increase of 180,000 in one month relative to Jul 2013. The number employed full-time fell to 117.308 million in Sep 2013 or by 560,000. The number employed full-time fell to 116.798 million in Oct 2013 or decline of 510.000 in one month. The number employed full-time rose to 116.875 million in Nov 2013, falling to 116.661 million in Dec 2013. The number employed full-time fell to 115.744 million in Jan 2014 but increased to 116.232 million in Feb 2014. Comparisons over long periods require use of NSA data. The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in Feb 2014 is 116.323 million, which is lower by 6.896 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 247.085 million in Feb 2014 or by 15.127 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 6.986 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 131.202 million full-time jobs with population of 247.085 million in Feb 2014 or 14.879 million fewer full-time jobs relative to actual 116.323 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 15 million. Mediocre GDP growth is the main culprit of the fractured US labor market. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp4q13_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth on trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,107.4 billion than actual $15,932.9 billion. There are about two trillion dollars of GDP less than on trend, explaining the 29.1 million unemployed or underemployed equivalent to actual unemployment of 17.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,932.9 billion in IVQ2013 or 6.2 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation.

Table I-9, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Feb 2014	7,186	117.819
Jan 2014	7,257	117.656
Dec 2013	7,771	117.278
Nov 2013	7,723	116.951
Oct 2013	8,016	116.306
Sep 2013	7,914	116.883
Aug 2013	7,898	116.301
Jul 2013	8,180	116.156
Jun 2013	8,194	116.087
May 2013	7,917	116.288
Apr 2013	7,929	116.062
Mar 2013	7,663	115.901
Feb 2013	7,991	115.785
Jan 2013	7,983	115.821
Dec 2012	7,929	115.735
Nov 2012	8,164	115.581
Oct 2012	8,231	115.531
Sep 2012	8,572	115.229
Aug 2012	8,045	114.626
Jul 2012	8,163	114.589
Jun 2012	8,154	114.728
May 2012	8,138	114.279
Apr 2012	7,913	114.398
Mar 2012	7,780	115.114
Feb 2012	8,133	114.210
Jan 2012	8,228	113.790
Dec 2011	8,177	113.740
Nov 2011	8,457	113.158
Oct 2011	8,675	112.906
Sep 2011	9,068	112.523
Aug 2011	8,820	112.643
Jul 2011	8,342	112.209
Not Seasonally Adjusted
Feb 2014	7,397	116.323
Jan 2014	7,771	115.744
Dec 2013	7,990	116.661
Nov 2013	7,563	116.875
Oct 2013	7,700	116.798
Sep 2013	7,522	117.308
Aug 2013	7,690	117.868
Jul 2013	8,324	117.688
Jun 2013	8,440	117.400
May 2013	7,618	116.643
Apr 2013	7,709	115.674
Mar 2013	7,734	114.796
Feb 2013	8,298	114.191
Jan 2013	8,628	113.868
Dec 2012	8,166	115.079
Nov 2012	7,994	115.515
Oct 2012	7,870	116.045
Sep 2012	8,110	115.678
Aug 2012	7,842	116.214
Jul 2012	8,316	116.131
Jun 2012	8,394	116.024
May 2012	7,837	114.634
Apr 2012	7,694	113.999
Mar 2012	7,867	113.916
Feb 2012	8,455	112.587
Jan 2012	8,918	111.879
Dec 2011	8,428	113.050
Nov 2011	8,271	113.138
Oct 2011	8,258	113.456
Sep 2011	8,541	112.980
Aug 2011	8,604	114.286
Jul 2011	8,514	113.759
Jun 2011	8,738	113.255
May 2011	8,270	112.618
Apr 2011	8,425	111.844
Mar 2011	8,737	111.186
Feb 2011	8,749	110.731
Jan 2011	9,187	110.373
Dec 2010	9,205	111.207
Nov 2010	8,670	111.348
Oct 2010	8,408	112.342
Sep 2010	8,628	112.385
Aug 2010	8,628	113.508
Jul 2010	8,737	113.974
Jun 2010	8,867	113.856
May 2010	8,513	112.809
Apr 2010	8,921	111.391
Mar 2010	9,343	109.877
Feb 2010	9,282	109.100
Jan 2010	9,290	108.777 (low)
Dec 2009	9,354 (high)	109.875
Nov 2009	8,894	111.274
Oct 2009	8,474	111.599
Sep 2009	8,255	111.991
Aug 2009	8,835	113.863
Jul 2009	9,103	114.184
Jun 2009	9,301	114.014
May 2009	8,785	113.083
Apr 2009	8,648	112.746
Mar 2009	9,305	112.215
Feb 2009	9,170	112.947
Jan 2009	8,829	113.815
Dec 2008	8,250	116.422
Nov 2008	7,135	118.432
Oct 2008	6,267	120.020
Sep 2008	5,701	120.213
Aug 2008	5,736	121.556
Jul 2008	6,054	122.378
Jun 2008	5,697	121.845
May 2008	5,096	120.809
Apr 2008	5,071	120.027
Mar 2008	5,038	119.875
Feb 2008	5,114	119.452
Jan 2008	5,340	119.332
Dec 2007	4,750	121.042
Nov 2007	4,374	121.846
Oct 2007	4,028	122.006
Sep 2007	4,137	121.728
Aug 2007	4,494	122.870
Jul 2007	4,516	123.219 (high)
Jun 2007	4,469	122.150
May 2007	4,315	120.846
Apr 2007	4,205	119.609
Mar 2007	4,384	119.640
Feb 2007	4,417	119.041
Jan 2007	4,726	119.094
Dec 2006	4,281	120.371
Nov 2006	4,054	120.507
Oct 2006	4,010	121.199
Sep 2006	3,735 (low)	120.780
Aug 2006	4,104	121.979
Jul 2006	4,450	121.951
Jun 2006	4,456	121.070
May 2006	3,968	118.925
Apr 2006	3,787	118.559
Mar 2006	4,097	117.693
Feb 2006	4,403	116.823
Jan 2006	4,597	116.395

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

People lose their marketable job skills after prolonged unemployment and face increasing difficulty in finding another job. Chart I-18 shows the sharp rise in unemployed over 27 weeks and stabilization at an extremely high level.

Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2014

Sources: US Bureau of Labor Statistics

Another segment of U6 consists of people marginally attached to the labor force who continue to seek employment but less frequently on the frustration there may not be a job for them. Chart I-19 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.

Chart I-19, US, Marginally Attached to the Labor Force, NSA Month, Thousands, 2001-2014

Sources: US Bureau of Labor Statistics

The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in Feb 2014 is 116.323 million, which is lower by 6.896 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 247.085 million in Feb 2014 or by 15.127 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 6.986 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 131.202 million full-time jobs with population of 247.085 million in Feb 2014 or 14.879 million fewer full-time jobs relative to actual 116.323 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 15 million. Chart I-20 provides unadjusted full-time jobs in the US from 2001 to 2014 with sharp drop and incomplete recovery. There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

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

Inferior performance of the US economy and labor markets, during cyclical slow growth not secular stagnation, is the critical current issue of analysis and policy design.

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2014

Sources: US Bureau of Labor Statistics

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2013. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2014

Sources: US Bureau of Labor Statistics

Chart I-20B provides number of full-time jobs in the US from 1968 to 2013. There were multiple recessions followed by expansions without contraction of full-time jobs and without recovery as during the period after 2008. The problem is specific of the current cycle and not secular.

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2014

Sources: US Bureau of Labor Statistics

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

Chart I-20C, US, Noninstitutional Civilian Population, Thousands, 1968-2013

Sources: US Bureau of Labor Statistics

IA4 Theory and Reality of Secular Stagnation: Youth and Middle-Age Unemployment. Three tables support the argument that the proper comparison of the business cycle is between the recessions of the 1980s and the global recession after IVQ2007 and not as argued erroneously with the Great Depression of the 1930s.

Table I-5 provides percentage change of real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Data are available for the 1930s only on a yearly basis. US GDP fell 4.7 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1981 to IVQ1982 and 4.3 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first three years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985 and 3.5 percent in 1986 while GDP grew, 2.5 percent in 2010, 1.8 percent in 2011, 2.8 percent in 2012 and 1.9 percent in 2013. Actual annual equivalent GDP growth in the four quarters of 2012 and first four quarters of 2013 is 2.3 percent and 2.7 percent in the four quarters of 2013 but only 2.3 percent discounting contribution of 1.67 percentage points of inventory accumulation to growth in IIIQ2013. GDP grew at 4.2 percent in 1985 and 3.5 percent in 1986 while the forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 2.2 to 2.3 percent in 2013 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20131218.pdf) with less reliable forecast of 2.8 to 3.2 percent in 2014 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20131218.pdf). Growth of GDP in the expansion from IIIQ2009 to IVQ2013 has been at average 2.3 percent in annual equivalent.

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

Year	GDP ∆%	Year	GDP ∆%	Year	GDP ∆%
1930	-8.5	1980	-0.2	2000	4.1
1931	-6.4	1981	2.6	2001	1.0
1932	-12.9	1982	-1.9	2002	1.8
1933	-1.3	1983	4.6	2003	2.8
1934	10.8	1984	7.3	2004	3.8
1935	8.9	1985	4.2	2005	3.4
1936	12.9	1986	3.5	2006	2.7
1937	5.1	1987	3.5	2007	1.8
1938	-3.3	1988	4.2	2008	-0.3
1930	8.0	1989	3.7	2009	-2.8
1940	8.8	1990	1.9	2010	2.5
1941	17.7	1991	-0.1	2011	1.8
1942	18.9	1992	3.6	2012	2.8
1943	17.0	1993	2.7	2013	1.9

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 4.7 percent, which is almost equal to the decline of 4.3 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

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

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	3	-2.4	-0.8
IIIQ1957 to IIQ1958	3	-3.0	-1.0
IVQ1973 to IQ1975	5	-3.1	-0.6
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.5	-0.64
IVQ2007 to IIQ2009	6	-4.3	-0.72

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

Table I-7 shows the mediocre average annual equivalent growth rate of 2.3 percent of the US economy in the eighteen quarters of the current cyclical expansion from IIIQ2009 to IVQ2013. In sharp contrast, the average growth rate of GDP was: 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986, 5.4 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986, 5.2 percent in the first sixteen quarters of expansion from IQ1983 to IVQ1986, 5.0 percent in the first seventeen quarters of expansion from IQ1983 to IQ1987 and 5.0 percent in the eighteen quarters of expansion from IQ1983 to IIQ1987. The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 decelerating to 1.8 percent annual growth in 2011 and 2.8 percent in 2012 (http://www.bea.gov/iTable/index_nipa.cfm) The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IIQ1987 and at 7.8 percent from IQ1983 to IVQ1983. GDP growth in the four quarters of 2012 and 2013 accumulated to 4.5 percent that is equivalent to 2.2 percent in a year. This is obtained by dividing GDP in IVQ2013 of $15,932.9 billion by GDP in IVQ2011 of $15,242.1 billion and compounding by 4/8: {[($15,932.9/$15,242.1)^4/8 -1]100 = 2.2%}. The US economy grew 2.5 percent in IVQ2013 relative to the same quarter a year earlier in IVQ2012. Another important revelation of the revisions and enhancements is that GDP was flat in IVQ2012, which is just at the borderline of contraction. The rate of growth of GDP in the third estimate of IIIQ2013 is 4.1 percent in seasonally adjusted annual rate (SAAR). Inventory accumulation contributed 1.67 percentage points to this rate of growth. The actual rate without this impulse of unsold inventories would have been 2.43 percent, or 0.6 percent in IIIQ2013, such that annual equivalent growth in 2013 is closer to 2.1 percent {[(1.003)(1.006)(1.006)(1.006^4/4-1]100 = 2.1%}, compounding the quarterly rates and converting into annual equivalent.

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

	Number of Quarters	Cumulative Growth ∆%	Average Annual Equivalent Growth Rate
IIIQ 1954 to IQ1957	11	12.8	4.5
First Four Quarters IIIQ1954 to IIQ1955	4	7.8
IIQ1958 to IIQ1959	5	10.0	7.9
First Four Quarters IIIQ1958 to IIQ1959	4	9.2
IIQ1975 to IVQ1976	8	8.3	4.1
First Four Quarters IIIQ1975 to IIQ1976	4	6.1
IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987 IQ1983-IIQ1987	13 15 16 17 18	19.9 21.6 22.3 23.1 24.5	5.7 5.4 5.2 5.0 5.0
First Four Quarters IQ1983 to IVQ1983	4	7.8
Average First Four Quarters in Four Expansions*		7.7
IIIQ2009 to IVQ2013	18	11.0	2.3
First Four Quarters IIIQ2009 to IIQ2010		2.7

*First Four Quarters: 7.8% IIIQ1954-IIQ1955; 9.2% IIIQ1958-IIQ1959; 6.1% IIIQ1975-IIQ1976; 7.8% IQ1983-IVQ1983

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

Table EMP provides the comparison between the labor market in the current whole cycle from 2007 to 2013 and the whole cycle from 1979 to 1986. In the entire cycle from 2007 to 2013, the number employed fell 2.118 million, full-time employed fell 4.777 million, part-time for economic reasons increased 3.534 and population increased 13.812 million. The number employed fell 1.5 percent, full-time employed fell 3.9 percent, part-time for economic reasons increased 80.3 percent and population increased 6.0 percent. There is sharp contrast with the contractions of the 1980s and with most economic history of the United States. In the whole cycle from 1979 to 1986, the number employed increased 10.773 million, full-time employed increased 7.875 million, part-time for economic reasons 2.011 million and population 15.724 million. In the entire cycle from 1979 to 1986, the number employed increased 10.9 percent, full-time employed 9.5 percent, part-time for economic reasons 56.2 percent and population 9.5 million. The difference between the 1980s and the current cycle after 2007 is in the high rate of growth after the contraction that maintained trend growth around 3.0 percent for the entire cycle and per capital growth at 2.0 percent. The evident fact is that current weakness in labor markets originates in cyclical slow growth and not in imaginary secular stagnation.

Table EMP, US, Annual Level of Employed, Full-Time Employed, Employed Part-Time for Economic Reasons and Noninstitutional Civilian Population, Millions

	Employed	Full-Time Employed	Part Time Economic Reasons	Noninstitutional Civilian Population
2000s
2000	136.891	113.846	3.227	212.577
2001	136.933	113.573	3.715	215.092
2002	136.485	112.700	4.213	217.570
2003	137.736	113.324	4.701	221.168
2004	139.252	114.518	4.567	223.357
2005	141.730	117.016	4.350	226.082
2006	144.427	119.688	4.162	228.815
2007	146.047	121.091	4.401	231.867
2008	145.362	120.030	5.875	233.788
2009	139.877	112.634	8.913	235.801
2010	139.064	111.714	8.874	237.830
2011	139.869	112.556	8.560	239.618
2012	142.469	114.809	8.122	243.284
2013	143.929	116.314	7.935	245.679
∆2007-2013	-2.118	-4.777	3.534	13.812
∆% 2007-2013	-1.5	-3.9	80.3	6.0
1980s
1979	98.824	82.654	3.577	164.863
1980	99.303	82.562	4.321	167.745
1981	100.397	83.243	4.768	170.130
1982	99.526	81.421	6.170	172.271
1983	100.834	82.322	6.266	174.215
1984	105.005	86.544	5.744	176.383
1985	107.150	88.534	5.590	178.206
1986	109.597	90.529	5.588	180.587
1987	112.440	92.957	5.401	182.753
1988	114.968	95.214	5.206	184.613
1989	117.342	97.369	4.894	186.393
∆1979-1986	10.773	7.875	2.011	15.724
∆% 1979-86	10.9	9.5	56.2	9.5

Source: Bureau of Labor Statistics

http://www.bls.gov/

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

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). Youth workers would obtain employment at a premium in an economy with declining population. In fact, there is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages. This is merely another case of theory without reality with dubious policy proposals. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design.

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

Y = ∑_is_iy_i (1)

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

∆Y = ∑_i∆s_iy*_i+ ∑_i∆y_is*_i (2)

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

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

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. There are accentuated cyclic factors for both the entire population and the young population of ages 16 to 24 years. Table Summary provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would not be secular but immediate. All indicators of the labor market weakened sharply during the contraction and did not recover. Population continued to grow but all other variables collapsed and did not recover. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-6). Hansen (1938, 1939) finds secular stagnation in lower growth of an aging population. In the current US economy, Table Summary shows that population is dynamic while the labor market is fractured. There is key explanation in the behavior of the civilian labor force participation rate (CLFP) and the employment population ratio (EPOP) that collapsed during the global recession with inadequate recovery. Abandoning job searches are difficult to capture in labor statistics but likely explain the decline in the participation of the population in the labor force. Allowing for abandoning job searches, the total number of people unemployed or underemployed is 29.1 million or 17.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html).

Table Summary Total, US, Total Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Thousands and Percent

	ICP	FTE	EMP	CLF	CLFP	EPOP	UNE
2006	228.8	119.7	144.4	151.4	66.2	63.1	7.0
2009	235.8	112.6	139.9	154.1	65.4	59.3	14.3
2012	243.3	114.8	142.5	155.0	63.7	58.6	12.5
2013	245.7	116.3	143.9	155.4	63.2	58.6	11.5
12/07	233.2	121.0	146.3	153.7	65.9	62.8	7.4
9/09	236.3	112.0	139.1	153.6	65.0	58.9	14.5
1/14	247.1	116.3	144.1	155.0	62.7	58.3	10.9

ICP: Total Noninstitutional Civilian Population; FT: Full-time Employment Level, EMP: Total Employment Level; CLF: Civilian Labor Force; CLFP: Civilian Labor Force Participation Rate; EPOP: Employment Population Ratio; UNE: Unemployment

Source: Bureau of Labor Statistics

The same situation is present in the labor market for young people in ages 16 to 24 years with data in Table Summary Youth. The youth noninstitutional civilian population (ICP) continued to increase during and after the global recession. There is the same disastrous labor market with decline for young people in employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP) and employment population ratio (EPOP). There are only increases for unemployment of young people (UNE) and youth unemployment rate (UNER). If aging were a factor of secular stagnation, growth of population of young people would attract a premium in remuneration in labor markets. The sad fact is that young people are also facing tough labor markets. The application of the theory of secular stagnation to the US economy and labor markets is void of reality in the form of key facts.

Table Summary Youth, US, Youth, Ages 16 to 24 Years, Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Thousands and Percent

	ICP	EMP	CLF	CLFP	EPOP	UNE	UNER
2006	36.9	20.0	22.4	60.6	54.2	2.4	10.5
2009	37.6	17.6	21.4	56.9	46.9	3.8	17.6
2012	38.7	17.8	21.3	54.9	46.0	3.5	16.2
2013	38.8	18.1	21.4	55.0	46.5	3.3	15.5
12/07	37.5	19.4	21.7	57.8	51.6	2.3	10.7
9/09	37.6	17.0	20.7	55.2	45.1	3.8	18.2
2/14	38.8	17.4	20.4	52.6	44.8	3.0	14.9

ICP: Youth Noninstitutional Civilian Population; EMP: Youth Employment Level; CLF: Youth Civilian Labor Force; CLFP: Youth Civilian Labor Force Participation Rate; EPOP: Youth Employment Population Ratio; UNE: Unemployment; UNER: Youth Unemployment Rate

Source: Bureau of Labor Statistics

The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs and to 17.834 million in 2012 or 2.207 million fewer jobs. Youth employment fell from 20.041 million in 2006 to 18.057 million in 2013 or 1.984 million fewer jobs. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.914 million in Jul 2006 with 19.684 million in Jul 2013 for 2.230 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 21.167 million in Aug 2006 to 18.636 million in Aug 2013 or by 2.531 million. The number of youth jobs fell from 19.604 million in Sep 2006 to 18.043 million in Sep 2013 or 1.561 million fewer youth jobs. The number of youth jobs fell from 20.129 million in Dec 2006 to 18.106 million in Dec 2013 or 2.023 million fewer jobs. The number of youth jobs fell from 19.415 million in Feb 2007 to 17.357 million in Feb 2014 or 2.058 million fewer youth jobs. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The youth civilian noninstitutional population increased 1.464 million from 37.302 in Feb 2007 to 38.766 million in Feb 2014 while the number of youth jobs decreased 2.058 million. The hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

Table I-10, US, Employment Level 16-24 Years, Thousands, NSA

Year	Jan	Feb	Sep	Oct	Nov	Dec
2001	19678	19745	19706	19694	19675	19547
2002	18653	19074	19466	19542	19397	19394
2003	18811	18880	18909	19139	19163	19136
2004	18852	18841	19158	19609	19615	19619
2005	18858	18670	19503	19794	19750	19733
2006	19003	19182	19604	19853	19903	20129
2007	19407	19415	19498	19564	19660	19361
2008	18724	18546	18818	18757	18454	18378
2009	17467	17606	16972	16671	16689	16615
2010	16166	16412	16874	16867	16946	16727
2011	16512	16638	17238	17532	17402	17234
2012	16944	17150	17687	17842	17877	17604
2013	17183	17257	18043	17976	18104	18106
2014	17372	17357

Source: Bureau of Labor Statistics

http://www2.census.gov/services/qss/qss.gif

Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2014. Employment level is sharply lower in Feb 2014 relative to the peak in 2007.

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2014

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

Chart I-21A provides the US civilian noninstitutional population ages 16 to 24 years not seasonally adjusted from 2001 to 2014. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The youth civilian noninstitutional population increased 1.464 million from 37.302 in Feb 2007 to 38.766 million in Feb 2014 while the number of youth jobs decreased 2.058 million.

Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2014

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

Chart I-21B provides the civilian labor force of the US ages 16 to 24 years NSA from 2001 to 2014. The US civilian labor force ages 16 to 24 years fell from 24.339 million in Jul 2007 to 23.506 million in Jul 2013, by 0.833 million or decline of 3.4 percent, while the civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013, by 1.418 million or 3.8 percent. The US civilian labor force ages 16 to 24 fell from 22.801 million in Aug 2007 to 22.089 million in Aug 2013, by 0.712 million or 3.1 percent, while the noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013, by 1.386 million or 3.7 percent. The US civilian labor force ages 16 to 24 years fell from 21.917 million in Sep 2007 to 21.183 million in Sep 2013, by 0.734 million or 3.3 percent while the civilian noninstitutional youth population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 by 1.355 million or 3.6 percent. The US civilian labor force fell from 21.821 million in Oct 2007 to 21.003 million in Oct 2013, by 0.818 million or 3.7 percent while the noninstitutional youth population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013, by 1.324 million or 3.5 percent. The US youth civilian labor force fell from 21.909 million in Nov 2007 to 20.825 million in Nov 2013, by 1.084 million or 4.9 percent while the civilian noninstitutional youth population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million. The US youth civilian labor force fell from 21.684 million in Dec 2007 to 20.642 million in Dec 2013, by 1.042 million or 4.8 percent, while the civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013, by 1.272 million or 3.4 percent. The youth civilian labor force of the US fell from 21.770 million in Jan 2007 to 20.423 million in Jan2014, by 1.347 million or 6.2 percent while the youth civilian noninstitutional population increased 37.282 million in Jan 2007 to 38.770 million in Jan 2014, by 1.488 million or 4.0 percent. The youth civilian labor force of the US fell 1.255 million from 21.645 million in Feb 2007 to 20.390 million in Feb 2014 while the youth civilian noninstitutional population increased 1.464 million from 37.302 million in Feb 2007 to 38.766 million in Feb 2014. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.

Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2014

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

Chart I-21C provides the ratio of labor force to noninstitutional population or labor force participation of ages 16 to 24 years not seasonally adjusted. The US labor force participation rates for ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2013 because of the frustration of young people who believe there may not be jobs available for them. The US labor force participation rate of young people fell from 63.9 in Aug 2006 to 56.9 in Aug 2013. The US labor force participation rate of young people fell from 59.1 percent in Sep 2006 to 54.6 percent in Sep 2013. The US labor force participation rate of young people fell from 59.7 percent in Oct 2006 to 54.1 in Oct 2013. The US labor force participation rate of young people fell from 59.7 percent in Nov 2006 to 53.7 percent in Nov 2013. The US labor force participation rate fell from 57.8 in Dec 2007 to 53.2 in Dec 2013. The youth labor force participation rate fell from 58.4 in Jan 2007 to 52.7 in Jan 2014. The US youth labor force participation rate fell from 58.0 percent in Feb 2007 to 53.3 percent in Feb 2013. Many young people abandoned searches for employment, dropping from the labor force.

Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2014

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

An important measure of the job market is the number of people with jobs relative to population available for work or civilian noninstitutional population or employment/population ratio. Chart I-21D provides the employment population ratio for ages 16 to 24 years. The US employment/population ratio NSA for ages 16 to 24 years collapsed from 59.2 in Jul 2006 to 50.7 in Jul 2013. The employment population ratio for ages 16 to 24 years dropped from 57.2 in Aug 2006 to 48.0 in Aug 2013. The employment population ratio for ages to 16 to 24 years declined from 52.9 in Sep 2006 to 46.5 in Sep 2013. The employment population ratio for ages 16 to 24 years fell from 53.6 in Oct 2006 to 46.3 in Oct 2013. The employment population ratio for ages 16 to 24 years fell from 53.7 in Nov 2007 to 46.7 in Nov 2013. The US employment population ratio for ages 16 to 24 years fell from 51.6 in Dec 2007 to 46.7 in Dec 2013. The US employment population ratio fell from 52.1 in Jan 2007 to 44.8 in Jan 2014. The US employment population ratio for ages 16 to 24 fell from 52.0 in Jan 2007 to 44.8 in Jan 2-14. Chart I-21D shows vertical drop during the global recession without recovery.

Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2014

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

Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million and 3451 thousand in 2012 or by 1.109 million. The unemployment level ages 16 to 23 years increased from 2342 in 2007 to 3324 thousand in 2013 or by 0.982 million. The unemployment level ages 16 to 24 years rose from 2.230 million in Feb 2007 to 3.033 million in Feb 2014 or by 0.803million. This situation may persist for many years.

Table I-11, US, Unemployment Level 16-24 Years, NSA, Thousands

Year	Jan	Feb	Sep	Oct	Nov	Dec	Annual
2001	2250	2258	2301	2424	2470	2412	2371
2002	2754	2731	2506	2468	2570	2374	2683
2003	2748	2740	2698	2522	2522	2248	2746
2004	2767	2631	2493	2572	2448	2294	2638
2005	2661	2787	2339	2285	2369	2055	2521
2006	2366	2433	2297	2252	2242	2007	2353
2007	2363	2230	2419	2258	2250	2323	2342
2008	2633	2480	2904	2842	2833	2928	2830
2009	3278	3457	3774	3789	3699	3532	3760
2010	3983	3888	3604	3731	3561	3352	3857
2011	3851	3696	3541	3386	3287	3161	3634
2012	3416	3507	3174	3285	3102	3153	3451
2013	3674	3449	3139	3028	2721	2536	3324
2014	3051	3033

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

Chart I-22 provides the unemployment level for ages 16 to 24 from 2001 to 2014. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013-2014 with recent marginal improvement alternating with deterioration.

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2014

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

Table I-12 provides the rate of unemployment of young peoples in ages 16 to 24 years. The annual rate jumped from 10.5 percent in 2007 to 18.4 percent in 2010, 17.3 percent in 2011 and 16.2 percent in 2012. The rate of youth unemployment fell marginally to 15.5 percent in 2013. During the seasonal peak in Jul, the rate of youth unemployed was 18.1 percent in Jul 2011, 17.1 percent in Jul 2012 and 16.3 percent in Jul 2013 compared with 10.8 percent in Jul 2007. The rate of youth unemployment rose from 11.2 in Jul 2006 to 16.3 percent in Jul 2013 and likely higher if adding those who ceased searching for a job in frustration none may be available. The rate of youth unemployment increased from 9.1 percent in Dec 2006 to 12.3 percent in Dec 2013. The rate of youth unemployment increased from 10.9 percent in Jan 2007 to 14.9 percent in Jan and Feb 2014. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them.

Table I-12, US, Unemployment Rate 16-24 Years, Thousands, NSA

Year	Jan	Feb	Mar	Jul	Aug	Sep	Oct	Nov	Dec	Annual
2001	10.3	10.3	10.2	10.5	10.7	10.5	11.0	11.2	11.0	10.6
2002	12.9	12.5	12.9	12.4	11.5	11.4	11.2	11.7	10.9	12.0
2003	12.7	12.7	12.2	13.3	11.9	12.5	11.6	11.6	10.5	12.4
2004	12.8	12.3	12.1	12.3	11.1	11.5	11.6	11.1	10.5	11.8
2005	12.4	13.0	11.7	11.0	10.8	10.7	10.3	10.7	9.4	11.3
2006	11.1	11.3	10.3	11.2	10.4	10.5	10.2	10.1	9.1	10.5
2007	10.9	10.3	9.7	10.8	10.5	11.0	10.3	10.3	10.7	10.5
2008	12.3	11.8	11.1	14.0	13.0	13.4	13.2	13.3	13.7	12.8
2009	15.8	16.4	16.1	18.5	18.0	18.2	18.5	18.1	17.5	17.6
2010	19.8	19.2	18.4	19.1	17.8	17.6	18.1	17.4	16.7	18.4
2011	18.9	18.2	17.2	18.1	17.5	17.0	16.2	15.9	15.5	17.3
2012	16.8	17.0	16.0	17.1	16.8	15.2	15.5	14.8	15.2	16.2
2013	17.6	16.7	15.9	16.3	15.6	14.8	14.4	13.1	12.3	15.5
2014	14.9	14.9

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

Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2001 to 2014. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels because of low growth of GDP. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2014

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

Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2014. The rate of youth unemployment rose to 20 percent during the contractions of the early 1980s and also during the contraction of the global recession in 2008 and 2009. The data illustrate again the argument in this blog that the contractions of the early 1980s are the valid framework for comparison with the global recession of 2008 and 2009 instead of misleading comparisons with the 1930s. During the initial phase of recovery, the rate of youth unemployment 16 to 24 years NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984. In contrast, the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 17.5 percent in Dec 2009, 16.7 percent in Dec 2010, 15.5 percent in Dec 2011, 15.2 percent in Dec 2012, 17.6 percent in Jan 2013, 16.7 percent in Feb 2013, 15.9 percent in Mar 2013, 15.1 percent in Apr 2013. The rate of youth unemployment was 16.4 percent in May 2013, 18.0 percent in Jun 2013, 16.3 percent in Jul 2013 and 15.6 percent in Aug 2013. In Sep 2006, the rate of youth unemployment was 10.5 percent, increasing to 14.8 percent in Sep 2013. The rate of youth unemployment was 10.3 in Oct 2007, increasing to 14.4 percent in Oct 2013. The rate of youth unemployment was 10.3 percent in Nov 2007, increasing to 13.1 percent in Nov 2013. The rate of youth unemployment was 10.7 percent in Dec 2013, increasing to 12.3 percent in Dec 2013. The rate of youth unemployment was 10.9 percent in Jan 2007, increasing to 14.9 percent in Jan 2014. The rate of youth unemployment was 10.3 percent in Feb 2007, increasing to 14.9 percent in Feb 2014. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 and 5.2 percent from IQ1983 to IIIQ1986 compared with 2.3 percent on average during the first seventeen quarters of expansion from IIIQ2009 to IVQ2013 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp4q13_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth on trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,107.4 billion than actual $15,932.9 billion. There are about two trillion dollars of GDP less than on trend, explaining the 29.1 million unemployed or underemployed equivalent to actual unemployment of 17.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,932.9 billion in IVQ2013 or 6.2 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation.

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2014

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

It is more difficult to move to other jobs after a certain age because of fewer available opportunities for mature individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.607 million in Oct 2006 to 4.576 million in Oct 2010 or by 184.8 percent. The number of unemployed ages 45 years and over declined to 3.800 million in Oct 2012 that is still higher by 136.5 percent than in Oct 2006. The number unemployed age 45 and over increased from 1.704 million in Nov 2006 to 3.861 million in Nov 2012, or 126.6 percent. The number unemployed age 45 and over is still higher by 98.5 percent at 3.383 million in Nov 2013 than 1.704 million in Nov 2006. The number unemployed age 45 and over jumped from 1.794 million in Dec 2006 to 4.762 million in Dec 2010 or 165.4 percent. At 3.927 million in Dec 2012, mature unemployment is higher by 2.133 million or 118.9 percent higher than 1.794 million in Dec 2006. The level of unemployment of those aged 45 year or more of 3.632 million in Oct 2013 is higher by 2.025 million than 1.607 million in Sep 2006 or higher by 126.0 percent. The number of unemployed 45 years and over increased from 1.794 million in Dec 2006 to 3.378 million in Nov 2013 or 88.3 percent. The annual number of unemployed 45 years and over increased from 1.848 million 2006 to 3.719 million in 2013 or 101.2 percent. The number of unemployed 45 years and over increased from 2.126 million in Jan 2006 to 4.394 million in Jan 2013, by 2.618 million or 106.7 percent. The number of unemployed 45 years and over rose from 2.126 million in Jan 2006 to 3.508 million in Jan 2014, by 1.382 million or 65.0 percent. The level of unemployed 45 years or older increased 2.051 million or 99.8 percent from 2.056 million in Feb 2006 to 4.107 million in Feb 2013 and at 3.490 million in Feb 2014 is higher by 69.7 percent than in Feb 2006. The actual number unemployed is likely much higher because many are not accounted who abandoned job searches in frustration there may not be a job for them. Recent improvements may be illusory.

Table I-13, US, Unemployment Level 45 Years and Over, Thousands NSA

Year	Jan	Feb	Sep	Oct	Nov	Dec	Annual
2000	1498	1392	1254	1202	1242	1217	1249
2001	1572	1587	1586	1722	1786	1901	1576
2002	2235	2280	1966	1945	2013	2210	2114
2003	2495	2415	2157	2032	2132	2130	2253
2004	2453	2397	1951	1931	2053	2086	2149
2005	2286	2286	1992	1875	1920	1963	2009
2006	2126	2056	1710	1607	1704	1794	1848
2007	2155	2138	1854	1885	1925	2120	1966
2008	2336	2336	2595	2728	3078	3485	2540
2009	4138	4380	4560	4492	4655	4960	4500
2010	5314	5307	4640	4576	4909	4762	4879
2011	5027	4837	4426	4375	4195	4182	4537
2012	4458	4472	3899	3800	3861	3927	4133
2013	4394	4107	3535	3632	3383	3378	3719
2014	3508	3490

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

Chart I-25 provides the level unemployed ages 45 years and over. There was an increase in the recessions of the 1980s, 1991 and 2001 followed by declines to earlier levels. The current expansion of the economy after IIIQ2009 has not been sufficiently vigorous to reduce significantly middle-age unemployment. Recent improvements could be illusory because many abandoned job searches in frustration that there may not be jobs for them and are not counted as unemployed.

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2014

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

The analysis by Kydland (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/kydland-bio.html) and Prescott (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/prescott-bio.html) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:

U_t = Uⁿ_t – α(π_t – π^e) α > 0 (1)

Where U_t is the rate of unemployment at current time t, Uⁿ_t is the natural rate of unemployment, π_t is the current rate of inflation and π^e is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:

W = W(π_t, U_t) (2)

The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (π_t, U_t- Uⁿ) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent on average since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). The Bureau of Labor Statistics important report on productivity and costs released on Mar 6, 2014 (http://www.bls.gov/lpc/) supports the argument of decline of productivity in the US analyzed by Prescott and Ohanian (2014Feb). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2013. The data confirm the argument of Prescott and Ohanian (2014Feb): productivity increased cumulatively 2.5 percent from 2011 to 2013 at the average annual rate of 0.8 percent. The situation is direr by excluding growth of 1.5 percent in 2013, which leaves an average of 0.5 percent for 2011 and 2013. Average productivity growth for the entire economic cycle from 2007 to 2013 is only 1.6 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.1 percent and 3.3 percent in 2013 consisted on reducing labor hours.

Table II-2, US, Revised Nonfarm Business Sector Productivity and Costs Annual Average, ∆% Annual Average

	2013 ∆%	2012 ∆%	2011 ∆%	2010 ∆%	2009 ∆%	2008 ∆%	2007 ∆%
Productivity	0.5	1.5	0.5	3.3	3.1	0.8	1.6
Real Hourly Compensation	0.1	0.5	-0.7	0.4	1.5	-1.1	1.4
Unit Labor Costs	1.1	1.2	2.0	-1.2	-2.0	2.0	2.6

Source: US Bureau of Labor Statistics

http://www.bls.gov/lpc/

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

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

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

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

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

U_t = Uⁿ_t – α(π_t – π^e) α > 0 (1)

W = W(π_t, U_t) (2)

The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (π_t, U_t- Uⁿ) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). The Bureau of Labor Statistics important report on productivity and costs released on Mar 6, 2014 (http://www.bls.gov/lpc/) supports the argument of decline of productivity in the US analyzed by Prescott and Ohanian (2014Feb). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2013. The data confirm the argument of Prescott and Ohanian (2014Feb): productivity increased cumulatively 2.5 percent from 2011 to 2013 at the average annual rate of 0.8 percent. The situation is direr by excluding growth of 1.5 percent in 2013, which leaves an average of 0.5 percent for 2011 and 2013. Average productivity growth for the entire economic cycle from 2007 to 2013 is only 1.6 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.1 percent and 3.3 percent in 2013 consisted on reducing labor hours.

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 theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-6). 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.”

Chart II-7 provides nonfarm-business labor productivity, measured by output per hour, from 1947 to 2013. The rate of productivity increase continued in the early part of the 2000s but then softened and fell during the global recession. The interruption of productivity increases occurred exclusively in the current business cycle. Lazear and Spletzer (2012JHJul22) find “primarily cyclic” factors in explaining the frustration of currently depressed labor markets in the United States. Stagnation of productivity is another cyclic event and not secular trend. The theory and application of secular stagnation to current US economic conditions is void of reality.

Chart II-7, US, Nonfarm Business Labor Productivity, Output per Hour, 1947-2013, Index 2005=100

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

Table II-6 expands Table II-2 providing more complete measurements of the Productivity and Cost research of the Bureau of Labor Statistics. The proper emphasis of Prescott and Ohanian (2014Feb) is on the low productivity increases from 2011 to 2013. Labor productivity increased 3.3 percent in 2010 and 3.1 percent in 2009. There is much stronger yet not sustained performance in 2010 with productivity growing 3.3 percent because of growth of output of 3.2 percent with decline of hours worked of 0.1 percent. Productivity growth of 3.1 percent in 2009 consists of decline of output by 4.3 percent while hours worked collapsed 7.2 percent, which is not a desirable route to progress. The expansion phase of the economic cycle concentrated in one year, 2010, with underperformance in the remainder of the expansion from 2011 to 2013 of productivity growth at average 0.8 percent per year.

Table II-6, US, Productivity and Costs, Annual Percentage Changes 2007-2013

	2013	2012	2011	2010	2009	2008	2007
Productivity	0.5	1.5	0.5	3.3	3.1	0.8	1.6
Output	2.2	3.7	2.5	3.2	-4.3	-1.3	2.3
Hours Worked	1.7	2.2	2.0	-0.1	-7.2	-2.0	0.7
Employment	1.8	2.0	1.5	-1.2	-5.7	-1.5	0.9
Average Weekly Hours Worked	-0.1	0.2	0.5	1.1	-1.6	-0.6	-0.2
Hourly Compensation	1.6	2.6	2.5	2.1	1.1	2.7	4.3
Consumer Price Inflation	1.5	2.1	3.2	1.6	-0.4	3.8	2.8
Real Hourly Compensation	0.1	0.5	-0.7	0.4	1.5	-1.1	1.4
Non-labor Payments	3.7	6.5	4.0	7.3	-0.1	-0.4	3.4
Output per Job	0.3	1.7	1.0	4.4	1.5	0.2	1.4

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

Productivity growth can bring about prosperity while productivity regression can jeopardize progress. 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. Table II-7 provides average growth rates of indicators in the research of productivity and growth of the US Bureau of Labor Statistics. There is dramatic decline of productivity growth in the whole cycle from 2.2 percent per year on average from 1947 to 2013 to 1.6 percent per year on average from 2007 to 2013. There is profound drop in the average rate of output growth from 3.4 percent on average from 1947 to 2013 to 1.0 percent from 2007 to 2013. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth on trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,107.4 billion than actual $15,932.9 billion. There are about two trillion dollars of GDP less than on trend, explaining the 29.1 million unemployed or underemployed equivalent to actual unemployment of 17.8 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,932.9 billion in IVQ2013 or 6.2 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. Real hourly compensation collapsed from average 1.6 percent per year from 1947 to 2013 to 0.3 percent per year from 2007 to 2013. The antithesis of secular stagnation is cyclical slow growth. The policy design deserves consideration of Kydland and Prescott (1977) and Prescott and Ohanian (2014Feb) to induce productivity growth for future progress. Hourly compensation increased at the average yearly rate of 5.1 percent from 1947 to 2013 and consumer price inflation at 3.6 percent with real hourly compensation increasing at the average yearly rate of 1.6 percent. Hourly compensation increased at the average yearly rate of 2.1 percent from 2007 to 2013 while consumer price inflation increased at 2.0 percent with real hourly compensation changing at the average yearly rate of 0.0 percent. While hours worked increased at the average yearly rate of 1.2 percent from 1947 to 2013, hours worked fell 3.7 percent from 2007 to 2013. While employment increased at the average yearly rate of 1.4 percent from 1947 to 2013, employment fell 3.3 percent from 2007 to 2013.

Table II-7, US, Productivity and Costs, Average Annual Percentage Changes 2007-2013 and 1947-2013

	Average Annual Percentage Rate 2007-2013	Average Annual Percentage Rate 1947-2013
Productivity	1.6	2.2
Output	1.0	3.4
Hours	-3.7*	1.2
Employment	-3.3*	1.4
Average Weekly Hours	-0.5*	-15.0*
Hourly Compensation	2.1	5.1
Consumer Price Inflation	2.0	3.6
Real Hourly Compensation	0.0	1.6
Unit Non-labor Payments	2.5	3.4
Output per Job	1.5	2.0

* Percentage Change

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

Unit labor costs increased sharply during the Great Inflation from the late 1960s to 1981 as shown by sharper slope in Chart II-8. Unit labor costs continued to increase but at a lower rate because of cyclic factors and not because of imaginary secular stagnation.

Chart II-8, US, Nonfarm Business, Unit Labor Costs, 1947-2013, Index 2005=100

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

Real hourly compensation increased at relatively high rates after 1947 to the early 1970s but reached a plateau that lasted until the early 1990s, as shown in Chart VA-22. There were rapid increases until the global recession. Cyclic factors and not alleged secular stagnation explain the interruption of increases in real hourly compensation.

Chart II-9, US, Nonfarm Business, Real Hourly Compensation, 1947-2013, Index 2005=100

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

IIA Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth. The valuable report on Financial Accounts of the United States formerly Flow of Funds Accounts of the United States provided by the Board of Governors of the Federal Reserve System (http://www.federalreserve.gov/releases/z1/Current/ http://www.federalreserve.gov/apps/fof/) is rich in important information and analysis. Table IIA-1, updated in this blog for every new quarterly release, shows the balance sheet of US households combined with nonprofit organizations in 2007, 2011, 2012 and IVQ2013. The data show the strong shock to US wealth during the contraction. Assets fell from $82.1 trillion in 2007 to $78.3 trillion in 2011 even after nine consecutive quarters of growth beginning in IIIQ2009 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html

http://wwwdev.nber.org/cycles/cyclesmain.html), for decline of $3.8 trillion or 4.6 percent. Assets stood at $84.5 trillion in 2012 for gain of $2.4 trillion relative to $82.1 trillion in 2007 or increase by 2.9 percent. Assets increased to $94.4 trillion in IVQ2013 by $12.3 trillion relative to 2007 or 15.0 percent. Liabilities declined from $14.4 trillion in 2007 to $13.6 trillion in 2011 or by $825.2 billion equivalent to decline by 5.6 percent. Liabilities declined $796.0 billion or 5.5 percent from 2007 to 2012 and increased 0.2 percent from 2011 to 2012. Liabilities fell from $14.4 trillion in 2007 to $13.8 trillion in IVQ2013, by $638.3 billion or decline of 4.2 percent. Net worth shrank from $67.8 trillion in 2007 to $64.8 trillion in 2011, that is, $3.0 trillion equivalent to decline of 4.4 percent. Net worth increased from $67,752.8 billion in 2007 to $80,663.7 billion in IVQ2013 by $12,910.9 billion or 19.1 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 233.049 in Dec 2013 (http://www.bls.gov/cpi/data.htm) or 11.0 percent. Net worth adjusted by CPI inflation increased 7.3 percent from 2007 to IVQ2013. Nonfinancial assets fell $729.2 billion from $28,199.9 billion in 2007 to $27,470.7 billion in IVQ2013 or 2.6 percent. There was brutal decline from 2007 to IVQ2013 of $1.381 trillion in real estate assets or by 5.9 percent. The National Association of Realtors estimated that the gains in net worth in homes by Americans were about $4 trillion between 2000 and 2005 (quoted in Pelaez and Pelaez, The Global Recession Risk (2007), 224-5).

Table IIA-1, US, Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars Outstanding End of Period, NSA

	2007	2011	2012	IVQ2013
Assets	82,146.7	78,331.9	84,460.8	94,419.3
Nonfinancial	28,199.9	23,264.0	25,003.8	27,470.7
Real Estate	23,377.0	18,109.4	19,708.3	21,996.4
Durable Goods	4,476.0	4,726.4	4,848.0	5,010.8
Financial	53,946.8	55,067.9	59,457.0	66,948.5
Deposits	7,564.0	8,738.5	9,201.1	9,447.6
Credit Market	5,036.7	5,489.9	5,640.7	5,652.1
Mutual Fund Shares	4,682.9	4,449.2	5,279.4	6,692.1
Equities Corporate	10,118.3	9,049.9	10,337.7	13,864.8
Equity Noncorporate	8,932.7	7,384.9	8,073.5	8,724.5
Pension	15,305.0	17,120.8	18,088.8	19,600.7
Liabilities	14,393.9	13,568.7	13,597.9	13,755.6
Home Mortgages	10,610.3	9,678.1	9,435.2	9,371.6
Consumer Credit	2,616.6	2,757.0	2,924.3	3,098.6
Net Worth	67,752.8	64,763.3	70,862.8	80,663.7

Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2014. Flow of funds, balance sheets and integrated macroeconomic accounts: fourth quarter 2013. Washington, DC, Federal Reserve System, Mar 6.

The explanation of the sharp contraction of household wealth 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 skills of the relationship banker convert 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 the 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 the US. 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.

Table IIA-2 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 95.4 percent in the 10-city composite of the Case-Shiller home price index and 81.0 percent in the 20-city composite between Dec 2000 and Dec 2005. Prices rose around 100 percent from Dec 2000 to Dec 2006, increasing 95.8 percent for the 10-city composite and 82.2 percent for the 20-city composite. House prices rose 37.6 percent between Dec 2003 and Dec 2005 for the 10-city composite and 34.2 percent for the 20-city composite propelled by low fed funds rates of 1.0 percent between Jun 2003 and Jun 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Jun 2004 until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Dec 2003 and Dec 2006, the 10-city index gained 37.9 percent and the 20-city index increased 35.1 percent. House prices have fallen from Dec 2006 to Dec 2013 by 19.0 percent for the 10-city composite and 18.5 percent for the 20-city composite. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Dec 2013, house prices increased 13.6 percent in the 10-city composite and increased 13.4 percent in the 20-city composite. Table I-4 also shows that house prices increased 58.6 percent between Dec 2000 and Dec 2013 for the 10-city composite and increased 48.5 percent for the 20-city composite. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The 10-city composite fell 20.4 percent from the peak in Jun 2006 to Dec 2013 and the 20-city composite fell 24.6 percent from the peak in Jul 2006 to Dec 2013. The final part of Table IIA-3 provides average annual percentage rates of growth of the house price indexes of Standard & Poor’s Case-Shiller. The average annual growth rate between Dec 1987 and Dec 2013 for the 10-city composite was 3.7 percent. Data for the 20-city composite are available only beginning in Jan 2000. House prices accelerated in the 1990s with the average rate of the 10-city composite of 5.0 percent between Dec 1992 and Dec 2000 while the average rate for the period Dec 1987 to Dec 2000 was 3.8 percent. Although the global recession affecting the US between IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly above 30 percent, the average annual growth rate of the 10-city composite between Dec 2000 and Dec 2013 was 3.6 percent while the rate of the 20-city composite was 3.1 percent.

Table IIA-2, US, Percentage Changes of Standard & Poor’s Case-Shiller Home Price Indices, Not Seasonally Adjusted, ∆%

	10-City Composite	20-City Composite
∆% Dec 2000 to Dec 2003	42.0	34.9
∆% Dec 2000 to Dec 2005	95.4	81.0
∆% Dec 2003 to Dec 2005	37.6	34.2
∆% Dec 2000 to Dec 2006	95.8	82.2
∆% Dec 2003 to Dec 2006	37.9	35.1
∆% Dec 2005 to Dec 2013	-18.8	-18.0
∆% Dec 2006 to Dec 2013	-19.0	-18.5
∆% Dec 2009 to Dec 2013	13.9	13.6
∆% Dec 2010 to Dec 2013	15.4	16.4
∆% Dec 2011 to Dec 2013	20.4	21.3
∆% Dec 2012 to Dec 2013	13.6	13.4
∆% Dec 2000 to Dec 2013	58.6	48.5
∆% Peak Jun 2006 Dec 2013	-20.4
∆% Peak Jul 2006 Dec 2013		-24.6
Average ∆% Dec 1987-Dec 2013	3.7	NA
Average ∆% Dec 1987-Dec 2000	3.8	NA
Average ∆% Dec 1992-Dec 2000	5.0	NA
Average ∆% Dec 2000-Dec 2013	3.6	3.1

Source: http://us.spindices.com/index-family/real-estate/sp-case-shiller

Monthly house prices increased sharply from Feb to Dec 2013 for both the 10- and 20-city composites. In Dec 2013, the seasonally adjusted 10-city composite increased 0.8 percent and the 20-city increased 0.8 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city decreased 0.1 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. With the exception of Feb through Apr 2012, house prices seasonally adjusted declined in every month for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table IIA-3. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. Without seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Aug 2011 but fell in every month from Sep 2011 to Feb 2012. The not seasonally adjusted index registers decline in Mar 2012 of 0.1 percent for the 10-city composite and is flat for the 20-city composite. Not seasonally adjusted house prices increased 1.4 percent in Apr 2012 and at high monthly percentage rates until Sep 2012. House prices not seasonally adjusted stalled from Oct 2012 to Jan 2013 and surged from Feb to Sep 2013, decelerating in Oct-Dec 2013. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

Table IIA-3, US, Monthly Percentage Change of S&P Case-Shiller Home Price Indices, Seasonally Adjusted and Not Seasonally Adjusted, ∆%

	10-City Composite SA	10-City Composite NSA	20-City Composite SA	20-City Composite NSA
Dec 2013	0.8	0.0	0.8	-0.1
Nov	0.9	-0.1	0.9	-0.1
Oct	1.0	0.2	1.1	0.2
Sep	1.0	0.7	1.0	0.7
Aug	1.0	1.3	1.0	1.3
Jul	0.7	1.9	0.7	1.8
Jun	1.0	2.2	0.9	2.2
May	1.0	2.5	0.9	2.5
Apr	1.7	2.6	1.7	2.6
Mar	1.8	1.3	1.8	1.3
Feb	1.3	0.3	1.2	0.2
Jan	0.7	0.0	0.8	0.0
Dec 2012	1.0	0.2	1.0	0.2
Nov	0.7	-0.3	0.8	-0.2
Oct	0.7	-0.2	0.7	-0.1
Sep	0.5	0.3	0.6	0.3
Aug	0.5	0.8	0.6	0.9
Jul	0.3	1.5	0.4	1.6
Jun	0.9	2.1	1.0	2.3
May	0.7	2.2	0.8	2.4
Apr	0.5	1.4	0.5	1.4
Mar	0.5	-0.1	0.5	0.0
Feb	0.0	-0.9	0.1	-0.8
Jan	-0.3	-1.1	-0.2	-1.0
Dec 2011	-0.4	-1.2	-0.4	-1.1
Nov	-0.5	-1.4	-0.5	-1.3
Oct	-0.5	-1.3	-0.5	-1.4
Sep	-0.4	-0.6	-0.4	-0.7
Aug	-0.3	0.1	-0.3	0.1
Jul	-0.2	0.9	-0.2	1.0
Jun	-0.1	1.0	-0.1	1.2
May	-0.3	1.0	-0.4	1.0
Apr	-0.2	0.6	-0.2	0.6
Mar	-0.4	-1.0	-0.5	-1.0
Feb	-0.4	-1.3	-0.3	-1.2
Jan	-0.3	-1.1	-0.3	-1.1
Dec 2010	-0.2	-0.9	-0.2	-1.0

Source: http://us.spindices.com/index-family/real-estate/sp-case-shiller

Table IIA-4 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2008 and 2009. Total assets fell $10.7 trillion or 13.0 percent from 2007 to 2008 and $9.2 trillion or 11.2 percent to 2009. Net worth fell $10.6 trillion from 2007 to 2008 or 15.6 percent and $8.8 trillion to 2009 or 13.0 percent. Subsidies to housing prolonged over decades together with interest rates at 1.0 percent from Jun 2003 to Jun 2004 inflated valuations of real estate and risk financial assets such as equities. The increase of fed funds rates by 25 basis points until 5.25 percent in Jun 2006 reversed carry trades through exotic vehicles such as subprime adjustable rate mortgages (ARM) and world financial markets. 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).

Table IIA-4, Difference of Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars from 2007 to 2008 and 2009

	2007	2008	Change to 2008	2009	Change to 2009
A	82,146.7	71,457.1	-10,689.6	72,972.2	-9,174.5
Non FIN	28,199.9	24,798.2	-3,401.7	23,664.2	-4,535.7
RE	23,377.0	19,845.8	-3,531.2	18,686.7	-4,690.3
FIN	53,946.8	46,658.9	-7.287.9	49,308.0	-4.638.8
LIAB	14,393.9	14,277.3	-116.6	14,052.0	-343.9
NW	67,752.8	57,179.8	-10,573.0	58,920.2	-8,832.6

A: Assets; Non FIN: Nonfinancial Assets; RE: Real Estate; FIN: Financial Assets; LIAB: Liabilities; NW: Net Worth

The apparent improvement in Table IIA-4A is mostly because of increases in valuations of risk financial assets by the carry trade from zero interest rates to leveraged exposures in risk financial assets such as stocks, high-yield bonds, emerging markets, commodities and so on. Zero interest rates also act to increase net worth by reducing debt or liabilities. The net worth of households has become an instrument of unconventional monetary policy by zero interest rates in the theory that increases in net worth increase consumption that accounts for 68.2 percent of GDP in IVQ2013 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IVQ2013, real estate fell in value by $1380.6 billion and financial assets increased $13,001.7 billion for net gain of real estate and financial assets of $11,621.1 billion, explaining most of the increase in net worth of $12,910.9 billion obtained by adding the decrease in liabilities of $638.3 billion to the increase of assets of $12,272.6 billion. Net worth increased from $67,752.8 billion in 2007 to $80,663.7 billion in IVQ2013 by $12,910.9 billion or 19.1percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 233.049 in Dec 2013 (http://www.bls.gov/cpi/data.htm) or 11.0 percent. Net worth adjusted by CPI inflation increased 7.3 percent from 2007 to IVQ2013. There are multiple complaints that unconventional monetary policy concentrates income on wealthier individuals because of their holdings of financial assets while the middle class has gained less because of fewer holdings of financial assets and higher share of real estate in family wealth. There is nothing new in these arguments. Interest rate ceilings on deposits and loans have been commonly used. The Banking Act of 1933 imposed prohibition of payment of interest on demand deposits and ceilings on interest rates on time deposits. These measures were justified by arguments that the banking panic of the 1930s was caused by competitive rates on bank deposits that led banks to engage in high-risk loans (Friedman, 1970, 18; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 74-5). The objective of policy was to prevent unsound loans in banks. Savings and loan institutions complained of unfair competition from commercial banks that led to continuing controls with the objective of directing savings toward residential construction. Friedman (1970, 15) argues that controls were passive during periods when rates implied on demand deposit were zero or lower and when Regulation Q ceilings on time deposits were above market rates on time deposits. The Great Inflation or stagflation of the 1960s and 1970s changed the relevance of Regulation Q. Friedman (1970, 26-7) predicted the future:

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

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

“These are the people who have the fewest alternative ways to invest their limited assets and are least sophisticated about the alternatives.” US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp4q13_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth on trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,107.4 billion than actual $15,932.9 billion. There are about two trillion dollars of GDP less than on trend, explaining the 29.1 million unemployed or underemployed equivalent to actual unemployment of 17.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,932.9 billion in IVQ2013 or 6.2 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation.

Table IIA-4A, US, Difference of Balance Sheet of Households and Nonprofit Organizations Billions of Dollars from 2007 to 2011 and IVQ2013

	Value 2007	Change to 2011	Change to 2012	Change to IVQ2013
Assets	82,146.7	-3,814.8	2,314.1	12,272.6
Nonfinancial	28,272.8	-4,935.9	-3,196.1	-729.2
Real Estate	23,449.8	-5,267.6	-3,668.7	-1,380.6
Financial	54,018.1	1,121.1	5,510.2	13,001.7
Liabilities	14,371.1	-825.2	-796.0	-638.3
Net Worth	67,990.3	-2,289.5	3,111.0	12,910.9

Net Worth = Assets – Liabilities

Source: Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System.

The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and from IVQ1979) to IQ1987 and from IVQ2007 to IIIQ2012 is provided in Table IIA-5. The data reveal the following facts for the cycles in the 1980s:

IVQ1979 to IIQ1987. Net worth increased 96.8 percent from IVQ1979 to IIQ1987, the all items CPI index increased 47.9 percent from 76.7 in Dec 1979 to 113.5 in Jun 1987 and real net worth increased 33.1 percent.
IQ1980 to IVQ1985. Net worth increased 65.4 percent, the all items CPI index increased 36.5 percent from 80.1 in Mar 1980 to 109.3 in Dec 1985 and real net worth increased 21.2 percent.
IVQ1979 to IVQ1985. Net worth increased 69.1 percent, the all items CPI index increased 42.5 percent from 76.7 in Dec 1979 to 109.3 in Dec 1985 and real net worth increased 18.7 percent.
IQ1980 to IIQ1987. Net worth increased 92.6 percent, the all items CPI index increased 41.7 percent from 80.1 in Mar 1980 to 113.5 in Jun 1987 and real net worth increased 35.9 percent.

There is disastrous performance in the current economic cycle:

IVQ2007 to IVQ2013. Net worth increased 19.1 percent, the all items CPI increased 11.0 percent from 210.036 in Dec 2007 to 233.049 in Dec 2013 and real or inflation adjusted net worth increased 7.3 percent.

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. 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 18 quarters from IVQ2009 to IVQ2013. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IVQ2013 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp4q13_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth on trend in the entire cycle from IVQ2007 to IV2013 would have accumulated to 20.3 percent. GDP in IVQ2013 would be $18,040.3 billion if the US had grown at trend, which is higher by $2,107.4 billion than actual $15,932.9 billion. There are about two trillion dollars of GDP less than on trend, explaining the 29.1 million unemployed or underemployed equivalent to actual unemployment of 17.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/03/rules-discretionary-authorities-and.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html). US GDP grew from $14,996.1 billion in IVQ2007 in constant dollars to $15,932.9 billion in IVQ2013 or 6.2 percent at the average annual equivalent rate of 1.0 percent. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation.

Table IIA-5, Net Worth of Households and Nonprofit Organizations in Billions of Dollars, IVQ1979 to IVQ1985 and IVQ2007 to IVQ2012

Period IQ1980 to IVQ1985
Net Worth of Households and Nonprofit Organizations USD Millions
IVQ1979 IQ1980	9,041.9 9,240.6
IVQ1985 IIIQ1986 IVQ1986 IQ1987 IIQ1987	15,285.4 16,295.1 16,846.5 17,509.9 17,795.9
∆ USD Billions IVQ1985 IIQ1987 IQ1980-IVQ1985 IQ1980-IIIQ1986 IQ1980-IVQ1986 IQ1980-IQ1987 IQ1980-IIQ1987	+6,243.5 ∆%69.1 R∆%18.7 +8,754.0 ∆%96.8 R∆%33.1 +6,044.8 ∆%65.4 R∆%21.2 +7,054.5 ∆%76.3 R∆%28.2 +7,605.9 ∆%82.3 R∆%32.2 +8,269.3 ∆%89.5 R∆%35.4 +8,555.3 ∆%92.6 R∆%35.9
Period IVQ2007 to IQ2013
Net Worth of Households and Nonprofit Organizations USD Millions
IVQ2007	67,752.8
IVQ2013	80,663.7
∆ USD Billions	+12,910.9 ∆%19.1 R∆%7.3

Net Worth = Assets – Liabilities. R∆% real percentage change or adjusted for CPI percentage change.

Chart IIA-1 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ2007 to IIIQ2013. There is remarkable stop and go behavior in this series with two sharp declines and two standstills in the 18 quarters of expansion of the economy beginning in IIIQ2009. The increase in net worth of households and nonprofit organizations is the result of increases in valuations of risk financial assets and compressed liabilities resulting from zero interest rates. Wealth of households and nonprofits organization increased 7.3 percent from IVQ2007 to IVQ2013 when adjusting for consumer price inflation.

Chart IIA-1, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ2007 to IVQ2013

Chart IIA-2 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1979 to IIQ1987. There are changes in the rates of growth of wealth suggested by the changing slopes but there is smooth upward trend. There was significant financial turmoil during the 1980s. Benston and Kaufman (1997, 139) find that there was failure of 1150 US commercial and savings banks between 1983 and 1990, or about 8 percent of the industry in 1980, which is nearly twice more than between the establishment of the Federal Deposit Insurance Corporation in 1934 through 1983. More than 900 savings and loans associations, representing 25 percent of the industry, were closed, merged or placed in conservatorships (see Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 74-7). The Financial Institutions Reform, Recovery and Enforcement Act of 1989 (FIRREA) created the Resolution Trust Corporation (RTC) and the Savings Association Insurance Fund (SAIF) that received $150 billion of taxpayer funds to resolve insolvent savings and loans. The GDP of the US in 1989 was $5657.7 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.65 percent of GDP in a year. US GDP in 2013 is estimated at $16,797.5 billion, such that the bailout would be equivalent to cost to taxpayers of about $445.1 billion in current GDP terms. A major difference with the Troubled Asset Relief Program (TARP) for private-sector banks is that most of the costs were recovered with interest gains whereas in the case of savings and loans there was no recovery. Money center banks were under extraordinary pressure from the default of sovereign debt by various emerging nations that represented a large share of their net worth (see Pelaez 1986). Net worth of households and nonprofit organizations increased 96.8 percent from IVQ1979 to IIQ1987 and 33.1 percent when adjusting for consumer price inflation. Net worth of households and nonprofit organizations increased 92.6 percent from IQ1980 to IIQ1987 and 35.9 percent when adjusting for consumer price inflation.

Chart IIA-2, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1979 to IIQ1987

Chart IIA-3 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1945 at $767.3 billion to IVQ2013 at $80,663.7 billion or increase of 10,412.7 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 234.049 in Dec 2013 or increase of 1,180.5 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 68 years with inflation-adjusted increase from $42.159 in dollars of 1945 to $346.123 in IVQ2013 or 720.9 percent. In a simple formula: {[($80,663.7/$767.3)/(234.049/18.2)-1]100 = 720.9%}. Wealth of households and nonprofit organizations increased from $767.3 billion at year-end 1945 to $80,663.7 billion at the end of 2013 or 10,412.7 percent. The consumer price index increased from 18.2 in Dec 1945 to 233.049 in Dec 2013 or 1180.5 percent. Net wealth of households and nonprofit organizations in dollars of 1945 increased from $42.159 in 1945 to $346.123 in 2013 or 720.9 percent at the average yearly rate of 3.1 percent. US real GDP grew at the average rate of 2.9 percent from 1945 to 2013 (http://www.bea.gov/iTable/index_nipa.cfm). The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIQ2009 caused sharp contraction of net worth of US households and nonprofit organizations. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 67 years when US GDP grew at 2.3 percent on average in the eighteen quarters between IIIQ2009 and IVQ2013 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). US GDP was $228.2 billion in 1945 and net worth of households and nonprofit organizations $767.3 for ratio of wealth to GDP of 3.36. The ratio of net worth of households and nonprofits of $67,752.3 billion in 2007 to GDP of $14,480.3 billion was 4.68. The ratio of net worth of households and nonprofits of $80,663.7 billion in 2013 to GDP of 16,797.5 billion was 4.80.

Chart IIA-3, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1945 to IVQ2013

Table IIA-6 provides percentage changes of nonfinancial domestic sector debt. Households increased debt by 10.0 percent in 2006 but have been reducing their debt continuously with the exception of growth at 1.4 percent in IIQ2012 but renewed decrease at 1.65 percent in IIIQ2012 and increase at 2.1 percent in IVQ2012. Household debt declined at 0.6 percent in IQ2013 and increased at 0.8 percent in IIQ2013 and at 3.0 percent in IVQ2013. Household debt increased at 0.4 percent in IVQ2013 with personal consumption expenditures contributing 1.73 percentage points to growth of GDP in IVQ2013 (http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html). Financial repression by zero fed funds rates or negative interest rates is intended to increase debt and reduce savings. Business had not been as exuberant in acquiring debt and has been increasing debt benefitting from historically low costs while increasing cash holdings to around $2 trillion by swelling undistributed profits because of the uncertainty of capital budgeting. The key to growth and hiring consists in creating the incentives for business to invest and hire. States and local government were forced into increasing debt by the decline in revenues but began to contract in IQ2011, decreasing again from IQ2011 to IVQ2011, increasing at 2.9 percent in IIQ2012 and decreasing at 0.2 percent in IIIQ2012 and 3.8 percent in IVQ2012. State and local government increased debt at 2.4 percent in IQ2013 and at 1.1 percent in IIQ2013. State and local government decreased debt at 3.9 percent in IIIQ2013 and at 4.9 percent in IVQ2013. Opposite behavior is found for the federal government that has been rapidly accumulating debt but without success in the self-assigned goal of promoting economic growth. Financial repression constitutes seigniorage of government debt (http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-financial.html http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-monetary.html).

Table IIA-6, US, Percentage Change of Nonfinancial Domestic Sector Debt

	Total	Households	Business	State & Local Govern-ment	Federal
IVQ2013	5.4	0.4	7.1	-4.9	11.6
IIIQ2013	3.8	3.0	8.4	-3.9	1.5
IIQ2013	3.5	0.8	7.7	1.1	2.5
IQ2013	4.4	-0.6	4.9	2.4	10.1
IVQ2012	6.2	2.1	9.2	-3.8	10.4
IIIQ2012	3.0	-1.5	5.0	-0.2	7.1
IIQ2012	5.3	1.4	5.0	2.9	11.0
IQ2012	4.7	-1.1	4.4	0.4	13.5
2013	4.3	0.9	7.2	-1.3	6.5
2012	4.9	0.2	7.2	-0.2	10.9
2011	3.7	-1.4	6.0	-1.7	11.4
2010	4.1	-2.6	1.5	2.3	20.2
2009	3.1	-1.7	-2.2	4.0	22.7
2008	6.0	0.1	6.3	0.6	24.2
2007	8.6	6.8	13.6	5.5	4.9
2006	8.7	10.0	10.9	3.9	3.9
2005	9.3	11.2	9.0	5.8	7.0
2004	9.3	11.1	6.8	11.4	9.0
2003	8.0	11.8	2.2	8.3	10.9

Table IIA-7 provides wealth of US households and nonprofit organizations since 2003 in billions of current dollars at the end of period, NSA. Wealth fell from $67,753 billion in 2007 to $58,920 billion in 2009 or 13.0 percent and to $64,763 billion in 2011 or 4.4 percent. Wealth increased 19.1 percent from 2007 to IVQ2013, increasing 7.3 percent after adjustment for inflation, primarily because of bloating financial assets while nonfinancial assets declined.

Table IIA-7, US, Net Worth of Households and Nonprofit Organizations, Billions of Dollars, Amounts Outstanding at End of Period, NSA

Quarter	Net Worth
IVQ2013	80,664
IIIQ2013	77,710
IIQ2013	75,434
IQ2013	74,088
IVQ2012	70,863
IIIQ2012	69,525
IIQ2012	67,266
IQ2012	67,220
2013	80,664
2012	70,863
2011	64,763
2010	63,354
2009	58,920
2008	57,180
2007	67,753
2006	67,331
2005	62,538
2004	56,515
2003	49,426

IIB United States Services. Chart II-1 of the US Census Bureau of the Department of Commerce provides the quarterly service report SA from IIIQ2003 to IVQ2013. Services revenue contracted during the recession from IVQ2007 (December) to IIQ2009 (June) (http://wwwdev.nber.org/cycles/cyclesmain.html) but there appears to be continuing growth especially for professional, scientific and technical services with steeper slope from IVQ2010 through IVQQ2013.

Chart II-1, US, Quarterly Revenue for Selected Services, SA $ Billions

Source: US Census Bureau

Total revenues of information services not seasonally adjusted in millions of current dollars are shown in Table II-1 from IVQ2003, when they become available, to IVQ2013. The row below current values provides percentage change in the quarter from the quarter a year earlier. Growth rates were robust before the global recession in the range from 3.7 percent in IVQ2004 to 5.5 percent in IQ2005. Percentage changes were negative in all quarters in 2009 with the largest losses in the first three quarters. Growth was milder in the expansion phase than before the global recession. As with most indicators of the US, growth was robust in the final three quarters of 2010 and initial quarters of 2011. Growth rates recovered to 5.6 percent in IVQ2012, 4.8 percent in IQ2013 and 4.4 percent in IIQ2013. Growth continued with 5.3 percent in IIIQ2013 relative to a year earlier and 5.5 percent in IVQ2013.

Table II-1, US, Information Services Revenue Not Seasonally Adjusted, Millions of Dollars, 2003-2013

Year	1st Quarter	2nd Quarter	3rd Quarter	4th Quarter
2003	NA	NA	NA	237,399
2004	223,675	233,241	232,983	246,201
∆%	NA	NA	NA	3.7
2005	236,033	244,136	244,711	255,856
∆%	5.5	4.7	5.0	3.9
2006	245,182	254,735	255,745	271,401
∆%	3.9	4.3	4.5	6.1
2007	257,973	265,739	267,325	281,304
∆%	5.2	4.3	4.5	3.6
2008	270,223	277,650	277,603	282,873
∆%	4.7	4.5	3.8	0.6
2009	261,921	266,862	265,511	280,665
∆%	-3.1	-3.9	-4.4	-0.8
2010	267,597	274,785	276,049	291,794
∆%	2.2	3.0	4.0	4.0
2011	277,416	289,110	288,779	305,253
∆%	3.7	5.2	4.6	4.6
2012	291,952	300,081	298,950	322,308
∆%	5.2	3.8	3.5	5.6
2013	306,040	313,234	314,646	340,037
∆%	4.8	4.4	5.3	5.5

Source: US Census Bureau

Chart II-2 provides total revenue of information services not seasonally adjusted from IVQ2013 to IVQ2013 in current millions of dollars not seasonally adjusted. Oscillating growth was strong before the drop of the global recession. Growth recovered in recent quarters relative to the same quarter a year earlier with strong increase in IVQ2012 followed by increases in all quarters in 2013.

Chart II-2, Quarterly Revenue for Information Services Not Seasonally Adjusted, Millions of Dollars 2003-2013

Source: US Census Bureau

A similar pattern is provided by Chart II-3 with quarterly total revenue of information services in current millions of dollars adjusted for seasonality. There is the same hump of the global recession followed by resumption of growth.

Chart II-3, Quarterly Revenue for Information Services Seasonally Adjusted, Millions of Dollars 2003-2013

Source: US Census Bureau

Table II-2 provides total revenue of financial services and insurance in current million dollars not seasonally adjusted from IIIQ2009, when data first become available, to IVQ2013. The row below values provides percentage changes in a quarter relative to the same quarter a year earlier. Percentage changes were negative until 2012 with 3.0 percent in IQ2012, 1.3 percent in IIQ2012, 5.4 percent in IIIQ2012 and 3.8 percent in IVQ2012. Revenue increased 1.1 percent in IQ2013 relative to a year earlier and increased 3.9 percent in IIQ2013. Revenue growth moderated to 0.4 percent in IIIQ2013 and recovered to 5.6 percent in IVQ2013.

Table II-2, US, Financial Services and Insurance Total Revenue Not Seasonally Adjusted, Millions of Dollars, 2003-2013

Year	1st Quarter	2nd Quarter	3rd Quarter	4th Quarter
2009	NA	NA	844,210	842,875
2010	831,167	831,769	831,075	832,059
∆%	NA	NA	-1.6	-1.3
2011	830,076	828,539	814,472	820,554
∆%	-0.1	-0.4	-2.0	-1.4
2012	854,954	839,140	858,619	851,997
∆%	3.0	1.3	5.4	3.8
2013	864,479	871,496	862,024	900,090
∆%	1.1	3.9	0.4	5.6

Source: US Census Bureau

Chart II-4 provides total quarterly revenue of financial services and insurance from IIIQ2009, when data first become available, to IVQ2013. Total revenue of financial services and insurance contracted 1.4 percent between IVQ2009 and IVQ2011 and grew 3.8 percent between IVQ2011 and IVQ2012. Revenue increased 1.1 percent in IQ2013 relative to a year earlier and 3.9 percent in IIQ2013. Revenue growth slowed to 0.4 percent in IIIQ2013 and jumped to 5.6 percent in IVQ2013.

Chart II-4, Total Quarterly Revenue for Financial Services and Insurance Not Seasonally Adjusted, Millions of Dollars 2003-2013

Source: US Census Bureau