Recovery without Hiring, Ten Million Fewer Full-Time Jobs, Youth Unemployment, Bank Risk Management, World Financial Turbulence and Global Economic Slowdown
Carlos M. Pelaez
© Carlos M. Pelaez, 2010, 2011, 2012
Executive Summary
I Recovery without Hiring
IA Hiring Collapse
IB Labor Underutilization
IC Ten Million Fewer Full-Time Jobs
ID Youth Unemployment
II United States International Trade
IIA United States International Trade Balance
IIB United States Import and Export Prices
III World Financial Turbulence
IIIA Financial Risks
IIIB Appendix on Safe Haven Currencies
IIIC Appendix on Fiscal Compact
IIID Appendix on European Central Bank Large Scale Lender of Last Resort
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
Appendix I The Great Inflation
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 forthcoming in the American Economic Review 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/2012/05/recovery-without-jobs-twenty-eight.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.
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.
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 69.4 million in 2004 to 50.1 million in 2011 or by 19.3 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 46.9 million in 2011 or by 12.6 million, as shown in Table ESI-1. The ratio of nonfarm hiring to unemployment (RNF) has fallen from 47.2 in 2005 to 38.1 in 2011 and in the private sector (RHP) from 52.1 in 2006 to 42.9 in 2011. The collapse of hiring in the US has not been followed by dynamic labor markets because of the low rate of economic growth of 2.4 percent in the first eleven quarters of expansion from IIIQ2009 to IVQ2011 compared with 6.2 percent in prior cyclical expansions (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.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 | 69,367 | 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 | 55,166 | 40.3 | 51,606 | 45.2 |
| 2009 | 46,398 | 35.5 | 43,052 | 39.8 |
| 2010 | 48,647 | 37.5 | 44,826 | 41.7 |
| 2011 | 50,083 | 38.1 | 46,869 | 42.9 |
Source: http://www.bls.gov/jlt/data.htm
Chart ESI-1 provides the yearly levels of total nonfarm hiring (NFH) in Table ESI-1. The fall of hiring during the contraction of 2007 to 2009 was much stronger than in the shallow contraction of 2001 with GDP contraction of only 0.4 percent from Mar 2001 (IQ2001) to Dec 2001 (IVQ 2001) compared with 5.1 percent contraction in the much longer recession from Dec 2007 (IVQ2007) to Jun 2009 (IIQ2009) (http://www.nber.org/cycles/cyclesmain.html). Recovery is tepid.
Chart ESI-1, US, Rate Total Nonfarm Hiring (HNF), Yearly, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Chart ESI-2 shows the ratio or rate of nonfarm hiring to unemployment (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), Yearly, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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, 11.6 in 2008 and 15.9 percent in 2009. On a yearly basis, nonfarm hiring grew 4.8 percent in 2010 relative to 2009 and 3.0 percent in 2011.
Table ESI-2, US, Annual Total Nonfarm Hiring (HNF), Yearly Percentage Change, 2001-2011
| Year | Annual |
| 2002 | -6.9 |
| 2003 | -3.6 |
| 2004 | 6.9 |
| 2005 | 4.6 |
| 2006 | 1.0 |
| 2007 | -2.1 |
| 2008 | -11.6 |
| 2009 | -15.9 |
| 2010 | 4.8 |
| 2011 | 3.0 |
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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), Yearly Percentage Change, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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 in 2011 than in 2010.
Chart ESI-4, US, Total Private Hiring, Yearly, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Chart ESI-5 plots the rate of total private hiring relative to unemployment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.
Chart ESI-5, US, Rate Total Private Hiring, Yearly, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Mar in the years from 2001 to 2012 in Table ESI-3. Hiring numbers are in thousands. There is some recovery in HNF from 3557 thousand (or 3.6 million) in Mar 2009 to 4036 thousand in Mar 2011 and 4117 thousand in Mar 2012 for cumulative gain of 15.7 percent. HP rose from 3384 thousand in Mar 2009 to 3860 thousand in Mar 2011 and 3900 thousand in Mar 2012 for cumulative gain of 15.2 percent. HNF has fallen from 5013 in Mar 2005 to 4117 in Mar 2012 or by 18.2 percent. HP has fallen from 4773 in Mar 2006 to 3900 in Mar 2012 or by 18.3 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 Mar | 5235 | 4.0 | 4993 | 4.5 |
| 2002 Mar | 4312 | 3.3 | 4097 | 3.8 |
| 2003 Mar | 4099 | 3.2 | 3900 | 3.6 |
| 2004 Mar | 4826 | 3.7 | 4592 | 4.3 |
| 2005 Mar | 4894 | 3.7 | 4677 | 4.3 |
| 2006 Mar | 5036 | 3.7 | 4773 | 4.2 |
| 2007 Mar | 5013 | 3.7 | 4749 | 4.2 |
| 2008 Mar | 4480 | 3.3 | 4256 | 3.7 |
| 2009 Mar | 3557 | 2.7 | 3384 | 3.1 |
| 2010 Mar | 3964 | 3.1 | 3703 | 3.5 |
| 2011 Mar | 4036 | 3.1 | 3860 | 3.6 |
| 2012 Mar | 4117 | 3.1 | 3900 | 3.6 |
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Chart ESI-6 provides total nonfarm hiring on a monthly basis from 2001 to 2012. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) in 2010 of 4786 in May. Nonfarm hiring fell again in Dec 2011 to 3038 from 3844 in Nov and to revised 3633 in Feb 2012, increasing to 4117 in Mar 2012. Chart ESI-6 provides seasonally-adjusted (SA) monthly data. The number of seasonally-adjusted hires in Aug 2011 was 4221 thousand, increasing to revised 4444 thousand in Feb 2012, or 5.3 percent, but falling to 4356 thousand in Mar 2012, or cumulative gain of 3.2 percent in Sep 2011. The number of hires not seasonally adjusted was 4655 in Aug 2011, falling to 3038 in Dec but increasing to 4072 in Jan 2012, falling again to 3580 in Feb 2012 and increasing to 4117 in Mar 2012. The number of nonfarm hiring not seasonally adjusted fell by 34.7 percent from 4655 in Aug to 3038 in Dec in a yearly-repeated seasonal pattern.
Chart ESI-6, US, Total Nonfarm Hiring (HNF), 2001-2012 Month SA
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Similar behavior occurs in the rate of nonfarm hiring plot in Chart ESI-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 Sep 2011 to 3.2 in Jan 2012 and 3.3 in both Feb and Mar 2012. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.3 in Dec, climbing to 3.1 in Jan 2012 but falling to revised 2.8 in Feb 2012 and increasing to 3.1 in Mar 2012. Rates of nonfarm hiring NSA were in the range of 2.8 (Dec) to 4.5 (Jun) in 2006.
Chart ESI-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
There is only milder improvement in total private hiring shown in Chart ESI-8. Hiring private (HP) rose in 2010 followed by stability and renewed increase in 2011. The number of private hiring seasonally adjusted fell from 4002 thousand in Sep 2011 to 3889 in Dec or by 2.8 percent, increasing to 3945 in Jan 2012 or decline by 1.4 relative to the level in Sep 2011 but moving to revised 4128 in Feb 2012 for increase of 3.1 percent relative to Sep 2011 and 4049 in Mar 2012 for increase of 1.2 percent relative to 4002 in Sep 2011. The number of private hiring not seasonally adjusted fell from 4130 in Sep 2011 to 2856 in Dec or by 30.8 percent, reaching 3782 in Jan 2012 or decline of 8.4 percent relative to Sep 2011 and 3900 in Mar 2012 or decline of 5.6 percent relative to Sep 2011. 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 4934 in Sep 2006 to 3635 in Dec 2006 or by 26.3 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 4293 in Jul 2011 or by 22.7 percent. The conclusion is that private hiring in the US is more than 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 2.4 percent in the eleven quarters of expansion of the economy since IIIQ2009 compared with average 6.2 percent in prior expansions from contractions (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Chart ESI-8, US, Total Private Hiring Month SA 2011-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Chart ESI-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data has not risen significantly above the peak in 2010. The rate seasonally adjusted fell from 3.6 in Sep 2011 to 3.5 in Dec 2011, increasing to 3.6 in Jan 2012 and 3.7 in both Feb and Mar 2012. The rate not seasonally adjusted (NSA) fell from 3.8 in Sep to 2.6 in Dec, increasing to revused 3.5 in Jan 2012 but falling to 3.1 in Feb 2012 and then increasing to 3.6 in Mar 2012. The NSA rate of private hiring fell from 4.9 in Jun 2006 to 3.6 in Jun 2009 but recovery was insufficient to only 4.1 in Jun 2011.
Chart ESI-9, US, Rate Total Private Hiring Month SA 2011-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
ESII Ten Million Fewer Full-Time Jobs. There is strong seasonality in US labor markets around the end of the year. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.270 million in Sep 2011 to 7.853 million in Apr 2012, seasonally adjusted, or decline of 1.417 million in just six months, as shown in Table ESII-1. The number employed full-time increased from 112.479 million in Sep 2011 to 115.290 million in Mar 2012 or 2.811 million but then fell to 111.478 million in Apr 2012 or 1.001 million fewer full-time employed than in Sep 2011. 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 than in Jan 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 113.916 in Mar 2012 or increase by 778,000 compared with the level in Nov 2011 and further increased to 113.999 in Apr 2012 or 861,000 more than in Nov 2011. 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 108.770 million in Jan 2010 or by 14.449 million. The number with full-time jobs in Apr 2012 is 113.999 million, which is lower by 9.2 million relative to the peak of 123.219 million in Jul 2007. There appear to be around 10 million less full-time jobs in the US than before the global recession. Growth at 2.4 percent on average in the eleven quarters of expansion since IIIQ2009 compared with 6.2 percent on average in expansions from postwar cyclical contractions is the main culprit of the fractured US labor market (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/05/recovery-without-jobs-twenty-eight.html).
Table ESII-1, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions
| Part-time Thousands | Full-time Millions | |
| Seasonally Adjusted | ||
| Apr 2012 | 7,853 | 111.478 |
| Mar 2012 | 7,672 | 115.290 |
| Feb 2012 | 8,119 | 114.408 |
| Jan 2012 | 8,230 | 113.845 |
| Dec 2011 | 8,098 | 113.765 |
| Nov 2011 | 8,469 | 113.212 |
| Oct 2011 | 8,790 | 112.841 |
| Sep 2011 | 9,270 | 112.479 |
| Aug 2011 | 8,787 | 112.406 |
| Not Seasonally Adjusted | ||
| 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 |
| 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 |
| 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 |
| Apr 2009 | 8,648 | 112.746 |
| Mar 2009 | 9,305 | 112.215 |
| Feb 2009 | 9,170 | 112.947 |
| Jan 2009 | 8,829 | 113.815 |
| Apr 2008 | 5,071 | 120.027 |
| Mar 2008 | 5,038 | 119.875 |
| Feb 2008 | 5,114 | 119.452 |
| Jan 2008 | 5,340 | 119.322 |
| Jul 2007 | 4,516 | 123.219 (high) |
| Apr 2007 | 4,205 | 119.609 |
| Mar 2007 | 4,384 | 119.640 |
| Feb 2007 | 4,417 | 119.041 |
| Jan 2007 | 4,726 | 119.094 |
| Sep 2006 | 3,735 (low) | 120.780 |
| 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/cps/data.htm
People lose their marketable job skills after prolonged unemployment and find increasing difficulty in finding another job. Chart ESII-1 shows the sharp rise in unemployed over 27 weeks and stabilization at an extremely high level.
Chart ESII-1, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2011
Sources: http://www.bls.gov/cps/data.htm
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 ESII-2 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.
Chart ESII-2, US, Marginally Attached to the Labor Force, NSA Month 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Chart ESII-3 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 2012 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-3, US, Full-time Employed, Thousands, NSA, 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
ESIII Youth Unemployment. The United States is experiencing high youth unemployment as in European economies. Table ESIII-1 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. 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. 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 ESIII-1, US, Employment Level 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Apr | Annual |
| 2001 | 19678 | 19745 | 19800 | 19778 | 20088 |
| 2002 | 18653 | 19074 | 19091 | 19108 | 19683 |
| 2003 | 18811 | 18880 | 18709 | 18873 | 19351 |
| 2004 | 18852 | 18841 | 18752 | 19184 | 19630 |
| 2005 | 18858 | 18670 | 18989 | 19071 | 19770 |
| 2006 | 19003 | 19182 | 19291 | 19406 | 20041 |
| 2007 | 19407 | 19415 | 19538 | 19368 | 19875 |
| 2008 | 18724 | 18546 | 18745 | 19161 | 19202 |
| 2009 | 17467 | 17606 | 17564 | 17739 | 17601 |
| 2010 | 16166 | 16412 | 16587 | 16764 | 17077 |
| 2011 | 16512 | 16638 | 16898 | 16970 | 17362 |
| 2012 | 16944 | 17150 | 17301 | 17387 |
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Chart ESIII-1 provides US employment level ages 16 to 24 years from 2002 to 2012. Employment level is sharply lower in Apr 2012 relative to the peak in 2007.
Chart ESIII-1, US, Employment Level 16-24 Years, Thousands SA, 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Table ESIII-2 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. This situation may persist for many years.
Table ESIII-2, US, Unemployment Level 16-24 Years, Thousands NSA
| Year | Jan | Feb | Mar | Apr | Annual |
| 2001 | 2250 | 2258 | 2253 | 2095 | 2371 |
| 2002 | 2754 | 2731 | 2822 | 2515 | 2683 |
| 2003 | 2748 | 2740 | 2601 | 2572 | 2746 |
| 2004 | 2767 | 2631 | 2588 | 2387 | 2638 |
| 2005 | 2661 | 2787 | 2520 | 2398 | 2521 |
| 2006 | 2366 | 2433 | 2216 | 2092 | 2353 |
| 2007 | 2363 | 2230 | 2096 | 2074 | 2342 |
| 2008 | 2633 | 2480 | 2347 | 2196 | 2830 |
| 2009 | 3278 | 3457 | 3371 | 3321 | 3760 |
| 2010 | 3983 | 3888 | 3748 | 3803 | 3857 |
| 2011 | 3851 | 3696 | 3520 | 3365 | 3634 |
| 2012 | 3416 | 3507 | 3294 | 3175 |
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Chart ESIII-2 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.
Chart ESIII-2, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Table ESIII-3 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 and 17.3 percent in 2011. During the seasonal peak in Jun 2011 the rate of youth unemployed was 18.1 percent compared with 10.8 percent in Jun 2007.
Table ESIII-3, US, Unemployment Rate 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Apr | Annual |
| 2001 | 10.3 | 10.3 | 10.2 | 9.6 | 10.6 |
| 2002 | 12.9 | 12.5 | 12.9 | 11.6 | 12.0 |
| 2003 | 12.7 | 12.7 | 12.2 | 12.0 | 12.4 |
| 2004 | 12.8 | 12.3 | 12.1 | 11.1 | 11.8 |
| 2005 | 12.4 | 13.0 | 11.7 | 11.2 | 11.3 |
| 2006 | 11.1 | 11.3 | 10.3 | 9.7 | 10.5 |
| 2007 | 10.9 | 10.3 | 9.7 | 9.7 | 10.5 |
| 2008 | 12.3 | 11.8 | 11.1 | 10.3 | 12.8 |
| 2009 | 15.8 | 16.4 | 16.1 | 15.8 | 17.6 |
| 2010 | 19.8 | 19.2 | 18.4 | 18.5 | 18.4 |
| 2011 | 18.9 | 18.2 | 17.2 | 16.5 | 17.3 |
| 2012 | 16.8 | 17.0 | 16.0 | 15.4 |
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Chart ESIII-3 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 23 years from 2002 to 2012. 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 eleven quarters of expansion of the economy since IIIQ2009.
Chart ESIII-3, US, Unemployment Rate 16-24 Years, Thousands, NSA, 2002-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Chart ESIII-4 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2012. 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 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: 19.9 percent in Jun 2009, 20.0 percent in Jun 2010 and 18.9 percent in Jun 2011. 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 2.4 percent on average during the first eleven quarters of expansion from IIIQ2009 to IQ2012 (see Table I-5 at http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html). The fractured US labor market denies an early start for young people.
Chart ESIII-4, US, Unemployment Rate 16-24 Years, Percent NSA, 1979-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
ESIV United States Trade. US exports and imports of goods not seasonally adjusted in Jan-Feb 2012 and Jan-Feb 2011 are shown in Table ESIV-1. The rate of growth of both exports and imports was 8.6 percent. The US has partial hedge of commodity price increases in exports of agricultural commodities that fell 6.8 percent and of mineral fuels that increased 18.0 percent both because of higher prices of raw materials and commodities. The US exports an insignificant amount of crude oil. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports rose 10.1 percent while imports rose 9.0 percent. Significant part of the US trade imbalance originates in imports of mineral fuels growing by 6.4 percent and crude oil increasing 8.5 percent. The limited hedge in exports of agricultural commodities and mineral fuels compared with substantial imports of mineral fuels and crude oil results in deterioration of the terms of trade of the US, or export prices relative to import prices, originating in commodity price increases caused by carry trades from zero interest rates.
Table ESIV-1, US, Exports and Imports of Goods, Not Seasonally Adjusted Millions of Dollars and %
| Jan-Mar 2012 $ Millions | Jan-Mar 2011 $ Millions | ∆% | |
| Exports | 381,471 | 351,109 | 8.6 |
| Manufactured | 252,462 | 229,316 | 10.1 |
| Agricultural | 35,005 | 37,558 | -6.8 |
| Mineral Fuels | 32,282 | 27,360 | 18.0 |
| Crude Oil | 429 | 301 | 42.5 |
| Imports | 552,432 | 508,850 | 8.6 |
| Manufactured | 406,027 | 372,479 | 9.0 |
| Agricultural | 26,787 | 24,173 | 10.8 |
| Mineral Fuels | 109,477 | 102,910 | 6.4 |
| Crude Oil | 81,618 | 75,191 | 8.5 |
Source: http://www.census.gov/foreign-trade/Press-Release/current_press_release/ft900.pdf
ESV JP Morgan Chase Risk Management. In its Form 10-Q Quarterly Report for IQ2012 filed with the Securities and Exchange Commission (SEC), JP Morgan Chase states (page 9, http://investor.shareholder.com/jpmorganchase/secfiling.cfm?filingID=19617-12-213):
“Since March 31, 2012, CIO has had significant mark-to market losses in its synthetic credit portfolio, and this portfolio has proven to be riskier, more volatile and less effective as an economic hedge than the Firm previously believed. The losses in CIO's synthetic credit portfolio have been partially offset by realized gains from sales, predominantly of credit-related positions, in CIO's AFS securities portfolio. As of March 31, 2012, the value of CIO's total AFS securities portfolio exceeded its cost by approximately $8 billion. Since then, this portfolio (inclusive of the realized gains in the second quarter to date) has appreciated in value.”
Dan Fitzpatrick, Robin Sidel and David Enrich, writing on “Bank order led to losing trades,” on May 12, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702304070304577398490966089810.html?mod=WSJPRO_hpp_LEFTTopStories), refer to a “person close to the bank” that the trading losses could have reached $2.3 billion in 15 days at the end of Apr and beginning of May for $153 million in daily average. Dan Fitzpatrick, Robin Sidel and David Enrich, writing on “Bank order led to losing trades,” on May 12, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702304070304577398490966089810.html?mod=WSJPRO_hpp_LEFTTopStories), inform on the basis of sources that the trading losses originated in an order to reduce credit exposures at the bank that could be sensitive to the European sovereign debt crisis. The mark-to-market losses originated in selling protection through the Markit CDX North American Investment Grade with 125 reference names (http://www.markit.com/assets/en/docs/products/data/indices/credit-index-annexes/IG%209%20v4.pdf http://www.markit.com/en/products/data/indices/credit-and-loan-indices/cdx/cdx.page). There are no details on the specific trade and what was being hedged. The Markit CDX family of indices is designed to provide vehicles to trade credit default swaps (CDS) worldwide (http://www.markit.com/en/products/data/indices/credit-and-loan-indices/cdx/cdx.page). The CDS buyer obtains credit protection against a credit event by paying a periodic fee to a seller in order to receive payment in case of default by a referenced credit (see Pelaez and Pelaez, International Financial Architecture (2005), 134-54). Types of credit events include bankruptcy, merger, cross acceleration, cross default, downgrade, failure to pay, repudiation, restructuring and currency inconvertibility. Credit events in the Markit CDS indices are bankruptcy and failure to pay, which are settled in credit event auctions (http://www.markit.com/en/products/data/indices/credit-and-loan-indices/cdx/cdx.page). There is insufficient information to analyze the trading exposures of the bank. The Value at Risk (VaR) (see Pelaez and Pelaez, International Financial Architecture (2005), 106-12, 289-92) of the Chief Investment Office (CIO) is estimated at $186 million on Mar 31, 2012. According to form 10-Q (http://investor.shareholder.com/jpmorganchase/secfiling.cfm?filingID=19617-12-213, page 73):
“VaR is calculated using a one day time horizon and an expected tail-loss methodology, and approximates a 95% confidence level. This means that, assuming current changes in market values are consistent with the historical changes used in the simulation, the Firm would expect to incur losses greater than that predicted by VaR estimates five times in every 100 trading days, or about 12 to 13 times a year.”
The CIO at JPMorgan Chase engages in risk management (http://investor.shareholder.com/jpmorganchase/secfiling.cfm?filingID=19617-12-213 74):
“Other VaR includes certain positions employed as part of the Firm’s risk management function within the Chief Investment Office (“CIO”) and in the Mortgage Production and Servicing business. CIO VaR includes positions, primarily in debt securities and credit products, used to manage structural and other risks including interest rate, credit and mortgage risks arising from the Firm’s ongoing business activities. Mortgage Production and Servicing VaR includes the Firm’s mortgage pipeline and warehouse loans, MSRs and all related hedges. CIO VaR averaged $129 million for the three months ended March 31, 2012, compared with $60 million for the comparable 2011 period. The increase in CIO average VaR was due to changes in the synthetic credit portfolio held by CIO as part of its management of structural and other risks arising from the Firm's on-going business activities.”
The Basel Committee on Banking Supervision (2011Jun, 42) Basel III capital adequacy framework provides for the use of index CDS as hedges, under specified conditions, for mitigation of counterparty credit risk (CCR). The risk management tool to be used for capital charges is the credit VaR.
JP Morgan Chase should maintain its traditional excellence in risk management. There are no evident risks to financial markets and the overall economy from the hedging losses of JP Morgan Chase. Parallels with this hedging loss and the causes of the dollar/credit crisis and global recession are misleading. The origins of the financial crisis and global recession are quite different. 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.”
ESVI 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 provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/pubs/ft/weo/2012/update/01/index.htm), of the world financial system with its Global Financial Stability Report (GFSR) (http://www.imf.org/external/pubs/ft/fmu/eng/2012/01/index.htm) and of fiscal affairs with the Fiscal Monitor (http://www.imf.org/external/pubs/ft/fm/2012/update/01/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. The growth rate of GDP of China in the first quarter of 2012 of 1.8 percent is equivalent to 7.4 percent per year
2. United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 30.5 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 (see Section I Inflation Waves at http://cmpassocregulationblog.blogspot.com/2012/03/global-financial-and-economic-risk.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
It is in this context of economic and financial uncertainties that decisions on portfolio choices of risk financial assets must be made. There is a new carry trade that learned from the losses after the crisis of 2007 or learned from the crisis how to avoid losses. The sharp rise in valuations of risk financial assets shown in Table VI-1 in the text after the first policy round of near zero fed funds and quantitative easing by the equivalent of withdrawing supply with the suspension of the 30-year Treasury auction was on a smooth trend with relatively subdued fluctuations. The credit crisis and global recession have been followed by significant fluctuations originating in sovereign risk issues in Europe, doubts of continuing high growth and accelerating inflation in China now complicated by political developments, events such as in the Middle East and Japan and legislative restructuring, regulation, insufficient growth, falling real wages, depressed hiring and high job stress of unemployment and underemployment in the US now with realization of growth standstill. The “trend is your friend” motto of traders has been replaced with a “hit and realize profit” approach of managing positions to realize profits without sitting on positions. There is a trend of valuation of risk financial assets driven by the carry trade from zero interest rates with fluctuations provoked by events of risk aversion or the “sharp shifts in risk appetite” of Blanchard (2012WEOApr, XIII). Table ESVI-1, which is updated for every comment of this blog, shows the deep contraction of valuations of risk financial assets after the Apr 2010 sovereign risk issues in the fourth column “∆% to Trough.” There was sharp recovery after around Jul 2010 in the last column “∆% Trough to 5/11/12,” which has been recently stalling or reversing amidst profound risk aversion. “Let’s twist again” monetary policy during the week of Sep 23 caused deep worldwide risk aversion and selloff of risk financial assets (http://cmpassocregulationblog.blogspot.com/2011/09/imf-view-of-world-economy-and-finance.html http://cmpassocregulationblog.blogspot.com/2011/09/collapse-of-household-income-and-wealth.html). Monetary policy was designed to increase risk appetite but instead suffocated risk exposures. There has been rollercoaster fluctuation in risk aversion and financial risk asset valuations: surge in the week of Dec 2, mixed performance of markets in the week of Dec 9, renewed risk aversion in the week of Dec 16, end-of-the-year relaxed risk aversion in thin markets in the weeks of Dec 23 and Dec 30, mixed sentiment in the weeks of Jan 6 and Jan 13 2012 and strength in the weeks of Jan 20, Jan 27 and Feb 3 followed by weakness in the week of Feb 10 but strength in the weeks of Feb 17 and 24 followed by uncertainty on financial counterparty risk in the weeks of Mar 2 and Mar 9. All financial values have fluctuated with events such as the surge in the week of Mar 16 on favorable news of Greece’s bailout even with new risk issues arising in the week of Mar 23 but renewed risk appetite in the week of Mar 30 because of the end of the quarter and the increase in the firewall of support of sovereign debts in the euro area. New risks developed in the week of Apr 6 with increase of yields of sovereign bonds of Spain and Italy, doubts on Fed policy and weak employment report. Asia and financial entities are experiencing their own risk environments. Financial markets were under stress in the week of Apr 13 because of the large exposure of Spanish banks to lending by the European Central Bank and the annual equivalent growth rate of China’s GDP of 7.4 percent in IQ2012. There was strength again in the week of Apr 20 because of the enhanced IMF firewall and Spain placement of debt, continuing into the week of Apr 27. Risk aversion returned in the week of May 4 because of the expectation of elections in Europe and the new trend of deterioration of job creation in the US. Europe’s sovereign debt crisis and the fractured US job market continued to influence risk aversion in the week of May 11. The highest valuations in column “∆% Trough to 5/11/12” are by US equities indexes: DJIA 32.4 percent and S&P 500 also 32.4 percent, driven by stronger earnings and economy in the US than in other advanced economies but with doubts on the relation of business revenue to the weakening economy and fractured job market. The DJIA reached in intraday trading 13,331.77 on Mar 16, which is the highest level in 52 weeks (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata). 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 5/11/12” had double digit gains relative to the trough around Jul 2, 2010 but now most valuations of equity indexes show increase of less than 10 percent: China’s Shanghai Composite is 0.5 percent above the trough; STOXX 50 of Europe is 1.8 percent below the trough; Japan’s Nikkei Average is 1.5 percent above the trough; Dow Asia Pacific is 5.9 percent above the trough; Dow Global is 8.9 percent above the trough; and NYSE Financial is 5.7 percent above the trough. DJ UBS Commodities is 8.7 percent above the trough. DAX is 16.0 percent above the trough. Japan’s Nikkei Average is 1.5 percent above the trough on Aug 31, 2010 and 21.4 percent below the peak on Apr 5, 2010. The Nikkei Average closed at 8953.31 on Fri May 11, 2012 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 12.7 percent lower than 10,254.43 on Mar 11, 2011, on the date of the Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar depreciated by 8.4 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 5/11/12” in Table ESVI-1 shows that with exception of increase of 0.3 percent of Germany’s Dax there were decreases of all valuations of risk financial assets in the week of May 4, 2012 such as 1.7 percent for DJIA, 1.1 percent for S&P 500, 1.6 percent for NYSE Financial, 2.1 percent for Dow Global, 4.3 percent for DJ Asia Pacific, 2.3 percent for Shanghai Composite, 4.9 percent for STOXX 50 and 1.7 percent for DJ UBS Commodities. There are still high uncertainties on European sovereign risks, 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 ESVI-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 5/11/12” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to May 4, 2012. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 5/11/12” but also relative to the peak in column “∆% Peak to 5/11/12.” There are now only three equity indexes above the peak in Table ESVI-1: DJIA 14.4 percent, S&P 500 11.2 percent and Dax 3.9 percent. There are several indexes below the peak: NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) by 15.8 percent, Nikkei Average by 21.4 percent, Shanghai Composite by 24.3 percent, Dow Asia Pacific by 7.3 percent, STOXX 50 by 16.9 percent and Dow Global by 11.2 percent. DJ UBS Commodities Index is now 7.1 percent below 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. 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 ESVI-1, Stock Indexes, Commodities, Dollar and 10-Year Treasury
| Peak | Trough | ∆% to Trough | ∆% Peak to 5/11 /12 | ∆% Week 5/11/ 12 | ∆% Trough to 5/11 12 | |
| DJIA | 4/26/ | 7/2/10 | -13.6 | 14.4 | -1.7 | 32.4 |
| S&P 500 | 4/23/ | 7/20/ | -16.0 | 11.2 | -1.1 | 32.4 |
| NYSE Finance | 4/15/ | 7/2/10 | -20.3 | -15.8 | -1.6 | 5.7 |
| Dow Global | 4/15/ | 7/2/10 | -18.4 | -11.2 | -2.1 | 8.9 |
| Asia Pacific | 4/15/ | 7/2/10 | -12.5 | -7.3 | -4.3 | 5.9 |
| Japan Nikkei Aver. | 4/05/ | 8/31/ | -22.5 | -21.4 | -4.6 | 1.5 |
| China Shang. | 4/15/ | 7/02 | -24.7 | -24.3 | -2.3 | 0.5 |
| STOXX 50 | 4/15/10 | 7/2/10 | -15.3 | -16.9 | -4.9 | -1.8 |
| DAX | 4/26/ | 5/25/ | -10.5 | 3.9 | 0.3 | 16.0 |
| Dollar | 11/25 2009 | 6/7 | 21.2 | 14.6 | 1.3 | 8.4 |
| DJ UBS Comm. | 1/6/ | 7/2/10 | -14.5 | -7.1 | -1.7 | 8.7 |
| 10-Year T Note | 4/5/ | 4/6/10 | 3.986 | 1.845 |
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 forthcoming in the American Economic Review 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/2012/05/recovery-without-jobs-twenty-eight.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. There are four subsections. IA Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IB 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 IC Ten Million Fewer Full-time Jobs. ID Youth Unemployment provides the data on high unemployment of ages 16 to 24 years.
IA 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 69.4 million in 2004 to 50.1 million in 2011 or by 19.3 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 46.9 million in 2011 or by 12.6 million, as shown in Table I-1. The ratio of nonfarm hiring to unemployment (RNF) has fallen from 47.2 in 2005 to 38.1 in 2011 and in the private sector (RHP) from 52.1 in 2006 to 42.9 in 2011. The collapse of hiring in the US has not been followed by dynamic labor markets because of the low rate of economic growth of 2.4 percent in the first eleven quarters of expansion from IIIQ2009 to IVQ2011 compared with 6.2 percent in prior cyclical expansions (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.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 | 69,367 | 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 | 55,166 | 40.3 | 51,606 | 45.2 |
| 2009 | 46,398 | 35.5 | 43,052 | 39.8 |
| 2010 | 48,647 | 37.5 | 44,826 | 41.7 |
| 2011 | 50,083 | 38.1 | 46,869 | 42.9 |
Source: http://www.bls.gov/jlt/data.htm
Chart I-1 provides the yearly levels of total nonfarm hiring (NFH) in Table I-1. The fall of hiring during the contraction of 2007 to 2009 was much stronger than in the shallow contraction of 2001 with GDP contraction of only 0.4 percent from Mar 2001 (IQ2001) to Dec 2001 (IVQ 2001) compared with 5.1 percent contraction in the much longer recession from Dec 2007 (IVQ2007) to Jun 2009 (IIQ2009) (http://www.nber.org/cycles/cyclesmain.html). Recovery is tepid.
Chart I-1, US, Rate Total Nonfarm Hiring (HNF), Yearly, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Chart I-2 shows the ratio or rate of nonfarm hiring to unemployment (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), Yearly, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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, 11.6 in 2008 and 15.9 percent in 2009. On a yearly basis, nonfarm hiring grew 4.8 percent in 2010 relative to 2009 and 3.0 percent in 2011.
Table I-2, US, Annual Total Nonfarm Hiring (HNF), Yearly Percentage Change, 2001-2011
| Year | Annual |
| 2002 | -6.9 |
| 2003 | -3.6 |
| 2004 | 6.9 |
| 2005 | 4.6 |
| 2006 | 1.0 |
| 2007 | -2.1 |
| 2008 | -11.6 |
| 2009 | -15.9 |
| 2010 | 4.8 |
| 2011 | 3.0 |
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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), Yearly Percentage Change, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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 in 2011 than in 2010.
Chart I-4, US, Total Private Hiring, Yearly, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Chart I-5 plots the rate of total private hiring relative to unemployment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.
Chart I-5, US, Rate Total Private Hiring, Yearly, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Mar in the years from 2001 to 2012 in Table I-3. Hiring numbers are in thousands. There is some recovery in HNF from 3557 thousand (or 3.6 million) in Mar 2009 to 4036 thousand in Mar 2011 and 4117 thousand in Mar 2012 for cumulative gain of 15.7 percent. HP rose from 3384 thousand in Mar 2009 to 3860 thousand in Mar 2011 and 3900 thousand in Mar 2012 for cumulative gain of 15.2 percent. HNF has fallen from 5013 in Mar 2005 to 4117 in Mar 2012 or by 18.2 percent. HP has fallen from 4773 in Mar 2006 to 3900 in Mar 2012 or by 18.3 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 Mar | 5235 | 4.0 | 4993 | 4.5 |
| 2002 Mar | 4312 | 3.3 | 4097 | 3.8 |
| 2003 Mar | 4099 | 3.2 | 3900 | 3.6 |
| 2004 Mar | 4826 | 3.7 | 4592 | 4.3 |
| 2005 Mar | 4894 | 3.7 | 4677 | 4.3 |
| 2006 Mar | 5036 | 3.7 | 4773 | 4.2 |
| 2007 Mar | 5013 | 3.7 | 4749 | 4.2 |
| 2008 Mar | 4480 | 3.3 | 4256 | 3.7 |
| 2009 Mar | 3557 | 2.7 | 3384 | 3.1 |
| 2010 Mar | 3964 | 3.1 | 3703 | 3.5 |
| 2011 Mar | 4036 | 3.1 | 3860 | 3.6 |
| 2012 Mar | 4117 | 3.1 | 3900 | 3.6 |
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2012. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) in 2010 of 4786 in May. Nonfarm hiring fell again in Dec 2011 to 3038 from 3844 in Nov and to revised 3633 in Feb 2012, increasing to 4117 in Mar 2012. Chart I-6 provides seasonally-adjusted (SA) monthly data. The number of seasonally-adjusted hires in Aug 2011 was 4221 thousand, increasing to revised 4444 thousand in Feb 2012, or 5.3 percent, but falling to 4356 thousand in Mar 2012, or cumulative gain of 3.2 percent in Sep 2011. The number of hires not seasonally adjusted was 4655 in Aug 2011, falling to 3038 in Dec but increasing to 4072 in Jan 2012, falling again to 3580 in Feb 2012 and increasing to 4117 in Mar 2012. The number of nonfarm hiring not seasonally adjusted fell by 34.7 percent from 4655 in Aug to 3038 in Dec in a yearly-repeated seasonal pattern.
Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2012 Month SA
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Similar behavior occurs in the rate of nonfarm hiring plot 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 Sep 2011 to 3.2 in Jan 2012 and 3.3 in both Feb and Mar 2012. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.3 in Dec, climbing to 3.1 in Jan 2012 but falling to revised 2.8 in Feb 2012 and increasing to 3.1 in Mar 2012. 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 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
There is only milder improvement in total private hiring shown in Chart I-8. Hiring private (HP) rose in 2010 followed by stability and renewed increase in 2011. The number of private hiring seasonally adjusted fell from 4002 thousand in Sep 2011 to 3889 in Dec or by 2.8 percent, increasing to 3945 in Jan 2012 or decline by 1.4 relative to the level in Sep 2011 but moving to revised 4128 in Feb 2012 for increase of 3.1 percent relative to Sep 2011 and 4049 in Mar 2012 for increase of 1.2 percent relative to 4002 in Sep 2011. The number of private hiring not seasonally adjusted fell from 4130 in Sep 2011 to 2856 in Dec or by 30.8 percent, reaching 3782 in Jan 2012 or decline of 8.4 percent relative to Sep 2011 and 3900 in Mar 2012 or decline of 5.6 percent relative to Sep 2011. 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 4934 in Sep 2006 to 3635 in Dec 2006 or by 26.3 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 4293 in Jul 2011 or by 22.7 percent. The conclusion is that private hiring in the US is more than 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 2.4 percent in the eleven quarters of expansion of the economy since IIIQ2009 compared with average 6.2 percent in prior expansions from contractions (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.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 2011-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data has not risen significantly above the peak in 2010. The rate seasonally adjusted fell from 3.6 in Sep 2011 to 3.5 in Dec 2011, increasing to 3.6 in Jan 2012 and 3.7 in both Feb and Mar 2012. The rate not seasonally adjusted (NSA) fell from 3.8 in Sep to 2.6 in Dec, increasing to revused 3.5 in Jan 2012 but falling to 3.1 in Feb 2012 and then increasing to 3.6 in Mar 2012. The NSA rate of private hiring fell from 4.9 in Jun 2006 to 3.6 in Jun 2009 but recovery was insufficient to only 4.1 in Jun 2011.
Chart I-9, US, Rate Total Private Hiring Month SA 2011-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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 Mar from 2001 to 2012. The final column provides annual TNF LD for the years from 2001 to 2010. Nonfarm job openings fell from a peak of 4615 in Mar 2007 to 3678 in Mar 2012 or by 20.3 percent while the rate dropped from 3.3 to 2.7. Nonfarm layoffs and discharges (TNF LD) rose from 1353 in Mar 2006 to 1990 in Mar 2009 or by 47.1 percent. The yearly data show layoffs and discharges rising from 21.2 million in 2006 to 26.8 million in 2009 or by 26.4 percent.
Table I-4, US, Job Openings and Total Separations, Thousands NSA
| TNF JOB | TNF JOB | TNF LD | TNF LD | |
| Mar 2001 | 4569 | 3.4 | 1800 | 24499 |
| Mar 2002 | 3414 | 2.6 | 1432 | 22922 |
| Mar 2003 | 2955 | 2.2 | 1488 | 23294 |
| Mar 2004 | 3300 | 2.5 | 1538 | 22802 |
| Mar 2005 | 3832 | 2.8 | 1595 | 22185 |
| Mar 2006 | 4384 | 3.1 | 1353 | 21157 |
| Mar 2007 | 4615 | 3.3 | 1446 | 22142 |
| Mar 2008 | 3919 | 2.8 | 1492 | 24166 |
| Mar 2009 | 2515 | 1.9 | 1990 | 26783 |
| Mar 2010 | 2593 | 2.0 | 1465 | 21784 |
| Mar 2011 | 3102 | 2.3 | 1321 | 20718 |
| Mar 2012 | 3678 | 2.7 | 1326 |
Notes: TNF JOB: Total Nonfarm Job Openings; LD: Layoffs and Discharges
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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 3057 in Nov 2010 with 3737 seasonally adjusted in Mar 2012 also higher than 3501 in Sep 2011. Job openings recovered in Dec 2011 at 3540 but fell into Jan 2012 to 3477. The high of job openings not seasonally adjusted in 2010 was 3221 in Oct 2010 that was surpassed by 3659 in Oct 2011, increasing to 3678 in Mar 2012. The level of job openings not seasonally adjusted fell to 2912 in Nov 2011 or by 17.9 percent relative to 3546 in Sep 2011. There is here again the strong seasonality of year-end labor data. Job openings NSA fell from 4678 in Oct 2006 to 2547 in Oct 2009 or by 45.6 percent, recovering to 3221 in Oct 2011 or by 26.5 percent, which is still 31.1 percent lower in Oct 2011 relative to Oct 2006. Again, the main problem in recovery of the US labor market has been the low rate of growth of 2.4 percent in the eleven quarters of expansion of the economy since IIIQ2009 compared with average 6.2 percent in prior expansions from contractions (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.
Chart I-10, US Job Openings, Thousands NSA, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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 2.6 percent in Dec 2011. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 2.7 in Jul 2011 and 2.7 in Mar 2012. The rate of job openings NSA fell from 3.5 in Apr 2006 to 1.9 in Apr 2009, recovering insufficiently to 2.7 in Mar 2012.
Chart I-11, US, Rate of Job Openings, Thousands NSA, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Total separations are shown in Chart I-12. Separations are much lower in 2012 than before the global recession.
Chart I-12, US, Total Separations, Month SA, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Yearly total separations are shown in Chart I-13. Separations are much lower in 2011 than before the global recession.
Chart I-13, US, Total Separations, Annual, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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 2011 or by 14.0 million and 48.2 million in 2011 or by 13.4 million.
Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2011
| Year | Annual |
| 2001 | 64765 |
| 2002 | 59190 |
| 2003 | 56487 |
| 2004 | 58340 |
| 2005 | 60733 |
| 2006 | 61565 |
| 2007 | 61162 |
| 2008 | 58601 |
| 2009 | 51527 |
| 2010 | 47641 |
| 2011 | 48242 |
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
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.
Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly SA, 2011-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Layoffs and discharges in Chart I-15 rose sharply to a peak in 2009. There was pronounced drop into 2010 and 2011.
Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2011
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
Table I-6 provides annual nonfarm layoffs and discharges from 2001 to 2011. Layoffs and discharges peaked at 26.8 million in 2009 and then fell to 20.7 million in 2011, by 6.1 million, or 22.8 percent.
Table I-6, US, Total Nonfarm Layoffs and Discharges, 2001-2011
| Year | Annual |
| 2001 | 24499 |
| 2002 | 22922 |
| 2003 | 23294 |
| 2004 | 22802 |
| 2005 | 22185 |
| 2006 | 21157 |
| 2007 | 22142 |
| 2008 | 24166 |
| 2009 | 26783 |
| 2010 | 21784 |
| 2011 | 20718 |
Source: US Bureau of Labor Statistics
http://www.bls.gov/jlt/data.htm
IB 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 14.1 in Mar 2012.
Table I-7, US, Alternative Measures of Labor Underutilization %
| U1 | U2 | U3 | U4 | U5 | U6 | |
| Apr 2012 NSA | 4.8 | 4.3 | 7.7 | 8.3 | 9.1 | 14.1 |
| Mar 2012 NSA | 4.9 | 4.8 | 8.4 | 8.9 | 9.7 | 14.8 |
| Feb 2012 NSA | 4.9 | 5.1 | 8.7 | 9.3 | 10.2 | 15.6 |
| Jan 2012 | 4.9 | 5.4 | 8.8 | 9.4 | 10.5 | 16.2 |
| Dec 2011 NSA | 4.8 | 5.0 | 8.3 | 8.8 | 9.8 | 15.2 |
| Nov 2011 NSA | 4.9 | 4.7 | 8.2 | 8.9 | 9.7 | 15.0 |
| Oct 2011 NSA | 5.0 | 4.8 | 8.5 | 9.1 | 10.0 | 15.3 |
| Sep 2011 | 5.2 | 5.0 | 8.8 | 9.4 | 10.2 | 15.7 |
| Jan 2011 NSA | 5.6 | 6.2 | 9.8 | 10.4 | 11.4 | 17.3 |
| Feb 2011 | 5.6 | 6.0 | 9.5 | 10.1 | 11.1 | 16.7 |
| Dec 2010 NSA | 5.4 | 5.9 | 9.1 | 9.9 | 10.7 | 16.6 |
| 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 |
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: http://www.bls.gov/cps/data.htm
Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.2 percent in Aug 2011 to 16.4 percent in Sep 2011 and then fell to 14.5 percent in Apr 2012. 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 27.8 million in job stress of unemployment/underemployment in Apr 2012, not seasonally adjusted, corresponding to 17.3 percent of the labor force (http://cmpassocregulationblog.blogspot.com/2012/05/recovery-without-jobs-twenty-eight.html Table I-4).
Table I-8, US, Alternative Measures of Labor Underutilization SA %
| Apr 2011 | Mar 2012 | Feb 2012 | Jan 2012 | Dec 2011 | Nov | Oct 2011 | Sep 2011 | |
| U1 | 4.5 | 4.6 | 4.8 | 4.9 | 5.0 | 5.0 | 5.1 | 5.3 |
| U2 | 4.4 | 4.5 | 4.7 | 4.7 | 4.9 | 4.9 | 5.1 | 5.2 |
| U3 | 8.1 | 8.2 | 8.3 | 8.3 | 8.5 | 8.7 | 8.9 | 9.0 |
| U4 | 8.7 | 8.7 | 8.9 | 8.9 | 9.1 | 9.3 | 9.5 | 9.6 |
| U5 | 9.5 | 9.6 | 9.8 | 9.9 | 10.0 | 10.2 | 10.4 | 10.5 |
| U6 | 14.5 | 14.5 | 14.9 | 15.1 | 15.2 | 15.6 | 16.0 | 16.4 |
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: http://www.bls.gov/cps/data.htm
Chart I-16 provides U6 on a monthly basis from 2001 to 2012. 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.
Chart I-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers as % of Labor Force, Month, SA, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
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.
Chart I-17, US, Working Part-time for Economic Reasons
Thousands, Month SA 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
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 9.270 million in Sep 2011 to 7.853 million in Apr 2012, seasonally adjusted, or decline of 1.417 million in just six months, as shown in Table I-9. The number employed full-time increased from 112.479 million in Sep 2011 to 115.290 million in Mar 2012 or 2.811 million but then fell to 111.478 million in Apr 2012 or 1.001 million fewer full-time employed than in Sep 2011. 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 than in Jan 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 113.916 in Mar 2012 or increase by 778,000 compared with the level in Nov 2011 and further increased to 113.999 in Apr 2012 or 861,000 more than in Nov 2011. 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 108.770 million in Jan 2010 or by 14.449 million. The number with full-time jobs in Apr 2012 is 113.999 million, which is lower by 9.2 million relative to the peak of 123.219 million in Jul 2007. There appear to be around 10 million less full-time jobs in the US than before the global recession. Growth at 2.4 percent on average in the eleven quarters of expansion since IIIQ2009 compared with 6.2 percent on average in expansions from postwar cyclical contractions is the main culprit of the fractured US labor market (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/05/recovery-without-jobs-twenty-eight.html).
Table I-9, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions
| Part-time Thousands | Full-time Millions | |
| Seasonally Adjusted | ||
| Apr 2012 | 7,853 | 111.478 |
| Mar 2012 | 7,672 | 115.290 |
| Feb 2012 | 8,119 | 114.408 |
| Jan 2012 | 8,230 | 113.845 |
| Dec 2011 | 8,098 | 113.765 |
| Nov 2011 | 8,469 | 113.212 |
| Oct 2011 | 8,790 | 112.841 |
| Sep 2011 | 9,270 | 112.479 |
| Aug 2011 | 8,787 | 112.406 |
| Not Seasonally Adjusted | ||
| 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 |
| 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 |
| 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 |
| Apr 2009 | 8,648 | 112.746 |
| Mar 2009 | 9,305 | 112.215 |
| Feb 2009 | 9,170 | 112.947 |
| Jan 2009 | 8,829 | 113.815 |
| Apr 2008 | 5,071 | 120.027 |
| Mar 2008 | 5,038 | 119.875 |
| Feb 2008 | 5,114 | 119.452 |
| Jan 2008 | 5,340 | 119.322 |
| Jul 2007 | 4,516 | 123.219 (high) |
| Apr 2007 | 4,205 | 119.609 |
| Mar 2007 | 4,384 | 119.640 |
| Feb 2007 | 4,417 | 119.041 |
| Jan 2007 | 4,726 | 119.094 |
| Sep 2006 | 3,735 (low) | 120.780 |
| 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/cps/data.htm
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 2001-2011
Sources: http://www.bls.gov/cps/data.htm
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 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
IC 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 2012 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, 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
ID Youth 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. 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. 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 | Apr | Annual |
| 2001 | 19678 | 19745 | 19800 | 19778 | 20088 |
| 2002 | 18653 | 19074 | 19091 | 19108 | 19683 |
| 2003 | 18811 | 18880 | 18709 | 18873 | 19351 |
| 2004 | 18852 | 18841 | 18752 | 19184 | 19630 |
| 2005 | 18858 | 18670 | 18989 | 19071 | 19770 |
| 2006 | 19003 | 19182 | 19291 | 19406 | 20041 |
| 2007 | 19407 | 19415 | 19538 | 19368 | 19875 |
| 2008 | 18724 | 18546 | 18745 | 19161 | 19202 |
| 2009 | 17467 | 17606 | 17564 | 17739 | 17601 |
| 2010 | 16166 | 16412 | 16587 | 16764 | 17077 |
| 2011 | 16512 | 16638 | 16898 | 16970 | 17362 |
| 2012 | 16944 | 17150 | 17301 | 17387 |
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2012. Employment level is sharply lower in Apr 2012 relative to the peak in 2007.
Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
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. This situation may persist for many years.
Table I-11, US, Unemployment Level 16-24 Years, Thousands NSA
| Year | Jan | Feb | Mar | Apr | Annual |
| 2001 | 2250 | 2258 | 2253 | 2095 | 2371 |
| 2002 | 2754 | 2731 | 2822 | 2515 | 2683 |
| 2003 | 2748 | 2740 | 2601 | 2572 | 2746 |
| 2004 | 2767 | 2631 | 2588 | 2387 | 2638 |
| 2005 | 2661 | 2787 | 2520 | 2398 | 2521 |
| 2006 | 2366 | 2433 | 2216 | 2092 | 2353 |
| 2007 | 2363 | 2230 | 2096 | 2074 | 2342 |
| 2008 | 2633 | 2480 | 2347 | 2196 | 2830 |
| 2009 | 3278 | 3457 | 3371 | 3321 | 3760 |
| 2010 | 3983 | 3888 | 3748 | 3803 | 3857 |
| 2011 | 3851 | 3696 | 3520 | 3365 | 3634 |
| 2012 | 3416 | 3507 | 3294 | 3175 |
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
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.
Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
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 and 17.3 percent in 2011. During the seasonal peak in Jun 2011 the rate of youth unemployed was 18.1 percent compared with 10.8 percent in Jun 2007.
Table I-12, US, Unemployment Rate 16-24 Years, Thousands, NSA
| Year | Jan | Feb | Mar | Apr | Annual |
| 2001 | 10.3 | 10.3 | 10.2 | 9.6 | 10.6 |
| 2002 | 12.9 | 12.5 | 12.9 | 11.6 | 12.0 |
| 2003 | 12.7 | 12.7 | 12.2 | 12.0 | 12.4 |
| 2004 | 12.8 | 12.3 | 12.1 | 11.1 | 11.8 |
| 2005 | 12.4 | 13.0 | 11.7 | 11.2 | 11.3 |
| 2006 | 11.1 | 11.3 | 10.3 | 9.7 | 10.5 |
| 2007 | 10.9 | 10.3 | 9.7 | 9.7 | 10.5 |
| 2008 | 12.3 | 11.8 | 11.1 | 10.3 | 12.8 |
| 2009 | 15.8 | 16.4 | 16.1 | 15.8 | 17.6 |
| 2010 | 19.8 | 19.2 | 18.4 | 18.5 | 18.4 |
| 2011 | 18.9 | 18.2 | 17.2 | 16.5 | 17.3 |
| 2012 | 16.8 | 17.0 | 16.0 | 15.4 |
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 23 years from 2002 to 2012. 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 eleven quarters of expansion of the economy since IIIQ2009.
Chart I-23, US, Unemployment Rate 16-24 Years, Thousands, NSA, 2002-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2012. 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 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: 19.9 percent in Jun 2009, 20.0 percent in Jun 2010 and 18.9 percent in Jun 2011. 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 2.4 percent on average during the first eleven quarters of expansion from IIIQ2009 to IQ2012 (see Table I-5 at http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html). The fractured US labor market denies an early start for young people.
Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1979-2012
Sources: US Bureau of Labor Statistics
http://www.bls.gov/cps/data.htm
II United States International Trade. There are two subsections below: IIA United States International Trade Balance and IIB United States Import and Export Prices.
IIA United States International Trade Balance. Table IIA-1 provides the trade balance of the US and monthly growth of exports and imports seasonally adjusted. The US trade balance deteriorated from deficit of $45,416 million in Feb 2012 to deficit of $51,825 billion in Mar 2012 with growth of exports of 2.9 percent lower than growth of imports of 5.2 percent. The US trade balance had improved from deficit of $52,522 million in Jan 2012 to lower deficit of $45,416 million in Feb 2012 mostly because of decline of imports by 2.8 percent while exports increased only 0.3 percent. The US trade balance deteriorated sharply from Nov to Jan with growth of imports by cumulative 4.9 percent and cumulative growth of exports of only 0.8 percent, resulting in deficits of $47,524 million in Nov, $50,421 million in Dec and $52,522 million in Jan, which are the highest since $51,774 million in Jun. There was mild improvement in the balance of international trade in goods and services of the US from Jul to Oct, declining from deficit of $50,210 million in May and $51,774 million in Jun to deficit of $43,121 million in Oct, as shown in Table IIA-1. In the months of Jun to Oct, exports increased 2.2 percent while imports fell 1.4 percent. The trade balance deteriorated from cumulative deficit of $500,027 million in Jan-Dec 2010 to deficit of $559,956 million in Jan-Dec 2011.
Table IIA-1, US, Trade Balance of Goods and Services Seasonally Adjusted Millions of Dollars and ∆%
| Trade Balance | Exports | Month ∆% | Imports | Month ∆% | |
| Mar 2012 | -51,825 | 186,770 | 2.9 | 238,595 | 5.2 |
| Feb | -45,416 | 181,490 | 0.3 | 226,906 | -2.8 |
| Jan | -52,522 | 180,921 | 1.5 | 233,443 | 2.1 |
| Dec 2011 | -50,421 | 178,229 | 0.4 | 228,650 | 1.6 |
| Nov | -47,524 | 177,567 | -1.1 | 225,091 | 1.1 |
| Oct | -43,121 | 179,593 | -0.9 | 222,714 | -1.1 |
| Sep | -44,009 | 181,156 | 1.4 | 225,165 | 0.6 |
| Aug | -45,091 | 178,639 | 0.1 | 223,730 | -0.1 |
| Jul | -45,613 | 178,395 | 3.8 | 224,008 | 0.2 |
| Jun | -51,774 | 171,806 | -2.2 | 223,580 | -1.1 |
| May | -50,210 | 175,744 | -0.3 | 225,954 | 2.9 |
| Apr | -43,231 | 176,315 | 1.3 | 219,547 | -0.2 |
| Mar | -46,059 | 173,997 | 5.0 | 220,056 | 4.2 |
| Feb | -45,381 | 165,741 | -1.3 | 211,123 | -2.0 |
| Jan | -47,521 | 167,864 | 2.4 | 215,385 | 5.3 |
| Dec 2010 | -40,454 | 164,006 | 1.7 | 204,459 | 2.2 |
| Jan-Dec | -559,956 | 2,105,046 | 2,665,002 | ||
| Jan-Dec | -500,027 | 1,837,577 | 2,337,604 |
Note: Trade Balance of Goods and Services = Exports of Goods and Services less Imports of Goods and Services. Trade balance may not add exactly because of errors of rounding.
Source: http://www.census.gov/foreign-trade/Press-Release/current_press_release/ft900.pdf
Table IIA-2 provides the US international trade balance, exports and imports on an annual basis from 1992 to 2011. The trade balance deteriorated sharply over the long term. The current account deficit of the US declined from $123.4 billion in IIQ2010, or 3.3 percent of GDP to $107.6 billion in IIIQ2011, or 2.8 percent of GDP, but increased to $124.1 billion in IVQ2011, or 3.2 percent of GDP. In IVQ2010, the deficit reached $112.2 billion or 3.3 percent of GDP (for the balance of payments in IVQ2011 see http://cmpassocregulationblog.blogspot.com/2012/03/global-financial-and-economic-risk_18.html). The balance of international transactions or balance of payments of the US for IQ2012 will be released on Jun 14, 2012 (http://www.bea.gov/newsreleases/international/transactions/transnewsrelease.htm).
In IVQ2010, “the deficit decreased to 3.0 percent of current-dollar GDP from 3.4 percent, the first decrease after five straight quarterly increases” (http://www.bea.gov/scb/pdf/2011/04%20April/0411_itaq-text.pdf 1). The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession (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). The current account deficit reached 6.1 percent of GDP in 2006. The external imbalance of the US measured by the current account deficit must be financed with foreign borrowings. The US borrows heavily from other countries. China is the largest holder of US Treasury securities with $1178.9 billion in Feb 2012, increasing 2.1 percent from $1154.1 billion in Feb 2011. Japan increased its holdings from $890.4 billion in Feb 2011 to $1095.9 billion in Feb 2012. Oil exporters increased their holdings from $219.0 billion in Feb 2011 to $264.5 billion in Feb 2012. Total foreign holdings of Treasury securities rose from $4467.0 billion in Feb 2011 to $5100.3 billion in Feb 2011, or 14.2 percent. The US continues to finance its fiscal and balance of payments deficits with foreign savings (see Table VA-13 at http://cmpassocregulationblog.blogspot.com/2012/04/imf-view-of-world-economy-and-finance_22.html).
Table IIA-2, US, International Trade Balance, Exports and Imports SA, Millions of Dollars
| Period | Balance | Exports | Imports |
| Total | |||
| Annual | |||
| 1992 | -39,212 | 616,882 | 656,094 |
| 1993 | -70,311 | 642,863 | 713,174 |
| 1994 | -98,493 | 703,254 | 801,747 |
| 1995 | -96,384 | 794,387 | 890,771 |
| 1996 | -104,065 | 851,602 | 955,667 |
| 1997 | -108,273 | 934,453 | 1,042,726 |
| 1998 | -166,140 | 933,174 | 1,099,314 |
| 1999 | -263,160 | 967,008 | 1,230,168 |
| 2000 | -376,749 | 1,072,783 | 1,449,532 |
| 2001 | -361,771 | 1,007,726 | 1,369,496 |
| 2002 | -417,432 | 980,879 | 1,398,311 |
| 2003 | -490,984 | 1,023,519 | 1,514,503 |
| 2004 | -605,357 | 1,163,146 | 1,768,502 |
| 2005 | -708,624 | 1,287,441 | 1,996,065 |
| 2006 | -753,288 | 1,459,823 | 2,213,111 |
| 2007 | -696,728 | 1,654,561 | 2,351,289 |
| 2008 | -698,338 | 1,842,682 | 2,541,020 |
| 2009 | -381,272 | 1,575,037 | 1,956,310 |
| 2010 | -500,027 | 1,837,577 | 2,337,604 |
| 2011 | -559,956 | 2,105,046 | 2,665,002 |
Source: http://www.bea.gov/international/index.htm#trade
Chart IIA-1 provides the chart of the US Census Bureau with inventories/sales ratios of merchant wholesalers from 2002 to 2011 seasonally adjusted. Inventory/sales ratios rise during contractions as merchants are caught with increasing inventories because of weak sales and fall during expansions as merchants attempt to fill sales with existing stocks.
Chart IIA-1 of the US Census Bureau of the Department of Commerce shows that the trade deficit (gap between exports and imports) fell during the economic contraction after 2007 but has grown again during the expansion. There was slight improvement at the margin from Jul to Oct 2011 but new increase in the gap from Nov to Jan and again in Mar as exports grow less rapidly than imports. Weaker world and internal demand and fluctuating commodity price increases explain the declining or less dynamic changes in exports and imports in Chart IIA-1.
Chart IIA-1, US Balance, Exports and Imports of Goods and Services $ Billions
Source: US Census Bureau
http://www.census.gov/briefrm/esbr/www/esbr042.html
The balance of international trade in goods of the US seasonally-adjusted is shown in Table IIA-3. The US has a dynamic surplus in services that reduces the large deficit in goods for a still very sizeable deficit in international trade of goods and services. The balance in international trade of goods deteriorated from $60.7 billion in Mar 2011 to $67.6 billion in Mar 2012. Deterioration of the goods balance in Mar 2012 relative to Mar 2011 occurred mostly in the non petroleum balance, exports less imports of goods other than petroleum, while there was improvement in the petroleum balance, exports less imports of petroleum goods. Exports rose 6.5 percent with non-petroleum exports growing 5.3 percent. Total imports rose 8.1 percent with petroleum imports increasing 1.9 percent and non-petroleum imports increasing 9.9 percent.
Table IIA-3, US, International Trade in Goods Balance, Exports and Imports $ Millions and ∆% SA
| Mar 2012 | Mar 2011 | ∆% | |
| Total Balance | -67,615 | -60,715 | |
| Petroleum | -28,576 | -30,356 | |
| Non Petroleum | -37,984 | -29,820 | |
| Total Exports | 132,670 | 124,517 | 6.5 |
| Petroleum | 10,291 | 7,799 | 31.9 |
| Non Petroleum | 121,178 | 115,049 | 5.3 |
| Total Imports | 200,285 | 185,232 | 8.1 |
| Petroleum | 38,867 | 38,154 | 1.9 |
| Non Petroleum | 159,162 | 144,869 | 9.9 |
Details may not add because of rounding and seasonal adjustment
Source: http://www.census.gov/foreign-trade/Press-Release/current_press_release/ft900.pdf
US exports and imports of goods not seasonally adjusted in Jan-Feb 2012 and Jan-Feb 2011 are shown in Table IIA-4. The rate of growth of both exports and imports was 8.6 percent. The US has partial hedge of commodity price increases in exports of agricultural commodities that fell 6.8 percent and of mineral fuels that increased 18.0 percent both because of higher prices of raw materials and commodities. The US exports an insignificant amount of crude oil. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports rose 10.1 percent while imports rose 9.0 percent. Significant part of the US trade imbalance originates in imports of mineral fuels growing by 6.4 percent and crude oil increasing 8.5 percent. The limited hedge in exports of agricultural commodities and mineral fuels compared with substantial imports of mineral fuels and crude oil results in deterioration of the terms of trade of the US, or export prices relative to import prices, originating in commodity price increases caused by carry trades from zero interest rates.
Table IIA-4, US, Exports and Imports of Goods, Not Seasonally Adjusted Millions of Dollars and %
| Jan-Mar 2012 $ Millions | Jan-Mar 2011 $ Millions | ∆% | |
| Exports | 381,471 | 351,109 | 8.6 |
| Manufactured | 252,462 | 229,316 | 10.1 |
| Agricultural | 35,005 | 37,558 | -6.8 |
| Mineral Fuels | 32,282 | 27,360 | 18.0 |
| Crude Oil | 429 | 301 | 42.5 |
| Imports | 552,432 | 508,850 | 8.6 |
| Manufactured | 406,027 | 372,479 | 9.0 |
| Agricultural | 26,787 | 24,173 | 10.8 |
| Mineral Fuels | 109,477 | 102,910 | 6.4 |
| Crude Oil | 81,618 | 75,191 | 8.5 |
Source: http://www.census.gov/foreign-trade/Press-Release/current_press_release/ft900.pdf
IIB Import Export Prices. Chart IIB-1 provides prices of total US imports 2001-2012. Prices fell during the contraction of 2001. Import price inflation accelerated after unconventional monetary policy of near zero interest rates in 2003-2004 and quantitative easing by withdrawing supply with the suspension of 30-year Treasury bond auctions. Slow pace of adjusting fed funds rates from 1 percent by increments of 25 basis points in 17 consecutive meetings of the Federal Open Market Committee (FOMC) between Jun 2004 and Jun 2006 continued to give impetus to carry trades. The reduction of fed funds rates toward zero in 2008 fueled a spectacular global hunt for yields that caused commodity price inflation in the middle of a global recession. After risk aversion in 2009 because of the announcement of TARP (Troubled Asset Relief Program) creating anxiety on “toxic assets” in bank balance sheets (see Cochrane and Zingales 2009), prices collapsed after unwinding carry trades. Renewed price increases returned with zero interest rates and quantitative easing. Monetary policy impulses in massive doses have driven inflation and valuation of risk financial assets in wide fluctuations over a decade.
Chart IIB-1, US, Prices of Total US Imports 2001=100, 2001-2012
Source: http://www.bls.gov/mxp/data.htm
Chart IIB-2 provides 12-month percentage changes of prices of total US imports from 2001 to 2012. The only plausible explanation for the wide oscillations is by the carry trade from unconventional monetary policy. Import prices jumped in 2008 during deep and protracted global recession driven by carry trades from zero interest rates to long, leveraged positions in commodity futures. Carry trades were unwound during the financial panic in the final quarter of 2008 that resulted in flight to government obligations. Import prices jumped again in 2009 with subdued risk aversion because US banks did not have unsustainable toxic assets. Import prices then fluctuated as carry trades were resumed during periods of risk appetite and unwound during risk aversion resulting from the European debt crisis.
Chart IIB-2, US, Prices of Total US Imports, 12-Month Percentage Changes, 2001-2012
Source: http://www.bls.gov/mxp/data.htm
Chart IIB-3 provides prices of US imports from 1982 to 2012. There is no similar episode to that of the increase of commodity prices in 2008 during a protracted and deep global recession with subsequent collapse during a flight into government obligations. Trade prices have been driven by carry trades created by unconventional monetary policy in the past decade.
Chart IIB-3, US, Prices of Total US Imports, 2001=100, 1982-2012
Source: http://www.bls.gov/mxp/data.htm
Chart IIB-4 provides 12-month percentage changes of US total imports from 1982 to 2012. There have not been wide consecutive oscillations as the ones during the global recession of IVQ2007 to IIQ2009.
Chart IIB-4, US, Prices of Total US Imports, 12-Month Percentage Changes, 1982-2012
Source: http://www.bls.gov/mxp/data.htm
Chart IIB-5 provides the index of US export prices from 2001 to 2012. Import and export prices have been driven by impulses of unconventional monetary policy in massive doses. The most recent segment in Chart IIB-5 shows declining trend resulting from a combination of the world economic slowdown and the decline of commodity prices as carry trade exposures are unwound because of risk aversion to the sovereign debt crisis in Europe.
Chart IIB-5, US, Prices of Total US Exports, 2001=100, 2001-2012
Source: http://www.bls.gov/mxp/data.htm
Chart IIB-6 provides prices of US total exports from 1982 to 2012. The rise before the global recession from 2003 to 2008, driven by carry trades, is also unique in the series.
Chart IIB-6, US, Prices of Total US Exports, 2001=100, 1982-2012
Source: http://www.bls.gov/mxp/data.htm
Chart IIB-7 provides 12-month percentage changes of total US exports from 1982 to 2012. The uniqueness of the oscillations around the global recession of IVQ2007 to IIQ2009 is clearly revealed.
Chart IIB-7, US, Prices of Total US Exports, 12-Month Percentage Changes, 1982-2012
Source: http://www.bls.gov/mxp/data.htm
Twelve-month percentage changes of US prices of exports and imports are provided in Table IIB-1. Import prices have been driven since 2003 by unconventional monetary policy of near zero interest rates influencing commodity prices according to moods of risk aversion. In a global recession without risk aversion until the panic of Sep 2008 with flight to government obligations, import prices rose 16.9 percent in the twelve months ending in Apr 2008 and fell 16.4 percent in the 12 months ending in Apr 2009 when risk aversion developed in 2008 until mid 2009. Import prices rose again sharply in Apr 2010 by 11.2 percent and in 2011 by 11.9 percent in the presence of zero interest rates with relaxed mood of risk aversion until carry trades were unwound in May 2011. There is similar behavior of prices of imports ex fuels, exports and exports ex agricultural goods but less pronounced than for commodity-rich prices dominated by carry trades from zero interest rates. A critical event resulting from unconventional monetary policy driving higher commodity prices by carry trades is the deterioration of the terms of trade, or export prices relative to import prices, that has adversely affected US real income growth relative to what it would have been in the absence of unconventional monetary policy. Europe, Japan and other advanced economies have experienced similar deterioration of their terms of trade.
Table IIB-1, US, Twelve-Month Percentage Rates of Change of Prices of Exports and Imports
| Imports | Imports Ex Fuels | Exports | Exports Non-Ag | |
| Apr 2012 | 0.5 | 1.3 | 0.7 | 1.2 |
| Apr 2011 | 11.9 | 4.6 | 9.2 | 6.8 |
| Apr 2010 | 11.2 | 3.2 | 5.5 | 5.7 |
| Apr 2009 | -16.4 | -3.8 | -6.7 | -5.4 |
| Apr 2008 | 16.9 | 6.0 | 8.0 | 5.7 |
| Apr 2007 | 2.1 | 2.7 | 5.1 | 4.0 |
| Apr 2006 | 5.8 | 0.6 | 2.5 | 2.6 |
| Apr 2005 | 8.4 | 2.4 | 3.1 | 4.5 |
| Apr 2004 | 4.6 | 2.4 | 4.1 | 2.4 |
| Apr 2003 | 1.8 | 0.4 | 1.6 | 1.2 |
| Apr 2002 | -3.6 | NA | -1.9 | -2.0 |
| Apr 2001 | -0.7 | NA | -0.1 | -0.1 |
Source: http://www.bls.gov/mxp/data.htm#
Chart IIB-8 shows the US monthly import price index of all commodities excluding fuels from 2001 to 2011. All curves of nominal values follow the same behavior under the influence of unconventional monetary policy. Zero interest rates without risk aversion result in jumps of nominal values while under strong risk aversion even with zero interest rates there are declines of nominal values.
Chart IIB-8, US, Import Price Index All Commodities Excluding Fuels, 2001=100, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-9 provides 12-month percentage changes of the US import price index excluding fuels between 2001 and 2012. There is the same behavior of carry trades driving up without risk aversion and down with risk aversion prices of raw materials, commodities and food in international trade during the global recession of IVQ2007 to IIQ2009 and in previous and subsequent periods.
Chart IIB-9, US, Import Price Index All Commodities Excluding Fuels, 12-Month Percentage Changes, 2002-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-10 provides the monthly US import price index ex petroleum from 2001 to 2012. Prices including or excluding commodities follow the same fluctuations and trends originating in impulses of unconventional monetary policy of zero interest rates.
Chart IIB-10, US, Import Price Index ex Petroleum, 2001=100, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-11 provides the US import price index ex petroleum from 1982 to 2012. There is the same unique hump in 2008 caused by carry trades from zero interest rates to prices of commodities and raw materials.
Chart IIB-11, US, Import Price Index ex Petroleum, 2001=100, 1982-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-12 provides 12-month percentage changes of the import price index ex petroleum from 1986 to 2012. The oscillations caused by the carry trade in increasing prices of commodities and raw materials without risk aversion and subsequently decreasing them during risk aversion are quite unique.
Chart IIB-12, US, Import Price Index ex Petroleum, 12-Month Percentage Changes, 1986-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-13 of the US Energy Information Administration provides the price of the crude oil futures contract from 1985 to 2012. There is the same hump in 2008 as in all charts caused by the common factor of carry trades from zero interest rates to commodity futures positions with risk appetite and subsequent decline when carry trades were unwound during shocks of risk aversion.
Chart IIB-13, US, Crude Oil Futures Contract
Source: US Energy Information Administration
http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RCLC1&f=D
The price index of US imports of petroleum and petroleum products in shown in Chart IIB-14. There is similar behavior of the curves all driven by the same impulses of monetary policy.
Chart IIB-14, US, Import Price Index of Petroleum and Petroleum Products, 2001=100, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-15 provides the price index of petroleum and petroleum products from 1982 to 2012. The rise in prices during the global recession in 2008 and the decline after the flight to government obligations is unique in the history of the series. Increases in prices of trade in petroleum and petroleum products were induced by carry trades and declines by unwinding carry trades in flight to government obligations.
Chart IIB-15, US, Import Price Index of Petroleum and Petroleum Products, 2001=100, 1982-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-16 provides 12-month percentage changes of the price index of US imports of petroleum and petroleum products from 1982 to 2012. There were wider oscillations in this index from 1999 to 2001 (see Barsky and Killian 2004 for an explanation).
Chart IIB-16, US, Import Price Index of Petroleum and Petroleum Products, 12-Month Percentage Changes, 1982-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
The price index of US exports of agricultural commodities is in Chart IB-17 from 2001 to 2012. There are similar fluctuations and trends as in all other price index originating in unconventional monetary policy repeated over a decade. The most recent segment in 2011 has declining trend in a new flight from risk resulting from the sovereign debt crisis in Europe.
Chart IIB-17, US, Exports Price Index of Agricultural Commodities, 2001=100, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-18 provides the price index of US exports of agricultural commodities from 1982 to 2012. The increase in 2008 in the middle of deep, protracted contraction was induced by unconventional monetary policy. The decline from 2008 into 2009 was caused by unwinding carry trades in a flight to government obligations. The increase into 2011 and current pause were also induced by unconventional monetary policy in waves of increases during relaxed risk aversion and declines during unwinding of positions because of aversion to financial risk.
Chart IIB-18, US, Exports Price Index of Agricultural Commodities, 2001=100, 1982-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-19 provides 12-month percentage changes of the index of US exports of agricultural commodities from 1986 to 2012. The wide swings in 2008, 2009 and 2011 are only explained by unconventional monetary policy inducing carry trades from zero interest rates to commodity futures and reversals during risk aversion.
Chart IIB-19, US, Exports Price Index of Agricultural Commodities, 12-Month Percentage Changes, 1986-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-20 shows the export price index of nonagricultural commodities from 2001 to 2012. Unconventional monetary policy of zero interest rates drove price behavior during the past decade. Policy has been based on the myth of stimulating the economy by climbing the negative slope of an imaginary short-term Phillips curve.
Chart IIB-20, US, Exports Price Index of Nonagricultural Commodities, 2001=100, 2001-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIB-21 provides a longer perspective of the price index of US nonagricultural commodities from 1982 to 2012. Increases and decreases around the global contraction after 2007 were caused by carry trade induced by unconventional monetary policy.
Chart IIB-21, US, Exports Price Index of Nonagricultural Commodities, 2001=100, 1982-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Finally, Chart IIB-22 provides 12-month percentage changes of the price index of US exports of nonagricultural commodities from 1986 to 2012. The wide swings before, during and after the global recession beginning in 2007 were caused by carry trades induced by unconventional monetary policy.
Chart IIB-22, US, Exports Price Index of Nonagricultural Commodities, 12-Month Percentage Changes, 1986-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
III World Financial Turbulence. Financial markets are being shocked by multiple factors including (1) world economic slowdown; (2) growth in China with political development, Japan and world trade; (3) slow growth propelled by savings reduction in the US with high unemployment/underemployment, falling wages and hiring collapse; and (3) the outcome of the sovereign debt crisis in Europe. This section provides current data and analysis. Subsection IIIA Financial Risks provides analysis of the evolution of valuations of risk assets during the week. There are various appendixes at the end of this section for convenience of reference of material related to the euro area debt crisis. Some of this material is updated in Subsection IIIA when new data are available and then maintained in the appendixes for future reference until updated again in Subsection IIIA. Subsection IIIB Appendix on Safe Haven Currencies discusses arguments and measures of currency intervention. Subsection IIIC Appendix on Fiscal Compact provides analysis of the restructuring of the fiscal affairs of the European Union in the agreement of European leaders reached on Dec 9, 2011. Subsection IIID Appendix on European Central Bank Large Scale Lender of Last Resort considers the policies of the European Central Bank. Appendix IIIE Euro Zone Survival Risk analyzes the threats to survival of the European Monetary Union. Subsection IIIF Appendix on Sovereign Bond Valuation provides more technical analysis.
IIIA Financial Risks. The past half year has been characterized by financial turbulence, attaining unusual magnitude in recent months. Table III-1, updated with every comment in this blog, provides beginning values on Fr May 4 and daily values throughout the week ending on Fri May 11 of various financial assets. Section VI Valuation of Risk Financial Assets provides a set of more complete values. All data are for New York time at 5 PM. The first column provides the value on Fri May 4 and the percentage change in that prior week below the label of the financial risk asset. For example, the US dollar (USD) appreciated 1.3 percent to USD 1.3084/EUR in the week ending on May 4. The first five asset rows provide five key exchange rates versus the dollar and the percentage cumulative appreciation (positive change or no sign) or depreciation (negative change or negative sign). Positive changes constitute appreciation of the relevant exchange rate and negative changes depreciation. Financial turbulence has been dominated by reactions to the new program for Greece (see section IB in http://cmpassocregulationblog.blogspot.com/2011/07/debt-and-financial-risk-aversion-and.html), modifications and new approach adopted in the Euro Summit of Oct 26 (European Commission 2011Oct26SS, 2011Oct26MRES), doubts on the larger countries in the euro zone with sovereign risks such as Spain and Italy but expanding into possibly France and Germany, the growth standstill recession and long-term unsustainable government debt in the US, worldwide deceleration of economic growth and continuing waves of inflation. The most important current shock is that resulting from the agreement by European leaders at their meeting on Dec 9 (European Council 2911Dec9), which is analyzed in IIIC Appendix on Fiscal Compact. European leaders reached a new agreement on Jan 30 (http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/127631.pdf).
The dollar/euro rate is quoted as number of US dollars USD per one euro EUR, USD 1.3084/EUR in the first row, first column in the block for currencies in Table III-1 for Fri May 4, appreciating to USD 1.3051/EUR on Mon May 7, or by 0.3 percent. The dollar appreciated because fewer dollars, $1.3051, were required on Mon May 7 to buy one euro than $1.3084 on May 4. Table III-1 defines a country’s exchange rate as number of units of domestic currency per unit of foreign currency. USD/EUR would be the definition of the exchange rate of the US and the inverse [1/(USD/EUR)] is the definition in this convention of the rate of exchange of the euro zone, EUR/USD. A convention used throughout this blog is required to maintain consistency in characterizing movements of the exchange rate in Table III-1 as appreciation and depreciation. The first row for each of the currencies shows the exchange rate at 5 PM New York time, such as USD 1.3051/EUR on May 7; the second row provides the cumulative percentage appreciation or depreciation of the exchange rate from the rate on the last business day of the prior week, in this case Fri May 4, to the last business day of the current week, in this case Fri May 11, such as appreciation by 1.3 percent to USD 1.2917/EUR by May 11; and the third row provides the percentage change from the prior business day to the current business day. For example, the USD appreciated (denoted by positive sign) by 1.3 percent from the rate of USD 1.3084/EUR on Fri May 4 to the rate of USD 1.2917/EUR on Fri May 11 {[(1.2917/1.3084) – 1]100 = -1.3%} and appreciated (denoted by positive sign) by 0.3 percent from the rate of USD 1.2950 on Thu May 10 to USD 1.2917/EUR on Fri May 11 {[(1.2917/1.2950) -1]100 = -0.3%}. Other factors constant, appreciation of the dollar relative to the euro is caused by increasing risk aversion, with rising uncertainty on European sovereign risks increasing dollar-denominated assets with sales of risk financial investments. Funds move away from higher yielding risk financial assets to the safety of dollar investments. When risk aversion declines, funds have been moving away from safe assets in dollars to risk financial assets, depreciating the dollar.
Table III-I, Weekly Financial Risk Assets Dec 26 to Dec 30, 2012
| Fri May 4, 2012 | M 7 | Tue 8 | W 9 | Thu 10 | Fr 11 |
| USD/EUR 1.3084 1.3% | 1.3051 0.3% 0.3% | 1.3006 0.6% 0.3% | 1.2938 1.1% 0.5% | 1.2950 1.0% -0.1% | 1.2917 1.3% 0.3% |
| JPY/ USD 79.84 0.5% | 79.92 -0.1% -0.1% | 79.86 0.0% 0.1% | 79.63 0.3% 0.3% | 80.01 -0.2% -0.5% | 79.94 -0.1% 0.1% |
| CHF/ USD 0.9181 -1.3% | 0.9206 -0.3% -0.3% | 0.9235 -0.6% -0.3% | 0.9284 -1.1% -0.5% | 0.9276 -1.0% 0.1% | 0.9299 -1.3% -0.2% |
| CHF/ EUR 1.2012 0.0% | 1.2014 0.0% 0.0% | 1.2010 0.0% 0.0% | 1.2010 0.0% 0.0% | 1.2012 0.0% 0.0% | 1.2011 0.0% 0.0% |
| USD/ AUD 1.0173 0.9830 -2.9% | 1.0196 0.9808 0.2% 0.2% | 1.0117 0.9884 -0.5% -0.8% | 1.0054 0.9946 -1.2% -0.6% | 1.0099 0.9901 -0.7% 0.5% | 1.0022 0.9978 -1.5% -0.8% |
| 10 Year T Note 1.876 | 1.88 | 1.84 | 1.83 | 1.88 | 1.845 |
| 2 Year T Note 0.256 | 0.25 | 0.25 | 0.26 | 0.26 | 0.248 |
| German Bond 2Y 0.08 10Y 1.58 | 2Y 0.10 10Y 1.60 | 2Y 0.09 10Y 1.54 | 2Y 0.07 10Y 1.52 | 2Y 0.07 10Y 1.54 | 2Y 0.09 10Y 1.52 |
| DJIA 13038.27 -1.4% | 13008.53 -0.2% -0.2% | 12932.09 -0.8% -0.6% | 12835.06 -1.6% -0.8% | 12855.04 -1.4% 0.2% | 12820.60 -1.7% -0.3% |
| DJ Global 1893.39 -2.7% | 1887.61 -0.3% -0.3% | 1871.53 -1.2% -0.9% | 1853.88 -2.1% -0.9% | 1861.66 -1.7% 0.4% | 1853.93 -2.1% -0.4% |
| DJ Asia Pacific 1266.78 -0.2% | 1239.77 -2.1% -2.1% | 1241.44 -2.0% 0.1% | 1225.47 -3.3% -1.3% | 1224.23 -3.3% -0.1% | 1212.53 -4.3% -1.0% |
| Nikkei 9380.25 -1.5% | 9119.14 -2.8% -2.8% | 9181.65 -2.1% 0.7% | 9045.06 -3.6% -1.5% | 9009.65 -4.0% -0.4% | 8953.31 -4.6% -0.6% |
| Shanghai 2452.01 2.3% | 2451.95 0.0% 0.0% | 2448.88 -0.1% -0.1% | 2408.59 -1.8% -1.7% | 2410.23 -1.7% 0.1% | 2394.98 -2.3% -0.6% |
| DAX 6561.47 -3.5% | 6569.48 0.1% 0.1% | 6444.74 -1.8% -1.9% | 6475.31 -1.3% 0.5% | 6518.00 -0.7% 0.7% | 6579.93 0.3% 1.0% |
| DJ UBS Comm. 137.14 -2.5 | 137.31 0.1% 0.1% | 136.27 -0.6% -0.8% | 135.91 -0.9% -0.3% | 136.01 -0.8% 0.1% | 134.75 -1.7% -0.9% |
| WTI $ B 98.50 -6.0% | 97.95 -0.6% -0.6% | 97.43 -1.1% -0.5% | 96.50 -2.0% -0.9% | 96.91 -1.6% -0.4% | 95.66 -2.9% -1.3% |
| Brent $/B 113.35 -5.2% | 113.38 0.0% 0.0% | 113.10 -0.2% -0.2% | 112.74 -0.5% -0.3% | 112.60 -0.7% -0.1% | 112.06 -1.1% -0.5% |
| Gold $/OZ 1642.4 -1.2% | 1639.5 -0.2% -0.2% | 1605.5 -2.2% -2.1% | 1591.1 -3.1% -0.9% | 1595.4 -2.9% 0.3% | 1580.0 -3.8% -0.9% |
Note: USD: US dollar; JPY: Japanese Yen; CHF: Swiss
Franc; AUD: Australian dollar; Comm.: commodities; OZ: ounce
Sources: http://www.bloomberg.com/markets/
http://professional.wsj.com/mdc/page/marketsdata.html?mod=WSJ_hps_marketdata
There were events in US banking and Spanish banks during the week of May 11. These events are as follows.
In its Form 10-Q Quarterly Report for IQ2012 filed with the Securities and Exchange Commission (SEC), JP Morgan Chase states (page 9, http://investor.shareholder.com/jpmorganchase/secfiling.cfm?filingID=19617-12-213):
“Since March 31, 2012, CIO has had significant mark-to market losses in its synthetic credit portfolio, and this portfolio has proven to be riskier, more volatile and less effective as an economic hedge than the Firm previously believed. The losses in CIO's synthetic credit portfolio have been partially offset by realized gains from sales, predominantly of credit-related positions, in CIO's AFS securities portfolio. As of March 31, 2012, the value of CIO's total AFS securities portfolio exceeded its cost by approximately $8 billion. Since then, this portfolio (inclusive of the realized gains in the second quarter to date) has appreciated in value.”
Dan Fitzpatrick, Robin Sidel and David Enrich, writing on “Bank order led to losing trades,” on May 12, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702304070304577398490966089810.html?mod=WSJPRO_hpp_LEFTTopStories), refer to a “person close to the bank” that the trading losses could have reached $2.3 billion in 15 days at the end of Apr and beginning of May for $153 million in daily average. Dan Fitzpatrick, Robin Sidel and David Enrich, writing on “Bank order led to losing trades,” on May 12, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702304070304577398490966089810.html?mod=WSJPRO_hpp_LEFTTopStories), inform on the basis of sources that the trading losses originated in an order to reduce credit exposures at the bank that could be sensitive to the European sovereign debt crisis. The mark-to-market losses originated in selling protection through the Markit CDX North American Investment Grade with 125 reference names (http://www.markit.com/assets/en/docs/products/data/indices/credit-index-annexes/IG%209%20v4.pdf http://www.markit.com/en/products/data/indices/credit-and-loan-indices/cdx/cdx.page). There are no details on the specific trade and what was being hedged. The Markit CDX family of indices is designed to provide vehicles to trade credit default swaps (CDS) worldwide (http://www.markit.com/en/products/data/indices/credit-and-loan-indices/cdx/cdx.page). The CDS buyer obtains credit protection against a credit event by paying a periodic fee to a seller in order to receive payment in case of default by a referenced credit (see Pelaez and Pelaez, International Financial Architecture (2005), 134-54). Types of credit events include bankruptcy, merger, cross acceleration, cross default, downgrade, failure to pay, repudiation, restructuring and currency inconvertibility. Credit events in the Markit CDS indices are bankruptcy and failure to pay, which are settled in credit event auctions (http://www.markit.com/en/products/data/indices/credit-and-loan-indices/cdx/cdx.page). There is insufficient information to analyze the trading exposures of the bank. The Value at Risk (VaR) (see Pelaez and Pelaez, International Financial Architecture (2005), 106-12, 289-92) of the Chief Investment Office (CIO) is estimated at $186 million on Mar 31, 2012. According to form 10-Q (http://investor.shareholder.com/jpmorganchase/secfiling.cfm?filingID=19617-12-213, page 73):
“VaR is calculated using a one day time horizon and an expected tail-loss methodology, and approximates a 95% confidence level. This means that, assuming current changes in market values are consistent with the historical changes used in the simulation, the Firm would expect to incur losses greater than that predicted by VaR estimates five times in every 100 trading days, or about 12 to 13 times a year.”
The CIO at JPMorgan Chase engages in risk management (http://investor.shareholder.com/jpmorganchase/secfiling.cfm?filingID=19617-12-213 74):
“Other VaR includes certain positions employed as part of the Firm’s risk management function within the Chief Investment Office (“CIO”) and in the Mortgage Production and Servicing business. CIO VaR includes positions, primarily in debt securities and credit products, used to manage structural and other risks including interest rate, credit and mortgage risks arising from the Firm’s ongoing business activities. Mortgage Production and Servicing VaR includes the Firm’s mortgage pipeline and warehouse loans, MSRs and all related hedges. CIO VaR averaged $129 million for the three months ended March 31, 2012, compared with $60 million for the comparable 2011 period. The increase in CIO average VaR was due to changes in the synthetic credit portfolio held by CIO as part of its management of structural and other risks arising from the Firm's on-going business activities.”
The Basel Committee on Banking Supervision (2011Jun, 42) Basel III capital adequacy framework provides for the use of index CDS as hedges, under specified conditions, for mitigation of counterparty credit risk (CCR). The risk management tool to be used for capital charges is the credit VaR.
JP Morgan Chase should maintain its traditional excellence in risk management. There are no evident risks to financial markets and the overall economy from the hedging losses of JP Morgan Chase. Parallels with this hedging loss and the causes of the dollar/credit crisis and global recession are misleading. The origins of the financial crisis and global recession are quite different. 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.”
Christopher Bjork and Jonathan House, writing on “Spain to take large stake in Bankia,” on May 9, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702304203604577394183882451046.html?mod=WSJ_hps_sections_markets), inform on the basis of sources that the government of Spain will take a position of 45 percent of the parent company of Bankia, which is the country’s third largest banks. The government of Spain would provide €10 billion to Bankia in exchange for convertible bonds that can be converted into equity under stipulated conditions. Jonathan House, Christopher Bjork and Sara Schaefer Muñoz, writing on “Spain tries a new cleanup,” on May 11, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702304203604577397951697148154.html?mod=WSJ_hp_LEFTWhatsNewsCollection), inform that the government Spain will require an increase in provisions of banks for potential losses by another €30 billion, or about $38.81 billion, and to accelerate sale of dubious assets. There are doubts if the value is sufficient. The credit standing of Spain may be further imperiled if the country is forced into bank nationalizations or absorptions of bad loans by the government. There is troubled history of government ownership and control of banks (Pelaez and Pelaez, Regulation of Banks and Finance: Theory and Policy after the Credit Crisis (2009b), 227-9; Pelaez 1975, Pelaez and Suzigan 1981, following Cameron 1961, 1967, 1972). Christopher Bjork and Jonathan House, writing on “Spanish banks’ ECB borrowing hits high,” on Apr 13, published by the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702304356604577341133498311916.html?mod=WSJ_hp_LEFTWhatsNewsCollection), analyze the impact on valuations of risk financial assets from new data on Spanish bank borrowing. The Bank of Spain, as quoted by Bjork and House, provided information on average Spanish bank borrowing from the European Central Bank increasing from €169.85 billion in Feb to €316.3 billion in Mar, or USD 417.10 billion, which are substantially higher than €106.3 billion before long-term refinancing operations (LTRO). Spain borrowed 28 percent of lending of €1.1 trillion by the ECB to banks in the euro zone. A crucial fact provided by Bjork and House is that Spanish banks devoted €40.6 billion of their assigned LTROs to buying Spanish government debt, which is equivalent to one half of the needs of Spain in 2012. LTROs are effectively a bailout of Spain in which the European Central Bank (ECB) is taking credit risks in contrast with mostly rate risks in quantitative easing by the Fed.
Economic and financial risks in the euro area are increasingly being dominated by analytical and political disagreement on conflicts of fiscal adjustment, financial stability, economic growth and employment. Political development is beginning to push for alternative paths of policy. Blanchard (2012WEOApr) and Draghi (2012May3) provide analysis of appropriate directions of policy.
Blanchard (2012WEOApr) finds that interest rates close to zero in advanced economies have not induced higher economic growth because of two main factors—fiscal consolidation and deleveraging—that restrict economic growth in the short-term. First, Blanchard (2012WEOApr, XIII) finds that assuming a multiplier of unity of the fiscal deficit on GDP, decrease of the cyclically-adjusted deficit of advanced economies by 1 percent would reduce economic growth by one percentage point. Second, deleveraging by banks, occurring mainly in Europe, tightens credit supply with similar reduction of euro area economic growth by one percentage point in 2012. The baseline of the World Economic Outlook (WEO) of the IMF (2012WEOApr) for Apr 2012 incorporates both effects, which results in weak economic growth, in particular in Europe, and prolonged unemployment. An important analysis by Blanchard (2012WEOApr, XIII) is that “financial uncertainty, together with sharp shifts in risk appetite, has led to volatile capital flows.” Blanchard (2012WEOApr) still finds that the greatest vulnerability is another profound crisis in Europe (ECB). Crisis prevention should buttress the resilience of affected countries during those shifts in risk appetite. The role of the enhanced firewall of the IMF, European Union (EU) and European Central Bank is gaining time during which countries could engage in fiscal consolidation and structural reforms that would diminish the shifts in risk appetite, preventing devastating effects of financial crises. Volatility in capital flows is equivalent to volatility of valuations of risk financial assets. The challenge to the policy mix consists in balancing the adverse short-term effects of fiscal consolidation and deleveraging with the beneficial long-term effects of eliminating the vulnerability to shocks of risk aversion. Blanchard (2012WEOApr) finds that policy should seek short-term credibility while implementing measures that restrict the path of expenditures together with simultaneous development of institutions and rules that constrain deficits and spending in the future. There is similar policy challenge in deleveraging banks, which is required for sound lending institutions, but without causing an adverse credit crunch. Advanced economies face a tough policy challenge of increasing demand and potential growth.
The President of the European Central Bank (ECB) Mario Draghi (2012May3) also outlines the appropriate policy mix for successful adjustment:
“It is of utmost importance to ensure fiscal sustainability and sustainable growth in the euro area. Most euro area countries made good progress in terms of fiscal consolidation in 2011. While the necessary comprehensive fiscal adjustment is weighing on near-term economic growth, its successful implementation will contribute to the sustainability of public finances and thereby to the lowering of sovereign risk premia. In an environment of enhanced confidence in fiscal balances, private sector activity should also be fostered, supporting private investment and medium-term growth.
At the same time, together with fiscal consolidation, growth and growth potential in the euro area need to be enhanced by decisive structural reforms. In this context, facilitating entrepreneurial activities, the start-up of new firms and job creation is crucial. Policies aimed at enhancing competition in product markets and increasing the wage and employment adjustment capacity of firms will foster innovation, promote job creation and boost longer-term growth prospects. Reforms in these areas are particularly important for countries which have suffered significant losses in cost competitiveness and need to stimulate productivity and improve trade performance.
In this context, let me make a few remarks on the adjustment process within the euro area. As we know from the experience of other large currency areas, regional divergences in economic developments are a normal feature. However, considerable imbalances have accumulated in the last decade in several euro area countries and they are now in the process of being corrected.
As concerns the monetary policy stance of the ECB, it has to be focused on the euro area. Our primary objective remains to maintain price stability over the medium term. This is the best contribution of monetary policy to fostering growth and job creation in the euro area.
Addressing divergences among individual euro area countries is the task of national governments. They must undertake determined policy actions to address major imbalances and vulnerabilities in the fiscal, financial and structural domains. We note that progress is being made in many countries, but several governments need to be more ambitious. Ensuring sound fiscal balances, financial stability and competitiveness in all euro area countries is in our common interest.”
Economic policy during the debt crisis of 1983 may be useful in analyzing the options of the euro area. Brazil successfully combined fiscal consolidation, structural reforms to eliminate subsidies and devaluation to parity. Brazil’s terms of trade, or export prices relative to import prices, deteriorated by 47 percent from 1977 to 1983 (Pelaez 1986, 46). Table III-1A provides selected economic indicators of the economy of Brazil from 1970 to 1985. In 1983, Brazil’s inflation was 164.9 percent, GDP fell 3.2 percent, idle capacity in manufacturing reached 24.0 percent and Brazil had an unsustainable foreign debt. US money center banks would have had negative capital if loans to emerging countries could have been marked according to loss given default and probability of default (for credit risk models see Pelaez and Pelaez (2005), International Financial Architecture, 134-54). Brazil’s current account of the balance of payments shrank from $16,310 million in 1982 to $6,837 million in 1983 because of the abrupt cessation of foreign capital inflows with resulting contraction of Brazil’s GDP by 3.2 percent. An important part of adjustment consisted of agile coordination of domestic production to cushion the impact of drastic reduction in imports. In 1984, Brazil had a surplus of $45 million in current account, the economy grew at 4.5 percent and inflation was stabilized at 232.9 percent.
Table III-1A, Brazil, Selected Economic Indicators 1970-1985
| Inflation ∆% | GDP Growth ∆% | Idle Capacity in MFG % | BOP Current Account USD MM | |
| 1985 | 223.4 | 7.4 | 19.8 | -630 |
| 1984 | 232.9 | 4.5 | 22.6 | 45 |
| 1983 | 164.9 | -3.2 | 24.0 | -6,837 |
| 1982 | 94.0 | 0.9 | 15.2 | -16,310 |
| 1981 | 113.0 | -1.6 | 12.3 | -11,374 |
| 1980 | 109.2 | 7.2 | 3.5 | -12,886 |
| 1979 | 55.4 | 6.4 | 4.1 | -10,742 |
| 1978 | 38.9 | 5.0 | 3.3 | -6,990 |
| 1977 | 40.6 | 5.7 | 3.2 | -4,037 |
| 1976 | 40.4 | 9.7 | 0.0 | -6,013 |
| 1975 | 27.8 | 5.4 | 3.0 | -6,711 |
| 1974 | 29.1 | 9.7 | 0.1 | -7,122 |
| 1973 | 15.4 | 13.6 | 0.3 | -1,688 |
| 1972 | 17.7 | 11.1 | 6.5 | -1,489 |
| 1971 | 21.5 | 12.0 | 9.8 | -1,307 |
| 1970 | 19.3 | 8.8 | 12.2 | -562 |
Source: Carlos 21.5Manuel Pelaez, O Cruzado e o Austral: São Paulo, Editora Atlas, 1986, 86.
Chart III-1 provides the tortuous Phillips Circuit of Brazil from 1963 to 1987. There were no reliable consumer price index and unemployment data in Brazil for that period. Chart III-1 used the more reliable indicator of inflation, the wholesale price index, and idle capacity of manufacturing as a proxy of unemployment in large urban centers.
©Carlos Manuel Pelaez, O cruzado e o austral. São Paulo: Editora Atlas, 1986, pages 94-5. Reprinted in: Brazil. Tomorrow’s Italy, The Economist, 17-23 January 1987, page 25.
A key to success in stabilizing an economy with significant risk aversion is finding parity of internal and external interest rates. Brazil implemented fiscal consolidation and reforms that are advisable in explosive foreign debt environments. In addition, Brazil had the capacity to find parity in external and internal interest rates to prevent capital flight and disruption of balance sheets (for analysis of balance sheets, interest rates, indexing, devaluation, financial instruments and asset/liability management in that period see Pelaez and Pelaez (2007), The Global Recession Risk: Dollar Devaluation and the World Economy, 178-87). Table III-1B provides monthly percentage changes of inflation, devaluation and indexing and the monthly percent overnight interest rate. Parity was attained by means of a simple inequality:
Cost of Domestic Loan ≥ Cost of Foreign Loan
This ordering was attained in practice by setting the domestic interest rate of the overnight interest rate plus spread higher than indexing of government securities with lower spread than loans in turn higher than devaluation plus spread of foreign loans. Interest parity required equality of inflation, devaluation and indexing. Brazil devalued the cruzeiro by 30 percent in 1983 because the depreciation of the German mark DM relative to the USD had eroded the competitiveness of Brazil’s products in Germany and in competition with German goods worldwide. The database of the Board of Governors of the Federal Reserve System quotes DM 1.7829/USD on Mar 3 1980 and DM 2.4425/USD on Mar 15, 1983 (http://www.federalreserve.gov/releases/h10/hist/dat89_ge.htm) for devaluation of 37.0 percent. Parity of costs and rates of domestic and foreign loans and assets required ensuring that there would not be appreciation of the exchange rate, inducing capital flight in expectation of future devaluation that would have reversed stabilization. One of the main problems of adjustment of members of the euro area with high debts is that they cannot adjust the exchange rate because of the common euro currency. This is not an argument in favor of breaking the euro area because there would be also major problems of adjustment such as exiting the euro in favor of a new Drachma in the case of Greece. Another hurdle of adjustment in the euro area is that Brazil could have moved swiftly to adjust its economy in 1983 but the euro area has major sovereignty and distribution of taxation hurdles in moving rapidly.
Table III-1B, Brazil, Inflation, Devaluation, Overnight Interest Rate and Indexing, Percent Per Month
| 1984 | Inflation IGP ∆% | Devaluation ∆% | Overnight Interest Rate % | Indexing ∆% |
| Jan | 9.8 | 9.8 | 10.0 | 9.8 |
| Feb | 12.3 | 12.3 | 12.2 | 12.3 |
| Mar | 10.0 | 10.1 | 11.3 | 10.0 |
| Apr | 8.9 | 8.8 | 10.1 | 8.9 |
| May | 8.9 | 8.9 | 9.8 | 8.9 |
| Jun | 9.2 | 9.2 | 10.2 | 9.2 |
| Jul | 10.3 | 10.2 | 11.9 | 10.3 |
| Aug | 10.6 | 10.6 | 11.0 | 10.6 |
| Sep | 10.5 | 10.5 | 11.9 | 10.5 |
| Oct | 12.6 | 12.6 | 12.9 | 12.6 |
| Nov | 9.9 | 9.9 | 10.9 | 9.9 |
| Dec | 10.5 | 10.5 | 11.5 | 10.5 |
Source: Carlos Manuel Pelaez, O Cruzado e o Austral: São Paulo, Editora Atlas, 1986, 86.
Spain continues to drive euro area credit risk with hurdles in adjusting its high fiscal deficit, domestic economic recession, high unemployment and unresolved bank balance sheets. Spain’s National Statistics Institute, Instituto Nacional de Estadística (INE), released on Apr 27 its “Economically Active Population Survey” for IQ2012 (http://www.ine.es/en/daco/daco42/daco4211/epa0112_en.pdf). INE’s summary of the survey is as follows (http://www.ine.es/en/daco/daco42/daco4211/epa0112_en.pdf):
“ Employment in the first quarter of 2012 registers a decrease of 374,300 persons, reaching a total of 17,433,200 employed persons. The interannual employment variation rate stands at –3.96%.
The economically active population drops by 8,400 persons this quarter. The number of unemployed persons increases by 365,900 persons, the total number thus standing at 5,639,500.
The unemployment rate grows 1.59 points, standing at 24.44%. In turn, the
activity rate remains at 59.94%.
The loss of employment is almost three times higher among men (278,300 less) than among women (96,000 less). Conversely, the loss of employment increases almost the same between men and women.
All sectors record a reduction in the number of employed persons this quarter.
Wage-earners with a permanent contract decrease by 138,400, and wage earners with a temporary contract do so by 279,600.
The number of households with all of their active members unemployed increases
by 153,400 this quarter, standing at 1,728,400.
By Autonomous Community, the unemployment rate fluctuates between 13.55% in País Vasco and 33.17% in Andalucía. The activity rate fluctuates between 51.33%, recorded in Principado de Asturias, and 64.77%, registered in Illes Balears.
Employment registers its greatest decreases in Andalucia, Cataluña and Comunitat Valenciana, and the greatest decrease in unemployment. Comunidad de Madrid was the only Autonomous Community that registers an increase in employment. The unemployment increases in all Autonomous Communities.”
The Bank of Spain released on Apr 18 new worrisome data on delinquent credit in Spain’s credit institutions (http://www.bde.es/webbde/es/secciones/prensa/Agenda/Datos_de_credit_c62379ebaa85631.html). The aggregate balance sheet of institutions supervised by the Bank of Spain registered total credit of €1,508,626 million in 2006 with delinquent credit of €10,859 million or 0.7 percent. The latest available data for Feb 2012 registers total credit of €1,763,312 million with delinquent credit of €143,815 million or 8.2 percent. Total credit has contracted from a peak of €1,869,882 million in 2008 to €1,763,313 on Feb 2012 or by 5.7 percent. Delinquent credit has risen from €10,859 million in 2006 to €143,815 million in Feb 2012 or by 1224 percent. The credit standing of Spain may be further imperiled if the country is forced into bank nationalizations or absorptions of bad loans by the government. There is troubled history of government ownership and control of banks (Pelaez and Pelaez, Regulation of Banks and Finance: Theory and Policy after the Credit Crisis (2009b), 227-9; Pelaez 1975, Pelaez and Suzigan 1981, following Cameron 1961, 1967, 1972). Christopher Bjork and Jonathan House, writing on “Spanish banks’ ECB borrowing hits high,” on Apr 13, published by the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702304356604577341133498311916.html?mod=WSJ_hp_LEFTWhatsNewsCollection), analyze the impact on valuations of risk financial assets from new data on Spanish bank borrowing. The Bank of Spain, as quoted by Bjork and House, provided information on average Spanish bank borrowing from the European Central Bank increasing from €169.85 billion in Feb to €316.3 billion in Mar, or USD 417.10 billion, which are substantially higher than €106.3 billion before long-term refinancing operations (LTRO). Spain borrowed 28 percent of lending of €1.1 trillion by the ECB to banks in the euro zone. A crucial fact provided by Bjork and House is that Spanish banks devoted €40.6 billion of their assigned LTROs to buying Spanish government debt, which is equivalent to one half of the needs of Spain in 2012. LTROs are effectively a bailout of Spain in which the European Central Bank (ECB) is taking credit risks in contrast with mostly rate risks in quantitative easing by the Fed.
A critical development in the resolution of the European debt crisis is the increase in available resources of the IMF announced in a joint statement of the IMFC and the Group of 20 Finance Ministers and Central Bank Governors (IMFC 2012Apr20):
“There are firm commitments to increase resources made available to the IMF by over $430 billion in addition to the quota increase under the 2010 reform. These resources will be available for the whole membership of the IMF, and not earmarked for any particular region.”
Resources are not earmarked for the European debt crisis but it is the most threatening current vulnerability in the world economy.
The JPY reversed recent depreciation. There was mild depreciating 0.1 percent during the week of May 11 but the JPY is strong as a result of risk aversion. Japan’s has not been very successful in the past in foreign exchange interventions (Pelaez and Pelaez, The Global Recession Risk (2007), 107-9). Japan is currently combining unconventional monetary policy and exchange intervention. The Policy Board of the Bank of Japan decided at its meeting on Apr 27, 2012 to enhance monetary easing as follows (http://www.boj.or.jp/en/announcements/release_2012/k120427a.pdf):
“1. At the Monetary Policy Meeting held today, the Policy Board of the Bank of Japan made the following decisions, by a unanimous vote, regarding the Asset Purchase Program (hereafter referred to as "the Program").
(1) The Bank decided to increase the total size of the Program by about 5 trillion yen, from about 65 trillion yen to about 70 trillion yen, with the following changes in its composition.
(a) An increase in the purchase of Japanese government bonds (JGBs) by about 10 trillion yen
(b) An increase in the purchases of exchange-traded funds (ETFs) and Japan real estate investment trusts (J-REITs) by about 200 billion yen and 10 billion yen, respectively
(c) A reduction in the maximum outstanding amount of the Bank's fixed-rate funds-supplying operation against pooled collateral with a six-month term, by about 5 trillion yen, taking into account the recent episodes of undersubscription
(2) With the aim of smoothly conducting the large-scale purchases after today's increase and encouraging a decline in longer-term interest rates effectively, the Bank decided to extend the remaining maturity of JGBs to be purchased under the Program from "one to two years" to "one to three years." It also decided to extend the remaining maturity of corporate bonds to be purchased under the Program just as is the case of JGBs.
(3) The Bank decided to increase the outstanding amount of the Program to about 70 trillion yen by around end-June 2013, while maintaining the existing schedule of increasing the outstanding amount of the Program to about 65 trillion yen by around end-2012.”
The Policy Board of the Bank of Japan decided at its meeting on April 10, 2010 to continue “powerful easing” (http://www.boj.or.jp/en/announcements/release_2012/k120410a.pdf 2):
“The Bank recognizes that Japan's economy faces the critical challenge of overcoming deflation and returning to a sustainable growth path with price stability. The goal of overcoming deflation will be achieved both through efforts to strengthen the economy's growth potential and support from the financial side. With this in mind, the Bank will pursue powerful monetary easing, and will support private financial institutions in their efforts to strengthen the foundations for Japan's economic growth via the fund-provisioning measure to support strengthening the foundations for economic growth. At today's meeting, as shown in the Attachment, the Bank established detailed rules for a new U.S. dollar lending arrangement equivalent to 1 trillion yen, of which a preliminary outline was released at the previous meeting in March.”
The Policy Board of the Bank of Japan decided three important measures of enhancing monetary easing at the meeting held on Feb 14, 2012 (Bank of Japan 2012EME, 2012PSG and 2012APP). First, the Bank of Japan (2012Feb14EME, 2012Feb14PSG) adopted a “price stability goal” for the “medium term” of 2 percent of the “year-on-year rate of change of the CPI” with the immediate goal of inflation of 1 percent. Japan’s CPI inflation in the 12 months ending in Dec was minus 0.2 percent. Second, the Bank of Japan (2012Feb14EME, 1-2) will conduct “virtually zero interest rate policy” by maintaining “the uncollateralized overnight call rate at around 0 to 0.1 percent.” Third, the Bank of Japan (20012Feb13EME, 2014Feb14APP) is increasing the size of its quantitative easing:
“The Bank increases the total size of the Asset Purchase Program by about 10 trillion yen, from about 55 trillion yen to about 65 trillion yen. The increase in the Program is earmarked for the purchase of Japanese government bonds. By fully implementing the Program including the additional expansion decided today, by the end of 2012, the amount outstanding of the Program will be increased by about 22 trillion yen from the current level of around 43 trillion yen.”
IIIB Appendix on Safe Haven Currencies analyzes the burden on the Japanese economy of yen appreciation. Policy rates close to zero by major central banks in the world together with quantitative easing tend to depreciate currencies. Monetary policy is an indirect form of currency intervention.
The Swiss franc depreciated another 1.3 percent in the week of May 11 to CHF 0.9299/USD relative to the dollar and remained unchanged relative to the euro at CHF 1.2011/EUR, as shown in Table III-1. The important event was appreciation of 0.3 percent by Apr 6 relative to the euro to the very bottom of the exchange rate floor at CHF 1.2009/EUR. William L. Watts, writing on “Euro weakness triggers Swissie showdown,” on Apr 5, published by MarketWatch (http://www.marketwatch.com/story/euro-weakness-triggers-swissie-showdown-2012-04-05), quotes exchange strategists claiming that at point on Apr 5 the Swiss franc traded at CHF 1.1990/EUR. Some participants believe that there was intervention by the Swiss National Bank to defend the floor of CHF `1.2000/EUR. The Australian dollar appreciated 0.1 percent to USD 1.0378/AUD by Apr 20 because of unfavorable environment for carry trades. The AUD is considered a carry trade commodity currency.
Risk aversion is captured by flight of investors from risk financial assets to the government securities of the US and Germany. Increasing aversion is captured by decrease of the yield of the ten-year Treasury. As shown in past updates of Table III-1, the ten-year Treasury yield fell from 2.234 percent on Mar 23 to 2.214 percent on Mar 30, collapsing to 2.058 percent on Apr 6 after the employment report and declining further to 1.987 percent on Apr 13, 1.959 percent on Apr 20 and 1.931 percent on Apr 27 because of increasing risk aversion. Elections in Europe and the weak employment report in Section I motivated further decline of the 10-year yield to 1.876 on May 4 with deterioration in Spain causing further decline to 1.845 percent. The ten-year Treasury yield is still at a level well below consumer price inflation of 2.7 percent in the 12 months ending in Mar (see subsection IB United States Inflation at http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html). Treasury securities continue to be safe haven for investors fearing risk but with concentration in shorter maturities such as the two-year Treasury. As shown in past updates of Table III-1, the two-year Treasury yield fell marginally from 0.35 percent on Mar 23 to 0.335 percent on Mar 30 and then to 0.31 percent on Apr 6 and 0.27 percent on Apr 13, remaining almost unchanged at 0.268 percent on Apr 20 and 0.26 percent on Apr 27, virtually unchanged at 0.256 percent on May 4 and 0.248 on May 11. Investors are willing to sacrifice yield relative to inflation in defensive actions to avoid turbulence in valuations of risk financial assets but may be managing duration more carefully. During the financial panic of Sep 2008, funds moved away from risk exposures to government securities. The latest statement of the Federal Open Market Committee (FOMC) on Apr 25, 2012 does not have sufficient changes suggesting that it contributed to the rise in Treasury yields (http://www.federalreserve.gov/newsevents/press/monetary/20120425a.htm). The statement continues to consider inflation low, unemployment high and growth at a moderate pace. Because of the “slack” in the economy, the FOMC anticipates maintaining the zero interest rate policy until 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20120425a.htm):
“In particular, the Committee decided today to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that economic conditions--including low rates of resource utilization and a subdued outlook for inflation over the medium run--are likely to warrant exceptionally low levels for the federal funds rate at least through late 2014.”
A similar risk aversion phenomenon occurred in Germany. Eurostat confirmed euro zone CPI inflation is at 2.7 percent for the 12 months ending in Mar 2012 but jumping 1.3 percent in the month of Mar (http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-17042012-AP/EN/2-17042012-AP-EN.PDF See Tables IV-4 through IV-7 at http://cmpassocregulationblog.blogspot.com/2012/04/imf-view-of-world-economy-and-finance.html) but the yield of the two-year German government bond fell from 0.23 percent on Mar 23 to 0.21 percent on Mar 30, 0.14 percent on Apr 6 and 0.13 percent on Apr 13 with 0.14 percent on Apr 20 and 0.10 percent on Apr 27, falling further to 0.08 percent on May 4 and 0.09 percent on May 11, while the yield of the ten-year German government bond fell from 1.87 on Mar 23 to 1.79 percent on Mar 30 and then to 1.74 on Apr 6 and also on Apr 13 with 1.71 percent on Apr 20 and 1.70 percent on Apr 27, as shown in Table III-1 and past updates. On May 4, the 10-year yield of Germany fell further to 1.58 percent and then 1.52 percent on May 11. Safety overrides inflation-adjusted yield but there could be duration aversion. Turbulence has also affected the market for German sovereign bonds.
Equity indexes in Table III-1 were mostly weak during the week of May 11. Germany’s Dax increased 0.3 percent while DJIA fell 1.7 percent in the week of May 11 and Dow Global dropped 2.1 percent. Japan’s Nikkei Average interrupted recent increases with decline of 3.9 percent in the week of Apr 6, decline of 0.5 percent in the week of Apr 13 and declines of 0.8 percent in the week of Apr 20, 0.4 percent in the week of Apr 27 and 1.5 percent in the week of May 4. The Nikkei Average dropped 4.6 percent in the week of Apr 11. Dow Asia Pacific dropped 4.3 percent in the week of May 11 while Shanghai’s composite dropped 2.3 percent.
Commodities fell during the week of May 4. The DJ UBS Commodities Index decreased 1.7 percent. WTI dropped 2.9 percent and Brent decreased 1.1 percent. Gold fell 3.8 percent.
Risk aversion during the week of Mar 2, 2012, was dominated by the long-term refinancing operations (LTRO) of the European Central Bank. LTROs and related principles are analyzed in subsection IIID Appendix on European Central Bank Large Scale Lender of Last Resort. First, as analyzed by David Enrich, writing on “ECB allots €529.5 billion in long-term refinancing operations,” published on Feb 29, 2012 by the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970203986604577252803223310964.html?mod=WSJ_hp_LEFTWhatsNewsCollection), the ECB provided a second round of three-year loans at 1.0 percent to about 800 banks. The earlier round provided €489 billion to more than 500 banks. Second, the ECB sets the fixed-rate for main refinancing operations at 1.00 percent and the overnight deposit facility at 0.25 percent (http://www.ecb.int/home/html/index.en.html) for negative spread of 75 basis points. That is, if a bank borrows at 1.0 percent for three years through the LTRO and deposits overnight at the ECB, it incurs negative spread of 75 basis points. An alternative allocation could be to lend for a positive spread to other banks. Richard Milne, writing on “Banks deposit record cash with ECB,” on Mar 2, 2012, published in the Financial Times (http://www.ft.com/intl/cms/s/0/9798fd36-644a-11e1-b30e-00144feabdc0.html#axzz1nxeicB6H), provides important information and analysis that banks deposited a record €776.9 billion at the ECB on Fri Mar 2 at interest receipt of 0.25 percent, just two days after receiving €529.5 billion of LTRO loans at interest cost of 1.0 percent. The main issue here is whether there is ongoing perceptions of high risks in counterparties in financial transactions that froze credit markets in 2008 (see Pelaez and Pelaez, Regulation of Banks and Finance (2009a), 57-60, 217-27, Financial Regulation after the Global Recession (2009b), 155-67). Richard Milne and Mary Watkins, writing on “European finance: the leaning tower of perils,” on Mar 27, 2012, published in the Financial Times (http://www.ft.com/intl/cms/s/0/82205f6e-7735-11e1-baf3-00144feab49a.html#axzz1qOqWaqF2), raise concerns that the large volume of LTROs can create future problems for banks and the euro area. An important issue is if the cheap loans at 1 percent for three-year terms finance the carry trade into securities of the governments of banks. Balance sheets of banks may be stressed during future sovereign-credit events. Sam Jones, writing on “ECB liquidity fuels high stakes hedging,” on Apr 4, 2012, published in the Financial Times (http://www.ft.com/intl/cms/s/0/cb74d63a-7e75-11e1-b009-00144feab49a.html#axzz1qyDYxLjS), analyzes unusually high spreads in government bond markets in Europe that could have been caused by LTROs. There has been active relative value arbitrage of these spreads similar to the strategies of Long-Term Capital Management (LTCM) of capturing high spreads in mortgage-backed securities jointly with hedges in Treasury securities (on LTCM see Pelaez and Pelaez, International Financial Architecture (2005), 108-12, 87-9, The Global Recession Risk (2007) 12-3, 102, 176, Globalization and the State, Vol. I (2008a), 59-64).
Table III-1C provides an update of the consolidated financial statement of the Eurosystem. The balance sheet has swollen with the LTROs. Line 5 “Lending to Euro Area Credit Institutions Related to Monetary Policy” increasing from €546,747 million on Dec 31, 2010, to €870,130 million on Dec 28, 2011 and €1,117,090 million on May 4, 2012. The sum of line 5 and line 7 (“Securities of Euro Area Residents Denominated in Euro”) has increased to €1,724,313 million in the statement of May 11.
Table III-1C, Consolidated Financial Statement of the Eurosystem, Million EUR
| Dec 31, 2010 | Dec 28, 2011 | May 4, 2012 | |
| 1 Gold and other Receivables | 367,402 | 419,822 | 432,705 |
| 2 Claims on Non Euro Area Residents Denominated in Foreign Currency | 223,995 | 236,826 | 241,977 |
| 3 Claims on Euro Area Residents Denominated in Foreign Currency | 26,941 | 95,355 | 51,965 |
| 4 Claims on Non-Euro Area Residents Denominated in Euro | 22,592 | 25,982 | 20,108 |
| 5 Lending to Euro Area Credit Institutions Related to Monetary Policy Operations Denominated in Euro | 546,747 | 879,130 | 1,117,090 |
| 6 Other Claims on Euro Area Credit Institutions Denominated in Euro | 45,654 | 94,989 | 204,691 |
| 7 Securities of Euro Area Residents Denominated in Euro | 457,427 | 610,629 | 607,223 |
| 8 General Government Debt Denominated in Euro | 34,954 | 33,928 | 30,589 |
| 9 Other Assets | 278,719 | 336,574 | 253,970 |
| TOTAL ASSETS | 2,004, 432 | 2,733,235 | 2,960,317 |
| Memo Items | |||
| Sum of 5 and 7 | 1,004,174 | 1,489,759 | 1,724,313 |
| Capital and Reserves | 78,143 | 81,481 | 85,545 |
Source: European Central Bank
http://www.ecb.int/press/pr/wfs/2011/html/fs110105.en.html
http://www.ecb.int/press/pr/wfs/2011/html/fs111228.en.html
http://www.ecb.int/press/pr/wfs/2012/html/fs120508.en.html
There is extremely important information in Table VE-9 for the current sovereign risk crisis in the euro zone. Table III-1D provides the structure of regional and country relations of Germany’s exports and imports with newly available data for Mar 2012. German exports to other European Union (EU) members are 57.6 percent of total exports in Mar 2012 and 58.4 percent in Jan-Mar 2012. Exports to the euro area are 38.5 percent in Mar and 39.0 percent in Jan-Mar. Exports to third countries are 42.4 percent of the total in Mar and 41.6 percent in Jan-Mar. There is similar distribution for imports. Economic performance in Germany is closely related to its high competitiveness in world markets. Weakness in the euro zone and the European Union in general could affect the German economy. This may be the major reason for choosing the “fiscal abuse” of the European Central Bank considered by Buiter (2011Oct31) over the breakdown of the euro zone. There is a tough analytical, empirical and forecasting doubt of growth and trade in the euro zone and the world with or without maintenance of the European Monetary Union (EMU) or euro zone. Germany could benefit from depreciation of the euro because of its high share in exports to countries not in the euro zone but breakdown of the euro zone raises doubts on the region’s economic growth that could affect German exports to other member states.
Table III-1D, Germany, Structure of Exports and Imports by Region, € Billions and ∆%
| Mar 2012 | Mar 12-Month | Jan–Mar 2012 € Billions | Jan-Mar 2012/ | |
| Total | 98.9 | 0.7 | 276.1 | 5.8 |
| A. EU | 57.0 % 57.6 | -2.8 | 161.3 % 58.4 | 2.3 |
| Euro Area | 38.1 % 38.5 | -3.6 | 107.7 % 39.0 | 1.1 |
| Non-euro Area | 18.9 % 19.1 | -1.4 | 53.6 % 19.4 | 4.7 |
| B. Third Countries | 41.9 % 42.4 | 6.1 | 114.8 % 41.6 | 11.2 |
| Total Imports | 81.5 | 2.6 | 230.6 | 4.8 |
| C. EU Members | 52.4 % 64.3 | 2.1 | 145.8 % 63.2 | 5.0 |
| Euro Area | 37.0 % 45.4 | 2.3 | 102.4 % 44.4 | 4.7 |
| Non-euro Area | 15.4 % 18.9 | 1.7 | 43.4 % 18.8 | 5.8 |
| D. Third Countries | 29.1 % 35.7 | 3.5 | 84.8 % 36.8 | 4.3 |
Notes: Total Exports = A+B; Total Imports = C+D
Source:
Statistiche Bundesamt Deutschland
IIIB Appendix on Safe Haven Currencies. Safe-haven currencies, such as the Swiss franc (CHF) and the Japanese yen (JPY) have been under threat of appreciation but also remained relatively unchanged. A characteristic of the global recession would be struggle for maintaining competitiveness by policies of regulation, trade and devaluation (Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation War (2008c)). Appreciation of the exchange rate causes two major effects on Japan.
1. Trade. Consider an example with actual data (Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008c), 70-72). The yen traded at JPY 117.69/USD on Apr 2, 2007 and at JPY 102.77/USD on Apr 2, 2008, or appreciation of 12.7 percent. This meant that an export of JPY 10,000 to the US sold at USD 84.97 on Apr 2, 2007 [(JPY 10,000)/(USD 117.69/USD)], rising to USD 97.30 on Apr 2, 2008 [(JPY 10,000)/(JPY 102.77)]. If the goods sold by Japan were invoiced worldwide in dollars, Japanese’s companies would suffer a reduction in profit margins of 12.7 percent required to maintain the same dollar price. An export at cost of JPY 10,000 would only bring JPY 8,732 when converted at JPY 102.77 to maintain the price of USD 84.97 (USD 84.97 x JPY 102.77/USD). If profit margins were already tight, Japan would be uncompetitive and lose revenue and market share. The pain of Japan from dollar devaluation is illustrated by Table 58 in the Nov 6 comment of this blog (http://cmpassocregulationblog.blogspot.com/2011/10/slow-growth-driven-by-reducing-savings.html): The yen traded at JPY 110.19/USD on Aug 18, 2008 and at JPY 75.812/USD on Oct 28, 2011, for cumulative appreciation of 31.2 percent. Cumulative appreciation from Sep 15, 2010 (JPY 83.07/USD) to Oct 28, 2011 (JPY 75.812) was 8.7 percent. The pain of Japan from dollar devaluation continues as illustrated by Table VI-6 in Section VII Valuation of Risk Financial Assets: The yen traded at JPY 110.19/USD on Aug 18, 2008 and at JPY 78.08/USD on Dec 23, 2011, for cumulative appreciation of 29.1 percent. Cumulative appreciation from Sep 15, 2010 (JPY 83.07/USD) to Dec 23, 2011 (JPY 78.08) was 6.0 percent.
2. Foreign Earnings and Investment. Consider the case of a Japanese company receiving earnings from investment overseas. Accounting the earnings and investment in the books in Japan would also result in a loss of 12.7 percent. Accounting would show fewer yen for investment and earnings overseas.
There is a point of explosion of patience with dollar devaluation and domestic currency appreciation. Andrew Monahan, writing on “Japan intervenes on yen to cap sharp rise,” on Oct 31, 2011, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204528204577009152325076454.html?mod=WSJPRO_hpp_MIDDLETopStories), analyzes the intervention of the Bank of Japan, at request of the Ministry of Finance, on Oct 31, 2011. Traders consulted by Monahan estimate that the Bank of Japan sold JPY 7 trillion, about $92.31 billion, against the dollar, exceeding the JPY 4.5 trillion on Aug 4, 2011. The intervention caused an increase of the yen rate to JPY 79.55/USD relative to earlier trading at a low of JPY 75.31/USD. The JPY appreciated to JPY76.88/USD by Fri Nov 18 for cumulative appreciation of 3.4 percent from JPY 79.55 just after the intervention. The JPY appreciated another 0.3 percent in the week of Nov 18 but depreciated 1.1 percent in the week of Nov 25. There was mild depreciation of 0.3 percent in the week of Dec 2 that was followed by appreciation of 0.4 percent in the week of Dec 9. The JPY was virtually unchanged in the week of Dec 16 with depreciation of 0.1 percent but depreciated by 0.5 percent in the week of Dec 23, appreciating by 1.5 percent in the week of Dec 30. Historically, interventions in yen currency markets have been unsuccessful (Pelaez and Pelaez, The Global Recession Risk (2007), 107-109). Interventions are even more difficult currently with daily trading of some $4 trillion in world currency markets. Risk aversion with zero interest rates in the US diverts hot capital movements toward safe-haven currencies such as Japan, causing appreciation of the yen. Mitsuru Obe, writing on Nov 25, on “Japanese government bonds tumble,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204452104577060231493070676.html?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes the increase in yields of the Japanese government bond with 10 year maturity to a high for one month of 1.025 percent at the close of market on Nov 25. Thin markets in after-hours trading may have played an important role in this increase in yield but there may have been an effect of a dreaded reduction in positions of bonds by banks under pressure of reducing assets. The report on Japan sustainability by the IMF (2011JSRNov23, 2), analyzes how rising yields could threaten Japan:
· “As evident from recent developments, market sentiment toward sovereigns with unsustainably large fiscal imbalances can shift abruptly, with adverse effects on debt dynamics. Should JGB yields increase, they could initiate an adverse feedback loop from rising yields to deteriorating confidence, diminishing policy space, and a contracting real economy.
· Higher yields could result in a withdrawal of liquidity from global capital markets, disrupt external positions and, through contagion, put upward pressure on sovereign bond yields elsewhere.”
Exchange rate controls by the Swiss National Bank (SNB) fixing the rate at a minimum of CHF 1.20/EUR (http://www.snb.ch/en/mmr/reference/pre_20110906/source/pre_20110906.en.pdf) has prevented flight of capital into the Swiss franc. The Swiss franc remained unchanged relative to the USD in the week of Dec 23 and appreciated 0.2 percent in the week of Dec 30 relative to the USD and 0.5 percent relative to the euro, as shown in Table II-1. Risk aversion is evident in the depreciation of the Australian dollar by cumulative 2.5 percent in the week of Fr Dec 16 after no change in the week of Dec 9. In the week of Dec 23, the Australian dollar appreciated 1.9 percent, appreciating another 0.5 percent in the week of Dec 30 as shown in Table II-1. Risk appetite would be revealed by carry trades from zero interest rates in the US and Japan into high yielding currencies such as in Australia with appreciation of the Australian dollar (see Pelaez and Pelaez, Globalization and the State, Vol. II (2008b), 202-4, Pelaez and Pelaez, Government Intervention in Globalization (2008c), 70-4).
IIIC Appendix on Fiscal Compact. There are three types of actions in Europe to steer the euro zone away from the threats of fiscal and banking crises: (1) fiscal compact; (2) enhancement of stabilization tools and resources; and (3) bank capital requirements. The first two consist of agreements by the Euro Area Heads of State and government while the third one consists of measurements and recommendations by the European Banking Authority.
1. Fiscal Compact. The “fiscal compact” consists of (1) conciliation of fiscal policies and budgets within a “fiscal rule”; and (2) establishment of mechanisms of governance, monitoring and enforcement of the fiscal rule.
i. Fiscal Rule. The essence of the fiscal rule is that “general government budgets shall be balanced or in surplus” by compliance of members countries that “the annual structural deficit does not exceed 0.5% of nominal GDP” (European Council 2011Dec9, 3). Individual member states will create “an automatic correction mechanism that shall be triggered in the event of deviation” (European Council 2011Dec9, 3). Member states will define their automatic correction mechanisms following principles proposed by the European Commission. Those member states falling into an “excessive deficit procedure” will provide a detailed plan of structural reforms to correct excessive deficits. The European Council and European Commission will monitor yearly budget plans for consistency with adjustment of excessive deficits. Member states will report in anticipation their debt issuance plans. Deficits in excess of 3 percent of GDP and/or debt in excess of 60 percent of GDP will trigger automatic consequences.
ii. Policy Coordination and Governance. The euro area is committed to following common economic policy. In accordance, “a procedure will be established to ensure that all major economic policy reforms planned by euro area member states will be discussed and coordinated at the level of the euro area, with a view to benchmarking best practices” (European Council 2011Dec9, 5). Governance of the euro area will be strengthened with regular euro summits at least twice yearly.
2. Stabilization Tools and Resources. There are several enhancements to the bailouts of member states.
i. Facilities. The European Financial Stability Facility (EFSF) will use leverage and the European Central Bank as agent of its market operations. The European Stability Mechanism (ESM) or permanent bailout facility will be operational as soon as 90 percent of the capital commitments are ratified by member states. The ESM is planned to begin in Jul 2012.
ii. Financial Resources. The overall ceiling of the EFSF/ESM of €500 billion (USD 670 billion) will be reassessed in Mar 2012. Measures will be taken to maintain “the combined effective lending capacity of EUR 500 billion” (European Council 2011Dec9, 6). Member states will “consider, and confirm within 10 days, the provision of additional resources for the IMF of up to EUR 200 billion (USD 270 billion), in the form of bilateral loans, to ensure that the IMF has adequate resources to deal with the crisis. We are looking forward to parallel contributions from the international community” (European Council 2011Dec9, 6). Matthew Dalton and Matina Stevis, writing on Dec 20, 2011, on “Euro Zone Agrees to New IMF Loans,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204791104577107974167166272.html?mod=WSJPRO_hps_MIDDLESecondNews), inform that at a meeting on Dec 20, finance ministers of the euro-zone developed plans to contribute €150 billion in bilateral loans to the IMF as provided in the agreement of Dec 9. Bailouts “will strictly adhere to the well established IMF principles and practices.” There is a specific statement on private sector involvement and its relation to recent experience: “We clearly reaffirm that the decisions taken on 21 July and 26/27 October concerning Greek debt are unique and exceptional; standardized and identical Collective Action clauses will be included, in such a way as to preserve market liquidity, in the terms and conditions of all new euro government bonds” (European Council 2011Dec9, 6). Will there be again “unique and exceptional” conditions? The ESM is authorized to take emergency decisions with “a qualified majority of 85% in case the Commission and the ECB conclude that an urgent decision related to financial assistance is needed when the financial and economic sustainability of the euro area is threatened” (European Council 2011Dec9, 6).
3. Bank Capital. The European Banking Authority (EBA) finds that European banks have a capital shortfall of €114.7 billion (http://stress-test.eba.europa.eu/capitalexercise/Press%20release%20FINAL.pdf). To avoid credit difficulties, the EBA recommends “that the credit institutions build a temporary capital buffer to reach a 9% Core Tier 1 ratio by 30 June 2012” (http://stress-test.eba.europa.eu/capitalexercise/EBA%20BS%202011%20173%20Recommendation%20FINAL.pdf 6). Patrick Jenkins, Martin Stabe and Stanley Pignal, writing on Dec 9, 2011, on “EU banks slash sovereign holdings,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/a6d2fd4e-228f-11e1-acdc-00144feabdc0.html#axzz1gAlaswcW), analyze the balance sheets of European banks released by the European Banking Authority. They conclude that European banks have reduced their holdings of riskier sovereign debt of countries in Europe by €65 billion from the end of 2010 to Sep 2011. Bankers informed that the European Central Bank and hedge funds acquired those exposures that represent 13 percent of their holdings of debt to Greece, Ireland, Italy, Portugal and Spain, which are down to €513 billion by the end of IIIQ2011.
The members of the European Monetary Union (EMU), or euro area, established the European Financial Stability Facility (EFSF), on May 9, 2010, to (http://www.efsf.europa.eu/about/index.htm):
- “Provide loans to countries in financial difficulties
- Intervene in the debt primary and secondary markets. Intervention in the secondary market will be only on the basis of an ECB analysis recognising the existence of exceptional financial market circumstances and risks to financial stability
- Act on the basis of a precautionary programme
- Finance recapitalisations of financial institutions through loans to governments”
The EFSF will be replaced by the permanent European Stability Mechanism (ESM) in 2013. On Mar 30, 2012, members of the euro area reached an agreement providing for sufficient funding required in rescue programs of members countries facing funding and fiscal difficulties and the transition from the EFSF to the ESM. The agreement of Mar 30, 2012 of the euro area members provides for the following (http://www.consilium.europa.eu/media/1513204/eurogroup_statement_30_march_12.pdf):
· Acceleration of ESM paid-in capital. The acceleration of paid-in capital for the ESM provides for two tranches paid in 2012, in July and Oct; another two tranches in 2013; and a final tranche in the first half of 2014. There could be acceleration of paid-in capital is required to maintain a 15 percent relation of paid-in capital and the outstanding issue of the ESM
· ESM Operation and EFSF transition. ESM will assume all new rescue programs beginning in Jul 2012. EFSF will administer programs begun before initiation of ESM activities. There will be a transition period for the EFSF until mid 2013 in which it can engage in new programs if required to maintain the full lending limit of €500 billion.
· Increase of ESM/EFSF lending limit. The combined ceiling of the ESM and EFSF will be increased to €700 billion to facilitate operation of the transition of the EFSF to the ESM. The ESM lending ceiling will be €500 billion by mid 2013. The combined lending ceiling of the ESM and EFSF will continue to €700 billion
· Prior lending. The bilateral Greek loan facility of €53 billion and €49 billion of the EFSF have been paid-out in supporting programs of countries: “all together the euro area is mobilizing an overall firewall of approximately EUR 800 billion, more than USD 1 trillion” (http://www.consilium.europa.eu/media/1513204/eurogroup_statement_30_march_12.pdf)
· Bilateral IMF contributions. Members of the euro area have made commitments of bilateral contributions to the IMF of €150 billion
A key development in the bailout of Greece is the approval by the Executive Board of the International Monetary Fund (IMF) on Mar 15, 2012, of a new four-year financing in the value of €28 billion to be disbursed in equal quarterly disbursements (http://www.imf.org/external/np/tr/2012/tr031512.htm). The sovereign debt crisis of Europe has moderated significantly with the elimination of immediate default of Greece. New economic and financial risk factors have developed, which are covered in VI Valuation of Risk Financial Assets and V World Economic Slowdown.
IIID Appendix on European Central Bank Large Scale Lender of Last Resort. European Central Bank. The European Central Bank (ECB) has been pressured to assist in the bailouts by acquiring sovereign debts. The ECB has been providing liquidity lines to banks under pressure and has acquired sovereign debts but not in the scale desired by authorities. In an important statement to the European Parliament, the President of the ECB Mario Draghi (2011Dec1) opened the possibility of further ECB actions but after a decisive “fiscal compact:”
“What I believe our economic and monetary union needs is a new fiscal compact – a fundamental restatement of the fiscal rules together with the mutual fiscal commitments that euro area governments have made.
Just as we effectively have a compact that describes the essence of monetary policy – an independent central bank with a single objective of maintaining price stability – so a fiscal compact would enshrine the essence of fiscal rules and the government commitments taken so far, and ensure that the latter become fully credible, individually and collectively.
We might be asked whether a new fiscal compact would be enough to stabilise markets and how a credible longer-term vision can be helpful in the short term. Our answer is that it is definitely the most important element to start restoring credibility.
Other elements might follow, but the sequencing matters. And it is first and foremost important to get a commonly shared fiscal compact right. Confidence works backwards: if there is an anchor in the long term, it is easier to maintain trust in the short term. After all, investors are themselves often taking decisions with a long time horizon, especially with regard to government bonds.
A new fiscal compact would be the most important signal from euro area governments for embarking on a path of comprehensive deepening of economic integration. It would also present a clear trajectory for the future evolution of the euro area, thus framing expectations.”
An important statement of Draghi (2011Dec15) focuses on the role of central banking: “You all know that the statutes of the ECB inherited this important principle and that central bank independence and the credible pursuit of price stability go hand in hand.”
Draghi (2011Dec19) explains measures to ensure “access to funding markets” by euro zone banks:
§ “We have decided on three-year refinancing operations to support the supply of credit to the euro area economy. These measures address the risk that persistent financial markets tensions could affect the capacity of euro area banks to obtain refinancing over longer horizons.
§ Earlier, in October, the Governing Council had already decided to have two more refinancing operations with a maturity of around one year.
§ Also, it was announced then that in all refinancing operations until at least the first half of 2012 all liquidity demand by banks would be fully allotted at fixed rate.
§ Funding via the covered bonds market was also facilitated by the ECB deciding in October to introduce a new Covered Bond Purchase Programme of €40 billion.
§ Funding in US dollar is facilitated by lowering the pricing on the temporary US dollar liquidity swap arrangements.”
Lionel Barber and Ralph Atkins interviewed Mario Draghi on Dec 14 with the transcript published in the Financial Times on Dec 18 (http://www.ft.com/intl/cms/s/0/25d553ec-2972-11e1-a066-00144feabdc0.html#axzz1gzoHXOj6) as “FT interview transcript: Mario Draghi.” A critical question in the interview is if the new measures are a European version of quantitative easing. Draghi analyzes the difference between the measures of the European Central Bank (ECB) and quantitative easing such as in Japan, US and UK:
1. The measures are termed “non-standard” instead of “unconventional.” While quantitative easing attempts to lower the yield of targeted maturities, the three-year facility operates through the “bank channel.” Quantitative easing would not be feasible because the ECB is statutorily prohibited of funding central governments. The ECB would comply with its mandate of medium-term price stability.
2. There is a critical difference in the two programs. Quantitative easing has been used as a form of financial repression known as “directed lending.” For example, the purchase of mortgage-backed securities more recently or the suspension of the auctions of 30-year bonds in response to the contraction early in the 2000s has the clear objective of directing spending to housing. The ECB gives the banks entire discretion on how to use the funding within their risk/return decisions, which could include purchase of government bonds.
The question on the similarity of the ECB three-year lending facility and quantitative easing is quite valid. Tracy Alloway, writing on Oct 10, 2011, on “Investors worry over cheap ECB money side effects,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/d2f87d16-f339-11e0-8383-00144feab49a.html#axzz1hAqMH1vn), analyzes the use of earlier long-term refinancing operations (LTRO) of the ECB. LTROs by the ECB in Jun, Sep and Dec 2009 lent €614 billion at 1 percent. Alloway quotes estimates of Deutsche Bank that banks used €442billion to acquire assets with higher yields. Carry trades developed from LTRO funds at 1 percent into liquid investments at a higher yield to earn highly profitable spreads. Alloway quotes estimates of Morgan Stanley that European debt of GIIPS (Greece, Ireland, Italy, Portugal and Spain) in European bank balance sheets is €700 billion. Tracy Alloway, writing on Dec 21, 2011, on “Demand for ECB loans rises to €489bn,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/d6ddd0ae-2bbd-11e1-98bc-00144feabdc0.html#axzz1hAqMH1vn), informs that European banks borrowed the largest value of €489 billion in all LTROs of the ECB. Tom Fairless and David Cottle, writing on Dec 21, 2011, on “ECB sees record refinancing demand,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204464404577111983838592746.html?mod=WSJPRO_hpp_LEFTTopStories), inform that the first of three operations of the ECB lent €489.19 billion, or $639.96 billion, to 523 banks. Three such LTROs could add to $1.9 trillion, which is not far from the value of quantitative easing in the US of $2.5 trillion. Fairless and Cottle find that there could be renewed hopes that banks could use the LTROs to support euro zone bond markets. It is possible that there could be official moral suasion by governments on banks to increase their holdings of government bonds or at least not to sell existing holdings. Banks are not free to choose assets in evaluation of risk and returns. Floods of cheap money at 1 percent per year induce carry trades to high-risk assets and not necessarily financing of growth with borrowing and lending decisions constrained by shocks of confidence.
The LTROs of the ECB are not very different from the liquidity facilities of the Fed during the financial crisis. Kohn (2009Sep10) finds that the trillions of dollars in facilities provided by the Fed (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-64, Regulation of Banks and Finance (2009b), 224-7) could fall under normal principles of “lender of last resort” of central banks:
“The liquidity measures we took during the financial crisis, although unprecedented in their details, were generally consistent with Bagehot's principles and aimed at short-circuiting these feedback loops. The Federal Reserve lends only against collateral that meets specific quality requirements, and it applies haircuts where appropriate. Beyond the collateral, in many cases we also have recourse to the borrowing institution for repayment. In the case of the TALF, we are backstopped by the Treasury. In addition, the terms and conditions of most of our facilities are designed to be unattractive under normal market conditions, thus preserving borrowers' incentives to obtain funds in the market when markets are operating normally. Apart from a very small number of exceptions involving systemically important institutions, such features have limited the extent to which the Federal Reserve has taken on credit risk, and the overall credit risk involved in our lending during the crisis has been small.
In Ricardo's view, if the collateral had really been good, private institutions would have lent against it. However, as has been recognized since Bagehot, private lenders, acting to protect themselves, typically severely curtail lending during a financial crisis, irrespective of the quality of the available collateral. The central bank--because it is not liquidity constrained and has the infrastructure in place to make loans against a variety of collateral--is well positioned to make those loans in the interest of financial stability, and can make them without taking on significant credit risk, as long as its lending is secured by sound collateral. A key function of the central bank is to lend in such circumstances to contain the crisis and mitigate its effects on the economy.”
The Bagehot (1873) principle is that central banks should provide a safety net, lending to temporarily illiquid but solvent banks and not to insolvent banks (see Cline 2001, 2002; Pelaez and Pelaez, International Financial Architecture (2005), 175-8). Kohn (2009Apr18) characterizes “quantitative easing” as “large scale purchases of assets:”
“Another aspect of our efforts to affect financial conditions has been the extension of our open market operations to large-scale purchases of agency mortgage-backed securities (MBS), agency debt, and longer-term Treasury debt. We initially announced our intention to undertake large-scale asset purchases last November, when the federal funds rate began to approach its zero lower bound and we needed to begin applying stimulus through other channels as the economic contraction deepened. These purchases are intended to reduce intermediate- and longer-term interest rates on mortgages and other credit to households and businesses; those rates influence decisions about investments in long-lived assets like houses, consumer durable goods, and business capital. In ordinary circumstances, the typically quite modest volume of central bank purchases and sales of such assets has only small and temporary effects on their yields. However, the extremely large volume of purchases now underway does appear to have substantially lowered yields. The decline in yields reflects "preferred habitat" behavior, meaning that there is not perfect arbitrage between the yields on longer-term assets and current and expected short-term interest rates. These preferences are likely to be especially strong in current circumstances, so that long-term asset prices rise and yields fall as the Federal Reserve acquires a significant portion of the outstanding stock of securities held by the public.”
Non-standard ECB policy and unconventional Fed policy have a common link in the scale of implementation or policy doses. Direct lending by the central bank to banks is the function “large scale lender of last resort.” If there is moral suasion by governments to coerce banks into increasing their holdings of government bonds, the correct term would be financial repression.
An important additional measure discussed by Draghi (2011Nov19) is relaxation on the collateral pledged by banks in LTROs:
“Some banks’ access to refinancing operations may be restricted by lack of eligible collateral. To overcome this, a temporary expansion of the list of collateral has been decided. Furthermore, the ECB intends to enhance the use of bank loans as collateral in Eurosystem operations. These measures should support bank lending, by increasing the amount of assets on euro area banks’ balance sheets that can be used to obtain central bank refinancing.”
There are collateral concerns about European banks. David Enrich and Sara Schaefer Muñoz, writing on Dec 28, on “European bank worry: collateral,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970203899504577126430202451796.html?mod=WSJPRO_hpp_LEFTTopStories), analyze the strain on bank funding from a squeeze in the availability of high-quality collateral as guarantee in funding. High-quality collateral includes government bonds and investment-grade non-government debt. There could be difficulties in funding for a bank without sufficient available high-quality collateral to offer in guarantee of loans. It is difficult to assess from bank balance sheets the availability of sufficient collateral to support bank funding requirements. There has been erosion in the quality of collateral as a result of the debt crisis and further erosion could occur. Perceptions of counterparty risk among financial institutions worsened the credit/dollar crisis of 2007 to 2009. The banking theory of Diamond and Rajan (2000, 2001a, 2001b) and the model of Diamond Dybvig (1983, 1986) provide the analysis of bank functions that explains the credit crisis of 2007 to 2008 (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 155-7, 48-52, Regulation of Banks and Finance (2009b), 52-66, 217-24). In fact, Rajan (2005, 339-41) anticipated the role of low interest rates in causing a hunt for yields in multiple financial markets from hedge funds to emerging markets and that low interest rates foster illiquidity. Rajan (2005, 341) argued:
“The point, therefore, is that common factors such as low interest rates—potentially caused by accommodative monetary policy—can engender excessive tolerance for risk on both sides of financial transactions.”
A critical function of banks consists of providing transformation services that convert illiquid risky loans and investment that the bank monitors into immediate liquidity such as unmonitored demand deposits. Credit in financial markets consists of the transformation of asset-backed securities (SRP) constructed with monitoring by financial institutions into unmonitored immediate liquidity by sale and repurchase agreements (SRP). In the financial crisis financial institutions distrusted the quality of their own balance sheets and those of their counterparties in SRPs. The financing counterparty distrusted that the financed counterparty would not repurchase the assets pledged in the SRP that could collapse in value below the financing provided. A critical problem was the unwillingness of banks to lend to each other in unsecured short-term loans. Emse Bartha, writing on Dec 28, on “Deposits at ECB hit high,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204720204577125913779446088.html?mod=WSJ_hp_LEFTWhatsNewsCollection), informs that banks deposited €453.034 billion, or $589.72 billion, at the ECB on Dec 28, which is a record high in two consecutive days. The deposit facility is typically used by banks when they do prefer not to extend unsecured loans to other banks. In addition, banks borrowed €6.225 billion from the overnight facility on Dec 28, when in normal times only a few hundred million euro are borrowed. The collateral issues and the possible increase in counterparty risk occurred a week after large-scale lender of last resort by the ECB in the value of €489 billion in the prior week. The ECB may need to extend its lender of last resort operations.
The financial reform of the United States around the proposal of a national bank by Alexander Hamilton (1780) to develop the money economy with specialization away from the barter economy is credited with creating the financial system that brought prosperity over a long period (see Pelaez 2008). Continuing growth and prosperity together with sound financial management earned the US dollar the role as reserve currency and the AAA rating of its Treasury securities. McKinnon (2011Dec18) analyzes the resolution of the European debt crisis by comparison with the reform of Alexander Hamilton. Northern states of the US had financed the revolutionary war with the issue of paper notes that were at risk of default by 1890. Alexander Hamilton proposed the purchase of the states’ paper notes by the Federal government without haircuts. McKinnon (2011Dec18) describes the conflicts before passing the assumption bill in 1790 for federal absorption of the debts of states. Other elements in the Hamilton reform consisted of creation of a market for US Treasury bonds by their use as paid-in capital in the First Bank of the United States. McKinnon (2011Dec18) finds growth of intermediation in the US by the branching of the First Bank of the United States throughout several states, accepting deposits to provide commercial short-term credit. The reform consolidated the union of states, fiscal credibility for the union and financial intermediation required for growth. The reform also introduced low tariffs and an excise tax on whisky to service the interest on the federal debt. Trade relations among members of the euro zone are highly important to economic activity. There are two lessons drawn by McKinnon (2011Dec18) from the experience of Hamilton for the euro zone currently. (1) The reform of Hamilton included new taxes for the assumption of debts of states with concrete provisions for their credibility. (2) Commercial lending was consolidated with a trusted bank both for accepting private deposits and for commercial lending, creating the structure of financial intermediation required for growth.
IIIE Appendix Euro Zone Survival Risk. Markets have been dominated by rating actions of Standard & Poor’s Ratings Services (S&PRS) (2012Jan13) on 16 members of the European Monetary Union (EMU) or eurozone. The actions by S&PRS (2012Jan13) are of several types:
1. Downgrades by two notches of long-term credit ratings of Cyprus (from BBB/Watch/NegA-3+ to BB+/Neg/B), Italy (from A/Watch Neg/A-1 to BBB+/Neg/A-2), Portugal (from BBB-/Watch Neg/A-3 to BB/Neg/B) and Spain (from AA-/Watch Neg/A-1+ to A/Neg/A-1).
2. Downgrades by one notch of long-term credit ratings of Austria (from AAA/Watch Neg/A-1+ to AA+/Neg/A-1+), France (from AAA/Watch Neg/A-1+ to AA+/Neg A-1+), Malta (from A/Watch, Neg/A-1 to A-/Neg/A-2), Slovakia (from A+/Watch Neg/A-1 to A/Stable/A-1) and Slovenia (AA-/Watch Neg/A-1+ to A+/Neg/A-1).
3. Affirmation of long-term ratings of Belgium (AA/Neg/A-1+), Estonia (AA-/Neg/A-1+), Finland (AAA/Neg/A-1+), Germany (AAA/Stable/A-1+), Ireland (BBB+/Neg/A-2), Luxembourg (AAA/Neg/A-1+) and the Netherlands (AAA/Neg/A-1+) with removal from CreditWatch.
4. Negative outlook on the long-term credit ratings of Austria, Belgium, Cyprus, Estonia, Finland, France, Ireland, Italy, Luxembourg, Malta, the Netherlands, Portugal, Slovenia and Spain, meaning that S&PRS (2012Jan13) finds that the ratings of these sovereigns have a chance of at least 1-to-3 of downgrades in 2012 or 2013.
S&PRS (2012Jan13) finds that measures by European policymakers may not be sufficient to contain sovereign risks in the eurozone. The sources of stress according to S&PRS (2012Jan13) are:
1. Worsening credit environment
2. Increases in risk premiums for many eurozone borrowers
3. Simultaneous attempts at reducing debts by both eurozone governments and households
4. More limited perspectives of economic growth
5. Deepening and protracted division among Europe’s policymakers in agreeing to approaches to resolve the European debt crisis
There is now only one major country in the eurozone with AAA rating of its long-term debt by S&PRS (2012Jan13): Germany. IIIE Appendix Euro Zone Survival Risk analyzes the hurdle of financial bailouts of euro area members by the strength of the credit of Germany alone. The sum of the debt of Italy, Spain, Portugal, Greece and Ireland is abouy $3531.6 billion. There is some simple “unpleasant bond arithmetic.” Suppose the entire debt burdens of the five countries with probability of default were to be guaranteed by France and Germany, which de facto would be required by continuing the euro zone. The sum of the total debt of these five countries and the debt of France and Germany is about $7385.1 billion, which would be equivalent to 126.3 percent of their combined GDP in 2010. Under this arrangement the entire debt of the euro zone including debt of France and Germany would not have nil probability of default. Debt as percent of Germany’s GDP would exceed 224 percent if including debt of France and 165 percent of German GDP if excluding French debt. The unpleasant bond arithmetic illustrates that there is a limit as to how far Germany and France can go in bailing out the countries with unsustainable sovereign debt without incurring severe pains of their own such as downgrades of their sovereign credit ratings. A central bank is not typically engaged in direct credit because of remembrance of inflation and abuse in the past. There is also a limit to operations of the European Central Bank in doubtful credit obligations. Charles Forelle, writing on Jan 14, 2012, on “Downgrade hurts euro rescue fund,” published by the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204409004577159210191567778.html), analyzes the impact of the downgrades on the European Financial Stability Facility (EFSF). The EFSF is a special purpose vehicle that has not capital but can raise funds to be used in bailouts by issuing AAA-rated debt. S&P may cut the rating of the EFSF to the new lowest rating of the six countries with AAA rating, which are now down to four with the downgrades of France and Austria. The other rating agencies Moody’s and Fitch have not taken similar action. On Jan, S&PRS (2012Jan16) did cut the long-term credit rating of the EFSF to AA+ and affirmed the short-term credit rating at A-+. The decision is derived from the reduction in credit rating of the countries guaranteeing the EFSF. In the view of S&PRS (2012Jan16), there are not sufficient credit enhancements after the reduction in the creditworthiness of the countries guaranteeing the EFSF. The decision could be reversed if credit enhancements were provided.
The flow of cash from safe havens to risk financial assets is processed by carry trades from zero interest rates that are frustrated by episodes of risk aversion or encouraged with return of risk appetite. European sovereign risk crises are closely linked to the exposures of regional banks to government debt. An important form of financial repression consists of changing the proportions of debt held by financial institutions toward higher shares in government debt. The financial history of Latin America, for example, is rich in such policies. Bailouts in the euro zone have sanctioned “bailing in” the private sector, which means that creditors such as banks will participate by “voluntary” reduction of the principal in government debt (see Pelaez and Pelaez, International Financial Architecture (2005), 163-202). David Enrich, Sara Schaeffer Muñoz and Patricia Knowsmann, writing on “European nations pressure own banks for loans,” on Nov 29, 2011, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204753404577066431341281676.html?mod=WSJPRO_hpp_MIDDLETopStories), provide important data and analysis on the role of banks in the European sovereign risk crisis. They assemble data from various sources showing that domestic banks hold 16.2 percent of Italy’s total government securities outstanding of €1,617.4 billion, 22.9 percent of Portugal’s total government securities of €103.9 billion and 12.3 percent of Spain’s total government securities of €535.3 billion. Capital requirements force banks to hold government securities to reduce overall risk exposure in balance sheets. Enrich, Schaeffer Muñoz and Knowsmann find information that governments are setting pressures on banks to acquire more government debt or at least to stop selling their holdings of government debt.
Bond auctions are also critical in episodes of risk aversion. David Oakley, writing on Jan 3, 2012, on “Sovereign issues draw euro to crunch point,” published by the Financial Times (http://www.ft.com/intl/cms/s/0/63b9d7ca-2bfa-11e1-98bc-00144feabdc0.html#axzz1iLNRyEbs), estimates total euro area sovereign issues in 2012 at €794 billion, much higher than the long-term average of €670 billion. Oakley finds that the sovereign issues are: Italy €220 billion, France €197 billion, Germany €178 billion and Spain €81 billion. Bond auctions will test the resilience of the euro. Victor Mallet and Robin Wigglesworth, writing on Jan 12, 2012, on “Spain and Italy raise €22bn in debt sales,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/e22c4e28-3d05-11e1-ae07-00144feabdc0.html#axzz1j4euflAi), analyze debt auctions during the week. Spain placed €10 billion of new bonds with maturities in 2015 and 2016, which was twice the maximum planned for the auction. Italy placed €8.5 billion of one-year bills at average yield of 2.735 percent, which was less than one-half of the yield of 5.95 percent a month before. Italy also placed €3.5 billion of 136-day bills at 1.64 percent. There may be some hope in the sovereign debt market. The yield of Italy’s 10-year bond dropped from around 7.20 percent on Jan 9 to about 6.70 percent on Jan 13 and then to around 6.30 percent on Jan 20. The yield of Spain’s 10-year bond fell from about 6.60 percent on Jan 9 to around 5.20 percent on Jan 13 and then to 5.50 percent on Jan 20.
A combination of strong economic data in China analyzed in subsection VC and the realization of the widely expected downgrade could explain the strength of the European sovereign debt market. Emese Bartha, Art Patnaude and Nick Cawley, writing on January 17, 2012, on “European T-bills see solid demand,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204555904577166363369792848.html?mod=WSJPRO_hpp_LEFTTopStories), analyze successful auctions treasury bills by Spain and Greece. A day after the downgrade, the EFSF found strong demand on Jan 17 for its six-month debt auction at the yield of 0.2664 percent, which is about the same as sovereign bills of France with the same maturity.
There may be some hope in the sovereign debt market. The yield of Italy’s 10-year bond dropped from around 7.20 percent on Jan 9 to about 6.70 percent on Jan 13 and then to around 6.30 percent on Jan 20. The yield of Spain’s 10-year bond fell from about 6.60 percent on Jan 9 to around 5.20 percent on Jan 13 and then to 5.50 percent on Jan 20. Paul Dobson, Emma Charlton and Lucy Meakin, writing on Jan 20, 2012, on “Bonds show return of crisis once ECB loans expire,” published in Bloomberg (http://www.bloomberg.com/news/2012-01-20/bonds-show-return-of-crisis-once-ecb-loans-expire-euro-credit.html), analyze sovereign debt and analysis of market participants. Large-scale lending of last resort by the European Central Bank, considered in VD Appendix on European Central Bank Large Scale Lender of Last Resort, provided ample liquidity in the euro zone for banks to borrow at 1 percent and lend at higher rates, including to government. Dobson, Charlton and Meakin trace the faster decline of yields of short-term sovereign debt relative to decline of yields of long-term sovereign debt. The significant fall of the spread of short relative to long yields could signal concern about the resolution of the sovereign debt while expanding lender of last resort operations have moderated relative short-term sovereign yields. Normal conditions would be attained if there is definitive resolution of long-term sovereign debt that would require fiscal consolidation in an environment of economic growth.
Charles Forelle and Stephen Fidler, writing on Dec 10, 2011, on “Questions place EU pact,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970203413304577087562993283958.html?mod=WSJPRO_hpp_LEFTTopStories#project%3DEUSUMMIT121011%26articleTabs%3Darticle), provide data, information and analysis of the agreement of Dec 9. There are multiple issues centering on whether investors will be reassured that the measures have reduced the risks of European sovereign obligations. While the European Central Bank has welcomed the measures, it is not yet clear of its future role in preventing erosion of sovereign debt values.
Another complicating factor is whether there will be further actions on sovereign debt ratings. On Dec 5, 2011, four days before the conclusion of the meeting of European leaders, Standard & Poor’s (2011Dec5) placed the sovereign ratings of 15 members of the euro zone on “CreditWatch with negative implications.” S&P finds five conditions that trigger the action: (1) worsening credit conditions in the euro area; (2) differences among member states on how to manage the debt crisis in the short run and on measures to move toward enhanced fiscal convergence; (3) household and government debt at high levels throughout large parts of the euro area; (4) increasing risk spreads on euro area sovereigns, including those with AAA ratings; and (5) increasing risks of recession in the euro zone. S&P also placed the European Financial Stability Facility (EFSF) in CreditWatch with negative implications (http://www.standardandpoors.com/ratings/articles/en/us/?articleType=HTML&assetID=1245325307963). On Dec 9, 2011, Moody’s Investors Service downgraded the ratings of the three largest French banks (http://www.moodys.com/research/Moodys-downgrades-BNP-Paribass-long-term-ratings-to-Aa3-concluding--PR_232989 http://www.moodys.com/research/Moodys-downgrades-Credit-Agricole-SAs-long-term-ratings-to-Aa3--PR_233004 http://www.moodys.com/research/Moodys-downgrades-Socit-Gnrales-long-term-ratings-to-A1--PR_232986 ).
Improving equity markets and strength of the euro appear related to developments in sovereign debt negotiations and markets. Alkman Granitsas and Costas Paris, writing on Jan 29, 2012, on “Greek debt deal, new loan agreement to finish next week,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204573704577189021923288392.html?mod=WSJPRO_hpp_LEFTTopStories), inform that Greece and its private creditors were near finishing a deal of writing off €100 billion, about $132 billion, of Greece’s debt depending on the conversations between Greece, the euro area and the IMF on the new bailout. An agreement had been reached in Oct 2011 for a new package of fresh money in the amount of €130 billion to fill needs through 2015 but was contingent on haircuts reducing Greece’s debt from 160 percent of GDP to 120 percent of GDP. The new bailout would be required to prevent default by Greece of €14.4 billion maturing on Mar 20, 2012. There has been increasing improvement of sovereign bond yields. Italy’s ten-year bond yield fell from over 6.30 percent on Jan 20, 2012 to slightly above 5.90 percent on Jan 27. Spain’s ten-year bond yield fell from slightly above 5.50 percent on Jan 20 to just below 5 percent on Jan 27.
An important difference, according to Beim (2011Oct9), between large-scale buying of bonds by the central bank between the Federal Reserve of the US and the European Central Bank (ECB) is that the Fed and most banks do not buy local and state government obligations with lower creditworthiness. The European Monetary Union (EMU) that created the euro and the ECB did not include common fiscal policy and affairs. Thus, EMU cannot issue its own treasury obligations. The line “Reserve bank credit” in the Fed balance sheet for Jan 25, 2012, is $2902 billion of which $2570 billion consisting of $1565 billion US Treasury notes and bonds, $68 billion inflation-indexed bonds and notes, $101 billion Federal agency debt securities and $836 billion mortgage-backed securities (http://www.federalreserve.gov/releases/h41/current/h41.htm#h41tab1). The Fed has been careful in avoiding credit risk in its portfolio of securities. The 11 exceptional liquidity facilities of several trillion dollars created during the financial crisis (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-62) have not resulted in any losses. The Fed has used unconventional monetary policy without credit risk as in classical central banking.
Beim (2011Oct9, 6) argues:
“In short, the ECB system holds more than €1 trillion of debt of the banks and governments of the 17 member states. The state-by-state composition of this debt is not disclosed, but the events of the past year suggest that a disproportionate fraction of these assets are likely obligations of stressed countries. If a significant fraction of the €1 trillion were to be restructured at 40-60% discounts, the ECB would have a massive problem: who would bail out the ECB?
This is surely why the ECB has been so shrill in its antagonism to the slightest mention of default and restructuring. They need to maintain the illusion of risk-free sovereign debt because confidence in the euro itself is built upon it.”
Table III-2 provides an update of the consolidated financial statement of the Eurosystem. The balance sheet has swollen with the LTROs. Line 5 “Lending to Euro Area Credit Institutions Related to Monetary Policy” increasing from €546,747 million on Dec 31, 2010, to €870,130 million on Dec 28, 2011 and €1,117,090 million on May 4, 2012. The sum of line 5 and line 7 (“Securities of Euro Area Residents Denominated in Euro”) has increased to €1,724,313 million in the statement of May 11.
This sum is roughly what concerns Beim (2012Oct9) because of the probable exposure relative to capital to institutions and sovereigns with higher default risk. To be sure, there is no precise knowledge of the composition of the ECB portfolio of loans and securities with weights and analysis of the risks of components. Javier E. David, writing on Jan 16, 2012, on “The risks in ECB’s crisis moves,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204542404577158753459542024.html?mod=WSJ_hp_LEFTWhatsNewsCollection), informs that the estimated debt of weakest euro zone sovereigns held by the ECB is €211 billion, with Greek debt in highest immediate default risk being only 17 percent of the total. Another unknown is whether there is high risk collateral in the €489 billion three-year loans to credit institutions at 1 percent interest rates. The potential risk is the need for recapitalization of the ECB that could find similar political hurdles as the bailout fund EFSF. There is a recurring issue of whether the ECB should accept a haircut on its portfolio of Greek bonds of €40 billion acquired at discounts from face value. An article on “Haircut for the ECB? Not so fast,” published by the Wall Street Journal on Jan 28, 2012 (http://blogs.wsj.com/davos/2012/01/28/haircut-for-the-ecb-not-so-fast/), informs of the remarks by Mark Carney, Governor of the Bank of Canada and President of the Financial Stability Board (FSB) (http://www.financialstabilityboard.org/about/overview.htm), expressing what appears to be correct doctrine that there could conceivably be haircuts for official debt but that such a decision should be taken by governments and not by central banks.
Table III-2, Consolidated Financial Statement of the Eurosystem, Million EUR
| Dec 31, 2010 | Dec 28, 2011 | May 4, 2012 | |
| 1 Gold and other Receivables | 367,402 | 419,822 | 432,705 |
| 2 Claims on Non Euro Area Residents Denominated in Foreign Currency | 223,995 | 236,826 | 241,977 |
| 3 Claims on Euro Area Residents Denominated in Foreign Currency | 26,941 | 95,355 | 51,965 |
| 4 Claims on Non-Euro Area Residents Denominated in Euro | 22,592 | 25,982 | 20,108 |
| 5 Lending to Euro Area Credit Institutions Related to Monetary Policy Operations Denominated in Euro | 546,747 | 879,130 | 1,117,090 |
| 6 Other Claims on Euro Area Credit Institutions Denominated in Euro | 45,654 | 94,989 | 204,691 |
| 7 Securities of Euro Area Residents Denominated in Euro | 457,427 | 610,629 | 607,223 |
| 8 General Government Debt Denominated in Euro | 34,954 | 33,928 | 30,589 |
| 9 Other Assets | 278,719 | 336,574 | 253,970 |
| TOTAL ASSETS | 2,004, 432 | 2,733,235 | 2,960,317 |
| Memo Items | |||
| Sum of 5 and 7 | 1,004,174 | 1,489,759 | 1,724,313 |
| Capital and Reserves | 78,143 | 81,481 | 85,545 |
Source: European Central Bank
http://www.ecb.int/press/pr/wfs/2011/html/fs110105.en.html
http://www.ecb.int/press/pr/wfs/2011/html/fs111228.en.html
http://www.ecb.int/press/pr/wfs/2012/html/fs120508.en.html
Professors Ricardo Caballero and Francesco Giavazzi (2012Jan15) find that the resolution of the European sovereign crisis with survival of the euro area would require success in the restructuring of Italy. That success would be assured with growth of the Italian economy. A critical problem is that the common euro currency prevents Italy from devaluing the exchange rate to parity or the exchange rate that would permit export growth to promote internal economic activity, which could generate fiscal revenues for primary fiscal surplus that ensure creditworthiness. Fiscal consolidation and restructuring are important but of long-term gestation. Immediate growth of the Italian economy would consolidate the resolution of the sovereign debt crisis. Caballero and Giavazzi (2012Jan15) argue that 55 percent of the exports of Italy are to countries outside the euro area such that devaluation of 15 percent would be effective in increasing export revenue. Newly available data in Table III-3 providing Italy’s trade with regions and countries supports the argument of Caballero and Giavazzi (2012Jan15). Italy’s exports to the European Monetary Union (EMU) are only 42.7 percent of the total. Exports to the non-European Union area are growing at 11.8 percent in Feb 2012 relative to Feb 2011 while those to EMU are growing at 3.5 percent.
Table III-3, Italy, Exports and Imports by Regions and Countries, % Share and 12-Month ∆%
| Feb 2012 | Exports | ∆% Feb 2012/ Feb 2011 | Imports | Imports |
| EU | 56.0 | 4.1 | 53.3 | -2.4 |
| EMU 17 | 42.7 | 3.5 | 43.2 | -1.5 |
| France | 11.6 | 5.4 | 8.3 | -1.5 |
| Germany | 13.1 | 7.4 | 15.6 | -4.4 |
| Spain | 5.3 | -7.4 | 4.5 | -6.0 |
| UK | 4.7 | 9.5 | 2.7 | -9.1 |
| Non EU | 44.0 | 11.8 | 46.7 | 4.6 |
| Europe non EU | 13.3 | 16.7 | 11.1 | 8.6 |
| USA | 6.1 | 21.5 | 3.3 | 7.2 |
| China | 2.7 | -4.8 | 7.3 | -11.5 |
| OPEC | 4.7 | 2.9 | 8.6 | 15.9 |
| Total | 100.0 | 7.3 | 100.0 | 0.8 |
Notes: EU: European Union; EMU: European Monetary Union (euro zone)
Source: http://www.istat.it/it/archivio/59291
Table III-4 provides Italy’s trade balance by regions and countries. Italy had trade deficit of €493 million with the 17 countries of the euro zone (EMU 17) in Feb and €535 million in Jan-Feb. Depreciation to parity could permit greater competitiveness in improving the trade surpluses of €699 million in Jan-Feb with Europe non European Union and of €1093 million with the US. There is significant rigidity in the trade deficits in Jan-Feb of €3209 million with China and €4472 million with members of the Organization of Petroleum Exporting Countries (OPEC).
Table III-4, Italy, Trade Balance by Regions and Countries, Millions of Euro
| Regions and Countries | Trade Balance Feb 2012 Millions of Euro | Trade Balance Cumulative Jan-Feb 2012 Millions of Euro |
| EU | 439 | 1,199 |
| EMU 17 | -493 | -535 |
| France | 964 | 1,796 |
| Germany | -470 | -870 |
| Spain | 158 | 484 |
| UK | 664 | 1,301 |
| Non EU | -1,552 | -6,658 |
| Europe non EU | 601 | 699 |
| USA | 837 | 1,093 |
| China | -1,477 | -3,209 |
| OPEC | -1,892 | -4,472 |
| Total | -1,113 | -5,549 |
Notes: EU: European Union; EMU: European Monetary Union (euro zone)
Source: http://www.istat.it/it/archivio/59291
Growth rates of Italy’s trade and major products are provided in Table III-5 for the period Feb 2012 relative to Feb 2011. Growth rates are high for the total and all segments of exports. Imports of nondurable goods increased 3.8 percent and imports of energy increased 29.7 percent driven by carry trades into commodities futures. The higher rate of growth of exports of 7.3 percent relative to imports of 0.8 percent may reflect weak demand in Italy.
Table III-5, Italy, Exports and Imports % Share of Products in Total and ∆%
| Exports | Exports | Imports | Imports | |
| Consumer | 28.9 | 8.0 | 25.0 | 2.5 |
| Durable | 5.9 | 2.8 | 3.0 | -6.6 |
| Non | 23.0 | 9.4 | 22.0 | 3.8 |
| Capital Goods | 32.2 | 5.8 | 20.8 | -5.2 |
| Inter- | 34.3 | 6.3 | 34.5 | -10.8 |
| Energy | 4.7 | 20.7 | 19.7 | 29.7 |
| Total ex Energy | 95.3 | 6.7 | 80.3 | -5.4 |
| Total | 100.0 | 7.3 | 100.0 | 0.8 |
Source: http://www.istat.it/it/archivio/59291
Table III-6 provides Italy’s trade balance by product categories in Feb 2012 and cumulative Jan-Feb 2012. Italy’s trade balance excluding energy generated surplus of €6475 million in Feb 2012 but the energy trade balance created deficit of €11,934 million. The overall deficit was €5459 million. Italy has significant competitiveness in various economic activities in contrast with some other countries with debt difficulties.
Table III-6, Italy, Trade Balance by Product Categories, € Millions
| Feb 2012 | Cumulative Jan-Feb 2012 | |
| Consumer Goods | 1,264 | 1,425 |
| Durable | 953 | 1,428 |
| Nondurable | 311 | -3 |
| Capital Goods | 3,161 | 5,160 |
| Intermediate Goods | 264 | -111 |
| Energy | -5,802 | -11,934 |
| Total ex Energy | 4,689 | 6,475 |
| Total | -1,113 | -5,459 |
Source: http://www.istat.it/it/archivio/59291
Brazil’s terms of trade, export prices relative to import prices, deteriorated 47 percent and 36 percent excluding oil (Pelaez 1987, 176-79; Pelaez 1986, 37-66; see Pelaez and Pelaez, The Global Recession Risk (2007), 178-87). Brazil had accumulated unsustainable foreign debt by borrowing to finance balance of payments deficits during the 1970s. Foreign lending virtually stopped. The German mark devalued strongly relative to the dollar such that Brazil’s products lost competitiveness in Germany and in multiple markets in competition with Germany. The resolution of the crisis was devaluation of the Brazilian currency by 30 percent relative to the dollar and subsequent maintenance of parity by monthly devaluation equal to inflation and indexing that resulted in financial stability by parity in external and internal interest rates avoiding capital flight. With a combination of declining imports, domestic import substitution and export growth, Brazil followed rapid growth in the US and grew out of the crisis with surprising GDP growth of 4.5 percent in 1984.
The euro zone faces a critical survival risk because several of its members may default on their sovereign obligations if not bailed out by the other members. The valuation equation of bonds is essential to understanding the stability of the euro area. An explanation is provided in this paragraph and readers interested in technical details are referred to the following Subsection IIID Appendix on Sovereign Bond Valuation. Contrary to the Wriston doctrine, investing in sovereign obligations is a credit decision. The value of a bond today is equal to the discounted value of future obligations of interest and principal until maturity. On Dec 30 the yield of the 2-year bond of the government of Greece was quoted around 100 percent. In contrast, the 2-year US Treasury note traded at 0.239 percent and the 10-year at 2.871 percent while the comparable 2-year government bond of Germany traded at 0.14 percent and the 10-year government bond of Germany traded at 1.83 percent. There is no need for sovereign ratings: the perceptions of investors are of relatively higher probability of default by Greece, defying Wriston (1982), and nil probability of default of the US Treasury and the German government. The essence of the sovereign credit decision is whether the sovereign will be able to finance new debt and refinance existing debt without interrupting service of interest and principal. Prices of sovereign bonds incorporate multiple anticipations such as inflation and liquidity premiums of long-term relative to short-term debt but also risk premiums on whether the sovereign’s debt can be managed as it increases without bound. The austerity measures of Italy are designed to increase the primary surplus, or government revenues less expenditures excluding interest, to ensure investors that Italy will have the fiscal strength to manage its debt of 120 percent of GDP, which is the third largest in the world after the US and Japan. Appendix IIIE links the expectations on the primary surplus to the real current value of government monetary and fiscal obligations. As Blanchard (2011SepWEO) analyzes, fiscal consolidation to increase the primary surplus is facilitated by growth of the economy. Italy and the other indebted sovereigns in Europe face the dual challenge of increasing primary surpluses while maintaining growth of the economy (for the experience of Brazil in the debt crisis of 1982 see Pelaez 1986, 1987).
Much of the analysis and concern over the euro zone centers on the lack of credibility of the debt of a few countries while there is credibility of the debt of the euro zone as a whole. In practice, there is convergence in valuations and concerns toward the fact that there may not be credibility of the euro zone as a whole. The fluctuations of financial risk assets of members of the euro zone move together with risk aversion toward the countries with lack of debt credibility. This movement raises the need to consider analytically sovereign debt valuation of the euro zone as a whole in the essential analysis of whether the single-currency will survive without major changes.
Welfare economics considers the desirability of alternative states, which in this case would be evaluating the “value” of Germany (1) within and (2) outside the euro zone. Is the sum of the wealth of euro zone countries outside of the euro zone higher than the wealth of these countries maintaining the euro zone? On the choice of indicator of welfare, Hicks (1975, 324) argues:
“Partly as a result of the Keynesian revolution, but more (perhaps) because of statistical labours that were initially quite independent of it, the Social Product has now come right back into its old place. Modern economics—especially modern applied economics—is centered upon the Social Product, the Wealth of Nations, as it was in the days of Smith and Ricardo, but as it was not in the time that came between. So if modern theory is to be effective, if it is to deal with the questions which we in our time want to have answered, the size and growth of the Social Product are among the chief things with which it must concern itself. It is of course the objective Social Product on which attention must be fixed. We have indexes of production; we do not have—it is clear we cannot have—an Index of Welfare.”
If the burden of the debt of the euro zone falls on Germany and France or only on Germany, is the wealth of Germany and France or only Germany higher after breakup of the euro zone or if maintaining the euro zone? In practice, political realities will determine the decision through elections.
The prospects of survival of the euro zone are dire. Table III-7 is constructed with IMF World Economic Outlook database (http://www.imf.org/external/pubs/ft/weo/2012/01/weodata/index.aspx) for GDP in USD billions, primary net lending/borrowing as percent of GDP and general government debt as percent of GDP for selected regions and countries in 2010.
Table III-7, World and Selected Regional and Country GDP and Fiscal Situation
| GDP 2012 | Primary Net Lending Borrowing | General Government Net Debt | |
| World | 69,660 | ||
| Euro Zone | 12,586 | -0.5 | 70.3 |
| Portugal | 221 | 0.1 | 110.9 |
| Ireland | 210 | -4.4 | 102.9 |
| Greece | 271 | -1.0 | 153.2 |
| Spain | 1,398 | -3.6 | 67.0 |
| Major Advanced Economies G7 | 34,106 | -4.8 | 88.3 |
| United States | 15,610 | -6.1 | 83.7 |
| UK | 2,453 | -5.3 | 84.2 |
| Germany | 3,479 | 1.0 | 54.1 |
| France | 2,712.0 | -2.2 | 83.2 |
| Japan | 5,981 | -8.9 | 135.2 |
| Canada | 1,805 | -3.1 | 35.4 |
| Italy | 2,067 | 2.9 | 102.3 |
| China | 7992 | -1.3* | 22.0** |
*Net Lending/borrowing**Gross Debt
Source: http://www.imf.org/external/pubs/ft/weo/2012/01/weodata/weoselgr.aspx
The data in Table III-7 are used for some very simple calculations in Table III-8. The column “Net Debt USD Billions” in Table III-8 is generated by applying the percentage in Table III-7 column “General Government Net Debt % GDP 2010” to the column “GDP USD Billions.” The total debt of France and Germany in 2012 is $4138.5 billion, as shown in row “B+C” in column “Net Debt USD Billions” The sum of the debt of Italy, Spain, Portugal, Greece and Ireland is $3927.8 billion, adding rows D+E+F+G+H in column “Net Debt USD billions.” There is some simple “unpleasant bond arithmetic” in the two final columns of Table III-8. Suppose the entire debt burdens of the five countries with probability of default were to be guaranteed by France and Germany, which de facto would be required by continuing the euro zone. The sum of the total debt of these five countries and the debt of France and Germany is shown in column “Debt as % of Germany plus France GDP” to reach $8066.3 billion, which would be equivalent to 130.3 percent of their combined GDP in 2012. Under this arrangement the entire debt of the euro zone including debt of France and Germany would not have nil probability of default. The final column provides “Debt as % of Germany GDP” that would exceed 231.9 percent if including debt of France and 167.0 percent of German GDP if excluding French debt. The unpleasant bond arithmetic illustrates that there is a limit as to how far Germany and France can go in bailing out the countries with unsustainable sovereign debt without incurring severe pains of their own such as downgrades of their sovereign credit ratings. A central bank is not typically engaged in direct credit because of remembrance of inflation and abuse in the past. There is also a limit to operations of the European Central Bank in doubtful credit obligations. Wriston (1982) would prove to be wrong again that countries do not bankrupt but would have a consolation prize that similar to LBOs the sum of the individual values of euro zone members outside the current agreement exceeds the value of the whole euro zone. Internal rescues of French and German banks may be less costly than bailing out other euro zone countries so that they do not default on French and German banks.
Table III-8, Guarantees of Debt of Sovereigns in Euro Area as Percent of GDP of Germany and France, USD Billions and %
| Net Debt USD Billions | Debt as % of Germany Plus France GDP | Debt as % of Germany GDP | |
| A Euro Area | 8,847.9 | ||
| B Germany | 1,882.1 | $8066.3 as % of $3479 =231.9% $5809.9 as % of $3479 =167.0% | |
| C France | 2,256.4 | ||
| B+C | 4,138.5 | GDP $6,191.0 Total Debt $8066.3 Debt/GDP: 130.3% | |
| D Italy | 2,114.5 | ||
| E Spain | 936.7 | ||
| F Portugal | 245.3 | ||
| G Greece | 415.2 | ||
| H Ireland | 216.1 | ||
| Subtotal D+E+F+G+H | 3,927.8 |
Source: calculation with IMF data http://www.imf.org/external/pubs/ft/weo/2012/01/weodata/index.aspx
There is extremely important information in Table III-9 for the current sovereign risk crisis in the euro zone. Table III-9 provides the structure of regional and country relations of Germany’s exports and imports with newly available data for Mar 2012. German exports to other European Union (EU) members are 57.6 percent of total exports in Mar 2012 and 58.4 percent in Jan-Mar 2012. Exports to the euro area are 38.5 percent in Mar and 39.0 percent in Jan-Mar. Exports to third countries are 42.4 percent of the total in Mar and 41.6 percent in Jan-Mar. There is similar distribution for imports. Economic performance in Germany is closely related to its high competitiveness in world markets. Weakness in the euro zone and the European Union in general could affect the German economy. This may be the major reason for choosing the “fiscal abuse” of the European Central Bank considered by Buiter (2011Oct31) over the breakdown of the euro zone. There is a tough analytical, empirical and forecasting doubt of growth and trade in the euro zone and the world with or without maintenance of the European Monetary Union (EMU) or euro zone. Germany could benefit from depreciation of the euro because of its high share in exports to countries not in the euro zone but breakdown of the euro zone raises doubts on the region’s economic growth that could affect German exports to other member states.
Table III-9, Germany, Structure of Exports and Imports by Region, € Billions and ∆%
| Mar 2012 | Mar 12-Month | Jan–Mar 2012 € Billions | Jan-Mar 2012/ | |
| Total | 98.9 | 0.7 | 276.1 | 5.8 |
| A. EU | 57.0 % 57.6 | -2.8 | 161.3 % 58.4 | 2.3 |
| Euro Area | 38.1 % 38.5 | -3.6 | 107.7 % 39.0 | 1.1 |
| Non-euro Area | 18.9 % 19.1 | -1.4 | 53.6 % 19.4 | 4.7 |
| B. Third Countries | 41.9 % 42.4 | 6.1 | 114.8 % 41.6 | 11.2 |
| Total Imports | 81.5 | 2.6 | 230.6 | 4.8 |
| C. EU Members | 52.4 % 64.3 | 2.1 | 145.8 % 63.2 | 5.0 |
| Euro Area | 37.0 % 45.4 | 2.3 | 102.4 % 44.4 | 4.7 |
| Non-euro Area | 15.4 % 18.9 | 1.7 | 43.4 % 18.8 | 5.8 |
| D. Third Countries | 29.1 % 35.7 | 3.5 | 84.8 % 36.8 | 4.3 |
Notes: Total Exports = A+B; Total Imports = C+D
Source:
Statistiche Bundesamt Deutschland
IIIF Appendix on Sovereign Bond Valuation. There are two approaches to government finance and their implications: (1) simple unpleasant monetarist arithmetic; and (2) simple unpleasant fiscal arithmetic. Both approaches illustrate how sovereign debt can be perceived riskier under profligacy.
First, Unpleasant Monetarist Arithmetic. Fiscal policy is described by Sargent and Wallace (1981, 3, equation 1) as a time sequence of D(t), t = 1, 2,…t, …, where D is real government expenditures, excluding interest on government debt, less real tax receipts. D(t) is the real deficit excluding real interest payments measured in real time t goods. Monetary policy is described by a time sequence of H(t), t=1,2,…t, …, with H(t) being the stock of base money at time t. In order to simplify analysis, all government debt is considered as being only for one time period, in the form of a one-period bond B(t), issued at time t-1 and maturing at time t. Denote by R(t-1) the real rate of interest on the one-period bond B(t) between t-1 and t. The measurement of B(t-1) is in terms of t-1 goods and [1+R(t-1)] “is measured in time t goods per unit of time t-1 goods” (Sargent and Wallace 1981, 3). Thus, B(t-1)[1+R(t-1)] brings B(t-1) to maturing time t. B(t) represents borrowing by the government from the private sector from t to t+1 in terms of time t goods. The price level at t is denoted by p(t). The budget constraint of Sargent and Wallace (1981, 3, equation 1) is:
D(t) = {[H(t) – H(t-1)]/p(t)} + {B(t) – B(t-1)[1 + R(t-1)]} (1)
Equation (1) states that the government finances its real deficits into two portions. The first portion, {[H(t) – H(t-1)]/p(t)}, is seigniorage, or “printing money.” The second part,
{B(t) – B(t-1)[1 + R(t-1)]}, is borrowing from the public by issue of interest-bearing securities. Denote population at time t by N(t) and growing by assumption at the constant rate of n, such that:
N(t+1) = (1+n)N(t), n>-1 (2)
The per capita form of the budget constraint is obtained by dividing (1) by N(t) and rearranging:
B(t)/N(t) = {[1+R(t-1)]/(1+n)}x[B(t-1)/N(t-1)]+[D(t)/N(t)] – {[H(t)-H(t-1)]/[N(t)p(t)]} (3)
On the basis of the assumptions of equal constant rate of growth of population and real income, n, constant real rate of return on government securities exceeding growth of economic activity and quantity theory equation of demand for base money, Sargent and Wallace (1981) find that “tighter current monetary policy implies higher future inflation” under fiscal policy dominance of monetary policy. That is, the monetary authority does not permanently influence inflation, lowering inflation now with tighter policy but experiencing higher inflation in the future.
Second, Unpleasant Fiscal Arithmetic. The tool of analysis of Cochrane (2011Jan, 27, equation (16)) is the government debt valuation equation:
(Mt + Bt)/Pt = Et∫(1/Rt, t+τ)st+τdτ (4)
Equation (4) expresses the monetary, Mt, and debt, Bt, liabilities of the government, divided by the price level, Pt, in terms of the expected value discounted by the ex-post rate on government debt, Rt, t+τ, of the future primary surpluses st+τ, which are equal to Tt+τ – Gt+τ or difference between taxes, T, and government expenditures, G. Cochrane (2010A) provides the link to a web appendix demonstrating that it is possible to discount by the ex post Rt, t+τ. The second equation of Cochrane (2011Jan, 5) is:
MtV(it, ·) = PtYt (5)
Conventional analysis of monetary policy contends that fiscal authorities simply adjust primary surpluses, s, to sanction the price level determined by the monetary authority through equation (5), which deprives the debt valuation equation (4) of any role in price level determination. The simple explanation is (Cochrane 2011Jan, 5):
“We are here to think about what happens when [4] exerts more force on the price level. This change may happen by force, when debt, deficits and distorting taxes become large so the Treasury is unable or refuses to follow. Then [4] determines the price level; monetary policy must follow the fiscal lead and ‘passively’ adjust M to satisfy [5]. This change may also happen by choice; monetary policies may be deliberately passive, in which case there is nothing for the Treasury to follow and [4] determines the price level.”
An intuitive interpretation by Cochrane (2011Jan 4) is that when the current real value of government debt exceeds expected future surpluses, economic agents unload government debt to purchase private assets and goods, resulting in inflation. If the risk premium on government debt declines, government debt becomes more valuable, causing a deflationary effect. If the risk premium on government debt increases, government debt becomes less valuable, causing an inflationary effect.
There are multiple conclusions by Cochrane (2011Jan) on the debt/dollar crisis and Global recession, among which the following three:
(1) The flight to quality that magnified the recession was not from goods into money but from private-sector securities into government debt because of the risk premium on private-sector securities; monetary policy consisted of providing liquidity in private-sector markets suffering stress
(2) Increases in liquidity by open-market operations with short-term securities have no impact; quantitative easing can affect the timing but not the rate of inflation; and purchase of private debt can reverse part of the flight to quality
(3) The debt valuation equation has a similar role as the expectation shifting the Phillips curve such that a fiscal inflation can generate stagflation effects similar to those occurring from a loss of anchoring expectations.
IV Global Inflation. There is inflation everywhere in the world economy, with slow growth and persistently high unemployment in advanced economies. Table IV-1, updated with every blog comment, provides the latest annual data for GDP, consumer price index (CPI) inflation, producer price index (PPI) inflation and unemployment (UNE) for the advanced economies, China and the highly-indebted European countries with sovereign risk issues. The table now includes the Netherlands and Finland that with Germany make up the set of northern countries in the euro zone that hold key votes in the enhancement of the mechanism for solution of sovereign risk issues (Peter Spiegel and Quentin Peel, “Europe: Northern Exposures,” Financial Times, Mar 9, 2011 http://www.ft.com/intl/cms/s/0/55eaf350-4a8b-11e0-82ab-00144feab49a.html#axzz1gAlaswcW). Newly available data on inflation is considered below in this section. Data in Table IV-1 for the euro zone and its members are updated from information provided by Eurostat but individual country information is provided in this section as soon as available, following Table IV-1. Data for other countries in Table IV-1 are also updated with reports from their statistical agencies. Economic data for major regions and countries is considered in Section V World Economic Slowdown following with individual country and regional data tables.
Table IV-1, GDP Growth, Inflation and Unemployment in Selected Countries, Percentage Annual Rates
| GDP | CPI | PPI | UNE | |
| US | 2.1 | 2.7 | 1.9 | 8.1 |
| Japan | -0.6 | 0.5 | 0.6 | 4.5 |
| China | 8.9 | 3.4 | -0.7 | |
| UK | 0.0 | 3.5* | 3.3* output | 8.3 |
| Euro Zone | 0.7 | 2.7 | 3.3 | 10.9 |
| Germany | 2.0 | 2.3 | 3.4 | 5.6 |
| France | 0.2 | 2.6 | 3.7 | 10.0 |
| Nether-lands | -0.7 | 2.9 | 3.6 | 5.0 |
| Finland | 1.2 | 2.9 | 2.7 | 7.5 |
| Belgium | 0.9 | 3.1 | 2.8 | 7.3 |
| Portugal | -2.7 | 3.1 | 3.5 | 15.3 |
| Ireland | NA | 2.2 | 3.1 | 14.5 |
| Italy | -0.5 | 3.8 | 2.7 | 9.8 |
| Greece | -7.0 | 1.4 | 6.7 | NA |
| Spain | 0.3 | 1.8 | 3.3 | 24.1 |
Notes: GDP: rate of growth of GDP; CPI: change in consumer price inflation; PPI: producer price inflation; UNE: rate of unemployment; all rates relative to year earlier
*Office for National Statistics http://www.ons.gov.uk/ons/rel/cpi/consumer-price-indices/march-2012/index.html **Core
PPI http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/april-2012/index.html
Source: EUROSTAT; country statistical sources http://www.census.gov/aboutus/stat_int.html
Table IV-1 shows the simultaneous occurrence of low growth, inflation and unemployment in advanced economies. The US grew at 2.1 percent in IQ2012 relative to IQ2011 (Table 8, p 11 in http://www.bea.gov/newsreleases/national/gdp/2012/pdf/gdp1q12_adv.pdf See Section I Mediocre Economic Growth at http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html). Japan’s GDP fell 0.6 percent in IVQ2011 relative to IVQ2010 and contracted 1.7 percent in IIQ2011 relative to IIQ2010 because of the Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011 but grew at the seasonally-adjusted annual rate (SAAR) of 7.1 percent in IIIQ2011 to decline at the SAAR of 0.7 percent in IVQ 2011 (see Section VB at http://cmpassocregulationblog.blogspot.com/2012/03/thirty-million-unemployed-or_11.html); the UK grew at 0.0 percent in IQ2012 relative to IQ2011 and GDP fell 0.2 percent in IQ2012 relative to IVQ2011 (see Section VB at http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment_29.html and http://www.ons.gov.uk/ons/rel/gva/gross-domestic-product--preliminary-estimate/q1-2012/stb-q1-2012.html); and the Euro Zone grew at 0.7 percent in IVQ2011 relative to IVQ2010 but declined 0.3 percent in IVQ2011 relative to IIIQ2011 (see Section VD at http://cmpassocregulationblog.blogspot.com/2012/03/thirty-million-unemployed-or_11.html and http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-06032012-AP/EN/2-06032012-AP-EN.PDF). These are stagnating or “growth recession” rates, which are positive growth rates instead of contractions but insufficient to recover employment. The rates of unemployment are quite high: 8.1 percent in the US but 17.3 percent for unemployment/underemployment or job stress of 27.8 million (see Table I-4 in Section I and earlier at http://cmpassocregulationblog.blogspot.com/2012/04/thirty-million-unemployed-or.html), 4.5 percent for Japan (see Section VB at http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment_29.html), 8.3 percent for the UK with high rates of unemployment for young people (see the labor statistics of the UK in Subsection VH in http://cmpassocregulationblog.blogspot.com/2012/04/imf-view-of-world-economy-and-finance_22.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/03/global-financial-and-economic-risk_18.html) and 10.9 percent in the Euro Zone (section VD at http://cmpassocregulationblog.blogspot.com/2012/05/recovery-without-jobs-twenty-eight_06.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/04/thirty-million-unemployed-or_08.html). Twelve-month rates of inflation have been quite high, even when some are moderating at the margin: 2.7 percent in the US, 0.5 percent for Japan, 3.6 percent for China, 2.7 percent for the Euro Zone and 3.5 percent for the UK (http://www.ons.gov.uk/ons/rel/cpi/consumer-price-indices/march-2012/index.html). Stagflation is still an unknown event but the risk is sufficiently high to be worthy of consideration (see http://cmpassocregulationblog.blogspot.com/2011/06/risk-aversion-and-stagflation.html). The analysis of stagflation also permits the identification of important policy issues in solving vulnerabilities that have high impact on global financial risks. There are six key interrelated vulnerabilities in the world economy that have been causing global financial turbulence: (1) sovereign risk issues in Europe resulting from countries in need of fiscal consolidation and enhancement of their sovereign risk ratings (see Section III in this post and the earlier post http://cmpassocregulationblog.blogspot.com/2012/05/recovery-without-jobs-twenty-eight.html); (2) the tradeoff of growth and inflation in China now with change in growth strategy to domestic consumption instead of investment and political developments in a decennial transition; (3) slow growth by repression of savings with de facto interest rate controls (see section I at http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html and earlier http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-economic-growth-falling-real.html), weak hiring with the loss of 10 million full-time jobs (see section I and earlier in http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/03/global-financial-and-economic-risk.html and http://cmpassocregulationblog.blogspot.com/2012/02/hiring-collapse-ten-million-fewer-full.html) and continuing job stress of 24 to 30 million people in the US and stagnant wages in a fractured job market (see Section I Twenty Eight Million Unemployed or Underemployed at http://cmpassocregulationblog.blogspot.com/2012/04/thirty-million-unemployed-or.html); (4) the timing, dose, impact and instruments of normalizing monetary and fiscal policies (see IV Budget/Debt Quagmire in http://cmpassocregulationblog.blogspot.com/2012/02/thirty-one-million-unemployed-or.html http://cmpassocregulationblog.blogspot.com/2011/08/united-states-gdp-growth-standstill.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html http://cmpassocregulationblog.blogspot.com/2011/03/global-financial-risks-and-fed.html http://cmpassocregulationblog.blogspot.com/2011/02/policy-inflation-growth-unemployment.html) in advanced and emerging economies; (5) the Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011 that had repercussions throughout the world economy because of Japan’s share of about 9 percent in world output, role as entry point for business in Asia, key supplier of advanced components and other inputs as well as major role in finance and multiple economic activities (http://professional.wsj.com/article/SB10001424052748704461304576216950927404360.html?mod=WSJ_business_AsiaNewsBucket&mg=reno-wsj); and (6) geopolitical events in the Middle East.
In the effort to increase transparency, the Federal Open Market Committee (FOMC) provides both economic projections of its participants and views on future paths of the policy rate that in the US is the federal funds rate or interest on interbank lending of reserves deposited at Federal Reserve Banks. These projections and views are discussed initially followed with appropriate analysis.
The statement of the FOMC at the conclusion of its meeting on Apr 25, 2012, revealed the following policy intentions (http://www.federalreserve.gov/newsevents/press/monetary/20120425a.htm):
“Release Date: April 25, 2012
For immediate release
Information received since the Federal Open Market Committee met in March suggests that the economy has been expanding moderately. Labor market conditions have improved in recent months; the unemployment rate has declined but remains elevated. Household spending and business fixed investment have continued to advance. Despite some signs of improvement, the housing sector remains depressed. Inflation has picked up somewhat, mainly reflecting higher prices of crude oil and gasoline. However, longer-term inflation expectations have remained stable.
Consistent with its statutory mandate, the Committee seeks to foster maximum employment and price stability. The Committee expects economic growth to remain moderate over coming quarters and then to pick up gradually. Consequently, the Committee anticipates that the unemployment rate will decline gradually toward levels that it judges to be consistent with its dual mandate. Strains in global financial markets continue to pose significant downside risks to the economic outlook. The increase in oil and gasoline prices earlier this year is expected to affect inflation only temporarily, and the Committee anticipates that subsequently inflation will run at or below the rate that it judges most consistent with its dual mandate.
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 expects to maintain a highly accommodative stance for monetary policy. In particular, the Committee decided today to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that economic conditions--including low rates of resource utilization and a subdued outlook for inflation over the medium run--are likely to warrant exceptionally low levels for the federal funds rate at least through late 2014.
The Committee also decided to continue its program to extend the average maturity of its holdings of securities as announced in September. The Committee is maintaining its existing policies of reinvesting principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities and of rolling over maturing Treasury securities at auction. The Committee will regularly review the size and composition of its securities holdings and is prepared to adjust those holdings as appropriate to promote a stronger economic recovery in a context of price stability.”
There are several important issues in this statement.
1. Mandate. The FOMC pursues a policy of attaining its “dual mandate” of (http://www.federalreserve.gov/aboutthefed/mission.htm):
“Conducting the nation's monetary policy by influencing the monetary and credit conditions in the economy in pursuit of maximum employment, stable prices, and moderate long-term interest rates”
2. Extending Average Maturity of Holdings of Securities. The statement of Apr 25, 2012, invokes the mandate that inflation is subdued but employment below maximum such that further accommodation is required. Accommodation consists of low interest rates. The new “Operation Twist” (http://cmpassocregulationblog.blogspot.com/2011_09_01_archive.html http://cmpassocregulationblog.blogspot.com/2011/09/collapse-of-household-income-and-wealth.html) or restructuring the portfolio of securities of the Fed by selling short-dated securities and buying long-term securities has the objective of reducing long-term interest rates. Lower interest rates would stimulate consumption and investment, or aggregate demand, increasing the rate of economic growth and thus reducing stress in job markets. Policy now focuses on improving conditions in real estate by attempting to reduce mortgage rates: “The Committee is maintaining its existing policies of reinvesting principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities and of rolling over maturing Treasury securities at auction.”
3. Target of Fed Funds Rate. The FOMC continues to maintain the target of fed funds rate at 0 to ¼ percent.
4. Advance Guidance. The FOMC increases transparency by advising on the expectation of the future path of fed funds rate. This guidance is the view that conditions such as “low rates of resource utilization and a subdued outlook for inflation over the medium run are likely to warrant exceptionally low levels for the federal funds rate at least through late 2014.”
5. Monitoring and Policy Focus. The FOMC reconsiders its policy continuously in accordance with available information: “The Committee will regularly review the size and composition of its securities holdings and is prepared to adjust those holdings as appropriate to promote a stronger economic recovery in a context of price stability.”
These policy statements are carefully crafted to express the intentions of the FOMC. The main objective of the statements is to communicate as clearly and firmly as possible the intentions of the FOMC to fulfill its dual mandate. During periods of low inflation and high unemployment and underemployment such as currently the FOMC may be more biased toward measures that stimulate the economy to reduce underutilization of workers and other productive resources. The FOMC also is vigilant about inflation and ready to change policy in the effort to attain its dual mandate.
The FOMC also released the economic projections of governors of the Board of Governors of the Federal Reserve and Federal Reserve Banks presidents shown in Table IV-2. The Fed releases the data with careful explanations (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20120425.pdf). Columns “∆% GDP,” “∆% PCE Inflation” and “∆% Core PCE Inflation” are changes “from the fourth quarter of the previous year to the fourth quarter of the year indicated.” The GDP report for IQ2012 is analyzed in the current post of this blog in section I. The Bureau of Economic Analysis (BEA) provides the GDP report with the second estimate for IQ2012 to be released on May 31 (http://www.bea.gov/newsreleases/national/gdp/gdpnewsrelease.htm). PCE inflation is the index of personal consumption expenditures (PCE) of the report of the Bureau of Economic Analysis (BEA) on “Personal Income and Outlays” (http://www.bea.gov/national/index.htm#personal), which is analyzed in this blog as soon as available. The next report will be released at 8:30 AM on Apr 30. PCE core inflation consists of PCE inflation excluding food and energy. Column “UNEMP %” is the rate of unemployment measured as the average civilian unemployment rate in the fourth quarter of the year. The Bureau of Labor Statistics (BLS) provides the Employment Situation Report with the civilian unemployment rate in the first Friday of every month, which is analyzed in this blog. The report for Apr will be released on May 4, 2012 (http://www.bls.gov/cps/). “Longer term projections represent each participant’s assessment of the rate to which each variable would be expected to converge under appropriate monetary policy and in the absence of further shocks to the economy” (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20120425.pdf).
It is instructive to focus on 2012, as 2013, 2014 and longer term are too far away, and there is not much information on what will happen in 2013 and beyond. The central tendency should provide reasonable approximation of the view of the majority of members of the FOMC but the second block of numbers provides the range of projections by FOMC participants. The first row for each year shows the projection introduced after the meeting of Jan 25 and the second row “Nov PR” the projection of the Nov meeting. There are three major changes in the view.
1. Growth “∆% GDP.” The FOMC has reduced the forecast of GDP growth in 2012 from 3.3 to 3.7 percent in Jun to 2.5 to 2.9 percent in Nov and 2.2 to 2.7 percent at the Jan 25 meeting but increased it to 2.4 to 2.9 percent at the Apr 25, 2012 meeting.
2. Rate of Unemployment “UNEM%.” The FOMC increased the rate of unemployment from 7.8 to 8.2 percent in Jun to 8.5 to 8.7 percent in Nov but has reduced it to 8.2 to 8.5 percent at the Jan 25 meeting and further down to 7.2 to 8.0 percent at the Apr 25, 2012 meeting.
3. Inflation “∆% PCE Inflation.” The FOMC changed the forecast of personal consumption expenditures (PCE) inflation from 1.5 to 2.0 percent in Jun to virtually the same of 1.4 to 2.0 percent in Nov but has reduced it to 1.4 to 1.8 percent at the Jan 25 meeting but increased it to 1.9 to 2.0 percent at the Apr 25, 2012 meeting.
4. Core Inflation “∆% Core PCE Inflation.” Core inflation is PCE inflation excluding food and energy. There is again not much of a difference of the projection for 2012 in Jun of 1.4 to 2.0 percent and the Nov projection of 1.5 to 2.0 percent, which has been reduced slightly to 1.5 to 1.8 percent at the Jan 25 meeting but increased to 1.5 to 1.8 percent at the Apr 25, 2012 meeting.
Table IV-2, US, Economic Projections of Federal Reserve Board Members and Federal Reserve Bank Presidents in FOMC, January 2012 and April 2012
| ∆% GDP | UNEM % | ∆% PCE Inflation | ∆% Core PCE Inflation | |
| Central | ||||
| 2012 | 2.4 to 2.9 | 7.2 to 8.0 | 1.9 to 2.0 | 1.8 to 2.0 |
| 2013 | 2.7 to 3.1 | 7.3 to 7.7 | 1.6 to 2.0 | 1.7 to 2.0 |
| 2014 | 3.1 to 3.6 | 6.7 to 7.4 | 1.7 to 2.0 | 1.8 to 2.0 |
| Longer Run Jan PR | 2.3 to 2.6 | 5.2 to 6.0 | 2.0 | |
| Range | ||||
| 2012 | 2.1 to 3.0 | 7.2 to 8.2 | 1.8 to 2.3 | 1.7 to 2.0 |
| 2013 | 2.4 to 3.8 | 7.0 to 8.1 | 1.5 to 2.1 | 1.6 to 2.1 |
| 2014 | 2.9 to 4.3 | 6.3 to 7.7 | 1.5 to 2.2 | 1.7 to 2.2 |
| Longer Run Jan PR | 2.2 to 3.0 | 4.9 to 6.0 | 2.0 |
Notes: UEM: unemployment; PR: Projection
Source: http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20120425.pdf
Another important decision at the FOMC meeting on Jan 25, 2012, is formal specification of the goal of inflation of 2 percent per year but without specific goal for unemployment (http://www.federalreserve.gov/newsevents/press/monetary/20120125c.htm):
“Following careful deliberations at its recent meetings, the Federal Open Market Committee (FOMC) has reached broad agreement on the following principles regarding its longer-run goals and monetary policy strategy. The Committee intends to reaffirm these principles and to make adjustments as appropriate at its annual organizational meeting each January.
The FOMC is firmly committed to fulfilling its statutory mandate from the Congress of promoting maximum employment, stable prices, and moderate long-term interest rates. The Committee seeks to explain its monetary policy decisions to the public as clearly as possible. Such clarity facilitates well-informed decisionmaking by households and businesses, reduces economic and financial uncertainty, increases the effectiveness of monetary policy, and enhances transparency and accountability, which are essential in a democratic society.
Inflation, employment, and long-term interest rates fluctuate over time in response to economic and financial disturbances. Moreover, monetary policy actions tend to influence economic activity and prices with a lag. Therefore, the Committee's policy decisions reflect its longer-run goals, its medium-term outlook, and its assessments of the balance of risks, including risks to the financial system that could impede the attainment of the Committee's goals.
The inflation rate over the longer run is primarily determined by monetary policy, and hence the Committee has the ability to specify a longer-run goal for inflation. The Committee judges that inflation at the rate of 2 percent, as measured by the annual change in the price index for personal consumption expenditures, is most consistent over the longer run with the Federal Reserve's statutory mandate. Communicating this inflation goal clearly to the public helps keep longer-term inflation expectations firmly anchored, thereby fostering price stability and moderate long-term interest rates and enhancing the Committee's ability to promote maximum employment in the face of significant economic disturbances.
The maximum level of employment is largely determined by nonmonetary factors that affect the structure and dynamics of the labor market. These factors may change over time and may not be directly measurable. Consequently, it would not be appropriate to specify a fixed goal for employment; rather, the Committee's policy decisions must be informed by assessments of the maximum level of employment, recognizing that such assessments are necessarily uncertain and subject to revision. The Committee considers a wide range of indicators in making these assessments. Information about Committee participants' estimates of the longer-run normal rates of output growth and unemployment is published four times per year in the FOMC's Summary of Economic Projections. For example, in the most recent projections, FOMC participants' estimates of the longer-run normal rate of unemployment had a central tendency of 5.2 percent to 6.0 percent, roughly unchanged from last January but substantially higher than the corresponding interval several years earlier.
In setting monetary policy, the Committee seeks to mitigate deviations of inflation from its longer-run goal and deviations of employment from the Committee's assessments of its maximum level. These objectives are generally complementary. However, under circumstances in which the Committee judges that the objectives are not complementary, it follows a balanced approach in promoting them, taking into account the magnitude of the deviations and the potentially different time horizons over which employment and inflation are projected to return to levels judged consistent with its mandate. ”
The probable intention of this specific inflation goal is to “anchor” inflationary expectations. Massive doses of monetary policy of promoting growth to reduce unemployment could conflict with inflation control. Economic agents could incorporate inflationary expectations in their decisions. As a result, the rate of unemployment could remain the same but with much higher rate of inflation (see Kydland and Prescott 1977 and Barro and Gordon 1983; 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). Strong commitment to maintaining inflation at 2 percent could control expectations of inflation.
The FOMC continues its efforts of increasing transparency that can improve the credibility of its firmness in implementing its dual mandate. Table IV-3 provides the views by participants of the FOMC of the levels at which they expect the fed funds rate in 2012, 2013, 2014 and the in the longer term. The table is inferred from a chart provided by the FOMC with the number of participants expecting the target of fed funds rate (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20120425.pdf). There are 14 participants expecting the rate to remain at 0 to ¼ percent in 2012 and only three to be higher. Not much change is expected in 2013 either with 11 participants anticipating the rate at the current target of 0 to ¼ percent and only six expecting higher rates. The rate would still remain at 0 to ¼ percent in 2014 for four participants with three expecting the rate to be in the range of 0.5 to 1 percent and three participants expecting rates from 1 to 2.0 percent but only 7 with rates exceeding 2.5 percent. This table is consistent with the guidance statement of the FOMC that rates will remain at low levels until late in 2014.
Table IV-3, US, Views of Target Federal Funds Rate at Year-End of Federal Reserve Board Members and Federal Reserve Bank Presidents Participating in FOMC, April 25, 2012
| 0 to 0.25 | 0.5 to 1.0 | 1.0 to 1.5 | 1.0 to 2.0 | 2.0 to 2.75 | 3.5 to 4.5 | |
| 2012 | 14 | 1 | 2 | |||
| 2013 | 11 | 1 | 3 | 2 | ||
| 2014 | 4 | 3 | 3 | 7 | ||
| Longer Run | 17 |
Source: http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20120425.pdf
Additional information is provided in Table IV-4 with the number of participants expecting increasing interest rates in the years from 2012 to 2015. It is evident from Table IV-4 that the prevailing view in the FOMC is for interest rates to continue at low levels in future years. This view is consistent with the economic projections of low economic growth, relatively high unemployment and subdued inflation provided in Table IV-2.
Table IV-4, US, Views of Appropriate Year of Increasing Target Federal Funds Rate of Federal Reserve Board Members and Federal Reserve Bank Presidents Participating in FOMC, Apr 25, 2012
| Appropriate Year of Increasing Target Fed Funds Rate | Number of Participants |
| 2012 | 3 |
| 2013 | 3 |
| 2014 | 7 |
| 2015 | 4 |
Source: http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20120425.pdf
The producer price index of the US from 1960 to 2012 in Chart IV-1 shows various periods of more rapid or less rapid inflation but no bumps. The major event is the decline in 2008 when risk aversion because of the global recession caused the collapse of oil prices from $148/barrel to less than $80/barrel with most other commodity prices also collapsing. The event had nothing in common with explanations of deflation but rather with the concentration of risk exposures in commodities after the decline of stock market indexes. Eventually, there was a flight to government securities because of the fears of insolvency of banks caused by statements supporting proposals for withdrawal of toxic assets from bank balance sheets in the Troubled Asset Relief Program (TARP), as explained by Cochrane and Zingales (2009). The bump in 2008 with decline in 2009 is consistent with the view that zero interest rates with subdued risk aversion induce carry trades into commodity futures.
Chart IV-1, US, Producer Price Index, Finished Goods, NSA, 1960-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
Chart IV-2 provides 12-month percentage changes of the producer price index from 1960 to 2012. The distinguishing event in Chart IV-2 is the Great Inflation of the 1970s. The shape of the two-hump Bactrian camel of the 1970s resembles the double hump from 2007 to 2012.
Chart IV-2, US, Producer Price Index, Finished Goods, 12-Month Percentage Change, NSA, 1960-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
The producer price index excluding food and energy from 1973 to 2012, the first historical date of availability in the dataset of the Bureau of Labor Statistics (BLS), shows similarly dynamic behavior as the overall index, as shown in Chart IV-3. There is no evidence of persistent deflation in the US PPI.
Chart IV-3, US Producer Price Index, Finished Goods Excluding Food and Energy, NSA, 1973-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
Chart IV-4 provides 12-month percentage rates of change of the finished goods index excluding food and energy. The dominating characteristic is the Great Inflation of the 1970s. The double hump illustrates how inflation may appear to be subdued and then returns with strength.
Chart IV-4, US Producer Price Index, Finished Goods Excluding Food and Energy, 12-Month Percentage Change, NSA, 1974-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
The producer price index of energy goods from 1974 to 2012 is provided in Chart IV-5. The first jump occurred during the Great Inflation of the 1970s analyzed in various comments of this blog (http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html) and in Appendix I. There is relative stability of producer prices after 1986 with another jump and decline in the late 1990s into the early 2000s. The episode of commodity price increases during a global recession in 2008 could only have occurred with interest rates dropping toward zero, which stimulated the carry trade from zero interest rates to leveraged positions in commodity futures. Commodity futures exposures were dropped in the flight to government securities after Sep 2008. Commodity future exposures were created again when risk aversion diminished around Mar 2011 after the finding that US bank balance sheets did not have the toxic assets that were mentioned in proposing TARP in Congress (see Cochrane and Zingales 2009). Fluctuations in commodity prices and other risk financial assets originate in carry trade when risk aversion ameliorates.
Chart IV-5, US, Producer Price Index, Finished Energy Goods, NSA, 1974-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
Chart IV-6 shows 12-month percentage changes of the producer price index of finished energy goods from 1975 to 2012. This index is only available after 1974 and captures only one of the humps of energy prices during the Great Inflation. Fluctuations in energy prices have occurred throughout history in the US but without provoking deflation. Two cases are the decline of oil prices in 2001 to 2002 that has been analyzed by Barsky and Kilian (2004) and the collapse of oil prices from over $140/barrel with shock of risk aversion to the carry trade in Sep 2008.
Chart IV-6, US, Producer Price Index, Finished Energy Goods, 12-Month Percentage Change, NSA, 1974-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
Headline and core producer price index are in Table IV-5. The headline PPI SA fell 0.2 percent in Apr while the 12-month rate NSA fell from 4.1 percent in Jan to 3.3 percent in Feb, 2.8 percent in Mar and 1.9 percent in Apr. The core PPI SA increased 0.2 percent in Mar and rose 2.7 percent in 12 months. Analysis of annual equivalent rates of change shows inflation waves similar to those worldwide (http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html). In the first wave, the absence of risk aversion from the sovereign risk crisis in Europe motivated the carry trade from zero interest rates into commodity futures that caused the average equivalent rate of 9.7 percent in the headline PPI in Jan-Apr and 4.0 percent in the core PPI. In the second wave, commodity futures prices collapsed in May with the return of risk aversion originating in the sovereign risk crisis of Europe. The annual equivalent rate of headline PPI inflation collapsed to 1.2 percent in May-Jul but the core annual equivalent inflation rate was much higher at 3.0 percent. In the third wave, headline PPI inflation resuscitated with annual equivalent at 6.6 percent in Jul-Sep and core PPI inflation at 4.1 percent. Core PPI inflation was persistent throughout 2011, jumping from annual equivalent at 2.4 percent in the first four months of 2010 to 2.7 percent in 12 months ending in Apr 2012 and 3.4 percent in annual equivalent rate in Dec 2011 to Mar 2012. Unconventional monetary policy is based on the proposition that core rates reflect more fundamental inflation and are thus better predictors of the future. In practice, the relation of core and headline inflation is as difficult to predict as future inflation (see IIID Supply Shocks in http://cmpassocregulationblog.blogspot.com/2011_05_01_archive.html). In the fourth wave, risk aversion originating in the lack of resolution of the European debt crisis caused unwinding of carry trades with annual equivalent headline PPI inflation of minus 1.2 percent in Oct-Nov and 0.6 percent in the core annual equivalent. In the fifth wave from Dec 2011 to Jan 2012, annual equivalent inflation was 0.6 percent for the headline index but 3.7 percent for the core index excluding food and energy. In the sixth wave, headline annual equivalent inflation in Feb-Apr was 0.8 percent for the headline PPI and 2.8 percent for the core. It is impossible to forecast PPI inflation and its relation to CPI inflation. “Inflation surprise” by monetary policy could be proposed to climb along a downward sloping Phillips curve, resulting in higher inflation but lower unemployment (see Kydland and Prescott 1977, Barro and Gordon 1983 and past comments of this blog 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). The architects of monetary policy would require superior inflation forecasting ability compared to forecasting naivety by everybody else. In practice, we are all naïve in forecasting inflation and other economic variables and events.
Table IV-5, US, Headline and Core PPI Inflation Monthly SA and 12-Month NSA ∆%
| Finished | Finished | Finished Core SA | Finished Core NSA | |
| Apr 2012 | -0.2 | 1.9 | 0.2 | 2.7 |
| Mar | 0.0 | 2.8 | 0.3 | 2.9 |
| Feb | 0.4 | 3.3 | 0.2 | 3.0 |
| AE ∆% Feb-Apr | 0.8 | 2.8 | ||
| Jan | 0.2 | 4.1 | 0.4 | 3.0 |
| Dec 2011 | -0.1 | 4.7 | 0.2 | 3.0 |
| AE ∆% Dec-Jan | 0.6 | 3.7 | ||
| Nov | 0.1 | 5.6 | 0.1 | 3.0 |
| Oct | -0.3 | 5.8 | 0.0 | 2.9 |
| AE ∆% Oct-Nov | -1.2 | 0.6 | ||
| Sep | 0.9 | 7.0 | 0.3 | 2.8 |
| Aug | 0.2 | 6.6 | 0.2 | 2.7 |
| Jul | 0.5 | 7.1 | 0.5 | 2.7 |
| AE ∆% Jul-Sep | 6.6 | 4.1 | ||
| Jun | 0.1 | 6.9 | 0.3 | 2.3 |
| May | 0.1 | 7.1 | 0.2 | 2.1 |
| AE ∆% May-Jul | 1.2 | 3.0 | ||
| Apr | 0.7 | 6.6 | 0.3 | 2.3 |
| Mar | 0.5 | 5.6 | 0.3 | 2.0 |
| Feb | 1.1 | 5.4 | 0.2 | 1.8 |
| Jan | 0.8 | 3.6 | 0.5 | 1.6 |
| AE ∆% Jan-Apr | 9.7 | 4.0 | ||
| Dec 2010 | 0.9 | 3.8 | 0.2 | 1.4 |
| Nov | 0.4 | 3.4 | -0.1 | 1.2 |
| Oct | 0.8 | 4.3 | -0.2 | 1.6 |
| Sep | 0.4 | 3.9 | 0.2 | 1.6 |
| Aug | 0.7 | 3.3 | 0.2 | 1.3 |
| Jul | 0.2 | 4.1 | 0.2 | 1.5 |
| Jun | -0.2 | 2.7 | 0.1 | 1.1 |
| May | -0.2 | 5.1 | 0.3 | 1.3 |
| Apr | -0.1 | 5.4 | 0.1 | 0.9 |
| Mar | 0.5 | 5.9 | 0.2 | 0.9 |
| Feb | -0.6 | 4.2 | 0.0 | 1.0 |
| Jan | 1.0 | 4.5 | 0.3 | 1.0 |
Note: Core: excluding food and energy; AE: annual equivalent
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
The US producer price index NSA from 2001 to 2012 is shown in Chart IV-7. There are two episodes of decline of the PPI during recessions in 2001 and in 2008. Barsky and Kilian (2004) consider the 2001 episode as one in which real oil prices were declining when recession began. Recession and the fall of commodity prices instead of generalized deflation explain the behavior of US inflation in 2008.
Chart IV-7, US, Producer Price Index, NSA, 2000-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
Twelve-month percentage changes of the PPI NSA from 2001 to 2012 are shown in Chart IV-8. It may be possible to forecast trends a few months in the future under adaptive expectations but turning points are almost impossible to anticipate especially when related to fluctuations of commodity prices in response to risk aversion. In a sense, monetary policy has been tied to behavior of the PPI in the negative 12-month rates in 2001 to 2003 and then again in 2009 to 2010. Monetary policy following deflation fears caused by commodity price fluctuations would introduce significant volatility and risks in financial markets and eventually in consumption and investment.
Chart IV-8, US, Producer Price Index, 12-Month Percentage Change NSA, 2000-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
The US PPI excluding food and energy from 2001 to 2012 is shown in Chart IV-9. There is here again a smooth trend of inflation instead of prolonged deflation as in Japan.
Chart IV-9, US, Producer Price Index Excluding Food and Energy, NSA, 2000-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
Twelve-month percentage changes of the producer price index excluding food and energy are shown in Chart IV-10. Fluctuations replicate those in the headline PPI. There is an evident trend of increase of 12 months rates of core PPI inflation in 2011 and in the firth month of 2012 but lower rates in the beginning of 2012.
Chart IV-10, US, Producer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2000-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
The US producer price index of energy goods from 2001 to 2012 is in Chart IV-11. There is a clear upward trend with fluctuations that would not occur under persistent deflation.
Chart IV-11, US, Producer Price Index Finished Energy Goods, NSA, 2000-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
Chart IV-12 provides 12-month percentage changes of the producer price index of energy goods from 2001 to 2012. The episode of declining prices of energy goods in 2001 to 2002 is related to the analysis of decline of real oil prices by Barsky and Kilian (2004). Interest rates dropping to zero during the global recession explain the rise of the PPI of energy goods toward 30 percent. Bouts of risk aversion with policy interest rates held close to zero explain the fluctuations in the 12-month rates of the PPI of energy goods in the expansion phase of the economy. Symmetric inflation targets induce significant instability in inflation and interest rates with adverse effects on financial markets and the overall economy.
Chart IV-12, US, Producer Price Index Energy Goods, 12-Month Percentage Change, NSA, 2000-2012
Source: US Bureau of Labor Statistics
http://www.bls.gov/ppi/data.htm
China is experiencing similar inflation behavior as the advanced economies, as shown in Table IV-6. Inflation of the price indexes for industry in Apr 2012 is 0.2 percent; 12-month inflation is minus 0.7 percent in Apr; and inflation in Jan-Apr 2012 relative to Jan-Apr 2011 is minus 0.1 percent. Drivers of inflation in Apr 2012 in China are provided in Table IV-6 in column “Month Apr ∆%.” There were increases of prices of mining & quarrying of 1.2 percent in Apr and 2.2 percent in 12 months. Consumer goods increased 0.1 percent in Apr and increased 1.1 percent in 12 months. Prices of inputs in the purchaser price index were flat in Apr and fell 0.8 percent in 12 months. Fuel and power increased 0.7 percent and 3.4 percent in 12 months. An important category of inputs for exports is textile raw materials, decreasing 0.2 percent in Apr and increasing 0.7 percent in Jan-Apr 2012 relative to the same period a year earlier.
Table IV-6, China, Price Indexes for Industry ∆%
| Month Apr ∆% | 12-Month Apr ∆% | Jan-Apr 2012/Jan-Apr 2011 ∆% | |
| I Producer Price Indexes | 0.2 | -0.7 | -0.1 |
| Means of Production | 0.2 | -1.2 | -0.6 |
| Mining & Quarrying | 1.2 | 2.2 | 4.1 |
| Raw Materials | 0.4 | 0.1 | 1.0 |
| Processing | 0.0 | -2.2 | -1.7 |
| Consumer Goods | 0.1 | 1.1 | 1.6 |
| Food | 0.3 | 2.2 | 2.7 |
| Clothing | 0.2 | 2.1 | 2.7 |
| Daily Use Articles | 0.2 | 1.1 | 1.3 |
| Durable Consumer Goods | -0.3 | -1.1 | -0.6 |
| II Purchaser Price Indexes | 0.0 | -0.8 | 0.6 |
| Fuel and Power | 0.7 | 3.4 | 5.3 |
| Ferrous Metals | -0.1 | -4.7 | -3.4 |
| Nonferrous Metals | -0.8 | -5.7 | -3.9 |
| Raw Chemical Materials | -0.2 | -3.0 | -1.4 |
| Wood & Pulp | 0.2 | 0.8 | 1.3 |
| Building Materials | -0.3 | 1.3 | 2.2 |
| Other Industrial Raw Materials | -0.1 | -0.9 | 0.0 |
| Agricultural | 0.1 | 0.5 | 1.8 |
| Textile Raw Materials | -0.2 | -0.9 | 0.7 |
Source: National Bureau of Statistics of China http://www.stats.gov.cn/english/pressrelease/t20120511_402804993.htm
China’s producer price inflation follows waves similar to those around the world (http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html), as shown in Table IV-7. In the first wave, annual equivalent inflation was 6.4 percent in Jan-Jun, driven by carry trades from zero interest rates to commodity futures. In the second wave, risk aversion unwound carry trades, resulting in annual equivalent inflation of minus 3.1 percent in Jul-Nov. In the third wave, renewed risk aversion resulted in annual equivalent inflation of minus 2.4 percent in Dec-Jan. In the fourth wave, new carry trades resulted in annual equivalent inflation of 2.4 percent in Feb-Apr 2012.
Table IV-7, China, Month and 12-Month Rate of Change of Producer Price Index, ∆%
| 12-Month ∆% | Month ∆% | |
| Apr 2012 | -0.7 | 0.2 |
| Mar | -0.3 | 0.3 |
| Feb | 0.0 | 0.1 |
| AE ∆% Feb-Apr | 2.4 | |
| Jan | 0.7 | -0.1 |
| Dec 2011 | 1.7 | -0.3 |
| AE ∆% Dec-Jan | -2.4 | |
| Nov | 2.7 | -0.7 |
| Oct | 5.0 | -0.7 |
| Sep | 6.5 | 0.0 |
| Aug | 7.3 | 0.1 |
| Jul | 7.5 | 0.0 |
| AE ∆% Jul-Nov | -3.1 | |
| Jun | 7.1 | 0.0 |
| May | 6.8 | 0.3 |
| Apr | 6.8 | 0.5 |
| Mar | 7.3 | 0.6 |
| Feb | 7.2 | 0.8 |
| Jan | 6.6 | 0.9 |
| AE ∆% Jan-Jun | 6.4 | |
| Dec 2010 | 5.9 | 0.7 |
AE: Annual Equivalent
Source: National Bureau of Statistics of China
http://www.stats.gov.cn/english/pressrelease/t20120511_402804993.htm
Chart IV-13 of the National Bureau of Statistics of China provides monthly and 12-month rates of inflation of the price indexes for the industrial sector. Negative monthly rates in Oct, Nov, Dec, Jan and Mar pulled down the 12-month rates to 5.0 percent in Oct, 2.7 percent in Nov, 1.7 percent in Dec, 0.7 percent in Jan, 0.0 percent in Feb, minus 0.3 percent in Mar and minus 0.7 percent in Apr.
Chart IV-13, China, Producer Prices for the Industrial Sector Month and 12 months ∆%
Source: National Bureau of Statistics of China
http://www.stats.gov.cn/english/pressrelease/t20120511_402804993.htm
Chart IV-14 of the National Bureau of Statistics of China provides monthly and 12-month inflation of the purchaser product indices for the industrial sector. Decreasing monthly inflation with four successive contractions from Oct to Jan pulled down the 12-month rate to minus 0.8 percent in Apr.
Chart IV-14, China, Purchaser Product Indices for Industrial Sector
Source: National Bureau of Statistics of China http://www.stats.gov.cn/english/pressrelease/t20120511_402804993.htm
China is highly conscious of food price inflation because of its high weight in the basket of consumption of the population. Consumer price inflation in China in Apr was minus 0.1 percent and 3.4 percent in 12 months, as shown in Table IV-8. Food prices fell 0.9 percent in Apr but increased 7.0 percent in 12 months and 7.8 percent in Jan-Apr 2012 relative to Jan-Apr 2011. Another area of concern is housing inflation of 0.2 percent in Apr and 1.8 percent in 12 months. Prices of services increased 0.5 percent in Apr and gained 1.7 percent in 12 months.
Table IV-8, China, Consumer Price Index
| 2012 | Apr Month ∆% | Apr 12- Month ∆% | Jan-Apr 2012 ∆% Jan-Apr 2011 |
| Consumer Prices | -0.1 | 3.4 | 3.7 |
| Urban | 0.0 | 3.4 | 3.7 |
| Rural | -0.2 | 3.3 | 3.7 |
| Food | -0.9 | 7.0 | 7.8 |
| Non-food | 0.3 | 1.7 | 1.8 |
| Consumer Goods | -0.3 | 4.1 | 4.5 |
| Services | 0.5 | 1.7 | 1.7 |
| Commodity Categories: | |||
| Food | -0.9 | 7.0 | 7.8 |
| Tobacco, Liquor | 0.2 | 3.4 | 3.6 |
| Clothing | 0.5 | 3.6 | 3.6 |
| Household | 0.2 | 2.2 | 2.4 |
| Healthcare & Personal Articles | 0.2 | 2.5 | 2.6 |
| Transportation & Communication | 0.4 | 0.3 | 0.2 |
| Recreation, Education, Culture & Services | 0.6 | 0.3 | 0.2 |
| Residence | 0.2 | 1.8 | 2.0 |
Source: National Bureau of Statistics of China http://www.stats.gov.cn/english/pressrelease/t20120511_402804992.htm
Month and 12-month rates of change of consumer prices are provided in Table IV-9. There are waves of consumer price inflation in China similar to those around the world (http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html). In the first wave, consumer prices increased at the annual equivalent rate of 8.3 percent in Jan-Mar 2011, driven by commodity price increases resulting from unconventional monetary policy of zero interest rates. In the second wave, risk aversion unwound carry trades with annual equivalent inflation falling to the rate of 2.0 percent in Apr-Jun. In the third wave, inflation returned at 2.9 percent with renewed interest in commodity exposures in Jul-Nov. In the fourth wave, inflation returned at a high 4.4 percent annual equivalent in Dec 2011 to Apr 2012.
Table IV-9, China, Month and 12-Month Rates of Change of Consumer Price Index ∆%
| Month ∆% | 12-Month ∆% | |
| Apr 2012 | -0.1 | 3.4 |
| Mar | 0.2 | 3.6 |
| Feb | -0.1 | 3.2 |
| Jan | 1.5 | 4.5 |
| Dec 2011 | 0.3 | 4.1 |
| AE ∆% Dec to Apr | 4.4 | |
| Nov | -0.2 | 4.2 |
| Oct | 0.1 | 5.5 |
| Sep | 0.5 | 6.1 |
| Aug | 0.3 | 6.2 |
| Jul | 0.5 | 6.5 |
| AE ∆% Jul to Nov | 2.9 | |
| Jun | 0.3 | 6.4 |
| May | 0.1 | 5.5 |
| Apr | 0.1 | 5.3 |
| AE ∆% Apr to Jun | 2.0 | 2.0 |
| Mar | -0.2 | 5.4 |
| Feb | 1.2 | 4.9 |
| Jan | 1.0 | 4.9 |
| AE ∆% Jan to Mar | 8.3 | |
| Dec 2010 | 0.5 | 4.6 |
AE: Annual Equivalent
Source: National Bureau of Statistics of China
http://www.stats.gov.cn/english/pressrelease/t20120511_402804992.htm
Chart IV-15 of the National Bureau of Statistics of China provides monthly and 12-month rates of consumer price inflation. In contrast with producer prices, consumer prices had not moderated at the monthly marginal rates. Consumer prices fell 0.2 percent in Nov after increasing only 0.1 percent in Oct but increased 0.3 percent in Dec and a high 1.5 percent in Jan, declining 0.1 percent in Feb, rising 0.2 percent in Mar and declining 0.1 percent in Apr. The decline of 0.1 percent in Feb pulled down the 12-month rate to 3.2 percent, which bounced back to 3.6 percent in Mar with the monthly increase of 0.2 percent and fell to 3.4 percent in Apr with the monthly decrease of 0.1 percent.
Chart IV-15, China, Consumer Prices ∆% Month and 12 Months Aug 2010 to Aug 2011
Source: National Bureau of Statistics of China
http://www.stats.gov.cn/english/pressrelease/t20120511_402804992.htm
There are waves of consumer price inflation in Germany similar to those worldwide (http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html), as shown in Table IV-10. In the first wave, annual equivalent inflation was 4.9 percent in Feb-Apr 2011 during risk appetite in carry trades from zero interest rates to commodity futures. In the second wave, annual equivalent consumer price inflation collapsed to 0.6 percent in May-Jun because of risk aversion caused by European sovereign debt. In the third wave, annual equivalent consumer price inflation was 1.2 percent in Jul-Nov as a result of relaxed risk aversion. In the fourth wave, annual equivalent inflation was 1.8 percent in Dec 2011 to Jan 2012. In the fifth wave, annual equivalent inflation rose to 4.9 percent in Feb-Apr during another energy-commodity carry trade shock.
Table IV-10, Germany, Consumer Price Index ∆%
| 12-Month ∆% | Month ∆% | |
| Apr 2012 | 2.1 | 0.2 |
| Mar | 2.1 | 0.3 |
| Feb | 2.3 | 0.7 |
| AE ∆% Feb-Apr | 4.9 | |
| Jan | 2.1 | -0.4 |
| Dec 2011 | 2.1 | 0.7 |
| AE ∆% Dec-Jan | 1.8 | |
| Nov | 2.4 | 0.0 |
| Oct | 2.5 | 0.0 |
| Sep | 2.6 | 0.1 |
| Aug | 2.4 | 0.0 |
| Jul | 2.4 | 0.4 |
| AE ∆% Jul-Nov | 1.2 | |
| Jun | 2.3 | 0.1 |
| May | 2.3 | 0.0 |
| AE ∆% May-Jun | 0.6 | |
| Apr | 2.4 | 0.2 |
| Mar | 2.1 | 0.5 |
| Feb | 2.1 | 0.5 |
| Jan | 2.0 | -0.4 |
| AE ∆% Feb-Apr | 4.9 | |
| Dec 2010 | 1.7 | 1.0 |
| Nov | 1.5 | 0.1 |
| Oct | 1.3 | 0.1 |
| Sep | 1.3 | -0.1 |
| Aug | 1.0 | 0.0 |
| Annual Average ∆% | ||
| 2011 | 2.3 | |
| 2010 | 1.1 | |
| 2009 | 0.4 | |
| 2008 | 2.6 |
AE: Annual Equivalent
Source: Statistiche Bundesamt Deutschland https://www.destatis.de/EN/PressServices/Press/pr/2012/05/PE12_160_611.html;jsessionid=A360E21B236D71AF14803853285C6843.cae1
https://www.destatis.de/DE/ZahlenFakten/Indikatoren/Konjunkturindikatoren/Konjunkturindikatoren.html
Chart IV-16, of the Statistiche Bundesamt Deutschland, or Federal Statistical Agency of Germany, provides the unadjusted consumer price index of Germany from 2003 to 2012. There is an evident acceleration in the form of sharper slope in the first months of 2011 and then a flattening in subsequent months with renewed strength in Dec, decline in Jan 2012 and another upward spike from Feb to Apr 2012. If risk aversion declines, new carry trades from zero interest rates to commodity futures could again result in higher inflation.
Chart IV-16, Germany, Consumer Price Index, Unadjusted, 2005=100
Source: Statistiche Bundesamt Deutschland
https://www.destatis.de/DE/ZahlenFakten/Indikatoren/Konjunkturindikatoren/Konjunkturindikatoren.html
Chart IV-17 of the Statistiche Bundesamt Deutschland, or Federal Statistical Agency of Germany, provides the unadjusted consumer price index of Germany and trend from 2007 to 2012. Inflation moderated during the global recession but regained the sharper slope with the new carry trades from zero interest rates to commodity futures beginning in 2010. The annual equivalent rate of 6.2 percent in Feb-Mar 2012 or 4.9 percent in Feb-Apr is pulling up the trend.
Chart IV-17, Germany, Consumer Price Index, Unadjusted and Trend, 2005=100
Source: Statistiche Bundesamt Deutschland
https://www.destatis.de/DE/ZahlenFakten/Indikatoren/Konjunkturindikatoren/Konjunkturindikatoren.html
Table IV-11 provides the monthly and 12-month rate of inflation for segments of the consumer price index in Apr 2012. Inflation excluding energy increased 0.1 percent in Apr 2012 and rose 1.5 percent in 12 months. Excluding household energy inflation increased 0.1 percent in Apr and rose 1.7 percent in 12 months. There were price increases across categories such as 0.2 percent in nondurable consumer goods and 0.1 percent in services. There were differences in inflation of energy-related prices. Heating oil rose 5.6 percent in 12 months but fell 1.9 percent in Apr. Motor fuels increased 1.2 percent in Apr and 6.3 percent in 12 months.
Table IV-11, Germany, Consumer Price Index ∆%
| Apr 2012 | Weight | 12- Month ∆% | Month ∆% |
| Total | 1,000.00 | 2.1 | 0.2 |
| Excluding heating oil and motor fuels | 955.42 | 1.7 | 0.1 |
| Excluding household energy | 940.18 | 1.7 | 0.1 |
| Excluding Energy | 904.81 | 1.5 | 0.1 |
| Total Goods | 493.00 | 3.1 | 0.2 |
| Nondurable Consumer Goods | 305.11 | 3.9 | 0.2 |
| Medium-Term Life Consumer Goods | 95.24 | 2.3 | 0.1 |
| Durable Consumer Goods | 97.3 | 0.1 | 0.0 |
| Services | 507.00 | 1.0 | 0.1 |
| Energy Components | |||
| Motor Fuels | 35.37 | 6.3 | 1.2 |
| Household Energy | 59.82 | 5.5 | 0.0 |
| Heating Oil | 9.21 | 5.6 | -1.9 |
| Food | 89.99 | 3.0 | -0.1 |
Source: Statistiche Bundesamt Deutschland https://www.destatis.de/EN/PressServices/Press/pr/2012/05/PE12_160_611.html;jsessionid=A360E21B236D71AF14803853285C6843.cae1
Inflation in the UK is somewhat higher than in many advanced economies, deserving more detailed analysis. Table IV-12 provides 12-month percentage changes of UK output prices for all manufactured products, excluding food, beverage and petroleum and excluding duty. The 12-month rates rose significantly in 2011 in all three categories, reaching 6.3 percent for all manufactured products in Sep 2011 but declining to 5.7 percent in Oct, 5.4 in Nov and down to 3.3 percent in Apr 2012. Output price inflation is highly sensitive to commodity prices as shown by the increase by 6.7 percent in 2008 when oil prices rose over $140/barrel even in the midst of a global recession driven by the carry trade from zero interest rates to oil futures. The mirage episode of false deflation in 2001 and 2002 is also captured by the output prices for the UK, which was originated in decline of commodity prices but was used as an argument for the unconventional monetary policy of zero interest rates and quantitative easing during the past decade.
Table IV-12, UK Output Prices 12 Months ∆% NSA
| All Manufactured Products | Excluding Food, Beverage and | All Excluding Duty | |
| Apr 2012 | 3.3 | 2.3 | 3.2 |
| Mar 2012 | 3.7 | 2.5 | 3.5 |
| Feb | 4.1 | 3.0 | 4.1 |
| Jan | 4.0 | 2.4 | 4.0 |
| Dec 2011 | 4.8 | 3.0 | 4.8 |
| Nov | 5.4 | 3.1 | 5.6 |
| Oct | 5.7 | 3.3 | 5.9 |
| Sep | 6.3 | 3.7 | 6.4 |
| Aug | 6.0 | 3.5 | 6.2 |
| Jul | 6.1 | 3.4 | 6.2 |
| Jun | 5.8 | 3.2 | 5.9 |
| May | 5.4 | 3.4 | 5.5 |
| Apr | 5.6 | 3.6 | 5.8 |
| Mar | 5.6 | 3.1 | 5.5 |
| Feb | 5.3 | 3.1 | 5.2 |
| Jan | 5.0 | 3.3 | 5.0 |
| Dec 2010 | 4.2 | 2.7 | 4.0 |
| Year ∆% | Ex Food | ||
| 2011 | 5.6 | 3.4 | 5.7 |
| 2010 | 4.2 | 3.0 | 3.9 |
| 2009 | 1.6 | 2.5 | 1.0 |
| 2008 | 6.7 | 3.7 | 6.7 |
| 2007 | 2.3 | 1.4 | 2.1 |
| 2006 | 2.0 | 1.5 | 2.0 |
| 2005 | 1.9 | 1.0 | 1.9 |
| 2004 | 1.0 | -0.3 | 0.6 |
| 2003 | 0.6 | 0.1 | 0.5 |
| 2002 | -0.1 | -0.4 | -0.1 |
| 2001 | -0.3 | -0.6 | -0.3 |
| 2000 | 1.4 | -0.5 | 0.8 |
| 1999 | 0.6 | -1.0 | -0.3 |
| 1998 | 0.0 | -0.8 | -0.9 |
| 1997 | 0.9 | 0.3 | 0.1 |
Source: http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/april-2012/index.html
Monthly and annual equivalent rates of change of output prices are shown in Table IV-13. There are waves of inflation similar to those in other countries (http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html). In the first wave, annual equivalent inflation was 12.0 percent in Jan-Apr with relaxed risk aversion in commodity markets. In the second wave, intermittent risk aversion resulted in annual equivalent inflation of 2.0 percent in May-Oct. In the third wave, alternation of risk aversion resulted in annual equivalent inflation of 1.6 percent in Nov-Jan. In the fourth wave, the energy commodity shock caused by carry trades caused the jump of annual equivalent inflation to 7.9 percent in Feb-Apr 2012.
Table IV-13, UK Output Prices Month ∆% NSA
| All Manufactured Products | Excluding Food, Beverage and | All Excluding Duty | |
| Apr 2012 | 0.7 | 0.6 | 0.6 |
| Mar | 0.6 | 0.1 | 0.5 |
| Feb | 0.6 | 0.5 | 0.6 |
| ∆% AE Feb-Apr | 7.9 | 4.9 | 7.0 |
| Jan | 0.4 | 0.3 | 0.3 |
| Dec 2011 | -0.2 | -0.1 | -0.2 |
| Nov | 0.2 | -0.1 | 0.2 |
| ∆% AE Nov-Jan | 1.6 | 0.4 | 1.2 |
| Oct | 0.0 | -0.1 | 0.1 |
| Sep | 0.3 | 0.3 | 0.2 |
| Aug | 0.0 | 0.1 | 0.1 |
| Jul | 0.3 | 0.4 | 0.3 |
| Jun | 0.2 | 0.2 | 0.2 |
| May | 0.2 | 0.2 | 0.2 |
| ∆% AE May-Oct | 2.0 | 2.2 | 2.2 |
| Apr | 1.1 | 0.8 | 0.9 |
| Mar | 1.1 | 0.5 | 1.1 |
| Feb | 0.5 | 0.0 | 0.5 |
| Jan | 1.1 | 0.8 | 1.1 |
| Jan-Apr | 12.0 | 6.5 | 11.4 |
| Dec 2010 | 0.5 | 0.0 | 0.6 |
Source:
http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/april-2012/index.html
Input prices in the UK have been more dynamic than output prices, as shown by Table IV-14. The 12-month rates of increase of input prices, even excluding food, tobacco, beverages and petroleum, are very high, reaching 18.1 percent in Sep 2011 for materials and fuels purchased and 13.3 percent excluding food, beverages and petroleum. Inflation in 12 months of materials and fuels purchased moderated to 5.6 percent in Mar 2012 and 4.2 percent excluding food, tobacco, beverages and petroleum with the rates falling further in Apr to 1.2 percent for materials and fuels purchased and 2.5 percent excluding food, tobacco, beverages and petroleum. There is only comparable experience with 22.2 percent inflation of materials and fuels purchased in 2008 and 16.9 percent excluding food, beverages and petroleum followed by decline of 3.8 percent by materials and fuels purchased and increase of 1.6 percent for the index excluding items. UK input and output inflation is sensitive to commodity price increases driven by carry trades from zero interest rates. The mirage of false deflation is also observed in input prices in 1997-9 and then again from 2001 to 2003.
Table IV-14, UK Input Prices 12 Months ∆% NSA
| Materials and Fuels Purchased | Excluding Food, Tobacco, Beverages and Petroleum | |
| Apr 2012 | 1.2 | 2.5 |
| Mar | 5.6 | 4.2 |
| Feb | 7.9 | 5.7 |
| Jan | 6.6 | 5.6 |
| Dec 2011 | 8.9 | 7.2 |
| Nov | 13.8 | 10.2 |
| Oct | 14.5 | 11.0 |
| Sep | 18.1 | 13.3 |
| Aug | 16.3 | 13.0 |
| Jul | 18.5 | 13.3 |
| Jun | 16.8 | 12.6 |
| May | 16.3 | 11.4 |
| Apr | 17.9 | 12.2 |
| Mar | 14.8 | 10.3 |
| Feb | 14.9 | 10.7 |
| Jan | 14.2 | 10.5 |
| Dec 2010 | 13.1 | 9.0 |
| Year ∆% | ||
| 2011 | 15.4 | 11.4 |
| 2010 | 9.9 | 5.7 |
| 2009 | -3.8 | 1.6 |
| 2008 | 22.2 | 16.9 |
| 2007 | 2.9 | 2.3 |
| 2006 | 9.8 | 7.3 |
| 2005 | 10.9 | 6.9 |
| 2004 | 3.3 | 1.6 |
| 2003 | 1.2 | -0.6 |
| 2002 | -4.4 | -4.8 |
| 2001 | -1.2 | -1.2 |
| 2000 | 7.4 | 3.7 |
| 1999 | -1.3 | -3.6 |
| 1998 | -9.1 | -4.6 |
| 1997 | -8.2 | -6.3 |
Source: http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/april-2012/index.html
Table IV-15 provides monthly percentage changes of UK input prices for materials and fuels purchased and excluding food, tobacco, beverages and petroleum. There are strong waves of inflation of input prices in the UK similar to those worldwide (http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html). In the first wave, input prices rose at the high annual equivalent rate of 35.6 percent in Jan-Apr 2011, driven by carry trades from unconventional monetary policy into commodity exposures. In the second wave, alternating risk aversion caused annual equivalent inflation of minus 3.1 percent in May-Oct. In the third wave, renewed risk aversion resulted in annual equivalent inflation of minus 1.2 percent in Nov-Dec. In the fourth wave, annual equivalent inflation of input prices in the UK surged at 8.9 percent in Jan-Apr under relaxed risk aversion. Annual equivalent inflation was 19.0 percent in Jan-Mar.
Table IV-15, UK Input Prices Month ∆%
| Materials and Fuels Purchased NSA | Excluding Food, Tobacco, Beverages and Petroleum SA | |
| Apr 2012 | -1.5 | 0.3 |
| Mar | 1.7 | -0.4 |
| Feb | 2.5 | 1.0 |
| Jan | 0.2 | -0.1 |
| ∆% AE Jan-Apr | 8.9 | 2.4 |
| Dec 2011 | -0.6 | -0.7 |
| Nov | 0.4 | 0.1 |
| ∆% AE Nov-Dec | -1.2 | -3.6 |
| Oct | -0.8 | -0.4 |
| Sep | 2.1 | 0.7 |
| Aug | -1.9 | 0.2 |
| Jul | 0.6 | 0.8 |
| Jun | 0.1 | 0.9 |
| May | -1.6 | -0.1 |
| ∆% AE May-Oct | -3.1 | 4.3 |
| Apr | 2.8 | 2.0 |
| Mar | 3.8 | 1.0 |
| Feb | 1.4 | 1.0 |
| Jan | 2.3 | 1.5 |
| ∆% AE Jan-Apr | 35.6 | 17.8 |
| Dec 2010 | 3.9 | 1.9 |
Source: http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/april-2012/index.html
The UK Office for National Statistics also provides contributions in percentage points to the monthly and 12-month rates of inflation of manufactured products, shown in Table IV-16. Petroleum is the third largest contributor with 0.44 percentage points to the 12-month rate behind 0.58 percentage points contributed by food products and 0.74 percentage points by tobacco and alcohol. There are diversified sources of contributions to 12 months output price inflation such as 0.44 percentage points by clothing, textile and leather and 0.14 percentage points by chemical and pharmaceutical. In general, contributions by products rich in commodities are the drivers of inflation. There were diversified contributions in percentage points to monthly inflation: 0.23 by tobacco and alcohol, 0.21 by computer, electrical and optical, 0.11 by transport equipment by petroleum and 0.07 by petroleum.
Table IV-16, Contributions to Month and 12-Month Change in Prices of All Manufactured Products, Percentage Points
| Apr 2012 | 12 Months | 12 Months ∆% | Month % Points | Month ∆% |
| Total % | 3.3 | 3.3 | 0.7 | 0.7 |
| Food Products | 0.58 | 3.6 | 0.05 | 0.2 |
| Tobacco & Alcohol | 0.74 | 7.2 | 0.23 | 2.2 |
| Clothing, Textile & Leather | 0.24 | 2.2 | -0.05 | -0.4 |
| Paper and Printing | 0.04 | 1.1 | 0.01 | 0.1 |
| Petroleum | 0.44 | 3.7 | 0.07 | 0.5 |
| Chemical & Pharmaceutical | 0.14 | 1.6 | 0.03 | 0.4 |
| Metal, Machinery & Equipment | 0.06 | 1.8 | 0.00 | 0.1 |
| Computer, Electrical & Optical | 0.26 | 3.0 | 0.21 | 2.4 |
| Transport Equipment | 0.15 | 1.5 | 0.11 | 1.2 |
| Other Manufactured Products | 0.66 | 4.0 | 0.05 | 0.2 |
Source: http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/april-2012/index.html
The UK Office for National Statistics also provides contributions in percentage points to the monthly and 12-month rates of inflation of input prices, shown in Table IV-17. Crude oil is the large contributor with 0.79 percentage points to the 12-month rate but minus 1.44 percentage points to the monthly rate in Apr. Inflation also transfers to the domestic economy through the prices of imported inputs: other imported materials contributed 0.75 percentage points to the 12-month rate and 0.13 percentage points to the April rate.
Table IV-17, UK, Contributions to Month and 12-Month Change in Prices of Inputs, Percentage Points
| Apr 2012 | 12 Months | 12 Months ∆% | Month % Points | Month ∆% |
| Total | 1.2 | 1.2 | -1.5 | -1.5 |
| Fuel | 0.79 | 8.7 | -0.01 | -0.1 |
| Crude Oil | -0.05 | -0.2 | -1.44 | -4.8 |
| Domestic Food Materials | -0.20 | -1.9 | -0.04 | 0.4 |
| Imported Food Materials | 0.23 | 4.6 | 0.01 | 0.2 |
| Other Domestic Produced Materials | 0.11 | 3.0 | 0.03 | 0.9 |
| Imported Metals | -0.58 | -6.8 | -0.14 | -1.8 |
| Imported Chemicals | 0.07 | 0.7 | 0.01 | 0.1 |
| Imported Parts and Equipment | 0.06 | 0.5 | -0.13 | -0.9 |
| Other Imported Materials | 0.75 | 7.8 | 0.13 | 1.3 |
Source: http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/april-2012/index.html
© Carlos M. Pelaez, 2010, 2011, 2012
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