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. The civilian noninstitutional population or those in condition to work increased from 228.815 million in 2006 to 253.538 million in 2016 or by 24.723 million. Hiring has not recovered precession levels while needs of hiring multiplied because of growth of population by more than 24 million.

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2016

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, 2001-2016

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 6.9 percent and 2.6 percent in 2003 followed by strong rebounds of 5.8 percent in 2004 and 4.7 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.0 in 2007, 12.0 in 2008 and 15.7 percent in 2009. On a yearly basis, nonfarm hiring grew 5.3 percent in 2010 relative to 2009, 3.3 percent in 2011, 4.1 percent in 2012 and 3.8 percent in 2013. Nonfarm hiring grew 8.0 percent in 2014 and increased 5.8 percent in 2015. Nonfarm hiring grew 1.1 percent in 2016. The relatively large length of 27 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, 2002-2016

Year	Annual ∆%
2002	-6.9
2003	-2.6
2004	5.8
2005	4.7
2006	0.6
2007	-2.0
2008	-12.0
2009	-15.7
2010	5.3
2011	3.3
2012	4.1
2013	3.8
2014	8.0
2015	5.8
2016	1.1

Source: US Bureau of Labor Statistics

Total private hiring (HP) 12-month percentage changes of annual data are in Chart I-3. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2016.

Chart I-3, US, Total Nonfarm Hiring Level, Annual, ∆%, 2001-2016

Source: Bureau of Labor Statistics

Total private hiring (HP) annual data are in Chart I-5. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2016.

Chart I-5, US, Total Private Hiring, Annual, 2001-2016

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, Annual, 2001-2016

Source: Bureau of Labor Statistics

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are in Table I-3 for the month of Dec in the years from 2001 to 2017. Hiring numbers are in thousands. There is recovery in HNF from 4005 thousand (or 4.1 million) in Jan 2009 to 3735 thousand in Jan 2010, 3772 thousand in Jan 2011, 4140 thousand in Jan 2012, 4277 thousand in Jan 2013, 4465 thousand in Jan 2014, 4833 thousand in Jan 2015, 4922 thousand in Jan 2016, and 5236 in Jan 2017 for cumulative gain of 30.7 percent at average rate of 3.4 percent per year. HP rose from 3707 thousand in Jan 2009 to 3470 thousand in Jan 2010, 3520 thousand in Jan 2011, 3885 thousand in Jan 2012, 4023 thousand in Jan 2013, 4209 thousand in Jan 2014, 4542 in Jan 2015, 4603 thousand in Jan 2016, and 4942 thousand in Jan 2017 for cumulative gain of 33.3 percent at the average yearly rate of 3.7 percent. HNF has increased from 5049 thousand in Jan 2006 to 5236 thousand in Jan 2017 or by 3.7 percent. HP has increased from 4776 thousand in Jan 2006 to 4942 thousand in Jan 2017 or by 3.5 percent. The civilian noninstitutional population of the US, or those in condition of working, rose from 227.553 million in Jan 2006 to 254.082 million in Jan 2017, by 26.529 million or 11.7 percent. There is often ignored ugly fact that hiring increased by around 3.7 percent while population available for working increased around 11.7 percent. Private hiring of 59.206 million in 2006 was equivalent to 25.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 58.385 million in 2016 or 23.0 percent of the civilian noninstitutional population of 253.538 million in 2016. The percentage of hiring in civilian noninstitutional population of 25.9 percent in 2006 would correspond to 65.666 million of hiring in 2016 (0.259x253.538), which would be 7.281 million higher than actual 58.385 million in 2016. 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. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.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	5862	4.5	5540	5.0
2002 Jan	4903	3.8	4619	4.3
2003 Jan	4983	3.9	4688	4.4
2004 Jan	4771	3.7	4525	4.2
2005 Jan	5109	3.9	4816	4.4
2006 Jan	5049	3.8	4776	4.3
2007 Jan	5066	3.7	4751	4.2
2008 Jan	4705	3.5	4425	3.9
2009 Jan	4005	3.0	3707	3.4
2010 Jan	3735	2.9	3470	3.3
2011 Jan	3772	2.9	3520	3.3
2012 Jan	4140	3.2	3885	3.6
2013 Jan	4277	3.2	4023	3.6
2014 Jan	4465	3.3	4209	3.7
2015 Jan	4833	3.5	4542	3.9
2016 Jan	4922	3.5	4603	3.9
2017 Jan	5236	3.7	4942	4.1

Source: Bureau of Labor Statistics

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2017. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4815 in May 2010 until it surpassed it with 5006 in Jun 2011 but declined to 3097 in Dec 2012. Nonfarm hiring fell to 2997 in Dec 2011 from 3814 in Nov 2011 and to revised 3627 in Feb 2012, increasing to 4182 in Mar 2012, 3097 in Dec 2012 and 4277 in Jan 2013 and declining to 3692 in Feb 2013. Nonfarm hires not seasonally adjusted increased to 4239 in Nov 2013 and 3233 in Dec 2013. Nonfarm hires reached 3729 in Dec 2014, 4057 in Dec 2015 and 3905 in Dec 2016. Nonfarm hires reached 5236 in Jan 2017. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Oct 2011 was 4239 thousand, increasing to revised 4419 thousand in Feb 2012, or 4.2 percent, moving to 4360 in Dec 2012 for cumulative increase of 3.0 percent from 4234 in Dec 2011 and 4500 in Dec 2013 for increase of 3.2 percent relative to 4360 in Dec 2012. The number of hires not seasonally adjusted was 5006 in Jun 2011, falling to 2997 in Dec 2011 but increasing to 4140 in Jan 2012 and declining to 3097 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 40.1 percent from 5006 in Jun 2011 to 2997 in Dec 2011 and fell 39.9 percent from 5151 in Jun 2012 to 3097 in Dec 2012 in a yearly-repeated seasonal pattern. The number of nonfarm hires not seasonally adjusted fell from 5102 in Jun 2013 to 3233 in Dec 2013, or decline of 36.6 percent, showing strong seasonality. The number of nonfarm hires not seasonally adjusted fell from 5520 in Jun 2014 to 3729 in Dec 2014 or 32.4 percent. The level of nonfarm hires fell from 5885 in Jun 2015 to 4057 in Dec 2015 or 31.1 percent. The level of nonfarm hires not seasonally adjusted fell from 5922 in Jun 2016 to 3905 in Dec 2016 or 34.1 percent.

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2017 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 stabilizing to 3.3 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 3.8 in Jun 2011 to 2.2 in Dec 2011, climbing to 3.8 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 2.3 in Dec 2013. The NSA rate of nonfarm hiring fell from 3.9 in Jun 2014 to 2.6 in Dec 2014. The NSA rate fell from 4.1 in Jun 2015 to 2.8 in Dec 2015. The NSA rate fell from 4.1 in Jun 2016 to 2.7 in Dec 2016. Rates of nonfarm hiring NSA were in the range of 2.7 (Dec) to 4.4 (Jun) in 2006. The rate of nonfarm hiring SA stood at 3.7 in Jan 2017 and at 3.7 NSA.

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2017

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 4043 thousand in Sep 2011 to 3933 in Dec 2011 or by 2.7 percent, decreasing to 4014 in Jan 2012 or decline by 0.7 percent relative to the level in Sep 2011. Private hiring fell to 3959 in Sep 2012 or lower by 2.1 percent relative to Sep 2011, moving to 4063 in Dec 2012 for increase of 1.2 percent relative to 4014 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4626 in Jun 2011 to 2817 in Dec 2011 or by 39.1 percent, reaching 3885 in Jan 2012 or decline of 16.0 percent relative to Jun 2011 and moving to 2918 in Dec 2012 or 38.5 percent lower relative to 4745 in Jun 2012. Hires not seasonally adjusted fell from 4743 in Jun 2013 to 3068 in Dec 2013. The level of private hiring NSA fell from 5101 in Jun 2014 to 3530 in Dec 2014 or 30.8 percent. The level of private hiring fell from 5452 in Jun 2015 to 3828 in Dec 2015 or 29.8 percent. The level of private hiring not seasonally adjusted fell from 5456 in Jun 2016 to 3711 in Dec 2016 or 32.0 percent. Companies reduce hiring in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5614 in Jun 2006 to 3579 in Dec 2006 or by 36.2 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. Hiring in the nonfarm sector (HNF) has declined from 63.491 million in 2006 to 62.719 million in 2016 or by 0.772 million while hiring in the private sector (HP) has declined from 59.206 million in 2006 to 58.385 million in 2016 or by 0.821 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.1 in 2005 to 43.5 in 2016 and in the private sector (RHP) from 52.8 in 2005 to 47.8 in 2016. Hiring has not recovered as in previous cyclical expansions because of the low rate of economic growth in the current cyclical expansion. The civilian noninstitutional population or those in condition to work increased from 228.815 million in 2006 to 253.538 million in 2016 or by 24.723 million. Hiring has not recovered prerecession levels while needs of hiring multiplied because of growth of population by more than 24 million. Private hiring of 59.206 million in 2006 was equivalent to 25.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 58.385 million in 2016 or 23.0 percent of the civilian noninstitutional population of 253.538 million in 2016. The percentage of hiring in civilian noninstitutional population of 25.9 percent in 2006 would correspond to 65.666 million of hiring in 2016 (0.259x253.538), which would be 7.281 million higher than actual 58.385 million in 2016.

Chart I-8, US, Total Private Hiring Month SA 2001-2017

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 3.5 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 3.9 in Aug 2012, 2.6 in Dec 2012 and 2.6 in Dec 2013. The NSA rate increased to 3.0 in Dec 2015 and 3.1 in Dec

2016. The rate NSA reached 4.1 in Jan 2017

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2017

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 Dec from 2001 to 2017. The final column provides annual TNF LD for the years from 2001 to 2016. Nonfarm job openings (TNF JOB) increased from a peak of 4717 in Jan 2007 to 5582 in Jan 2016 or by 18.3 percent while the rate increased from 3.4 to 3.8. This was mediocre performance because the civilian noninstitutional population of the US, or those in condition of working rose from 227.553 million in Jan 2006 to 254.082 million in Jan 2017, by 26.529 million or 11.7 percent. Nonfarm layoffs and discharges (TNF LD) rose from 2103 in Jan 2006 to 3209 in Jan 2009 or by 52.6 percent. The annual data show layoffs and discharges rising from 20.9 million in 2006 to 26.6 million in 2009 or by 27.3 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. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions.

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	5569	4.1	2940	24271
Jan 2002	3930	3.0	2504	22719
Jan 2003	3953	3.0	2601	23420
Jan 2004	3585	2.7	2508	22584
Jan 2005	3775	2.8	2478	22151
Jan 2006	4412	3.2	2103	20856
Jan 2007	4717	3.4	2187	21997
Jan 2008	4366	3.1	2303	23969
Jan 2009	2868	2.1	3209	26557
Jan 2010	2744	2.1	2343	21703
Jan 2011	3036	2.3	2161	20756
Jan 2012	3769	2.8	2059	20942
Jan 2013	3796	2.8	1965	19888
Jan 2014	3957	2.8	2138	20398
Jan 2015	5068	3.5	2151	20954
Jan 2016	5679	3.9	2141	19911
Jan 2017	5582	3.8	2065

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

Source: Bureau of Labor Statistics

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 3220 seasonally adjusted in Apr 2010 with 3570 seasonally adjusted in Dec 2012, which is higher by 10.9 percent relative to Apr 2010 but higher by 1.4 percent relative to 3521 in Nov 2012 and lower by 6.8 percent than 3831 in Mar 2012. Nonfarm job openings increased from 3570 in Dec 2012 to 3742 in Dec 2013 or by 4.8 percent and to 4795 in Dec 2014 or 28.1 percent relative to 2013. The high of job openings not seasonally adjusted was 3408 in Apr 2010 that was surpassed by 3647 in Jul 2011, increasing to 3906 in Oct 2012 but declining to 3213 in Dec 2012 and increasing to 3371 in Dec 2013. The level of job opening NSA increased to 4961 in Dec 2015. The level of job opening NSA increased to 5116 in Dec 2016, reaching 5582 in Jan 2017. The level of job openings not seasonally adjusted fell to 3213 in Dec 2012 or by 17.5 percent relative to 3893 in Apr 2012. There is here again the strong seasonality of year-end labor data. Job openings fell from 4209 in Apr 2013 to 3371 in Dec 2013 and from 4844 in Apr 2014 to 4398 in Dec 2014, showing strong seasonal effects. The level of nonfarm job openings decreased from 5933 in Apr 2015 to 4961 in Dec 2015 or by 16.4 percent. The level of nonfarm job openings NSA fell from 5951 in Apr 2016 to 5116 in Dec 2016 or 14.0 percent. Nonfarm job openings (TNF JOB) increased from a peak of 4717 in Jan 2007 to 5582 in Jan 2016 or by 18.3 percent while the rate increased from 3.4 to 3.8. This was mediocre performance because the civilian noninstitutional population of the US, or those in condition of working rose from 227.553 million in Jan 2006 to 254.082 million in Jan 2017, by 26.529 million or 11.7 percent.

Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions.

Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. 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 IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Feb 1919 to Feb 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 144.4892 in Feb 2017. The actual index NSA in Feb 2017 is 103.4436, which is 28.4 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Feb 2017. Using trend growth of 2.0 percent per year, the index would increase to 130.9602 in Feb 2017. The output of manufacturing at 103.4436 in Feb 2017 is 21.0 percent below trend under this alternative calculation.

Chart I-10, US Job Openings, Thousands NSA, 2001-2017

Source: US Bureau of Labor Statistics

The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted increased from 2.2 in Jan 2011 to 2.5 in Dec 2011, 2.6 in Dec 2012, 2.7 in Dec 2013 and 3.3 in Dec 2014. The rate seasonally adjusted stood at 3.6 in Dec 2015 and 3.7 in Dec 2016. The rate seasonally adjusted reached 3.7 in Jan 2017. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 3.0 in Apr 2013, easing to 2.4 in Dec 2013. The rate of job openings NSA fell from 3.3 in Jul 2007 to 1.6 in Nov-Dec 2009, recovering to 3.3 in Dec 2015. The rate of job opening NSA stood at 3.4 in Dec 2016, reaching 3.8 in Jan 2017.

Chart I-11, US, Rate of Job Openings, NSA, 2001-2017

Source: US Bureau of Labor Statistics

Total separations are in Chart I-12. Separations are lower in 2012-17 than before the global recession but hiring has not recovered.

Chart I-12, US, Total Nonfarm Separations, Month Thousands SA, 2001-2017

Source: US Bureau of Labor Statistics

Chart I-13 provides annual total separations. Separations fell sharply during the global recession but hiring has not recovered relative to population growth.

Chart I-13, US, Total Separations, Annual, Thousands, 2001-2016

Source: US Bureau of Labor Statistics

Table I-5 provides total nonfarm total separations from 2001 to 2016. Separations fell from 61.3 million in 2006 to 47.6 million in 2010 or by 13.6 million and 48.2 million in 2011 or by 13.1 million. Total separations increased from 48.2 million in 2011 to 51.9 million in 2013 or by 3.7 million and to 55.6 million in 2014 or by 7.4 million relative to 2011. Total separations increased to 59.3 million in 2015 or by 11.1 million relative to 2011. Total separations increased to 60.419 million in 2016 or 12.2 million relative to 2011.

Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2016

Year	Annual Thousands
2001	64560
2002	58942
2003	56961
2004	58224
2005	60633
2006	61284
2007	60984
2008	58209
2009	51358
2010	47649
2011	48214
2012	50131
2013	51932
2014	55587
2015	59275
2016	60419

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. 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. Growth rates have been unusually low in the expansion of the current economic cycle.

Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly Thousands SA, 2001-2017

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. There is mild increase into 2014-2015 followed by decline in 2016.

Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2016

Source: US Bureau of Labor Statistics

Annual layoff and discharges are in Table I-6. Layoffs and discharges increased sharply from 20.856 million in 2006 to 26.557 million in 2009 or 27.3 percent. Layoff and discharges fell to 19.888 million in 2013 or 25.1 percent relative to 2009 and increased to 20.398 million in 2014 or 2.6 percent relative to 2013. Layoffs and discharges increased to 20.954 million in 2015 or 2.7 percent relative to 2014. Layoffs and discharges fell to 19.911 in 2016 or 5.0 percent relative to 2015.

Table I-6, US, Total Nonfarm Layoffs and Discharges, Thousands, 2001-2016

Year	Annual Thousands
2001	24271
2002	22719
2003	23420
2004	22584
2005	22151
2006	20856
2007	21997
2008	23969
2009	26557
2010	21703
2011	20756
2012	20942
2013	19888
2014	20398
2015	20954
2016	19911

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 adjusted has risen from 8.2 percent in 2006 to 9.5 percent in Feb 2017.

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

	U1	U2	U3	U4	U5	U6
2017
Feb	1.9	2.6	4.9	5.3	6.0	9.5
Jan	2.0	2.7	5.1	5.5	6.2	10.1
2016
Dec	1.9	2.3	4.5	4.8	5.5	9.1
Nov	1.8	2.1	4.4	4.8	5.6	9.0
Oct	1.9	2.1	4.7	5.0	5.7	9.2
Sep	1.9	2.2	4.8	5.1	5.9	9.3
Aug	1.8	2.4	5.0	5.3	6.0	9.7
Jul	1.9	2.4	5.1	5.5	6.3	10.1
Jun	1.9	2.3	5.1	5.4	6.1	9.9
May	2.0	2.1	4.5	4.9	5.6	9.4
Apr	2.2	2.3	4.7	5.0	5.7	9.3
Mar	2.3	2.6	5.1	5.5	6.1	9.9
Feb	2.2	2.7	5.2	5.6	6.3	10.1
Jan	2.1	2.7	5.3	5.7	6.5	10.5
2015
Dec	2.1	2.4	4.8	5.2	5.9	9.8
Nov	2.1	2.3	4.8	5.2	5.8	9.6
Oct	2.1	2.3	4.8	5.2	6.0	9.5
Sep	2.0	2.2	4.9	5.3	6.0	9.6
Aug	2.1	2.5	5.2	5.6	6.3	10.3
Jul	2.0	2.7	5.6	6.0	6.7	10.7
Jun	2.1	2.5	5.5	5.8	6.6	10.8
May	2.4	2.5	5.3	5.6	6.4	10.4
Apr	2.4	2.5	5.1	5.5	6.4	10.4
Mar	2.6	2.9	5.6	6.0	6.8	11.0
Feb	2.7	3.0	5.8	6.3	7.1	11.4
Jan	2.7	3.1	6.1	6.5	7.4	12.0
2014
Dec	2.5	2.8	5.4	5.8	6.7	11.1
Nov	2.7	2.7	5.5	5.9	6.8	11.0
Oct	2.7	2.6	5.5	6.0	6.8	11.1
Sep	2.7	2.7	5.7	6.2	7.1	11.3
Aug	2.8	3.0	6.3	6.7	7.5	12.0
Jul	2.8	3.1	6.5	7.0	7.8	12.6
Jun	2.8	3.0	6.3	6.7	7.5	12.4
May	3.1	3.0	6.1	6.5	7.3	11.7
Apr	3.3	3.2	5.9	6.3	7.2	11.8
Mar	3.7	3.7	6.8	7.2	8.1	12.8
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
2016	2.0	2.3	4.9	5.2	5.9	9.6
2015	2.3	2.6	5.3	5.7	6.4	10.4
2014	3.0	3.1	6.2	6.6	7.5	12.0
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

Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.1 percent in Aug 2011 to 16.4 percent in Sep 2011 and then fell to 14.5 percent in Mar 2012, reaching 9.2 percent in Feb 2017. 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 24.2 million in job stress of unemployment/underemployment in Dec 2016, not seasonally adjusted, corresponding to 14.4 percent of the labor force (https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html).

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

	U1	U2	U3	U4	U5	U6
Feb 2017	1.8	2.3	4.7	5.0	5.7	9.2
Jan	1.9	2.3	4.8	5.1	5.8	9.4
Dec 2016	1.9	2.3	4.7	5.0	5.7	9.2
Nov	1.8	2.2	4.6	5.0	5.8	9.3
Oct	2.0	2.3	4.8	5.1	5.9	9.5
Sep	2.0	2.5	4.9	5.3	6.0	9.7
Aug	1.9	2.4	4.9	5.3	5.9	9.7
Jul	2.0	2.3	4.9	5.2	6.0	9.7
Jun	2.0	2.4	4.9	5.2	6.0	9.6
May	1.9	2.3	4.7	5.0	5.7	9.7
Apr	2.1	2.4	5.0	5.3	6.0	9.7
Mar	2.1	2.4	5.0	5.4	6.0	9.8
Feb	2.1	2.4	4.9	5.3	6.0	9.8
Jan	2.0	2.3	4.9	5.3	6.2	9.9
Dec 2015	2.1	2.4	5.0	5.4	6.1	9.9
Nov	2.1	2.5	5.0	5.4	6.1	9.9
Oct	2.1	2.5	5.0	5.4	6.2	9.8
Sep	2.1	2.4	5.0	5.4	6.2	10.0
Aug	2.2	2.5	5.1	5.5	6.2	10.2
Jul	2.1	2.6	5.2	5.6	6.4	10.3
Jun	2.2	2.6	5.3	5.6	6.4	10.5
May	2.4	2.7	5.5	5.8	6.6	10.7
Apr	2.3	2.6	5.4	5.9	6.7	10.8
Mar	2.4	2.7	5.4	5.9	6.7	10.9
Feb	2.5	2.7	5.5	6.0	6.8	11.0
Jan	2.7	2.7	5.7	6.1	7.0	11.3
Dec 2014	2.6	2.8	5.6	6.0	6.9	11.2
Nov	2.7	2.9	5.8	6.2	7.0	11.4
Oct	2.8	2.8	5.7	6.2	7.0	11.5
Sep	2.8	2.9	5.9	6.3	7.3	11.8
Aug	2.9	3.0	6.2	6.6	7.4	12.0
July	2.9	3.1	6.2	6.6	7.5	12.2
Jun	3.0	3.1	6.1	6.5	7.3	12.0
May	3.1	3.2	6.3	6.7	7.5	12.1
Apr	3.2	3.3	6.2	6.7	7.5	12.3
Mar	3.4	3.5	6.7	7.1	7.9	12.6
Feb	3.4	3.5	6.7	7.1	8.0	12.6
Jan	3.4	3.5	6.6	7.1	8.1	12.7
Dec 2013	3.6	3.5	6.7	7.3	8.1	13.1
Nov	3.7	3.7	6.9	7.4	8.2	13.1
Oct	3.8	4.0	7.2	7.7	8.5	13.6
Sep	3.8	3.8	7.2	7.7	8.6	13.7
Aug	3.9	3.7	7.3	7.8	8.6	13.6
Jul	3.9	3.8	7.3	7.9	8.7	13.8
Jun	4.0	3.9	7.5	8.1	9.0	14.2
May	4.1	3.9	7.5	8.0	8.8	13.8
Apr	4.1	4.1	7.6	8.1	8.9	14.0
Mar	4.1	4.1	7.5	8.0	8.9	13.8
Feb	4.1	4.2	7.7	8.2	9.2	14.4
Jan	4.2	4.3	8.0	8.5	9.4	14.5
Dec 2012	4.3	4.2	7.9	8.5	9.4	14.4
Nov	4.2	4.2	7.7	8.3	9.2	14.4
Oct	4.4	4.2	7.8	8.3	9.2	14.4
Sep	4.4	4.2	7.8	8.3	9.3	14.8
Aug	4.5	4.4	8.1	8.6	9.6	14.6
Jul	4.5	4.6	8.2	8.7	9.6	14.8
Jun	4.7	4.6	8.2	8.7	9.6	14.8
May	4.6	4.5	8.2	8.7	9.6	14.7
Apr	4.6	4.4	8.2	8.8	9.6	14.6
Mar	4.6	4.5	8.2	8.7	9.6	14.5
Feb	4.7	4.6	8.3	8.9	9.8	15.0
Jan	4.8	4.7	8.3	8.9	9.9	15.2
Dec 2011	4.9	4.9	8.5	9.1	10.0	15.2
Nov	5.0	5.0	8.6	9.3	10.1	15.5
Oct	5.1	5.1	8.8	9.4	10.3	15.8
Sep	5.4	5.2	9.0	9.7	10.5	16.4
Aug	5.4	5.2	9.0	9.6	10.5	16.1
Jul	5.3	5.3	9.0	9.6	10.6	15.9
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	5.3	5.5	9.0	9.6	10.6	16.0
Jan	5.5	5.5	9.1	9.7	10.8	16.2

Source: US Bureau of Labor Statistics

Chart I-16 provides U6 on a monthly basis from 2001 to 2017. 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, 2001-2017

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 relative stability in 2013-2017.

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

Thousands, Month SA 2001-2017

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.

Seasonally adjusted part-time for economic reasons. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.166 million in Sep 2011 to 7.775 million in Mar 2012, seasonally adjusted, or decline of 1.391 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.671 million in Sep 2012 for increase of 697,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.203 million in Oct 2012 or by 468,000 again in one month, further declining to 8.166 million in Nov 2012 for another major one-month decline of 37,000 and 7.943 million in Dec 2012 or fewer 223,000 in just one month. The number employed part-time for economic reasons increased to 8.074 million in Jan 2013 or 131,000 more than in Dec 2012 and to 8.119 million in Feb 2013, declining to 7.864 million in May 2013 but increasing to 8.096 million in Jun 2013. The number employed part-time for economic reasons fell to 7.804 million in Aug 2013 for decline of 279,000 in one month from 8.083 million in Jul 2013. The number employed part-time for economic reasons increased 207,000 from 7.804 million in Aug 2013 to 8.011 million in Sep 2013. The number part-time for economic reasons rose to 7.995 million in Oct 2013, falling by 265,000 to 7.730 million in Nov 2013. The number part-time for economic reasons increased to 7.792 million in Dec 2013, decreasing to 7.298 million in Jan 2014. The number employed part-time for economic reasons fell from 7.298 million in Jan 2014 to 7.262 million in Feb 2014. The number employed part-time for economic reasons increased to 7.403 million in Mar 2014 and 7.466 million in Apr 2014. The number employed part-time for economic reasons fell to 7.170 million in May 2014, increasing to 7.469 million in Jun 2014. The level employed part-time for economic reasons fell to 7.430 million in Jul 2014 and 7.173 million in Aug 2014. The level employed part-time for economic reasons fell to 7.123 million in Sep 2014, 7.033 million in Oct 2014 and 6.870 million in Nov 2014. The level employed part-time for economic reasons fell to 6.819 million in Dec 2014, increasing to 6.836 million in Jan 2015. The level employed part-time for economic reasons fell to 6.664 million in Feb 2015, increasing to 6.646 million in Mar 2015. The level of employed part-time for economic reasons fell to 6.563 million in Apr 2015, increasing to 6.544 million in May 2015. The level employed part-time for economic reasons fell to 6.463 million in Jun 2015 and 6.292 million in Jul 2015. The level employed part-time for economic reasons increased to 6.438 million in Aug 2015, declining to 6.031 million in Sep 2015. The level employed part-time for economic reasons fell to 5.734 million in Oct 2015, increasing to 6.113 million in Nov 2015. The level of part-time for economic reasons fell to 6.057 million in Dec 2015, decreasing to 6.035 million in Jan 2016. The level employed part-time for economic reasons decreased to 6.019 million in Feb 2016 and increased to 6.120 million in Mar 2016. The level employed part-time for economic reasons fell to 5.970 million in Apr 2016 and increased to 6.409 million in May 2016. The level of part-time for economic reasons fell to 5.820 million in Jun 2016, increasing to 5.936 million in Jul 2016. The level of part-time for economic reasons increased to 6.027 million in Aug 2016, decreasing to 5.874 million in Sep 2016. The level of part-time for economic reasons reached 5.850 million in Oct 2016, decreasing to 5.659 million in Nov 2016 and 5.598 million in Dec 2016. The level of part-time for economic reasons increased to 5.840 million in Jan 2017, decreasing to 5.704 million in Feb 2017.
Seasonally adjusted full-time. The number employed full-time increased from 112.923 million in Oct 2011 to 115.024 million in Mar 2012 or 2.101 million but then fell to 114.233 million in May 2012 or 0.791 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.736 million in Aug 2012 to 115.570 million in Oct 2012 or increase of 0.834 million full-time jobs in two months and further to 115.724 million in Jan 2013 or increase of 0.988 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.674 million in Feb 2013, increasing to 116.247 million in May 2013 and 116.126 million in Jun 2013. Then number of full-time jobs increased to 116.155 million in Jul 2013, 116.435 million in Aug 2013 and 116.895 million in Sep 2013. The number of full-time jobs fell to 116.362 million in Oct 2013 and increased to 117.046 in Nov 2013. The level of full-time jobs increased to 117.351 million in Dec 2013, increasing to 117.504 million in Jan 2014 and 117.747 million in Feb 2014. The level of employment full-time increased to 117.941 million in Mar 2014 and 118.516 million in Apr 2014. The level of full-time employment reached 118.816 million in May 2014, decreasing to 118.238 million in Jun 2014. The level of full-time jobs increased to 118.450 million in Jul 2014 and 118.707 million in Aug 2014. The level of full-time jobs increased to 119.338 million in Sep 2014, 119.763 million in Oct 2014 and 119.645 million in Nov 2014. The level of full-time jobs increased to 120.075 million in Dec 2014 and 120.575 million in Jan 2015. The level of full-time jobs increased to 120.776 million in Feb 2015 and 120.963 million in Mar 2015. The level of full-time jobs decreased to 120.870 million in Apr 2015, increasing to 121.523 million in May 2015 and decreasing to 121.066 million in Jun 2015. The level of full-time jobs increased to 121.629 million in Jul 2015 and increased to 121.934 million in Aug 2015, decreasing to 121.829 million in Sep 2015. The level of full-time jobs increased to 122.071 million in Oct 2015 and increased to 122.110 million in Nov 2015. The level of full-time jobs increased to 122.700 million in Dec 2015 and 123.116 million in Jan 2016. The level of full-time jobs increased to 123.210 million in Feb 2016 and increased to 123.513 million in Mar 2016. The level of full-time jobs decreased to 123.259 million in Apr 2016 and 123.232 million in May 2016. The level of full-time jobs increased to 123.618 million in Jun 2016, increasing to 123.888 million in Jul 2016. The level of full-time jobs increased to 124.256 million in Aug 2016, decreasing to 124.253 million in Sep 2016 and 124.190 million in Oct 2016. The level of full-time jobs increased to 124.213 million in Nov 2016 and 124.248 million in Dec 2016. The level of full-time jobs increased to 124.705 million in Jan 2017, increasing to 125.031 million in Feb 2017. Adjustments of benchmark and seasonality-factors at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2016/02/fluctuating-risk-financial-assets-in.html http://cmpassocregulationblog.blogspot.com/2015/02/job-creation-and-monetary-policy-twenty.html http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html).
Not seasonally adjusted part-time for economic reasons. 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 fewer 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 level of part-time for economic reasons increased to 7.455 million in Mar 2014 and fell to 7.243 million in Apr 2014. The number of part-time for economic reasons fell to 6.960 million in May 2014, increasing to 7.805 million in Jun 2014. The level of part-time for economic reasons fell to 7.665 million in Jul 2014 and 7.083 million in Aug 2014. The level of part-time for economic reasons fell to 6.711 million in Sep 2014 and increased to 6.787 million in Oct 2014. The level of part-time for economic reasons reached 6.713 million in Nov 2014 and 6.970 million in Dec 2014, increasing to 7.269 million in Jan 2015. The level of part-time for economic reasons fell to 6.772 million in Feb 2015 and 6.672 million in Mar 2015, falling to 6.356 million in Apr 2015. The level of part-time for economic reasons increased to 6.363 million in May 2015 and to 6.776 million in Jun 2015, decreasing to 6.511 million in Jul 2015. The level of part-time for economic reasons fell to 6.361 million in Aug 2015 and 5.693 million in Sep 2015. The level of part-time for economic reasons fell to 5.536 million in Oct 2015, increasing to 5.967 million in Nov 2015. The level of part-time for economic reasons increased to 6.179 million in Dec 2015, increasing to 6.406 million in Jan 2016. The level of part-time for economic reasons decreased to 6.106 million in Feb 2016 and increased to 6.138 million in Mar 2016. The level of part-time for economic reasons decreased to 5.771 million in Apr 2016 and increased to 6.238 million in May 2016. The level of part-time for economic reasons decreased to 6.119 million in Jun 2016, increasing to 6.157 million in Jul 2016. The level of part-time for economic reasons fell to 5.963 million in Aug 2016, decreasing to 5.550 million in Sep 2016. The level of part-time for economic reasons increased to 5.648 million in Oct 2016, decreasing to 5.518 million in Nov 2016 and increasing to 5.707 million in Dec 2016. The level of part-time for economic reasons increased to 6.226 million in Jan 2017, decreasing to 5.773 million in Feb 2017.
Not seasonally adjusted full-time. 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 116.323 million in Feb 2014. The level of full-time jobs increased to 116.985 in Mar 2014 and 118.073 million in Apr 2014. The number of full-time jobs increased to 119.179 million in May 2014, increasing to 119.472 million in Jun 2014. The level of full-time jobs increased to 119.900 million in Jul 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 2017 is 123.610 million, which is higher by 0.391 million relative to the peak of 123.219 million in Jul 2007.
Loss of full-time jobs. 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 254.246 million in Feb 2017 or by 22.288 million (http://www.bls.gov/data/). The number with full-time jobs in Feb 2017 is 123.610 million, which is higher by 0.391 million relative to the peak of 123.219 million in Jul 2007. The ratio of full-time jobs of 123.219 million in Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 135.005 million full-time jobs with population of 254.246 million in Feb 2017 (0.531 x 254.246) or 11.395 million fewer full-time jobs relative to actual 123.610 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 20 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 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. 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 IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Feb 1919 to Feb 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 144.4892 in Feb 2017. The actual index NSA in Feb 2017 is 103.4436, which is 28.4 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Feb 2017. Using trend growth of 2.0 percent per year, the index would increase to 130.9602 in Feb 2017. The output of manufacturing at 103.4436 in Feb 2017 is 21.0 percent below trend under this alternative calculation.

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

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Feb 2017	5.704	125.031
Jan 2017	5,840	124.705
Dec 2016	5,598	124.248
Nov 2016	5,659	124.213
Oct 2016	5,850	124.190
Sep 2016	5,874	124.253
Aug 2016	6,027	124.256
Jul 2016	5,936	123.888
Jun 2016	5,820	123.618
May 2016	6,409	123.232
Apr 2016	5,970	123.259
Mar 2016	6,120	123.513
Feb 2016	6,019	123.210
Jan 2016	6,035	123.116
Dec 2015	6,057	122.700
Nov 2015	6,113	122.110
Oct 2015	5,734	122.071
Sep 2015	6,031	121.829
Aug 2015	6,438	121.934
Jul 2015	6,292	121.629
Jun 2015	6,463	121.066
May 2015	6,544	121.523
Apr 2015	6,563	120.870
Mar 2015	6,646	120.963
Feb 2015	6,664	120.776
Jan 2015	6,836	120.575
Dec 2014	6,819	120.075
Nov 2014	6,870	119.645
Oct 2014	7,033	119.763
Sep 2014	7,123	119.338
Aug 2014	7,173	118.707
Jul 2014	7,430	118.450
Jun 2014	7,469	118.238
May 2014	7,170	118.816
Apr 2014	7,466	118.516
Mar 2014	7,403	117.941
Feb 2014	7,262	117.747
Jan 2014	7,298	117.504
Dec 2013	7,792	117.351
Nov 2013	7,730	117.046
Oct 2013	7,995	116.362
Sep 2013	8,011	116.895
Aug 2013	7,804	116.435
Jul 2013	8,083	116.155
Jun 2013	8,096	116.126
May 2013	7,864	116.247
Apr 2013	7,936	116.044
Mar 2013	7,658	115.785
Feb 2013	8,119	115.674
Jan 2013	8,074	115.724
Dec 2012	7,943	115.791
Nov 2012	8,166	115.655
Oct 2012	8,203	115.570
Sep 2012	8,671	115.252
Aug 2012	7,974	114.736
Jul 2012	8,082	114.575
Jun 2012	8,072	114.749
May 2012	8,101	114.233
Apr 2012	7,913	114.371
Mar 2012	7,775	115.024
Feb 2012	8,238	114.141
Jan 2012	8,305	113.755
Dec 2011	8,171	113.774
Nov 2011	8,447	113.213
Oct 2011	8,657	112.923
Sep 2011	9,166	112.544
Aug 2011	8,788	112.723
Jul 2011	8,281	112.193
Not Seasonally Adjusted
Feb 2017	5,773	123.610
Jan 2017	6,226	123.015
Dec 2016	5,707	123.570
Nov 2016	5,518	123.960
Oct 2016	5,648	124.588
Sep 2016	5,550	124.278
Aug 2016	5,963	125.892
Jul 2016	6,157	125.507
Jun 2016	6,119	124.903
May 2016	6,238	123.548
Apr 2016	5,771	122.742
Mar 2016	6,138	122.522
Feb 2016	6,106	121.757
Jan 2016	6,406	121.411
Dec 2015	6,179	122.013
Nov 2015	5,967	121.897
Oct 2015	5,536	122.466
Sep 2015	5,693	122.303
Aug 2015	6,361	123.420
Jul 2015	6,511	123.142
Jun 2015	6,776	122.268
May 2015	6,363	121.863
Apr 2015	6,356	120.402
Mar 2015	6,672	119.981
Feb 2015	6,772	119.313
Jan 2015	7,269	118.840
Dec 2014	6,970	119.394
Nov 2014	6,713	119.441
Oct 2014	6,787	120.176
Sep 2014	6,711	119.791
Aug 2014	7,083	120.110
Jul 2014	7,665	119.900
Jun 2014	7,805	119.472
May 2014	6,960	119.179
Apr 2014	7,243	118.073
Mar 2014	7,455	116.985
Feb 2014	7,397	116.323
Jan 2014	7,771	115.774
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

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 2001-2017

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, 2001-2017

Sources: US Bureau of Labor Statistics

Chart I-20 provides the level of full-time jobs from 2001 to 2017. 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 254.246 million in Feb 2017 or by 22.288 million (http://www.bls.gov/data/). The number with full-time jobs in Feb 2017 is 123.610 million, which is higher by 0.391 million relative to the peak of 123.219 million in Jul 2007. The ratio of full-time jobs of 123.219 million in Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 135.005 million full-time jobs with population of 254.246 million in Feb 2017 (0.531 x 254.246) or 11.395 million fewer full-time jobs relative to actual 123.610 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 20 million. Mediocre GDP growth is the main culprit of the fractured US labor market.

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

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

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). This is merely another case of theory without reality with dubious policy proposals.

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, 2001-2017

Sources: US Bureau of Labor Statistics

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2017. 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, 2001-2017

Sources: US Bureau of Labor Statistics

Chart I-20B provides number of full-time jobs in the US from 1968 to 2017. 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-

2017

Sources: US Bureau of Labor Statistics

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2017. 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, 1968-2017

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-9A provides percentage change of real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Data are available for the 1930s only on a yearly basis. US GDP fell 4.7 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1982 and 4.2 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. In contrast, GDP grew 2.5 percent in 2010, 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014 and 2.6 percent in 2015. GDP grew 1.6 percent in 2016. Actual annual equivalent GDP growth in the twenty quarters from 2012 to 2016 is 2.0 percent and 1.9 percent in the four quarters ending in IVQ2016. GDP grew at 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. The forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 1.9 to 2.3 percent in 2017 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20161214.pdf) with less reliable forecast of 1.8 to 2.2 percent in 2017 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20161214.pdf). Growth of GDP in the expansion from IIIQ2009 to IIIQ2016 has been at average 2.1 percent in annual equivalent.

Table I-9A, US, Percentage Change of GDP in the 1930s, 1980s and 2000s, ∆%

Year	GDP ∆%	Year	GDP ∆%	Year	GDP ∆%
1930	-8.5	1980	-0.2	2000	4.1
1931	-6.4	1981	2.6	2001	1.0
1932	-12.9	1982	-1.9	2002	1.8
1933	-1.3	1983	4.6	2003	2.8
1934	10.8	1984	7.3	2004	3.8
1935	8.9	1985	4.2	2005	3.3
1936	12.9	1986	3.5	2006	2.7
1937	5.1	1987	3.5	2007	1.8
1938	-3.3	1988	4.2	2008	-0.3
1939	8.0	1989	3.7	2009	-2.8
1940	8.8	1990	1.9	2010	2.5
1941	17.7	1991	-0.1	2011	1.6
1942	18.9	1992	3.6	2012	2.2
1943	17.0	1993	2.7	2013	1.7
1944	8.0	1994	4.0	2014	2.4
1945	-1.0	1995	2.7	2015	2.6
1946	-11.6	1996	3.8	2016	1.6

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

Characteristics of the four cyclical contractions are in Table I-9B with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.7 percent, which is almost equal to the decline of 4.2 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

Table I-9B, US, Number of Quarters, GDP Cumulative Percentage Contraction and Average Percentage Annual Equivalent Rate in Cyclical Contractions

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	3	-2.4	-0.8
IIIQ1957 to IIQ1958	3	-3.0	-1.0
IVQ1973 to IQ1975	5	-3.1	-0.6
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.5	-0.64
IVQ2007 to IIQ2009	6	-4.2	-0.72

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

Table I-9C shows the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the thirty quarters of the current cyclical expansion from IIIQ2009 to IVQ2016. In sharp contrast, the average growth rate of GDP was:

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

The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill with annual growth of 2.5 percent in 2010 decelerating to 1.6 percent annual growth in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014, 2.6 percent in 2015 and 1.6 percent in 2016 (http://www.bea.gov/iTable/index_nipa.cfm). The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988. 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989. 4.5 percent from IQ1983 to IVQ1989, 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983. GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the twenty quarters from 2012 to 2016 accumulated to 10.6 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IVQ2016 of $16,804.1 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/20: {[($16,804.1/$15,190.3)^4/20 -1]100 = 2.0 percent}.

Table I-9C shows that GDP grew 17.1 percent in the first thirty quarters of expansion from IIIQ2009 to IVQ2016 at the annual equivalent rate of 2.1 percent.

Table I-9C, US, Number of Quarters, Cumulative Growth and Average Annual Equivalent Growth Rate in Cyclical Expansions

	Number of Quarters	Cumulative Growth ∆%	Average Annual Equivalent Growth Rate
IIIQ 1954 to IQ1957	11	12.8	4.5
First Four Quarters IIIQ1954 to IIQ1955	4	7.8
IIQ1958 to IIQ1959	5	10.0	7.9
First Four Quarters IIIQ1958 to IIQ1959	4	9.2
IIQ1975 to IVQ1976	8	8.3	4.1
First Four Quarters IIIQ1975 to IIQ1976	4	6.1
IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987 IQ1983-IIQ1987 IQ1983 to IIIQ1987 IQ1983 to IVQ1987 IQ1983 to IQ1988 IQ1983 to IIQ1988 IQ1983 to IIIQ1988 IQ1983 to IVQ1988 IQ1983 to IQ1989 IQ1983 to IIQ1989 IQ1983 to IIIQ1989 IQ1983 to IVQ1989 IQ1983 to IQ1990 IQ1983 to IIQ1990	13 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30	19.9 21.6 22.3 23.1 24.5 25.6 27.7 28.4 30.1 30.9 32.6 34.0 35.0 36.0 36.3 37.8 38.3	5.7 5.4 5.2 5.0 5.0 4.9 5.0 4.9 4.9 4.8 4.8 4.8 4.7 4.7 4.5 4.5 4.4
First Four Quarters IQ1983 to IVQ1983	4	7.8
Average First Four Quarters in Four Expansions*		7.7
IIIQ2009 to IVQ2016	30	17.1	2.1
First Four Quarters IIIQ2009 to IIQ2010		2.7

*First Four Quarters: 7.8% IIIQ1954-IIQ1955; 9.2% IIIQ1958-IIQ1959; 6.1% IIIQ1975-IQ1976; 7.8% IQ1983-IVQ1983

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

Table EMP provides the comparison between the labor market in the current whole cycle from 2007 to 2016 and the whole cycle from 1979 to 1989. In the entire cycle from 2007 to 2016, the number employed increased 5.389 million, full-time employed increased 2.670 million, part-time for economic reasons increased 1.542 million and population increased 21.491 million. The number employed increased 3.7 percent, full-time employed increased 2.2 percent, part-time for economic reasons increased 35.0 percent and population increased 9.3 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 1989, the number employed increased 18.518 million, full-time employed increased 14.715 million, part-time for economic reasons increased 1.317 million and population increased 21.530 million. In the entire cycle from 1979 to 1989, the number employed increased 18.7 percent, full-time employed increased 17.8 percent, part-time for economic reasons increased 36.8 percent and population increased 13.1 percent. 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
2014	146.305	118.718	7.213	247.947
2015	148.834	121.492	6.371	250.801
2016	151.436	123.761	5.943	253.358
∆2007-2016	5.389	2.670	1.542	21.491
∆% 2007-2016	3.7	2.2	35.0	9.3
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
∆1979-1989	18.518	14.715	1.317	21.530
∆% 1979-1989	18.7	17.8	36.8	13.1

Source: Bureau of Labor Statistics

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 Total provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment level (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would spread over long periods instead of immediately. 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), 11-16). 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 24.2 million or 14.4 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.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, Millions 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
2014	247.9	118.7	146.3	155.9	62.9	59.0	9.6
2015	250.8	121.5	148.8	157.1	62.7	59.3	8.3
2016	253.5	123.8	151.4	159.2	62.8	5	7.8
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
2/17	254.2	123.6	151.6	159.5	62.7	59.6	7.9

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, which are best explained by accentuated cyclic factors analyzed by Lazear and Spletzer (2012JHJul22).

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, Millions 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	38.8	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
2014	38.7	18.4	21.3	55.0	47.6	2.9	13.4
2015	38.6	18.8	21.2	55.0	48.6	2.5	11.6
2016	38.4	19.0	21.2	55.2	49.4	2.2	10.4
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
2/17	38.2	18.6	20.7	54.1	48.7	2.1	10.1

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

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

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. Youth employment fell from 20.041 million in 2006 to 18.442 million in 2014 or 1.599 million. Youth employment fell from 20.041 million in 2006 to 18.756 million in 2015 or 1.285 million. Youth employment fell from 20.041 million in 2006 to 18.992 million in 2016 or 1.049 million. The level of youth jobs fell from 20.129 million in Dec 2006 to 18.347 million in Dec 2014 for 1.782 million fewer youth jobs. The level of youth jobs fell from 20.129 million in Dec 2006 to 18.720 million in Dec 2015 or 1.409 million fewer jobs. Youth jobs fell from 20.129 million in Dec 2006 to 18.830 million in Dec 2016 or 1.299 million. Youth jobs fell from 19.003 million in Jan 2016 to 18.311 million in Jan 2017 or 0.692 million. 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 21.167 million in Aug 2006 to 18.972 million in Aug 2014 for 2.195 million fewer jobs. Youth employment fell from 21.914 million in Jul 2006 to 20.085 million in Jul 2014 for 1.829 million fewer youth jobs. The number of youth jobs fell from 21.268 million in Jun 2006 million to 19.421 million in Jun 2014 or 1.847 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 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 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 civilian noninstitutional population increased 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 while jobs for ages 16 to 24 years decreased 1.599 million from 19.538 million in Mar 2007 to 17.939 million in Mar 2014. The civilian noninstitutional population ages 16 to 24 years increased 1.410 million from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 while the number of youth jobs fell 1.347 million. The civilian noninstitutional population increased 1.370 million from 37.379 million in May 2007 to 38.749 million in May 2014 while the number of youth jobs decreased 1.128 million. The civilian noninstitutional population increased 1.330 million from 37.410 million in Jun 2007 to 38.740 million in Jun 2014 while the number of youth jobs fell 1.847 million from 21.268 million in Jun 2006 to 19.421 million in Jun 2014. The youth civilian noninstitutional population increased by 1.292 million from 37.443 million in Jul 2007 to 38.735 million in Jul 2014 while the number of youth jobs fell 1.632 million. The youth civilian noninstitutional population increased from 37.445 million in Aug 2007 to 38.706 million in Aug 2014 or 1.251 million while the number of youth jobs fell 1.441 million. The youth civilian noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014 while the number of youth jobs fell 1.500 million. The youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million while the number of youth jobs fell 1.072 million. The youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million while the number of youth jobs fell 1.327 million. The civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million while the number of youth jobs fell 1.782 million. The civilian noninstitutional population increased 1.971 million from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 while the number of youth jobs fell 1.091 million. The civilian noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015 while the number of youth jobs fell 0.960 million. The civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015 while the number of youth jobs fell 1.215 million. The youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015 while the number of youth jobs fell 1.165 million. The youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015 while the number of youth jobs fell 1.060 million. The youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015 while the number of youth jobs fell 1.479 million. The youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015 while the number of youth jobs fell 1.581 million. The youth civilian noninstitutional population increased 1.548 million from 37.008 million in Aug 2006 to 38.556 million in Aug 2015 while the number of youth jobs fell 1.590 million. The youth civilian noninstitutional population increased 1,498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015 while the number of youth jobs fell 1.249 million. The youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015 while the number of youth jobs fell 1.199 million. The youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015 while the number of youth jobs fell 1.418 million. The youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015 while the level of youth jobs 1.409 million. The youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016 while the level of youth jobs fell 0.844 million. The youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016 while the number of youth jobs fell 0.726 million. The youth civilian noninstitutional population increased 1,662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016 while the number of youth jobs fell 0.711 million. The youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016 while the number of youth jobs fell 0.895 million. The youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016 while the number of youth jobs fell 0.894 million. The youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016 while the number of youth jobs fell 1.301 million. The youth civilian noninstitutional population increased 1.461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016 while the number of youth jobs fell 1.458 million. The youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016 while the number of youth jobs fell 1.291 million. The youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016 while the number of youth jobs fell 0.911 million. The youth civilian noninstitutional population increased 1.320 million from 37.047 million in Oct 2006 to 38.367 million in Oct 2016 while the number of youth jobs fell 1.158 million. The youth civilian noninstitutional population increased 1.283 million from 37.076 million in Nov 2006 to 38.359 million in Nov 2016 while the number of youth jobs fell 1.102 million. The youth civilian noninstitutional population increased 1.248 million from 37.100 million in Dec 2006 to 38.348 million in Dec 2016 while the number of youth jobs fell 1.299 million. The youth civilian noninstitutional population increased 1.488 million from 36.761 million in Jan 2006 to 38.249 million in Jan 2017 while the number of youth jobs decreased 0.692 million. The youth civilian noninstitutional population increased 1.440 million from 36.791 million in Feb 2006 to 38.231 million in Feb 2017 while the number of youth jobs decreased 0.578 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

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

Year	Jan	Feb	Oct	Nov	Dec	Annual
2001	19678	19745	19694	19675	19547	20088
2002	18653	19074	19542	19397	19394	19683
2003	18811	18880	19139	19163	19136	19351
2004	18852	18841	19609	19615	19619	19630
2005	18858	18670	19794	19750	19733	19770
2006	19003	19182	19853	19903	20129	20041
2007	19407	19415	19564	19660	19361	19875
2008	18724	18546	18757	18454	18378	19202
2009	17467	17606	16671	16689	16615	17601
2010	16166	16412	16867	16946	16727	17077
2011	16512	16638	17532	17402	17234	17362
2012	16944	17150	17842	17877	17604	17834
2013	17183	17257	17976	18104	18106	18057
2014	17372	17357	18781	18576	18347	18442
2015	17912	18222	18654	18485	18720	18756
2016	18159	18456	18695	18801	18830	18992
2017	18311	18604

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2017

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

Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2017. Employment level is sharply lower in Feb 2017 relative to the peak in 2007. The following Chart I-21A relates youth employment and youth civilian noninstitutional population.

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2017 Source: US Bureau of Labor Statistics ttp://www.bls.gov/data/

Chart I-21A provides the US civilian noninstitutional population ages 16 to 24 years not seasonally adjusted from 2001 to 2017. 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 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 civilian noninstitutional population increased 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 while jobs for ages 16 to 24 years decreased 1.599 million from 19.538 million in Mar 2007 to 17.939 million in Mar 2014. The civilian noninstitutional population ages 16 to 24 years increased 1.410 million from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 while the number of youth jobs fell 1.347 million. The civilian noninstitutional population increased 1.370 million from 37.379 million in May 2007 to 38.749 million in May 2014 while the number of youth jobs decreased 1.128 million. The civilian noninstitutional population increased 1.330 million from 37.410 million in Jun 2007 to 38.740 million in Jun 2014 while the number of youth jobs fell 1.847 million from 21.268 million in Jun 2006 to 19.421 million in Jun 2014. The youth civilian noninstitutional population increased by 1.292 million from 37.443 million in Jul 2007 to 38.735 million in Jul 2014 while the number of youth jobs fell 1.632 million. The youth civilian noninstitutional population increased from 37.445 million in Aug 2007 to 38.706 million in Aug 2014 or 1.251 million while the number of youth jobs fell 1.441 million. The youth civilian noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014 while the number of youth jobs fell 1.500 million. The youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million while the number of youth jobs fell 1.072 million. The youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million while the number of youth jobs fell 1.327 million. The civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million while the number of youth jobs fell 1.782 million. The civilian noninstitutional population increased 1.971 million from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 while the number of youth jobs fell 1.091 million. The civilian noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015 while the number of youth jobs fell 0.960 million. The civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015 while the number of youth jobs fell 1.215 million. The youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015 while the number of youth jobs fell 1.165 million. The youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015 while the number of youth jobs fell 1.060 million. The youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015 while the number of youth jobs fell 1.479 million. The youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015 while the number of youth jobs fell 1.581 million. The youth civilian noninstitutional population increased 1.548 million from 37.008 million in Aug 2006 to 38.556 million in Aug 2015 while the number of youth jobs fell 1.590 million. The youth civilian noninstitutional population increased 1,498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015 while the number of youth jobs fell 1.249 million. The youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015 while the number of youth jobs fell 1.199 million. The youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015 while the number of youth jobs fell 1.418 million. The youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015 while the level of youth jobs 1.409 million. The youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016 while the level of youth jobs fell 0.844 million. The youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016 while the number of youth jobs fell 0.726 million. The youth civilian noninstitutional population increased 1,662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016 while the number of youth jobs fell 0.711 million. The youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016 while the number of youth jobs fell 0.895 million. The youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016 while the number of youth jobs fell 0.894 million. The youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016 while the number of youth jobs fell 1.301 million. The youth civilian noninstitutional population increased 1.461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016 while the number of youth jobs fell 1.458 million. The youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016 while the number of youth jobs fell 1.291 million. The youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016 while the number of youth jobs fell 0.911 million. The youth civilian noninstitutional population increased 1.320 million from 37.047 million in Oct 2006 to 38.367 million in Oct 2016 while the number of youth jobs fell 1.158 million. The youth civilian noninstitutional population increased 1.283 million from 37.076 million in Nov 2006 to 38.359 million in Nov 2016 while the number of youth jobs fell 1.102 million. The youth civilian noninstitutional population increased 1.248 million from 37.100 million in Dec 2006 to 38.348 million in Dec 2016 while the number of youth jobs fell 1.299 million. The youth civilian noninstitutional population increased 1.488 million from 36.761 million in Jan 2006 to 38.249 million in Jan 2017 while the number of youth jobs decreased 0.692 million. The youth civilian noninstitutional population increased 1.440 million from 36.791 million in Feb 2006 to 38.231 million in Feb 2017 while the number of youth jobs decreased 0.578 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.

Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2017

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 2017. 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 Jan 2014, 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. The youth civilian labor force of the US fell 0.693 million from 21.634 million in Mar 2007 to 20.941 million in Mar 2014 or 3.2 person while the youth noninstitutional civilian population 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 or 3.9 percent. The US youth civilian labor force fell 981 thousand from 21.442 million in Apr 2007 to 20.461 million in Apr 2014 while the youth civilian noninstitutional population increased from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 by 1.410 thousand or 3.8 percent. The youth civilian labor force decreased from 21.659 million in May 2007 to 21.160 million in May 2014 by 499 thousand or 2.3 percent while the youth civilian noninstitutional population increased 1.370 million from 37.739 million in May 2007 to 38.749 million in May 2007 or by 2.7 percent. The youth civilian labor force decreased from 24.128 million in Jun 2006 to 22.851 million in Jun 2014 by 1.277 million or 5.3 percent while the civilian noninstitutional population increased from 36.943 million in Jun 2006 to 38.740 million in Jun 2014 by 1.797 million or 4.9 percent. The youth civilian labor force fell from 24.664 million in Jul 2006 to 23.437 million in Jul 2014 while the civilian noninstitutional population increased from 36.989 million in Jul 2006 to 38.735 million in Jul 2014. The youth civilian labor force fell 1.818 million from 23.634 million in Aug 2006 to 21.816 million in Aug 2014 while the civilian noninstitutional population increased from 37.008 million in Aug 2006 to 38.706 million in Aug 2914 or 1.698 million. The youth civilian labor force fell 0.942 million from 21.901 million in Sep 2006 to 20.959 million in Sep 2014 while the noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014. The youth civilian labor force decreased 0.702 million from 22.105 million in Oct 2006 to 21.403 million in Oct 2014 while the youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million. The youth civilian labor force decreased 1.111 million from 22.145 million in Nov 2006 to 21.034 million in Nov 2014 while the youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million. The youth civilian labor force decreased 1.472 million from 22.136 million in Dec 2006 to 20.664 million in Dec 2014 while the youth civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million. The youth civilian labor force decreased 0.831 million from 21.368 million in Jan 2006 to 20.555 million in Jan 2015 while the youth noninstitutional population increased from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 or 1.971 million. The youth civilian labor force decreased 0.864 million from 21.615 million in Feb 2006 to 20.751 million in Feb 2015 while the youth noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015. The youth civilian labor force decreased 0.907 million from 21.507 million in Mar 2006 to 20.600 million in Mar 2015 while the civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015. The youth civilian labor force decreased 1.082 million from 21.498 million in Apr 2006 to 20.416 million in Apr 2015 while the youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015. The youth civilian labor force decreased 0.681 million from 22.023 million in May 2006 to 21.342 million in May 2015 while the youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015. The youth civilian labor force decreased 1.202 million from 24.128 million in Jun 2006 to 22.926 million in Jun 2015 while the youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015. The youth civilian labor force decreased 1.502 million from 24.664 million in Jul 2007 to 23.162 million in Jul 2015 while the youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015. The youth civilian labor force decreased 1.667 million from 23.634 million in Aug 2006 to 21.967 million in Aug 2015 while the youth civilian noninstitutional population increased 1.548 million from 37.008 in Aug 2006 to 38.556 million in Aug 2015. The youth civilian labor force decreased 1.290 million from 21.901 million in Sep 2006 to 20.611 in Sep 2015 while the youth civilian noninstitutional population increased 1.498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015. The youth civilian labor force decreased 1.228 million from 22.105 million in Oct 2006 to 20.877 million in Oct 2015 while the youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015. The youth civilian labor force decreased 1.513 million from 22.145 million in Nov 2006 to 20.632 million in Nov 2015 while the youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015. The youth civilian labor force decreased 1.301 million from 22.136 million in Dec 2006 to 20.835 million in Dec 2015 while the youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015. The youth civilian labor force decreased 1.004 million from 21.368 million in Jan 2006 to 20.364 million in Jan 2016 while the youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016. The youth civilian labor force decreased 0.930 million from 21.615 million in Feb 2006 to 20.685 million in Feb 2016 while the youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016. The youth civilian labor force decreased 0.767 million from 21.507 million in Mar 2006 to 20.740 million in Mar 2016 while the youth civilian noninstitutional population increased 1.662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016. The youth civilian labor force decreased 0.950 million from 21.498 million in Apr 2006 to 20.548 million in Apr 2016 while the youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016. The youth civilian labor force decreased 0.921 million from 22.023 million in May 2006 to 21.102 million in May 2016 while the youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016. The youth civilian labor force decreased 1.373 million from 24.128 million in Jun 2006 to 22.755 million in Jun 2016 while the youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016. The youth civilian labor force decreased 1.560 million from 24.664 million in Jul 2006 to 23.104 million in Jul 2016 while the youth civilian noninstitutional population increased 1,461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016. The youth civilian labor force decreased 1.536 million from 23.634 million in Aug 2006 to 22.098 million in Aug 2016 while the youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016. The youth civilian labor force decreased 1.082 million from 21.901 million in Sep 2006 to 20.891 million in Sep 2016 while the youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016. The youth civilian labor force decreased 1.315 million from 22.105 million in Oct 2006 to 20.790 million in Oct 2016 while the youth civilian noninstitutional population increased 1.320 million from 37.047 million in Oct 2006 to 38.367 million in Oct 2016. The youth civilian labor force decreased 1.410 million from 22.145 million in Nov 2006 to 20.735 million in Nov 2016 while the youth civilian noninstitutional population increased 1.283 million from 37.076 million in Nov 2006 to 38.359 million in Nov 2016. The youth civilian labor force decreased 1.447 million from 22.136 million in Dec 2006 to 20.689 million in Dec 2016 while the youth civilian noninstitutional population increased 1.248 million from 37.100 million in Dec 2006 to 38.348 million in Dec 2016. The youth civilian labor force decreased 0.861 million from 21.368 million in Jan 2006 to 20.507 million in Jan 2017 while the youth civilian noninstitutional population increased 1.488 million from 36.761 million in Jan 2006 to 38.249 million in Jan 2017. The youth civilian labor force decreased 0.918 million from 21.615 million in Feb 2006 to 20.697 million in Feb 2017 while the youth civilian noninstitutional population increased 1.440 million from 36.791 million in Feb 2006 to 38.231 million in Feb 2017. 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, 2001-2017

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 52.6 percent in Feb 2013. The labor force participation rate of ages 16 to 24 years fell from 58.0 in Mar 2007 to 54.0 in Mar 2014. The labor force participation rate of ages 16 to 24 years fell from 57.4 in Apr 2007 to 52.8 in Apr 2014. The labor force participation rate of ages 16 to 24 years fell from 57.9 in May 2007 to 54.6 in May 2014. The labor force participation rate of ages 16 to 24 years fell from 65.3 in Jun 2006 to 59.0 in Jun 2014. The labor force participation rate ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2014. The labor force participation rate ages 16 to 24 years fell from 63.9 in Aug 2006 to 56.4 in Aug 2014. The labor force participation rate ages 16 to 24 years fell from 59.1 in Sep 2006 to 54.2 in Sep 2014. The labor force participation rate ages 16 to 24 years fell from 59.7 in Oct 2006 to 55.4 in Oct 2014. The labor force participation rate ages 16 to 24 years fell from 59.7 in Nov 2006 to 54.5 in Nov 2014. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 53.5 in Dec 2014. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 53.1 in Jan 2015. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 53.6 in Feb 2015. The labor force participation rate ages 16 to 64 fell from 58.4 in Mar 2006 to 53.3 in Mar 2015. The labor force participation rate ages 16 to 64 fell from 58.7 in Apr 2005 to 52.8 in Apr 2006. The labor force participation rate ages 16 to 64 fell from 59.7 in May 2006 to 55.2 in May 2015. The labor force participation rate ages 16 to 64 fell from 65.3 in Jun 2006 to 59.4 in Jun 2015. The labor force participation rate ages 16 to 24 fell from 66.7 in Jul 2006 to 60.0 in Jul 2014. The labor force participation rate ages 16 to 24 fell from 63.9 in Aug 2006 to 57.0 in Aug 2015. The labor force participation rate ages 16 to 24 fell from 59.1 in Sep 2006 to 53.5 in Sep 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Oct 2006 to 54.2 in Oct 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Nov 2006 to 53.6 in Nov 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 54.2 in Dec 2015. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 52.9 in Jan 2016. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 53.7 in Feb 2016. The labor force participation rate ages 16 to 24 fell from 58.4 in Mar 2006 to 53.9 in Mar 2016. The labor force participation rate ages 16 to 24 fell from 58.3 in Apr 2006 to 53.4 in Apr 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in May 2006 to 54.9 in May 2016. The labor force participation rate ages 16 to 24 fell from 65.3 in Jun 2006 to 59.2 in Jun 2016. The labor force participation rate ages 16 to 24 fell from 66.7 in Jul 2006 to 60.1 in Jul 2016. The labor force participation rate ages 16 to 24 fell from 63.9 in Aug 2006 to 57.5 in Aug 2016. The labor force participation rate ages 16 to 24 fell from 59.1 in Sep 2006 to 54.2 in Sep 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in Oct 2006 to 54.2 in Oct 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in Nov 2006 to 54.1 in Nov 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 54.0 in Dec 2016. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 53.6 in Jan 2017. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 54.1 in Feb 2017. 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, 2001-2017

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 (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 Feb 2007 to 44.8 in Feb 2014. The US employment population ratio for ages 16 to 24 years fell from 52.3 in Mar 2007 to 46.3 in Mar 2014. The US employment population ratio for ages 16 to 24 years fell from 51.9 in Apr 2007 to 46.5 in Apr 2014. The US employment population ratio for ages 16 to 24 years fell from 52.1 in May 2007 to 47.3 in May 2014. The US employment population ratio for ages 16 to 24 years fell from 57.6 in Jun 2006 to 50.1 in Jun 2014. The US employment population ratio for ages 16 to 24 years fell from 59.2 in Jul 2006 to 50.1 in Jul 2014. The employment population ratio for ages 16 to 24 years fell from 57.2 in Aug 2006 to 49.0 in Aug 2014. The employment population ratio for ages 16 to 24 fell from 52.9 in Sep 2006 to 46.8 in Sep 2014. The employment population ratio for ages 16 to 24 fell from 53.6 in Oct 2006 to 48.6 in Oct 2014. The employment population ratio for ages 16 to 24 fell from 53.7 in Nov 2006 to 48.1 in Nov 2014. The employment population ration for ages 16 to 24 fell from 54.3 in Dec 2006 to 47.5 in Dec 2014. The employment population ration for ages 16 to 24 years fell from 51.7 in Jan 2006 to 46.2 in Jan 2015. The employment population ratio for ages 16 to 24 fell from 52.1 in Feb 2006 to 47.1 in Feb 2015. The employment population ratio for ages 16 to 24 years fell from 52.4 in Mar 2006 to 46.7 in Mar 2015. The employment population ratio for ages 16 to 24 years fell from 52.7 in Apr 2006 to 47.2 in Apr 2015. The employment population ratio for ages 16 to 24 fell from 53.6 in May 206 to 48.4 in May 2015. The employment population ratio for ages 16 to 24 fell from 57.6 in Jun 2006 to 51.3 in Jun 2015. The employment population ratio for ages 16 to 24 fell from 59.2 in Jul 2006 to 52.7 in Jul 2015. The employment population ratio for ages 16 to 24 fell from 57.2 in Aug 2006 to 50.8 in Aug 2015. The employment population ratio for ages 16 to 24 years fell from 52.9 in Sep 2006 to 47.6 in Sep 2015. The employment population ratio for ages 16 to 24 years fell from 53.6 in Oct 2006 to 48.5 in Oct 2015. The employment population ratio for ages 16 to 24 years fell from 53.7 in Nov 2006 to 48.1 in Nov 2015. The employment population ratio for ages 16 to 24 years fell from 54.3 in Dec 2006 to 48.7 in Dec 2015. The employment population ratio for ages 16 to 24 years fell from 51.7 in Jan 2006 to 47.2 in Jan 2016. The employment population ration for ages 16 to 24 years fell from 52.1 in Feb 2006 to 48.0 in Feb 2016. The employment population ratio for ages 16 to 24 fell from 52.4 in Mar 2006 to 48.3 in Mar 2016. The employment population ratio for ages 16 to 24 fell from 52.7 in Apr 2006 to 48.1 in Apr 2016. The employment population ratio for ages 16 to 24 fell from 53.6 in May 2006 to 49.1 in May 2016. The employment population ratio for ages 16 to 24 fell from 57.6 in Jun 2006 to 51.9 in Jun 2016. The employment population ratio for ages 16 to 24 fell from 59.2 in Jul 2006 to 53.2 in Jul 2016. The employment population ratio for ages 16 to 24 fell from 57.2 in Aug 2006 to 51.7 in Aug 2016. The employment population ratio for ages 16 to 24 fell from 52.9 in Sep 2006 to 48.7 in Sep 2016. The employment population ratio for ages 16 to 24 fell from 53.6 in Oct 2006 to 48.7 in Oct 2016. The employment population ratio for ages 16 to 24 fell from 53.7 in Nov 2006 to 49.0 in Nov 2016. The employment population ratio for ages 16 to 24 fell from 54.3 in Dec 2006 to 49.1 in Dec 2016. The employment population ratio for ages 16 to 24 fell from 51.7 in Jan 2006 to 47.9 in Jan 2017. The employment population ratio for ages 16 to 24 fell from 52.1 in Feb 2006 to 48.7 in Feb 2017. 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, 2001-2017

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 24 years increased from 2342 in 2007 to 3324 thousand in 2013 or by 0.982 million. The unemployment level ages 16 to 24 years increased from 2342 thousand in 2007 to 2853 thousand in 2014 or by 0.511 million. The unemployment level for ages 16 to 24 increased from 2342 thousand in 2007 to 2467 thousand in 2015, decreasing to 2.211 million in 2016. The unemployment level ages 16 to 24 years decreased from 2.433 million in Feb 2006 to 2.093 million in Feb 2017 or decrease by 0.340 million. This situation may persist for many years.

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

Year	Jan	Feb	Aug	Sep	Oct	Nov	Dec	Annual
2001	2250	2258	2461	2301	2424	2470	2412	2371
2002	2754	2731	2688	2506	2468	2570	2374	2683
2003	2748	2740	2724	2698	2522	2522	2248	2746
2004	2767	2631	2585	2493	2572	2448	2294	2638
2005	2661	2787	2519	2339	2285	2369	2055	2521
2006	2366	2433	2467	2297	2252	2242	2007	2353
2007	2363	2230	2388	2419	2258	2250	2323	2342
2008	2633	2480	2990	2904	2842	2833	2928	2830
2009	3278	3457	4004	3774	3789	3699	3532	3760
2010	3983	3888	3903	3604	3731	3561	3352	3857
2011	3851	3696	3820	3541	3386	3287	3161	3634
2012	3416	3507	3672	3174	3285	3102	3153	3451
2013	3674	3449	3453	3139	3028	2721	2536	3324
2014	3051	3033	2844	2854	2622	2458	2317	2853
2015	2644	2529	2390	2256	2223	2147	2114	2467
2016	2205	2229	2221	2126	2094	1934	1859	2211
2017	2195	2093

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 2017. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013-2014 with recent marginal improvement in 2015-17 alternating with deterioration.

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2017

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, declining to 13.4 percent in Dec 2014. 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 percent 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 rose from 10.8 in Jul 2007 to 14.3 in Jul 2014. 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 rate of youth unemployment increased from 9.7 percent in Mar 2007 to 14.3 percent in Mar 2014. The rate of youth unemployment increased from 9.7 percent in Apr 2007 to 11.9 percent in Apr 2014. The rate of youth unemployment increased from 10.2 percent in May 2007 to 13.4 percent in May 2014. The rate of youth unemployment increased from 12.0 percent in Jun 2007 to 15.0 percent in Jun 2014. The rate of youth unemployment increased from 10.8 in Jul 2007 to 14.3 in Jul 2014. The rate of youth unemployment increased from 10.5 in Aug 2007 to 13.0 in Aug 2014. The rate of youth unemployment increased from 11.0 in Sep 2007 to 13.6 in Sep 2014. The rate of youth unemployment increased from 10.3 in Oct 2007 to 12.2 in Oct 2014. The rate of youth unemployment increased from 10.3 in Nov 2007 to 11.7 in Nov 2014. The rate of youth unemployment increased from 10.7 in Dec 2007 to 11.2 in Dec 2014. The rate of youth unemployment increased from 10.9 in Jan 2007 to 12.9 in Jan 2015. The rate of youth unemployment increased from 10.3 percent in Feb 2007 to 12.2 percent in Feb 2015. The rate of youth unemployment increased from 9.7 in Mar 2007 to 12.3 in Mar 2015. The rate of youth unemployment increased from 9.7 in Apr 2007 to 10.7 in Apr 2015. The rate of youth unemployment increased from 10.2 in May 2007 to 12.3 in May 2015. The rate of youth unemployment increased from 11.9 in Jun 2006 to 13.7 in Jun 2015. The rate of youth unemployment increased from 10.8 in Jul 2007 to 12.2 in Jul 2015. The rate of youth unemployment increased from 10.5 in Aug 2007 to 10.9 in Aug 2015. The rate of youth unemployment decreased from 11.0 in Sep 2007 to 10.9 in Sep 2015. The rate of youth unemployment increased from 10.3 in Oct 2007 to 10.6 in Oct 2015. The rate of youth unemployment increased from 10.3 in Nov 2007 to 10.4 in Nov 2015. The rate of youth unemployment decreased from 10.7 in Dec 2007 to 10.1 in Dec 2015. The rate of youth unemployment decreased from 10.9 in Jan 2007 to 10.8 in Jan 2016. The rate of youth unemployment increased from 10.3 in Feb 2007 to 10.8 in Feb 2016. The rate of youth unemployment increased from 9.7 in Mar 2007 to 10.4 in Mar 2016. The rate of youth unemployment increased from 9.7 in Apr 2007 to 9.9 in Apr 2016. The rate of youth unemployment increased from 10.2 in May 2007 to 10.6 in May 2016. The rate of youth unemployment increased from 12.0 in Jun 2007 to 12.3 in Jun 2016. The rate of youth unemployment increased from 10.8 in Jul 2007 to 11.5 in Jul 2016. The rate of youth unemplopyment fell from 10.5 in Aug 2007 to 10.1 in Aug 2016. The rate of youth unemployment fell from 11.0 in Sep 2007 to 10.2 in Sep 2016. The rate of youth unemployment fell from 10.3 in Oct 2007 to 10.1 in Oct 2016. The rate of youth unemployment fell from 10.3 in Nov 2007 to 9.3 in Nov 2016. The rate of youth unemployment fell from 10.7 in Dec 2007 to 9.0 in Dec 2016. The rate of youth unemployment fell from 10.9 in Jan 2007 to 10.7 in Jan 2017. The rate of youth unemployment fell from 10.3 in Feb 2007 to 10.1 in Feb 2017. 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	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Annual
2001	10.3	10.3	10.2	9.6	10.0	11.6	10.5	10.7	10.5	11.0	11.2	11.0	10.6
2002	12.9	12.5	12.9	11.6	11.6	13.2	12.4	11.5	11.4	11.2	11.7	10.9	12.0
2003	12.7	12.7	12.2	12.0	13.0	14.8	13.3	11.9	12.5	11.6	11.6	10.5	12.4
2004	12.8	12.3	12.1	11.1	12.2	13.4	12.3	11.1	11.5	11.6	11.1	10.5	11.8
2005	12.4	13.0	11.7	11.2	11.9	12.6	11.0	10.8	10.7	10.3	10.7	9.4	11.3
2006	11.1	11.3	10.3	9.7	10.2	11.9	11.2	10.4	10.5	10.2	10.1	9.1	10.5
2007	10.9	10.3	9.7	9.7	10.2	12.0	10.8	10.5	11.0	10.3	10.3	10.7	10.5
2008	12.3	11.8	11.1	10.3	13.3	14.4	14.0	13.0	13.4	13.2	13.3	13.7	12.8
2009	15.8	16.4	16.1	15.8	18.0	19.9	18.5	18.0	18.2	18.5	18.1	17.5	17.6
2010	19.8	19.2	18.4	18.5	18.4	20.0	19.1	17.8	17.6	18.1	17.4	16.7	18.4
2011	18.9	18.2	17.2	16.5	17.5	18.9	18.1	17.5	17.0	16.2	15.9	15.5	17.3
2012	16.8	17.0	16.0	15.4	16.3	18.1	17.1	16.8	15.2	15.5	14.8	15.2	16.2
2013	17.6	16.7	15.9	15.1	16.4	18.0	16.3	15.6	14.8	14.4	13.1	12.3	15.5
2014	14.9	14.9	14.3	11.9	13.4	15.0	14.3	13.0	13.6	12.2	11.7	11.2	13.4
2015	12.9	12.2	12.3	10.7	12.3	13.7	12.2	10.9	10.9	10.6	10.4	10.1	11.6
2016	10.8	10.8	10.4	9.9	10.6	12.3	11.5	10.1	10.2	10.1	9.3	9.0	10.4
2017	10.7	10.1

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 2017. 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, 2001-2017

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 2017. 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 rate of youth unemployment was 9.7 percent in Mar 2007, increasing to 14.3 percent in Mar 2014. The rate of youth unemployment was 9.7 percent in Apr 2007, increasing to 11.9 percent in Apr 2014. The rate of youth unemployment was 10.2 percent in May 2007, increasing to 13.4 percent in May 2014. The rate of youth unemployment was 12.0 percent in Jun 2007, increasing to 15.0 percent in Jun 2014. The rate of youth unemployment was 10.8 percent in Jul 2007, increasing to 14.3 percent in Jul 2014. The rate of youth unemployment was 10.5 percent in Aug 2007, increasing to 13.0 percent in Aug 2014. The rate of youth unemployment was 11.0 percent in Sep 2007, increasing to 13.6 percent in Sep 2014. The rate of youth unemployment increased from 10.3 in Oct 2007 to 12.2 in Oct 2014. The rate of youth unemployment increased from 10.3 percent in Nov 2007 to 11.7 percent in Nov 2014. The rate of youth unemployment increased from 10.7 in Dec 2007 to 11.2 in Dec 2014. The rate of youth unemployment increased from 9.7 in Mar 2007 to 12.3 in Mar 2015. The rate of youth unemployment increased from 9.7 in Apr 2007 to 10.7 in Apr 2015. The rate of youth unemployment increased from 10.2 in May 2007 to 12.3 in May 2015. The rate of youth unemployment increased from 12.0 in Jun 2007 to 13.7 in Jun 2015. The rate of youth unemployment increased from 10.8 in Jul 2007 to 12.2 in Jul 2015. The rate of youth unemployment increased from 10.5 in Aug 2007 to 10.9 in Aug 2015. The rate of youth unemployment decreased from 11.0 in Sep 2007 to 10.9 in Sep 2015. The rate of youth unemployment increased from 10.3 in Oct 2007 to 10.6 in Oct 2015, decreasing to 10.4 in Nov 2015. The rate of youth unemployment decreased to 10.1 in Dec 2015. The rate of youth unemployment stood at 10.8 in Jan 2016, 10.8 in Feb 2016, 10.4 in Mar 2016 and 9.9 in Apr 2016. The rate of youth unemployment increased to 10.6 in May 2016 and 12.3 in Jun 2016. The rate of youth unemployment fell to 11.5 in Jul 2016, decreasing to 10.1 in Aug 2016. The rate of youth unemployment increased to 10.2 in Sep 2016, decreasing to 10.1 in Oct 2016 and 9.3 in Nov 2016. The rate of youth unemployment decreased to 9.0 in Dec 2016, increasing to 10.7 in Jan 2017. The rate of youth unemployment fell to 10.1 in Feb 2017.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. The difference originates in the vigorous seasonally adjusted annual equivalent average rate of GDP growth of 5.9 percent during the recovery from IQ1983 to IVQ1985 and 4.4 percent from IQ1983 to IIQ1990 compared with 2.1 percent on average during the first 30 quarters of expansion from IIIQ2009 to IVQ2016. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. 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 IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Feb 1919 to Feb 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 144.4892 in Feb 2017. The actual index NSA in Feb 2017 is 103.4436, which is 28.4 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Feb 2017. Using trend growth of 2.0 percent per year, the index would increase to 130.9602 in Feb 2017. The output of manufacturing at 103.4436 in Feb 2017 is 21.0 percent below trend under this alternative calculation.

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2017

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 Oct 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 in 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 number of unemployed 45 years and over increased 2.048 million or 108.9 percent from 1.881 million in Mar 2006 to 3.929 million in Mar 2013 and at 3.394 million in Mar 2014 is higher by 80.4 percent than in Mar 2006. The number of unemployed 45 years and over increased 1.846 million or 100.2 percent from 1.843 million in Apr 2006 to 3.689 million in Apr 2013 and at 3.006 million in Apr 2014 is higher by 1.163 million or 63.1 percent. The number of unemployed ages 45 years and over increased 102.1 percent from 1.784 million in May 2006 to 3.605 million in May 2014 and at 2.913 million in May 2014 is higher by 63.3 percent than in May 2007.

The number of unemployed ages 45 years and over increased 102.1 percent from 1.805 million in Jun 2007 to 3.648 million in Jun 2013 and at 2.832 million in Jun 2014 is higher by 56.9 percent than in Jun 2007. The number of unemployed ages 45 years and over increased 81.5 percent from 2.053 million in Jul 2007 to 3.727 million in Jul 2013 and at 3.083 million in Jul 2014 is higher by 50.2 percent than in Jul 2007. The level unemployed ages 45 years and over increased 84.4 percent from 1.956 million in Aug 2007 to 3.607 million in Aug 2013 and at 3.037 million in Aug 2014 is 55.2 percent higher than in Aug 2007. The level unemployed ages 45 years and over increased 90.7 percent from 1.854 million in Sep 2007 to 3.535 million in Sep 2013 and at 2.640 million in Sep 2014 is 42.4 percent higher than in Sep 2007. The level unemployed ages 45 years and over increased 1.747 million from 1.885 million in Oct 2007 to 3.632 million in Oct 2013 and at 2.606 million in Oct 2014 is 38.2 percent higher than in Oct 2007. The level unemployed ages 45 years and over increased 1.458 million from 1.925 million in Nov 2007 to 3.383 million in Nov 2013 and at 2.829 million in Nov 2014 is 47.0 percent higher than in Nov 2007. The level of unemployed ages 45 years and over increased 1.258 million from Dec 2007 to Dec 2013 and at 2.667 million in Dec 2014 is 25.8 higher than in Dec 2007. The level unemployed ages 45 years and over increased 1.353 million from Jan 2007 to Jan 2015 and at 3.077 million in Jan 2015 is 42.8 percent higher than in Jan 2007. The level unemployed ages 45 years and over increased 1.352 million from 2.138 million in Feb 2007 to 3.490 million in Feb 2014 and at 2.991 million in Feb 2015 is 39.9 percent higher than in Feb 2007. The level of unemployed ages 45 years and over increased 1.363 million from 2.031 million in Mar 2007 to 3.394 million in Mar 2014 and at 2.724 million in Mar 2015 is 34.1 percent higher than in Mar 2007. The level of unemployed ages 45 years and over increased from 1.871 million in Apr 2007 to 3.006 million in Apr 2014 and at 2.579 million in Apr 2015 is 37.8 higher than in Apr 2007. The level of unemployed ages 45 years and over increased from 1.803 million in May 2007 to 2.913 million in Jun 2014 and at 2.457 million in May 2015 is 36.3 percent higher than in May 2007. The level of unemployed ages 45 years and over increased from 1.805 million in Jun 2007 to 2.832 million in Jun 2014 and at 2.359 million in Jun 2015 is 30.7 percent higher than in Jun 2007. The level of unemployed ages 45 years and over increased from 2.053 million in Jul 2007 to 3.083 million in Jul 2014 and at 2.666 million in Jul 2015 is 30.0 percent higher than in Jul 2007. The level of unemployed ages 45 years and over increased from 1.956 million in Aug 2007 to 3.037 million in Aug 2014 and at 2.693 million in Aug 2015 is 37.7 higher than in Aug 2007. The level of unemployed ages 45 years and over increased from 1.854 million in Sep 2007 to 2.640 million in Sep 2015 and at 2.388 million in Sep 2015 is 28.8 percent higher than in Sep 2007. The level of unemployment ages 45 years and over increased from 1.885 million in Oct 2007 to 2.606 million in Oct 2014 and at 2.290 million in Oct 2015 is 21.5 percent higher than in Oct 2007. The level of unemployment ages 45 years and over increased from 1.925 million in Nov 2007 to 2.829 million in Nov 2014 and at 2.349 million in Nov 2015 is 22.0 percent higher than in Nov 2007. The level of unemployment ages 45 years and over increased from 2.120 million in Dec 2007 to 2.667 million in Dec 2014 and at 2.317 million in Dec 2015 is 9.3 percent higher than in Dec 2007. The level of unemployment ages 45 and over increased from 2.155 million in Jan 2007 to 3.077 million in Jan 2015 and at 2.736 million in Jan 2016 is 27.0 percent higher than in Jan 2007. The level of unemployment ages 45 and over increased from 2.138 million in Feb 2007 to 2.991 million in Feb 2015 and at 2.744 million in Feb 2016 is 28.3 percent higher than in Feb 2007. The level of unemployment ages 45 and over increased from 2.031 million in Mar 2007 to 2.724 million in Mar 2015 and at 2.747 million in Mar 2016 is 35.3 percent higher than in Mar 2007. The level of unemployment ages 45 and over increased from 1.871 million in Apr 2007 to 2.579 million in Apr 2015 and at 2.410 million in Apr 2016 is 28.8 percent higher than in Apr 2007. The level of unemployment ages 45 and over increased from 1.803 million in May 2007 to 2.457 million in May 2015 and at 2.190 million in May 2016 is 21.5 percent higher than in May 2007. The level of unemployment ages 45 and over increased from 1.805 million in Jun 2007 to 2.359 million in Jun 2015 and at 2.345 million in Jun 2016 is 29.9 percent higher than in Jun 2007. The level of unemployment ages 45 and over increased from 2.053 million in Jul 2007 to 2.666 million in Jul 2015 and at 2.619 million in Jul 2016 is 27.6 percent higher than in Jul 2007. The level of unemployment ages 45 and over increased from 1.956 million in Aug 2007 to 2.693 million in Aug 2015 and at 2.565 million in Aug 2016 is 31.1 percent higher than in Aug 2007. The level of unemployment ages 45 and over increased from 1.854 million in Sep 2007 to 2.388 million in Sep 2015 and at 2.414 million in Sep 2016 is 30.2 percent higher than in Sep 2007. The level of unemployment ages 45 and over increased from 1.885 million in Oct 2007 to 2.290 million in Oct 2015 and at 2.337 million in Oct 2016 is 24.0 percent higher than in Oct 2007. The level of unemployment ages 45 and over increased from 1.925 million in Nov 2007 to 2.349 million in Nov 2015 and at 2.355 million in Nov 2016 is 22.3 percent higher than in Nov 2007. The level of unemployment ages 45 and over increased from 2.120 million in Dec 2007 to 2.317 million in Dec 2015 and at 2.360 million in Dec 2016 is 11.3 percent higher than in Dec 2007. The level of unemployment ages 45 and over increased from 2.155 million in Jan 2007 to 2.736 million in Jan 2016 and at 2.585 million in Jan 2017 is 20.0 percent higher than in Jan 2007. The level of unemployment ages 45 and over increased from 2.138 million in Feb 2007 to 2.744 million in Feb 2016 and at 2.493 million in Feb 2017 is 16.6 percent higher than in Feb 2007. 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. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. 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 IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Feb 1919 to Feb 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 144.4892 in Feb 2017. The actual index NSA in Feb 2017 is 103.4436, which is 28.4 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Feb 2017. Using trend growth of 2.0 percent per year, the index would increase to 130.9602 in Feb 2017. The output of manufacturing at 103.4436 in Feb 2017 is 21.0 percent below trend under this alternative calculation.

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

Year	Jan	Feb	Aug	Sep	Oct	Nov	Dec	Annual
2000	1498	1392	1339	1254	1202	1242	1217	1249
2001	1572	1587	1640	1586	1722	1786	1901	1576
2002	2235	2280	2114	1966	1945	2013	2210	2114
2003	2495	2415	2301	2157	2032	2132	2130	2253
2004	2453	2397	2082	1951	1931	2053	2086	2149
2005	2286	2286	1895	1992	1875	1920	1963	2009
2006	2126	2056	1869	1710	1607	1704	1794	1848
2007	2155	2138	1956	1854	1885	1925	2120	1966
2008	2336	2336	2695	2595	2728	3078	3485	2540
2009	4138	4380	4683	4560	4492	4655	4960	4500
2010	5314	5307	5128	4640	4576	4909	4762	4879
2011	5027	4837	4592	4426	4375	4195	4182	4537
2012	4458	4472	4179	3899	3800	3861	3927	4133
2013	4394	4107	3607	3535	3632	3383	3378	3719
2014	3508	3490	3037	2640	2606	2829	2667	3000
2015	3077	2991	2693	2388	2290	2349	2317	2574
2016	2736	2744	2565	2414	2337	2355	2360	2485
2017	2585	2493

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, 1976-2017

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

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, 2014, 2015 and IVQ2016. The contraction caused a strong shock to US wealth. Assets fell from $80.9 trillion in 2007 to $77.1 trillion in 2011 (http://www.federalreserve.gov/releases/z1/Current/) even after nine consecutive quarters of growth beginning in IIIQ2009 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html), for decline of $3.8 trillion or 4.7 percent. Assets stood at $101.9 trillion in 2015 for gain of $21.0 trillion relative to $80.9 trillion in 2007 or increase by 26.0 percent, using unrounded data for percentage calculations. Assets increased to $107.9 trillion in IVQ2016 by $27.0 trillion relative to 2007 or 33.4 percent. Liabilities declined from $14.4 trillion in 2007 to $13.6 trillion in 2011 or by $752.8 billion equivalent to decline by 5.2 percent. Liabilities increased $182.7 billion or 1.3 percent from 2007 to 2015. Liabilities increased from $14.4 trillion in 2007 to $15.1 trillion in IVQ2016, by $691.0 billion or increase of 4.8 percent. Net worth shrank from $66.5 trillion in 2007 to $63.4 trillion in 2011, that is, $3.1 trillion equivalent to decline of 4.7 percent. Net worth increased from $66,499.3 billion in 2007 to $92,805.4 billion in IVQ2016 by $26,306.1 billion or 39.6 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 241.432 in Dec 2016 (http://www.bls.gov/cpi/data.htm) or 14.9 percent. Net worth adjusted by CPI inflation increased 21.4 percent from 2007 to IVQ2016. Nonfinancial assets increased $4352.8 billion from $28,078.6 billion in 2007 to $32,431.4 billion in IVQ2016 or 15.5 percent. There was increase from 2007 to IVQ2016 of $3259.3 billion in real estate assets or by 14.0 percent. Real estate assets adjusted for CPI inflation fell 0.8 percent between 2007 and IVQ2016. 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	2014	2015	IVQ2016
Assets	80,912.4	98,172.3	101,918.0	107,909.5
Nonfinancial	28,078.6	28,718.8	30,496.8	32,431.4
Real Estate	23,269.1	23,212.7	24,790.1	26,528.4
Durable Goods	4,476.0	5,052.9	5,236.8	5,417.9
Financial	52,833.9	69,453.5	71,421.3	75,478.1
Deposits	5,968.2	7,891.0	8,391.3	9,102.0
Debt Secs.	3,951.4	3,979.2	4,422.7	4,246.0
Mutual Fund Shares	4,314.9	6,726.2	6,504.3	6,851.5
Equities Corporate	10,046.8	14,357.4	14,189.7	15,874.2
Equity Noncorporate	8,816.4	10,103.0	10,834.2	11,249.3
Pension	15,080.9	20,666.8	21,256.1	22,259.4
Liabilities	14,413.1	14,288.1	14,631.0	15,104.1
Home Mortgages	10,613.1	9,454.9	9,536.2	9,753.7
Consumer Credit	2,609.9	3,318.0	3,535.7	3,764.7
Net Worth	66,499.3	83,884.2	87,287.1	92,805.4

Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

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-1 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, 81.0 percent in the 20-city composite and 65.6 percent in the US national home price index 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, 82.2 percent for the 20-city composite and 68.4 percent in the US national index. House prices rose 37.6 percent between Dec 2003 and Dec 2005 for the 10-city composite, 34.2 percent for the 20-city composite and 29.0 percent for the US national propelled by low fed funds rates of 1.0 percent between Dec 2003 and Dec 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Dec 2004 until Dec 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; the 20-city index increased 35.1 percent; and the US national 31.2 percent. House prices have fallen from Dec 2006 to Dec 2016 by 7.2 percent for the 10-city composite and 5.3 percent for the 20-city composite, increasing 1.3 percent for the US national. 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 2016, house prices increased 4.9 percent in the 10-city composite, increasing 5.6 percent in the 20-city composite and 5.8 percent in the US national. Table IIA-1 also shows that house prices increased 81.8 percent between Dec 2000 and Dec 2016 for the 10-city composite, increasing 72.6 percent for the 20-city composite and 70.5 percent for the US national. 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 8.8 percent from the peak in Jun 2006 to Dec 2016 and the 20-city composite fell 6.7 percent from the peak in Jul 2006 to Dec 2016. The US national increased 0.5 percent in Dec 2016 from the peak of the 10-city composite in Jun 2006 and 0.5 percent from the peak of the 20-city composite to Jul 2016. The final part of Table II-2 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 2016 for the 10-city composite was 3.8 percent and 3.5 percent for the US national. 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. The average rate for the US national was 3.5 percent from Dec 1987 to Dec 2016 and 3.6 percent from Dec 1987 to Dec 2000. 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 2016 was 3.8 percent while the rate of the 20-city composite was 3.5 percent and 3.4 percent for the US national.

Table IIA-1, US, Percentage Changes of Standard & Poor’s Case-Shiller Home Price Indices, Not Seasonally Adjusted, ∆%

	10-City Composite	20-City Composite	US National
∆% Dec 2000 to Dec 2003	42.0	35.0	28.3
∆% Dec 2000 to Dec 2005	95.4	81.0	65.6
∆% Dec 2003 to Dec 2005	37.6	34.2	29.0
∆% Dec 2000 to Dec 2006	95.8	82.2	68.4
∆% Dec 2003 to Dec 2006	37.9	35.1	31.2
∆% Dec 2005 to Dec 2016	-7.0	-4.6	3.0
∆% Dec 2006 to Dec 2016	-7.2	-5.3	1.3
∆% Dec 2009 to Dec 2016	30.5	32.0	26.5
∆% Dec 2010 to Dec 2016	32.3	35.3	31.9
∆% Dec 2011 to Dec 2016	38.0	41.0	37.3
∆% Dec 2012 to Dec 2016	30.2	31.9	28.9
∆% Dec 2013 to Dec 2016	14.6	16.3	16.4
∆% Dec 2014 to Dec 2016	10.1	11.4	11.4
∆% Dec 2015 to Dec 2016	4.9	5.6	5.8
∆% Dec 2000 to Dec 2016	81.8	72.6	70.5
∆% Peak Jun 2006 Dec 2016	-8.8		0.5
∆% Peak Jul 2006 Dec 2016		-6.7	0.5
Average ∆% Dec 1987-Dec 2016	3.8	NA	3.5
Average ∆% Dec 1987-Dec 2000	3.8	NA	3.6
Average ∆% Dec 1992-Dec 2000	5.0	NA	4.5
Average ∆% Dec 2000-Dec 2016	3.8	3.5	3.4

Price increases measured by the Case-Shiller house price indices show in data for Jan 2017 that “home prices continued their rise across the country over the last 12 months” (https://www.spice-indices.com/idpfiles/spice-assets/resources/public/documents/490149_cshomeprice-release-0228.pdf?force_download=true). Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the 10- and 20-city composites, as shown in Table IIA-2. In Jan 2013, the seasonally adjusted 10-city composite increased 0.8 percent and the 20-city increased 0.9 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city changed 0.0 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. With the exception of Mar through Apr 2012, house prices seasonally adjusted declined in most months for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table IIA-2. 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 2013-Feb 2014. House prices grew at fast rates in Mar 2014. The 10-city NSA index increased 0.3 percent in Dec 2016 and the 20-city increased 0.3 percent. The 20-city SA increased 0.9 percent in Dec 2016 and the 20-city composite SA increased 0.9 percent. 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-2, 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 2016	0.9	0.3	0.9	0.3
Nov	0.9	0.2	0.9	0.2
Oct	0.6	0.0	0.7	0.1
Sep	0.5	0.1	0.6	0.1
Aug	0.2	0.3	0.2	0.3
Jul	0.0	0.5	0.1	0.5
Jun	-0.1	0.7	0.0	0.8
May	-0.2	0.8	-0.1	0.9
Apr	-0.3	1.0	-0.3	1.1
Mar	1.1	0.9	1.1	1.0
Feb	0.5	0.2	0.6	0.2
Jan	0.7	-0.1	0.7	0.0
Dec 2015	0.5	-0.1	0.6	0.0
Nov	0.7	0.0	0.8	0.0
Oct	0.6	-0.1	0.6	0.0
Sep	0.5	0.1	0.6	0.1
Aug	0.1	0.2	0.2	0.3
Jul	0.1	0.6	0.1	0.7
Jun	0.1	0.9	0.1	1.0
May	0.1	1.1	0.1	1.1
Apr	-0.3	1.1	-0.3	1.1
Mar	0.9	0.8	1.1	0.9
Feb	0.9	0.5	0.9	0.5
Jan	0.6	-0.1	0.6	-0.1
Dec 2014	0.7	0.0	0.7	0.0
Nov	0.5	-0.3	0.5	-0.2
Oct	0.6	-0.1	0.6	-0.1
Sep	0.3	-0.1	0.4	-0.1
Aug	0.0	0.2	0.1	0.2
Jul	0.0	0.6	0.0	0.6
Jun	0.1	1.0	0.1	1.0
May	0.0	1.1	0.1	1.1
Apr	-0.2	1.1	-0.2	1.2
Mar	1.0	0.8	1.0	0.9
Feb	0.5	0.0	0.5	0.0
Jan	0.7	-0.1	0.6	-0.1
Dec 2013	0.6	-0.1	0.6	-0.1
Nov	0.8	0.0	0.8	-0.1
Oct	0.9	0.2	0.9	0.2
Sep	1.1	0.7	1.1	0.7
Aug	1.1	1.3	1.1	1.3
Jul	1.1	1.9	1.1	1.8
Jun	1.2	2.2	1.1	2.2
May	1.3	2.5	1.3	2.5
Apr	1.4	2.6	1.3	2.6
Mar	1.5	1.3	1.5	1.3
Feb	1.0	0.3	0.9	0.2
Jan	0.8	0.0	0.9	0.0
Dec 2012	0.9	0.2	0.9	0.2
Nov	0.6	-0.3	0.7	-0.2
Oct	0.6	-0.2	0.7	-0.1
Sep	0.6	0.3	0.6	0.3
Aug	0.6	0.8	0.6	0.9
Jul	0.6	1.5	0.7	1.6
Jun	1.0	2.1	1.1	2.3
May	1.0	2.2	1.1	2.4
Apr	0.3	1.4	0.4	1.4
Mar	0.2	-0.1	0.2	0.0
Feb	-0.1	-0.9	0.0	-0.8
Jan	-0.3	-1.1	-0.2	-1.0
Dec 2011	-0.5	-1.2	-0.4	-1.1
Nov	-0.6	-1.4	-0.5	-1.3
Oct	-0.6	-1.3	-0.6	-1.4
Sep	-0.3	-0.6	-0.4	-0.7
Aug	-0.2	0.1	-0.2	0.1
Jul	-0.1	0.9	0.0	1.0
Jun	-0.1	1.0	-0.1	1.2
May	-0.2	1.0	-0.2	1.0
Apr	-0.3	0.6	-0.2	0.6
Mar	-0.6	-1.0	-0.7	-1.0
Feb	-0.4	-1.3	-0.4	-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-corelogic-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 $10.4 trillion or 12.8 percent from 2007 to 2008 and $8.8 trillion or 10.9 percent to 2009. Net worth fell $10.4 trillion from 2007 to 2008 or 15.7 percent and $8.7 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	80,912.4	70,517.5	-10,394.9	72,079.1	-8,833.3
Non FIN	28,078.6	24,403.5	-3,675.1	23,414.6	-4,664.0
RE	23,269.1	19,469.3	-3,799.8	18,458.2	-4,810.9
FIN	52,833.9	46,114.0	-6,719.9	48,664.5	-4,169.4
LIAB	14,413.1	14,326.9	-86.20	14,126.4	-286.7
NW	66,499.3	56,190.6	-10,308.7	57,952.7	-8,546.6

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

Source: Board of Governors of the Federal Reserve System. 2017. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2016. Washington, DC, Federal Reserve System, Dec 8. http://www.federalreserve.gov/releases/z1/.

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 68.9 percent of GDP in IVQ2016 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IVQ2016, real estate increased in value by $3259.3 billion and financial assets increased $22,644.2 billion for net gain of real estate and financial assets of $25,903.5 billion, explaining most of the increase in net worth of $26,306.1 billion obtained by deducting the increase in liabilities of $619.0 billion from the increase of assets of $26,997.1 billion. Net worth increased from $66,499.3 billion in 2007 to $92,805.4 billion in IVQ2016 by $23,306.1 billion or 39.6 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 241.432 in Dec 2016 (http://www.bls.gov/cpi/data.htm) or 14.9 percent. Net worth adjusted by CPI inflation increased 21.4 percent from 2007 to IVQ2016. Real estate assets adjusted for CPI inflation fell 0.8 percent from 2007 to IVQ2016. 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.” Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. 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 IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Feb 1919 to Feb 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 144.4892 in Feb 2017. The actual index NSA in Feb 2017 is 103.4436, which is 28.4 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Feb 2017. Using trend growth of 2.0 percent per year, the index would increase to 130.9602 in Feb 2017. The output of manufacturing at 103.4436 in Feb 2017 is 21.0 percent below trend under this alternative calculation.

Table IIA-4A, US, Difference of Balance Sheet of Households and Nonprofit Organizations Billions of Dollars from 2007 to 2014, 2015 and IVQ2016

	Value 2007	Change to 2014	Change to 2015	Change to IVQ2016
Assets	80,912.4	17,259.9	21,005.6	26,997.1
Nonfinancial	28,078.6	640.2	2,418.2	4,352.8
Real Estate	23,269.1	-56.4	1,521.9	3,259.3
Financial	52,833.9	16,619.6	18,587.4	22,644.2
Liabilities	14,413.1	-125.0	217.9	691.0
Net Worth	66,499.3	17,384.9	20,787.8	26,306.1

Net Worth = Assets – Liabilities

Source: Net Worth = Assets – Liabilities

The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and from IVQ1979) to IIQ1990 and from IVQ2007 to IVQ2016 is in Table IIA-5. The data reveal the following facts for the cycles in the 1980s:

IVQ1979 to IIQ1990. Net worth increased 142.0 percent from IVQ1979 to IIQ1990, the all items CPI index increased 69.4 percent from 76.7 in Dec 1979 to 129.9 in Jun 1990 and real net worth increased 42.9 percent.
IQ1980 to IVQ1985. Net worth increased 65.8 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 21.5 percent.
IVQ1979 to IVQ1985. Net worth increased 69.3 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 18.8 percent.
IQ1980 to IQ1989. Net worth increased 118.9 percent, the all items CPI index increased 52.7 percent from 80.1 in Mar 1980 to 122.3 in Mar 1989 and real net worth increased 43.4 percent.
IQ1980 to IIQ1989. Net worth increased 123.3 percent, the all items CPI index increased 54.9 percent from 80.1 in Mar 1980 to 124.1 in Jun 1989 and real net worth increased 44.1 percent.
IQ1980 to IIIQ1989. Net worth increased 129.3 percent, the all items CPI index increased 56.1 percent from 80.1 in Mar 1980 to 125.0 in Sep 1989 and real net worth increased 46.9 percent.
IQ1980 to IVQ1989. Net worth increased 133.3 percent, the all items CPI index increased 57.4 from 80.1 in Mar 1980 to 126.1 in Dec 1989 and real net worth increased 48.2 percent.
IQ1980 to IQ1990. Net worth increased 134.5 percent, the all items CPI index increased 60.7 percent from 80.1 in Mar 1980 to 128.7 in Mar 1990 and real net worth increased 46.0 percent.
IQ1980 to IIQ1990. Net worth increased 137.1 percent, the all items CPI index increased 62.2 percent from 80.1 in Mar 1980 to 129.9 in Jun 1990 and real net worth increased 46.2 percent

There is disastrous performance in the current economic cycle:

IVQ2007 to IVQ2016. Net worth increased 39.6 percent, the all items CPI increased 14.9 percent from 210.036 in Dec 2007 to 241.432 in Dec 2016 and real or inflation adjusted net worth increased 21.4 percent. Real estate assets adjusted for inflation fell 0.8 percent. Growth of real net worth at the long-term average of 3.1 percent per year from IVQ1945 to IVQ2016 would have accumulated to 31.6 percent in the entire cycle from IVQ2007 to IVQ2016, much higher than actual 21.4 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. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 30 quarters from IIIQ2009 to IVQ2016. 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 IVQ2016 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp4q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IVQ2016 would have accumulated to 30.5 percent. GDP in IVQ2016 would be $19,564.3 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2760.2 billion than actual $16,804.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.4 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html and earlier https://cmpassocregulationblog.blogspot.com/2017/02/twenty-six-million-unemployed-or.html). US GDP in IVQ2016 is 14.1 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,804.1 billion in IVQ2016 or 12.1 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Feb 1919 to Feb 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 144.4892 in Feb 2017. The actual index NSA in Feb 2017 is 103.4436, which is 28.4 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Feb 2017. Using trend growth of 2.0 percent per year, the index would increase to 130.9602 in Feb 2017. The output of manufacturing at 103.4436 in Feb 2017 is 21.0 percent below trend under this alternative calculation.

Table IIA-5, Net Worth of Households and Nonprofit Organizations in Billions of Dollars, IVQ1979 to IIQ1990 and IVQ2007 to IVQ2016

Period IQ1980 to IIQ1990
Net Worth of Households and Nonprofit Organizations USD Millions
IVQ1979 IQ1980	8,991.8 9,178.3
IVQ1985 IIIQ1986 IVQ1986 IQ1987 IIQ1987 IIIQ1987 IVQ1987 IQ1988 IIQ1988 IIIQ1988 IVQ1988 IQ1989 IIQ1989 IIIQ1989 IVQ1989 IQ1990 IIQ1990	15,221.8 16,232.9 16,874.8 17,443.5 17,731.2 18,147.2 17,997.6 18,472.4 18,874.3 19,165.3 19,648.9 20,089.4 20,495.4 21,047.6 21,412.8 21,527.5 21,760.0
∆ USD Billions IVQ1985 IVQ1979 to IIQ1990 IQ1980-IVQ1985 IQ1980-IIIQ1986 IQ1980-IVQ1986 IQ1980-IQ1987 IQ1980-IIQ1987 IQ1980-IIIQ1987 IQ1980-IVQ1987 IQ1980-IQ1988 IQ1980-IIQ1988 IQ1980-IIIQ1988 IQ1980-IVQ1988 IQ1980-IQ1989 IQ1980-IIQ1989 IQ1980-IIIQ1989 IQ1980-IVQ1989 IQ1980-IQ1990 IQ1980-IIQ1990	+6,230.0 ∆%69.3 R∆18.8 +12,768.2 ∆%142.0 R∆%42.9 +6,043.5 ∆%65.8 R∆%21.5 +7,054.6 ∆%76.9 R∆%28.6 +7,606.5 ∆%82.9 R∆%32.6 +8,265.2 ∆%90.1 R∆%35.8 +8,552.9 ∆%93.2 R∆%36.3 +8,968.9 ∆%97.7 R∆%37.7 +8819.3 ∆%96.1 R∆%36.1 +9294.1 ∆%101.3 R∆%38.4 +9696.0 ∆%105.6 R∆%39.6 +9987.0 ∆%108.8 R∆%39.6 +10470.6 ∆%114.1 R∆%42.3 +10911.1 ∆%118.9 R∆%43.4 +11,317.1 ∆%123.3 R∆% 44.1 +11,869.3 ∆%129.3 R∆% 46.9 +12,234.5 ∆%133.3 R∆%48.2 +12,349.2 ∆%134.5 R∆%46.0 +12581.7 ∆%137.1 R∆%46.2
Period IVQ2007 to IVQ2016
Net Worth of Households and Nonprofit Organizations USD Millions
IVQ2007	66,499.3
IVQ2016	92,805.4
∆ USD Billions	+26,306.1 ∆%39.6 R∆%21.4

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

Source: Board of Governors of the Federal Reserve System. 2017. Flow of funds, balance sheets and integrated macroeconomic accounts: fourth quarter 2016. Washington, DC, Federal Reserve System, Mar 9. http://www.federalreserve.gov/releases/z1/.

Chart IIA-1 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ2007 to IVQ2016. There is remarkable stop and go behavior in this series with two sharp declines and two standstills in the 30 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 21.4 percent from IVQ2007 to IVQ2016 when adjusting for consumer price inflation.

Chart IIA-1, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ2007 to IVQ2016

Chart IIA-2 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1979 to IIQ1990. 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. The Bureau of Economic Analysis estimates US GDP in 2016 at $18,565.6 billion, such that the bailout would be equivalent to cost to taxpayers of about $492.0 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 142.0 percent from IVQ1979 to IIQ1990 and 42.9 percent when adjusting for consumer price inflation. Net worth of households and nonprofit organizations increased 137.1 percent from IQ1980 to IIQ1990 and 46.2 percent when adjusting for consumer price inflation.

Chart IIA-2, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1979 to IIQ1990

Chart IIA-3 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1945 at $802.4 billion to IVQ2015 at $87,287.1 billion or increase of 10,778.3 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 236.525 in Dec 2015 or increase of 1,199.6 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 70 years with inflation-adjusted increase from $44.088 in dollars of 1945 to $384.396 in IVQ2016 or 771.9 percent. In a simple formula: {[($92,805.4/$802.4)/(241.432/18.2)-1]100 = 771.9%}. Wealth of households and nonprofit organizations increased from $802.4 billion at year-end 1945 to $92,805.4 billion at the end of IVQ2016 or 11,466.0 percent. The consumer price index increased from 18.2 in Dec 1945 to 241.432 in Dec 2016 or 1,226.5 percent. Net wealth of households and nonprofit organizations in dollars of 1945 increased from $44.088 in 1945 to $384.396 in IVQ2016 or 771.9 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 2016 (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 70 years when US GDP grew at 2.1 percent on average in the thirty quarters between IIIQ2009 and IVQ2016 (https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html). US GDP was $228.2 billion in 1945 and net worth of households and nonprofit organizations $802.4 billion for ratio of wealth to GDP of 3.52. The ratio of net worth of households and nonprofits of $66,499.3 billion in 2007 to GDP of $14,477.6 billion was 4.59. The ratio of net worth of households and nonprofits of $92,805.4 billion in 2016 to GDP of $18,565.6 billion was 5.0. The final data point in Chart IIA-3 is net worth of household and nonprofit institutions at $92,805.4 billion in IVQ2016 for increase of 11,466.0 percent relative to $802.4 billion in IVQ1945. CPI adjusted net worth of household and nonprofit institutions increased from $44.088 in IVQ1945 to $384.396 in IVQ2016 or 771.9 percent at the annual equivalent rate of 3.1 percent.

Chart IIA-3, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1945 to IVQ2016

Table IIA-6 provides percentage changes of nonfinancial domestic sector debt. Households increased debt by 10.5 percent in 2006 but reduced debt from 2010 to 2011. Households have increased debt moderately since 2012. Financial repression by zero fed funds rates or negative interest rates intends 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 2.1 percent in IIQ2012 and decreasing at 0.2 percent in IIIQ2012 and 2.6 percent in IVQ2012. State and local government increased debt at 1.9 percent in IQ2013 and decreased at 1.1 percent in IIQ2013. State and local government decreased debt at 3.0 percent in IIIQ2013 and at 2.8 percent in IVQ2013. State and local government reduced debt at 1.7 percent in IQ2014 and decreased at 0.4 percent in IIQ2014. State and local government reduced debt at 2.7 percent in IIIQ2014 and increased at 0.7 percent in IVQ2014. State and local government increased debt at 1.8 percent in IQ2015 and increased at 0.2 percent in IIIQ2015. State and local government decreased debt at 1.2 percent in IVQ2015. State and local government increased debt at 0.7 percent in IQ2016 and increased at 2.2 percent in IIQ2016. State and local government increased debt at 0.8 percent in IIIQ2016. Opposite behavior is 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	Federal	State & Local Govern-ment
IVQ2016	2.9	3.8	2.6	2.9	0.2
IIIQ2016	5.8	3.9	6.3	8.2	0.7
IIQ2016	4.3	4.3	4.0	5.0	2.2
IQ2016	5.3	2.3	9.4	5.6	0.7
IVQ2015	7.8	3.8	5.6	15.4	-1.2
IIIQ2015	2.7	1.3	5.5	2.1	0.2
IIQ2015	4.4	3.8	8.0	2.7	0.5
IQ2015	2.7	2.0	7.4	-0.3	1.6
IVQ2014	3.5	2.3	6.4	3.1	0.7
2016	4.7	3.6	5.7	5.6	1.0
2015	4.4	2.8	6.8	5.0	0.3
2014	4.3	3.0	6.1	5.4	-1.1
2013	3.8	1.8	4.6	6.7	-1.8
2012	5.0	2.0	4.6	10.1	-0.2
2011	3.5	-0.4	2.7	10.8	-1.5
2010	4.4	-0.4	-0.7	18.5	2.4
2009	3.6	0.4	-4.0	20.4	4.4
2008	5.8	0.1	5.9	21.4	1.2
2007	8.1	7.2	12.4	4.7	6.0
2006	8.4	10.5	9.8	3.9	4.4

Table IIA-7 provides wealth of US households and nonprofit organizations since 2005 in billions of current dollars at the end of period, NSA. Wealth fell from $66,499 billion in 2007 to $57,953 billion in 2009 or 12.9 percent and to $63,390 billion in 2011 or 4.7 percent. Wealth increased 39.6 percent from 2007 to IVQ2016, increasing 21.4 percent after adjustment for inflation, primarily because of bloating financial assets while nonfinancial assets declined/stagnated in real terms.

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

Quarter	Net Worth
IVQ2016	92,805
IIIQ2016	90,762
IIQ2016	88,708
IQ2016	87,889
IVQ2015	87,287
IIIQ2015	85,249
IIQ2015	86,434
IQ2015	85,798
IVQ2014	83,884
IIIQ2014	82,057
IIQ2014	81,725
IQ2014	80,109
IVQ2013	78,904
IIIQ2013	76,178
IIQ2013	73,709
IQ2013	72,208
IVQ2012	69,240
2016	92,805
2015	87,287
2014	83,884
2013	78,904
2012	69,240
2011	63,390
2010	62,100
2009	57,953
2008	56,191
2007	66,499
2006	66,192
2005	61,896

I United States Housing Collapse. Data and other information continue to provide depressed conditions in the US housing market in a longer perspective, with recent improvement at the margin. Table IIB-1 shows sales of new houses in the US at seasonally adjusted annual equivalent rate (SAAR). House sales fell in 28 of 74 months from Feb 2011 to Feb 2017 with monthly declines of 5 in 2011, 4 in 2012, 4 in 2013, 6 in 2014, 3 in 2015 and 6 in 2016. In Jan-Apr 2012, house sales increased at the annual equivalent rate of 11.8 percent and at 22.3 percent in May-Sep 2012. There was significant strength in Sep-Dec 2011 with annual equivalent rate of 48.4 percent. Sales of new houses fell 7.0 percent in Oct 2012 with increase of 9.5 percent in Nov 2012. Sales of new houses rebounded 10.8 percent in Jan 2013 with annual equivalent rate of 51.5 percent from Oct 2012 to Jan 2013 because of the increase of 10.8 percent in Jan 2013. New house sales increased at annual equivalent 9.9 percent in Feb-Mar 2013. New house sales weakened, decreasing at 2.3 percent in annual equivalent from Apr to Dec 2013 with significant volatility illustrated by decline of 18.8 percent in Jul 2013 and increase of 11.3 percent in Oct 2013. New house sales fell 1.1 percent in Dec 2013. New house sales increased 1.4 percent in Jan 2014 and fell 5.4 percent in Feb 2014, decreasing 3.1 percent in Mar 2014. New house sales decreased 2.2 percent in Apr 2014 and increased 12.7 percent in May 2014. New house sales fell 8.0 percent in Jun 2014 and decreased 3.4 percent in Jul 2014. New house sales jumped 11.7 percent in Aug 2014 and increased 3.8 percent in Sep 2014. New House sales increased 1.7 percent in Oct 2014 and fell 5.9 percent in Nov 2014. House sales fell at the annual equivalent rate of 2.6 percent in Sep-Nov 2014. New house sales increased 10.3 percent in Dec 2014 and increased 6.5 percent in Jan 2015. Sales of new houses increased 4.8 percent in Feb 2015 and fell 10.7 percent in Mar 2015. House sales increased 2.0 percent in Apr 2015. The annual equivalent rate in Dec 2014-Apr 2015 was 31.6 percent. New house sales increased 1.4 percent in May 2015 and fell 6.9 percent in Jun 2015, increasing 5.5 percent in Jul 2015. New house sales fell at annual equivalent 1.6 percent in May-Jul 2015. New house sales increased 1.4 percent in Aug 2015 and fell 9.5 percent in Sep 2015. New house sales decreased at annual equivalent 40.3 percent in Aug-Sep 2015. New house sales increased 4.6 percent in Oct 2015 and increased 6.3 percent in Nov 2015, increasing 5.9 percent in Dec 2015. New house sales increased at the annual equivalent rate of 92.2 percent in Oct-Dec 2015. New house sales decreased 2.2 percent in Jan 2016 at the annual equivalent rate of minus 23.4 percent. New house sales decreased 0.2 percent in Feb 2016 and increased 2.3 percent in Mar 2016. New house sales jumped at 6.1 percent in Apr 2016. New house sales increased at the annual equivalent rate of 37.7 percent in Feb-Apr 2016. New house sales decreased 0.7 percent in May 2016 and decreased 1.4 percent in Jun 2016. New house sales jumped 11.5 percent in Aug 2016. New house sales increased at the annual equivalent rate of 42.0 percent in May-Jul 2016. New house sales fell 10.1 percent in Aug 2016 and increased 1.6 percent in Sep 2016, changing 0.0 percent in Oct 2016. New house sales fell at the annual equivalent rate of minus 30.4 percent in Aug-Oct 2016. New house sales increased at 0.9 percent in Nov 2016 and fell at 7.5 percent in Dec 2016. New house sales fell at 33.9 percent annual equivalent in Nov-Dec 2016. New house sales increased at 5.3 percent in Jan 2017 and increased at 6.1 percent in Feb 2017. New house sales increased at 94.5 percent annual equivalent in Jan-Feb 2017. There are with wide monthly oscillations. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), analyze how builders have provided financial assistance to home buyers, including those short of cash and with weaker credit background, explaining the rise in new home sales and the highest gap between prices of new and existing houses. The 30-year conventional mortgage rate increased from 3.40 on Apr 25, 2013 to 4.58 percent on Aug 22, 2013 (http://www.federalreserve.gov/releases/h15/data.htm), which could also be a factor in recent weakness with improvement after the rate fell to 4.26 in Nov 2013. The conventional mortgage rate rose to 4.48 percent on Dec 26, 2013 and fell to 4.32 percent on Jan 30, 2014. The conventional mortgage rate increased to 4.37 percent on Feb 26, 2014 and 4.40 percent on Mar 27, 2014. The conventional mortgage rate fell to 4.14 percent on Apr 22, 2014, stabilizing at 4.14 on Jun 26, 2014. The conventional mortgage rate stood at 3.93 percent on Aug 20, 2015 and at 3.91 percent on Sep 17, 2015. The conventional mortgage rate was at 3.79 percent on Oct 22, 2015. The conventional mortgage rate was 3.97 percent on Nov 20, 2015. The conventional mortgage rate was 3.97 percent on Dec 18, 2015, and 3.92 percent on Jan 14, 2016. The conventional mortgage rate was 3.65 percent on Feb 19, 2016. The commercial mortgage rate was 3.73 percent on Mar 17, 2016 and 3.59 percent on Apr 21, 2016. The conventional mortgage rate was 3.58 on May 19, 2016. The conventional mortgage rate was 3.54 percent on Jun 19, 2016 and 3.45 percent on Jul 21, 2016. The conventional mortgage rate was 3.43 percent on Aug 18, 2016 and 3.48 percent on Sep 22, 2016. The conventional mortgage rate was 3.94 on Nov 17, 2016 and 4.30 percent on Dec 22. The conventional mortgage rate was 4.19 percent on Jan 26, 2017 and 4.15 percent on Feb 17, 2017. The conventional mortgage rate was 4.1 percent on Mar 16, 2017. The conventional mortgage rate measured in a survey by Freddie Mac (http://www.freddiemac.com/pmms/ http://www.freddiemac.com/pmms/abtpmms.htm) is the “interest rate a lender would charge to lend mortgage money to a qualified borrower.”

Table IIB-1, US, Sales of New Houses at Seasonally-Adjusted (SA) Annual Equivalent Rate, Thousands and %

	SA Annual Rate Thousands	∆%
Feb 2017	592	6.1
Jan	558	5.3
AE ∆% Jan-Feb		94.5
Dec 2016	530	-7.5
Nov	573	0.9
AE ∆% Nov-Dec		-33.9
Oct	568	0.0
Sep	568	1.6
Aug	559	-10.1
AE ∆% Aug-Oct		-30.4
Jul	622	11.5
Jun	558	-1.4
May	566	-0.7
AE ∆% May-Jul		42.0
Apr	570	6.1
Mar	537	2.3
Feb	525	-0.2
AE ∆% Feb-Apr		37.7
Jan	526	-2.2
AE ∆% Jan		-23.4
Dec 2015	538	5.9
Nov	508	6.3
Oct	478	4.6
AE ∆% Oct-Dec		92.2
Sep	457	-9.5
Aug	505	1.4
AE ∆% Aug-Sep		-40.3
Jul	498	5.5
Jun	472	-6.9
May	507	1.4
AE ∆% May-Jul		-1.6
Apr	500	2.0
Mar	490	-10.7
Feb	549	4.8
Jan	524	6.5
Dec 2014	492	10.3
AE ∆% Dec-Apr		31.6
Nov	446	-5.9
Oct	474	1.7
Sep	466	3.8
AE ∆% Sep-Nov		-2.6
Aug	449	11.7
Jul	402	-3.4
Jun	416	-8.0
May	452	12.7
Apr	401	-2.2
Mar	410	-3.1
Feb	423	-5.4
Jan	447	1.4
AE ∆% Jan-Aug		2.6
Dec 2013	441	-1.1
Nov	446	0.5
Oct	444	11.3
Sep	399	5.0
Aug	380	1.1
Jul	376	-18.8
Jun	463	7.7
May	430	-4.7
Apr	451	0.4
AE ∆% Apr-Dec		-2.3
Mar	449	2.3
Feb	439	-0.7
AE ∆% Feb-Mar		9.9
Jan	442	10.8
Dec 2012	399	1.8
Nov	392	9.5
Oct	358	-7.0
AE ∆% Oct-Jan		51.5
Sep	385	2.7
Aug	375	1.6
Jul	369	2.5
Jun	360	-2.7
May	370	4.5
AE ∆% May-Sep		22.3
Apr	354	0.0
Mar	354	-3.3
Feb	366	9.3
Jan	335	-1.8
AE ∆% Jan-Apr		11.8
Dec 2011	341	4.0
Nov	328	3.8
Oct	316	3.9
Sep	304	1.7
AE ∆% Sep-Dec		48.4
Aug	299	1.0
Jul	296	-1.7
Jun	301	-1.3
May	305	-1.6
AE ∆% May-Aug		-10.3
Apr	310	3.3
Mar	300	11.1
Feb	270	-12.1
Jan	307	-5.8
AE ∆% Jan-Apr		-14.2
Dec 2010	326	13.6

AE: Annual Equivalent

Source: US Census Bureau

There is additional information of the report of new house sales in Table IIB-2. The stock of unsold houses fell from rates of 6 to 8 percent of sales in 2011 to 4 to 5 percent in 2013 and 5.4 percent in Feb 2017. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), find that inventories of houses have declined as investors acquire distressed houses of higher quality. Median and average house prices oscillate. In Feb 2017, median prices of new houses sold not seasonally adjusted (NSA) decreased 3.9 percent after decreasing 6.6 percent in

Jan 2017. Average prices increased 9.9 percent in Feb 2017 and decreased 7.9 percent in Jan 2017. Between Dec 2010 and Feb 2017, median prices increased 22.8 percent, partly concentrated in increases of 6.9 percent in Feb 2016, 6.1 percent in Nov 2015, 2.5 percent in Sep 2015, 14.5 percent in Oct 2014, 4.0 percent in Aug 2014, 4.0 percent in May 2014 and 5.2 percent in Mar 2014. Average prices increased 33.8 percent between Dec 2010 and Feb 2017, with increases of 5.2 percent in Mar 2016, 5.4 percent in Sep 2015, 3.8 percent in Jul 2015 and 20.3 percent in Oct 2014. Between Dec 2010 and Dec 2012, median prices increased 7.1 percent and average prices increased 2.6 percent. Price increases concentrated in 2012 with increase of median prices of 18.2 percent from Dec 2011 to Dec 2012 and of average prices of 13.8 percent. Median prices increased 16.9 percent from Dec 2012 to Dec 2014, with increase of 14.5 percent in Oct 2014, while average prices increased 24.8 percent, with increase of 20.3 percent in Oct 2014. Median prices decreased 1.0 percent from Dec 2014 to Dec 2015 while average prices fell 4.1 percent. Median prices increased 10.3 percent from Dec 2015 to Dec 2016 while average prices increased 7.7 percent. Median prices decreased 4.9 percent from Feb 2016 to Feb 2017 while average prices increased 11.7 percent. Robbie Whelan, writing on “New homes hit record as builders cap supply,” on May 24, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323475304578500973445311276.html?mod=WSJ_economy_LeftTopHighlights), finds that homebuilders are continuing to restrict the number of new homes for sale. Restriction of available new homes for sale increases prices paid by buyers.

Table IIB-2, US, New House Stocks and Median and Average New Homes Sales Price

	Unsold* Stocks in Equiv. Months of Sales SA %	Median New House Sales Price USD NSA	Month ∆%	Average New House Sales Price USD NSA	Month ∆%
Feb 2017	5.4	296,200	-3.9	390,400	9.9
Jan	5.6	308,200	-6.6	355,300	-7.9
Dec 2016	5.8	329,900	3.6	385,700	5.8
Nov	5.2	318,300	5.4	364,600	7.0
Oct	5.2	302,000	-6.7	340,600	-8.6
Sep	5.1	323,700	7.0	372,800	2.2
Aug	5.2	302,400	2.5	364,700	2.7
Jul	4.6	295,000	-8.3	355,000	-2.6
Jun	5.2	321,600	8.6	364,300	4.1
May	5.1	296,000	-7.9	350,000	-7.9
Apr	5.1	321,300	3.2	380,000	3.3
Mar	5.5	311,400	0.0	367,700	5.2
Feb	5.5	311,300	6.9	349,400	-4.4
Jan	5.5	291,100	-2.6	365,600	2.1
Dec 2015	5.2	299,000	-5.7	358,100	-5.0
Nov	5.4	317,000	6.1	376,800	2.7
Oct	5.6	298,700	-2.9	366,900	-0.2
Sep	5.8	307,600	2.5	367,800	5.4
Aug	5.2	300,200	1.4	348,800	2.0
Jul	5.2	296,000	2.4	341,900	3.8
Jun	5.5	289,200	0.6	329,300	-3.4
May	5.0	287,400	-1.8	340,800	1.8
Apr	5.0	292,700	-0.2	334,700	-5.1
Mar	5.0	293,400	-0.2	352,700	-0.9
Feb	4.5	293,900	0.7	355,900	0.0
Jan	4.8	292,000	-3.3	356,000	-4.7
Dec 2014	5.1	302,000	-0.2	373,500	4.1
Nov	5.7	302,700	1.1	358,800	-6.6
Oct	5.3	299,400	14.5	384,000	20.3
Sep	5.3	261,500	-10.4	319,100	-10.4
Aug	5.5	291,700	4.0	356,200	3.2
Jul	6.1	280,400	-2.3	345,200	2.1
Jun	5.7	287,000	0.5	338,100	4.5
May	5.1	285,600	4.0	323,500	-0.5
Apr	5.7	274,500	-2.8	325,100	-1.9
Mar	5.6	282,300	5.2	331,500	1.7
Feb	5.3	268,400	-0.5	325,900	-3.4
Jan	5.1	269,800	-2.1	337,300	5.0
Dec 2013	5.1	275,500	-0.6	321,200	-4.3
Nov	5.0	277,100	4.8	335,600	0.0
Oct	4.9	264,300	-2.0	335,700	4.4
Sep	5.5	269,800	5.7	321,400	3.4
Aug	5.5	255,300	-2.6	310,800	-5.8
Jul	5.4	262,200	0.9	329,900	7.8
Jun	4.1	259,800	-1.5	306,100	-2.5
May	4.5	263,700	-5.6	314,000	-6.8
Apr	4.3	279,300	8.5	337,000	12.3
Mar	4.1	257,500	-2.9	300,200	-3.9
Feb	4.2	265,100	5.4	312,500	1.8
Jan	4.0	251,500	-2.6	306,900	2.6
Dec 2012	4.5	258,300	5.4	299,200	2.9
Nov	4.6	245,000	-0.9	290,700	1.9
Oct	4.9	247,200	-2.9	285,400	-4.1
Sep	4.5	254,600	0.6	297,700	-2.6
Aug	4.6	253,200	6.7	305,500	8.2
Jul	4.6	237,400	2.1	282,300	3.9
Jun	4.8	232,600	-2.8	271,800	-3.2
May	4.7	239,200	1.2	280,900	-2.4
Apr	4.9	236,400	-1.4	287,900	1.5
Mar	4.9	239,800	0.0	283,600	3.5
Feb	4.8	239,900	8.2	274,000	3.1
Jan	5.3	221,700	1.4	265,700	1.1
Dec 2011	5.3	218,600	2.0	262,900	5.2
Nov	5.7	214,300	-4.7	250,000	-3.2
Oct	6.0	224,800	3.6	258,300	1.1
Sep	6.3	217,000	-1.2	255,400	-1.5
Aug	6.5	219,600	-4.5	259,300	-4.1
Jul	6.7	229,900	-4.3	270,300	-1.0
Jun	6.6	240,200	8.2	273,100	4.0
May	6.6	222,000	-1.2	262,700	-2.3
Apr	6.7	224,700	1.9	268,900	3.1
Mar	7.2	220,500	0.2	260,800	-0.8
Feb	8.1	220,100	-8.3	262,800	-4.7
Jan	7.3	240,100	-0.5	275,700	-5.5
Dec 2010	7.0	241,200	9.8	291,700	3.5

*Percent of new houses for sale relative to houses sold

Source: US Census Bureau

The depressed level of residential construction and new house sales in the US is evident in Table IIB-3 providing new house sales not seasonally adjusted in Jan of various years. New house sales increased 7.1 percent from Jan-Feb 2016 to Jan-Feb 2017. Sales of new houses are higher in Jan-Feb 2017 relative to Jan-Feb 2015 with increase of 7.1 percent. Sales of new houses are higher in Jan-Feb 2017 relative to Jan-Feb 2014 with increase of 32.4 percent. Sales of new houses in Jan-Feb 2017 are substantially lower than in many years between 1971 and 2016 with the exception of the years from 2008 to 2017. There are only six other increases of 32.4 percent relative to Jan-Feb 2013, 69.8 percent relative to Jan-Feb 2012, 109.3 percent relative to Jan-Feb 2011, 76.5 percent relative to Jan-Feb 2010 and 69.8 percent relative to Jan-Feb 2009. New house sales in Jan-Feb 2017 are 2.2 percent lower than in Jan-Feb 2008. Sales of new houses in Jan-Feb 2017 are lower by 32.8 percent relative to Jan-Feb 2007, 49.2 percent relative to 2006, 55.2 percent relative to 2005 and 52.9 percent relative to 2004. The housing boom peaked in 2005 and 2006 when increases in fed funds rates to 5.25 percent in Jun 2006 from 1.0 percent in Jun 2004 affected subprime mortgages that were programmed for refinancing in two or three years on the expectation that price increases forever would raise home equity. Higher home equity would permit refinancing under feasible mortgages incorporating full payment of principal and interest (Gorton 2009EFM; see other references in http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Sales of new houses in Jan 2017 relative to the same period in 2003 fell 43.0 percent and 40.0 percent relative to the same period in 2002. Similar percentage declines are also for 2017 relative to years from 2000 to 2004. Sales of new houses in Jan-Feb 2017 fell 4.3 per cent relative to the same period in 1995. The population of the US was 179.3 million in 1960 and 281.4 million in 2000 (Hobbs and Stoops 2002, 16). Detailed historical census reports are available from the US Census Bureau at (http://www.census.gov/population/www/censusdata/hiscendata.html). The estimate of the US population is 418.8 million in 2015. The US population increased by 133.6 percent from 1960 to 2015. The final row of Table IIB-3 reveals catastrophic data: sales of new houses in Jan-Feb 2017 of 90 thousand units are lower by 4.3 percent relative to 94 thousand units of houses sold in Jan-Feb 1971, which is the ninth year when data become available in 1963. The civilian noninstitutional population increased from 122.416 million in 1963 to 253.538 million in 2016, or 107.1 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

Table IIB-3, US, Sales of New Houses Not Seasonally Adjusted, Thousands and %

	Not Seasonally Adjusted Thousands
Jan-Feb 2017	90
Jan-Feb 2016	84
Jan-Feb 2017/Jan-Feb 2016	7.1
Jan-Feb 2015	84
∆% Jan-Feb 2017/Jan-Feb 2015	7.1
Jan-Feb 2014	68
∆% Jan-Feb 2017/Jan-Feb 2014	32.4
Jan-Feb 2013	68
∆% Jan-Feb 2017/Jan-Feb 2013	32.4
Jan-Feb 2012	53
∆% Jan-Feb 2017/Jan-Feb 2012	69.8
Jan-Feb 2011	43
∆% Jan-Feb 2017/Jan-Feb 2011	109.3
Jan-Feb 2010	51
∆% Jan-Feb 2017/ Jan-Feb 2010	76.5
Jan-Feb 2009	53
∆% Jan-Feb 2017/ Jan-Feb 2009	69.8
Jan-Feb 2008	92
∆% Jan-Feb 2017/ Jan-Feb 2008	-2.2
Jan-Feb 2007	134
∆% Jan-Feb 2017/ Jan-Feb 2007	-32.8
Jan-Feb 2006	177
∆% Jan-Feb 2017/Jan-Feb 2006	-49.2
Jan-Feb 2005	201
∆% Jan-Feb 2017/Jan-Feb 2005	-55.2
Jan-Feb 2004	191
∆% Jan-Feb 2017/Jan-Feb 2004	-52.9
Jan-Feb 2003	158
∆% Jan-Feb 2017/ Jan-Feb 2003	-43.0
Jan-Feb 2002	150
∆% Jan-Feb 2017/ Jan-Feb 2002	-40.0
Jan-Feb 2001	157
∆% Jan-Feb 2017/ Jan-Feb 2001	-42.7
Jan-Feb 2000	145
∆% Jan-Feb 2017/ Jan-Feb 2000	-37.9
Jan-Feb 1995	94
∆% Jan-Feb 2017/ Jan-Feb 1995	-4.3
Jan-Feb 1971	94
∆% Jan-Feb 2017/ Jan-Feb 1971	-4.3

Source: US Census Bureau

The revised level of 306 thousand new houses sold in 2011 is the lowest since 560 thousand in 1963 in the 53 years of available data while the level of 368 thousand in 2012 is only higher than 323 thousand in 2010. The level of sales of new houses of 437 thousand in 2014 is the lowest from 1963 to 2009 with exception of 412 thousand in 1982 and 436 thousand in 1981. The population of the US increased 129.4 million from 179.3 million in 1960 to 308.7 million in 2010, or 72.2 percent. The estimate of the US population is 418.8 million in 2015. The US population increased 133.6 percent from 1960 to 2015. The civilian noninstitutional population increased from 122.416 million in 1963 to 253.538 million in 2016, or 107.1 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

The civilian noninstitutional population is the universe of the labor force. In fact, there is no year from 1963 to 2013 in Table IIA-4 with sales of new houses below 400 thousand with the exception of the immediately preceding years of 2009, 2010, 2011 and 2012.

Table IIB-4, US, New Houses Sold, NSA Thousands

Period	Sold during Period
1963	560
1964	565
1965	575
1966	461
1967	487
1968	490
1969	448
1970	485
1971	656
1972	718
1973	634
1974	519
1975	549
1976	646
1977	819
1978	817
1979	709
1980	545
1981	436
1982	412
1983	623
1984	639
1985	688
1986	750
1987	671
1988	676
1989	650
1990	534
1991	509
1992	610
1993	666
1994	670
1995	667
1996	757
1997	804
1998	886
1999	880
2000	877
2001	908
2002	973
2003	1,086
2004	1,203
2005	1,283
2006	1,051
2007	776
2008	485
2009	375
2010	323
2011	306
2012	368
2013	429
2014	437
2015	501
2016	560

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr051.html

Chart IIB-1 of the US Bureau of the Census shows the sharp decline of sales of new houses in the US. Sales rose temporarily until about mid 2010 but then declined to a lower plateau followed by increase, stability and new oscillating increase.

Chart IIB-1, US, New One-Family Houses Sold in the US, SAAR (Seasonally Adjusted Annual Rate)

Source: US Census Bureau

Table IIB-5. The percentage change of new house sales from 1963 to 2016 is 0.0 percent. Between 1991 and 2001, sales of new houses rose 78.4 percent at the average yearly rate of 6.0 percent. Between 1995 and 2005 sales of new houses increased 92.4 percent at the yearly rate of 6.8 percent. There are similar rates in all years from 2000 to 2005. The boom in housing construction and sales began in the 1980s and 1990s. The collapse of real estate culminated several decades of housing subsidies and policies to lower mortgage rates and borrowing terms (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 42-8). Sales of new houses sold in 2016 fell 16.0 percent relative to the same period in 1995 and 56.4 percent relative to 2005.

Table IIB-5, US, Percentage Change and Average Yearly Rate of Growth of Sales of New One-Family Houses

	∆%	Average Yearly % Rate
1963-2016	0.0	NA
1991-2001	78.4	6.0
1995-2005	92.4	6.8
2000-2005	46.3	7.9
1995-2016	-16.0	NA
2000-2016	-36.1	NA
2005-2016	-56.4	NA

NA: Not Applicable

Source: US Census Bureau

Chart IIB-2 of the US Bureau of the Census provides the entire monthly sample of new houses sold in the US between Jan 1963 and Feb 2017 without seasonal adjustment. The series is almost stationary until the 1990s. There is sharp upward trend from the early 1990s to 2005-2006 after which new single-family houses sold collapse to levels below those in the beginning of the series.

Chart IIB-2, US, New Single-family Houses Sold, NSA, 1963-2017

Source: US Census Bureau

The available historical annual data of median and average prices of new houses sold in the US between 1963 and 2016 is in Table IIB-6. On a yearly basis, median and average prices reached a peak in 2007 and then fell substantially. There is recovery in 2012-2016.

Table IIB-6, US, Median and Average Prices of New Houses Sold, Annual Data

Period	Median	Average
1963	$18,000	$19,300
1964	$18,900	$20,500
1965	$20,000	$21,500
1966	$21,400	$23,300
1967	$22,700	$24,600
1968	$24,700	$26,600
1969	$25,600	$27,900
1970	$23,400	$26,600
1971	$25,200	$28,300
1972	$27,600	$30,500
1973	$32,500	$35,500
1974	$35,900	$38,900
1975	$39,300	$42,600
1976	$44,200	$48,000
1977	$48,800	$54,200
1978	$55,700	$62,500
1979	$62,900	$71,800
1980	$64,600	$76,400
1981	$68,900	$83,000
1982	$69,300	$83,900
1983	$75,300	$89,800
1984	$79,900	$97,600
1985	$84,300	$100,800
1986	$92,000	$111,900
1987	$104,500	$127,200
1988	$112,500	$138,300
1989	$120,000	$148,800
1990	$122,900	$149,800
1991	$120,000	$147,200
1992	$121,500	$144,100
1993	$126,500	$147,700
1994	$130,000	$154,500
1995	$133,900	$158,700
1996	$140,000	$166,400
1997	$146,000	$176,200
1998	$152,500	$181,900
1999	$161,000	$195,600
2000	$169,000	$207,000
2001	$175,200	$213,200
2002	$187,600	$228,700
2003	$195,000	$246,300
2004	$221,000	$274,500
2005	$240,900	$297,000
2006	$246,500	$305,900
2007	$247,900	$313,600
2008	$232,100	$292,600
2009	$216,700	$270,900
2010	$221,800	$272,900
2011	$227,200	$267,900
2012	$245,200	$292,200
2013	$268,900	$324,500
2014	$282,800	$345,800
2015	$296,400	$360,600
2016	$315,500	$370,800

Source: US Census Bureau

Table IIB-7. Prices rose sharply between 2000 and 2005. In fact, prices in 2016 are higher than in 2000. Between 2006 and 2016, median prices of new houses sold increased 28.0 percent and average prices increased 21.2 percent. Between 2015 and 2016, median prices increased 6.4 percent and average prices increased 2.8 percent.

Table IIB-7, US, Percentage Change of New Houses Median and Average Prices, NSA, ∆%

	Median New Home Sales Prices ∆%	Average New Home Sales Prices ∆%
∆% 2000 to 2003	15.4	19.0
∆% 2000 to 2005	42.5	43.5
∆% 2000 to 2016	86.7	79.1
∆% 2005 to 2016	31.0	24.8
∆% 2000 to 2006	45.9	47.8
∆% 2006 to 2016	28.0	21.2
∆% 2009 to 2016	45.6	36.9
∆% 2010 to 2016	42.2	35.9
∆% 2011 to 2016	38.9	38.4
∆% 2012 to 2016	28.7	26.9
∆% 2013 to 2016	17.3	14.3
∆% 2014 to 2016	11.6	7.2
∆% 2015 to 2016	6.4	2.8

Source: US Census Bureau

Chart IIB-3 of the US Census Bureau provides the entire series of new single-family sales median prices from Jan 1963 to Feb 2017. There is long-term sharp upward trend with few declines until the current collapse. Median prices increased sharply during the Great Inflation of the 1960s and 1970s and paused during the savings and loans crisis of the late 1980s and the recession of 1991. Housing subsidies throughout the 1990s caused sharp upward trend of median new house prices that accelerated after the fed funds rate of 1 percent from 2003 to 2004. There was sharp reduction of prices after 2006 with recovery recently above earlier prices.

Chart IIB-3, US, Median Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1963-2017

Source: US Census Bureau

Chart IIB-4 of the US Census Bureau provides average prices of new houses sold from the mid-1970s to Feb 2017. There is similar behavior as with median prices of new houses sold in Chart IIB-3. The only stress occurred in price pauses during the savings and loans crisis of the late 1980s and the collapse after 2006 with recent recovery.

Chart IIB-4, US, Average Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1975-2017

Source: US Census Bureau