Recovery without Hiring, Ten Million Fewer Full-time Jobs with Thirteen Million More Population, World Inflation Waves, Balance of Payments and Fiscal Deficits Threatening Premium on Treasury Securities, Loss of Inflation Adjusted Household Wealth, Squeeze of Economic Activity by Carry Trades, World Economic Slowdown and Global Recession Risk
Carlos M. Pelaez
© Carlos M. Pelaez, 2010, 2011, 2012, 2013
Executive Summary
I Recovery without Hiring
IA1 Hiring Collapse
IA2 Labor Underutilization
IA3 Ten Million Fewer Full-time Job
IA4 Youth and Middle-Aged Unemployment
IB Destruction of Household Wealth for Inflation Adjusted Loss
IC Unresolved US Balance of Payments Deficits and Fiscal Imbalance Threatening Risk Premium on Treasury Securities
II World Inflation Waves
IIA Appendix: Transmission of Unconventional Monetary Policy
IIA1 Theory
IIA2 Policy
IIA3 Evidence
IIA4 Unwinding Strategy
IIB United States Inflation
IIC Long-term US Inflation
IID Current US Inflation
IIE Theory and Reality of Economic History and Monetary Policy Based on Fear of Deflation
III World Financial Turbulence
IIIA Financial Risks
IIIE Appendix Euro Zone Survival Risk
IIIF Appendix on Sovereign Bond Valuation
IV Global Inflation
V World Economic Slowdown
VA United States
VB Japan
VC China
VD Euro Area
VE Germany
VF France
VG Italy
VH United Kingdom
VI Valuation of Risk Financial Assets
VII Economic Indicators
VIII Interest Rates
IX Conclusion
References
Appendixes
Appendix I The Great Inflation
IIIB Appendix on Safe Haven Currencies
IIIC Appendix on Fiscal Compact
IIID Appendix on European Central Bank Large Scale Lender of Last Resort
IIIG Appendix on Deficit Financing of Growth and the Debt Crisis
IIIGA Monetary Policy with Deficit Financing of Economic Growth
IIIGB Adjustment during the Debt Crisis of the 1980s
Executive Summary
ESI Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels have increased by only 4 percent since Jan 2009. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job currently is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). Lazear and Spletzer (2012Mar, 1) argue that reductions of churn reduce the operational effectiveness of labor markets. Churn is part of the allocation of resources or in this case labor to occupations of higher marginal returns. The decline in churn can harm static and dynamic economic efficiency. Losses from decline of churn during recessions can affect an economy over the long-term by preventing optimal growth trajectories because resources are not used in the occupations where they provide highest marginal returns. Lazear and Spletzer (2012Mar 7-8) conclude that: “under a number of assumptions, we estimate that the loss in output during the recession [of 2007 to 2009] and its aftermath resulting from reduced churn equaled $208 billion. On an annual basis, this amounts to about .4% of GDP for a period of 3½ years.”
There are two additional facts discussed below: (1) there are about ten million fewer full-time jobs currently than before the recession of 2008 and 2009; and (2) the extremely high and rigid rate of youth unemployment is denying an early start to young people ages 16 to 24 years while unemployment of ages 45 years or over has swelled.
An important characteristic of the current fractured labor market of the US is the closing of the avenue for exiting unemployment and underemployment normally available through dynamic hiring. Another avenue that is closed is the opportunity for advancement in moving to new jobs that pay better salaries and benefits again because of the collapse of hiring in the United States. Those who are unemployed or underemployed cannot find a new job even accepting lower wages and no benefits. The employed cannot escape declining inflation-adjusted earnings because there is no hiring. The objective of this section is to analyze hiring and labor underutilization in the United States.
An appropriate measure of job stress is considered by Blanchard and Katz (1997, 53):
“The right measure of the state of the labor market is the exit rate from unemployment, defined as the number of hires divided by the number unemployed, rather than the unemployment rate itself. What matters to the unemployed is not how many of them there are, but how many of them there are in relation to the number of hires by firms.”
The natural rate of unemployment and the similar NAIRU are quite difficult to estimate in practice (Ibid; see Ball and Mankiw 2002).
The Bureau of Labor Statistics (BLS) created the Job Openings and Labor Turnover Survey (JOLTS) with the purpose that (http://www.bls.gov/jlt/jltover.htm#purpose):
“These data serve as demand-side indicators of labor shortages at the national level. Prior to JOLTS, there was no economic indicator of the unmet demand for labor with which to assess the presence or extent of labor shortages in the United States. The availability of unfilled jobs—the jobs opening rate—is an important measure of tightness of job markets, parallel to existing measures of unemployment.”
The BLS collects data from about 16,000 US business establishments in nonagricultural industries through the 50 states and DC. The data are released monthly and constitute an important complement to other data provided by the BLS (see also Lazear and Spletzer 2012Mar, 6-7).
Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 51.9 million in 2012 or by 11.8 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 48.5 million in 2012 or by 11.0 million, as shown in Table ESI-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.2 in 2005 to 38.9 in 2012 and in the private sector (RHP) from 52.1 in 2006 to 43.4 in 2012. The collapse of hiring in the US has not been followed by dynamic labor markets because of the low rate of economic growth of 2.1 percent in the first fourteen quarters of expansion from IIIQ2009 to IVQ2012 compared with 6.2 percent in prior cyclical expansions (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html).
Table ESI-1, US, Annual Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US and Percentage of Total Employment
| HNF | Rate RNF | HP | Rate HP | |
| 2001 | 62,948 | 47.8 | 58,825 | 53.1 |
| 2002 | 58,583 | 44.9 | 54,759 | 50.3 |
| 2003 | 56,451 | 43.4 | 53,056 | 48.9 |
| 2004 | 60,367 | 45.9 | 56,617 | 51.6 |
| 2005 | 63,150 | 47.2 | 59,372 | 53.1 |
| 2006 | 63,773 | 46.9 | 59,494 | 52.1 |
| 2007 | 62,421 | 45.4 | 58,035 | 50.3 |
| 2008 | 55,128 | 40.3 | 51,591 | 45.1 |
| 2009 | 46,357 | 35.4 | 43,031 | 39.8 |
| 2010 | 48,607 | 37.4 | 44,788 | 41.7 |
| 2011 | 49,675 | 37.8 | 46,552 | 42.5 |
| 2012 | 51,991 | 38.9 | 48,493 | 43.4 |
Source: Bureau of Labor Statistics http://www.bls.gov/jlt/
Chart ESI-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 been recovered, remaining at a depressed level.
Chart ESI-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2012
Source: US Bureau of Labor Statistics
Chart ESI-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.
Chart ESI-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2012
Source: US Bureau of Labor Statistics
Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table ESI-2. There were much milder declines in 2002 of 6.9 percent and 3.6 percent in 2003 followed by strong rebounds of 6.9 percent in 2004 and 4.6 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.1 in 2007, 11.7 in 2008 and 15.9 percent in 2009. On a yearly basis, nonfarm hiring grew 4.9 percent in 2010 relative to 2009, 2.2 percent in 2011 and 4.7 percent in 2012.
Table ESI-2, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2002-2012
| Year | Annual |
| 2002 | -6.9 |
| 2003 | -3.6 |
| 2004 | 6.9 |
| 2005 | 4.6 |
| 2006 | 1.0 |
| 2007 | -2.1 |
| 2008 | -11.7 |
| 2009 | -15.9 |
| 2010 | 4.9 |
| 2011 | 2.2 |
| 2012 | 4.7 |
Source: Bureau of Labor Statistics
Chart ESI-3 plots yearly percentage changes of nonfarm hiring. Percentage declines after 2007 were quite sharp.
Chart ESI-3, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2001-2012
Source: Bureau of Labor Statistics
Total private hiring (HP) yearly data are provided in Chart ESI-4. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2012.
Chart ESI-4, US, Total Private Hiring Level, Annual, 2001-2012
Source: Bureau of Labor Statistics
Chart ESI-5 plots the rate of total private hiring relative to employment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.
Chart ESI-5, US, Rate Total Private Hiring, Annual, 2001-2012
Source: Bureau of Labor Statistics
Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Jan in the years from 2001 to 2013 in Table ESI-3. Hiring numbers are in thousands. There is virtually no recovery in HNF from 4078 thousand (or 4.1 million) in Jan 2009 to 3806 thousand in Jan 2011, 4013 thousand in Jan 2012 and 4073 thousand in Jan 2013 for cumulative gain of minus 0.1 percent. HP rose from 3765 thousand in Jan 2009 to 3551 thousand in Jan 2011, 3749 thousand in Jan 2012 and 3808 in Jan 2013 for cumulative gain of 1.1 percent. HNF has fallen from 3835 in Dec 2006 to 3017 in Dec 2012 or by 21.3 percent. HP has fallen from 5160 in Jan 2005 to 4073 in Jan 2013 or by 21.1 percent. 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 ESI-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 | 5953 | 4.6 | 5632 | 5.1 |
| 2002 Jan | 4978 | 3.9 | 4695 | 4.4 |
| 2003 Jan | 5076 | 4.0 | 4775 | 4.5 |
| 2004 Jan | 4829 | 3.8 | 4563 | 4.3 |
| 2005 Jan | 5160 | 4.0 | 4856 | 4.5 |
| 2006 Jan | 5098 | 3.8 | 4825 | 4.3 |
| 2007 Jan | 5142 | 3.8 | 4820 | 4.3 |
| 2008 Jan | 4791 | 3.5 | 4495 | 4.0 |
| 2009 Jan | 4078 | 3.1 | 3765 | 3.5 |
| 2010 Jan | 3748 | 2.9 | 3479 | 3.3 |
| 2011 Jan | 3806 | 3.0 | 3551 | 3.3 |
| 2012 Jan | 4013 | 3.1 | 3749 | 3.4 |
| 2013 Jan | 4073 | 3.1 | 3808 | 3.4 |
Source: Bureau of Labor Statistics http://www.bls.gov/jlt/
ESII Ten Million Fewer Full-time Jobs with Thirteen Million More Population, Youth Unemployment and Middle-Aged Unemployment. There is strong seasonality in US labor markets around the end of the year. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.101 million in Sep 2011 to 8.043 million in Aug 2012, seasonally adjusted, or decline of 1.058 million in nine months, as shown in Table ESII-1, but then rebounded to 8.607 million in Sep 2012 for increase of 564,000 in one month from Aug to Sep 2012, declining to 8.286 million in Oct 2012 or by 321,000 again in one month, further declining to 8.138 million in Nov 2012 for another major one-month decline of 148,000 and 7.918 million in Dec 2012 or fewer 220,000 in just one month. The number employed part-time for economic reasons increased to 7.973 million in Jan 2013 or 55,000 more than in Dec 2012 and to 7,988 million in Feb 2013. There is an increase of 243,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 95,000 from Aug 2012 to Nov 2012. The number employed full-time increased from 112.871 million in Oct 2011 to 115.145 million in Mar 2012 or 2.274 million but then fell to 114.300 million in May 2012 or 0.845 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.492 million in Aug 2012 to 115.469 million in Oct 2012 or increase of 0.977 million full-time jobs in two months and further to 115.918 million in Jan 2013 or increase of 1.426 million more full-time jobs in four months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.841 in Feb 2013. Benchmark and seasonality-factors adjustments at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.0151 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 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. 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 2013 is 114.191 million, which is lower by 9.028 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 244.828 million in Feb 2013 or by 12.870 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 9.028 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 13 million. Growth at 2.1 percent on average in the fourteen quarters of expansion from IIIQ2009 to IVQ2012 compared with 6.2 percent on average in expansions from postwar cyclical contractions is the main culprit of the fractured US labor market (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html).
Table ESII-1, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions
| Part-time Thousands | Full-time Millions | |
| Seasonally Adjusted | ||
| Feb 2013 | 7,988 | 115.841 |
| Jan 2013 | 7,973 | 115.918 |
| Dec 2012 | 7,918 | 115.868 |
| Nov 2012 | 8,138 | 115.665 |
| Oct 2012 | 8,286 | 115.469 |
| Sep 2012 | 8,607 | 115.259 |
| Aug 2012 | 8,043 | 114.492 |
| Jul 2012 | 8,245 | 114.478 |
| Jun 2012 | 8,210 | 114.606 |
| May 2012 | 8,116 | 114.300 |
| Apr 2012 | 7,896 | 114.441 |
| Mar 2012 | 7,664 | 115.145 |
| Feb 2012 | 8,127 | 114.263 |
| Jan 2012 | 8,220 | 113.833 |
| Dec 2011 | 8,168 | 113.820 |
| Nov 2011 | 8,436 | 113.217 |
| Oct 2011 | 8,726 | 112.871 |
| Sep 2011 | 9,101 | 112.541 |
| Aug 2011 | 8,816 | 112.555 |
| Jul 2011 | 8,416 | 112.141 |
| Not Seasonally Adjusted | ||
| Feb 2013 | 8,298 | 114.191 |
| Jan 2013 | 8,628 | 113.868 |
| Dec 2012 | 8,116 | 115.079 |
| Nov 2012 | 7,994 | 115.515 |
| Oct 2012 | 7,870 | 116.045 |
| Sep 2012 | 8,110 | 115.678 |
| Aug 2012 | 7,842 | 116.214 |
| Jul 2012 | 8,316 | 116.131 |
| Jun 2012 | 8,394 | 116.024 |
| May 2012 | 7,837 | 114.634 |
| Apr 2012 | 7,694 | 113.999 |
| Mar 2012 | 7,867 | 113.916 |
| Feb 2012 | 8,455 | 112.587 |
| Jan 2012 | 8,918 | 111.879 |
| Dec 2011 | 8,428 | 113.050 |
| Nov 2011 | 8,271 | 113.138 |
| Oct 2011 | 8,258 | 113.456 |
| Sep 2011 | 8,541 | 112.980 |
| Aug 2011 | 8,604 | 114.286 |
| Jul 2011 | 8,514 | 113.759 |
| Jun 2011 | 8,738 | 113.255 |
| May 2011 | 8,270 | 112.618 |
| Apr 2011 | 8,425 | 111.844 |
| Mar 2011 | 8,737 | 111.186 |
| Feb 2011 | 8,749 | 110.731 |
| Jan 2011 | 9,187 | 110.373 |
| Dec 2010 | 9,205 | 111.207 |
| Nov 2010 | 8,670 | 111.348 |
| Oct 2010 | 8,408 | 112.342 |
| Sep 2010 | 8,628 | 112.385 |
| Aug 2010 | 8,628 | 113.508 |
| Jul 2010 | 8,737 | 113.974 |
| Jun 2010 | 8,867 | 113.856 |
| May 2010 | 8,513 | 112.809 |
| Apr 2010 | 8,921 | 111.391 |
| Mar 2010 | 9,343 | 109.877 |
| Feb 2010 | 9,282 | 109.100 |
| Jan 2010 | 9,290 | 108.777 (low) |
| Dec 2009 | 9,354 (high) | 109.875 |
| Nov 2009 | 8,894 | 111.274 |
| Oct 2009 | 8,474 | 111.599 |
| Sep 2009 | 8,255 | 111.991 |
| Aug 2009 | 8,835 | 113.863 |
| Jul 2009 | 9,103 | 114.184 |
| Jun 2009 | 9,301 | 114.014 |
| May 2009 | 8,785 | 113.083 |
| Apr 2009 | 8,648 | 112.746 |
| Mar 2009 | 9,305 | 112.215 |
| Feb 2009 | 9,170 | 112.947 |
| Jan 2009 | 8,829 | 113.815 |
| Dec 2008 | 8,250 | 116.422 |
| Nov 2008 | 7,135 | 118.432 |
| Oct 2008 | 6,267 | 120.020 |
| Sep 2008 | 5,701 | 120.213 |
| Aug 2008 | 5,736 | 121.556 |
| Jul 2008 | 6,054 | 122.378 |
| Jun 2008 | 5,697 | 121.845 |
| May 2008 | 5,096 | 120.809 |
| Apr 2008 | 5,071 | 120.027 |
| Mar 2008 | 5,038 | 119.875 |
| Feb 2008 | 5,114 | 119.452 |
| Jan 2008 | 5,340 | 119.332 |
| Dec 2007 | 4,750 | 121.042 |
| Nov 2007 | 4,374 | 121.846 |
| Oct 2007 | 4,028 | 122.006 |
| Sep 2007 | 4,137 | 121.728 |
| Aug 2007 | 4,494 | 122.870 |
| Jul 2007 | 4,516 | 123.219 (high) |
| Jun 2007 | 4,469 | 122.150 |
| May 2007 | 4,315 | 120.846 |
| Apr 2007 | 4,205 | 119.609 |
| Mar 2007 | 4,384 | 119.640 |
| Feb 2007 | 4,417 | 119.041 |
| Jan 2007 | 4,726 | 119.094 |
| Dec 2006 | 4,281 | 120.371 |
| Nov 2006 | 4,054 | 120.507 |
| Oct 2006 | 4,010 | 121.199 |
| Sep 2006 | 3,735 (low) | 120.780 |
| Aug 2006 | 4,104 | 121.979 |
| Jul 2006 | 4,450 | 121.951 |
| Jun 2006 | 4,456 | 121.070 |
| May 2006 | 3,968 | 118.925 |
| Apr 2006 | 3,787 | 118.559 |
| Mar 2006 | 4,097 | 117.693 |
| Feb 2006 | 4,403 | 116.823 |
| Jan 2006 | 4,597 | 116.395 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart ESII-1 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 2013 with fluctuations around the typical behavior of a stationary series: there is no improvement in the United States in creating full-time jobs.
Chart ESII-1, US, Full-time Employed, Thousands, NSA, 2001-2013
Sources: US Bureau of Labor Statistics
Chart ESII-1A provides the noninstitutional civilian population of the United States from 2001 to 2013. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.
Chart ESII-1A, US, Noninstitutional Civilian Population, 2001-2013
Sources: US Bureau of Labor Statistics
Chart ESII-2 provides number of full-time jobs in the US from 1968 to 2013. There were multiple recessions followed by expansions without contraction of full-time jobs without recovery as during the period after 2008.
Chart ESII-2, US, Full-time Employed, Thousands, NSA, 1968-2013
Sources: US Bureau of Labor Statistics
Chart ESII-3 provides the noninstitutional civilian population of the United States from 1968 to 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.
Chart ESII-3, US, Noninstitutional Civilian Population, 2001-2013
Sources: US Bureau of Labor Statistics
Chart ESII-4 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2013. 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 claim 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 while 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 and 16.7 percent in Feb 2013. In Jul 2007, the rate of youth unemployment was 10.8 percent, increasing to 17.1 percent in Jul 2012. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.2 percent on average during the first fourteen quarters of expansion from IIIQ2009 to IVQ2012 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html). The fractured US labor market denies an early start for young people.
Chart ESII4, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2013
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 matured individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table ESII-2 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.985 million in Jul 2006 to 4.821 million in July 2010 or by 142.9 percent. The number of unemployed ages 45 years and over declined to 4.405 million in Jul 2012 that is still higher by 121.9 percent than in Jul 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 and at 3.927 million in Dec 2012 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 4.107 million in Feb 2013 is higher by 2.051 million than 2.056 million in Feb 2006 or higher by 100.0 percent.
Table ESII-2, US, Unemployment Level 45 Years and Over, Thousands NSA
| Year | Jan | Feb | Mar | Apr | Dec | Annual |
| 2000 | 1498 | 1392 | 1291 | 1062 | 1217 | 1249 |
| 2001 | 1572 | 1587 | 1533 | 1421 | 1901 | 1576 |
| 2002 | 2235 | 2280 | 2138 | 2101 | 2210 | 2114 |
| 2003 | 2495 | 2415 | 2485 | 2287 | 2130 | 2253 |
| 2004 | 2453 | 2397 | 2354 | 2160 | 2086 | 2149 |
| 2005 | 2286 | 2286 | 2126 | 1939 | 1963 | 2009 |
| 2006 | 2126 | 2056 | 1881 | 1843 | 1794 | 1848 |
| 2007 | 2155 | 2138 | 2031 | 1871 | 2120 | 1966 |
| 2008 | 2336 | 2336 | 2326 | 2104 | 3485 | 2540 |
| 2009 | 4138 | 4380 | 4518 | 4172 | 4960 | 4500 |
| 2010 | 5314 | 5307 | 5194 | 4770 | 4762 | 4879 |
| 2011 | 5027 | 4837 | 4748 | 4373 | 4182 | 4537 |
| 2012 | 4458 | 4472 | 4390 | 4037 | 3927 | 4133 |
| 2013 | 4394 | 4107 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart ESII-5 provides the level unemployed ages 45 years and over. There was sharp increase during the global recession and inadequate decline. There was an increase during the 2001 recession and then stability. The US is facing a major challenge of reemploying middle-aged workers.
Chart ESII-5, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
ESIII Unresolved US Balance of Payments Deficits and Fiscal Imbalance Threatening Risk Premium on Treasury Securities. The current account of the US balance of payments is provided in Table ESIII-1 for IVQ2011 and IVQ2012. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US decreased from $117.9 billion in IVQ2011, or 3.1 percent of GDP, to $111.2 billion in IIIQ2012, or 2.8 percent of GDP. The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession but is combined now with much higher imbalance in the Treasury budget (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71).
Table ESIII-1, US Balance of Payments, Millions of Dollars NSA
| IVQ2011 | IVQ2012 | Difference | |
| Goods Balance | -186,332 | -176,774 | 9,558 |
| X Goods | 387,237 | 399,304 | 3.1 ∆% |
| M Goods | -573,569 | -576,078 | 0.4 ∆% |
| Services Balance | 44,252 | 52,148 | 3,647 |
| X Services | 151,164 | 158,749 | 5.0 ∆% |
| M Services | -106,912 | -106,601 | -0.3 ∆% |
| Balance Goods and Services | -142,080 | -124,626 | 17,454 |
| Balance Income | 56,263 | 48,293 | -7,970 |
| Unilateral Transfers | -32,135 | -34,827 | -2,692 |
| Current Account Balance | -117,952 | -111,159 | 6,793 |
| % GDP | IVQ2011 | IVQ2012 | IIIQ2012 |
| 3.1 | 2.8 | 2.8 |
X: exports; M: imports
Balance on Current Account = Balance on Goods and Services + Balance on Income + Unilateral Transfers
Source: Bureau of Economic Analysis http://www.bea.gov/international/index.htm#bop http://www.bea.gov/iTable/index_nipa.cfm
In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):
“Imagine that fiscal policy dominates monetary policy. The fiscal authority independently sets its budgets, announcing all current and future deficits and surpluses and thus determining the amount of revenue that must be raised through bond sales and seignorage. Under this second coordination scheme, the monetary authority faces the constraints imposed by the demand for government bonds, for it must try to finance with seignorage any discrepancy between the revenue demanded by the fiscal authority and the amount of bonds that can be sold to the public. Suppose that the demand for government bonds implies an interest rate on bonds greater than the economy’s rate of growth. Then if the fiscal authority runs deficits, the monetary authority is unable to control either the growth rate of the monetary base or inflation forever. If the principal and interest due on these additional bonds are raised by selling still more bonds, so as to continue to hold down the growth of base money, then, because the interest rate on bonds is greater than the economy’s growth rate, the real stock of bonds will growth faster than the size of the economy. This cannot go on forever, since the demand for bonds places an upper limit on the stock of bonds relative to the size of the economy. Once that limit is reached, the principal and interest due on the bonds already sold to fight inflation must be financed, at least in part, by seignorage, requiring the creation of additional base money.”
The alternative fiscal scenario of the CBO (2012NovCDR) resembles an economic world in which eventually the placement of debt reaches a limit of what is proportionately desired of US debt in investment portfolios. This unpleasant environment is occurring in various European countries.
The current real value of government debt plus monetary liabilities depends on the expected discounted values of future primary surpluses or difference between tax revenue and government expenditure excluding interest payments (Cochrane 2011Jan, 27, equation (16)). There is a point when adverse expectations about the capacity of the government to generate primary surpluses to honor its obligations can result in increases in interest rates on government debt.
This analysis suggests that there may be a point of saturation of demand for United States financial liabilities without an increase in interest rates on Treasury securities. A risk premium may develop on US debt. Such premium is not apparent currently because of distressed conditions in the world economy and international financial system. Risk premiums are observed in the spread of bonds of highly indebted countries in Europe relative to bonds of the government of Germany.
The issue of global imbalances centered on the possibility of a disorderly correction (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). Such a correction has not occurred historically but there is no argument proving that it could not occur. The need for a correction would originate in unsustainable large and growing United States current account deficits (CAD) and net international investment position (NIIP) or excess of financial liabilities of the US held by foreigners net of financial liabilities of foreigners held by US residents. The IMF estimated that the US could maintain a CAD of two to three percent of GDP without major problems (Rajan 2004). The threat of disorderly correction is summarized by Pelaez and Pelaez, The Global Recession Risk (2007), 15):
“It is possible that foreigners may be unwilling to increase their positions in US financial assets at prevailing interest rates. An exit out of the dollar could cause major devaluation of the dollar. The depreciation of the dollar would cause inflation in the US, leading to increases in American interest rates. There would be an increase in mortgage rates followed by deterioration of real estate values. The IMF has simulated that such an adjustment would cause a decline in the rate of growth of US GDP to 0.5 percent over several years. The decline of demand in the US by four percentage points over several years would result in a world recession because the weakness in Europe and Japan could not compensate for the collapse of American demand. The probability of occurrence of an abrupt adjustment is unknown. However, the adverse effects are quite high, at least hypothetically, to warrant concern.”
The United States could be moving toward a situation typical of heavily indebted countries, requiring fiscal adjustment and increases in productivity to become more competitive internationally. The CAD and NIIP of the United States are not observed in full deterioration because the economy is well below potential. There are two complications in the current environment relative to the concern with disorderly correction in the first half of the past decade. Table ESIII-2 provides data on the US fiscal and balance of payments imbalances. In 2007, the federal deficit of the US was $161 billion corresponding to 1.2 percent of GDP while the Congressional Budget Office (CBO 2012NovCDR) estimates the federal deficit in 2012 at $1089 billion or 7.0 percent of GDP (http://cmpassocregulationblog.blogspot.com/2013/02/united-states-unsustainable-fiscal.html). The combined record federal deficits of the US from 2009 to 2012 are $5092 billion or 33 percent of the estimate of GDP of $15,549 billion for fiscal year 2012 by the CBO (http://www.cbo.gov/publication/43905 CBO (2013BEOFeb5)). The deficits from 2009 to 2012 exceed one trillion dollars per year, adding to $5092 trillion in four years, using the fiscal year deficit of $1089.4 billion for fiscal year 2012 (http://www.fms.treas.gov/mts/mts0912.txt), which is the worst fiscal performance since World War II. Federal debt in 2007 was $5035 billion, less than the combined deficits from 2009 to 2012 of $5092 billion. Federal debt in 2011 was 67.8 percent of GDP and is estimated to reach 72.5 percent of GDP in 2012 (CBO2012AugBEO, CBO2012NovCDR, CBO2013BEOFeb5). This situation may worsen in the future (CBO 2012LTBO):
“The budget outlook is much bleaker under the extended alternative fiscal scenario, which maintains what some analysts might consider “current policies,” as opposed to current laws. Federal debt would grow rapidly from its already high level, exceeding 90 percent of GDP in 2022. After that, the growing imbalance between revenues and spending, combined with spiraling interest payments, would swiftly push debt to higher and higher levels. Debt as a share of GDP would exceed its historical peak of 109 percent by 2026, and it would approach 200 percent in 2037.
The changes under this scenario would result in much lower revenues than would occur under the extended baseline scenario because almost all expiring tax provisions are assumed to be extended through 2022 (with the exception of the current reduction in the payroll tax rate for Social Security). After 2022, revenues under this scenario are assumed to remain at their 2022 level of 18.5 percent of GDP, just above the average of the past 40 years.
Outlays would be much higher than under the other scenario. This scenario incorporates assumptions that through 2022, lawmakers will act to prevent Medicare’s payment rates for physicians from declining; that after 2022, lawmakers will not allow various restraints on the growth of Medicare costs and health insurance subsidies to exert their full effect; and that the automatic reductions in spending required by the Budget Control Act of 2011 will not occur (although the original caps on discretionary appropriations in that law are assumed to remain in place). Finally, under this scenario, federal spending as a percentage of GDP for activities other than Social Security, the major health care programs, and interest payments is assumed to return to its average level during the past two decades, rather than fall significantly below that level, as it does under the extended baseline scenario.”
Table ESIII-2, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and %
| 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | |
| Goods & | -696 | -698 | -379 | -495 | -560 | -539 |
| Income | 101 | 147 | 119 | 184 | 227 | 198 |
| UT | -115 | -126 | -122 | -131 | -133 | -134 |
| Current Account | -710 | -677 | -382 | -442 | -466 | -475 |
| NGDP | 14028 | 14291 | 13974 | 14499 | 15076 | 15681 |
| Current Account % GDP | -5.1 | -4.7 | -2.7 | -3.1 | -3.1 | -3.0 |
| NIIP | -1796 | -3260 | -2321 | -2474 | -4030 | NA |
| US Owned Assets Abroad | 18399 | 19464 | 18512 | 20298 | 21132 | NA |
| Foreign Owned Assets in US | 20195 | 22724 | 20833 | 22772 | 25162 | NA |
| NIIP % GDP | -12.8 | -22.8 | -16.6 | -17.1 | -26.7 | NA |
| Exports | 2488 | 2657 | 2181 | 2519 | 2848 | 2937 |
| NIIP % | -72 | -123 | -106 | -98 | -142 | NA |
| DIA MV | 5274 | 3102 | 4287 | 4767 | 4499 | NA |
| DIUS MV | 3551 | 2486 | 2995 | 3397 | 3509 | NA |
| Fiscal Balance | -161 | -459 | -1413 | -1294 | -1296 | -1089 |
| Fiscal Balance % GDP | -1.2 | -3.2 | -10.1 | -9.0 | -8.7 | -7.0 |
| Federal Debt | 5035 | 5803 | 7545 | 9019 | 10128 | 11280 |
| Federal Debt % GDP | 36.3 | 40.5 | 54.1 | 62.9 | 67.8 | 72.5 |
| Federal Outlays | 2729 | 2983 | 3518 | 3456 | 3598 | 3538 |
| ∆% | 2.8 | 9.3 | 17.9 | -1.8 | 4.1 | -1.7 |
| % GDP | 19.7 | 20.8 | 25.2 | 24.1 | 24.1 | 22.8 |
| Federal Revenue | 2568 | 2524 | 2105 | 2162 | 2302 | 2449 |
| ∆% | 6.7 | -1.7 | -16.6 | 2.7 | 6.5 | 6.4 |
| % GDP | 18.5 | 17.6 | 15.1 | 15.1 | 15.4 | 15.8 |
Sources:
Notes: UT: unilateral transfers; NGDP: nominal GDP or in current dollars; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value. There are minor discrepancies in the decimal point of percentages of GDP between the balance of payments data and federal debt, outlays, revenue and deficits in which the original number of the CBO source is maintained. These discrepancies do not alter conclusions.
Sources: http://www.bea.gov/international/index.htm#bop Balance of Payments and NIIP, Bureau of Economic Analysis (BEA)
Gross Domestic Product, Bureau of Economic Analysis (BEA) http://www.bea.gov/iTable/index_nipa.cfm
Chart ESIII-1 of the Board of Governors of the Federal Reserve System provides the overnight Fed funds rate on business days from Jan 10, 1979, at 9.91 percent per year, to Mar 14, 2013, at 0.15 percent per year. US recessions are in shaded areas according to the reference dates of the NBER (http://www.nber.org/cycles.html). In the Fed effort to control the “Great Inflation” of the 1930s (see http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I The Great Inflation; see Taylor 1993, 1997, 1998LB, 1999, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB and http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html), the fed funds rate increased from 8.34 percent on Jan 3, 1979 to a high in Chart ESIII-1 of 22.36 percent per year on Jul 22, 1981 with collateral adverse effects in the form of impaired savings and loans associations in the United States, emerging market debt and money-center banks (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 72-7; Pelaez 1986, 1987). Another episode in Chart ESIII-1 is the increase in the fed funds rate from 3.15 percent on Jan 3, 1994, to 6.56 percent on Dec 21, 1994, which also had collateral effects in impairing emerging market debt in Mexico and Argentina and bank balance sheets in a world bust of fixed income markets during pursuit by central banks of non-existing inflation (Pelaez and Pelaez, International Financial Architecture (2005), 113-5). Another interesting policy impulse is the reduction of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of equally non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85), followed by increments of 25 basis points from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006 in Chart ESIII-1. Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment 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 interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).
The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity 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). A final episode in Chart ESIII-1 is the reduction of the fed funds rate from 5.41 percent on Aug 9, 2007, to 2.97 percent on October 7, 2008, to 0.12 percent on Dec 5, 2008 and close to zero throughout a long period with the final point at 0.16 percent on Mar 7, 2013. Evidently, this behavior of policy would not have occurred had there been theory, measurements and forecasts to avoid these violent oscillations that are clearly detrimental to economic growth and prosperity without inflation. Current policy consists of forecast mandate of maintaining policy accommodation until the forecast of the rate of unemployment reaches 6.5 percent and the rate of personal consumption expenditures excluding food and energy reaches 2.5 percent (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm). It is a forecast mandate because of the lags in effect of monetary policy impulses on income and prices (Romer and Romer 2004). The intention is to reduce unemployment close to the “natural rate” (Friedman 1968, Phelps 1968) of around 5 percent and inflation at or below 2.0 percent. If forecasts were reasonably accurate, there would not be policy errors. A commonly analyzed risk of zero interest rates is the occurrence of unintended inflation that could precipitate an increase in interest rates similar to the Himalayan rise of the fed funds rate from 9.91 percent on Jan 10, 1979, at the beginning in Chart ESIII-1, to 22.36 percent on Jul 22, 1981. There is a less commonly analyzed risk of the development of a risk premium on Treasury securities because of the unsustainable Treasury deficit/debt of the United States (http://cmpassocregulationblog.blogspot.com/2013/02/united-states-unsustainable-fiscal.html). There is not a fiscal cliff or debt limit issue ahead but rather free fall into a fiscal abyss. The combination of the fiscal abyss with zero interest rates could trigger the risk premium on Treasury debt or Himalayan hike in interest rates.
Chart ESIII-1, US, Fed Funds Rate, Business Days, Jan 10, 1979 to Mar 14, 2013, Percent per Year
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/h15/update/
There is a false impression of the existence of a monetary policy “science,” measurements and forecasting with which to steer the economy into “prosperity without inflation.” Market participants are remembering the Great Bond Crash of 1994 shown in Table ESIII-3 when monetary policy pursued nonexistent inflation, causing trillions of dollars of losses in fixed income worldwide while increasing the fed funds rate from 3 percent in Jan 1994 to 6 percent in Dec. The exercise in Table ESIII-3 shows a drop of the price of the 30-year bond by 18.1 percent and of the 10-year bond by 14.1 percent. CPI inflation remained almost the same and there is no valid counterfactual that inflation would have been higher without monetary policy tightening because of the long lag in effect of monetary policy on inflation (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). The pursuit of nonexistent deflation during the past ten years has resulted in the largest monetary policy accommodation in history that created the 2007 financial market crash and global recession and is currently preventing smoother recovery while creating another financial crash in the future. The issue is not whether there should be a central bank and monetary policy but rather whether policy accommodation in doses from zero interest rates to trillions of dollars in the fed balance sheet endangers economic stability.
Table ESIII-3, Fed Funds Rates, Thirty and Ten Year Treasury Yields and Prices, 30-Year Mortgage Rates and 12-month CPI Inflation 1994
| 1994 | FF | 30Y | 30P | 10Y | 10P | MOR | CPI |
| Jan | 3.00 | 6.29 | 100 | 5.75 | 100 | 7.06 | 2.52 |
| Feb | 3.25 | 6.49 | 97.37 | 5.97 | 98.36 | 7.15 | 2.51 |
| Mar | 3.50 | 6.91 | 92.19 | 6.48 | 94.69 | 7.68 | 2.51 |
| Apr | 3.75 | 7.27 | 88.10 | 6.97 | 91.32 | 8.32 | 2.36 |
| May | 4.25 | 7.41 | 86.59 | 7.18 | 88.93 | 8.60 | 2.29 |
| Jun | 4.25 | 7.40 | 86.69 | 7.10 | 90.45 | 8.40 | 2.49 |
| Jul | 4.25 | 7.58 | 84.81 | 7.30 | 89.14 | 8.61 | 2.77 |
| Aug | 4.75 | 7.49 | 85.74 | 7.24 | 89.53 | 8.51 | 2.69 |
| Sep | 4.75 | 7.71 | 83.49 | 7.46 | 88.10 | 8.64 | 2.96 |
| Oct | 4.75 | 7.94 | 81.23 | 7.74 | 86.33 | 8.93 | 2.61 |
| Nov | 5.50 | 8.08 | 79.90 | 7.96 | 84.96 | 9.17 | 2.67 |
| Dec | 6.00 | 7.87 | 81.91 | 7.81 | 85.89 | 9.20 | 2.67 |
Notes: FF: fed funds rate; 30Y: yield of 30-year Treasury; 30P: price of 30-year Treasury assuming coupon equal to 6.29 percent and maturity in exactly 30 years; 10Y: yield of 10-year Treasury; 10P: price of 10-year Treasury assuming coupon equal to 5.75 percent and maturity in exactly 10 years; MOR: 30-year mortgage; CPI: percent change of CPI in 12 months
Sources: yields and mortgage rates http://www.federalreserve.gov/releases/h15/data.htm CPI ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.t
Table ESIII-4 provides major foreign holders of US Treasury securities. China is the largest holder with $1264.5 billion in Jan 2013, increasing 8.4 percent from $1166.2 billion in Jan 2012. Japan increased its holdings from $1080.8 billion in Jan 2012 to $1115.2 billion in Jan 2013 or by 3.2 percent likely in part by intervention to buy dollars against the yen to depreciate the overvalued yen/dollar rate that diminishes the competitiveness of Japan. Total foreign holdings of Treasury securities rose from $5056.8 billion in Jan 2012 to $5616.5 billion in Jan 2013, or 11.1 percent. The US continues to finance its fiscal and balance of payments deficits with foreign savings (see Pelaez and Pelaez, The Global Recession Risk (2007)). A point of saturation of holdings of US Treasury debt may be reached as foreign holders evaluate the threat of reduction of principal by dollar devaluation and reduction of prices by increases in yield, including possibly risk premium. Shultz et al (2012) find that the Fed financed three-quarters of the US deficit in fiscal year 2011, with foreign governments financing significant part of the remainder of the US deficit while the Fed owns one in six dollars of US national debt. Concentrations of debt in few holders are perilous because of sudden exodus in fear of devaluation and yield increases and the limit of refinancing old debt and placing new debt. In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):
“Imagine that fiscal policy dominates monetary policy. The fiscal authority independently sets its budgets, announcing all current and future deficits and surpluses and thus determining the amount of revenue that must be raised through bond sales and seignorage. Under this second coordination scheme, the monetary authority faces the constraints imposed by the demand for government bonds, for it must try to finance with seignorage any discrepancy between the revenue demanded by the fiscal authority and the amount of bonds that can be sold to the public. Suppose that the demand for government bonds implies an interest rate on bonds greater than the economy’s rate of growth. Then if the fiscal authority runs deficits, the monetary authority is unable to control either the growth rate of the monetary base or inflation forever. If the principal and interest due on these additional bonds are raised by selling still more bonds, so as to continue to hold down the growth of base money, then, because the interest rate on bonds is greater than the economy’s growth rate, the real stock of bonds will growth faster than the size of the economy. This cannot go on forever, since the demand for bonds places an upper limit on the stock of bonds relative to the size of the economy. Once that limit is reached, the principal and interest due on the bonds already sold to fight inflation must be financed, at least in part, by seignorage, requiring the creation of additional base money.”
Table ESIII-4, US, Major Foreign Holders of Treasury Securities $ Billions at End of Period
| Jan 2013 | Dec 2012 | Jan 2012 | |
| Total | 5616.5 | 5573.8 | 5056.8 |
| China | 1264.5 | 1220.4 | 1166.2 |
| Japan | 1115.2 | 1111.2 | 1080.8 |
| Oil Exporters | 262.0 | 262.0 | 268.5 |
| Brazil | 253.4 | 253.3 | 228.2 |
| Caribbean Banking Centers | 236.9 | 266.2 | 223.8 |
| Taiwan | 196.6 | 195.4 | 178.5 |
| Switzerland | 192.7 | 195.4 | 145.8 |
| Russia | 162.9 | 161.5 | 145.7 |
| Luxembourg | 144.7 | 155.0 | 136.6 |
| Belgium | 143.5 | 138.8 | 131.5 |
| Hong Kong | 142.9 | 141.9 | 134.2 |
| United Kingdom | 135.7 | 132.6 | 115.7 |
| Foreign Official Holdings | 4089.7 | 4032.2 | 3688.3 |
| A. Treasury Bills | 377.1 | 372.7 | 350.4 |
| B. Treasury Bonds and Notes | 3712.6 | 3659.5 | 3337.8 |
Source: http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/ticsec2.aspx#ussecs
ESIV World Inflation Waves. This section provides analysis and data on world inflation waves. There are detailed sections in the main text. IIA Appendix: Transmission of Unconventional Monetary Policy provides more technical analysis. Section IIB United States Inflation analyzes inflation in the United States in two subsections: IIC Long-term US Inflation and IID Current US Inflation. There is similar lack of reality in economic history as in monetary policy based on fear of deflation as analyzed in Subsection IIAE Theory and Reality of Economic History and Monetary Policy Based on Fear of Deflation
The critical fact of current world financial markets is the combination of “unconventional” monetary policy with intermittent shocks of financial risk aversion. There are two interrelated unconventional monetary policies. First, unconventional monetary policy consists of (1) reducing short-term policy interest rates toward the “zero bound” such as fixing the fed funds rate at 0 to ¼ percent by decision of the Federal Open Market Committee (FOMC) since Dec 16, 2008 (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm). Second, unconventional monetary policy also includes a battery of measures to also reduce long-term interest rates of government securities and asset-backed securities such as mortgage-backed securities.
When inflation is low, the central bank lowers interest rates to stimulate aggregate demand in the economy, which consists of consumption and investment. When inflation is subdued and unemployment high, monetary policy would lower interest rates to stimulate aggregate demand, reducing unemployment. When interest rates decline to zero, unconventional monetary policy would consist of policies such as large-scale purchases of long-term securities to lower their yields. A major portion of credit in the economy is financed with long-term asset-backed securities. Loans for purchasing houses, automobiles and other consumer products are bundled in securities that in turn are sold to investors. Corporations borrow funds for investment by issuing corporate bonds. Loans to small businesses are also financed by bundling them in long-term bonds. Securities markets bridge the needs of higher returns by savers obtaining funds from investors that are channeled to consumers and business for consumption and investment. Lowering the yields of these long-term bonds could lower costs of financing purchases of consumer durables and investment by business. The essential mechanism of transmission from lower interest rates to increases in aggregate demand is portfolio rebalancing. Withdrawal of bonds in a specific maturity segment or directly in a bond category such as currently mortgage-backed securities causes reductions in yield that are equivalent to increases in the prices of the bonds. There can be secondary increases in purchases of those bonds in private portfolios in pursuit of their increasing prices. Lower yields translate into lower costs of buying homes and consumer durables such as automobiles and also lower costs of investment for business. There are two additional intended routes of transmission.
1. Unconventional monetary policy or its expectation can increase stock market valuations (Bernanke 2010WP). Increases in equities traded in stock markets can augment perceptions of the wealth of consumers inducing increases in consumption.
2. Unconventional monetary policy causes devaluation of the dollar relative to other currencies, which can cause increases in net exports of the US that increase aggregate economic activity (Yellen 2011AS).
Monetary policy can lower short-term interest rates quite effectively. Lowering long-term yields is somewhat more difficult. The critical issue is that monetary policy cannot ensure that increasing credit at low interest cost increases consumption and investment. There is a large variety of possible allocation of funds at low interest rates from consumption and investment to multiple risk financial assets. Monetary policy does not control how investors will allocate asset categories. A critical financial practice is to borrow at low short-term interest rates to invest in high-risk, leveraged financial assets. Investors may increase in their portfolios asset categories such as equities, emerging market equities, high-yield bonds, currencies, commodity futures and options and multiple other risk financial assets including structured products. If there is risk appetite, the carry trade from zero interest rates to risk financial assets will consist of short positions at short-term interest rates (or borrowing) and short dollar assets with simultaneous long positions in high-risk, leveraged financial assets such as equities, commodities and high-yield bonds. Low interest rates may induce increases in valuations of risk financial assets that may fluctuate in accordance with perceptions of risk aversion by investors and the public. During periods of muted risk aversion, carry trades from zero interest rates to exposures in risk financial assets cause temporary waves of inflation that may foster instead of preventing financial instability. During periods of risk aversion such as fears of disruption of world financial markets and the global economy resulting from collapse of the European Monetary Union, carry trades are unwound with sharp deterioration of valuations of risk financial assets. More technical discussion is in IA Appendix: Transmission of Unconventional Monetary Policy.
Symmetric inflation targets appear to have been abandoned in favor of a self-imposed single jobs mandate of easing monetary policy even with the economy growing at or close to potential output. Monetary easing by unconventional measures is now open ended in perpetuity, or QE→∞, as provided in the statement of the meeting of the Federal Open Market Committee (FOMC) on Sep 13, 2012 (http://www.federalreserve.gov/newsevents/press/monetary/20120913a.htm):
“To support a stronger economic recovery and to help ensure that inflation, over time, is at the rate most consistent with its dual mandate, the Committee agreed today to increase policy accommodation by purchasing additional agency mortgage-backed securities at a pace of $40 billion per month. The Committee also will continue through the end of the year its program to extend the average maturity of its holdings of securities as announced in June, and it is maintaining its existing policy of reinvesting principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities. These actions, which together will increase the Committee’s holdings of longer-term securities by about $85 billion each month through the end of the year, should put downward pressure on longer-term interest rates, support mortgage markets, and help to make broader financial conditions more accommodative.
To support continued progress toward maximum employment and price stability, the Committee expects that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the economic recovery strengthens.”
Charles Evans, President of the Federal Reserve Bank of Chicago, proposed an “economic state-contingent policy” or “7/3” approach (Evans 2012 Aug 27):
“I think the best way to provide forward guidance is by tying our policy actions to explicit measures of economic performance. There are many ways of doing this, including setting a target for the level of nominal GDP. But recognizing the difficult nature of that policy approach, I have a more modest proposal: I think the Fed should make it clear that the federal funds rate will not be increased until the unemployment rate falls below 7 percent. Knowing that rates would stay low until significant progress is made in reducing unemployment would reassure markets and the public that the Fed would not prematurely reduce its accommodation.
Based on the work I have seen, I do not expect that such policy would lead to a major problem with inflation. But I recognize that there is a chance that the models and other analysis supporting this approach could be wrong. Accordingly, I believe that the commitment to low rates should be dropped if the outlook for inflation over the medium term rises above 3 percent.
The economic conditionality in this 7/3 threshold policy would clarify our forward policy intentions greatly and provide a more meaningful guide on how long the federal funds rate will remain low. In addition, I would indicate that clear and steady progress toward stronger growth is essential.”
Evans (2012Nov27) modified the “7/3” approach to a “6.5/2.5” approach:
“I have reassessed my previous 7/3 proposal. I now think a threshold of 6-1/2 percent for the unemployment rate and an inflation safeguard of 2-1/2 percent, measured in terms of the outlook for total PCE (Personal Consumption Expenditures Price Index) inflation over the next two to three years, would be appropriate.”
The Federal Open Market Committee (FOMC) decided at its meeting on Dec 12, 2012 to implement the “6.5/2.5” approach (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm):
“To support continued progress toward maximum employment and price stability, the Committee expects that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the asset purchase program ends and the economic recovery strengthens. In particular, the Committee decided to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that this exceptionally low range for the federal funds rate will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee’s 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored.”
The actual objective is attempting to bring the unemployment rate to 5.2 percent but because of the lag in effect of monetary policy impulses on income and prices policy uses “projections” such that the target of monetary policy is a forecast of unemployment and inflation. Unconventional monetary policy will remain in perpetuity, or QE→∞, changing to a “growth mandate.” There are two reasons explaining unconventional monetary policy of QE→∞: insufficiency of job creation to reduce unemployment/underemployment at current rates of job creation; and growth of GDP at 1.5 percent, which is well below 3.0 percent estimated by Lucas (2011May) from 1870 to 2010. Unconventional monetary policy interprets the dual mandate of low inflation and maximum employment as mainly a “growth mandate” of forcing economic growth in the US at a rate that generates full employment. A hurdle to this “growth mandate” is that the US economy grew at 6.2 percent on average during cyclical expansions in the postwar period while growth has been at only 2.1 percent on average in the cyclical expansion in the 14 quarters from IIIQ2009 to IVQ2012. Zero interest rates and quantitative easing have not provided the impulse for growth and were not required in past successful cyclical expansions.
First, total nonfarm payroll employment seasonally adjusted (SA) increased 236,000 in Feb 2013 and private payroll employment rose 246,000. The number of nonfarm jobs and private jobs created has been declining in 2012 from 311,000 in Jan 2012 to 87,000 in Jun, 138,000 in Sep, 160,000 in Oct, 247,000 in Nov and 219,000 in Dec 2012 for total nonfarm jobs and from 323,000 in Jan 2012 to 78,000 in Jun, 118,000 in Sep, 217,000 in Oct, 256,000 in Nov and 224,000 in Dec 2012 for private jobs. Average new nonfarm jobs in the quarter Dec 2011 to Feb 2012 were 270,667 per month, declining to average 157,273 per month in the eleven months from Mar 2012 to Jan 2013. Average new private jobs in the quarter Dec 2011 to Feb 2012 were 279,000 per month, declining to average 165,545 per month in the eleven months from Mar 2012 to Jan 2013. The number of 140,000 new private new jobs created in Jan 2013 is lower than the average 165,545 per month in Mar 2012 to Jan 2013. New farm jobs created in Feb 2013 were 236,000 and 246,000 in private jobs, which exceeds the average for the prior eleven months. The US labor force increased from 153.617 million in 2011 to 154.975 million in 2012 by 1.358 million or 113,167 per month. The average increase of nonfarm jobs in the six months from Sep 2012 to Feb 2013 was 186,500, which is a rate of job creation inadequate to reduce significantly unemployment and underemployment in the United States because of 113,167 new entrants in the labor force per month with 30.8 million unemployed or underemployed. The difference between the average increase of 186,500 new private nonfarm jobs per month in the US from Sep 2012 to Feb 2013 and the 113,167 average monthly increase in the labor force from 2011 to 2012 is 73,333 monthly new jobs net of absorption of new entrants in the labor force. There are 30.8 million in job stress in the US currently. The provision of 73,333 new jobs per month net of absorption of new entrants in the labor force would require 419 months to provide jobs for the unemployed and underemployed (30.761 million divided by 73,333) or 34.9 years (419 divided by 12). The civilian labor force of the US in Feb 2013 not seasonally adjusted stood at 154.727 million with 12.500 million unemployed or effectively 19.849 million unemployed in this blog’s calculation by inferring those who are not searching because they believe there is no job for them for effective labor force of 162.076 million. Reduction of one million unemployed at the current rate of job creation without adding more unemployment requires 1.1 years (1 million divided by product of 73,333 by 12, which is 879,996). Reduction of the rate of unemployment to 5 percent of the labor force would be equivalent to unemployment of only 7.736 million (0.05 times labor force of 154.727 million) for new net job creation of 4.764 million (12.500 million unemployed minus 7.736 million unemployed at rate of 5 percent) that at the current rate would take 5.4 years (4.764 million divided by 879,996). Under the calculation in this blog there are 19.849 million unemployed by including those who ceased searching because they believe there is no job for them and effective labor force of 162.076 million. Reduction of the rate of unemployment to 5 percent of the labor force would require creating 12.614 million jobs net of labor force growth that at the current rate would take 13.3 years (19.849 million minus 0.05(162.076 million) or 11.745 million divided by 879,996, using LF PART 66.2% and Total UEM in Table I-4). These calculations assume that there are no more recessions, defying United States economic history with periodic contractions of economic activity when unemployment increases sharply. The number employed in the US fell from 147.118 million in Nov 2007 to 142.228 million in Feb 2013, by 4.890 million, or decline of 3.3 percent, while the noninstitutional population increased from 232.939 million in Nov 2007 to 244.828 million in Feb 2013, by 11.889 million or increase of 5.1 percent, using not seasonally adjusted data. There is actually not sufficient job creation to merely absorb new entrants in the labor force because of those dropping from job searches, worsening the stock of unemployed or underemployed in involuntary part-time jobs.
Second, calculations show that actual growth is around 1.6 to 2.0 percent per year. This rate is well below 3 percent per year in trend from 1870 to 2010, which has been always recovered after events such as wars and recessions (Lucas 2011May). Growth is not only mediocre but sharply decelerating to a rhythm that is not consistent with reduction of unemployment and underemployment of 30.8 million people corresponding to 19.2 percent of the effective labor force of the United States (http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). In the four quarters of 2011 and the four quarters of 2012, US real GDP grew at the seasonally-adjusted annual equivalent rates of 0.1 percent in the first quarter of 2011 (IQ2011), 2.5 percent in IIQ2011, 1.3 percent in IIIQ2011, 4.1 percent in IVQ2011, 2.0 percent in IQ2012, 1.3 percent in IIQ2012, 3.1 percent in IIIQ2012 and revised 0.1 percent in IVQ2012. GDP growth in IIIQ2012 was revised from 2.7 percent seasonally adjusted annual rate (SAAR) to 3.1 percent but mostly because of contribution of 0.73 percentage points of inventory accumulation and one-time contribution of 0.64 percentage points of expenditures in national defense that without them would have reduced growth from 3.1 percent to 1.73 percent. Equally, GDP growth in IVQ2012 is measured in the advanced estimate as 0.1 percent but mostly because of deduction of divestment of inventories of 1.55 percentage points and deduction of one-time national defense expenditures of 1.28 percentage points. The annual equivalent rate of growth of GDP for the four quarters of 2011 and the four quarters of 2012 is 2.0 percent, obtained as follows. Discounting 0.1 percent to one quarter is 0.025 percent {[(1.001)1/4 -1]100 = 0.025}; discounting 2.5 percent to one quarter is 0.62 percent {[(1.025)1/4 – 1]100}; discounting 1.3 percent to one quarter is 0.32 percent {[(1.013)1/4 – 1]100}; discounting 4.1 percent to one quarter is 1.0 {[(1.04)1/4 -1]100; discounting 2.0 percent to one quarter is 0.50 percent {[(1.020)1/4 -1]100); discounting 1.3 percent to one quarter is 0.32 percent {[(1.013)1/4 -1]100}; discounting 3.1 percent to one quarter is 0.77 {[(1.031)1/4 -1]100); and discounting 0.1 percent to one quarter is 0.025 percent {[(1.001)1/4 – 1]100}. Real GDP growth in the four quarters of 2011 and the four quarters of 2012 accumulated to 3.6 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.00025) - 1]100 = 3.6%}. This is equivalent to growth from IQ2011 to IVQ2012 obtained by dividing the seasonally-adjusted annual rate (SAAR) of IVQ2012 of $13,656.8 billion by the SAAR of IVQ2010 of $13,181.2 (http://www.bea.gov/iTable/iTable.cfm?ReqID=9&step=1) and expressing as percentage {[($13,658.8/$13,181.2) - 1]100 = 3.6%}. The growth rate in annual equivalent for the four quarters of 2011 and the four quarters of 2012 is 1.8 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.00025)4/8 -1]100 = 1.8%], or {[($13,656.8/$13,181.2)]4/8-1]100 = 1.8%} dividing the SAAR of IVQ2012 by the SAAR of IVQ2010 in Table II-6 below, obtaining the average for eight quarters and the annual average for one year of four quarters. Growth in the four quarters of 2012 accumulates to 1.6 percent {[(1.02)1/4(1.013)1/4(1.031)1/4(1.001)1/4 -1]100 = 1.6%}. This is equivalent to dividing the SAAR of $13,656.8 billion for IVQ2012 by the SAAR of $13,441.0 billion in IVQ2011 to obtain 1.6 percent {[($13,656.8/$13,441.0) – 1]100 = 1.6%}. The US economy is still close to a standstill especially considering the GDP report in detail. Excluding growth at the SAAR of 2.5 percent in IIQ2011 and 4.1 percent in IVQ2011 while converting growth in IIIQ2012 to 1.73 percent by deducting from 3.1 percent one-time inventory accumulation of 0.73 percentage points and national defense expenditures of 0.64 percentage points and converting growth in IVQ2012 by adding 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditure reductions to obtain 2.84 percent, the US economy grew at 1.5 percent in the remaining six quarters {[(1.00025x1.0032x1.005x1.0032x1.0043x1.0070)4/6 – 1]100 = 1.5%} with declining growth trend in three consecutive quarters from 4.1 percent in IVQ2011, to 2.0 percent in IQ2012, 1.3 percent in IIQ2012, 3.1 percent in IIIQ2012 that is more like 1.73 percent without inventory accumulation and national defense expenditures and 0.1 percent in IVQ2012 that is more likely 2.84 percent by adding 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditures. Weakness of growth is more clearly shown by adjusting the exceptional one-time contributions to growth from items that are not aggregate demand: 2.53 percentage points contributed by inventory change to growth of 4.1 percent in IVQ2011; 0.64 percentage points contributed by expenditures in national defense together with 0.73 points of inventory accumulation to growth of 3.1 percent in IIIQ2012; and deduction of 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditure reductions. The Bureau of Economic Analysis (BEA) of the US Department of Commerce released on Thus Feb 28, 2012, the second estimate of GDP for IVQ2012 at 0.1 percent seasonally-adjusted annual rate (SAAR) (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp4q12_2nd.pdf). In the four quarters of 2012, the US economy is growing at the annual equivalent rate of 2.0 percent {([(1.021/4(1.013)1/4(1.0173)1/4(1.0284)1/4]-1)100 = 2.0%} by excluding inventory accumulation of 0.73 percentage points and exceptional defense expenditures of 0.64 percentage points from growth 3.1 percent at SAAR in IIIQ2012 to obtain adjusted 1.73 percent SSAR and adding 1.28 percentage points of national defense expenditure reductions and 1.55 percentage points of inventory divestment to growth of 0.1 percent SAAR in IVQ2012 to obtain 2.84 percent.
In fact, it is evident to the public that this policy will be abandoned if inflation costs rise. There is concern of the production and employment costs of controlling future inflation. Even if there is no inflation, QE→∞ cannot be abandoned because of the fear of rising interest rates. The economy would operate in an inferior allocation of resources and suboptimal growth path, or interior point of the production possibilities frontier where the optimum of productive efficiency and wellbeing is attained, because of the distortion of risk/return decisions caused by perpetual financial repression. Not even a second-best allocation is feasible with the shocks to efficiency of financial repression in perpetuity.
Table ESIV-1 provides annual equivalent rates of inflation for producer price indexes followed in this blog of countries and regions that account for close to three quarters of world output. The behavior of the US producer price index in 2011 and into 2012-2013 shows neatly multiple waves. (1) In Jan-Apr 2011, without risk aversion, US producer prices rose at the annual equivalent rate of 10.0 percent. (2) After risk aversion, producer prices increased in the US at the annual equivalent rate of 1.8 percent in May-Jun 2011. (3) From Jul to Sep 2011, under alternating episodes of risk aversion, producer prices increased at the annual equivalent rate of 4.9 percent. (4) Under the pressure of risk aversion because of the European debt crisis US producer prices increased at the annual equivalent rate of 0.6 percent in Oct-Nov 2011. (5) From Dec 2011 to Jan 2012, US producer were flat at the annual equivalent rate of 0.0 percent. (6) Inflation of producer prices returned with 2.4 percent annual equivalent in Feb-Mar 2012. (7) With return of risk aversion from the European debt crisis, producer prices fell at the annual equivalent rate of 4.7 percent in Apr-May 2012. (8) New positions in commodity futures even with continuing risk aversion caused annual equivalent inflation of 3.0 percent in Jun-Jul 2012. (9) Relaxed risk aversion because of announcement of sovereign bond-buying by the European Central Bank induced carry trades that resulted in annual equivalent producer price inflation in the US of 12.7 percent in Aug-Sep 2012. (10) Renewed risk aversion caused unwinding of carry trades of zero interest rates to commodity futures exposures with annual equivalent inflation of minus 3.5 percent in Oct-Dec 2012. (10) In Jan-Feb 2013, producer prices rose at the annual equivalent rate of 5.5 percent with more relaxed risk aversion at the margin. Resolution of the European debt crisis if there is not an unfavorable growth event with political development in China would result in jumps of valuations of risk financial assets. Increases in commodity prices would cause the same high producer price inflation experienced in Jan-Apr 2011 and Aug-Sep 2012. An episode of exploding commodity prices could ignite inflationary expectations that would result in an inflation phenomenon of costly resolution. There are nine producer-price indexes in Table ESIV-1 for seven countries (two for the UK) and one region (euro area) showing very similar behavior. Zero interest rates without risk aversion cause increases in commodity prices that in turn increase input and output prices. Producer price inflation rose at very high rates during the first part of 2011 for the US, Japan, China, Euro Area, Germany, France, Italy and the UK when risk aversion was contained. With the increase in risk aversion in May and Jun 2011, inflation moderated because carry trades were unwound. Producer price inflation returned after Jul 2011, with alternating bouts of risk aversion. In the final months of the year producer price inflation collapsed because of the disincentive to exposures in commodity futures resulting from fears of resolution of the European debt crisis. There is renewed worldwide inflation in the early part of 2012 with subsequent collapse because of another round of sharp risk aversion. Sharp worldwide jump in producer prices occurred recently as a result of the combination of zero interest rates forever or QE→∞ with temporarily relaxed risk aversion. Producer prices were moderating or falling in the final months of 2012 because of renewed risk aversion that causes unwinding of carry trades from zero interest rates to commodity futures exposures. In the first months of 2013, new carry trades caused higher worldwide inflation. Unconventional monetary policy fails in stimulating the overall real economy, merely introducing undesirable instability as monetary authorities cannot control allocation of floods of money at zero interest rates to carry trades into risk financial assets. The economy is constrained in a suboptimal allocation of resources that is perpetuated along a continuum of short-term periods results in long-term or dynamic inefficiency in the form of a trajectory of economic activity that is lower than what would be attained with rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html).
Table ESIV-1, Annual Equivalent Rates of Producer Price Indexes
| INDEX 2011-2013 | AE ∆% |
| US Producer Price Index | |
| AE ∆% Jan-Feb 2013 | 5.5 |
| AE ∆% Oct-Dec 2012 | -3.5 |
| AE ∆% Aug-Sep 2012 | 12.7 |
| AE ∆% Jun-Jul 2012 | 3.0 |
| AE ∆% Apr-May 2012 | -4.7 |
| AE ∆% Feb-Mar 2012 | 2.4 |
| AE ∆% Dec 2011-Jan-2012 | 0.0 |
| AE ∆% Oct-Nov 2011 | 0.6 |
| AE ∆% Jul-Sep 2011 | 4.9 |
| AE ∆% May-Jun 2011 | 1.8 |
| AE ∆% Jan-Apr 2011 | 10.0 |
| Japan Corporate Goods Price Index | |
| AE ∆% Dec 2012-Feb 2013 | 3.7 |
| AE ∆% Oct-Nov 2012 | -1.8 |
| AE ∆% Aug-Sep 2012 | 2.4 |
| AE ∆% May-Jul 2012 | -5.8 |
| AE ∆% Feb-Apr 2012 | 2.4 |
| AE ∆% Dec 2011-Jan 2012 | -0.6 |
| AE ∆% Jul-Nov 2011 | -2.2 |
| AE ∆% May-Jun 2011 | -1.2 |
| AE ∆% Jan-Apr 2011 | 5.9 |
| China Producer Price Index | |
| AE ∆% Jan-Feb 2013 | 2.4 |
| AE ∆% Nov-Dec 2012 | -1.2 |
| AE ∆% Oct 2012 | 2.4 |
| AE ∆% May-Sep 2012 | -5.8 |
| AE ∆% Feb-Apr 2012 | 2.4 |
| AE ∆% Dec 2011-Jan 2012 | -2.4 |
| AE ∆% Jul-Nov 2011 | -3.1 |
| AE ∆% Jan-Jun 2011 | 6.4 |
| Euro Zone Industrial Producer Prices | |
| AE ∆% Jan 2013 | 7.4 |
| AE ∆% Nov-Dec 2012 | -2.4 |
| AE ∆% Sep-Oct 2012 | 1.2 |
| AE ∆% Jul-Aug 2012 | 7.4 |
| AE ∆% Apr-Jun 2012 | -3.2 |
| AE ∆% Jan-Mar 2012 | 8.3 |
| AE ∆% Oct-Dec 2011 | 0.4 |
| AE ∆% Jul-Sep 2011 | 2.4 |
| AE ∆% May-Jun 2011 | -1.2 |
| AE ∆% Jan-Apr 2011 | 11.4 |
| Germany Producer Price Index | |
| AE ∆% Jan 2013 | 10.0 NSA 2.4 SA |
| AE ∆% Oct-Dec 2012 | -1.6 NSA 1.6 SA |
| AE ∆% Aug-Sep 2012 | 4.9 NSA 5.5 SA |
| AE ∆% May-Jul 2012 | -2.8 NSA –0.4 SA |
| AE ∆% Feb-Apr 2012 | 4.9 NSA 0.8 SA |
| AE ∆% Dec 2011-Jan 2012 | 1.2 NSA 0.0 SA |
| AE ∆% Oct-Nov 2011 | 1.8 NSA 3.7 SA |
| AE ∆% Jul-Sep 2011 | 2.8 NSA 3.7 SA |
| AE ∆% May-Jun 2011 | 0.6 NSA 3.7 SA |
| AE ∆% Jan-Apr 2011 | 10.4 NSA 6.5 SA |
| France Producer Price Index for the French Market | |
| AE ∆% Jan 2013 | 6.2 |
| AE ∆% Nov-Dec 2012 | -4.7 |
| AE ∆% Jul-Oct 2012 | 8.1 |
| AE ∆% Apr-Jun 2012 | -8.1 |
| AE ∆% Jan-Mar 2012 | 8.7 |
| AE ∆% Oct-Dec 2011 | 2.4 |
| AE ∆% Jul-Sep 2011 | 2.8 |
| AE ∆% May-Jun 2011 | -3.5 |
| AE ∆% Jan-Apr 2011 | 11.7 |
| Italy Producer Price Index | |
| AE ∆% Sep 2012-Jan 2013 | -4.2 |
| AE ∆% Jul-Aug 2012 | 7.4 |
| AE ∆% May-Jun 2012 | -0.6 |
| AE ∆% Mar-Apr 2012 | 6.2 |
| AE ∆% Jan-Feb 2012 | 8.1 |
| AE ∆% Oct-Dec 2011 | 1.2 |
| AE ∆% Jul-Sep 2011 | 4.5 |
| AE ∆% May-Jun 2011 | 1.8 |
| AE ∆% Jan-April 2011 | 10.4 |
| UK Output Prices | |
| AE ∆% Jan 2013 | 2.4 |
| AE ∆% Nov-Dec 2012 | -2.4 |
| AE ∆% Jul-Oct 2012 | 4.0 |
| AE ∆% May-Jun 2012 | -5.3 |
| AE ∆% Feb-Apr 2012 | 7.9 |
| AE ∆% Nov 2011-Jan-2012 | 1.6 |
| AE ∆% May-Oct 2011 | 2.0 |
| AE ∆% Jan-Apr 2011 | 12.0 |
| UK Input Prices | |
| AE ∆% Dec 2012-Jan 2013 | 8.1 |
| AE ∆% Sep-Nov 2012 | 1.6 |
| AE ∆% Jul-Aug 2012 | 14.0 |
| AE ∆% Apr-Jun 2012 | -21.9 |
| AE ∆% Jan-Mar 2012 | 18.1 |
| AE ∆% Nov-Dec 2011 | -1.2 |
| AE ∆% May-Oct 2011 | -3.1 |
| AE ∆% Jan-Apr 2011 | 35.6 |
AE: Annual Equivalent
Sources:
http://www.stats.gov.cn/enGliSH/
http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database
https://www.destatis.de/EN/Homepage.html
http://www.insee.fr/en/default.asp
http://www.ons.gov.uk/ons/index.html
Similar world inflation waves are in the behavior of consumer price indexes of six countries and the euro zone in Table ESIV-2. US consumer price inflation shows similar waves. (1) Under risk appetite in Jan-Apr 2011 consumer prices increased at the annual equivalent rate of 4.6 percent. (2) Risk aversion caused the collapse of inflation to annual equivalent 3.0 percent in May-Jun 2011. (3) Risk appetite drove the rate of consumer price inflation in the US to 3.3 percent in Jul-Sep 2011. (4) Gloomier views of carry trades caused the collapse of inflation in Oct-Nov 2011 to annual equivalent 0.6 percent. (5) Consumer price inflation resuscitated with increased risk appetite at annual equivalent of 1.2 percent in Dec 2011 to Jan 2012. (6) Consumer price inflation returned at 2.4 percent annual equivalent in Feb-Apr 2012. (7) Under renewed risk aversion, annual equivalent consumer price inflation in the US was 0.0 percent in May-Jul 2012. (8) Inflation jumped to annual equivalent 4.9 percent in Aug-Oct 2012. (9) Unwinding of carry trades caused negative annual equivalent inflation of 0.8 percent in Nov 2012-Jan 2013 but some countries experienced higher inflation in Dec 2012 and Jan 2013. (10) Inflation jumped again with annual equivalent inflation of 8.7 percent in Feb 2013 in a mood of relaxed risk aversion. Inflationary expectations can be triggered in one of these episodes of accelerating inflation because of commodity carry trades induced by unconventional monetary policy of zero interest rates in perpetuity or QE→∞ or almost continuous time. Alternating episodes of increase and decrease of inflation introduce uncertainty in household planning that frustrates consumption and home buying. Announcement of purchases of impaired sovereign bonds by the European Central Bank relaxed risk aversion that induced carry trades into commodity exposures, increasing prices of food, raw materials and energy. There is similar behavior in all the other consumer price indexes in Table ESIV-2. China’s CPI increased at annual equivalent 8.3 percent in Jan-Mar 2011, 2.0 percent in Apr-Jun, 2.9 percent in Jul-Dec and resuscitated at 5.8 percent annual equivalent in Dec 2011 to Mar 2012, declining to minus 3.9 percent in Apr-Jun 2012 but resuscitating at 4.1 percent in Jul-Sep 2012, declining to minus 1.2 percent in Oct 2012 and 0.0 percent in Oct-Nov 2012. High inflation in China at annual equivalent 5.5 percent in Nov-Dec 2012 is attributed to inclement winter weather that caused increases in food prices. Continuing pressure of food prices caused annual equivalent inflation of 12.2 percent in China in Dec 2012 to Feb 2013. The euro zone harmonized index of consumer prices (HICP) increased at annual equivalent 5.2 percent in Jan-Apr 2011, minus 2.4 percent in May-Jul 2011, 4.3 percent in Aug-Dec 2011, minus 3.0 percent in Dec 2011-Jan 2012 and then 9.6 percent in Feb-Apr 2012, falling to minus 2.8 percent annual equivalent in May-Jul 2012 but resuscitating at 5.3 percent in Aug-Oct 2012. The recent shock of risk aversion forced minus 2.4 percent annual equivalent in Nov 2012. As in several European countries, annual equivalent inflation jumped to 4.9 percent in the euro area in Dec 2012. The HICP price index fell at annual equivalent 11.4 percent in Jan 2013 and increased at 4.9 percent in Feb 2013. The price indexes of the largest members of the euro zone, Germany, France and Italy, and the euro zone as a whole, exhibit the same inflation waves. The United Kingdom CPI increased at annual equivalent 6.5 percent in Jan-Apr 2011, falling to only 0.4 percent in May-Jul 2011 and then increasing at 4.6 percent in Aug-Nov 2011. UK consumer prices fell at 0.6 percent annual equivalent in Dec 2011 to Jan 2012 but increased at 6.2 percent annual equivalent from Feb to Apr 2012. In May-Jun 2012, with renewed risk aversion, UK consumer prices fell at the annual equivalent rate of minus 3.0 percent. Inflation returned in the UK at average annual equivalent of 4.5 percent in Jul-Dec 2012 with inflation in Oct 2012 caused mostly by increases of university tuition fees. Inflation returned at 4.5 percent annual equivalent in Jul-Dec 2012 and was higher in annual equivalent producer price inflation in the UK in Jul-Oct 2012 at 4.0 percent for output prices and 14.0 percent for input prices in Jul-Aug 2012 (see Table ESIV-1). Consumer prices fell at annual equivalent 5.8 percent in Jan 2013.
Table ESIV-2, Annual Equivalent Rates of Consumer Price Indexes
| Index 2011-2013 | AE ∆% |
| US Consumer Price Index | |
| AE ∆% Feb 2013 | 8.7 |
| AE ∆% Nov 2012-Jan 2013 | -0.8 |
| AE ∆% Aug-Oct 2012 | 4.9 |
| AE ∆% May-Jul 2012 | 0.0 |
| AE ∆% Feb-Apr 2012 | 2.4 |
| AE ∆% Dec 2011-Jan 2012 | 1.2 |
| AE ∆% Oct-Nov 2011 | 0.6 |
| AE ∆% Jul-Sep 2011 | 3.3 |
| AE ∆% May-Jun 2011 | 3.0 |
| AE ∆% Jan-Apr 2011 | 4.6 |
| China Consumer Price Index | |
| AE ∆% Dec 2012-Feb 2013 | 12.2 |
| AE ∆% Oct-Nov 2012 | 0.0 |
| AE ∆% Jul-Sep 2012 | 4.1 |
| AE ∆% Apr-Jun 2012 | -3.9 |
| AE ∆% Dec 2011-Mar 2012 | 5.8 |
| AE ∆% Jul-Nov 2011 | 2.9 |
| AE ∆% Apr-Jun 2011 | 2.0 |
| AE ∆% Jan-Mar 2011 | 8.3 |
| Euro Zone Harmonized Index of Consumer Prices | |
| AE ∆% Feb 2013 | 4.9 |
| AE ∆% Jan 2013 | -11.4 |
| AE ∆% Dec 2012 | 4.9 |
| AE ∆% Nov 2012 | -2.4 |
| AE ∆% Aug-Oct 2012 | 5.3 |
| AE ∆% May-Jul 2012 | -2.8 |
| AE ∆% Feb-Apr 2012 | 9.6 |
| AE ∆% Dec 2011-Jan 2012 | -3.0 |
| AE ∆% Aug-Nov 2011 | 4.3 |
| AE ∆% May-Jul 2011 | -2.4 |
| AE ∆% Jan-Apr 2011 | 5.2 |
| Germany Consumer Price Index | |
| AE ∆% Feb 2013 | 7.4 NSA 1.2 SA |
| AE ∆% Jan 2013 | -5.8 NSA –1.2 SA |
| AE ∆% Sep-Dec 2012 | 1.5 NSA 1.2 SA |
| AE ∆% Jul-Aug 2012 | 4.9 NSA 3.7 SA |
| AE ∆% May-Jun 2012 | -1.2 NSA 1.2 SA |
| AE ∆% Feb-Apr 2012 | 4.5 NSA 2.0 SA |
| AE ∆% Dec 2011-Jan 2012 | 0.6 NSA 1.8 SA |
| AE ∆% Jul-Nov 2011 | 1.7 NSA 1.9 SA |
| AE ∆% May-Jun 2011 | 0.6 NSA 3.0 SA |
| AE ∆% Feb-Apr 2011 | 3.0 NSA 2.4 SA |
| France Consumer Price Index | |
| AE ∆% Feb 2013 | 3.7 |
| AE ∆% Nov 2012-Jan 2013 | -1.6 |
| AE ∆% Aug-Oct 2012 | 2.4 |
| AE ∆% May-Jul 2012 | -2.0 |
| AE ∆% Feb-Apr 2012 | 5.3 |
| AE ∆% Dec 2011-Jan 2012 | 0.0 |
| AE ∆% Aug-Nov 2011 | 2.7 |
| AE ∆% May-Jul 2011 | -0.8 |
| AE ∆% Jan-Apr 2011 | 4.3 |
| Italy Consumer Price Index | |
| AE ∆% Dec 2012-Feb 2013 | 2.0 |
| AE ∆% Sep-Nov 2012 | -0.8 |
| AE ∆% Jul-Aug 2012 | 3.0 |
| AE ∆% May-Jun 2012 | 1.2 |
| AE ∆% Feb-Apr 2012 | 5.7 |
| AE ∆% Dec 2011-Jan 2012 | 4.3 |
| AE ∆% Oct-Nov 2011 | 3.0 |
| AE ∆% Jul-Sep 2011 | 2.4 |
| AE ∆% May-Jun 2011 | 1.2 |
| AE ∆% Jan-Apr 2011 | 4.9 |
| UK Consumer Price Index | |
| AE ∆% Jan 2013 | -5.8 |
| AE ∆% Jul-Dec 2012 | 4.5 |
| AE ∆% May-Jun 2012 | -3.0 |
| AE ∆% Feb-Apr 2012 | 6.2 |
| AE ∆% Dec 2011-Jan 2012 | -0.6 |
| AE ∆% Aug-Nov 2011 | 4.6 |
| AE ∆% May-Jul 2011 | 0.4 |
| AE ∆% Jan-Apr 2011 | 6.5 |
AE: Annual Equivalent
Sources:
http://www.stats.gov.cn/enGliSH/
http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database
https://www.destatis.de/EN/Homepage.html
http://www.insee.fr/en/default.asp
http://www.ons.gov.uk/ons/index.html
ESV Destruction of Household Wealth for Inflation Adjusted Loss of 10.9 Percent. The 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/default.htm http://www.federalreserve.gov/apps/fof/) is rich in valuable information. Table ESV-1, updated in this blog for every new quarterly release, shows the balance sheet of US households combined with nonprofit organizations in 2007, 2011 and 2012. The data show the strong shock to US wealth during the contraction. Assets fell from $80.4 trillion in 2007 to $74.0 trillion in 2011 even after nine consecutive quarters of growth beginning in IIIQ2009 (http://wwwdev.nber.org/cycles/cyclesmain.html http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html), for decline of $6.4 trillion or 7.5 percent. Assets stood at $79.5 trillion in 2012 for loss of $0.9 trillion relative to $80.4 trillion in 2007 or decline by 1.1 percent. Liabilities declined from $14.3 trillion in 2007 to $13.4 trillion in 2011 or by $854.6 billion equivalent to decline by 6.0 percent. Liabilities declined $822.3 billion or 5.8 percent from 2007 to 2012 but increased 0.2 percent from 2011 to 2012. Net worth shrank from $66.1 trillion in 2007 to $60.6 trillion in 2011, that is, $5.5 trillion equivalent to decline of 8.3 percent. Net worth declined $46.6 billion from 2007 to 2012 or 0.1 percent and increased 9.0 percent from 2011 to 2012. There was brutal decline from 2007 to 2012 of $3.6 trillion in real estate assets or by 15.2 percent. The National Association of Realtors estimated that the gains in net worth in homes by Americans were about $4 trillion between 2000 and 2005 (quoted in Pelaez and Pelaez, The Global Recession Risk (2007), 224-5).
Table ESV-1, US, Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars Outstanding End of Period, NSA
| 2007 | 2011 | 2012 | |
| Assets | 80,393.7 | 74,028.8 | 79,524.8 |
| Nonfinancial | 28,207.4 | 23,423.5 | 25,134.4 |
| Real Estate | 23,477.1 | 18,373.8 | 19,914.4 |
| Durable Goods | 4,468.3 | 4,732.2 | 4,885.6 |
| Financial | 52,186.2 | 50,605.3 | 54,390.5 |
| Deposits | 7,478.6 | 8,561.7 | 9,045.6 |
| Credit Market | 4,949.3 | 5,192.2 | 5,230.6 |
| Mutual Fund Shares | 4,589.2 | 4,384.2 | 5,300.9 |
| Equities Corporate | 9,710.2 | 8,850.1 | 9,770.5 |
| Equity Noncorporate | 9,325.8 | 7,650.7 | 8,079.1 |
| Pension | 13,477.7 | 13,133.2 | 14,060.7 |
| Liabilities | 14,275.4 | 13,420.8 | 13,453.1 |
| Home Mortgages | 10,579.7 | 9,660.7 | 9,430.5 |
| Consumer Credit | 2,528.8 | 2,627.4 | 2,779.2 |
| Net Worth | 66,118.3 | 60,608.0 | 66,071.7 |
Net Worth = Assets – Liabilities
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7. http://www.federalreserve.gov/releases/z1/default.htm
Table ESV-2 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2011 with apparent mitigation in 2012 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 71 percent of GDP, generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and 2012, real estate fell in value by $3.6 trillion and financial assets increased $2.2 trillion for net loss of real estate and financial assets of $1.4 trillion, explaining most of the drop in net worth of $46.6 billion obtained by adding the decrease in liabilities of $822.3 billion to the decrease of assets of $868.9 billion. Calculations show that actual economic growth in the US is around 1.6 to 2.0 percent per year. This rate is well below 3 percent per year in trend from 1870 to 2010, which has been always recovered after events such as wars and recessions (Lucas 2011May). Growth is not only mediocre but sharply decelerating to a rhythm that is not consistent with reduction of unemployment and underemployment of 30.8 million people corresponding to 19.0 percent of the effective labor force of the United States (http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). In the four quarters of 2011 and the four quarters of 2012, US real GDP grew at the seasonally-adjusted annual equivalent rates of 0.1 percent in the first quarter of 2011 (IQ2011), 2.5 percent in IIQ2011, 1.3 percent in IIIQ2011, 4.1 percent in IVQ2011, 2.0 percent in IQ2012, 1.3 percent in IIQ2012, 3.1 percent in IIIQ2012 and revised 0.1 percent in IVQ2012. GDP growth in IIIQ2012 was revised from 2.7 percent seasonally adjusted annual rate (SAAR) to 3.1 percent but mostly because of contribution of 0.73 percentage points of inventory accumulation and one-time contribution of 0.64 percentage points of expenditures in national defense that without them would have reduced growth from 3.1 percent to 1.73 percent. Equally, GDP growth in IVQ2012 is measured in the advanced estimate as 0.1 percent but mostly because of deduction of divestment of inventories of 1.55 percentage points and deduction of one-time national defense expenditures of 1.28 percentage points. The annual equivalent rate of growth of GDP for the four quarters of 2011 and the four quarters of 2012 is 2.0 percent, obtained as follows. Discounting 0.1 percent to one quarter is 0.025 percent {[(1.001)1/4 -1]100 = 0.025}; discounting 2.5 percent to one quarter is 0.62 percent {[(1.025)1/4 – 1]100}; discounting 1.3 percent to one quarter is 0.32 percent {[(1.013)1/4 – 1]100}; discounting 4.1 percent to one quarter is 1.0 {[(1.04)1/4 -1]100; discounting 2.0 percent to one quarter is 0.50 percent {[(1.020)1/4 -1]100); discounting 1.3 percent to one quarter is 0.32 percent {[(1.013)1/4 -1]100}; discounting 3.1 percent to one quarter is 0.77 {[(1.031)1/4 -1]100); and discounting 0.1 percent to one quarter is 0.025 percent {[(1.001)1/4 – 1]100}. Real GDP growth in the four quarters of 2011 and the four quarters of 2012 accumulated to 3.6 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.00025) - 1]100 = 3.6%}. This is equivalent to growth from IQ2011 to IVQ2012 obtained by dividing the seasonally-adjusted annual rate (SAAR) of IVQ2012 of $13,656.8 billion by the SAAR of IVQ2010 of $13,181.2 (http://www.bea.gov/iTable/iTable.cfm?ReqID=9&step=1) and expressing as percentage {[($13,658.8/$13,181.2) - 1]100 = 3.6%}. The growth rate in annual equivalent for the four quarters of 2011 and the four quarters of 2012 is 1.8 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.00025)4/8 -1]100 = 1.8%], or {[($13,656.8/$13,181.2)]4/8-1]100 = 1.8%} dividing the SAAR of IVQ2012 by the SAAR of IVQ2010, obtaining the average for eight quarters and the annual average for one year of four quarters. Growth in the four quarters of 2012 accumulates to 1.6 percent {[(1.02)1/4(1.013)1/4(1.031)1/4(1.001)1/4 -1]100 = 1.6%}. This is equivalent to dividing the SAAR of $13,656.8 billion for IVQ2012 by the SAAR of $13,441.0 billion in IVQ2011 to obtain 1.6 percent {[($13,656.8/$13,441.0) – 1]100 = 1.6%}. The US economy is still close to a standstill especially considering the GDP report in detail. Excluding growth at the SAAR of 2.5 percent in IIQ2011 and 4.1 percent in IVQ2011 while converting growth in IIIQ2012 to 1.73 percent by deducting from 3.1 percent one-time inventory accumulation of 0.73 percentage points and national defense expenditures of 0.64 percentage points and converting growth in IVQ2012 by adding 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditure reductions to obtain 2.84 percent, the US economy grew at 1.5 percent in the remaining six quarters {[(1.00025x1.0032x1.005x1.0032x1.0043x1.0070)4/6 – 1]100 = 1.5%} with declining growth trend in three consecutive quarters from 4.1 percent in IVQ2011, to 2.0 percent in IQ2012, 1.3 percent in IIQ2012, 3.1 percent in IIIQ2012 that is more like 1.73 percent without inventory accumulation and national defense expenditures and 0.1 percent in IVQ2012 that is more likely 2.84 percent by adding 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditures. Weakness of growth is more clearly shown by adjusting the exceptional one-time contributions to growth from items that are not aggregate demand: 2.53 percentage points contributed by inventory change to growth of 4.1 percent in IVQ2011; 0.64 percentage points contributed by expenditures in national defense together with 0.73 points of inventory accumulation to growth of 3.1 percent in IIIQ2012; and deduction of 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditure reductions. The Bureau of Economic Analysis (BEA) of the US Department of Commerce released on Thus Feb 28, 2012, the second estimate of GDP for IVQ2012 at 0.1 percent seasonally-adjusted annual rate (SAAR) (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp4q12_2nd.pdf). In the four quarters of 2012, the US economy is growing at the annual equivalent rate of 2.0 percent {([(1.021/4(1.013)1/4(1.0173)1/4(1.0284)1/4]-1)100 = 2.0%} by excluding inventory accumulation of 0.73 percentage points and exceptional defense expenditures of 0.64 percentage points from growth 3.1 percent at SAAR in IIIQ2012 to obtain adjusted 1.73 percent SSAR and adding 1.28 percentage points of national defense expenditure reductions and 1.55 percentage points of inventory divestment to growth of 0.1 percent SAAR in IVQ2012 to obtain 2.84 percent.
Table ESV-2, US, Difference of Balance Sheet of Households and Nonprofit Organizations Billions of Dollars from 2007 to 2011 and 2012
| Value 2007 | Change to 2009 | Change to 2011 | Change to 2012 | |
| Assets | 80,393.7 | -10,787.5 | -6,364.9 | -868.9 |
| Nonfinancial | 28,207.4 | -4,426.3 | -4,783.9 | -3,073.0 |
| Real Estate | 23,477.1 | -4,572.4 | -5,103.3 | -3,562.7 |
| Financial | 52,186.2 | -6,361.1 | -1,580.9 | 2,204.3 |
| Liabilities | 14,275.4 | -387.5 | -854.6 | -822.3 |
| Net Worth | 66,118.3 | -10,400.1 | -5,510.3 | -46.6 |
Net Worth = Assets – Liabilities
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7.
http://www.federalreserve.gov/releases/z1/default.htm
The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and also from IVQ1979) to IVQ1985 and from IVQ2007 to IVQ2012 is provided in Table ESV-3. Net worth of households and nonprofit organizations increased from $8,326.4 billion in IVQ1979 to $14,395.2 billion in IVQ1985 by 72.9 percent or 69.3 percent from $8,502.9 billion in IQ1980. The starting quarter does not bias the results. The US consumer price index not seasonally adjusted increased from 76.7 in Dec 1979 to 109.3 in Dec 1985 or 42.5 percent or 36.5 percent from 80.1 in Mar 1980 (using consumer price index data from the US Bureau of Labor Statistics at http://www.bls.gov/cpi/data.htm). In terms of purchasing power measured by the consumer price index, real wealth of households and nonprofit organizations increased 21.3 percent in constant purchasing power from IVQ1979 to IVQ1985 or 24.0 percent from IQ1980. In contrast, as shown in Table ESV-3, net worth of households and nonprofit organizations fell from $66,118.3 billion in IVQ2007 to $66,071.7 billion in IVQ2012 by $46.6 billion or 0.1 percent. The US consumer price index was 210.036 in Dec 2007 and 229.601 in Dec 2012 for increase of 9.1 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 8.4 percent in 2012 than in 2007 after fourteen consecutive quarters of expansion from IIIQ2009 to IVQ2012 relative to IVQ2007 when the recession began. The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. The average growth rate from IIIQ2009 to IVQ2012 has been 2.1 percent, which is substantially lower than the average of 6.2 percent in cyclical expansions after World War II and 5.7 percent in the expansion from IQ1983 to IVQ1985 (http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions.
Table ESV-3, Net Worth of Households and Nonprofit Organizations in Billions of Dollars, IVQ1979 to IVQ1985 and IVQ2007 to IVQ2012
| Period IQ1980 to IVQ1985 | |
| Net Worth of Households and Nonprofit Organizations USD Millions | |
| IVQ1979 IQ1980 | 8,326.4 8,502.9 |
| IVQ1985 | 14,395.2 |
| ∆ USD Billions IQ1980 | +6,068.8 +5,892.3 |
| Period IVQ2007 to IIQ2012 | |
| Net Worth of Households and Nonprofit Organizations USD Millions | |
| IVQ2007 | 66,118.3 |
| IVQ2012 | 66,071.7 |
| ∆ USD Billions | -46.6 |
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar 7. http://www.federalreserve.gov/releases/z1/default.htm
Chart ESV-1 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ2007 to IVQ2012. There is remarkable stop and go behavior in this series with two sharp declines and two standstills in the 14 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.
Chart ESV-1, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ2007 to IVQ2012
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7.
http://www.federalreserve.gov/releases/z1/default.htm
Chart ESV-2 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1979 to IVQ1985. 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 $5482.1 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.74 percent of GDP in a year. US GDP in 2011 is estimated at $15,681.5 billion, such that the bailout would be equivalent to cost to taxpayers of about $429.7 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).
Chart ESV-2, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1979 to IVQ1985
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7.
http://www.federalreserve.gov/releases/z1/default.htm
Chart ESV-3 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1945 at $710,125.9 million to IVQ2012 at $66,071.7 billion or increase of 9,204.2 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 229.601 in Dec 2012 or 1,161.5 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 67 years with inflation adjusted increase of 637.5 percent. The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIQ2009 caused sharp contraction of US household and nonprofit net worth. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 67 years when US GDP grew at 2.1 percent on average in fourteen quarters between IIIQ2009 and IVQ2012 in contrast with average 5.7 percent from IQ1983 to IVQ1985 and average 6.2 percent during cyclical expansions in major postwar economic cycles (http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html).
Chart ESV-3, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1945 to IVQ2012
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7.
http://www.federalreserve.gov/releases/z1/default.htm
ESVI Squeeze of Economic Activity by Carry Trades from Zero Interest Rates to Costs of Commodities. There was milder increase in Japan’s export corporate goods price index during the global recession in 2008 but similar sharp decline during the bank balance sheets effect in late 2008, as shown in Chart ESVI-1 of the Bank of Japan. Japan exports industrial goods whose prices have been less dynamic than those of commodities and raw materials. As a result, the export CGPI on the yen basis in Chart ESVI-1 trends down with oscillations after a brief rise in the final part of the recession in 2009. The export corporate goods price index fell from 104.8 in Jun 2009 to 94 in Feb 2012 or minus 10.3 percent and increased to 105.9 in Feb 2013 for a gain of 12.7 percent relative to Feb 2012 and 1.0 percent relative to Jun 2009. The choice of Jun 2009 is designed to capture the reversal of risk aversion beginning in Sep 2008 with the announcement of toxic assets in banks that would be withdrawn with the Troubled Asset Relief Program (TARP) (Cochrane and Zingales 2009). Reversal of risk aversion in the form of flight to the USD and obligations of the US government opened the way to renewed carry trades from zero interest rates to exposures in risk financial assets such as commodities. Japan exports industrial products and imports commodities and raw materials.
Chart ESVI-1, Japan, Export Corporate Goods Price Index, Monthly, Yen Basis, 2008-2013
Source: Bank of Japan
http://www.stat-search.boj.or.jp/index_en.html
Chart ESVI-2 provides the export corporate goods price index on the basis of the contract currency. The export corporate goods price index on the basis of the contract currency increased from 97.9 in Jun 2009 to 102.3 in Feb 2012 or 4.5 percent but dropped to 101.5 in Feb 2013 or minus 0.8 percent relative to Feb 2012 and gained 3.7 percent relative to Jun 2009.
Chart ESVI-2, Japan, Export Corporate Goods Price Index, Monthly, Contract Currency Basis, 2008-2013
Source: Bank of Japan
http://www.stat-search.boj.or.jp/index_en.html
Japan imports primary commodities and raw materials. As a result, the import corporate goods price index on the yen basis in Chart ESVI-3 shows an upward trend after the rise during the global recession in 2008 driven by carry trades from fed funds rates collapsing to zero into commodity futures and decline during risk aversion from late 2008 into beginning of 2008 originating in doubts about soundness of US bank balance sheets. More careful measurement should show that the terms of trade of Japan, export prices relative to import prices, declined during the commodity shocks originating in unconventional monetary policy. The decline of the terms of trade restricted potential growth of income in Japan. The import corporate goods price index on the yen basis increased from 93.5 in Jun 2009 to 106.4 in Feb 2012 or 13.8 percent and to 120.4 in Feb 2013 or gain of 13.2 percent relative to Feb 2012 and 28.8 percent relative to Jun 2009. Recent depreciation of the yen relative to the dollar explains the increase in imports in domestic yen prices.
Chart ESVI-3, Japan, Import Corporate Goods Price Index, Monthly, Yen Basis, 2008-2013
Source: Bank of Japan
http://www.stat-search.boj.or.jp/index_en.html
Chart ESVI-4 provides the import corporate goods price index on the contract currency basis. The import corporate goods price index on the basis of the contract currency increased from 86.2 in Jun 2009 to 115.8 in Feb 2012 or 34.3 percent and to 114.9 in Feb 2013 or minus 0.8 percent relative to Feb 2012 and gain of 33.3 percent relative to Jun 2009. There is evident deterioration of the terms of trade of Japan: the export corporate goods price index on the basis of the contract currency increased 3.7 percent from Jun 2009 to Feb 2012 while the import corporate goods price index increased 33.3 percent. Prices of Japan’s exports of corporate goods, mostly industrial products, increased only 3.7 percent from Jun 2009 to Feb 2012, while imports of corporate goods, mostly commodities and raw materials increased 33.3 percent. Unconventional monetary policy induces carry trades from zero interest rates to exposures in commodities that squeeze economic activity of industrial countries by increases in prices of imported commodities and raw materials during periods without risk aversion. Reversals of carry trades during periods of risk aversion decrease prices of exported commodities and raw materials that squeeze economic activity in economies exporting commodities and raw materials. Devaluation of the dollar by unconventional monetary policy could increase US competitiveness in world markets but economic activity is squeezed by increases in prices of imported commodities and raw materials. Unconventional monetary policy causes instability worldwide instead of the mission of central banks of promoting financial and economic stability.
Chart ESVI-4, Japan, Import Corporate Goods Price Index, Monthly, Contract Currency Basis, 2008-2013
Source: Bank of Japan
http://www.stat-search.boj.or.jp/index_en.html
Further insight into inflation of the corporate goods price index (CGPI) of Japan is provided in Table ESVI-1. Petroleum and coal with weight of 5.7 percent increased 3.6 percent in Feb 2013 and increased 8.7 percent in 12 months. Japan exports manufactured products and imports raw materials and commodities such that the country’s terms of trade, or export prices relative to import prices, deteriorate during commodity price increases. In contrast, prices of production machinery, with weight of 3.1 percent, increased 0.0 percent in Feb 2013 and increased 1.0 percent in 12 months. In general, most manufactured products have been experiencing negative or low increases in prices while inflation rates have been high in 12 months for products originating in raw materials and commodities. Ironically, unconventional monetary policy of zero interest rates and quantitative easing that intended to increase aggregate demand and GDP growth deteriorated the terms of trade of advanced economies with adverse effects on real income.
Table ESVI-1, Japan, Corporate Goods Prices and Selected Components, % Weights, Month and 12 Months ∆%
| Feb 2013 | Weight | Month ∆% | 12 Month ∆% |
| Total | 1000.0 | 0.4 | -0.1 |
| Food, Beverages, Tobacco, Feedstuffs | 137.5 | 0.1 | 0.5 |
| Petroleum & Coal | 57.4 | 3.6 | 8.7 |
| Production Machinery | 30.8 | 0.0 | 1.0 |
| Electronic Components | 31.0 | 0.1 | -1.9 |
| Electric Power, Gas & Water | 52.7 | -0.5 | 3.8 |
| Iron & Steel | 56.6 | 0.2 | -8.2 |
| Chemicals | 92.1 | 0.8 | 1.0 |
| Transport | 136.4 | 0.0 | -2.2 |
Source: Bank of Japan http://www.stat-search.boj.or.jp/index_en.html http://www.boj.or.jp/en/statistics/pi/cgpi_release/cgpi1302.pdf
Percentage point contributions to change of the corporate goods price index (CGPI) in Feb 2013 are provided in Table ESVI-2 divided into domestic, export and import segments. In the domestic CGPI, increasing 0.4 percent in Feb 2013, the energy shock resulting from carry trades is evident in the contribution of 0.25 percentage points by petroleum and coal products in new carry trades of exposures in commodity futures. The exports CGPI increased 0.4 percent on the basis of the contract currency with contribution of 0.16 percentage points by chemicals & related products and 0.12 percentage points by metals & related products. The imports CGPI increased 0.6 percent on the contract currency basis. Petroleum, coal & natural gas added 0.48 percentage points because of new carry trades into energy commodity exposures while other primary products and manufactured goods added 0.03 percentage points. Shocks of risk aversion cause unwinding carry trades that result in declining commodity prices with resulting downward pressure on price indexes. The volatility of inflation adversely affects financial and economic decisions worldwide.
Table ESVI-2, Japan, Percentage Point Contributions to Change of Corporate Goods Price Index
| Groups Feb 2013 | Contribution to Change Percentage Points |
| A. Domestic Corporate Goods Price Index | Monthly Change: |
| Petroleum & Coal Products | 0.25 |
| Nonferrous Metals | 0.07 |
| Chemicals & Related Products | 0.07 |
| Agriculture, Forestry & Fishery | 0.04 |
| Scrap & Waste | 0.04 |
| Electric, Power, Gas & Water | -0.03 |
| B. Export Price Index | Monthly Change: |
| Chemicals & Related Products | 0.16 |
| Transportation Equipment | 0.06 |
| Metals & Related Products | 0.05 |
| Other Primary Products & Manufactured Goods | 0.04 |
| C. Import Price Index | Monthly Change: 0.6 % contract currency basis |
| Petroleum, Coal & Natural Gas | 0.48 |
| Metals & Related Products | 0.05 |
| Other Primary Products & Manufactured Goods | 0.03 |
Source: Bank of Japan
http://www.stat-search.boj.or.jp/index_en.html http://www.boj.or.jp/en/statistics/pi/cgpi_release/cgpi1302.pdf
ESVII Global Financial and Economic Risk. The International Monetary Fund (IMF) provides an international safety net for prevention and resolution of international financial crises. The IMF’s Financial Sector Assessment Program (FSAP) provides analysis of the economic and financial sectors of countries (see Pelaez and Pelaez, International Financial Architecture (2005), 101-62, Globalization and the State, Vol. II (2008), 114-23). Relating economic and financial sectors is a challenging task both for theory and measurement. The IMF (2012WEOOct) provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/pubs/ft/weo/2012/02/index.htm), of the world financial system with its Global Financial Stability Report (GFSR) (IMF 2012GFSROct) (http://www.imf.org/external/pubs/ft/gfsr/2012/02/index.htm) and of fiscal affairs with the Fiscal Monitor (IMF 2012FMOct) (http://www.imf.org/external/pubs/ft/fm/2012/02/fmindex.htm). There appears to be a moment of transition in global economic and financial variables that may prove of difficult analysis and measurement. It is useful to consider a summary of global economic and financial risks, which are analyzed in detail in the comments of this blog in Section VI Valuation of Risk Financial Assets, Table VI-4.
Economic risks include the following:
1. China’s Economic Growth. China is lowering its growth target to 7.5 percent per year. China’s GDP growth decelerated significantly from annual equivalent 9.9 percent in IIIQ2011 to 7.0 percent in IVQ2011 and 6.1 percent in IQ2012, rebounding to 8.2 percent in IIQ2012, 9.1 percent in IIIQ2012 and 8.2 percent in IVQ2012. (See Subsection VC at http://cmpassocregulationblog.blogspot.com/2013/01/recovery-without-hiring-world-inflation.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html).
2. United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 30.8 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically-low hiring and declining real wages.
3. Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
4. World Inflation Waves. Inflation continues in repetitive waves globally (Section II and earlier http://cmpassocregulationblog.blogspot.com/2013/02/world-inflation-waves-united-states.html).
A list of financial uncertainties includes:
1. Euro Area Survival Risk. The resilience of the euro to fiscal and financial doubts on larger member countries is still an unknown risk.
2. Foreign Exchange Wars. Exchange rate struggles continue as zero interest rates in advanced economies induce devaluation of their currencies.
3. Valuation of Risk Financial Assets. Valuations of risk financial assets have reached extremely high levels in markets with lower volumes.
4. Duration Trap of the Zero Bound. The yield of the US 10-year Treasury rose from 2.031 percent on Mar 9, 2012, to 2.294 percent on Mar 16, 2012. Considering a 10-year Treasury with coupon of 2.625 percent and maturity in exactly 10 years, the price would fall from 105.3512 corresponding to yield of 2.031 percent to 102.9428 corresponding to yield of 2.294 percent, for loss in a week of 2.3 percent but far more in a position with leverage of 10:1. Min Zeng, writing on “Treasurys fall, ending brutal quarter,” published on Mar 30, 2012, in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702303816504577313400029412564.html?mod=WSJ_hps_sections_markets), informs that Treasury bonds maturing in more than 20 years lost 5.52 percent in the first quarter of 2012.
5. Credibility and Commitment of Central Bank Policy. There is a credibility issue of the commitment of monetary policy (Sargent and Silber 2012Mar20).
6. Carry Trades. Commodity prices driven by zero interest rates have resumed their increasing path with fluctuations caused by intermittent risk aversion.
A competing event is the high level of valuations of risk financial assets (http://cmpassocregulationblog.blogspot.com/2013/01/peaking-valuation-of-risk-financial.html). Matt Jarzemsky, writing on Dow industrials set record,” on Mar 5, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324156204578275560657416332.html), analyzes that the DJIA broke the closing high of 14164.53 set on Oct 9, 2007, and subsequently also broke the intraday high of 14198.10 reached on Oct 11, 2007. The DJIA closed at 14514.11 on Fri Mar 15, 2013, which is higher by 2.5 percent than the value of 14,164.52 reached on Oct 9, 2007 and higher by 2.2 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs. Jon Hilsenrath, writing on “Jobs upturn isn’t enough to satisfy Fed,” on Mar 8, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324582804578348293647760204.html), finds that much stronger labor market conditions are required for the Fed to end quantitative easing. Unconventional monetary policy with zero interest rates and quantitative easing is quite difficult to unwind because of the adverse effects of raising interest rates on valuations of risk financial assets and home prices, including the very own valuation of the securities held outright in the Fed balance sheet. Gradual unwinding of 1 percent fed funds rates from Jun 2003 to Jun 2004 by seventeen consecutive increases of 25 percentage points from Jun 2004 to Jun 2006 to reach 5.25 percent caused default of subprime mortgages and adjustable-rate mortgages linked to the overnight fed funds rate. The zero interest rate has penalized liquidity and increased risks by inducing carry trades from zero interest rates to speculative positions in risk financial assets. There is no exit from zero interest rates without provoking another financial crash.
The carry trade from zero interest rates to leveraged positions in risk financial assets had proved strongest for commodity exposures but US equities have regained leadership. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 3/15/13” in Table ESVII-1 had double digit gains relative to the trough around Jul 2, 2010 followed by negative performance but now some valuations of equity indexes show varying behavior: DJIA is 49.8 percent above the trough; S&P 500 is 52.6 percent above the trough; China’s Shanghai Composite is 4.4 percent below the trough; Japan’s Nikkei Average is 42.3 percent above the trough; DJ Asia Pacific TSM is 21.8 percent above the trough; Dow Global is 25.9 percent above the trough; STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 18.3 percent above the trough; and NYSE Financial Index is 31.3 percent above the trough. DJ UBS Commodities is 11.6 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 41.8 percent above the trough. Japan’s Nikkei Average is 42.3 percent above the trough on Aug 31, 2010 and 10.2 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 12560.95 on Fri Mar 15, 2013 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 22.5 percent higher than 10,254.43 on Mar 11, 2011, on the date of the Tōhoku or Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar depreciated by 9.7 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 3/15/13” in Table ESVII-1 shows that there were decreases of valuations of risk financial assets in the week of Mar 15, 2013 such as 1.7 percent for China’s Shanghai Composite. Nikkei Average increased 2.3 percent in the week. DJ UBS Commodities increased 0.8 percent. Dow Global increased 0.8 percent in the week of Mar 15, 2013. The DJIA increased 0.8 percent and S&P 500 increased 0.6 percent. There were increases in several indexes such as 1.0 percent for DJ Asia Pacific. DAX of Germany increased 0.7 percent. NYSE Financial increased 1.0 percent. The USD depreciated 0.6 percent. There are still high uncertainties on European sovereign risks and banking soundness, US and world growth slowdown and China’s growth tradeoffs. Sovereign problems in the “periphery” of Europe and fears of slower growth in Asia and the US cause risk aversion with trading caution instead of more aggressive risk exposures. There is a fundamental change in Table ESVII-1 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 3/15/13” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Mar 15, 2013. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 3/15/13” but also relative to the peak in column “∆% Peak to 3/15/13.” There are now several equity indexes above the peak in Table ESVII-1: DJIA 29.5 percent, S&P 500 28.2 percent, DAX 27.0 percent, DJ Asia Pacific 6.6 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 4.6 percent, Nikkei Average 10.2 percent, Dow Global 2.7 percent and STOXX 50 0.2 percent. There is one equity index below the peak: Shanghai Composite by 28.0 percent. DJ UBS Commodities Index is now 4.6 percent below the peak. The US dollar strengthened 13.6 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010. Kate Linebaugh, writing on “Falling revenue dings stocks,” on Oct 20, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444592704578066933466076070.html?mod=WSJPRO_hpp_LEFTTopStories), identifies a key financial vulnerability: falling revenues across markets for United States reporting companies. Global economic slowdown is reducing corporate sales and squeezing corporate strategies. Linebaugh quotes data from Thomson Reuters that 100 companies of the S&P 500 index have reported declining revenue only 1 percent higher in Jun-Sep 2012 relative to Jun-Sep 2011 but about 60 percent of the companies are reporting lower sales than expected by analysts with expectation that revenue for the S&P 500 will be lower in Jun-Sep 2012 for the entities represented in the index. Results of US companies are likely repeated worldwide. It may be quite painful to exit QE→∞ or use of the balance sheet of the central together with zero interest rates forever. The basic valuation equation that is also used in capital budgeting postulates that the value of stocks or of an investment project is given by:
Where Rτ is expected revenue in the time horizon from τ =1 to T; Cτ denotes costs; and ρ is an appropriate rate of discount. In words, the value today of a stock or investment project is the net revenue, or revenue less costs, in the investment period from τ =1 to T discounted to the present by an appropriate rate of discount. In the current weak economy, revenues have been increasing more slowly than anticipated in investment plans. An increase in interest rates would affect discount rates used in calculations of present value, resulting in frustration of investment decisions. If V represents value of the stock or investment project, as ρ → ∞, meaning that interest rates increase without bound, then V → 0, or
![clip_image040[1]](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiSb8qdFIjXnk70cnHcWt4dlEjO30HIFOqqq4RMr6jaeiLZzQBRBnlA_0GH6B9-fMxSZJbX5r_ley9x3oiJxc9hpmBKhDYCb3e7yNFbTHvkosRLLzm4BAivThsy5bmRLAlBtV65PCLN7YkC/s1600-h/clip_image040%25255B1%25255D%25255B2%25255D.gif "clip_image040[1]"){kind=small}
declines. Equally, decline in expected revenue from the stock or project, Rτ, causes decline in valuation. An intriguing issue is the difference in performance of valuations of risk financial assets and economic growth and employment. Paul A. Samuelson (http://www.nobelprize.org/nobel_prizes/economics/laureates/1970/samuelson-bio.html) popularized the view of the elusive relation between stock markets and economic activity in an often-quoted phrase “the stock market has predicted nine of the last five recessions.” In the presence of zero interest rates forever, valuations of risk financial assets are likely to differ from the performance of the overall economy. The interrelations of financial and economic variables prove difficult to analyze and measure.
Table ESVII-1, Stock Indexes, Commodities, Dollar and 10-Year Treasury
| Peak | Trough | ∆% to Trough | ∆% Peak to 3/15/ /13 | ∆% Week 3/15/13 | ∆% Trough to 3/15/ 13 | |
| DJIA | 4/26/ | 7/2/10 | -13.6 | 29.5 | 0.8 | 49.8 |
| S&P 500 | 4/23/ | 7/20/ | -16.0 | 28.2 | 0.6 | 52.6 |
| NYSE Finance | 4/15/ | 7/2/10 | -20.3 | 4.6 | 1.0 | 31.3 |
| Dow Global | 4/15/ | 7/2/10 | -18.4 | 2.7 | 0.8 | 25.9 |
| Asia Pacific | 4/15/ | 7/2/10 | -12.5 | 6.6 | 1.0 | 21.8 |
| Japan Nikkei Aver. | 4/05/ | 8/31/ | -22.5 | 10.2 | 2.3 | 42.3 |
| China Shang. | 4/15/ | 7/02 | -24.7 | -28.0 | -1.7 | -4.4 |
| STOXX 50 | 4/15/10 | 7/2/10 | -15.3 | 0.2 | 0.6 | 18.3 |
| DAX | 4/26/ | 5/25/ | -10.5 | 27.0 | 0.7 | 41.8 |
| Dollar | 11/25 2009 | 6/7 | 21.2 | 13.6 | -0.6 | -9.7 |
| DJ UBS Comm. | 1/6/ | 7/2/10 | -14.5 | -4.6 | 0.8 | 11.6 |
| 10-Year T Note | 4/5/ | 4/6/10 | 3.986 | 1.992 |
T: trough; Dollar: positive sign appreciation relative to euro (less dollars paid per euro), negative sign depreciation relative to euro (more dollars paid per euro)
Source: http://professional.wsj.com/mdc/page/marketsdata.html?mod=WSJ_hps_marketdata
I Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels have increased by only 4 percent since Jan 2009. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job currently is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). Lazear and Spletzer (2012Mar, 1) argue that reductions of churn reduce the operational effectiveness of labor markets. Churn is part of the allocation of resources or in this case labor to occupations of higher marginal returns. The decline in churn can harm static and dynamic economic efficiency. Losses from decline of churn during recessions can affect an economy over the long-term by preventing optimal growth trajectories because resources are not used in the occupations where they provide highest marginal returns. Lazear and Spletzer (2012Mar 7-8) conclude that: “under a number of assumptions, we estimate that the loss in output during the recession [of 2007 to 2009] and its aftermath resulting from reduced churn equaled $208 billion. On an annual basis, this amounts to about .4% of GDP for a period of 3½ years.”
There are two additional facts discussed below: (1) there are about ten million fewer full-time jobs currently than before the recession of 2008 and 2009; and (2) the extremely high and rigid rate of youth unemployment is denying an early start to young people ages 16 to 24 years while unemployment of ages 45 years or over has swelled. There are four subsections. IA1 Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IA2 Labor Underutilization provides the measures of labor underutilization of the Bureau of Labor Statistics (BLS). Statistics on the decline of full-time employment are in IA3 Ten Million Fewer Full-time Jobs. IA4 Youth and Middle-Age Unemployment provides the data on high unemployment of ages 16 to 24 years and of ages 45 years or over.
IA1 Hiring Collapse. An important characteristic of the current fractured labor market of the US is the closing of the avenue for exiting unemployment and underemployment normally available through dynamic hiring. Another avenue that is closed is the opportunity for advancement in moving to new jobs that pay better salaries and benefits again because of the collapse of hiring in the United States. Those who are unemployed or underemployed cannot find a new job even accepting lower wages and no benefits. The employed cannot escape declining inflation-adjusted earnings because there is no hiring. The objective of this section is to analyze hiring and labor underutilization in the United States.
An appropriate measure of job stress is considered by Blanchard and Katz (1997, 53):
“The right measure of the state of the labor market is the exit rate from unemployment, defined as the number of hires divided by the number unemployed, rather than the unemployment rate itself. What matters to the unemployed is not how many of them there are, but how many of them there are in relation to the number of hires by firms.”
The natural rate of unemployment and the similar NAIRU are quite difficult to estimate in practice (Ibid; see Ball and Mankiw 2002).
The Bureau of Labor Statistics (BLS) created the Job Openings and Labor Turnover Survey (JOLTS) with the purpose that (http://www.bls.gov/jlt/jltover.htm#purpose):
“These data serve as demand-side indicators of labor shortages at the national level. Prior to JOLTS, there was no economic indicator of the unmet demand for labor with which to assess the presence or extent of labor shortages in the United States. The availability of unfilled jobs—the jobs opening rate—is an important measure of tightness of job markets, parallel to existing measures of unemployment.”
The BLS collects data from about 16,000 US business establishments in nonagricultural industries through the 50 states and DC. The data are released monthly and constitute an important complement to other data provided by the BLS (see also Lazear and Spletzer 2012Mar, 6-7).
Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 51.9 million in 2012 or by 11.8 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 48.5 million in 2012 or by 11.0 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.2 in 2005 to 38.9 in 2012 and in the private sector (RHP) from 52.1 in 2006 to 43.4 in 2012. The collapse of hiring in the US has not been followed by dynamic labor markets because of the low rate of economic growth of 2.1 percent in the first fourteen quarters of expansion from IIIQ2009 to IVQ2012 compared with 6.2 percent in prior cyclical expansions (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html).
Table I-1, US, Annual Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US and Percentage of Total Employment
| HNF | Rate RNF | HP | Rate HP | |
| 2001 | 62,948 | 47.8 | 58,825 | 53.1 |
| 2002 | 58,583 | 44.9 | 54,759 | 50.3 |
| 2003 | 56,451 | 43.4 | 53,056 | 48.9 |
| 2004 | 60,367 | 45.9 | 56,617 | 51.6 |
| 2005 | 63,150 | 47.2 | 59,372 | 53.1 |
| 2006 | 63,773 | 46.9 | 59,494 | 52.1 |
| 2007 | 62,421 | 45.4 | 58,035 | 50.3 |
| 2008 | 55,128 | 40.3 | 51,591 | 45.1 |
| 2009 | 46,357 | 35.4 | 43,031 | 39.8 |
| 2010 | 48,607 | 37.4 | 44,788 | 41.7 |
| 2011 | 49,675 | 37.8 | 46,552 | 42.5 |
| 2012 | 51,991 | 38.9 | 48,493 | 43.4 |
Source: Bureau of Labor Statistics http://www.bls.gov/jlt/
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 been recovered, remaining at a depressed level.
Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2012
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.
Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2012
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 3.6 percent in 2003 followed by strong rebounds of 6.9 percent in 2004 and 4.6 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.1 in 2007, 11.7 in 2008 and 15.9 percent in 2009. On a yearly basis, nonfarm hiring grew 4.9 percent in 2010 relative to 2009, 2.2 percent in 2011 and 4.7 percent in 2012.
Table I-2, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2002-2012
| Year | Annual |
| 2002 | -6.9 |
| 2003 | -3.6 |
| 2004 | 6.9 |
| 2005 | 4.6 |
| 2006 | 1.0 |
| 2007 | -2.1 |
| 2008 | -11.7 |
| 2009 | -15.9 |
| 2010 | 4.9 |
| 2011 | 2.2 |
| 2012 | 4.7 |
Source: Bureau of Labor Statistics
Chart I-3 plots yearly percentage changes of nonfarm hiring. Percentage declines after 2007 were quite sharp.
Chart I-3, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2001-2012
Source: Bureau of Labor Statistics
Total private hiring (HP) yearly data are provided in Chart I-4. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2012.
Chart I-4, US, Total Private Hiring Level, Annual, 2001-2012
Source: Bureau of Labor Statistics
Chart I-5 plots the rate of total private hiring relative to employment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.
Chart I-5, US, Rate Total Private Hiring, Annual, 2001-2012
Source: Bureau of Labor Statistics
Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Jan in the years from 2001 to 2013 in Table I-3. Hiring numbers are in thousands. There is virtually no recovery in HNF from 4078 thousand (or 4.1 million) in Jan 2009 to 3806 thousand in Jan 2011, 4013 thousand in Jan 2012 and 4073 thousand in Jan 2013 for cumulative gain of minus 0.1 percent. HP rose from 3765 thousand in Jan 2009 to 3551 thousand in Jan 2011, 3749 thousand in Jan 2012 and 3808 in Jan 2013 for cumulative gain of 1.1 percent. HNF has fallen from 3835 in Dec 2006 to 3017 in Dec 2012 or by 21.3 percent. HP has fallen from 5160 in Jan 2005 to 4073 in Jan 2013 or by 21.1 percent. 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 | 5953 | 4.6 | 5632 | 5.1 |
| 2002 Jan | 4978 | 3.9 | 4695 | 4.4 |
| 2003 Jan | 5076 | 4.0 | 4775 | 4.5 |
| 2004 Jan | 4829 | 3.8 | 4563 | 4.3 |
| 2005 Jan | 5160 | 4.0 | 4856 | 4.5 |
| 2006 Jan | 5098 | 3.8 | 4825 | 4.3 |
| 2007 Jan | 5142 | 3.8 | 4820 | 4.3 |
| 2008 Jan | 4791 | 3.5 | 4495 | 4.0 |
| 2009 Jan | 4078 | 3.1 | 3765 | 3.5 |
| 2010 Jan | 3748 | 2.9 | 3479 | 3.3 |
| 2011 Jan | 3806 | 3.0 | 3551 | 3.3 |
| 2012 Jan | 4013 | 3.1 | 3749 | 3.4 |
| 2013 Jan | 4073 | 3.1 | 3808 | 3.4 |
Source: Bureau of Labor Statistics http://www.bls.gov/jlt/
Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2013. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4774 in May 2010 until it surpassed it with 4883 in Jun 2011 but declined to 3013 in Dec 2012. Nonfarm hiring fell again in Dec 2011 to 2990 from 3827 in Nov and to revised 3683 in Feb 2012, increasing to 4210 in Mar 2012, 3013 in Dec 2012 and 4073 in Jan 2013. Chart I-6 provides seasonally-adjusted (SA) monthly data. The number of seasonally-adjusted hires in Aug 2011 was 4187 thousand, increasing to revised 4489 thousand in Feb 2012, or 7.2 percent, moving to 4195 in Dec 2012 for cumulative increase of 0.5 percent from 4174 in Dec 2011 and 4247 for increase of 1.2 percent relative to 4195 in Dec 2012. The number of hires not seasonally adjusted was 4883 in Jun 2011, falling to 2990 in Dec 2011 but increasing to 4013 in Jan 2012 and declining to 3013 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 38.8 percent from 4883 in Jun 2011 to 2990 in Dec 2011 and fell 41.3 percent from 5130 in Jun 2012 to 3013 in Dec 2012 in a yearly-repeated seasonal pattern.
Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2013 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 3.4 in May 2012 and falling to 3.2 in both Jun and Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.1 in Dec 2012 and 3.1 in Jan 2013. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.2 in Dec 2012, climbing to 3.8 in Jun 2012 but falling to 2.2 in Dec 2012 and 3.1 in Jan 2013. Rates of nonfarm hiring NSA were in the range of 2.8 (Dec) to 4.5 (Jun) in 2006.
Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2013
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 4026 thousand in Sep 2011 to 3876 in Dec 2011 or by 3.7 percent, increasing to 3915 in Jan 2012 or decline by 2.8 percent relative to the level in Sep 2011 but decreasing to 3934 in Sep 2012 or lower by 2.3 percent relative to Sep 2011 and decreasing to 3915 in Dec 2012 for change of 0.0 percent relative to 3915 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4504 in Jun 2011 to 2809 in Dec 2011 or by 37.6 percent, reaching 3749 in Jan 2012 or decline of 16.8 percent relative to Jun 2011 and moving to 2842 in Dec 2012 or 39.8 percent lower relative to 4724 in Jun 2012. Companies do not hire in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5661 in Jun 2006 to 3635 in Dec 2006 or by 35.8 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Jul 2006 private hiring NSA was 5555, declining to 4245 in Jul 2011 or by 23.6 percent and to 4277 in Jul 2012 or lower by 23.0 percent relative to Jul 2006. Private hiring NSA fell from 5215 in Sep 2005 to 4005 in Sep 2012 or 23.2 percent and fell from 3635 in Dec 2006 to 2842 in Dec 2012 or 21.8 percent. The conclusion is that private hiring in the US is around 20 percent below the hiring before the global recession. The main problem in recovery of the US labor market has been the low rate of growth of 2.1 percent in the fourteen quarters of expansion of the economy from IIIQ2009 to IVQ2012 compared with average 6.2 percent in prior expansions from contractions (see table I-5 in ) http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Chart I-8, US, Total Private Hiring Month SA 2001-2013
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 3.6 in Sep 2011 to 3.5 in Dec 2011 and reached 3.5 in Dec 2012 and 3.5 in Jan 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 2.5 in Dec 2012 and 3.4 in Jan 2013. The NSA rate of private hiring fell from 4.8 in Jul 2006 to 3.4 in Aug 2009 but recovery was insufficient to only 3.8 in Aug 2012, 2.5 in Dec 2012 and 3.4 in Jan 2013.
Chart I-9, US, Rate Total Private Hiring Month SA 2001-2013
Source: Bureau of Labor Statistics
The JOLTS report of the Bureau of Labor Statistics also provides total nonfarm job openings (TNF JOB), TNF JOB rate and TNF LD (layoffs and discharges) shown in Table I-4 for the month of Jan from 2001 to 2013. The final column provides annual TNF LD for the years from 2001 to 2012. Nonfarm job openings (TNF JOB) fell from a peak of 4794 in Jan 2007 to 3879 in Jan 2013 or by 19.1 percent while the rate dropped from 3.4 to 2.8. Nonfarm layoffs and discharges (TNF LD) rose from 2167 in Jan 2006 to 3308 in Jan 2009 or by 52.7 percent. The annual data show layoffs and discharges rising from 21.2 million in 2006 to 26.8 million in 2009 or by 26.4 percent. Business pruned payroll jobs to survive the global recession but there has not been hiring because of the weak recovery in the form of growth of 2.1 percent on average in the fourteen quarters of expansion from IIIQ2009 to IVQ2012 in contrast with 6.2 percent on average in cyclical expansions in the United States (see Table I-5 at http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html).
Table I-4, US, Job Openings and Total Separations, Thousands NSA
| TNF JOB | TNF JOB | TNF LD | TNF LD | |
| Jan 2001 | 5771 | 4.2 | 3037 | 24499 |
| Jan 2002 | 3920 | 3.0 | 2495 | 22922 |
| Jan 2003 | 3938 | 3.0 | 2602 | 23294 |
| Jan 2004 | 3567 | 2.7 | 2462 | 22802 |
| Jan 2005 | 3845 | 2.9 | 2476 | 22185 |
| Jan 2006 | 4524 | 3.3 | 2167 | 21157 |
| Jan 2007 | 4794 | 3.4 | 2197 | 22142 |
| Jan 2008 | 4419 | 3.2 | 2337 | 24181 |
| Jan 2009 | 2961 | 2.2 | 3308 | 26784 |
| Jan 2010 | 2879 | 2.2 | 2357 | 21773 |
| Jan 2011 | 3025 | 2.3 | 2147 | 20401 |
| Jan 2012 | 3587 | 2.7 | 2022 | 20546 |
| Jan 2013 | 3879 | 2.8 | 1888 |
Notes: TNF JOB: Total Nonfarm Job Openings; LD: Layoffs and Discharges
Source: Bureau of Labor Statistics http://www.bls.gov/jlt/
Chart I-10 shows monthly job openings rising from the trough in 2009 to a high in the beginning of 2010. Job openings then stabilized into 2011 but have surpassed the peak of 3142 seasonally adjusted in Apr 2010 with 3612 seasonally adjusted in Dec 2012, which is higher by 15.0 percent relative to Apr 2010 but lower by 4.7 percent than 3789 in Nov 2012 and lower than 3848 in Mar 2012 by 6.1 percent. Nonfarm job openings increased from 3612 in Dec 2012 to 3693 in Jan 2012 or by 2.2 percent. The high of job openings not seasonally adjusted in 2010 was 3396 in Apr 2010 that was surpassed by 3659 in Oct 2011, increasing to 3525 in Oct 2012 but declining to 3103 in Dec 2012 and increasing to 3879 in Jan 2013. The level of job openings not seasonally adjusted fell to 3103 in Dec 2012 or by 19.0 percent relative to 3831 in Apr 2012. There is here again the strong seasonality of year-end labor data. The level of job openings of 3879 in Jan 2013 NSA is lower by 19.1 percent relative to 4794 in Dec 2007. The main problem in recovery of the US labor market has been the low rate of growth of 2.1 percent in the fourteen quarters of expansion of the economy since IIIQ2009 compared with average 6.2 percent in prior expansions from contractions (see table I-5 at http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Chart I-10, US Job Openings, Thousands NSA, 2001-2013
Source: US Bureau of Labor Statistics
The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted rose from 2.1 percent in Jan 2011 to 2.5 percent in Dec 2011, 2.6 in Dec 2012 and 2.7 in Jan 2013. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 2.8 in Jan 2013. The rate of job openings NSA fell from 3.4 in Jul 2007 to 1.6 in Nov-Dec 2009, recovering insufficiently to 2.8 in Jan 2013.
Chart I-11, US, Rate of Job Openings, NSA, 2001-2013
Source: US Bureau of Labor Statistics
Total separations are shown in Chart I-12. Separations are much lower in 2012 than before the global recession but hiring has not recovered.
Chart I-12, US, Total Nonfarm Separations, Month SA, 2001-2013
Source: US Bureau of Labor Statistics
Annual total separations are shown in Chart I-13. Separations are much lower in 2011-2012 than before the global recession but without recovery in hiring.
Chart I-13, US, Total Separations, Annual, 2001-2012
Source: US Bureau of Labor Statistics
Table I-5 provides total nonfarm total separations from 2001 to 2011. Separations fell from 61.6 million in 2006 to 47.6 million in 2010 or by 14.0 million and 47.6 million in 2011 or by 14.0 million. Total separations increased from 47.6 million in 2011 to 49.7 million in 2012 or by 2.1 million.
Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2012
| Year | Annual |
| 2001 | 64765 |
| 2002 | 59190 |
| 2003 | 56487 |
| 2004 | 58340 |
| 2005 | 60733 |
| 2006 | 61565 |
| 2007 | 61162 |
| 2008 | 58627 |
| 2009 | 51532 |
| 2010 | 47646 |
| 2011 | 47626 |
| 2012 | 49676 |
Source: US Bureau of Labor Statistics
Monthly data of layoffs and discharges reach a peak in early 2009, as shown in Chart I-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business. Weak rates of growth of 2.1 percent of GDP on average from IIIQ2009 to IVQ2012 compared with 6.2 percent on average in cyclical expansions (http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html) frustrated employment recovery.
Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly SA, 2011-2013
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.
Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2012
Source: US Bureau of Labor Statistics
Table I-6 provides annual nonfarm layoffs and discharges from 2001 to 2012. Layoffs and discharges peaked at 26.8 million in 2009 and then fell to 20.4 million in 2011, by 6.4 million, or 23.9 percent. Total nonfarm layoffs and discharges increased mildly to 20.5 million in 2012.
Table I-6, US, Total Nonfarm Layoffs and Discharges, 2001-2012
| Year | Annual |
| 2001 | 24499 |
| 2002 | 22922 |
| 2003 | 23294 |
| 2004 | 22802 |
| 2005 | 22185 |
| 2006 | 21157 |
| 2007 | 22142 |
| 2008 | 24181 |
| 2009 | 26784 |
| 2010 | 21773 |
| 2011 | 20401 |
| 2012 | 20546 |
Source: US Bureau of Labor Statistics
IA2 Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table I-7. The most comprehensive measure is U6 that consists of total unemployed plus total employed part time for economic reasons plus all marginally attached workers as percent of the labor force. U6 not seasonally annualized has risen from 8.2 percent in 2006 to 14.9 percent in Feb 2013.
Table I-7, US, Alternative Measures of Labor Underutilization NSA %
| U1 | U2 | U3 | U4 | U5 | U6 | |
| 2013 | ||||||
| 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 | ||||||
| 2012 | 4.5 | 4.4 | 8.1 | 8.6 | 9.5 | 14.7 |
| 2011 | 5.3 | 5.3 | 8.9 | 9.5 | 10.4 | 15.9 |
| 2010 | 5.7 | 6.0 | 9.6 | 10.3 | 11.1 | 16.7 |
| 2009 | 4.7 | 5.9 | 9.3 | 9.7 | 10.5 | 16.2 |
| 2008 | 2.1 | 3.1 | 5.8 | 6.1 | 6.8 | 10.5 |
| 2007 | 1.5 | 2.3 | 4.6 | 4.9 | 5.5 | 8.3 |
| 2006 | 1.5 | 2.2 | 4.6 | 4.9 | 5.5 | 8.2 |
| 2005 | 1.8 | 2.5 | 5.1 | 5.4 | 6.1 | 8.9 |
| 2004 | 2.1 | 2.8 | 5.5 | 5.8 | 6.5 | 9.6 |
| 2003 | 2.3 | 3.3 | 6.0 | 6.3 | 7.0 | 10.1 |
| 2002 | 2.0 | 3.2 | 5.8 | 6.0 | 6.7 | 9.6 |
| 2001 | 1.2 | 2.4 | 4.7 | 4.9 | 5.6 | 8.1 |
| 2000 | 0.9 | 1.8 | 4.0 | 4.2 | 4.8 | 7.0 |
Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.1 percent in Aug 2011 to 16.3 percent in Sep 2011 and then fell to 14.5 percent in Apr 2012 and 14.3 percent in Feb 2013. 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 30.9 million in job stress of unemployment/underemployment in Feb 2013, not seasonally adjusted, corresponding to 19.2 percent of the labor force (Table I-4 http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html).
Table I-8, US, Alternative Measures of Labor Underutilization SA %
| U1 | U2 | U3 | U4 | U5 | U6 | |
| Feb 2013 | 4.2 | 4.2 | 7.7 | 8.3 | 9.2 | 14.3 |
| Jan | 4.2 | 4.3 | 7.9 | 8.4 | 9.3 | 14.4 |
| Dec 2012 | 4.3 | 4.1 | 7.8 | 8.5 | 9.4 | 14.4 |
| Nov | 4.3 | 4.1 | 7.8 | 8.3 | 9.2 | 14.4 |
| Oct | 4.4 | 4.2 | 7.9 | 8.4 | 9.3 | 14.5 |
| Sep | 4.3 | 4.2 | 7.8 | 8.3 | 9.3 | 14.7 |
| Aug | 4.4 | 4.5 | 8.1 | 8.6 | 9.6 | 14.7 |
| Jul | 4.5 | 4.6 | 8.2 | 8.7 | 9.7 | 14.9 |
| Jun | 4.6 | 4.6 | 8.2 | 8.7 | 9.6 | 14.8 |
| May | 4.6 | 4.5 | 8.2 | 8.7 | 9.6 | 14.8 |
| Apr | 4.5 | 4.5 | 8.1 | 8.7 | 9.5 | 14.5 |
| Mar | 4.6 | 4.5 | 8.2 | 8.7 | 9.6 | 14.5 |
| Feb | 4.8 | 4.6 | 8.3 | 8.9 | 9.8 | 15.0 |
| Jan | 4.8 | 4.7 | 8.3 | 8.9 | 9.9 | 15.1 |
| Dec 2011 | 4.9 | 4.9 | 8.5 | 9.0 | 10.0 | 15.2 |
| Nov | 5.0 | 4.9 | 8.6 | 9.3 | 10.2 | 15.5 |
| Oct | 5.1 | 5.1 | 8.9 | 9.5 | 10.4 | 16.0 |
| Sep | 5.4 | 5.2 | 9.0 | 9.6 | 10.5 | 16.3 |
| Aug | 5.3 | 5.2 | 9.0 | 9.6 | 10.5 | 16.1 |
| Jul | 5.3 | 5.3 | 9.0 | 9.7 | 10.6 | 16.0 |
| Jun | 5.3 | 5.3 | 9.1 | 9.7 | 10.7 | 16.1 |
| May | 5.3 | 5.4 | 9.0 | 9.5 | 10.3 | 15.8 |
| Apr | 5.2 | 5.4 | 9.0 | 9.6 | 10.5 | 16.0 |
| Mar | 5.3 | 5.4 | 8.9 | 9.5 | 10.4 | 15.8 |
| Feb | 5.4 | 5.5 | 9.0 | 9.6 | 10.6 | 16.0 |
| Jan | 5.5 | 5.5 | 9.1 | 9.7 | 10.8 | 16.2 |
Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-16 provides U1 on a monthly basis from 2001 to 2013. 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 7.9 percent in Dec 2006 and the peak was 17.1 percent in Oct-Dec 2009. 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, 2001-2013
Source: US Bureau of Labor Statistics
Chart I-17 provides the number employed part-time for economic reasons or who cannot find full-time employment. There are sharp declines at the end of 2009, 2010 and 2011 but an increase in 2012 followed by stability.
Chart I-17, US, Working Part-time for Economic Reasons
Thousands, Month SA 2001-2013
Sources: US Bureau of Labor Statistics
There is strong seasonality in US labor markets around the end of the year. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.101 million in Sep 2011 to 8.043 million in Aug 2012, seasonally adjusted, or decline of 1.058 million in nine months, as shown in Table I-9, but then rebounded to 8.607 million in Sep 2012 for increase of 564,000 in one month from Aug to Sep 2012, declining to 8.286 million in Oct 2012 or by 321,000 again in one month, further declining to 8.138 million in Nov 2012 for another major one-month decline of 148,000 and 7.918 million in Dec 2012 or fewer 220,000 in just one month. The number employed part-time for economic reasons increased to 7.973 million in Jan 2013 or 55,000 more than in Dec 2012 and to 7,988 million in Feb 2013. There is an increase of 243,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 95,000 from Aug 2012 to Nov 2012. The number employed full-time increased from 112.871 million in Oct 2011 to 115.145 million in Mar 2012 or 2.274 million but then fell to 114.300 million in May 2012 or 0.845 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.492 million in Aug 2012 to 115.469 million in Oct 2012 or increase of 0.977 million full-time jobs in two months and further to 115.918 million in Jan 2013 or increase of 1.426 million more full-time jobs in four months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.841 in Feb 2013. Benchmark and seasonality-factors adjustments at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.0151 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 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. 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 2013 is 114.191 million, which is lower by 9.028 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 244.828 million in Feb 2013 or by 12.870 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 9.028 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 13 million. Growth at 2.1 percent on average in the fourteen quarters of expansion from IIIQ2009 to IVQ2012 compared with 6.2 percent on average in expansions from postwar cyclical contractions is the main culprit of the fractured US labor market (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html).
Table I-9, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions
| Part-time Thousands | Full-time Millions | |
| Seasonally Adjusted | ||
| Feb 2013 | 7,988 | 115.841 |
| Jan 2013 | 7,973 | 115.918 |
| Dec 2012 | 7,918 | 115.868 |
| Nov 2012 | 8,138 | 115.665 |
| Oct 2012 | 8,286 | 115.469 |
| Sep 2012 | 8,607 | 115.259 |
| Aug 2012 | 8,043 | 114.492 |
| Jul 2012 | 8,245 | 114.478 |
| Jun 2012 | 8,210 | 114.606 |
| May 2012 | 8,116 | 114.300 |
| Apr 2012 | 7,896 | 114.441 |
| Mar 2012 | 7,664 | 115.145 |
| Feb 2012 | 8,127 | 114.263 |
| Jan 2012 | 8,220 | 113.833 |
| Dec 2011 | 8,168 | 113.820 |
| Nov 2011 | 8,436 | 113.217 |
| Oct 2011 | 8,726 | 112.871 |
| Sep 2011 | 9,101 | 112.541 |
| Aug 2011 | 8,816 | 112.555 |
| Jul 2011 | 8,416 | 112.141 |
| Not Seasonally Adjusted | ||
| Feb 2013 | 8,298 | 114.191 |
| Jan 2013 | 8,628 | 113.868 |
| Dec 2012 | 8,116 | 115.079 |
| Nov 2012 | 7,994 | 115.515 |
| Oct 2012 | 7,870 | 116.045 |
| Sep 2012 | 8,110 | 115.678 |
| Aug 2012 | 7,842 | 116.214 |
| Jul 2012 | 8,316 | 116.131 |
| Jun 2012 | 8,394 | 116.024 |
| May 2012 | 7,837 | 114.634 |
| Apr 2012 | 7,694 | 113.999 |
| Mar 2012 | 7,867 | 113.916 |
| Feb 2012 | 8,455 | 112.587 |
| Jan 2012 | 8,918 | 111.879 |
| Dec 2011 | 8,428 | 113.050 |
| Nov 2011 | 8,271 | 113.138 |
| Oct 2011 | 8,258 | 113.456 |
| Sep 2011 | 8,541 | 112.980 |
| Aug 2011 | 8,604 | 114.286 |
| Jul 2011 | 8,514 | 113.759 |
| Jun 2011 | 8,738 | 113.255 |
| May 2011 | 8,270 | 112.618 |
| Apr 2011 | 8,425 | 111.844 |
| Mar 2011 | 8,737 | 111.186 |
| Feb 2011 | 8,749 | 110.731 |
| Jan 2011 | 9,187 | 110.373 |
| Dec 2010 | 9,205 | 111.207 |
| Nov 2010 | 8,670 | 111.348 |
| Oct 2010 | 8,408 | 112.342 |
| Sep 2010 | 8,628 | 112.385 |
| Aug 2010 | 8,628 | 113.508 |
| Jul 2010 | 8,737 | 113.974 |
| Jun 2010 | 8,867 | 113.856 |
| May 2010 | 8,513 | 112.809 |
| Apr 2010 | 8,921 | 111.391 |
| Mar 2010 | 9,343 | 109.877 |
| Feb 2010 | 9,282 | 109.100 |
| Jan 2010 | 9,290 | 108.777 (low) |
| Dec 2009 | 9,354 (high) | 109.875 |
| Nov 2009 | 8,894 | 111.274 |
| Oct 2009 | 8,474 | 111.599 |
| Sep 2009 | 8,255 | 111.991 |
| Aug 2009 | 8,835 | 113.863 |
| Jul 2009 | 9,103 | 114.184 |
| Jun 2009 | 9,301 | 114.014 |
| May 2009 | 8,785 | 113.083 |
| Apr 2009 | 8,648 | 112.746 |
| Mar 2009 | 9,305 | 112.215 |
| Feb 2009 | 9,170 | 112.947 |
| Jan 2009 | 8,829 | 113.815 |
| Dec 2008 | 8,250 | 116.422 |
| Nov 2008 | 7,135 | 118.432 |
| Oct 2008 | 6,267 | 120.020 |
| Sep 2008 | 5,701 | 120.213 |
| Aug 2008 | 5,736 | 121.556 |
| Jul 2008 | 6,054 | 122.378 |
| Jun 2008 | 5,697 | 121.845 |
| May 2008 | 5,096 | 120.809 |
| Apr 2008 | 5,071 | 120.027 |
| Mar 2008 | 5,038 | 119.875 |
| Feb 2008 | 5,114 | 119.452 |
| Jan 2008 | 5,340 | 119.332 |
| Dec 2007 | 4,750 | 121.042 |
| Nov 2007 | 4,374 | 121.846 |
| Oct 2007 | 4,028 | 122.006 |
| Sep 2007 | 4,137 | 121.728 |
| Aug 2007 | 4,494 | 122.870 |
| Jul 2007 | 4,516 | 123.219 (high) |
| Jun 2007 | 4,469 | 122.150 |
| May 2007 | 4,315 | 120.846 |
| Apr 2007 | 4,205 | 119.609 |
| Mar 2007 | 4,384 | 119.640 |
| Feb 2007 | 4,417 | 119.041 |
| Jan 2007 | 4,726 | 119.094 |
| Dec 2006 | 4,281 | 120.371 |
| Nov 2006 | 4,054 | 120.507 |
| Oct 2006 | 4,010 | 121.199 |
| Sep 2006 | 3,735 (low) | 120.780 |
| Aug 2006 | 4,104 | 121.979 |
| Jul 2006 | 4,450 | 121.951 |
| Jun 2006 | 4,456 | 121.070 |
| May 2006 | 3,968 | 118.925 |
| Apr 2006 | 3,787 | 118.559 |
| Mar 2006 | 4,097 | 117.693 |
| Feb 2006 | 4,403 | 116.823 |
| Jan 2006 | 4,597 | 116.395 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
People lose their marketable job skills after prolonged unemployment and find 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 2001-2013
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 2001-2013
Sources: US Bureau of Labor Statistics
IA3 Ten Million Fewer Full-time Jobs. Chart I-20 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 2013 with fluctuations around the typical behavior of a stationary series: there is no improvement in the United States in creating full-time jobs.
Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2013
Sources: US Bureau of Labor Statistics
Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2013. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.
Chart I-20A, US, Noninstitutional Civilian Population, 2001-2013
Sources: US Bureau of Labor Statistics
Chart I-20B provides number of full-time jobs in the US from 1968 to 2013. There were multiple recessions followed by expansions without contraction of full-time jobs without recovery as during the period after 2008.
Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2013
Sources: US Bureau of Labor Statistics
Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.
Chart I-20C, US, Noninstitutional Civilian Population, 2001-2013
Sources: US Bureau of Labor Statistics
IA4 Youth Unemployment and Middle-Aged Unemployment. 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. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.914 million in Jul 2006 with 19.461 million in Jul 2012 for 2.453 million fewer youth jobs. There are two hardships behind these data. First, young people cannot find employment after finishing high-school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.
Table I-10, US, Employment Level 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Nov | Dec | Annual |
| 2001 | 19678 | 19745 | 19800 | 19675 | 19547 | 20088 |
| 2002 | 18653 | 19074 | 19091 | 19397 | 19394 | 19683 |
| 2003 | 18811 | 18880 | 18709 | 19163 | 19136 | 19351 |
| 2004 | 18852 | 18841 | 18752 | 19615 | 19619 | 19630 |
| 2005 | 18858 | 18670 | 18989 | 19750 | 19733 | 19770 |
| 2006 | 19003 | 19182 | 19291 | 19903 | 20129 | 20041 |
| 2007 | 19407 | 19415 | 19538 | 19660 | 19361 | 19875 |
| 2008 | 18724 | 18546 | 18745 | 18454 | 18378 | 19202 |
| 2009 | 17467 | 17606 | 17564 | 16689 | 16615 | 17601 |
| 2010 | 16166 | 16412 | 16587 | 16946 | 16727 | 17077 |
| 2011 | 16512 | 16638 | 16898 | 17402 | 17234 | 17362 |
| 2012 | 16944 | 17150 | 17301 | 17877 | 17604 | 17834 |
| 2013 | 17183 | 17257 |
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 2013. Employment level is sharply lower in Jun 2012 relative to the peak in 2007.
Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2013
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. This situation may persist for many years.
Table I-11, US, Unemployment Level 16-24 Years, Thousands NSA
| Year | Jan | Feb | Mar | Apr | Dec | Annual |
| 2001 | 2250 | 2258 | 2253 | 2095 | 2412 | 2371 |
| 2002 | 2754 | 2731 | 2822 | 2515 | 2374 | 2683 |
| 2003 | 2748 | 2740 | 2601 | 2572 | 2248 | 2746 |
| 2004 | 2767 | 2631 | 2588 | 2387 | 2294 | 2638 |
| 2005 | 2661 | 2787 | 2520 | 2398 | 2055 | 2521 |
| 2006 | 2366 | 2433 | 2216 | 2092 | 2007 | 2353 |
| 2007 | 2363 | 2230 | 2096 | 2074 | 2323 | 2342 |
| 2008 | 2633 | 2480 | 2347 | 2196 | 2928 | 2830 |
| 2009 | 3278 | 3457 | 3371 | 3321 | 3532 | 3760 |
| 2010 | 3983 | 3888 | 3748 | 3803 | 3352 | 3857 |
| 2011 | 3851 | 3696 | 3520 | 3365 | 3161 | 3634 |
| 2012 | 3416 | 3507 | 3294 | 3175 | 3153 | 3451 |
| 2013 | 3674 | 3449 |
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
Chart I-22 provides the unemployment level ages 16 to 24 from 2002 to 2012. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013.
Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2013
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. During the seasonal peak in Jul the rate of youth unemployed was 18.1 percent in Jul 2011 and 17.1 percent in Jul 2012 compared with 10.8 percent in Jul 2007.
Table I-12, US, Unemployment Rate 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Apr | May | Jun | Nov | Dec | Annual |
| 2001 | 10.3 | 10.3 | 10.2 | 9.6 | 10.0 | 11.6 | 11.2 | 11.0 | 10.6 |
| 2002 | 12.9 | 12.5 | 12.9 | 11.6 | 11.6 | 13.2 | 11.7 | 10.9 | 12.0 |
| 2003 | 12.7 | 12.7 | 12.2 | 12.0 | 13.0 | 14.8 | 11.6 | 10.5 | 12.4 |
| 2004 | 12.8 | 12.3 | 12.1 | 11.1 | 12.2 | 13.4 | 11.1 | 10.5 | 11.8 |
| 2005 | 12.4 | 13.0 | 11.7 | 11.2 | 11.9 | 12.6 | 10.7 | 9.4 | 11.3 |
| 2006 | 11.1 | 11.3 | 10.3 | 9.7 | 10.2 | 11.9 | 10.1 | 9.1 | 10.5 |
| 2007 | 10.9 | 10.3 | 9.7 | 9.7 | 10.2 | 12.0 | 10.3 | 10.7 | 10.5 |
| 2008 | 12.3 | 11.8 | 11.1 | 10.3 | 13.3 | 14.4 | 13.3 | 13.7 | 12.8 |
| 2009 | 15.8 | 16.4 | 16.1 | 15.8 | 18.0 | 19.9 | 18.1 | 17.5 | 17.6 |
| 2010 | 19.8 | 19.2 | 18.4 | 18.5 | 18.4 | 20.0 | 17.4 | 16.7 | 18.4 |
| 2011 | 18.9 | 18.2 | 17.2 | 16.5 | 17.5 | 18.9 | 15.9 | 15.5 | 17.3 |
| 2012 | 16.8 | 17.0 | 16.0 | 15.4 | 16.3 | 18.1 | 14.8 | 15.2 | 16.2 |
| 2013 | 17.6 | 16.7 |
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 2002 to 2013. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels during the fourteen consecutive quarters of expansion of the economy since IIIQ2009 because of much lower growth at 2.1 percent annual equivalent on average compared with 6.2 percent on average in cyclical expansions since World War II (Table I -5 http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html).
Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2013
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 2013. 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 claim 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 while 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 and 16.7 percent in Feb 2013. In Jul 2007, the rate of youth unemployment was 10.8 percent, increasing to 17.1 percent in Jul 2012. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.2 percent on average during the first fourteen quarters of expansion from IIIQ2009 to IVQ2012 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html). The fractured US labor market denies an early start for young people.
Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2013
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 matured 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 1.985 million in Jul 2006 to 4.821 million in July 2010 or by 142.9 percent. The number of unemployed ages 45 years and over declined to 4.405 million in Jul 2012 that is still higher by 121.9 percent than in Jul 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 and at 3.927 million in Dec 2012 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 4.107 million in Feb 2013 is higher by 2.051 million than 2.056 million in Feb 2006 or higher by 100.0 percent.
Table I-13, US, Unemployment Level 45 Years and Over, Thousands NSA
| Year | Jan | Feb | Mar | Apr | Dec | Annual |
| 2000 | 1498 | 1392 | 1291 | 1062 | 1217 | 1249 |
| 2001 | 1572 | 1587 | 1533 | 1421 | 1901 | 1576 |
| 2002 | 2235 | 2280 | 2138 | 2101 | 2210 | 2114 |
| 2003 | 2495 | 2415 | 2485 | 2287 | 2130 | 2253 |
| 2004 | 2453 | 2397 | 2354 | 2160 | 2086 | 2149 |
| 2005 | 2286 | 2286 | 2126 | 1939 | 1963 | 2009 |
| 2006 | 2126 | 2056 | 1881 | 1843 | 1794 | 1848 |
| 2007 | 2155 | 2138 | 2031 | 1871 | 2120 | 1966 |
| 2008 | 2336 | 2336 | 2326 | 2104 | 3485 | 2540 |
| 2009 | 4138 | 4380 | 4518 | 4172 | 4960 | 4500 |
| 2010 | 5314 | 5307 | 5194 | 4770 | 4762 | 4879 |
| 2011 | 5027 | 4837 | 4748 | 4373 | 4182 | 4537 |
| 2012 | 4458 | 4472 | 4390 | 4037 | 3927 | 4133 |
| 2013 | 4394 | 4107 |
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 sharp increase during the global recession and inadequate decline. There was an increase during the 2001 recession and then stability. The US is facing a major challenge of reemploying middle-aged workers.
Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/data/
IB Destruction of Household Wealth for Inflation Adjusted Loss. The 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/default.htm http://www.federalreserve.gov/apps/fof/) is rich in valuable information. Table IIA-1, updated in this blog for every new quarterly release, shows the balance sheet of US households combined with nonprofit organizations in 2007, 2011 and 2012. The data show the strong shock to US wealth during the contraction. Assets fell from $80.4 trillion in 2007 to $74.0 trillion in 2011 even after nine consecutive quarters of growth beginning in IIIQ2009 (http://wwwdev.nber.org/cycles/cyclesmain.html http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html), for decline of $6.4 trillion or 7.5 percent. Assets stood at $79.5 trillion in 2012 for loss of $0.9 trillion relative to $80.4 trillion in 2007 or decline by 1.1 percent. Liabilities declined from $14.3 trillion in 2007 to $13.4 trillion in 2011 or by $854.6 billion equivalent to decline by 6.0 percent. Liabilities declined $822.3 billion or 5.8 percent from 2007 to 2012 but increased 0.2 percent from 2011 to 2012. Net worth shrank from $66.1 trillion in 2007 to $60.6 trillion in 2011, that is, $5.5 trillion equivalent to decline of 8.3 percent. Net worth declined $46.6 billion from 2007 to 2012 or 0.1 percent and increased 9.0 percent from 2011 to 2012. There was brutal decline from 2007 to 2012 of $3.6 trillion in real estate assets or by 15.2 percent. The National Association of Realtors estimated that the gains in net worth in homes by Americans were about $4 trillion between 2000 and 2005 (quoted in Pelaez and Pelaez, The Global Recession Risk (2007), 224-5).
Table IB-1, US, Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars Outstanding End of Period, NSA
| 2007 | 2011 | 2012 | |
| Assets | 80,393.7 | 74,028.8 | 79,524.8 |
| Nonfinancial | 28,207.4 | 23,423.5 | 25,134.4 |
| Real Estate | 23,477.1 | 18,373.8 | 19,914.4 |
| Durable Goods | 4,468.3 | 4,732.2 | 4,885.6 |
| Financial | 52,186.2 | 50,605.3 | 54,390.5 |
| Deposits | 7,478.6 | 8,561.7 | 9,045.6 |
| Credit Market | 4,949.3 | 5,192.2 | 5,230.6 |
| Mutual Fund Shares | 4,589.2 | 4,384.2 | 5,300.9 |
| Equities Corporate | 9,710.2 | 8,850.1 | 9,770.5 |
| Equity Noncorporate | 9,325.8 | 7,650.7 | 8,079.1 |
| Pension | 13,477.7 | 13,133.2 | 14,060.7 |
| Liabilities | 14,275.4 | 13,420.8 | 13,453.1 |
| Home Mortgages | 10,579.7 | 9,660.7 | 9,430.5 |
| Consumer Credit | 2,528.8 | 2,627.4 | 2,779.2 |
| Net Worth | 66,118.3 | 60,608.0 | 66,071.7 |
Net Worth = Assets – Liabilities
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7. http://www.federalreserve.gov/releases/z1/default.htm
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 IB-2 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 96.1 percent in the 10-city composite of the Case-Shiller home price index and 81.4 percent in the 20-city composite between Nov 2000 and Nov 2005. Prices rose around 100 percent from Nov 2000 to Nov 2006, increasing 98.9 percent for the 10-city composite and 84.7 percent for the 20-city composite. House prices rose 38.4 percent between Nov 2003 and Nov 2005 for the 10-city composite and 34.7 percent for the 20-city composite propelled by low fed funds rates of 1.0 percent between Jun 2003 and Jun 2004 and then only increasing by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Nov 2003 and Nov 2006 the 10-city index gained 40.5 percent and the 20-city index increased 37.1 percent. House prices have fallen from Nov 2006 to Nov 2012 by 29.3 percent for the 10-city composite and 28.7 percent for the 20-city composite. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Nov 2012, house prices increased 4.5 percent in the 10-city composite and increased 5.5 percent in the 20-city composite. Table IB-2 also shows that house prices increased 40.6 percent between Nov 2000 and Nov 2012 for the 10-city composite and increased 31.6 percent for the 20-city composite. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The 10-city composite fell 30.1 percent from the peak in Jun 2006 to Nov 2012 and the 20-city composite fell 29.4 percent from the peak in Jul 2006 to Nov 2012. The final part of Table IB-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 2011 for the 10-city composite was 3.8 percent. Data for the 20-city composite are available only beginning in Jan 2000. House prices accelerated in the 1990s with the average rate of the 10-city composite of 5.0 percent between Dec 1992 and Dec 2000 while the average rate for the period Dec 1987 to Dec 2000 was 3.8 percent. Although the global recession affecting the US between IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly above 30 percent, the average annual growth rate of the 10-city composite between Dec 2000 and Dec 2011 was 2.3 percent while the rate of the 20-city composite was 1.9 percent.
Table IB-2, US, Percentage Changes of Standard & Poor’s Case-Shiller Home Price Indices, Not Seasonally Adjusted, ∆%
| 10-City Composite | 20-City Composite | |
| ∆% Nov 2000 to Nov 2003 | 41.7 | 34.7 |
| ∆% Nov 2000 to Nov 2005 | 96.1 | 81.4 |
| ∆% Nov 2003 to Nov 2005 | 38.4 | 34.7 |
| ∆% Nov 2000 to Nov 2006 | 98.9 | 84.7 |
| ∆% Nov 2003 to Nov 2006 | 40.4 | 37.1 |
| ∆% Nov 2005 to Nov 2012 | -28.3 | -27.4 |
| ∆% Nov 2006 to Nov 2012 | -29.3 | -28.7 |
| ∆% Nov 2009 to Nov 2012 | 0.0 | -0.2 |
| ∆% Nov 2010 to Nov 2012 | 0.5 | 1.4 |
| ∆% Nov 2011 to Nov 2012 | 4.5 | 5.5 |
| ∆% Nov 2000 to Nov 2012 | 40.6 | 31.6 |
| ∆% Peak Jun 2006 Nov 2012 | -30.1 | |
| ∆% Peak Jul 2006 Nov 2012 | -29.4 | |
| Average ∆% Dec 1987-Dec 2011 | 3.1 | NA |
| Average ∆% Dec 1987-Dec 2000 | 3.8 | NA |
| Average ∆% Dec 1992-Dec 2000 | 5.0 | NA |
| Average ∆% Dec 2000-Dec 2011 | 2.3 | 1.9 |
Table IB-3 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2011 with apparent mitigation in 2012 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 71 percent of GDP, generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and 2012, real estate fell in value by $3.6 trillion and financial assets increased $2.2 trillion for net loss of real estate and financial assets of $1.4 trillion, explaining most of the drop in net worth of $46.6 billion obtained by adding the decrease in liabilities of $822.3 billion to the decrease of assets of $868.9 billion. Calculations show that actual economic growth in the US is around 1.6 to 2.0 percent per year. This rate is well below 3 percent per year in trend from 1870 to 2010, which has been always recovered after events such as wars and recessions (Lucas 2011May). Growth is not only mediocre but sharply decelerating to a rhythm that is not consistent with reduction of unemployment and underemployment of 30.8 million people corresponding to 19.0 percent of the effective labor force of the United States (http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). In the four quarters of 2011 and the four quarters of 2012, US real GDP grew at the seasonally-adjusted annual equivalent rates of 0.1 percent in the first quarter of 2011 (IQ2011), 2.5 percent in IIQ2011, 1.3 percent in IIIQ2011, 4.1 percent in IVQ2011, 2.0 percent in IQ2012, 1.3 percent in IIQ2012, 3.1 percent in IIIQ2012 and revised 0.1 percent in IVQ2012. GDP growth in IIIQ2012 was revised from 2.7 percent seasonally adjusted annual rate (SAAR) to 3.1 percent but mostly because of contribution of 0.73 percentage points of inventory accumulation and one-time contribution of 0.64 percentage points of expenditures in national defense that without them would have reduced growth from 3.1 percent to 1.73 percent. Equally, GDP growth in IVQ2012 is measured in the advanced estimate as 0.1 percent but mostly because of deduction of divestment of inventories of 1.55 percentage points and deduction of one-time national defense expenditures of 1.28 percentage points. The annual equivalent rate of growth of GDP for the four quarters of 2011 and the four quarters of 2012 is 2.0 percent, obtained as follows. Discounting 0.1 percent to one quarter is 0.025 percent {[(1.001)1/4 -1]100 = 0.025}; discounting 2.5 percent to one quarter is 0.62 percent {[(1.025)1/4 – 1]100}; discounting 1.3 percent to one quarter is 0.32 percent {[(1.013)1/4 – 1]100}; discounting 4.1 percent to one quarter is 1.0 {[(1.04)1/4 -1]100; discounting 2.0 percent to one quarter is 0.50 percent {[(1.020)1/4 -1]100); discounting 1.3 percent to one quarter is 0.32 percent {[(1.013)1/4 -1]100}; discounting 3.1 percent to one quarter is 0.77 {[(1.031)1/4 -1]100); and discounting 0.1 percent to one quarter is 0.025 percent {[(1.001)1/4 – 1]100}. Real GDP growth in the four quarters of 2011 and the four quarters of 2012 accumulated to 3.6 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.00025) - 1]100 = 3.6%}. This is equivalent to growth from IQ2011 to IVQ2012 obtained by dividing the seasonally-adjusted annual rate (SAAR) of IVQ2012 of $13,656.8 billion by the SAAR of IVQ2010 of $13,181.2 (http://www.bea.gov/iTable/iTable.cfm?ReqID=9&step=1) and expressing as percentage {[($13,658.8/$13,181.2) - 1]100 = 3.6%}. The growth rate in annual equivalent for the four quarters of 2011 and the four quarters of 2012 is 1.8 percent {[(1.00025 x 1.0062 x 1.0032 x 1.010 x 1.005 x 1.0032 x 1.0077 x 1.00025)4/8 -1]100 = 1.8%], or {[($13,656.8/$13,181.2)]4/8-1]100 = 1.8%} dividing the SAAR of IVQ2012 by the SAAR of IVQ2010 in Table II-6 below, obtaining the average for eight quarters and the annual average for one year of four quarters. Growth in the four quarters of 2012 accumulates to 1.6 percent {[(1.02)1/4(1.013)1/4(1.031)1/4(1.001)1/4 -1]100 = 1.6%}. This is equivalent to dividing the SAAR of $13,656.8 billion for IVQ2012 by the SAAR of $13,441.0 billion in IVQ2011 to obtain 1.6 percent {[($13,656.8/$13,441.0) – 1]100 = 1.6%}. The US economy is still close to a standstill especially considering the GDP report in detail. Excluding growth at the SAAR of 2.5 percent in IIQ2011 and 4.1 percent in IVQ2011 while converting growth in IIIQ2012 to 1.73 percent by deducting from 3.1 percent one-time inventory accumulation of 0.73 percentage points and national defense expenditures of 0.64 percentage points and converting growth in IVQ2012 by adding 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditure reductions to obtain 2.84 percent, the US economy grew at 1.5 percent in the remaining six quarters {[(1.00025x1.0032x1.005x1.0032x1.0043x1.0070)4/6 – 1]100 = 1.5%} with declining growth trend in three consecutive quarters from 4.1 percent in IVQ2011, to 2.0 percent in IQ2012, 1.3 percent in IIQ2012, 3.1 percent in IIIQ2012 that is more like 1.73 percent without inventory accumulation and national defense expenditures and 0.1 percent in IVQ2012 that is more likely 2.84 percent by adding 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditures. Weakness of growth is more clearly shown by adjusting the exceptional one-time contributions to growth from items that are not aggregate demand: 2.53 percentage points contributed by inventory change to growth of 4.1 percent in IVQ2011; 0.64 percentage points contributed by expenditures in national defense together with 0.73 points of inventory accumulation to growth of 3.1 percent in IIIQ2012; and deduction of 1.55 percentage points of inventory divestment and 1.28 percentage points of national defense expenditure reductions. The Bureau of Economic Analysis (BEA) of the US Department of Commerce released on Thus Feb 28, 2012, the second estimate of GDP for IVQ2012 at 0.1 percent seasonally-adjusted annual rate (SAAR) (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp4q12_2nd.pdf). In the four quarters of 2012, the US economy is growing at the annual equivalent rate of 2.0 percent {([(1.021/4(1.013)1/4(1.0173)1/4(1.0284)1/4]-1)100 = 2.0%} by excluding inventory accumulation of 0.73 percentage points and exceptional defense expenditures of 0.64 percentage points from growth 3.1 percent at SAAR in IIIQ2012 to obtain adjusted 1.73 percent SSAR and adding 1.28 percentage points of national defense expenditure reductions and 1.55 percentage points of inventory divestment to growth of 0.1 percent SAAR in IVQ2012 to obtain 2.84 percent.
Table IB-3, US, Difference of Balance Sheet of Households and Nonprofit Organizations Billions of Dollars from 2007 to 2011 and 2012
| Value 2007 | Change to 2009 | Change to 2011 | Change to 2012 | |
| Assets | 80,393.7 | -10,787.5 | -6,364.9 | -868.9 |
| Nonfinancial | 28,207.4 | -4,426.3 | -4,783.9 | -3,073.0 |
| Real Estate | 23,477.1 | -4,572.4 | -5,103.3 | -3,562.7 |
| Financial | 52,186.2 | -6,361.1 | -1,580.9 | 2,204.3 |
| Liabilities | 14,275.4 | -387.5 | -854.6 | -822.3 |
| Net Worth | 66,118.3 | -10,400.1 | -5,510.3 | -46.6 |
Net Worth = Assets – Liabilities
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7.
http://www.federalreserve.gov/releases/z1/default.htm
The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and also from IVQ1979) to IVQ1985 and from IVQ2007 to IVQ2012 is provided in Table IB-4. Net worth of households and nonprofit organizations increased from $8,326.4 billion in IVQ1979 to $14,395.2 billion in IVQ1985 by 72.9 percent or 69.3 percent from $8,502.9 billion in IQ1980. The starting quarter does not bias the results. The US consumer price index not seasonally adjusted increased from 76.7 in Dec 1979 to 109.3 in Dec 1985 or 42.5 percent or 36.5 percent from 80.1 in Mar 1980 (using consumer price index data from the US Bureau of Labor Statistics at http://www.bls.gov/cpi/data.htm). In terms of purchasing power measured by the consumer price index, real wealth of households and nonprofit organizations increased 21.3 percent in constant purchasing power from IVQ1979 to IVQ1985 or 24.0 percent from IQ1980. In contrast, as shown in Table IB-4, net worth of households and nonprofit organizations fell from $66,118.3 billion in IVQ2007 to $66,071.7 billion in IVQ2012 by $46.6 billion or 0.1 percent. The US consumer price index was 210.036 in Dec 2007 and 229.601 in Dec 2012 for increase of 9.1 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 8.4 percent in 2012 than in 2007 after fourteen consecutive quarters of expansion from IIIQ2009 to IVQ2012 relative to IVQ2007 when the recession began. The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. The average growth rate from IIIQ2009 to IVQ2012 has been 2.1 percent, which is substantially lower than the average of 6.2 percent in cyclical expansions after World War II and 5.7 percent in the expansion from IQ1983 to IVQ1985 (http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions.
Table IB-4, Net Worth of Households and Nonprofit Organizations in Billions of Dollars, IVQ1979 to IVQ1985 and IVQ2007 to IVQ2012
| Period IQ1980 to IVQ1985 | |
| Net Worth of Households and Nonprofit Organizations USD Millions | |
| IVQ1979 IQ1980 | 8,326.4 8,502.9 |
| IVQ1985 | 14,395.2 |
| ∆ USD Billions IQ1980 | +6,068.8 +5,892.3 |
| Period IVQ2007 to IIQ2012 | |
| Net Worth of Households and Nonprofit Organizations USD Millions | |
| IVQ2007 | 66,118.3 |
| IVQ2012 | 66,071.7 |
| ∆ USD Billions | -46.6 |
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar 7. http://www.federalreserve.gov/releases/z1/default.htm
Chart IB-1 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ2007 to IVQ2012. There is remarkable stop and go behavior in this series with two sharp declines and two standstills in the 14 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.
Chart IB-1, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ2007 to IVQ2012
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7.
http://www.federalreserve.gov/releases/z1/default.htm
Chart IB-2 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1979 to IVQ1985. 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 $5482.1 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.74 percent of GDP in a year. US GDP in 2011 is estimated at $15,681.5 billion, such that the bailout would be equivalent to cost to taxpayers of about $429.7 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).
Chart IB-2, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1979 to IVQ1985
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7.
http://www.federalreserve.gov/releases/z1/default.htm
Chart IIA-3 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1945 at $710,125.9 million to IVQ2012 at $66,071.7 billion or increase of 9,204.2 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 229.601 in Dec 2012 or 1,161.5 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 67 years with inflation adjusted increase of 637.5 percent. The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIQ2009 caused sharp contraction of US household and nonprofit net worth. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 67 years when US GDP grew at 2.1 percent on average in fourteen quarters between IIIQ2009 and IVQ2012 in contrast with average 5.7 percent from IQ1983 to IVQ1985 and average 6.2 percent during cyclical expansions in major postwar economic cycles (http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html).
Chart IB-3, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1945 to IVQ2012
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7.
http://www.federalreserve.gov/releases/z1/default.htm
Households increased debt by 9.9 percent in 2006 but have been reducing their debt continuously with the exception of growth at 0.1 percent in IVQ2011 and 1.3 percent in IIQ2012 but renewed decrease at 2.0 percent in IIIQ2012 and increase at 2.4 percent in IVQ2012. Financial repression by zero fed funds rates or negative interest rates is intended to increase debt and reduce savings. Business had not been as exuberant in acquiring debt and has been increasing debt benefitting from historically low costs while increasing cash holdings to around $2 trillion by swelling undistributed profits because of the uncertainty of capital budgeting. The key to growth and hiring consists in creating the incentives for business to invest and hire. States and local government were forced into increasing debt by the decline in revenues but began to contract in IQ2011, decreasing again from IQ2011 to IQ2012, increasing at 3.1 percent in IIQ2012 and decreasing at 0.1 percent in IIIQ2012 and 3.7 percent in IVQ2012. Opposite behavior is found for the federal government that has been rapidly accumulating debt but without success in the self-assigned goal of promoting economic growth. Financial repression constitutes seigniorage of government debt (http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-financial.html http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-monetary.html).
Table IB-4, US, Percentage Change of Nonfinancial Domestic Sector Debt
| Total | Households | Business | State & | Federal | |
| IVQ2012 | 6.4 | 2.4 | 8.7 | -3.7 | 11.2 |
| IIIQ2012 | 2.6 | -2.0 | 4.7 | -0.1 | 6.2 |
| IIQ2012 | 5.2 | 1.3 | 4.9 | 3.1 | 10.9 |
| IQ2012 | 4.7 | -0.9 | 4.2 | 0.0 | 13.7 |
| IVQ 20111 | 5.0 | 0.1 | 5.2 | -1.2 | 12.7 |
| IIIQ 2011 | 4.3 | -1.7 | 4.3 | -0.2 | 13.7 |
| IIQ 2011 | 2.6 | -2.7 | 5.4 | -2.8 | 8.2 |
| IQ 2011 | 2.5 | -2.0 | 3.8 | -2.8 | 9.1 |
| 2012 | 4.8 | 0.2 | 5.7 | -0.2 | 10.9 |
| 2011 | 3.7 | -1.6 | 4.8 | -1.7 | 11.4 |
| 2010 | 4.1 | -2.7 | 1.4 | 2.3 | 20.2 |
| 2009 | 3.1 | -1.7 | -2.1 | 4.0 | 22.7 |
| 2008 | 5.8 | -0.2 | 6.2 | 0.6 | 24.2 |
| 2007 | 8.5 | 6.6 | 13.7 | 5.5 | 4.9 |
| 2006 | 8.6 | 9.9 | 10.9 | 3.9 | 3.9 |
| 2005 | 9.2 | 11.2 | 9.0 | 5.8 | 7.0 |
| 2004 | 9.3 | 11.1 | 6.7 | 9.5 | 9.0 |
| 2003 | 8.0 | 11.8 | 2.2 | 8.3 | 10.9 |
| 2002 | 7.3 | 10.6 | 3.0 | 11.1 | 7.6 |
| 2001 | 6.3 | 9.6 | 5.7 | 8.8 | -0.2 |
Source: Quarterly data are at seasonally-adjusted annual rates (SAAR).
Source: Board of Governors of the Federal Reserve System. 2013Mar7. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System, Mar7. http://www.federalreserve.gov/releases/z1/default.htm
IIB Unresolved US Balance of Payments Deficits and Fiscal Imbalance Threatening Risk Premium on Treasury Securities. The current account of the US balance of payments is provided in Table IC-1 for IVQ2011 and IVQ2012. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US decreased from $117.9 billion in IVQ2011, or 3.1 percent of GDP, to $111.2 billion in IIIQ2012, or 2.8 percent of GDP. The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession but is combined now with much higher imbalance in the Treasury budget (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71).
Table IC-1, US Balance of Payments, Millions of Dollars NSA
| IVQ2011 | IVQ2012 | Difference | |
| Goods Balance | -186,332 | -176,774 | 9,558 |
| X Goods | 387,237 | 399,304 | 3.1 ∆% |
| M Goods | -573,569 | -576,078 | 0.4 ∆% |
| Services Balance | 44,252 | 52,148 | 3,647 |
| X Services | 151,164 | 158,749 | 5.0 ∆% |
| M Services | -106,912 | -106,601 | -0.3 ∆% |
| Balance Goods and Services | -142,080 | -124,626 | 17,454 |
| Balance Income | 56,263 | 48,293 | -7,970 |
| Unilateral Transfers | -32,135 | -34,827 | -2,692 |
| Current Account Balance | -117,952 | -111,159 | 6,793 |
| % GDP | IVQ2011 | IVQ2012 | IIIQ2012 |
| 3.1 | 2.8 | 2.8 |
X: exports; M: imports
Balance on Current Account = Balance on Goods and Services + Balance on Income + Unilateral Transfers
Source: Bureau of Economic Analysis http://www.bea.gov/international/index.htm#bop http://www.bea.gov/iTable/index_nipa.cfm
In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):
“Imagine that fiscal policy dominates monetary policy. The fiscal authority independently sets its budgets, announcing all current and future deficits and surpluses and thus determining the amount of revenue that must be raised through bond sales and seignorage. Under this second coordination scheme, the monetary authority faces the constraints imposed by the demand for government bonds, for it must try to finance with seignorage any discrepancy between the revenue demanded by the fiscal authority and the amount of bonds that can be sold to the public. Suppose that the demand for government bonds implies an interest rate on bonds greater than the economy’s rate of growth. Then if the fiscal authority runs deficits, the monetary authority is unable to control either the growth rate of the monetary base or inflation forever. If the principal and interest due on these additional bonds are raised by selling still more bonds, so as to continue to hold down the growth of base money, then, because the interest rate on bonds is greater than the economy’s growth rate, the real stock of bonds will growth faster than the size of the economy. This cannot go on forever, since the demand for bonds places an upper limit on the stock of bonds relative to the size of the economy. Once that limit is reached, the principal and interest due on the bonds already sold to fight inflation must be financed, at least in part, by seignorage, requiring the creation of additional base money.”
The alternative fiscal scenario of the CBO (2012NovCDR) resembles an economic world in which eventually the placement of debt reaches a limit of what is proportionately desired of US debt in investment portfolios. This unpleasant environment is occurring in various European countries.
The current real value of government debt plus monetary liabilities depends on the expected discounted values of future primary surpluses or difference between tax revenue and government expenditure excluding interest payments (Cochrane 2011Jan, 27, equation (16)). There is a point when adverse expectations about the capacity of the government to generate primary surpluses to honor its obligations can result in increases in interest rates on government debt.
This analysis suggests that there may be a point of saturation of demand for United States financial liabilities without an increase in interest rates on Treasury securities. A risk premium may develop on US debt. Such premium is not apparent currently because of distressed conditions in the world economy and international financial system. Risk premiums are observed in the spread of bonds of highly indebted countries in Europe relative to bonds of the government of Germany.
The issue of global imbalances centered on the possibility of a disorderly correction (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). Such a correction has not occurred historically but there is no argument proving that it could not occur. The need for a correction would originate in unsustainable large and growing United States current account deficits (CAD) and net international investment position (NIIP) or excess of financial liabilities of the US held by foreigners net of financial liabilities of foreigners held by US residents. The IMF estimated that the US could maintain a CAD of two to three percent of GDP without major problems (Rajan 2004). The threat of disorderly correction is summarized by Pelaez and Pelaez, The Global Recession Risk (2007), 15):
“It is possible that foreigners may be unwilling to increase their positions in US financial assets at prevailing interest rates. An exit out of the dollar could cause major devaluation of the dollar. The depreciation of the dollar would cause inflation in the US, leading to increases in American interest rates. There would be an increase in mortgage rates followed by deterioration of real estate values. The IMF has simulated that such an adjustment would cause a decline in the rate of growth of US GDP to 0.5 percent over several years. The decline of demand in the US by four percentage points over several years would result in a world recession because the weakness in Europe and Japan could not compensate for the collapse of American demand. The probability of occurrence of an abrupt adjustment is unknown. However, the adverse effects are quite high, at least hypothetically, to warrant concern.”
The United States could be moving toward a situation typical of heavily indebted countries, requiring fiscal adjustment and increases in productivity to become more competitive internationally. The CAD and NIIP of the United States are not observed in full deterioration because the economy is well below potential. There are two complications in the current environment relative to the concern with disorderly correction in the first half of the past decade. Table IC-2 provides data on the US fiscal and balance of payments imbalances. In 2007, the federal deficit of the US was $161 billion corresponding to 1.2 percent of GDP while the Congressional Budget Office (CBO 2012NovCDR) estimates the federal deficit in 2012 at $1089 billion or 7.0 percent of GDP (http://cmpassocregulationblog.blogspot.com/2013/02/united-states-unsustainable-fiscal.html). The combined record federal deficits of the US from 2009 to 2012 are $5092 billion or 33 percent of the estimate of GDP of $15,549 billion for fiscal year 2012 by the CBO (http://www.cbo.gov/publication/43905 CBO (2013BEOFeb5)). The deficits from 2009 to 2012 exceed one trillion dollars per year, adding to $5092 trillion in four years, using the fiscal year deficit of $1089.4 billion for fiscal year 2012 (http://www.fms.treas.gov/mts/mts0912.txt), which is the worst fiscal performance since World War II. Federal debt in 2007 was $5035 billion, less than the combined deficits from 2009 to 2012 of $5092 billion. Federal debt in 2011 was 67.8 percent of GDP and is estimated to reach 72.5 percent of GDP in 2012 (CBO2012AugBEO, CBO2012NovCDR, CBO2013BEOFeb5). This situation may worsen in the future (CBO 2012LTBO):
“The budget outlook is much bleaker under the extended alternative fiscal scenario, which maintains what some analysts might consider “current policies,” as opposed to current laws. Federal debt would grow rapidly from its already high level, exceeding 90 percent of GDP in 2022. After that, the growing imbalance between revenues and spending, combined with spiraling interest payments, would swiftly push debt to higher and higher levels. Debt as a share of GDP would exceed its historical peak of 109 percent by 2026, and it would approach 200 percent in 2037.
The changes under this scenario would result in much lower revenues than would occur under the extended baseline scenario because almost all expiring tax provisions are assumed to be extended through 2022 (with the exception of the current reduction in the payroll tax rate for Social Security). After 2022, revenues under this scenario are assumed to remain at their 2022 level of 18.5 percent of GDP, just above the average of the past 40 years.
Outlays would be much higher than under the other scenario. This scenario incorporates assumptions that through 2022, lawmakers will act to prevent Medicare’s payment rates for physicians from declining; that after 2022, lawmakers will not allow various restraints on the growth of Medicare costs and health insurance subsidies to exert their full effect; and that the automatic reductions in spending required by the Budget Control Act of 2011 will not occur (although the original caps on discretionary appropriations in that law are assumed to remain in place). Finally, under this scenario, federal spending as a percentage of GDP for activities other than Social Security, the major health care programs, and interest payments is assumed to return to its average level during the past two decades, rather than fall significantly below that level, as it does under the extended baseline scenario.”
Table IC-2, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and %
| 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | |
| Goods & | -696 | -698 | -379 | -495 | -560 | -539 |
| Income | 101 | 147 | 119 | 184 | 227 | 198 |
| UT | -115 | -126 | -122 | -131 | -133 | -134 |
| Current Account | -710 | -677 | -382 | -442 | -466 | -475 |
| NGDP | 14028 | 14291 | 13974 | 14499 | 15076 | 15681 |
| Current Account % GDP | -5.1 | -4.7 | -2.7 | -3.1 | -3.1 | -3.0 |
| NIIP | -1796 | -3260 | -2321 | -2474 | -4030 | NA |
| US Owned Assets Abroad | 18399 | 19464 | 18512 | 20298 | 21132 | NA |
| Foreign Owned Assets in US | 20195 | 22724 | 20833 | 22772 | 25162 | NA |
| NIIP % GDP | -12.8 | -22.8 | -16.6 | -17.1 | -26.7 | NA |
| Exports | 2488 | 2657 | 2181 | 2519 | 2848 | 2937 |
| NIIP % | -72 | -123 | -106 | -98 | -142 | NA |
| DIA MV | 5274 | 3102 | 4287 | 4767 | 4499 | NA |
| DIUS MV | 3551 | 2486 | 2995 | 3397 | 3509 | NA |
| Fiscal Balance | -161 | -459 | -1413 | -1294 | -1296 | -1089 |
| Fiscal Balance % GDP | -1.2 | -3.2 | -10.1 | -9.0 | -8.7 | -7.0 |
| Federal Debt | 5035 | 5803 | 7545 | 9019 | 10128 | 11280 |
| Federal Debt % GDP | 36.3 | 40.5 | 54.1 | 62.9 | 67.8 | 72.5 |
| Federal Outlays | 2729 | 2983 | 3518 | 3456 | 3598 | 3538 |
| ∆% | 2.8 | 9.3 | 17.9 | -1.8 | 4.1 | -1.7 |
| % GDP | 19.7 | 20.8 | 25.2 | 24.1 | 24.1 | 22.8 |
| Federal Revenue | 2568 | 2524 | 2105 | 2162 | 2302 | 2449 |
| ∆% | 6.7 | -1.7 | -16.6 | 2.7 | 6.5 | 6.4 |
| % GDP | 18.5 | 17.6 | 15.1 | 15.1 | 15.4 | 15.8 |
Sources:
Notes: UT: unilateral transfers; NGDP: nominal GDP or in current dollars; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value. There are minor discrepancies in the decimal point of percentages of GDP between the balance of payments data and federal debt, outlays, revenue and deficits in which the original number of the CBO source is maintained. These discrepancies do not alter conclusions.
Sources: http://www.bea.gov/international/index.htm#bop Balance of Payments and NIIP, Bureau of Economic Analysis (BEA)
Gross Domestic Product, Bureau of Economic Analysis (BEA) http://www.bea.gov/iTable/index_nipa.cfm
Chart IC-2 of the Board of Governors of the Federal Reserve System provides the overnight Fed funds rate on business days from Jan 10, 1979, at 9.91 percent per year, to Mar 14, 2013, at 0.15 percent per year. US recessions are in shaded areas according to the reference dates of the NBER (http://www.nber.org/cycles.html). In the Fed effort to control the “Great Inflation” of the 1930s (see http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I The Great Inflation; see Taylor 1993, 1997, 1998LB, 1999, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB and http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html), the fed funds rate increased from 8.34 percent on Jan 3, 1979 to a high in Chart IC-2 of 22.36 percent per year on Jul 22, 1981 with collateral adverse effects in the form of impaired savings and loans associations in the United States, emerging market debt and money-center banks (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 72-7; Pelaez 1986, 1987). Another episode in Chart IC-2 is the increase in the fed funds rate from 3.15 percent on Jan 3, 1994, to 6.56 percent on Dec 21, 1994, which also had collateral effects in impairing emerging market debt in Mexico and Argentina and bank balance sheets in a world bust of fixed income markets during pursuit by central banks of non-existing inflation (Pelaez and Pelaez, International Financial Architecture (2005), 113-5). Another interesting policy impulse is the reduction of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of equally non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85), followed by increments of 25 basis points from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006 in Chart IC-2. Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment 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 interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).
The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity 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). A final episode in Chart IC-2 is the reduction of the fed funds rate from 5.41 percent on Aug 9, 2007, to 2.97 percent on October 7, 2008, to 0.12 percent on Dec 5, 2008 and close to zero throughout a long period with the final point at 0.16 percent on Mar 7, 2013. Evidently, this behavior of policy would not have occurred had there been theory, measurements and forecasts to avoid these violent oscillations that are clearly detrimental to economic growth and prosperity without inflation. Current policy consists of forecast mandate of maintaining policy accommodation until the forecast of the rate of unemployment reaches 6.5 percent and the rate of personal consumption expenditures excluding food and energy reaches 2.5 percent (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.htm). It is a forecast mandate because of the lags in effect of monetary policy impulses on income and prices (Romer and Romer 2004). The intention is to reduce unemployment close to the “natural rate” (Friedman 1968, Phelps 1968) of around 5 percent and inflation at or below 2.0 percent. If forecasts were reasonably accurate, there would not be policy errors. A commonly analyzed risk of zero interest rates is the occurrence of unintended inflation that could precipitate an increase in interest rates similar to the Himalayan rise of the fed funds rate from 9.91 percent on Jan 10, 1979, at the beginning in Chart IC-2, to 22.36 percent on Jul 22, 1981. There is a less commonly analyzed risk of the development of a risk premium on Treasury securities because of the unsustainable Treasury deficit/debt of the United States (http://cmpassocregulationblog.blogspot.com/2013/02/united-states-unsustainable-fiscal.html). There is not a fiscal cliff or debt limit issue ahead but rather free fall into a fiscal abyss. The combination of the fiscal abyss with zero interest rates could trigger the risk premium on Treasury debt or Himalayan hike in interest rates.
Chart VI-10, US, Fed Funds Rate, Business Days, Jan 10, 1979 to Mar 14, 2013, Percent per Year
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/h15/update/
There is a false impression of the existence of a monetary policy “science,” measurements and forecasting with which to steer the economy into “prosperity without inflation.” Market participants are remembering the Great Bond Crash of 1994 shown in Table IC-3 when monetary policy pursued nonexistent inflation, causing trillions of dollars of losses in fixed income worldwide while increasing the fed funds rate from 3 percent in Jan 1994 to 6 percent in Dec. The exercise in Table IC-3 shows a drop of the price of the 30-year bond by 18.1 percent and of the 10-year bond by 14.1 percent. CPI inflation remained almost the same and there is no valid counterfactual that inflation would have been higher without monetary policy tightening because of the long lag in effect of monetary policy on inflation (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). The pursuit of nonexistent deflation during the past ten years has resulted in the largest monetary policy accommodation in history that created the 2007 financial market crash and global recession and is currently preventing smoother recovery while creating another financial crash in the future. The issue is not whether there should be a central bank and monetary policy but rather whether policy accommodation in doses from zero interest rates to trillions of dollars in the fed balance sheet endangers economic stability.
Table IC-3, Fed Funds Rates, Thirty and Ten Year Treasury Yields and Prices, 30-Year Mortgage Rates and 12-month CPI Inflation 1994
| 1994 | FF | 30Y | 30P | 10Y | 10P | MOR | CPI |
| Jan | 3.00 | 6.29 | 100 | 5.75 | 100 | 7.06 | 2.52 |
| Feb | 3.25 | 6.49 | 97.37 | 5.97 | 98.36 | 7.15 | 2.51 |
| Mar | 3.50 | 6.91 | 92.19 | 6.48 | 94.69 | 7.68 | 2.51 |
| Apr | 3.75 | 7.27 | 88.10 | 6.97 | 91.32 | 8.32 | 2.36 |
| May | 4.25 | 7.41 | 86.59 | 7.18 | 88.93 | 8.60 | 2.29 |
| Jun | 4.25 | 7.40 | 86.69 | 7.10 | 90.45 | 8.40 | 2.49 |
| Jul | 4.25 | 7.58 | 84.81 | 7.30 | 89.14 | 8.61 | 2.77 |
| Aug | 4.75 | 7.49 | 85.74 | 7.24 | 89.53 | 8.51 | 2.69 |
| Sep | 4.75 | 7.71 | 83.49 | 7.46 | 88.10 | 8.64 | 2.96 |
| Oct | 4.75 | 7.94 | 81.23 | 7.74 | 86.33 | 8.93 | 2.61 |
| Nov | 5.50 | 8.08 | 79.90 | 7.96 | 84.96 | 9.17 | 2.67 |
| Dec | 6.00 | 7.87 | 81.91 | 7.81 | 85.89 | 9.20 | 2.67 |
Notes: FF: fed funds rate; 30Y: yield of 30-year Treasury; 30P: price of 30-year Treasury assuming coupon equal to 6.29 percent and maturity in exactly 30 years; 10Y: yield of 10-year Treasury; 10P: price of 10-year Treasury assuming coupon equal to 5.75 percent and maturity in exactly 10 years; MOR: 30-year mortgage; CPI: percent change of CPI in 12 months
Sources: yields and mortgage rates http://www.federalreserve.gov/releases/h15/data.htm CPI ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.t
The Congressional Budget Office (CBO 2013BEOFeb5) estimates potential GDP, potential labor force and potential labor productivity provided in Table IC-4. The average rate of growth of potential GDP from 1950 to 2012 is estimated at 3.3 percent per year. The projected path is significantly lower at 2.2 percent per year from 2012 to 2023. The legacy of the economic cycle with expansion from IIIQ2009 to IVQ2012 at 2.1 percent on average in contrast with 6.2 percent in prior expansions of the economic cycle in the postwar (http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html) may perpetuate unemployment and underemployment estimated at 30.9 million or 19.2 percent of the effective labor force in Feb 2013 (http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html) with much lower hiring than in the period before the current cycle (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/02/recovery-without-hiring-united-states.html).
Table IC-4, US, Congressional Budget Office History and Projections of Potential GDP of US Overall Economy, ∆%
| Potential GDP | Potential Labor Force | Potential Labor Productivity* | |
| Average Annual ∆% | |||
| 1950-1973 | 3.9 | 1.6 | 2.3 |
| 1974-1981 | 3.3 | 2.5 | 0.8 |
| 1982-1990 | 3.1 | 1.6 | 1.5 |
| 1991-2001 | 3.1 | 1.3 | 1.8 |
| 2002-2012 | 2.2 | 0.8 | 1.4 |
| Total 1950-2012 | 3.3 | 1.5 | 1.7 |
| Projected Average Annual ∆% | |||
| 2013-2018 | 2.2 | 0.6 | 1.6 |
| 2019-2023 | 2.3 | 0.5 | 1.8 |
| 2012-2023 | 2.2 | 0.5 | 1.7 |
*Ratio of potential GDP to potential labor force
Source: Congressional Budget Office, CBO (2013BEOFeb5).
Chart IX-1 of the Congressional Budget Office (CBO 2013BEOFeb5) provides actual and potential GDP of the United States from 2000 to 2011 and projected to 2024. Lucas (2011May) estimates trend of United States real GDP of 3.0 percent from 1870 to 2010 and 2.2 percent for per capita GDP. The United States successfully returned to trend growth of GDP by higher rates of growth during cyclical expansion as analyzed by Bordo (2012Sep27, 2012Oct21) and Bordo and Haubrich (2012DR). Growth in expansions following deeper contractions and financial crises was much higher in agreement with the plucking model of Friedman (1964, 1988). The unusual weakness of growth at 2.1 percent on average from IIIQ2009 to IVQ2012 during the current economic expansion in contrast with 6.2 percent on average in postwar cyclical expansions (http://cmpassocregulationblog.blogspot.com/2013/03/mediocre-gdp-growth-at-16-to-20-percent.html) cannot be explained by the contraction of 4.7 of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 30.9 million or 19.2 percent of the labor as estimated for Jan 2013 (http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html) and the collapse of hiring (Section and earlier http://cmpassocregulationblog.blogspot.com/2013/02/recovery-without-hiring-united-states.html).
Chart IC-2, US, Congressional Budget Office, Actual and Projections of Potential GDP, 2000-2024, Trillions of Dollars
Source: Congressional Budget Office, CBO (2013BEOFeb5).
Chart IC-3 of the Bureau of Economic Analysis of the Department of Commerce shows on the lower negative panel the sharp increase in the deficit in goods and the deficits in goods and services from 1960 to 2012. The upper panel shows the increase in the surplus in services that was insufficient to contain the increase of the deficit in goods and services. The adjustment during the global recession has been in the form of contraction of economic activity that reduced demand for goods.
Chart IC-3, US, Balance of Goods, Balance on Services and Balance on Goods and Services, 1960-2012, Millions of Dollars
Source: Bureau of Economic Analysis http://www.bea.gov/iTable/index_ita.cfm
Chart IC-4 of the Bureau of Economic Analysis shows exports and imports of goods and services from 1960 to 2012. Exports of goods and services in the upper positive panel have been quite dynamic but have not compensated for the sharp increase in imports of goods. The US economy apparently has become less competitive in goods than in services.
Chart IC-4, US, Exports and Imports of Goods and Services, 1960-2012, Millions of Dollars
Source: Bureau of Economic Analysis http://www.bea.gov/iTable/index_ita.cfm
Chart IC-5 of the Bureau of Economic Analysis shows the US balance on current account from 1960 to 2012. The sharp devaluation of the dollar resulting from unconventional monetary policy of zero interest rates and elimination of auctions of 30-year Treasury bonds did not adjust the US balance of payments. Adjustment only occurred after the contraction of economic activity during the global recession.
Chart IC-5, US, Balance on Current Account, 1960-2012, Millions of Dollars
Source: Bureau of Economic Analysis http://www.bea.gov/iTable/index_ita.cfm
Chart IC-5 of the Bureau of Economic Analysis provides real GDP in the US from 1960 to 2012. The contraction of economic activity during the global recession was a major factor in the reduction of the current account deficit as percent of GDP.
Chart IIB-6, US, Real GDP, 1960-2012, Billions of Chained 2005 Dollars
Source: Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Risk aversion channels funds toward US long-term and short-term securities that finance the US balance of payments and fiscal deficits benefitting at the moment from risk flight to US dollar denominated assets. Net foreign purchases of US long-term securities (row C in Table IC-6) decreased from $64.2 billion in Dec 2012 to $25.7 billion in Jan 2013. Foreign (residents) purchases minus sales of US long-term securities (row A in Table IC-6) in Dec 2012 of $76.5 billion decreased to $48.2 billion in Jan 2013. Net US (residents) purchases of long-term foreign securities (row B in Table IC) decreased from minus $12.3 billion in Dec 2012 to minus $22.5 billion in Jan 2013. In Jan 2013,
C = A + B = $48.2 billion - $22.5 billion = $25.7 billion
There are minor rounding errors. There is decreasing demand in Table IC-6 in Jan in A1 private purchases by residents overseas of US long-term securities of $14.8 billion of which decreases in A11 Treasury securities of $20.8 billion, decrease in A12 of $0.9 billion in agency securities, increase by $2.5 billion of corporate bonds and increase of $4.4 billion in equities. Worldwide risk aversion causes flight into US Treasury obligations with significant oscillations. Official purchases of securities in row A2 increased $9.1 billion with increase of Treasury securities of $8.4 billion in Dec. Official purchases of agency securities increased $9.1 billion in Dec and decreased $63.0 billion in Jan. Row D shows increase in Jan in purchases of short-term dollar denominated obligations. Foreign private holdings of US Treasury bills increased $6.0 billion (row D11) with foreign official holdings increasing $4.4 billion while the category “other” increased $1.4 billion. Risk aversion of default losses in foreign securities dominates decisions to accept zero interest rates in Treasury securities with no perception of principal losses. In the case of long-term securities, investors prefer to sacrifice inflation and possible duration risk to avoid principal losses.
Table IC-6, Net Cross-Borders Flows of US Long-Term Securities, Billion Dollars, NSA
| Jan 2012 12 Months | Jan 2013 12 Months | Dec 2012 | Jan 2013 | |
| A Foreign Purchases less Sales of | 515.9 | 573.8 | 76.5 | 48.2 |
| A1 Private | 340.7 | 330.2 | 67.3 | -14.8 |
| A11 Treasury | 311.4 | 130.6 | 21.5 | -20.8 |
| A12 Agency | 65.5 | 132.5 | 18.9 | -0.9 |
| A13 Corporate Bonds | -45.5 | -28.7 | 1.6 | 2.5 |
| A14 Equities | 9.2 | 95.7 | 25.3 | 4.4 |
| A2 Official | 175.2 | 243.6 | 9.1 | 63.0 |
| A21 Treasury | 159.2 | 220.8 | 8.4 | 53.1 |
| A22 Agency | 13.3 | 3.3 | -0.8 | 5.5 |
| A23 Corporate Bonds | -0.7 | 10.9 | 0.9 | 3.1 |
| A24 Equities | 3.4 | 8.6 | 0.6 | 1.3 |
| B Net US Purchases of LT Foreign Securities | -90.1 | -64.7 | -12.3 | -22.5 |
| B1 Foreign Bonds | -32.9 | -9.2 | -7.5 | -2.7 |
| B2 Foreign Equities | -57.2 | -55.5 | -4.8 | -19.8 |
| C Net Foreign Purchases of US LT Securities | 425.8 | 509.1 | 64.2 | 25.7 |
| D Increase in Foreign Holdings of Dollar Denominated Short-term | -118.0 | 115.5 | -5.6 | 11.8 |
| D1 US Treasury Bills | -76.7 | 67.6 | -11.9 | 10.4 |
| D11 Private | 11.8 | 41.0 | -1.2 | 6.0 |
| D12 Official | -88.5 | 26.6 | -10.7 | 4.4 |
| D2 Other | -41.3 | 47.9 | 6.3 | 1.4 |
C = A + B;
A = A1 + A2
A1 = A11 + A12 + A13 + A14
A2 = A21 + A22 + A23 + A24
B = B1 + B2
D = D1 + D2
Sources: http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/ticpress.aspx
Table IC-7 provides major foreign holders of US Treasury securities. China is the largest holder with $1264.5 billion in Jan 2013, increasing 8.4 percent from $1166.2 billion in Jan 2012. Japan increased its holdings from $1080.8 billion in Jan 2012 to $1115.2 billion in Jan 2013 or by 3.2 percent likely in part by intervention to buy dollars against the yen to depreciate the overvalued yen/dollar rate that diminishes the competitiveness of Japan. Total foreign holdings of Treasury securities rose from $5056.8 billion in Jan 2012 to $5616.5 billion in Jan 2013, or 11.1 percent. The US continues to finance its fiscal and balance of payments deficits with foreign savings (see Pelaez and Pelaez, The Global Recession Risk (2007)). A point of saturation of holdings of US Treasury debt may be reached as foreign holders evaluate the threat of reduction of principal by dollar devaluation and reduction of prices by increases in yield, including possibly risk premium. Shultz et al (2012) find that the Fed financed three-quarters of the US deficit in fiscal year 2011, with foreign governments financing significant part of the remainder of the US deficit while the Fed owns one in six dollars of US national debt. Concentrations of debt in few holders are perilous because of sudden exodus in fear of devaluation and yield increases and the limit of refinancing old debt and placing new debt. In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):
“Imagine that fiscal policy dominates monetary policy. The fiscal authority independently sets its budgets, announcing all current and future deficits and surpluses and thus determining the amount of revenue that must be raised through bond sales and seignorage. Under this second coordination scheme, the monetary authority faces the constraints imposed by the demand for government bonds, for it must try to finance with seignorage any discrepancy between the revenue demanded by the fiscal authority and the amount of bonds that can be sold to the public. Suppose that the demand for government bonds implies an interest rate on bonds greater than the economy’s rate of growth. Then if the fiscal authority runs deficits, the monetary authority is unable to control either the growth rate of the monetary base or inflation forever. If the principal and interest due on these additional bonds are raised by selling still more bonds, so as to continue to hold down the growth of base money, then, because the interest rate on bonds is greater than the economy’s growth rate, the real stock of bonds will growth faster than the size of the economy. This cannot go on forever, since the demand for bonds places an upper limit on the stock of bonds relative to the size of the economy. Once that limit is reached, the principal and interest due on the bonds already sold to fight inflation must be financed, at least in part, by seignorage, requiring the creation of additional base money.”
Table IC-7, US, Major Foreign Holders of Treasury Securities $ Billions at End of Period
| Jan 2013 | Dec 2012 | Jan 2012 | |
| Total | 5616.5 | 5573.8 | 5056.8 |
| China | 1264.5 | 1220.4 | 1166.2 |
| Japan | 1115.2 | 1111.2 | 1080.8 |
| Oil Exporters | 262.0 | 262.0 | 268.5 |
| Brazil | 253.4 | 253.3 | 228.2 |
| Caribbean Banking Centers | 236.9 | 266.2 | 223.8 |
| Taiwan | 196.6 | 195.4 | 178.5 |
| Switzerland | 192.7 | 195.4 | 145.8 |
| Russia | 162.9 | 161.5 | 145.7 |
| Luxembourg | 144.7 | 155.0 | 136.6 |
| Belgium | 143.5 | 138.8 | 131.5 |
| Hong Kong | 142.9 | 141.9 | 134.2 |
| United Kingdom | 135.7 | 132.6 | 115.7 |
| Foreign Official Holdings | 4089.7 | 4032.2 | 3688.3 |
| A. Treasury Bills | 377.1 | 372.7 | 350.4 |
| B. Treasury Bonds and Notes | 3712.6 | 3659.5 | 3337.8 |
Source: http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/ticsec2.aspx#ussecs
© Carlos M. Pelaez, 2010, 2011, 2012, 2013
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