Sunday, April 15, 2012

The Fractured Labor Market with Hiring Collapse, Ten Million Fewer Full-Time Jobs, Youth Unemployment, World Inflation Waves and Global Financial and Economic Risk: Part I

 

The Fractured Labor Market with Hiring Collapse, Ten Million Fewer Full-Time Jobs, Youth Unemployment, World Inflation Waves and Global Financial and Economic Risk

Carlos M. Pelaez

© Carlos M. Pelaez, 2010, 2011, 2012

Executive Summary

I World Inflation Waves

IA World Inflation Waves

IB United States Inflation

IB1 Long-term US Inflation

IB2 Current US Inflation

IB3 Import Export Prices

II Hiring Collapse

IIA Hiring Collapse

IIB Labor Underutilization

IIC Ten Million Fewer Full-time Jobs

IID Youth Unemployment

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 (http://cmpassocregulationblog.blogspot.com/2012/04/thirty-million-unemployed-or.html) 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. 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.

ESII 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 ESII-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 ten 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-economic-growth-falling-real.html). 

Table ESII-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 ESII-1 provides the yearly levels of total nonfarm hiring (NFH) in Table II-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.

clip_image002

Chart ESII-1, US, Total Nonfarm Hiring (HNF), Yearly, 2001-2011

Source: US Bureau of Labor Statistics

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

Chart ESII-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.

clip_image004

Chart ESII-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 ESII-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 ESII-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 ESII-3 plots yearly percentage changes of nonfarm hiring. Percentage declines after 2007 were quite sharp.

clip_image006

Chart ESII-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 ESII-4. There has been sharp contraction of total private hiring in the US and only milder recovery in 2011 than in 2010.

clip_image008

Chart ESII-4, US, Total Private Hiring, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

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

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

clip_image010

Chart ESII-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 Feb in the years from 2001 to 2012 in Table ESII-3. Hiring numbers are in thousands. There is some recovery in HNF from 3124 thousand (or 3.1 million) in Feb 2010 to 3335 thousand in Feb 2011 and 3580 thousand in Feb 2012 for cumulative gain of 14.6 percent. HP rose from 2921 thousand in Feb 2010 to 3169 thousand in Feb 2011 and 3358 thousand in Feb 2012 for cumulative gain of 14.9 percent. HNF has fallen from 4421 in Feb 2005 to 3580 in Feb 2012 or by 19.0 percent. HP has fallen from 4176 in Feb 2006 to 3358 in Feb 2012 or by 19.6 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 ESII-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 Feb

4399

3.4

4136

3.8

2002 Feb

4007

3.1

3774

3.5

2003 Feb

3821

3.0

3617

3.4

2004 Feb

3840

3.0

3618

3.4

2005 Feb

4305

3.3

4079

3.7

2006 Feb

4421

3.3

4176

3.7

2007 Feb

4265

3.1

4001

3.5

2008 Feb

4012

2.9

3782

3.3

2009 Feb

3273

2.5

3090

2.8

2010 Feb

3124

2.4

2921

2.8

2011 Feb

3335

2.6

3169

3.0

2012 Feb

3580

2.7

3358

3.1

Source:  US Bureau of Labor Statistics

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

Chart ESII-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 3580 in Feb 2012. Chart ESII-6 provides seasonally-adjusted (SA) monthly data. The number of seasonally-adjusted hires in Sep 2011 was 4221 thousand, increasing to 4385 thousand in Feb 2012, or 2.5 percent. The number of hires not seasonally adjusted was 4507 in Sep, falling to 3038 in Dec but increasing to 4072 in Jan 2012 and falling again to 3580 in Feb 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.

clip_image012

Chart ESII-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 ESII-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 Feb 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 2.7 in Feb 2012. Rates of nonfarm hiring NSA were in the range of 2.8 (Dec) to 4.5 (Jun) in 2006.

clip_image014

Chart ESII-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 ESII-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 4075 in Feb 2012 for increase of 1.8 percent relative to 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 3358 in Feb 2012 or decline of 18.7 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 ten 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-economic-growth-falling-real.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

clip_image016

Chart ESII-8, US, Total Private Hiring Month SA 2011-2012

Source: US Bureau of Labor Statistics

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

Chart ESII-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 Feb 2012. The rate not seasonally adjusted (NSA) fell from 3.8 in Sep to 2.6 in Dec, increasing to 3.4 in Jan 2012 but falling to 3.1 in Feb 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.

clip_image018

Chart ESII-9, US, Rate Total Private Hiring Month SA 2011-2011

Source: US Bureau of Labor Statistics

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

ESIII 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 7.672 million in Mar 2012, seasonally adjusted, or decline of 1.598 million in just six months, as shown in Table ESIII-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. 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. 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. 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 Mar 2012 is 113.916 million, which is lower by 9.3 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 ten 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/2012/04/mediocre-economic-growth-falling-real.html).

Table ESIII-1, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions

 

Part-time Thousands

Full-time Millions

Seasonally Adjusted

   

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

   

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

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

113.138

Oct 2010

8,408

112.342

Mar 2010

9,343 (high)

109.877

Feb 2010

9,282

109.100

Jan 2010

9,290

108.770 (low)

Mar 2009

9,305

112.215

Feb 2009

9,170

112.947

Jan 2009

8,829

113.815

Feb 2008

5,114

119.452

Mar 2008

5,038

119.875

Jan 2008

5,340

119.322

Jul 2007

4,516

123.219 (high)

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

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 ESIII-1 shows the sharp rise in unemployed over 27 weeks and stabilization at an extremely high level.

clip_image020

Chart ESIII-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 ESIII-2 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.

clip_image022

Chart ESIII-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 ESIII-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.

clip_image024

Chart ESIII-3, US, Full-time Employed, Thousands, NSA, 2001-2012

Sources: US Bureau of Labor Statistics

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

ESIV Youth Unemployment. The United States is experiencing high youth unemployment as in European economies. Table ESIV-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 ESIV-1, US, Employment Level 16-24 Years, Thousands, NSA

Year

Jan

Feb

Mar

Annual

2001

19678

19745

19800

20088

2002

18653

19074

19091

19683

2003

18811

18880

18709

19351

2004

18852

18841

18752

19630

2005

18858

18670

18989

19770

2006

19003

19182

19291

20041

2007

19407

19415

19538

19875

2008

18724

18546

18745

19202

2009

17467

17606

17564

17601

2010

16166

16412

16587

17077

2011

16512

16638

16898

17362

2012

16944

17150

17301

 

Sources: US Bureau of Labor Statistics

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

Chart ESIV-1 provides US employment level ages 16 to 24 years from 2002 to 2012. Employment level is sharply lower in Mar 2012 relative to the peak in 2007.

clip_image026

Chart ESIV-1, US, Employment Level 16-24 Years, Thousands SA, 2002-2012

Sources: US Bureau of Labor Statistics

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

Table ESIV-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 ESIV-2, US, Unemployment Level 16-24 Years, Thousands NSA

Year

Jan

Feb

Mar

Annual

2001

2250

2258

2253

2371

2003

2748

2740

2601

2746

2004

2767

2631

2588

2638

2005

2661

2787

2520

2521

2006

2366

2433

2216

2353

2007

2363

2230

2096

2342

2008

2633

2480

2347

2830

2009

3278

3457

3371

3760

2010

3983

3888

3748

3857

2011

3851

3696

3520

3634

2012

3416

3507

3294

 

Sources: US Bureau of Labor Statistics

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

Chart ESIV-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.

clip_image028

Chart ESIV-2, US, Unemployment Level 16-24 Years, Thousands SA, 2002-2012

Sources: US Bureau of Labor Statistics

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

Table ESIV-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 ESIV-3, US, Unemployment Rate 16-24 Years, Thousands, NSA

Year

Jan

Feb

Mar

Annual

2001

10.3

10.3

10.2

10.6

2002

12.9

12.5

12.9

12.0

2003

12.7

12.7

12.2

12.4

2004

12.8

12.3

12.1

11.8

2005

12.4

13.0

11.7

11.3

2006

11.1

11.3

10.3

10.5

2007

10.9

10.3

9.7

10.5

2008

12.3

11.8

11.1

12.8

2009

15.8

16.4

16.1

17.6

2010

19.8

19.2

18.4

18.4

2011

18.9

18.2

17.2

17.3

2012

16.8

17.0

16.0

 

Sources: US Bureau of Labor Statistics

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

Chart ESIV-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 ten quarters of expansion of the economy since IIIQ2009.

clip_image030

Chart ESIV-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 ESIV-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 ten quarters of expansion from IIIQ2009 to IVQ2011 (see Table I-5 at http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-economic-growth-falling-real.html). The fractured US labor market denies an early start for young people.

clip_image032

Chart ESIV-4, US, Unemployment Rate 16-24 Years, Percent NSA, 1979-2012

Sources: US Bureau of Labor Statistics

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

ESV World Inflation Waves. The critical fact of current world financial markets is the combination of “unconventional” monetary policy with intermittent shocks of financial risk aversion. There are two interrelated unconventional monetary policies. First, unconventional monetary policy consists of (1) reducing short-term policy interest rates toward the “zero bound” such as fixing the fed funds rate at 0 to ¼ percent by decision of the Federal Open Market Committee (FOMC) since Dec 16, 2008 (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm). Second, unconventional monetary policy also includes a battery of measures to also reduce long-term interest rates of government securities and asset-backed securities such as mortgage-backed securities.

When inflation is low, the central bank lowers interest rates to stimulate aggregate demand in the economy, which consists of consumption and investment. When inflation is subdued and unemployment high, monetary policy would lower interest rates to stimulate aggregate demand, reducing unemployment. When interest rates decline to zero, unconventional monetary policy would consist of policies such as large-scale purchases of long-term securities to lower their yields. A major portion of credit in the economy is financed with long-term asset-backed securities. Loans for purchasing houses, automobiles and other consumer products are bundled in securities that in turn are sold to investors. Corporations borrow funds for investment by issuing corporate bonds. Loans to small businesses are also financed by bundling them in long-term bonds. Securities markets bridge the needs of higher returns by savers obtaining funds from investors that are channeled to consumers and business for consumption and investment. Lowering the yields of these long-term bonds could lower costs of financing purchases of consumer durables and investment by business. The essential mechanism of transmission from lower interest rates to increases in aggregate demand is portfolio rebalancing. Withdrawal of bonds in a specific maturity segment or directly in a bond category such as currently mortgage-backed securities causes reductions in yield that are equivalent to increases in the prices of the bonds. There can be secondary increases in purchases of those bonds in private portfolios in pursuit of their increasing prices. Lower yields translate into lower costs of buying homes and consumer durables such as automobiles and also lower costs of investment for business. There are two additional intended routes of transmission.

1. Unconventional monetary policy or its expectation can increase stock market valuations (Bernanke 2010WP). Increases in equities traded in stock markets can increase the wealth of consumers inducing increases in consumption.

2. Unconventional monetary policy causes devaluation of the dollar relative to other currencies, which can cause increases in net exports of the US that increase aggregate economic activity (Yellen 2011AS).

Monetary policy can lower short-term interest rates quite effectively. Lowering long-term yields is somewhat more difficult. The critical issue is that monetary policy cannot ensure that increasing credit at low interest cost increases consumption and investment. There is a large variety of possible allocation of funds at low interest rates from consumption and investment to multiple risk financial assets. Monetary policy does not control how investors will allocate asset categories. A critical financial practice is to borrow at low short-term interest rates to invest in high-risk, leveraged financial assets. Investors may increase in their portfolios asset categories such as equities, emerging market equities, high-yield bonds, currencies, commodity futures and options and multiple other risk financial assets including structured products. If there is risk appetite, the carry trade from zero interest rates to risk financial assets will consist of short positions at short-term interest rates (or borrowing) and short dollar assets with simultaneous long positions in high-risk, leveraged financial assets such as equities, commodities and high-yield bonds. Low interest rates may induce increases in valuations of risk financial assets that may fluctuate in accordance with perceptions of risk aversion by investors and the public. During periods of muted risk aversion, carry trades from zero interest rates to exposures in risk financial assets cause temporary waves of inflation that may foster instead of preventing financial stability. During periods of risk aversion such as fears of disruption of world financial markets and the global economy resulting from collapse of the European Monetary Union, carry trades are unwound with sharp deterioration of valuations of risk financial assets. More technical discussion is in IF Appendix: Transmission of Unconventional Monetary Policy at http://cmpassocregulationblog.blogspot.com/2012/01/financial-risk-aversion-and-collapse-of.html.

Table ESV-1 provides annual equivalent rates of inflation for producer price indexes followed in this blog. The behavior of the US producer price index in 2011 shows neatly six waves. (1) In Jan-Apr, without risk aversion, US producer prices rose at the annual equivalent rate of 9.7 percent. (2) After risk aversion, producer prices increased in the US at the annual equivalent rate of 1.2 percent in May-Jul. (3) From Jul to Sep, under alternating episodes of risk aversion, producer prices increased at the annual equivalent rate of 6.6 percent. (4) Under the pressure of risk aversion because of the European debt crisis US producer prices fell at the annual equivalent rate of 1.2 percent in Oct-Nov. (5) From Dec 2011 to Jan 2012, US producer prices rose at the annual equivalent rate of 1.2 percent with relaxed risk aversion and commodity-price increases at the margin. (6) Inflation of producer prices returned with 2.4 percent annual equivalent in Feb-Mar 2012. Resolution of the European debt crisis if there is not an unfavorable growth event with political development in China would result in jumps of valuations of risk financial assets. Increases in commodity prices would cause the same high producer price inflation experienced in Jan-Apr. There are seven producer-price indexes in Table ESV-1 for six countries (two for the UK) showing very similar behavior. Zero interest rates without risk aversion cause increases in commodity prices that in turn increase input and output prices. Producer price inflation rose at very high rates during the first part of 2011 for the US, China, Germany, France, Italy and the UK when risk aversion was contained. With the increase in risk aversion in May and Jun, inflation moderated because carry trades were unwound. Producer price inflation returned since July, with alternating bouts of risk aversion. In the final months of the year producer price inflation collapsed because of the disincentive to exposures in commodity futures resulting from fears of resolution of the European debt crisis. There is renewed worldwide inflation in the early part of 2012. Unconventional monetary policy fails in stimulating the overall real economy, merely introducing undesirable instability as monetary authorities cannot control allocation of floods of money at zero interest rates to carry trades into risk financial assets.

Table ESV-1, Annual Equivalent Rates of Producer Price Indexes

INDEX 2011-2012

AE ∆%

US Producer Price Index

 

AE  ∆% Feb-Mar

2.4

AE  ∆% Dec-Jan

1.2

AE  ∆% Oct-Nov

-1.2

AE ∆% Jul-Sep

6.6

AE ∆% May-Jul

1.2

AE ∆% Jan-Apr

9.7

Japan Corporate Goods Price Index

 

AE % Feb-Mar

4.9

AE ∆% Dec-Feb

0.4

AE ∆% Jul-Nov

-2.1

AE ∆% May-Jun

-1.2

AE ∆% Jan-Apr

7.1

China Producer Price Index

 

AE ∆% Feb-Mar

2.4

AE ∆% Dec-Jan

-2.4

AE ∆% Jul-Nov

-3.1

AE ∆% Jan-Jun

6.4

Germany Producer Price Index

 

AE ∆% Dec-Feb

3.2

AE ∆% Oct-Dec

-0.4

AE ∆% Jul-Sep

2.8

AE ∆% May-Jun

0.6

AE ∆% Jan-Apr

10.3

France Producer Price Index for the French Market

 

AE ∆% Dec-Jan

3.0

AE ∆% Oct-Dec

2.8

AE ∆% Jul-Sep

2.4

AE ∆% May-Jun

-3.5

AE ∆% Jan-Apr

11.4

Italy Producer Price Index

 

AE ∆% Jan-Feb

7.4

AE ∆% Nov-Jan

4.5

AE ∆% Oct-Dec

0.4

AE ∆% Jul-Sep

2.4

AE ∆% May-Jun

-1.2

AE ∆% Jan-April

10.7

UK Output Prices

 

AE ∆% Feb-Mar

7.4

AE ∆% Nov-Jan

1.6

AE ∆% May-Oct

2.0

AE ∆% Jan-Apr

12.0

UK Input Prices

 

AE ∆% Jan-Mar

20.0

AE ∆% Nov-Dec

-1.2

AE ∆% May-Oct

-3.1

AE ∆% Jan-Apr

35.6

AE: Annual Equivalent

Sources: http://www.bls.gov/ppi/data.htm http://www.boj.or.jp/en/statistics/pi/cgpi_release/cgpi1203.pdf http://www.stats.gov.cn/english/pressrelease/t20120410_402797821.htm

https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/2012/03/PD12_099_61241.html

http://www.insee.fr/en/themes/info-rapide.asp?id=25&date=20120227

http://www.istat.it/it/archivio/58193

http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/march-2012/index.html

Similar world inflation waves are in the behavior of consumer price indexes of six countries and the euro zone in Table ESV-2. US consumer price inflation shows six waves. (1) Under risk appetite in Jan-Apr consumer prices increased at the annual equivalent rate of 4.9 percent. (2) Risk aversion caused the collapse of inflation to annual equivalent 2.8 percent in May-Jul. (3) Risk appetite drove the rate of consumer price inflation in the US to 3.7 percent in Jul-Sep. (4) Gloomier views of carry trades caused the collapse of inflation in Oct-Nov to annual equivalent 0.6 percent. (5) Consumer price inflation resuscitated with increased risk appetite at annual equivalent of 1.2 percent in Dec 2011 to Jan 2012. (6) Consumer price inflation returned at 4.3 percent annual equivalent in Feb-Mar 2012. There is similar behavior in all the other consumer price indexes in Table ESV-2. China’s CPI increased at annual equivalent 8.3 percent in Jan-Mar, 2.0 percent in Apr-Jun, 2.9 percent in Jul-Dec and resuscitated at 5.8 percent annual equivalent in Dec 2011 to Mar 2012. The euro zone harmonized index of consumer prices (HICP) increased at annual equivalent 5.2 percent in Jan-Apr, minus 2.4 percent in May-Jul, 3.9 percent in Aug-Dec but remained flat in Dec-Feb. The price indexes of the largest members of the euro zone, Germany, France and Italy, exhibit the same inflation waves. The United Kingdom CPI increased at annual equivalent 6.5 percent in Jan-Apr, falling to only 0.4 percent in May-Jul and then increasing at 4.7 percent in Aug-Dec. UK consumer prices increased at 2.0 percent annual equivalent from Dec 2011 to Feb 2012.

Table ESV-2, Annual Equivalent Rates of Consumer Price Indexes

Index 2011-2012

AE ∆%

US Consumer Price Index

 

AE ∆% Feb-Mar

4.3

AE ∆% Dec-Jan

1.2

AE ∆% Oct-Nov

0.6

AE ∆% Jul-Sep

3.7

AE ∆% May-Jul

2.8

AE ∆% Jan-Apr

4.9

China Consumer Price Index

 
   

AE ∆% Dec-Mar

5.8

AE ∆% Jul-Nov

2.9

AE ∆% Apr-Jun

2.0

AE ∆% Jan-Mar

8.3

Euro Zone Harmonized Index of Consumer Prices

 

AE ∆% Dec-Feb

0.0

AE ∆% Aug-Dec

3.9

AE ∆% May-Jul

-2.4

AE ∆% Jan-Apr

5.2

Germany Consumer Price Index

 

AE ∆% Feb-Mar

6.2

AE ∆% Dec-Feb

1.6

AE ∆% Aug-Dec

2.7

AE ∆% May-Jul

-0.8

AE ∆% Jan-Apr

4.3

France Consumer Price Index

 

AE ∆% Feb-Mar

7.4

AE ∆% Dec-Feb

1.6

AE ∆% Aug-Nov

2.7

AE ∆% May-Jul

-0.8

AE ∆% Jan-Apr

4.3

Italy Consumer Price Index

 

AE ∆% Feb-Mar

5.5

AE ∆% Dec-Jan

4.3

AE ∆% Oct-Nov

3.0

AE ∆% Jul-Sep

2.4

AE ∆% May-Jun

1.2

AE ∆% Jan-Apr

4.9

UK Consumer Price Index

 

AE ∆% Dec-Feb

2.0

AE ∆% Aug-Dec

4.6

AE ∆% May-Jul

0.4

AE ∆% Jan-Apr

6.5

AE: Annual Equivalent

Sources: http://www.bls.gov/cpi/data.htm http://www.stats.gov.cn/english/pressrelease/t20120410_402797823.htm

http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-14032012-BP/EN/2-14032012-BP-EN.PDF

http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home

https://www.destatis.de/EN/PressServices/Press/pr/2012/04/PE12_134_611.html

http://www.insee.fr/en/themes/info-rapide.asp?id=29&date=20120412

http://www.istat.it/it/archivio/59216

http://www.ons.gov.uk/ons/rel/cpi/consumer-price-indices/february-2012/index.html

ESVI United States Inflation. Monetary policy pursues symmetric inflation targets of maintaining core inflation of the index of personal consumption expenditures (core PCE) in an open interval of 2.00 percent. If inflation increases above 2.00 percent, the central bank could use restrictive monetary policy such as increases in interest rates to contain inflation in a tight range or interval around 2.00 percent. If inflation falls below 2 percent, the central bank could use restrictive monetary policy such as lowering interest rates to prevent inflation from falling too much below 2.00 percent. Currently, with about thirty million unemployed and underemployed (http://cmpassocregulationblog.blogspot.com/2012/04/thirty-million-unemployed-or.html), there may even be a policy bias to raise or at least ignore inflation, even with falling real wages, maintaining accommodation as a form of promoting full employment. There are two arguments in favor of symmetric inflation targets preventing inflation from falling to very low levels.

1. Room for interest rate policy. Nominal interest rates hardly ever fall below zero. In economic jargon, the floor of zero nominal interest rates is referred to as “the zero bound.” Symmetric targets are proposed to maintain a sufficiently high inflation rate such that interest rates can be lowered to promote economic activity when recession threatens. With inflation close to zero there is no room for lowering interest rates with policy tools.

2. Fear of Deflation. Inflation is a process of sustained increases in prices. Deflation is a process of sustained decreases in prices. The probability of deflation increases as inflation approximates zero. The influence of fear of deflation in monetary policy is discussed in Pelaez and Pelaez (International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-95).

Key percentage average yearly rates of the US economy on growth and inflation are provided in Table ESVI-1 updated with release of new data. The choice of dates prevents the measurement of long-term potential economic growth because of two recessions from IQ2001 (Mar) to IVQ2001 (Nov) with decline of GDP of 0.4 percent and the drop in GDP of 5.1 percent in IVQ2007 (Dec) to IIQ2009 (June) (http://www.nber.org/cycles.html) followed with unusually low economic growth for an expansion phase after recession with the economy growing at 1.6 percent IVQ2011 relative to IVQ2010 (http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-economic-growth-falling-real.html). Between 2000 and 2011, real GDP grew at the average rate of 1.6 percent per year, nominal GDP at 3.9 percent and the implicit deflator at 2.3 percent. Between 2000 and 2012, the average rate of CPI inflation was 2.5 percent per year and 2.0 percent excluding food and energy. PPI inflation increased at 3.0 percent per year on average and at 1.7 percent excluding food and energy. There is also inflation in international trade. Import prices grew at 3.1 percent per year between 2000 and 2012. The commodity price shock is revealed by inflation of import prices of petroleum increasing at 13.0 percent per year between 2000 and 2011 and at 12.7 percent between 2000 and 2012. The average growth rates of import prices excluding fuels are much lower at 2.0 percent for 2002 to 2011 and also 2.0 percent for 2000 to 2012. Export prices rose at the average rate of 2.6 percent between 2000 and 2011 and at 2.5 percent from 2000 to 2012. What spared the US of sharper decade-long deterioration of the terms of trade, (export prices)/(import prices), was its diversification and competitiveness in agriculture. Agricultural export prices grew at the average yearly rate of 7.3 percent from 2000 to 2011 and at 6.2 percent from 2000 to 2012. US nonagricultural export prices rose at 2.2 percent per year from 2000 to 2011 and at 2.1 percent from 2000 to 2012. The share of petroleum imports in US trade far exceeds that of agricultural exports. Unconventional monetary policy inducing carry trades in commodities has deteriorated US terms of trade, prices of exports relative to prices of imports, tending to reduce US aggregate real income. These dynamic growth rates are not similar to those for the economy of Japan where inflation was negative in seven of the 10 years in the 2000s.

Table ESVI-1, US, Average Growth Rates of Real and Nominal GDP, Consumer Price Index, Producer Price Index and Import and Export Prices, Percent per Year

Real GDP

2000-2011: 1.6%

Nominal GDP

2000-2011: 3.9%

Implicit Price Deflator

2000-2011: 2.3%

CPI

2000-2011: 2.5%
2000-2012: 2.5%

CPI ex Food and Energy

2000-2011: 2.0%
2000-2012: 2.0%

PPI

2000-2011: 3.00%
2000-2012: 3.0%

PPI ex Food and Energy

2000-2011: 1.6%
2000-2012: 1.7%

Import Prices

2000-2011: 3.1%
2000-2012: 3.1%

Import Prices of Petroleum and Petroleum Products

2000-2011: 13.0%
2000-2012:  12.7%

Import Prices Excluding Petroleum

2000-2011: 1.3%
2000-2012: 1.3%

Import Prices Excluding Fuels

2002-2011: 2.0%
2002-2012:  2.0%

Export Prices

2000-2011: 2.6%
2000-2012: 2.5%

Agricultural Export Prices

2000-2011: 7.3%
2000-2012: 6.2%

Nonagricultural Export Prices

2000-2011: 2.2%
2000-2012: 2.1%

Note: rates for price indexes in the row beginning with “CPI” and ending in the row “Nonagricultural Export Prices” are for Mar 2000 to Mar 2011 and for Mar 2000 to Mar 2012 using not seasonally adjusted indexes. Import prices excluding fuels are not available before 2002.

Sources: http://www.bea.gov/iTable/index_nipa.cfm http://www.bls.gov/ppi/data.htm

http://www.bls.gov/mxp/data.htm http://www.bls.gov/cpi/data.htm

Unconventional monetary policy of zero interest rates and large-scale purchases of long-term securities for the balance sheet of the central bank is proposed to prevent deflation. The data of CPI inflation of all goods and CPI inflation excluding food and energy for the past six decades show only one negative change by 0.4 percent in the CPI all goods annual index in 2009 but not one year of negative annual yearly change in the CPI excluding food and energy measuring annual inflation (http://cmpassocregulationblog.blogspot.com/2011/08/world-financial-turbulence-global.html). Zero interest rates and quantitative easing are designed to lower costs of borrowing for investment and consumption, increase stock market valuations and devalue the dollar. In practice, the carry trade is from zero interest rates to a large variety of risk financial assets including commodities. Resulting commodity price inflation squeezes family budgets and deteriorates the terms of trade with negative effects on aggregate demand and employment. Excessive valuations of risk financial assets eventually result in crashes of financial markets with possible adverse effects on economic activity and employment.

Producer price inflation history in the past five decades does not provide evidence of deflation. The finished core PPI does not register even one single year of decline. The headline PPI experienced only six isolated cases of decline (http://cmpassocregulationblog.blogspot.com/2011/08/world-financial-turbulence-global.html):

-0.3 percent in 1963,

-1.4 percent in 1986,

-0.8 percent in 1986,

-0.8 percent in 1998,

-1.3 percent in 2001

-2.6 percent in 2009.

Deflation should show persistent cases of decline of prices and not isolated events. Fear of deflation in the US has caused a distraction of monetary policy. Symmetric inflation targets around 2 percent in the presence of multiple lags in effect of monetary policy and imperfect knowledge and forecasting are mostly unfeasible and likely to cause price and financial instability instead of desired price and financial stability

There have been six waves of consumer price inflation in the US in 2011 that are illustrated in Table ESVI-2. The first wave occurred in Jan-Apr and was caused by the carry trade of commodity prices induced by unconventional monetary policy of zero interest rates. Cheap money at zero opportunity cost was channeled into financial risk assets, causing increases in commodity prices. The annual equivalent rate of increase of the all-items CPI in Jan-Apr was 4.9 percent and the CPI excluding food and energy increased at annual equivalent rate of 2.4 percent. The second wave occurred during the collapse of the carry trade from zero interest rates to exposures in commodity futures as a result of risk aversion in financial markets created by the sovereign debt crisis in Europe. The annual equivalent rate of increase of the all-items CPI dropped to 2.8 percent in May-Jul while the annual equivalent rate of the CPI excluding food and energy increased at 3.0 percent. In the third wave in Jul-Sep, the annual equivalent CPI rose at 3.7 percent while the core CPI increased at 2.0 percent. The fourth wave occurred in the form of decrease of the CPI all-items annual equivalent rate to 0.6 percent in Oct-Nov with the annual equivalent rate of the CPI excluding food and energy remaining at 2.4 percent. The fifth wave occurred in Dec-Jan with annual equivalent headline inflation of 1.2 percent and core inflation of 1.8 percent. In the sixth wave, headline CPI inflation increased at annual equivalent 4.3 percent in Feb-Mar and core CPI inflation at 1.8 percent. The conclusion is that inflation accelerates and decelerates in unpredictable fashion that turns symmetric inflation targets in a source of destabilizing shocks to the financial system and eventually the overall economy. Unconventional monetary policy of zero interest rates and withdrawal of bonds to lower long-term interest rates distorts risk/return decisions required for efficient allocation of resources and attaining optimal growth paths and prosperity.

Table ESVI-2, US, Headline and Core CPI Inflation Monthly SA and 12 Months NSA ∆%

 

All Items 

SA Month

All Items NSA 12 month

Core SA
Month

Core NSA
12 months

Mar 2012

0.3

2.7

0.2

2.3

Feb

0.4

2.9

0.1

2.2

AE ∆% Feb-Mar

4.3

 

1.8

 

Jan

0.2

2.9

0.2

2.3

Dec 2011

0.0

3.0

0.1

2.2

AE ∆% Dec-Jan

1.2

 

1.8

 

Nov

0.1

3.4

0.2

2.2

Oct

0.0

3.5

0.2

2.1

AE ∆% Oct-Nov

0.6

 

2.4

 

Sep

0.3

3.9

0.1

2.0

Aug

0.3

3.8

0.2

2.0

Jul

0.3

3.6

0.2

1.8

AE ∆% Jul-Sep

3.7

 

2.0

 

Jun

0.1

3.6

0.2

1.6

May

0.3

3.6

0.3

1.5

AE ∆%  May-Jul

2.8

 

3.0

 

Apr

0.4

3.2

0.2

1.3

Mar

0.5

2.7

0.2

1.2

Feb

0.4

2.1

0.2

1.1

Jan

0.3

1.6

0.2

1.0

AE ∆%  Jan-Apr

4.9

 

2.4

 

Dec 2010

0.4

1.5

0.1

0.8

Nov

0.2

1.1

0.1

0.8

Oct

0.3

1.2

0.0

0.6

Sep

0.1

1.1

0.0

0.8

Aug

0.2

1.1

0.1

0.9

Jul

0.2

1.2

0.1

0.9

Jun

0.0

1.1

0.1

0.9

May

-0.1

2.0

0.1

0.9

Apr

0.0

2.2

0.0

0.9

Mar

0.0

2.3

0.1

1.1

Feb

0.0

2.1

0.1

1.3

Jan

0.1

1.6

-0.1

1.6

Note: Core: excluding food and energy; AE: annual equivalent

Source: US Bureau of Labor Statistics

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

The behavior of the US consumer price index NSA from 2001 to 2011 is provided in Chart ESVI-1. Inflation in the US is very dynamic without deflation risks that would justify symmetric inflation targets. The hump in 2008 originated in the carry trade from interest rates dropping to zero into commodity futures. There is no other explanation for the increase of oil prices toward $140/barrel during the global recession. The unwinding of the carry trade with the TARP announcement of toxic assets in banks channeled cheap money into government obligations (see Cochrane and Zingales 2009).

clip_image034

Chart ESVI-1, US, Consumer Price Index, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

Chart ESVI-2 provides 12-month percentage changes of the consumer price index from 2001 to 2012. There was no deflation or threat of deflation from 2008 into 2009. Commodity prices collapsed during the panic of toxic assets in banks. When stress tests in 2009 revealed US bank balance sheets in much stronger position, cheap money at zero opportunity cost exited government obligations and flowed into carry trades of risk financial assets. Increases in commodity prices drove again the all items CPI with interruptions during risk aversion originating in the sovereign debt crisis of Europe.

clip_image036

Chart ESVI-2, US, Consumer Price Index, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

The trend of increase of the consumer price index excluding food and industry in Chart ESVI-3 does not reveal any threat of deflation that would justify symmetric inflation targets. There are mild oscillations in a neat upward trend.

clip_image038

Chart ESVI-3, US, Consumer Price Index Excluding Food and Energy, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

Chart ESVI-4 provides 12-month percentage change of the consumer price index excluding food and energy. Past-year rates of inflation fell toward 1 percent from 2001 into 2003 as a result of the recession and the decline of commodity prices beginning before the recession with declines of real oil prices. Near zero interest rates with fed funds at 1 percent between Jun 2003 and Jun 2004 stimulated carry trades of all types, including in buying homes with subprime mortgages in expectation that low interest rates forever would increase home prices permanently, creating the equity that would permit the conversion of subprime mortgages into creditworthy mortgages (Gorton 2009EFM; see http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Inflation rose and then collapsed during the unwinding of carry trades and the housing debacle of the global recession. Carry trade into 2011 and 2012 gave a new impulse to CPI inflation, all items and core. Symmetric inflation targets destabilize the economy by encouraging hunts for yields that inflate and deflate financial assets, obscuring risk/return decisions on production, investment and hiring.

clip_image040

Chart ESVI-4, US, Consumer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

ESVII Global Financial and Economic Risk. The International Monetary Fund (IMF) provides an international safety net for prevention and resolution of international financial crises. The IMF’s Financial Sector Assessment Program (FSAP) provides analysis of the economic and financial sectors of countries (see Pelaez and Pelaez, International Financial Architecture (2005), 101-62, Globalization and the State, Vol. II (2008), 114-23). Relating economic and financial sectors is a challenging task both for theory and measurement. The IMF 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. Table ESVII-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 4/13/12,” 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 with exception of China’s Shanghai Composite show positive change in valuation in column “∆% Trough to 4/13/12” after 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 16 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. The highest valuations are by US equities indexes: DJIA 32.7 percent and S&P 500 34.0 percent, driven by stronger earnings and economy in the US than in other advanced economies. 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, all assets in the column “∆% Trough to 4/13/12” had double digit gains relative to the trough around Jul 2, 2010 but now only three valuation show increase of less than 10 percent: China’s Shanghai Composite is 1.0 percent below the trough; STOXX 50 of Europe is 3.2 percent above the trough; and Japan’s Nikkei Average is 9.2 percent above the trough. DJ UBS Commodities is 12.5 percent above the trough; Dow Global is 12.1 percent above the trough; and DAX is 16.1 percent above the trough. Japan’s Nikkei Average is 9.8 percent above the trough on Aug 31, 2010 and 15.0 percent below the peak on Apr 5, 2010. The Nikkei Average closed at 9637.99 on Fri Apr 13, 2012 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 6.0 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 9.7 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 4/13/12” in Table ESVII-1 shows declines of all valuations of risk financial assets in the week of Apr 13, 2012, with exception of gain of 2.3 percent by China’s Shanghai Composite and gain of 0.2 percent for DJ Asia Pacific, because of the new issues of world economic and financial risks. 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 ESVII-1 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 4/13/12” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Apr 6, 2012. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 4/13/12” but also relative to the peak in column “∆% Peak to 4/13/12.” There are now only three equity indexes above the peak in Table ESVII-1: DJIA 14.7 percent, S&P 500 12.6 percent and Dax 4.0 percent. There are several indexes below the peak: NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) by 14.0 percent, Nikkei Average by 15.4 percent, Shanghai Composite by 25.5 percent, STOXX 50 by 12.6 percent and Dow Global by 8.5 percent. DJ UBS Commodities Index is now 3.8 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 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010.

Table ESVII-1, Stock Indexes, Commodities, Dollar and 10-Year Treasury

 

Peak

Trough

∆% to Trough

∆% Peak to 4/13

/12

∆% Week 4/13/ 12

∆% Trough to 4/13

12

DJIA

4/26/
10

7/2/10

-13.6

14.7

-1.6

32.7

S&P 500

4/23/
10

7/20/
10

-16.0

12.6

-2.0

34.0

NYSE Finance

4/15/
10

7/2/10

-20.3

-14.0

-2.3

7.9

Dow Global

4/15/
10

7/2/10

-18.4

-8.5

-2.1

12.1

Asia Pacific

4/15/
10

7/2/10

-12.5

-2.3

0.2

11.6

Japan Nikkei Aver.

4/05/
10

8/31/
10

-22.5

-15.4

-0.5

9.2

China Shang.

4/15/
10

7/02
/10

-24.7

-25.5

2.3

-1.0

STOXX 50

4/15/10

7/2/10

-15.3

-12.6

-2.4

3.2

DAX

4/26/
10

5/25/
10

-10.5

4.0

-2.8

16.1

Dollar
Euro

11/25 2009

6/7
2010

21.2

13.6

0.1

-9.7

DJ UBS Comm.

1/6/
10

7/2/10

-14.5

-3.8

-1.6

12.5

10-Year T Note

4/5/
10

4/6/10

3.986

1.987

   

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)

7. Source: http://professional.wsj.com/mdc/page/marketsdata.html?mod=WSJ_hps_marketdata

I World Inflation Waves. This section provides analysis and data on world inflation waves. The general framework is provided in Subsection IA World Inflation Waves. Subsection IIB United States Inflation analyzes inflation in the United States in three subsections: IB1 Long-term US Inflation, IB2 Current US Inflation and IB3 Import Export Prices.

IA World Inflation Waves. The critical fact of current world financial markets is the combination of “unconventional” monetary policy with intermittent shocks of financial risk aversion. There are two interrelated unconventional monetary policies. First, unconventional monetary policy consists of (1) reducing short-term policy interest rates toward the “zero bound” such as fixing the fed funds rate at 0 to ¼ percent by decision of the Federal Open Market Committee (FOMC) since Dec 16, 2008 (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm). Second, unconventional monetary policy also includes a battery of measures to also reduce long-term interest rates of government securities and asset-backed securities such as mortgage-backed securities.

When inflation is low, the central bank lowers interest rates to stimulate aggregate demand in the economy, which consists of consumption and investment. When inflation is subdued and unemployment high, monetary policy would lower interest rates to stimulate aggregate demand, reducing unemployment. When interest rates decline to zero, unconventional monetary policy would consist of policies such as large-scale purchases of long-term securities to lower their yields. A major portion of credit in the economy is financed with long-term asset-backed securities. Loans for purchasing houses, automobiles and other consumer products are bundled in securities that in turn are sold to investors. Corporations borrow funds for investment by issuing corporate bonds. Loans to small businesses are also financed by bundling them in long-term bonds. Securities markets bridge the needs of higher returns by savers obtaining funds from investors that are channeled to consumers and business for consumption and investment. Lowering the yields of these long-term bonds could lower costs of financing purchases of consumer durables and investment by business. The essential mechanism of transmission from lower interest rates to increases in aggregate demand is portfolio rebalancing. Withdrawal of bonds in a specific maturity segment or directly in a bond category such as currently mortgage-backed securities causes reductions in yield that are equivalent to increases in the prices of the bonds. There can be secondary increases in purchases of those bonds in private portfolios in pursuit of their increasing prices. Lower yields translate into lower costs of buying homes and consumer durables such as automobiles and also lower costs of investment for business. There are two additional intended routes of transmission.

3. Unconventional monetary policy or its expectation can increase stock market valuations (Bernanke 2010WP). Increases in equities traded in stock markets can increase the wealth of consumers inducing increases in consumption.

4. Unconventional monetary policy causes devaluation of the dollar relative to other currencies, which can cause increases in net exports of the US that increase aggregate economic activity (Yellen 2011AS).

Monetary policy can lower short-term interest rates quite effectively. Lowering long-term yields is somewhat more difficult. The critical issue is that monetary policy cannot ensure that increasing credit at low interest cost increases consumption and investment. There is a large variety of possible allocation of funds at low interest rates from consumption and investment to multiple risk financial assets. Monetary policy does not control how investors will allocate asset categories. A critical financial practice is to borrow at low short-term interest rates to invest in high-risk, leveraged financial assets. Investors may increase in their portfolios asset categories such as equities, emerging market equities, high-yield bonds, currencies, commodity futures and options and multiple other risk financial assets including structured products. If there is risk appetite, the carry trade from zero interest rates to risk financial assets will consist of short positions at short-term interest rates (or borrowing) and short dollar assets with simultaneous long positions in high-risk, leveraged financial assets such as equities, commodities and high-yield bonds. Low interest rates may induce increases in valuations of risk financial assets that may fluctuate in accordance with perceptions of risk aversion by investors and the public. During periods of muted risk aversion, carry trades from zero interest rates to exposures in risk financial assets cause temporary waves of inflation that may foster instead of preventing financial stability. During periods of risk aversion such as fears of disruption of world financial markets and the global economy resulting from collapse of the European Monetary Union, carry trades are unwound with sharp deterioration of valuations of risk financial assets. More technical discussion is in IF Appendix: Transmission of Unconventional Monetary Policy at http://cmpassocregulationblog.blogspot.com/2012/01/financial-risk-aversion-and-collapse-of.html.

Table IA-1 provides annual equivalent rates of inflation for producer price indexes followed in this blog. The behavior of the US producer price index in 2011 shows neatly six waves. (1) In Jan-Apr, without risk aversion, US producer prices rose at the annual equivalent rate of 9.7 percent. (2) After risk aversion, producer prices increased in the US at the annual equivalent rate of 1.2 percent in May-Jul. (3) From Jul to Sep, under alternating episodes of risk aversion, producer prices increased at the annual equivalent rate of 6.6 percent. (4) Under the pressure of risk aversion because of the European debt crisis US producer prices fell at the annual equivalent rate of 1.2 percent in Oct-Nov. (5) From Dec 2011 to Jan 2012, US producer prices rose at the annual equivalent rate of 1.2 percent with relaxed risk aversion and commodity-price increases at the margin. (6) Inflation of producer prices returned with 2.4 percent annual equivalent in Feb-Mar 2012. Resolution of the European debt crisis if there is not an unfavorable growth event with political development in China would result in jumps of valuations of risk financial assets. Increases in commodity prices would cause the same high producer price inflation experienced in Jan-Apr. There are seven producer-price indexes in Table IA-1 for six countries (two for the UK) showing very similar behavior. Zero interest rates without risk aversion cause increases in commodity prices that in turn increase input and output prices. Producer price inflation rose at very high rates during the first part of 2011 for the US, China, Germany, France, Italy and the UK when risk aversion was contained. With the increase in risk aversion in May and Jun, inflation moderated because carry trades were unwound. Producer price inflation returned since July, with alternating bouts of risk aversion. In the final months of the year producer price inflation collapsed because of the disincentive to exposures in commodity futures resulting from fears of resolution of the European debt crisis. There is renewed worldwide inflation in the early part of 2012. Unconventional monetary policy fails in stimulating the overall real economy, merely introducing undesirable instability as monetary authorities cannot control allocation of floods of money at zero interest rates to carry trades into risk financial assets.

Table IA-1, Annual Equivalent Rates of Producer Price Indexes

INDEX 2011-2012

AE ∆%

US Producer Price Index

 

AE  ∆% Feb-Mar

2.4

AE  ∆% Dec-Jan

1.2

AE  ∆% Oct-Nov

-1.2

AE ∆% Jul-Sep

6.6

AE ∆% May-Jul

1.2

AE ∆% Jan-Apr

9.7

Japan Corporate Goods Price Index

 

AE % Feb-Mar

4.9

AE ∆% Dec-Feb

0.4

AE ∆% Jul-Nov

-2.1

AE ∆% May-Jun

-1.2

AE ∆% Jan-Apr

7.1

China Producer Price Index

 

AE ∆% Feb-Mar

2.4

AE ∆% Dec-Jan

-2.4

AE ∆% Jul-Nov

-3.1

AE ∆% Jan-Jun

6.4

Germany Producer Price Index

 

AE ∆% Dec-Feb

3.2

AE ∆% Oct-Dec

-0.4

AE ∆% Jul-Sep

2.8

AE ∆% May-Jun

0.6

AE ∆% Jan-Apr

10.3

France Producer Price Index for the French Market

 

AE ∆% Dec-Jan

3.0

AE ∆% Oct-Dec

2.8

AE ∆% Jul-Sep

2.4

AE ∆% May-Jun

-3.5

AE ∆% Jan-Apr

11.4

Italy Producer Price Index

 

AE ∆% Jan-Feb

7.4

AE ∆% Nov-Jan

4.5

AE ∆% Oct-Dec

0.4

AE ∆% Jul-Sep

2.4

AE ∆% May-Jun

-1.2

AE ∆% Jan-April

10.7

UK Output Prices

 

AE ∆% Feb-Mar

7.4

AE ∆% Nov-Jan

1.6

AE ∆% May-Oct

2.0

AE ∆% Jan-Apr

12.0

UK Input Prices

 

AE ∆% Jan-Mar

20.0

AE ∆% Nov-Dec

-1.2

AE ∆% May-Oct

-3.1

AE ∆% Jan-Apr

35.6

AE: Annual Equivalent

Sources: http://www.bls.gov/ppi/data.htm http://www.boj.or.jp/en/statistics/pi/cgpi_release/cgpi1203.pdf http://www.stats.gov.cn/english/pressrelease/t20120410_402797821.htm

https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/2012/03/PD12_099_61241.html

http://www.insee.fr/en/themes/info-rapide.asp?id=25&date=20120227

http://www.istat.it/it/archivio/58193

http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/march-2012/index.html

Similar world inflation waves are in the behavior of consumer price indexes of six countries and the euro zone in Table IA-2. US consumer price inflation shows six waves. (1) Under risk appetite in Jan-Apr consumer prices increased at the annual equivalent rate of 4.9 percent. (2) Risk aversion caused the collapse of inflation to annual equivalent 2.8 percent in May-Jul. (3) Risk appetite drove the rate of consumer price inflation in the US to 3.7 percent in Jul-Sep. (4) Gloomier views of carry trades caused the collapse of inflation in Oct-Nov to annual equivalent 0.6 percent. (5) Consumer price inflation resuscitated with increased risk appetite at annual equivalent of 1.2 percent in Dec 2011 to Jan 2012. (6) Consumer price inflation returned at 4.3 percent annual equivalent in Feb-Mar 2012. There is similar behavior in all the other consumer price indexes in Table IA-2. China’s CPI increased at annual equivalent 8.3 percent in Jan-Mar, 2.0 percent in Apr-Jun, 2.9 percent in Jul-Dec and resuscitated at 5.8 percent annual equivalent in Dec 2011 to Mar 2012. The euro zone harmonized index of consumer prices (HICP) increased at annual equivalent 5.2 percent in Jan-Apr, minus 2.4 percent in May-Jul, 3.9 percent in Aug-Dec but remained flat in Dec-Feb. The price indexes of the largest members of the euro zone, Germany, France and Italy, exhibit the same inflation waves. The United Kingdom CPI increased at annual equivalent 6.5 percent in Jan-Apr, falling to only 0.4 percent in May-Jul and then increasing at 4.7 percent in Aug-Dec. UK consumer prices increased at 2.0 percent annual equivalent from Dec 2011 to Feb 2012.

Table IA-2, Annual Equivalent Rates of Consumer Price Indexes

Index 2011-2012

AE ∆%

US Consumer Price Index

 

AE ∆% Feb-Mar

4.3

AE ∆% Dec-Jan

1.2

AE ∆% Oct-Nov

0.6

AE ∆% Jul-Sep

3.7

AE ∆% May-Jul

2.8

AE ∆% Jan-Apr

4.9

China Consumer Price Index

 
   

AE ∆% Dec-Mar

5.8

AE ∆% Jul-Nov

2.9

AE ∆% Apr-Jun

2.0

AE ∆% Jan-Mar

8.3

Euro Zone Harmonized Index of Consumer Prices

 

AE ∆% Dec-Feb

0.0

AE ∆% Aug-Dec

3.9

AE ∆% May-Jul

-2.4

AE ∆% Jan-Apr

5.2

Germany Consumer Price Index

 

AE ∆% Feb-Mar

6.2

AE ∆% Dec-Feb

1.6

AE ∆% Aug-Dec

2.7

AE ∆% May-Jul

-0.8

AE ∆% Jan-Apr

4.3

France Consumer Price Index

 

AE ∆% Feb-Mar

7.4

AE ∆% Dec-Feb

1.6

AE ∆% Aug-Nov

2.7

AE ∆% May-Jul

-0.8

AE ∆% Jan-Apr

4.3

Italy Consumer Price Index

 

AE ∆% Feb-Mar

5.5

AE ∆% Dec-Jan

4.3

AE ∆% Oct-Nov

3.0

AE ∆% Jul-Sep

2.4

AE ∆% May-Jun

1.2

AE ∆% Jan-Apr

4.9

UK Consumer Price Index

 

AE ∆% Dec-Feb

2.0

AE ∆% Aug-Dec

4.6

AE ∆% May-Jul

0.4

AE ∆% Jan-Apr

6.5

AE: Annual Equivalent

Sources: http://www.bls.gov/cpi/data.htm http://www.stats.gov.cn/english/pressrelease/t20120410_402797823.htm

http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-14032012-BP/EN/2-14032012-BP-EN.PDF

http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home

https://www.destatis.de/EN/PressServices/Press/pr/2012/04/PE12_134_611.html

http://www.insee.fr/en/themes/info-rapide.asp?id=29&date=20120412

http://www.istat.it/it/archivio/59216

http://www.ons.gov.uk/ons/rel/cpi/consumer-price-indices/february-2012/index.html

IIB United States Inflation. Monetary policy pursues symmetric inflation targets of maintaining core inflation of the index of personal consumption expenditures (core PCE) in an open interval of 2.00 percent. If inflation increases above 2.00 percent, the central bank could use restrictive monetary policy such as increases in interest rates to contain inflation in a tight range or interval around 2.00 percent. If inflation falls below 2 percent, the central bank could use restrictive monetary policy such as lowering interest rates to prevent inflation from falling too much below 2.00 percent. Currently, with about thirty million unemployed and underemployed (http://cmpassocregulationblog.blogspot.com/2012/04/thirty-million-unemployed-or.html), there may even be a policy bias to raise or at least ignore inflation, even with falling real wages, maintaining accommodation as a form of promoting full employment. There are two arguments in favor of symmetric inflation targets preventing inflation from falling to very low levels.

3. Room for interest rate policy. Nominal interest rates hardly ever fall below zero. In economic jargon, the floor of zero nominal interest rates is referred to as “the zero bound.” Symmetric targets are proposed to maintain a sufficiently high inflation rate such that interest rates can be lowered to promote economic activity when recession threatens. With inflation close to zero there is no room for lowering interest rates with policy tools.

4. Fear of Deflation. Inflation is a process of sustained increases in prices. Deflation is a process of sustained decreases in prices. The probability of deflation increases as inflation approximates zero. The influence of fear of deflation in monetary policy is discussed in Pelaez and Pelaez (International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-95).

Subsection IIB1 Long-term US Inflation evaluates long-term inflation in the US, concluding that there has not been deflation risk since World War II. Subsection IIB2 Current US Inflation finds no evidence in current inflation justifying fear of deflation. Subsection IIB3 Import Export Prices analyzes inflation in US international trade.

IIB1 Long-term US Inflation. Key percentage average yearly rates of the US economy on growth and inflation are provided in Table IB-1 updated with release of new data. The choice of dates prevents the measurement of long-term potential economic growth because of two recessions from IQ2001 (Mar) to IVQ2001 (Nov) with decline of GDP of 0.4 percent and the drop in GDP of 5.1 percent in IVQ2007 (Dec) to IIQ2009 (June) (http://www.nber.org/cycles.html) followed with unusually low economic growth for an expansion phase after recession with the economy growing at 1.6 percent IVQ2011 relative to IVQ2010 (http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-economic-growth-falling-real.html). Between 2000 and 2011, real GDP grew at the average rate of 1.6 percent per year, nominal GDP at 3.9 percent and the implicit deflator at 2.3 percent. Between 2000 and 2012, the average rate of CPI inflation was 2.5 percent per year and 2.0 percent excluding food and energy. PPI inflation increased at 3.0 percent per year on average and at 1.7 percent excluding food and energy. There is also inflation in international trade. Import prices grew at 3.1 percent per year between 2000 and 2012. The commodity price shock is revealed by inflation of import prices of petroleum increasing at 13.0 percent per year between 2000 and 2011 and at 12.7 percent between 2000 and 2012. The average growth rates of import prices excluding fuels are much lower at 2.0 percent for 2002 to 2011 and also 2.0 percent for 2000 to 2012. Export prices rose at the average rate of 2.6 percent between 2000 and 2011 and at 2.5 percent from 2000 to 2012. What spared the US of sharper decade-long deterioration of the terms of trade, (export prices)/(import prices), was its diversification and competitiveness in agriculture. Agricultural export prices grew at the average yearly rate of 7.3 percent from 2000 to 2011 and at 6.2 percent from 2000 to 2012. US nonagricultural export prices rose at 2.2 percent per year from 2000 to 2011 and at 2.1 percent from 2000 to 2012. The share of petroleum imports in US trade far exceeds that of agricultural exports. Unconventional monetary policy inducing carry trades in commodities has deteriorated US terms of trade, prices of exports relative to prices of imports, tending to reduce US aggregate real income. These dynamic growth rates are not similar to those for the economy of Japan where inflation was negative in seven of the 10 years in the 2000s.

Table IB-1, US, Average Growth Rates of Real and Nominal GDP, Consumer Price Index, Producer Price Index and Import and Export Prices, Percent per Year

Real GDP

2000-2011: 1.6%

Nominal GDP

2000-2011: 3.9%

Implicit Price Deflator

2000-2011: 2.3%

CPI

2000-2011: 2.5%
2000-2012: 2.5%

CPI ex Food and Energy

2000-2011: 2.0%
2000-2012: 2.0%

PPI

2000-2011: 3.00%
2000-2012: 3.0%

PPI ex Food and Energy

2000-2011: 1.6%
2000-2012: 1.7%

Import Prices

2000-2011: 3.1%
2000-2012: 3.1%

Import Prices of Petroleum and Petroleum Products

2000-2011: 13.0%
2000-2012:  12.7%

Import Prices Excluding Petroleum

2000-2011: 1.3%
2000-2012: 1.3%

Import Prices Excluding Fuels

2002-2011: 2.0%
2002-2012:  2.0%

Export Prices

2000-2011: 2.6%
2000-2012: 2.5%

Agricultural Export Prices

2000-2011: 7.3%
2000-2012: 6.2%

Nonagricultural Export Prices

2000-2011: 2.2%
2000-2012: 2.1%

Note: rates for price indexes in the row beginning with “CPI” and ending in the row “Nonagricultural Export Prices” are for Mar 2000 to Mar 2011 and for Mar 2000 to Mar 2012 using not seasonally adjusted indexes. Import prices excluding fuels are not available before 2002.

Sources: http://www.bea.gov/iTable/index_nipa.cfm http://www.bls.gov/ppi/data.htm

http://www.bls.gov/mxp/data.htm http://www.bls.gov/cpi/data.htm

Unconventional monetary policy of zero interest rates and large-scale purchases of long-term securities for the balance sheet of the central bank is proposed to prevent deflation. The data of CPI inflation of all goods and CPI inflation excluding food and energy for the past six decades show only one negative change by 0.4 percent in the CPI all goods annual index in 2009 but not one year of negative annual yearly change in the CPI excluding food and energy measuring annual inflation (http://cmpassocregulationblog.blogspot.com/2011/08/world-financial-turbulence-global.html). Zero interest rates and quantitative easing are designed to lower costs of borrowing for investment and consumption, increase stock market valuations and devalue the dollar. In practice, the carry trade is from zero interest rates to a large variety of risk financial assets including commodities. Resulting commodity price inflation squeezes family budgets and deteriorates the terms of trade with negative effects on aggregate demand and employment. Excessive valuations of risk financial assets eventually result in crashes of financial markets with possible adverse effects on economic activity and employment.

Producer price inflation history in the past five decades does not provide evidence of deflation. The finished core PPI does not register even one single year of decline. The headline PPI experienced only six isolated cases of decline (http://cmpassocregulationblog.blogspot.com/2011/08/world-financial-turbulence-global.html):

-0.3 percent in 1963,

-1.4 percent in 1986,

-0.8 percent in 1986,

-0.8 percent in 1998,

-1.3 percent in 2001

-2.6 percent in 2009.

Deflation should show persistent cases of decline of prices and not isolated events. Fear of deflation in the US has caused a distraction of monetary policy. Symmetric inflation targets around 2 percent in the presence of multiple lags in effect of monetary policy and imperfect knowledge and forecasting are mostly unfeasible and likely to cause price and financial instability instead of desired price and financial stability.

Chart IB-1 provides US nominal GDP from 1980 to 2010. The only major bump in the chart occurred in the recession of IVQ2007 to IIQ2009. Tendency for deflation would be reflected in persistent bumps. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.5 percent cumulatively and fell 45.6 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

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Chart IB-1, US, Nominal GDP 1980-2011

Source: US Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

Chart IB-2 provides US real GDP from 1980 to 2011. Persistent deflation threatening real economic activity would also be reflected in the series of long-term growth of GDP. There is no such behavior in Chart II-2 except for periodic recessions in the US economy that have occurred throughout history.

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Chart IB-2, US, Real GDP 1980-2011

Source: US Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

Deflation would also be in evidence in long-term series of prices in the form of bumps. The GDP implicit deflator series in Chart IB-3 from 1980 to 2011 shows rather dynamic behavior over time. The US economy is not plagued by deflation but by long-run inflation.

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Chart IB-3, US, GDP Implicit Price Deflator 1980-2011

Source: US Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

Chart IB-4 provides percent change from preceding quarter in prices of GDP at seasonally-adjusted annual rates (SAAR) from 1980 to 2011. There is one case of negative change in IIQ2009. There has not been actual deflation or risk of deflation in the US that would justify unconventional monetary policy.

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Chart IB-4, Percent Change from Preceding Period in Prices for GDP Seasonally Adjusted at Annual Rates 1980-2011

Source: US Bureau of Economic Analysis

http://www.bea.gov/iTable/index_nipa.cfm

Chart IB-5 provides percent change from preceding year in prices of GDP from 1980 to 2011. There was not one single year of deflation or risk of deflation in the past three decades.

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Chart IB-5, Percent Change from Preceding Year in Prices for Gross Domestic Product 1980-2011

Source: http://www.bea.gov/iTable/index_nipa.cfm

The producer price index of the US from 1960 to 2012 in Chart IB-6 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.

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Chart IB-6, US, Producer Price Index, Finished Goods, NSA, 1960-2012

Source: US Bureau of Labor Statistics

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

Chart IB-7 provides 12-month percentage changes of the producer price index from 1960 to 2012. The distinguishing event in Chart II-7 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.

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Chart IB-7, 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 IB-8. There is no evidence of persistent deflation in the US PPI.

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Chart IB-8, 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 IB-9 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.

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Chart IB-9, 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 IB-10. 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.

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Chart IB-10, US, Producer Price Index, Finished Energy Goods, NSA, 1974-2012

Source: US Bureau of Labor Statistics

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

Chart 1B-11 shows 12-month percentage change 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.

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Chart IB-11, 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

Chart IB-12 provides the consumer price index NSA from 1960 to 2012. The dominating characteristic is the increase in slope during the Great Inflation from the middle of the 1960s through the 1970s. There is long-term inflation in the US and no evidence of deflation risks.

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Chart IB-12, US, Consumer Price Index, NSA, 1960-2012

Source: US Bureau of Labor Statistics

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

Chart IB-13 provides 12-month percentage changes of the consumer price index from 1960 to 2012. There are actually three waves of inflation in the second half of the 1960s, in the mid 1970s and again in the late 1970s. Inflation rates then stabilized in a range with only two episodes above 5 percent.

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Chart IB-13, US, Consumer Price Index, All Items, 12- Month Percentage Change 1960-2012

Source: US Bureau of Labor Statistics

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

Chart IB-14 provides the consumer price index excluding food and energy from 1960 to 2012. There is long-term inflation in the US without episodes of deflation.

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Chart IB-14, US, Consumer Price Index Excluding Food and Energy, NSA, 1960-2012

Source: US Bureau of Labor Statistics

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

Chart IB-15 provides 12-month percentage changes of the consumer price index excluding food and energy from 1960 to 2012. There are three waves of inflation in the 1970s during the Great Inflation. There is no episode of deflation.

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Chart IB-15, US, Consumer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 1960-2012

Source: US Bureau of Labor Statistics

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

The consumer price index of housing is provided in Chart IB-16. There was also acceleration during the Great Inflation of the 1970s. The index flattens after the global recession in IVQ2007 to IIQ2009. Housing prices collapsed under the weight of construction of several times more housing than needed. Surplus housing originated in subsidies and artificially low interest rates in the shock of unconventional monetary policy in 2003 to 2004 in fear of deflation.

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Chart IB-16, US, Consumer Price Index Housing, NSA, 1967-2012

Source: US Bureau of Labor Statistics

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

Chart IB-17 provides 12-month percentage changes of the housing CPI. The Great Inflation also had extremely high rates of housing inflation. Housing is considered as potential hedge of inflation.

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Chart IB-17, US, Consumer Price Index, Housing, 12- Month Percentage Change, NSA, 1968-2012

Source: US Bureau of Labor Statistics

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

IB2 Current US Inflation. Consumer price inflation has fluctuated in recent months. Table IB-2 provides 12-month consumer price inflation in Mar and annual equivalent percentage changes for the months of Jan to Mar 2012 of the CPI and major segments. The final column provides inflation from Feb to Mar 2012. CPI inflation in the 12 months ending in Mar reached 2.7 percent, the annual equivalent rate Jan to Mar was higher at 3.7 percent and the monthly inflation rate of 0.3 percent also annualizes at 3.7 percent {[(1.003)12 – 1]100}. These inflation rates fluctuate in accordance with inducement of risk appetite or frustration by risk aversion of carry trades from zero interest rates to commodity futures. Excluding food and energy, CPI inflation was 2.3 percent in the 12 months ending in Mar and 2.0 percent in annual equivalent in Jan-Mar. There is no deflation in the US economy that could justify further quantitative easing. Consumer food prices in the US have risen 3.3 percent in 12 months in Mar and at 1.6 percent in annual equivalent in Jan-Mar. Monetary policies stimulating carry trades of commodities that increase prices of food constitute a highly regressive tax on lower income families for whom food is a major portion of the consumption basket. Energy consumer prices increased 4.6 percent in 12 months, 18.8 percent in annual equivalent in Jan-Mar and 0.9 percent in Mar (annualizing at 11.4 percent) as the carry trade from zero interest rates to commodity futures was unwound and repositioned during alternating risk aversion and risk appetite originating in the European debt crisis and increasingly in growth and politics in China. For lower income families, food and energy are a major part of the family budget. Inflation is not low or threatening deflation in annual equivalent in Jan-Mar in any of the categories in Table IB-2 but simply reflecting waves of inflation originating in carry trades. An upward trend is determined by carry trades from zero interest rates to commodity futures positions with episodes of risk aversion causing fluctuations.

Table IB-2, US, Consumer Price Index Percentage Changes 12 months NSA and Annual Equivalent ∆%

 

∆% 12 Months Mar 2012/Mar
2011 NSA

∆% Annual Equivalent Jan to Mar 2012 SA

∆% Mar/Feb SA

CPI All Items

2.7

3.7

0.3

CPI ex Food and Energy

2.3

2.0

0.2

Food

3.3

1.6

0.2

Food at Home

3.6

0.4

0.1

Food Away from Home

3.0

2.8

0.2

Energy

4.6

18.5

0.9

Gasoline

9.0

40.0

1.7

Fuel Oil

5.3

31.3

2.7

New Vehicles

2.5

3.2

0.2

Used Cars and Trucks

3.2

0.4

1.3

Medical Care Commodities

3.3

7.4

0.4

Apparel

4.9

2.0

0.5

Services Less Energy Services

2.3

2.0

0.2

Shelter

2.1

2.4

0.2

Transportation Services

1.4

0.4

0.3

Medical Care Services

3.5

2.0

0.3

Source: US Bureau of Labor Statistics http://www.bls.gov/news.release/pdf/cpi.pdf

The weights of the CPI, US city average for all urban consumers representing about 87 percent of the US population (http://www.bls.gov/cpi/cpiovrvw.htm#item1), are shown in Table IB-3 with the BLS update of Mar 7, 2012 (http://www.bls.gov/cpi/cpiri2011.pdf). Housing has a weight of 41.020 percent. The combined weight of housing and transportation is 58.895 percent or more than one half of consumer expenditures of all urban consumers. The combined weight of housing, transportation and food and beverages is 74.151 percent of the US CPI.

Table IB-3, US, Relative Importance, 2009-2010 Weights, of Components in the Consumer Price Index, US City Average, Dec 2011

All Items

100.000

Food and Beverages

15.256

  Food

   14.308

  Food at home

     8.638

  Food away from home

     5.669

Housing

41.020

  Shelter

    31.539

  Rent of primary residence

      6.485

  Owners’ equivalent rent

    23.957

Apparel

  3.562

Transportation

16.875

  Private Transportation

    15.694

  New vehicles

      3.195

  Used cars and trucks

      1.913

  Motor fuel

      5.463

    Gasoline

      5.273

Medical Care

7.061

  Medical care commodities

      1.716

  Medical care services

      5.345

Recreation

6.044

Education and Communication

6.797

Other Goods and Services

3.385

Note: reissued Mar 7, 2012. Refers to all urban consumers, covering approximately 87 percent of the US population (see http://www.bls.gov/cpi/cpiovrvw.htm#item1)

Source:

US Bureau of Labor Statistics http://www.bls.gov/cpi/cpiri2011.pdf

Chart IB-18 provides the US consumer price index for housing from 2001 to 2012. Housing prices rose sharply during the decade until the bump of the global recession and increased again in 2011 with some stabilization currently. The CPI excluding housing would likely show much higher inflation. Income remaining after paying for indispensable shelter has been compressed by the commodity carry trades resulting from unconventional monetary policy.

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Chart IB-18, US, Consumer Price Index, Housing, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

Chart IB-19 provides 12-month percentage changes of the housing CPI. Percentage changes collapsed during the global recession but have been rising into positive territory in 2011 and 2012.

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Chart IB-19, US, Consumer Price Index, Housing, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

There have been six waves of consumer price inflation in the US in 2011 that are illustrated in Table IB-4. The first wave occurred in Jan-Apr and was caused by the carry trade of commodity prices induced by unconventional monetary policy of zero interest rates. Cheap money at zero opportunity cost was channeled into financial risk assets, causing increases in commodity prices. The annual equivalent rate of increase of the all-items CPI in Jan-Apr was 4.9 percent and the CPI excluding food and energy increased at annual equivalent rate of 2.4 percent. The second wave occurred during the collapse of the carry trade from zero interest rates to exposures in commodity futures as a result of risk aversion in financial markets created by the sovereign debt crisis in Europe. The annual equivalent rate of increase of the all-items CPI dropped to 2.8 percent in May-Jul while the annual equivalent rate of the CPI excluding food and energy increased at 3.0 percent. In the third wave in Jul-Sep, the annual equivalent CPI rose at 3.7 percent while the core CPI increased at 2.0 percent. The fourth wave occurred in the form of decrease of the CPI all-items annual equivalent rate to 0.6 percent in Oct-Nov with the annual equivalent rate of the CPI excluding food and energy remaining at 2.4 percent. The fifth wave occurred in Dec-Jan with annual equivalent headline inflation of 1.2 percent and core inflation of 1.8 percent. In the sixth wave, headline CPI inflation increased at annual equivalent 4.3 percent in Feb-Mar and core CPI inflation at 1.8 percent. The conclusion is that inflation accelerates and decelerates in unpredictable fashion that turns symmetric inflation targets in a source of destabilizing shocks to the financial system and eventually the overall economy. Unconventional monetary policy of zero interest rates and withdrawal of bonds to lower long-term interest rates distorts risk/return decisions required for efficient allocation of resources and attaining optimal growth paths and prosperity.

Table IB-4, US, Headline and Core CPI Inflation Monthly SA and 12 Months NSA ∆%

 

All Items 

SA Month

All Items NSA 12 month

Core SA
Month

Core NSA
12 months

Mar 2012

0.3

2.7

0.2

2.3

Feb

0.4

2.9

0.1

2.2

AE ∆% Feb-Mar

4.3

 

1.8

 

Jan

0.2

2.9

0.2

2.3

Dec 2011

0.0

3.0

0.1

2.2

AE ∆% Dec-Jan

1.2

 

1.8

 

Nov

0.1

3.4

0.2

2.2

Oct

0.0

3.5

0.2

2.1

AE ∆% Oct-Nov

0.6

 

2.4

 

Sep

0.3

3.9

0.1

2.0

Aug

0.3

3.8

0.2

2.0

Jul

0.3

3.6

0.2

1.8

AE ∆% Jul-Sep

3.7

 

2.0

 

Jun

0.1

3.6

0.2

1.6

May

0.3

3.6

0.3

1.5

AE ∆%  May-Jul

2.8

 

3.0

 

Apr

0.4

3.2

0.2

1.3

Mar

0.5

2.7

0.2

1.2

Feb

0.4

2.1

0.2

1.1

Jan

0.3

1.6

0.2

1.0

AE ∆%  Jan-Apr

4.9

 

2.4

 

Dec 2010

0.4

1.5

0.1

0.8

Nov

0.2

1.1

0.1

0.8

Oct

0.3

1.2

0.0

0.6

Sep

0.1

1.1

0.0

0.8

Aug

0.2

1.1

0.1

0.9

Jul

0.2

1.2

0.1

0.9

Jun

0.0

1.1

0.1

0.9

May

-0.1

2.0

0.1

0.9

Apr

0.0

2.2

0.0

0.9

Mar

0.0

2.3

0.1

1.1

Feb

0.0

2.1

0.1

1.3

Jan

0.1

1.6

-0.1

1.6

Note: Core: excluding food and energy; AE: annual equivalent

Source: US Bureau of Labor Statistics

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

The behavior of the US consumer price index NSA from 2001 to 2011 is provided in Chart IB-20. Inflation in the US is very dynamic without deflation risks that would justify symmetric inflation targets. The hump in 2008 originated in the carry trade from interest rates dropping to zero into commodity futures. There is no other explanation for the increase of oil prices toward $140/barrel during the global recession. The unwinding of the carry trade with the TARP announcement of toxic assets in banks channeled cheap money into government obligations (see Cochrane and Zingales 2009).

clip_image034[1]

Chart IB-20, US, Consumer Price Index, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

Chart IB-21 provides 12-month percentage changes of the consumer price index from 2001 to 2012. There was no deflation or threat of deflation from 2008 into 2009. Commodity prices collapsed during the panic of toxic assets in banks. When stress tests in 2009 revealed US bank balance sheets in much stronger position, cheap money at zero opportunity cost exited government obligations and flowed into carry trades of risk financial assets. Increases in commodity prices drove again the all items CPI with interruptions during risk aversion originating in the sovereign debt crisis of Europe.

clip_image036[1]

Chart IB-21, US, Consumer Price Index, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

The trend of increase of the consumer price index excluding food and industry in Chart IB-22 does not reveal any threat of deflation that would justify symmetric inflation targets. There are mild oscillations in a neat upward trend.

clip_image038[1]

Chart IB-22, US, Consumer Price Index Excluding Food and Energy, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

Chart II-23 provides 12-month percentage change of the consumer price index excluding food and energy. Past-year rates of inflation fell toward 1 percent from 2001 into 2003 as a result of the recession and the decline of commodity prices beginning before the recession with declines of real oil prices. Near zero interest rates with fed funds at 1 percent between Jun 2003 and Jun 2004 stimulated carry trades of all types, including in buying homes with subprime mortgages in expectation that low interest rates forever would increase home prices permanently, creating the equity that would permit the conversion of subprime mortgages into creditworthy mortgages (Gorton 2009EFM; see http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Inflation rose and then collapsed during the unwinding of carry trades and the housing debacle of the global recession. Carry trade into 2011 and 2012 gave a new impulse to CPI inflation, all items and core. Symmetric inflation targets destabilize the economy by encouraging hunts for yields that inflate and deflate financial assets, obscuring risk/return decisions on production, investment and hiring.

clip_image040[1]

Chart IB-23, US, Consumer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

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

Headline and core producer price index are in Table IB-5. The headline PPI SA was flat in Mar while the 12-month rate NSA fell from 4.1 percent in Jan to 3.3 percent in Feb and 2.8 percent in Mar. The core PPI SA increased 0.3 percent in Mar and rose 2.9 percent in 12 months. Analysis of annual equivalent rates of change shows six different waves. 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 2.9 percent in 12 months ending in Mar 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 1.2 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-Mar was 2.4 percent for the headline PPI and 3.0 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 IB-5, US, Headline and Core PPI Inflation Monthly SA and 12 Months NSA ∆%

 

Finished
Goods SA
Month

Finished
Goods NSA 12 months

Finished Core SA
Month

Finished Core NSA
12 months

Mar 2012

0.0

2.8

0.3

2.9

Feb

0.4

3.3

0.2

3.0

AE ∆% Feb-Mar

2.4

 

3.0

 

Jan

0.1

4.1

0.4

3.0

Dec 2011

0.1

4.8

0.2

3.0

AE ∆% Dec-Jan

1.2

 

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 IB-24. 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.

clip_image080

Chart IB-24, 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 IB-25. 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.

clip_image082

Chart IB-25, 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 IB-26. There is here again a smooth trend of inflation instead of prolonged deflation as in Japan.

clip_image084

Chart IB-26, 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 IB-27. 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.

clip_image086

Chart IB-27, 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 IB-28. There is a clear upward trend with fluctuations that would not occur under persistent deflation.

clip_image088

Chart IB-28, US, Producer Price Index Finished Energy Goods, NSA, 2000-2012

Source: US Bureau of Labor Statistics

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

Chart IB-29 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.

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Chart IB-29, 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

Table IB-6 provides 12-month percentage changes of the CPI all items, CPI core and CPI housing from 2001 to 2011. There is no evidence in these data supporting symmetric inflation targets that would only induce greater instability in inflation, interest rates and financial markets. Unconventional monetary policy drives wide swings in allocations of positions into risk financial assets that generate instability instead of intended pursuit of prosperity without inflation. There is insufficient knowledge and imperfect tools to maintain the gap of actual relative to potential output constantly at zero while restraining inflation in an open interval of (1.99, 2.0). The impact on the overall economy and the financial system of errors of policy are magnified by large-scale policy doses of trillions of dollars of quantitative easing and zero interest rates. The US economy has been experiencing financial repression as a result of negative real rates of interest in the past few years and programmed in monetary policy statements until 2014 or, for practical purposes, forever. The essential calculus of risk/return in capital budgeting and financial allocations has been distorted.

Table IB-6, CPI All Items, CPI Core and CPI Housing, 12-Month Percentage Change, NSA 2001-2012

Mar

CPI All Items

CPI Core ex Food and Energy

CPI Housing

2012

2.7

2.3

1.7

2011

2.7

1.2

0.8

2010

2.3

1.1

-0.6

2009

-0.4

1.8

1.4

2008

4.0

2.4

3.0

2007

2.8

2.5

3.4

2006

3.4

2.1

3.7

2005

3.1

2.3

3.3

2004

1.7

1.6

2.0

2003

3.0

1.7

2.9

2002

1.5

2.4

2.1

2001

2.9

2.7

4.5

Source: US Bureau of Labor Statistics

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

IB3 Import Export Prices. Chart IB3-1 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.

clip_image092

Chart IB3-1, US, Prices of Total US Imports 2001=100, 2001-2012

Source: http://www.bls.gov/mxp/data.htm

Chart IB3-2 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.

clip_image094

Chart IB3-2, US, Prices of Total US Imports, 12-Month Percentage Changes, 2001-2012

Source: http://www.bls.gov/mxp/data.htm

Chart IB3-3 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.

clip_image096

Chart IB3-3, US, Prices of Total US Imports, 2001=100, 1982-2012

Source: http://www.bls.gov/mxp/data.htm

Chart IB3-4 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.

clip_image098

Chart IB3-4, US, Prices of Total US Imports, 12-Month Percentage Changes, 1982-2012

Source: http://www.bls.gov/mxp/data.htm

Chart IB3-5 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 IIC-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.

clip_image100

Chart IB3-5, US, Prices of Total US Exports, 2001=100, 2001-2012

Source: http://www.bls.gov/mxp/data.htm

Chart IB3-6 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.

clip_image102

Chart IB3-6, US, Prices of Total US Exports, 2001=100, 1982-2012

Source: http://www.bls.gov/mxp/data.htm

Chart IB3-7 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.

clip_image104

Chart IB3-7, 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 IB3-1. 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 15.2 percent in the twelve months ending in Mar 2008 and fell 14.9 percent in the 12 months ending in Mar 2009 when risk aversion developed in 2008 until mid 2009. Import prices rose again sharply in 2010 by 11.2 percent and in 2011 by 10.3 percent until carry trades were unwound in May 2011 in the presence of zero interest rates with relaxed mood of risk aversion. 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 IB3-1, US, Twelve-Month Percentage Rates of Change of Prices of Exports and Imports

 

Imports

Imports Ex Fuels

Exports

Exports Non-Ag

Mar 2012

3.4

2.0

0.9

1.7

Mar 2011

10.3

4.4

9.5

7.1

Mar 2010

11.2

2.7

4.9

4.6

Mar 2009

-14.9

-2.8

-6.7

-5.0

Mar 2008

15.2

5.1

7.9

5.5

Mar 2007

2.8

2.6

5.4

4.3

Mar 2006

4.5

0.7

2.3

2.5

Mar 2005

7.6

2.5

3.3

4.5

Mar 2004

1.1

2.1

3.3

1.8

Mar 2003

6.8

0.6

2.2

1.6

Mar 2002

-5.6

NA

-2.4

-2.4

Mar 2001

-1.6

NA

0.0

-0.1

Source: http://www.bls.gov/mxp/data.htm#

Chart IB3-8 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 and zero interest rates while under strong risk aversion there are declines of nominal values.

clip_image106

Chart IB3-8, 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 IB3-9 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.

clip_image108

Chart IB3-9, 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 IB3-10 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.

clip_image110

Chart IB3-10, US, Import Price Index ex Petroleum, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

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

Chart IB3-11 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.

clip_image112

Chart IB3-11, US, Import Price Index ex Petroleum, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

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

Chart IB3-12 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.

clip_image114

Chart IB3-12, 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 IB3-13 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.

clip_image116

Chart IIC-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 IB3-14. There is similar behavior of the curves all driven by the same impulses of monetary policy.

clip_image118

Chart IB3-14, 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 IB3-15 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.

clip_image120

Chart IB3-15, 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 IB3-16 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).

clip_image122

Chart IB3-16, 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 IB3-17 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.

clip_image124

Chart IB3-17, 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 IB3-18 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.

clip_image126

Chart IB3-18, 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 IB3-19 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.

clip_image128

Chart IB3-19, 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 IB3-20 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.

clip_image130

Chart IB3-20, 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 IB3-21 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.

clip_image132

Chart IB3-21, 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 IB3-22 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.

clip_image134

Chart IB3-22, 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

II 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 (http://cmpassocregulationblog.blogspot.com/2012/04/thirty-million-unemployed-or.html) 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. 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. IIA Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IIB 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 IIC Ten Million Fewer Full-time Jobs. IID Youth Unemployment provides the data on high unemployment of ages 16 to 24 years.

IIA 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 II-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 ten 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-economic-growth-falling-real.html). 

Table II-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 II-1 provides the yearly levels of total nonfarm hiring (NFH) in Table II-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.

clip_image002[1]

Chart II-1, US, Total Nonfarm Hiring (HNF), Yearly, 2001-2011

Source: US Bureau of Labor Statistics

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

Chart II-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.

clip_image004[1]

Chart II-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 II-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 II-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 II-3 plots yearly percentage changes of nonfarm hiring. Percentage declines after 2007 were quite sharp.

clip_image006[1]

Chart II-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 II-4. There has been sharp contraction of total private hiring in the US and only milder recovery in 2011 than in 2010.

clip_image008[1]

Chart II-4, US, Total Private Hiring, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

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

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

clip_image010[1]

Chart II-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 Feb in the years from 2001 to 2012 in Table II-3. Hiring numbers are in thousands. There is some recovery in HNF from 3124 thousand (or 3.1 million) in Feb 2010 to 3335 thousand in Feb 2011 and 3580 thousand in Feb 2012 for cumulative gain of 14.6 percent. HP rose from 2921 thousand in Feb 2010 to 3169 thousand in Feb 2011 and 3358 thousand in Feb 2012 for cumulative gain of 14.9 percent. HNF has fallen from 4421 in Feb 2005 to 3580 in Feb 2012 or by 19.0 percent. HP has fallen from 4176 in Feb 2006 to 3358 in Feb 2012 or by 19.6 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 II-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 Feb

4399

3.4

4136

3.8

2002 Feb

4007

3.1

3774

3.5

2003 Feb

3821

3.0

3617

3.4

2004 Feb

3840

3.0

3618

3.4

2005 Feb

4305

3.3

4079

3.7

2006 Feb

4421

3.3

4176

3.7

2007 Feb

4265

3.1

4001

3.5

2008 Feb

4012

2.9

3782

3.3

2009 Feb

3273

2.5

3090

2.8

2010 Feb

3124

2.4

2921

2.8

2011 Feb

3335

2.6

3169

3.0

2012 Feb

3580

2.7

3358

3.1

Source:  US Bureau of Labor Statistics

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

Chart II-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 3580 in Feb 2012. Chart II-6 provides seasonally-adjusted (SA) monthly data. The number of seasonally-adjusted hires in Sep 2011 was 4221 thousand, increasing to 4385 thousand in Feb 2012, or 2.5 percent. The number of hires not seasonally adjusted was 4507 in Sep, falling to 3038 in Dec but increasing to 4072 in Jan 2012 and falling again to 3580 in Feb 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.

clip_image012[1]

Chart II-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 II-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 Feb 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 2.7 in Feb 2012. Rates of nonfarm hiring NSA were in the range of 2.8 (Dec) to 4.5 (Jun) in 2006.

clip_image014[1]

Chart II-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 II-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 4075 in Feb 2012 for increase of 1.8 percent relative to 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 3358 in Feb 2012 or decline of 18.7 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 ten 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-economic-growth-falling-real.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

clip_image016[1]

Chart II-8, US, Total Private Hiring Month SA 2011-2012

Source: US Bureau of Labor Statistics

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

Chart II-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 Feb 2012. The rate not seasonally adjusted (NSA) fell from 3.8 in Sep to 2.6 in Dec, increasing to 3.4 in Jan 2012 but falling to 3.1 in Feb 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.

clip_image018[1]

Chart II-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 II-4 for the month of Feb from 2001 to 2012. The final column provides TNF LD for the years from 2001 to 2010. Nonfarm job openings fell from a peak of 4267 in Feb 2076 to 3306 in Feb 2012 or by 22.5 percent while the rate dropped from 3.0 to 2.5. Nonfarm layoffs and discharges (TNF LD) rose from 1420 in Feb 2006 to 2032 in Feb 2009 or by 43.1 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 II-4, US, Job Openings and Total Separations, Thousands NSA

 

TNF JOB

TNF JOB
Rate

TNF LD

TNF LD
Year

Feb 2001

4389

3.2

1442

24499

Feb 2002

3164

2.4

1624

22922

Feb 2003

3174

2.4

1611

23294

Feb 2004

3209

2.4

1559

22802

Feb 2005

3550

2.6

1573

22185

Feb 2006

4088

3.0

1420

21157

Feb 2007

4267

3.0

1449

22142

Feb 2008

3870

2.8

1508

24166

Feb 2009

2653

2.0

2032

26783

Feb 2010

2441

1.9

1426

21784

Feb 2011

2873

2.2

1276

20718

Feb 2012

3306

2.5

1310

 

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 II-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 3477 seasonally adjusted in Jan 2012 relative and 3498 in Feb 2012 but fell from 3501 in Sep 2011. Job openings recovered in Dec at 3540 but fell into Jan and Feb 2012. 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 3661 in Jan 2012 but then falling to 3306 in Feb 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 ten 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-economic-growth-falling-real.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

clip_image136

Chart II-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 II-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 but fell to 2.5 in Feb 2012. The rate of job openings NSA fell from 3.5 in Apr 2006 to 1.9 in Apr 2009, recovering insufficiently to 2.5 in Feb 2012.

clip_image138

Chart II-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 II-12. Separations are much lower in 2012 than before the global recession.

clip_image140

Chart II-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 II-13. Separations are much lower in 2011 than before the global recession.

clip_image142

Chart II-13, US, Total Separations, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

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

Table II-5 provides total nonfarm total separations from 2001 to 2010. Separations fell from 61.6 million in 2006 to 47.6 million in 2010 or by 14.0 million and 48.2 million in 2011 or by 13.4 million.

Table II-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 II-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.

clip_image144

Chart II-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 II-15 rose sharply to a peak in 2009. There was pronounced drop into 2010 and 2011.

clip_image146

Chart II-15, US, Total Nonfarm Layoffs and Discharges, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

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

Table II-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 II-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

IIB Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table II-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 14.8 in Feb 2012.

Table II-7, US, Alternative Measures of Labor Underutilization %

 

U1

U2

U3

U4

U5

U6

Mar 2012 NSA

4.6

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
NSA

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
NSA

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 II-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 Mar 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 29.4 million in job stress of unemployment/underemployment in Mar 2012, not seasonally adjusted, corresponding to 18.3 percent of the labor force (http://cmpassocregulationblog.blogspot.com/2012/04/thirty-million-unemployed-or.html Table I-4).

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

 

Mar  2012

Feb   2012

Jan    2012

Dec    2011

Nov
2011

Oct 2011

Sep 2011

Aug  2011

U1

4.6

4.8

4.9

5.0

5.0

5.1

5.3

5.3

U2

4.5

4.7

4.7

4.9

4.9

5.1

5.2

5.3

U3

8.2

8.3

8.3

8.5

8.7

8.9

9.0

9.1

U4

8.7

8.9

8.9

9.1

9.3

9.5

9.6

9.6

U5

9.6

9.8

9.9

10.0

10.2

10.4

10.5

10.6

U6

14.5

14.9

15.1

15.2

15.6

16.0

16.4

16.2

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

Source: http://www.bls.gov/cps/data.htm

Chart II-16 provides U6 on a monthly basis from 2001 to 2011. 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 Jan, Feb and Mar 2012.

clip_image148

Chart II-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 II-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.

clip_image150

Chart II-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 7.672 million in Mar 2012, seasonally adjusted, or decline of 1.598 million in just six months, as shown in Table II-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. 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. 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. 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 Mar 2012 is 113.916 million, which is lower by 9.3 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 ten 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/2012/04/mediocre-economic-growth-falling-real.html).

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

 

Part-time Thousands

Full-time Millions

Seasonally Adjusted

   

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

   

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

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

113.138

Oct 2010

8,408

112.342

Mar 2010

9,343 (high)

109.877

Feb 2010

9,282

109.100

Jan 2010

9,290

108.770 (low)

Mar 2009

9,305

112.215

Feb 2009

9,170

112.947

Jan 2009

8,829

113.815

Feb 2008

5,114

119.452

Mar 2008

5,038

119.875

Jan 2008

5,340

119.322

Jul 2007

4,516

123.219 (high)

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

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 II-18 shows the sharp rise in unemployed over 27 weeks and stabilization at an extremely high level.

clip_image020[1]

Chart II-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 II-19 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.

clip_image022[1]

Chart II-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

IIC Ten Million Fewer Full-time Jobs. Chart II-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.

clip_image024[1]

Chart II-20, US, Full-time Employed, Thousands, NSA, 2001-2012

Sources: US Bureau of Labor Statistics

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

IID Youth Unemployment. The United States is experiencing high youth unemployment as in European economies. Table II-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 II-10, US, Employment Level 16-24 Years, Thousands, NSA

Year

Jan

Feb

Mar

Annual

2001

19678

19745

19800

20088

2002

18653

19074

19091

19683

2003

18811

18880

18709

19351

2004

18852

18841

18752

19630

2005

18858

18670

18989

19770

2006

19003

19182

19291

20041

2007

19407

19415

19538

19875

2008

18724

18546

18745

19202

2009

17467

17606

17564

17601

2010

16166

16412

16587

17077

2011

16512

16638

16898

17362

2012

16944

17150

17301

 

Sources: US Bureau of Labor Statistics

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

Chart II-21 provides US employment level ages 16 to 24 years from 2002 to 2012. Employment level is sharply lower in Mar 2012 relative to the peak in 2007.

clip_image026[1]

Chart II-21, US, Employment Level 16-24 Years, Thousands SA, 2002-2012

Sources: US Bureau of Labor Statistics

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

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

Year

Jan

Feb

Mar

Annual

2001

2250

2258

2253

2371

2003

2748

2740

2601

2746

2004

2767

2631

2588

2638

2005

2661

2787

2520

2521

2006

2366

2433

2216

2353

2007

2363

2230

2096

2342

2008

2633

2480

2347

2830

2009

3278

3457

3371

3760

2010

3983

3888

3748

3857

2011

3851

3696

3520

3634

2012

3416

3507

3294

 

Sources: US Bureau of Labor Statistics

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

Chart II-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.

clip_image028[1]

Chart II-22, US, Unemployment Level 16-24 Years, Thousands SA, 2002-2012

Sources: US Bureau of Labor Statistics

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

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

Year

Jan

Feb

Mar

Annual

2001

10.3

10.3

10.2

10.6

2002

12.9

12.5

12.9

12.0

2003

12.7

12.7

12.2

12.4

2004

12.8

12.3

12.1

11.8

2005

12.4

13.0

11.7

11.3

2006

11.1

11.3

10.3

10.5

2007

10.9

10.3

9.7

10.5

2008

12.3

11.8

11.1

12.8

2009

15.8

16.4

16.1

17.6

2010

19.8

19.2

18.4

18.4

2011

18.9

18.2

17.2

17.3

2012

16.8

17.0

16.0

 

Sources: US Bureau of Labor Statistics

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

Chart II-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 ten quarters of expansion of the economy since IIIQ2009.

clip_image030[1]

Chart II-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 II-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 ten quarters of expansion from IIIQ2009 to IVQ2011 (see Table I-5 at http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-economic-growth-falling-real.html). The fractured US labor market denies an early start for young people.

clip_image032[1]

Chart II-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1979-2012

Sources: US Bureau of Labor Statistics

http://www.bls.gov/cps/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 Mar 30 and daily values throughout the week ending on Fri Apr 6 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 Apr 6 and the percentage change in that prior week below the label of the financial risk asset. For example, the US dollar (USD) appreciated 0.1 percent to USD 1.3078/EUR in the week ending on Apr 6. 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 1.3096/EUR in the first row, first column in the block for currencies in Table III-1 for Fri Apr 6, depreciating to USD 1.3110/EUR on Mon Apr 8, or by 0.1 percent. The dollar depreciated because more dollars, $1.3110, were required on Mon Apr 9 to buy one euro than $1.3096 on Apr 6. 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 1.3084/EUR on Apr 10; 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 Apr 6, to the last business day of the current week, in this case Fri Apr 13, such as appreciation by 0.1 percent to USD 1.3078/EUR by Apr 13; 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 0.1 percent from the rate of USD 1.3096/EUR on Fri Apr 6 to the rate of USD 1.3078/EUR on Fri Apr 13 {[(1.3078/1.3096) – 1]100 = -0.1%} and depreciated (denoted by negative sign) by 0.6 percent from the rate of USD 1.3108 on Wed Apr 11 to USD 1.3191/EUR on Thus Apr 12 {[(1.3191/1.3108) -1]100 = 0.6%}. 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 Apr 9 to Apr 13, 2012

Fri Apr 6, 2012

Mon 9

Tue 10

Wed 11

Thu 12

Fr 13

USD/EUR

1.3096

1.8%

1.3110

-0.1%

-0.1%

1.3084

0.1%

0.2%

1.3108

-0.1%

-0.2%

1.3191

-0.7%

-0.6%

1.3078

0.1%

0.9%

JPY/  USD

81.63

1.4%

81.58

0.1%

0.1%

80.69

1.2%

1.1%

80.87

0.9%

-0.2%

80.89

0.9%

0.0%

80.92

0.9%

0.0%

CHF/  USD

0.9169

-1.6%

0.9169

0.0%

0.0%

0.9183

-0.2%

-0.2%

0.9174

-0.1%

0.1%

0.9111

0.6%

0.7%

0.9195

-0.3%

-0.9%

CHF/ EUR

1.2009

0.3%

1.2021

-0.1%

-0.1%

1.2016

-0.1%

0.0%

1.2025

-0.1%

0.1%

1.2017

-0.1%

0.1%

1.2024

-0.1%

-0.1%

USD/  AUD

1.0309

0.9700

-0.4%

1.0315

0.9695

0.1%

0.1%

1.0254

0.9752

-0.5%

-0.6%

1.0299

0.9710

-0.1%

0.4%

1.0442

0.9577

1.3%

1.4%

1.0372

0.9641

0.6%

-0.7%

10 Year  T Note

2.058

2.04

1.98

2.03

2.05

1.987

2 Year     T Note

0.31

0.31

0.29

0.29

0.29

0.27

German Bond

2Y 0.14 10Y 1.74

2Y 0.14 10Y 1.74

2Y 0.10 10Y 1.64

2Y 0.14 10Y 1.78

2Y 0.14 10Y 1.79

2Y 0.13 10Y 1.74

DJIA

13060.14

-1.1%

12929.59

-1.0%

-1.0%

12715.93

-2.6%

-1.7%

12805.39

-1.9%

0.7%

12986.58

-0.6%

1.4%

12849.59

-1.6%

-1.1%

DJ Global

1950.61

-2.4%

1937.08

-0.7%

-0.7%

1903.47

-2.4%

-1.7%

1913.65

-1.9%

0.5%

1937.05

-0.7%

1.2%

1909.67

-2.1%

-1.4%

DJ Asia Pacific

1275.69

-1.5%

1267.82

-0.6%

-0.6%

1266.32

-0.7%

-0.1%

1257.81

-1.4%

-0.7%

1267.82

-0.6%

0.8%

1278.01

0.2%

0.8%

Nikkei

9688.45

-3.9%

9546.26

-1.5%

-1.5%

9538.02

-1.6%

-0.1%

9458.74

-2.4%

-0.8%

9524.79

-1.7%

0.7%

9637.99

-0.5%

1.2%

Shanghai

2306.55

1.9%

2285.78

-0.9%

-0.9%

2305.86

0.0%

0.9%

2308.92

0.1%

0.1%

2350.86

1.9%

1.8%

2359.16

2.3%

0.4%

DAX

6775.26

-2.5%

6775.26

-2.5%

-0.1%

6606.43

-2.5%

-2.5%

6674.73

-1.5%

1.0%

6743.24

-0.5%

1.0%

6583.90

-2.8%

-2.4%

DJ UBS

Comm.

141.66

-0.2%

140.89

-0.5%

-0.5%

139.38

-1.6%

-1.3%

139.63

-1.4%

0.2%

141.35

-0.2%

1.2%

139.46

-1.6%

-1.4%

WTI $ B

103.31

0.3%

102.29

-1.0%

-1.0%

101.22

-2.0%

-1.0%

102.56

-0.7%

1.3%

103.71

0.4%

1.1%

102.83

-0.5%

-0.8%

Brent    $/B

123.43

0.4%

122.63

-0.6%

-0.6%

119.79

-2.9%

-2.3%

119.91

-2.9%

0.1%

121.71

-1.4%

1.5%

121.22

-1.8%

-0.4%

Gold  $/OZ

1630.1

-2.5%

1642.7

0.8%

0.8%

1658.7

1.8%

1.0%

1658.9

1.8%

0.0%

1677.3

2.9%

1.1%

1658.2

1.7%

-1.1%

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

Economic and financial information on Spain and China drove risk during the week. First, there are renewed concerns on the ability of Spain to move forward its program of fiscal and financial adjustment without disruption in the form of difficulties in financing in international debt markets. 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. Second, China’s economy continued to decelerate in the first quarter of 2012. More detailed analysis is provided in subsection VC China. GDP grew at 8.1 percent in IQ2012 relative to a year earlier. The quarterly rate of growth of 1.8 percent in IQ2012 is equivalent to 7.4 percent in a year of four quarters. Other critical issues in China are (1) the change in model of growth from high domestic investment to internal consumption; and (2) political development regarding the decennial change in political structure and leadership at the end of the year.

The JPY continued to reverse recent depreciation, appreciating 0.9 percent during the week of Apr 13. 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 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 0.3 percent in the week of Apr 13 to CHF 0.9195/USD relative to the dollar and depreciated 0.1 percent relative to the euro to CHF 1.2024, as shown in Table III-1. The important event in the prior week 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 depreciated 0.4 percent to USD 1.0309/AUD by Apr 6 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 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 on Apr 13 because of increasing risk aversion. 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. 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 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. 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 March 13, 2012 does not have sufficient changes suggesting that it contributed to the rise in Treasury yields. The statement continues to consider inflation low, unemployment high and growth at a moderate pace. Because of the “slack” in the economy, the FOMC maintained the zero interest rate policy until 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20120313a.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 Feb 2012 (http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-14032012-BP/EN/2-14032012-BP-EN.PDF) and flash estimate of 2.6 percent for the 12 months ending in Mar (http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-30032012-AP/EN/2-30032012-AP-EN.PDF) but the yield of the two-year German government bond fell from 0.23 on Mar 23 to 0.21 percent on Mar 30, 0.14 percent on Apr 6 and 0.13 percent on Apr 13 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, as shown in Table III-1. 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 weak during the week of Apr 13 because of the new factors of risk aversion. Germany’s Dax fell 2.8 percent while DJIA lost 1.6 percent in the week of Apr 13 and Dow Global fell 2.1 percent. Japan’s Nikkei Average interrupted recent increases with decline of 3.9 percent in the week of Apr 6 and decline of 0.5 percent in the week of Apr 13. Dow Asia Pacific increased 0.2 percent in the week of Apr 13 while Shanghai’s composite increased 2.3 percent.

Commodities were mixed during the week of Apr 6. The DJ UBS Commodities Index dropped 1.6 percent. WTI lost 0.5 percent and Brent decreased 1.9 percent. Gold rose 1.7 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-1A 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” increased from €546,747 million on Dec 31, 2010, to €870,130 million on Dec 28, 2011 and €1,154,483 million on Apr 6, 2012. The sum of line 5 and line 7 (“Securities of Euro Area Residents Denominated in Euro”) has increased to €1,782,433 million in the statement of Apr 6.

Table III-1A, Consolidated Financial Statement of the Eurosystem, Million EUR

 

Dec 31, 2010

Dec 28, 2011

Apr 6, 2012

1 Gold and other Receivables

367,402

419,822

423,706

2 Claims on Non Euro Area Residents Denominated in Foreign Currency

223,995

236,826

240,334

3 Claims on Euro Area Residents Denominated in Foreign Currency

26,941

95,355

53,771

4 Claims on Non-Euro Area Residents Denominated in Euro

22,592

25,982

19,870

5 Lending to Euro Area Credit Institutions Related to Monetary Policy Operations Denominated in Euro

546,747

879,130

1,154,483

6 Other Claims on Euro Area Credit Institutions Denominated in Euro

45,654

94,989

60,752

7 Securities of Euro Area Residents Denominated in Euro

457,427

610,629

627,950

8 General Government Debt Denominated in Euro

34,954

33,928

31,131

9 Other Assets

278,719

336,574

344,337

TOTAL ASSETS

2,004, 432

2,733,235

2,965,333

Memo Items

     

Sum of 5 and  7

1,004,174

1,489,759

1,782,433

Capital and Reserves

78,143

81,481

83,887

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/fs120411.en.html

There is extremely important information in Table III-9 for the current sovereign risk crisis in the euro zone. Table III-1B provides the structure of regional and country relations of Germany’s exports and imports with newly available data for Feb. German exports to other European Union (EU) members are 58.5 percent of total exports in Feb 2012 and 58.9 percent in Jan-Feb 2012. Exports to the euro area are 38.8 percent in Feb and 39.3 percent in Jan-Feb. Exports to third countries are 37.9 percent of the total in Feb and 41.1 percent in Jan-Feb. 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-1B, Germany, Structure of Exports and Imports by Region, € Billions and ∆%

 

Feb 2012 
€ Billions

Feb 12-Month
∆%

Jan–Feb 2012 € Billions

Jan-Feb 2012/
Jan-Dec 2011 ∆%

Total
Exports

91.3

8.6

177.3

8.9

A. EU
Members

53.4

% 58.5

5.4

104.4

% 58.9

5.4

Euro Area

35.4

% 38.8

3.3

69.7

% 39.3

4.0

Non-euro Area

18.0

% 19.7

9.7

34.7

% 19.6

8.5

B. Third Countries

37.9

% 41.5

13.4

72.9

% 41.1

14.4

Total Imports

76.5

6.1

149.3

6.2

C. EU Members

48.7

% 63.7

6.6

93.6

% 62.7

6.9

Euro Area

34.1

% 44.6

5.5

65.5

% 43.9

6.3

Non-euro Area

14.6

% 19.1

9.3

28.1

% 18.8

8.6

D. Third Countries

27.8

% 36.3

5.2

55.8

% 37.4

4.9

Notes: Total Exports = A+B; Total Imports = C+D

Source:

Statistiche Bundesamt Deutschland

https://www.destatis.de/EN/PressServices/Press/pr/2012/04/PE12_129_51.html

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” increased from €546,747 million on Dec 31, 2010, to €870,130 million on Dec 28, 2011 and €1,154,483 million on Apr 6, 2012. The sum of line 5 and line 7 (“Securities of Euro Area Residents Denominated in Euro”) has increased to €1,782,433 million in the statement of Apr 6.

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

Apr 6, 2012

1 Gold and other Receivables

367,402

419,822

423,706

2 Claims on Non Euro Area Residents Denominated in Foreign Currency

223,995

236,826

240,334

3 Claims on Euro Area Residents Denominated in Foreign Currency

26,941

95,355

53,771

4 Claims on Non-Euro Area Residents Denominated in Euro

22,592

25,982

19,870

5 Lending to Euro Area Credit Institutions Related to Monetary Policy Operations Denominated in Euro

546,747

879,130

1,154,483

6 Other Claims on Euro Area Credit Institutions Denominated in Euro

45,654

94,989

60,752

7 Securities of Euro Area Residents Denominated in Euro

457,427

610,629

627,950

8 General Government Debt Denominated in Euro

34,954

33,928

31,131

9 Other Assets

278,719

336,574

344,337

TOTAL ASSETS

2,004, 432

2,733,235

2,965,333

Memo Items

     

Sum of 5 and  7

1,004,174

1,489,759

1,782,433

Capital and Reserves

78,143

81,481

83,887

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/fs120411.en.html

Table III-3, Italy, Exports and Imports by Regi 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 currency prevents Italy from devaluation to parity or the exchange rate that would permit export growth to promote internal economic activity that generates 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 42.6 percent of the total. Exports to the non-European Union area are growing at 4.8 percent in Jan 2012 relative to Jan 2011 while those to EMU are growing at 2.9 percent.

Table III-3, Italy, Exports and Imports by Regions and Countries, % Share and 12-Month ∆%

 

Exports
% Share

∆% Jan 2012/ Jan 2011

Imports
% Share

Imports
∆% Jan 2012/ Jan 2011

EU

56.0

3.9

53.3

-5.4

EMU 17

42.6

2.9

43.2

-5.2

France

11.6

4.2

8.3

-3.7

Germany

13.1

7.6

15.6

-4.9

Spain

5.3

-3.6

4.5

-6.2

UK

4.7

9.1

2.7

-12.5

Non EU

44.0

4.8

46.7

0.2

Europe non EU

13.3

21.9

11.1

-2.8

USA

6.1

-19.1

3.3

15.2

China

2.7

-11.8

7.3

-15.8

OPEC

4.7

15.4

8.6

13.6

Total

100.0

4.3

100.0

-2.6

Notes: EU: European Union; EMU: European Monetary Union (euro zone)

Source: http://www.istat.it/it/archivio/57081

Table III-4 provides Italy’s trade balance by regions and countries. Italy has a trade deficit of €44 million with the 17 countries of the euro zone (EMU 17). Depreciation to parity could permit greater competitiveness in improving the trade surpluses of €98 million with Europe non European Union and of €256 million with the US. There is significant rigidity in the trade deficits of €1732 million with China and €2581 million with oil exporting countries (OPEC).

Table III-4, Italy, Trade Balance by Regions and Countries, Millions of Euro 

Regions and Countries

Trade Balance Jan 2012 Millions of Euro

Trade Balance Cumulative Jan 2012 Millions of Euro

EU

756

756

EMU 17

-44

-44

France

831

831

Germany

-399

-399

Spain

326

326

UK

636

636

Non EU

-5,106

-5,106

Europe non EU

98

98

USA

256

256

China

-1,732

-1,732

OPEC

-2,581

-2,581

Total

-4,350

-4,350

Notes: EU: European Union; EMU: European Monetary Union (euro zone)

Source: http://www.istat.it/it/archivio/57081

Growth rates of Italy’s trade and major products are provided in Table III-5 for the period Jan 2012 relative to Jan 2011. Growth rates are high for the total and all segments with the exception of decline of durable goods imports of 4.5 percent and decline of exports of 0.2 percent. Capital goods exports decreased 0.3 percent relative to a year earlier but imports of capital goods fell 6.6 percent and exports of intermediate products rose 4.2 percent.

Table III-5, Italy, Exports and Imports % Share of Products in Total and ∆%

 

Exports
Share %

Exports
∆% Jan 2012/ Jan 2011

Imports
Share %

Imports
∆% Jan 2012/ Jan 2011

Consumer
Goods

28.9

5.6

25.0

0.8

Durable

5.9

-0.2

3.0

-4.5

Non
Durable

23.0

6.9

22.0

1.6

Capital Goods

32.2

-0.3

20.8

-6.6

Inter-
mediate Goods

34.3

4.2

34.5

-11.9

Energy

4.7

23.2

19.7

11.8

Total ex Energy

95.3

3.2

80.3

-6.6

Total

100.0

4.3

100.0

-2.6

Source: http://www.istat.it/it/archivio/57081

Table III-6 provides Italy’s trade balance by product categories in Jan 2012. Italy’s trade balance excluding energy is a surplus of €1781 million in Jan 2012 but the energy trade balance is a deficit of €6132 million. Italy has significant competitiveness in contrast with some other countries with debt difficulties.

Table III-6, Italy, Trade Balance by Product Categories, € Millions

 

Jan 2012

Cumulative Jan 2012

Consumer Goods

161

161

  Durable

471

471

  Nondurable

-310

-310

Capital Goods

1,997

1,997

Intermediate Goods

-376

-376

Energy

-6,132

-6,132

Total ex Energy

1,781

1,781

Total

-4,350

-4,350

Source: http://www.istat.it/it/archivio/57081

Brazil faced in the debt crisis of 1982 a more complex policy mix. Between 1977 and 1983, 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 (see Table III-1). 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 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 2010
USD Billions

Primary Net Lending Borrowing
% GDP 2010

General Government Net Debt
% GDP 2010

World

62,911.2

   

Euro Zone

12,167.8

-3.6

65.9

Portugal

229.2

-6.3

88.7

Ireland

206.9

-28.9

78.0

Greece

305.4

-4.9

142.8

Spain

1,409.9

-7.8

48.8

Major Advanced Economies G7

31,716.9

-6.5

76.5

United States

14,526.6

-8.4

68.3

UK

2,250.2

-7.7

67.7

Germany

3,286.5

-1.2

57.6

France

2,562.7

-4.9

76.5

Japan

5,458.8

-8.1

117.2

Canada

1,577.0

-4.9

32.2

Italy

2,055.1

-0.3

99.4

China

5,878.3

-2.3

33.8*

Cyprus

23.2

-5.3

61.6

*Gross Debt

Source: http://www.imf.org/external/pubs/ft/weo/2011/01/weodata/index.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 2010 is $3853.5 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 $3531.6 billion. 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 $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. The final column provides “Debt as % of Germany GDP” that 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. 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

8,018.6

   

B Germany

1,893.0

 

$7385.1 as % of $3286.5 =224.7%

$5424.6 as % of $3286.5 =165.1%

C France

1,960.5

   

B+C

3,853.5

GDP $5849.2

Total Debt

$7385.1

Debt/GDP: 126.3%

 

D Italy

2,042.8

   

E Spain

688.0

   

F Portugal

203.3

   

G Greece

436.1

   

H Ireland

161.4

   

Subtotal D+E+F+G+H

3,531.6

   

Source: calculation with IMF data http://www.imf.org/external/pubs/ft/weo/2011/01/weodata/index.aspx

There is extremely important information in Table III-9 for the current sovereign risk crisis in the euro zone. Table III-1B provides the structure of regional and country relations of Germany’s exports and imports with newly available data for Feb. German exports to other European Union (EU) members are 58.5 percent of total exports in Feb 2012 and 58.9 percent in Jan-Feb 2012. Exports to the euro area are 38.8 percent in Feb and 39.3 percent in Jan-Feb. Exports to third countries are 37.9 percent of the total in Feb and 41.1 percent in Jan-Feb. 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 ∆%

 

Feb 2012 
€ Billions

Feb 12-Month
∆%

Jan–Feb 2012 € Billions

Jan-Feb 2012/
Jan-Dec 2011 ∆%

Total
Exports

91.3

8.6

177.3

8.9

A. EU
Members

53.4

% 58.5

5.4

104.4

% 58.9

5.4

Euro Area

35.4

% 38.8

3.3

69.7

% 39.3

4.0

Non-euro Area

18.0

% 19.7

9.7

34.7

% 19.6

8.5

B. Third Countries

37.9

% 41.5

13.4

72.9

% 41.1

14.4

Total Imports

76.5

6.1

149.3

6.2

C. EU Members

48.7

% 63.7

6.6

93.6

% 62.7

6.9

Euro Area

34.1

% 44.6

5.5

65.5

% 43.9

6.3

Non-euro Area

14.6

% 19.1

9.3

28.1

% 18.8

8.6

D. Third Countries

27.8

% 36.3

5.2

55.8

% 37.4

4.9

Notes: Total Exports = A+B; Total Imports = C+D

Source:

Statistiche Bundesamt Deutschland

https://www.destatis.de/EN/PressServices/Press/pr/2012/04/PE12_129_51.html

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)stdτ (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, which are equal to TtGt 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.

© Carlos M. Pelaez, 2010, 2011, 2012

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