Sunday, July 5, 2015

Turbulence of Financial Asset Valuations, Twenty-five Million Unemployed or Underemployed, Job Creation, Stagnating Real Wages, Collapse of United States Dynamism of Income Growth and Employment Creation, World Cyclical Slow Growth and Global Recession Risk: Part V

 

Turbulence of Financial Asset Valuations, Twenty-five Million Unemployed or Underemployed, Job Creation, Stagnating Real Wages, Collapse of United States Dynamism of Income Growth and Employment Creation, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015

I Twenty Five Million Unemployed or Underemployed

IA1 Summary of the Employment Situation

IA2 Number of People in Job Stress

IA3 Long-term and Cyclical Comparison of Employment

IA4 Job Creation

IB Stagnating Real Wages

II IB Collapse of United States Dynamism of Income Growth and Employment Creation

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

IIID Appendix on European Central Bank Large Scale Lender of Last Resort

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during the Debt Crisis of the 1980s

V World Economic Slowdown. Table V-1 is constructed with the database of the IMF (http://www.imf.org/external/ns/cs.aspx?id=29) to show GDP in dollars in 2013 and the growth rate of real GDP of the world and selected regional countries from 2013 to 2017. The data illustrate the concept often repeated of “two-speed recovery” of the world economy from the recession of 2007 to 2009. The IMF has changed its forecast of the world economy to 3.4 percent in 2014 but accelerating to 3.5 percent in 2015, 3.8 percent in 2016 and 3.8 percent in 2016. Slow-speed recovery occurs in the “major advanced economies” of the G7 that account for $34,883 billion of world output of $75,471 billion, or 46.2 percent, but are projected to grow at much lower rates than world output, 2.1 percent on average from 2014 to 2017 in contrast with 3.6 percent for the world as a whole. While the world would grow 15.3 percent in the four years from 2014 to 2017, the G7 as a whole would grow 8.6 percent. The difference in dollars of 2013 is high: growing by 15.2 percent would add around $11.5 trillion of output to the world economy, or roughly, two times the output of the economy of Japan of $4,920 billion but growing by 8.6 percent would add $6.5 trillion of output to the world, or about the output of Japan in 2013. The “two speed” concept is in reference to the growth of the 150 countries labeled as emerging and developing economies (EMDE) with joint output in 2013 of $29,358 billion, or 38.9 percent of world output. The EMDEs would grow cumulatively 19.9 percent or at the average yearly rate of 4.7 percent, contributing $5.8 trillion from 2014 to 2017 or the equivalent of somewhat less than the GDP of $9,469 billion of China in 2013. The final four countries in Table V-1 often referred as BRIC (Brazil, Russia, India, China), are large, rapidly growing emerging economies. Their combined output in 2013 adds to $15,814 billion, or 21.0 percent of world output, which is equivalent to 45.3 percent of the combined output of the major advanced economies of the G7.

Table V-1, IMF World Economic Outlook Database Projections of Real GDP Growth

 

GDP USD 2013

Real GDP ∆%
2014

Real GDP ∆%
2015

Real GDP ∆%
2016

Real GDP ∆%
2017

World

75,471

3.4

3.5

3.8

3.8

G7

34,883

1.7

2.3

2.3

2.0

Canada

1,839

2.5

2.2

2.0

2.0

France

2,807

0.4

1.2

1.5

1.7

DE

3,731

1.6

1.6

1.7

1.5

Italy

2,138

-0.4

0.5

1.1

1.1

Japan

4,920

-0.1

1.0

1.2

0.4

UK

2,680

2.6

2.7

2.3

2.2

US

16,768

2.4

3.1

3.1

2.7

Euro Area

13,143

0.9

1.5

1.7

1.6

DE

3,731

1.6

1.6

1.7

1.5

France

2,807

0.4

1.2

1.5

1.7

Italy

2,138

-0.4

0.5

1.1

1.1

POT

225

0.9

1.6

1.5

1.4

Ireland

232

4.8

3.9

3.3

2.8

Greece

242

0.7

2.5

3.7

3.2

Spain

1,393

1.4

2.5

2.0

1.8

EMDE

29,358

4.6

4.3

4.7

5.0

Brazil

2,391

0.1

-1.0

1.0

2.3

Russia

2,079

0.6

-3.8

-1.1

1.0

India

1,875

7.2

7.5

7.5

7.6

China

9,469

7.4

6.8

6.3

6.0

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries); POT: Portugal

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2015/01/weodata/index.aspx

Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (http://www.imf.org/external/pubs/ft/weo/2015/01/weodata/index.aspx ). Table V-2 is constructed with the WEO database to provide rates of unemployment from 2013 to 2017 for major countries and regions. In fact, unemployment rates for 2014 in Table I-2 are high for all countries: unusually high for countries with high rates most of the time and unusually high for countries with low rates most of the time. The rates of unemployment are particularly high in 2014 for the countries with sovereign debt difficulties in Europe: 13.9 percent for Portugal (POT), 11.3 percent for Ireland, 26.5 percent for Greece, 24.5 percent for Spain and 12.8 percent for Italy, which is lower but still high. The G7 rate of unemployment is 7.1 percent. Unemployment rates are not likely to decrease substantially if slow growth persists in advanced economies.

Table I-2, IMF World Economic Outlook Database Projections of Unemployment Rate as Percent of Labor Force

 

% Labor Force 2013

% Labor Force 2014

% Labor Force 2015

% Labor Force 2016

% Labor Force 2017

World

NA

NA

NA

NA

NA

G7

7.1

6.4

6.0

5.8

5.8

Canada

7.1

6.9

7.0

6.9

6.8

France

10.3

10.2

10.1

9.9

9.7

DE

5.2

5.0

4.9

4.8

4.8

Italy

12.2

12.8

12.6

12.3

12.0

Japan

4.0

3.6

3.7

3.7

3.8

UK

7.6

6.2

5.4

5.4

5.4

US

7.4

6.2

5.5

5.2

5.0

Euro Area

12.0

11.6

11.1

10.6

10.3

DE

5.2

5.0

4.9

4.8

4.8

France

10.3

10.2

10.1

9.9

9.7

Italy

12.2

12.8

12.6

12.3

12.0

POT

16.2

13.9

13.1

12.6

12.1

Ireland

13.0

11.3

9.8

8.8

8.3

Greece

27.5

26.5

24.8

22.1

20.0

Spain

26.1

24.5

22.6

21.1

19.9

EMDE

NA

NA

NA

NA

NA

Brazil

5.4

4.8

5.9

6.3

5.9

Russia

5.5

5.1

6.5

6.5

6.0

India

NA

NA

NA

NA

NA

China

4.1

4.1

4.1

4.1

4.1

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)

Source: IMF World Economic Outlook

http://www.imf.org/external/pubs/ft/weo/2015/01/weodata/index.aspx

Table V-3 provides the latest available estimates of GDP for the regions and countries followed in this blog from IQ2012 to IQ2015 available now for all countries. There are preliminary estimates for most countries for IQ2015. Growth is weak throughout most of the world.

  • Japan. The GDP of Japan increased 1.0 percent in IQ2012, 4.1 percent at SAAR (seasonally adjusted annual rate) and 3.5 percent relative to a year earlier but part of the jump could be the low level a year earlier because of the Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011. Japan is experiencing difficulties with the overvalued yen because of worldwide capital flight originating in zero interest rates with risk aversion in an environment of softer growth of world trade. Japan’s GDP fell 0.5 percent in IIQ2012 at the seasonally adjusted annual rate (SAAR) of minus 1.8 percent, which is much lower than 4.1 percent in IQ2012. Growth of 3.5 percent in IIQ2012 in Japan relative to IIQ2011 has effects of the low level of output because of Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011. Japan’s GDP contracted 0.4 percent in IIIQ2012 at the SAAR of minus 1.8 percent and increased 0.2 percent relative to a year earlier. Japan’s GDP decreased 0.1 percent in IVQ2012 at the SAAR of minus 0.6 percent and changed 0.0 percent relative to a year earlier. Japan grew 1.3 percent in IQ2013 at the SAAR of 5.3 percent and increased 0.4 percent relative to a year earlier. Japan’s GDP increased 0.7 percent in IIQ2013 at the SAAR of 2.9 percent and increased 1.4 percent relative to a year earlier. Japan’s GDP grew 0.5 percent in IIIQ2013 at the SAAR of 2.0 percent and increased 2.2 percent relative to a year earlier. In IVQ2013, Japan’s GDP decreased 0.2 percent at the SAAR of minus 0.9 percent, increasing 2.3 percent relative to a year earlier. Japan’s GDP increased 1.1 percent in IQ2014 at the SAAR of 4.4 percent and increased 2.4 percent relative to a year earlier. In IIQ2014, Japan’s GDP fell 1.7 percent at the SAAR of minus 6.8 percent and fell 0.4 percent relative to a year earlier. Japan’s GDP contracted 0.5 percent in IIIQ2014 at the SAAR of minus 2.0 percent and fell 1.4 percent relative to a year earlier. In IVQ2014, Japan’s GDP grew 0.3 percent, at the SAAR of 1.2 percent, decreasing 1.0 percent relative to a year earlier. The GDP of Japan increased 1.0 percent in IQ2015 at the SAAR of 3.9 percent and decreased 0.9 percent relative to a year earlier.
  • China. China’s GDP grew 1.4 percent in IQ2012, annualizing to 5.7 percent, and 8.1 percent relative to a year earlier. The GDP of China grew at 2.1 percent in IIQ2012, which annualizes to 8.7 percent and 7.6 percent relative to a year earlier. China grew at 2.0 percent in IIIQ2012, which annualizes at 8.2 percent and 7.4 percent relative to a year earlier. In IVQ2012, China grew at 1.9 percent, which annualizes at 7.8 percent, and 7.9 percent in IVQ2012 relative to IVQ2011. In IQ2013, China grew at 1.7 percent, which annualizes at 7.0 percent and 7.8 percent relative to a year earlier. In IIQ2013, China grew at 1.8 percent, which annualizes at 7.4 percent and 7.5 percent relative to a year earlier. China grew at 2.3 percent in IIIQ2013, which annualizes at 9.5 percent and 7.9 percent relative to a year earlier. China grew at 1.8 percent in IVQ2013, which annualized to 7.4 percent and 7.6 percent relative to a year earlier. China’s GDP grew 1.6 percent in IQ2014, which annualizes to 6.6 percent, and 7.4 percent relative to a year earlier. China’s GDP grew 2.0 percent in IIQ2014, which annualizes at 8.2 percent, and 7.5 percent relative to a year earlier. China’s GDP grew 1.9 percent in IIIQ2014, which is equivalent to 7.8 percent in a year, and 7.3 percent relative to a year earlier. The GDP of China grew 1.5 percent in IVQ2014, which annualizes at 6.1 percent, and 7.3 percent relative to a year earlier. The GDP of China grew at 1.3 percent in IQ2015, which annualizes at 5.3 percent, and 7.0 percent relative to a year earlier. There is decennial change in leadership in China (http://www.xinhuanet.com/english/special/18cpcnc/index.htm). Growth rates of GDP of China in a quarter relative to the same quarter a year earlier have been declining from 2011 to 2015.
  • Euro Area. GDP fell 0.2 percent in the euro area in IQ2012 and decreased 0.5 in IQ2012 relative to a year earlier. Euro area GDP contracted 0.3 percent IIQ2012 and fell 0.8 percent relative to a year earlier. In IIIQ2012, euro area GDP fell 0.1 percent and declined 0.9 percent relative to a year earlier. In IVQ2012, euro area GDP fell 0.3 percent relative to the prior quarter and fell 0.9 percent relative to a year earlier. In IQ2013, the GDP of the euro area fell 0.4 percent and decreased 1.1 percent relative to a year earlier. The GDP of the euro area increased 0.4 percent in IIQ2013 and fell 0.5 percent relative to a year earlier. In IIIQ2013, euro area GDP increased 0.2 percent and fell 0.2 percent relative to a year earlier. The GDP of the euro area increased 0.3 percent in IVQ2013 and increased 0.5 percent relative to a year earlier. In IQ2014, the GDP of the euro area increased 0.2 percent and 1.1 percent relative to a year earlier. The GDP of the euro area increased 0.1 percent in IIQ2014 and increased 0.8 percent relative to a year earlier. The euro area’s GDP increased 0.2 percent in IIIQ2014 and increased 0.8 percent relative to a year earlier. The GDP of the euro area increased 0.4 percent in IVQ2014 and increased 0.9 percent relative to a year earlier. Euro are GDP increased 0.4 percent in IQ2015 and increased 1.0 percent relative to a year earlier.
  • Germany. The GDP of Germany increased 0.3 percent in IQ2012 and 1.5 percent relative to a year earlier. In IIQ2012, Germany’s GDP increased 0.1 percent and increased 0.3 percent relative to a year earlier but 0.8 percent relative to a year earlier when adjusted for calendar (CA) effects. In IIIQ2012, Germany’s GDP increased 0.1 percent and 0.1 percent relative to a year earlier. Germany’s GDP contracted 0.4 percent in IVQ2012 and decreased 0.3 percent relative to a year earlier. In IQ2013, Germany’s GDP decreased 0.4 percent and fell 1.8 percent relative to a year earlier. In IIQ2013, Germany’s GDP increased 0.8 percent and 0.5 percent relative to a year earlier. The GDP of Germany increased 0.3 percent in IIIQ2013 and 0.8 percent relative to a year earlier. In IVQ2013, Germany’s GDP increased 0.4 percent and 1.0 percent relative to a year earlier. The GDP of Germany increased 0.8 percent in IQ2014 and 2.6 percent relative to a year earlier. In IIQ2014, Germany’s GDP contracted 0.1 percent and increased 1.0 percent relative to a year earlier. The GDP of Germany increased 0.1 percent in IIIQ2014 and increased 1.2 percent relative to a year earlier. Germany’s GDP increased 0.7 percent in IVQ2014 and increased 1.6 percent relative to a year earlier. The GDP of Germany increased 0.3 percent in IQ2015 and increased 1.1 percent relative to a year earlier.
  • United States. Growth of US GDP in IQ2012 was 0.6 percent, at SAAR of 2.3 percent and higher by 2.6 percent relative to IQ2011. US GDP increased 0.4 percent in IIQ2012, 1.6 percent at SAAR and 2.3 percent relative to a year earlier. In IIIQ2012, US GDP grew 0.6 percent, 2.5 percent at SAAR and 2.7 percent relative to IIIQ2011. In IVQ2012, US GDP grew 0.0 percent, 0.1 percent at SAAR and 1.6 percent relative to IVQ2011. In IQ2013, US GDP grew at 2.7 percent SAAR, 0.7 percent relative to the prior quarter and 1.7 percent relative to the same quarter in 2013. In IIQ2013, US GDP grew at 1.8 percent in SAAR, 0.4 percent relative to the prior quarter and 1.8 percent relative to IIQ2012. US GDP grew at 4.5 percent in SAAR in IIIQ2013, 1.1 percent relative to the prior quarter and 2.3 percent relative to the same quarter a year earlier (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/dollar-devaluation-and-carry-trade.html). In IVQ2013, US GDP grew 0.9 percent at 3.5 percent SAAR and 3.1 percent relative to a year earlier. In IQ2014, US GDP decreased 0.5 percent, increased 1.9 percent relative to a year earlier and fell 2.1 percent at SAAR. In IIQ2014, US GDP increased 1.1 percent at 4.6 percent SAAR and increased 2.6 percent relative to a year earlier. US GDP increased 1.2 percent in IIIQ2014 at 5.0 percent SAAR and increased 2.7 percent relative to a year earlier. In IVQ2014, US GDP increased 0.5 percent at SAAR of 2.2 percent and increased 2.4 percent relative to a year earlier. GDP changed 0.0 percent in IQ2015 at SAAR of minus 0.2 percent and grew 2.9 percent relative to a year earlier.
  • United Kingdom. In IQ2012, UK GDP increased 0.1 percent, increasing 1.0 percent relative to a year earlier. UK GDP fell 0.2 percent in IIQ2012 and increased 0.6 percent relative to a year earlier. UK GDP increased 0.8 percent in IIIQ2012 and increased 0.7 percent relative to a year earlier. UK GDP fell 0.3 percent in IVQ2012 relative to IIIQ2012 and increased 0.4 percent relative to a year earlier. UK GDP increased 0.6 percent in IQ2013 and 0.9 percent relative to a year earlier. UK GDP increased 0.6 percent in IIQ2013 and 1.7 percent relative to a year earlier. In IIIQ2013, UK GDP increased 0.7 percent and 1.6 percent relative to a year earlier. UK GDP increased 0.4 percent in IVQ2013 and 2.4 percent relative to a year earlier. In IQ2014, UK GDP increased 0.9 percent and 2.7 percent relative to a year earlier. UK GDP increased 0.9 percent in IIQ2014 and 3.0 percent relative to a year earlier. In IIIQ2014, UK GDP increased 0.7 percent and increased 3.0 percent relative to a year earlier. UK GDP increased 0.8 percent in IVQ2014 and increased 3.4 percent relative to a year earlier. In IQ2015, GDP increased 0.4 percent and 2.9 percent relative to a year earlier.
  • Italy. Italy has experienced decline of GDP in seven consecutive quarters from IIIQ2011 to IQ2013 and in IQ2014, IIQ2014 and IIIQ2014. Italy’s GDP fell 1.0 percent in IQ2012 and declined 2.3 percent relative to IQ2011. Italy’s GDP fell 0.6 percent in IIQ2012 and declined 3.1 percent relative to a year earlier. In IIIQ2012, Italy’s GDP fell 0.5 percent and declined 3.1 percent relative to a year earlier. The GDP of Italy contracted 0.5 percent in IVQ2012 and fell 2.7 percent relative to a year earlier. In IQ2013, Italy’s GDP contracted 0.9 percent and fell 2.6 percent relative to a year earlier. Italy’s GDP changed 0.0 percent in IIQ2013 and fell 2.0 percent relative to a year earlier. The GDP of Italy increased 0.1 percent in IIIQ2013 and declined 1.4 percent relative to a year earlier. Italy’s GDP changed 0.0 percent in IVQ2013 and decreased 0.9 percent relative to a year earlier. In IQ2014, Italy’s GDP decreased 0.2 percent and fell 0.2 percent relative to a year earlier. The GDP of Italy fell 0.1 percent in IIQ2014 and declined 0.3 percent relative to a year earlier. In IIIQ2014, Italy’s GDP contracted 0.1 percent and fell 0.5 percent relative to a year earlier. The GDP of Italy changed 0.0 percent in IVQ20214 and declined 0.4 percent relative to a year earlier. In IQ2015, Italy’s GDP increased 0.3 percent and increased 0.1 percent relative to a year earlier
  • France. France’s GDP changed 0.0 percent in IQ2012 and increased 0.4 percent relative to a year earlier. France’s GDP decreased 0.3 percent in IIQ2012 and increased 0.2 percent relative to a year earlier. In IIIQ2012, France’s GDP increased 0.3 percent and increased 0.3 percent relative to a year earlier. France’s GDP changed 0.0 percent in IVQ2012 and changed 0.0 percent relative to a year earlier. In IQ2013, France’s GDP increased 0.1 percent and increased 0.1 percent relative to a year earlier. The GDP of France increased 0.8 percent in IIQ2013 and increased 1.2 percent relative to a year earlier. France’s GDP decreased 0.1 percent in IIIQ2013 and increased 0.8 percent relative to a year earlier. The GDP of France increased 0.2 percent in IVQ2013 and increased 1.0 percent relative to a year earlier. In IQ2014, France’s GDP decreased 0.2 percent and increased 0.7 percent relative to a year earlier. In IIQ2014, France’s GDP contracted 0.1 percent and decreased 0.2 percent relative to a year earlier. France’s GDP increased 0.2 percent in IIIQ2014 and increased 0.2 percent relative to a year earlier. The GDP of France increased 0.1 percent in IVQ2014 and changed 0.0 percent relative to a year earlier. France’s GDP increased 0.6 percent in IQ2015 and increased 0.8 percent relative to a year earlier

Table V-3, Percentage Changes of GDP Quarter on Prior Quarter and on Same Quarter Year Earlier, ∆%

 

IQ2012/IVQ2011

IQ2012/IQ2011

United States

QOQ: 0.6       

SAAR: 2.3

2.6

Japan

QOQ: 1.0

SAAR: 4.1

3.5

China

1.4

8.1

Euro Area

-0.2

-0.5

Germany

0.3

1.5

France

0.0

0.4

Italy

-1.0

-2.3

United Kingdom

0.1

1.0

 

IIQ2012/IQ2012

IIQ2012/IIQ2011

United States

QOQ: 0.4        

SAAR: 1.6

2.3

Japan

QOQ: -0.5
SAAR: -1.8

3.5

China

2.1

7.6

Euro Area

-0.3

-0.8

Germany

0.1

0.3 0.8 CA

France

-0.3

0.2

Italy

-0.6

-3.1

United Kingdom

-0.2

0.6

 

IIIQ2012/ IIQ2012

IIIQ2012/ IIIQ2011

United States

QOQ: 0.6 
SAAR: 2.5

2.7

Japan

QOQ: –0.4
SAAR: –1.8

0.2

China

2.0

7.4

Euro Area

-0.1

-0.9

Germany

0.1

0.1

France

0.3

0.3

Italy

-0.5

-3.1

United Kingdom

0.8

0.7

 

IVQ2012/IIIQ2012

IVQ2012/IVQ2011

United States

QOQ: 0.0
SAAR: 0.1

1.6

Japan

QOQ: -0.1

SAAR: -0.6

0.0

China

1.9

7.9

Euro Area

-0.3

-0.9

Germany

-0.4

-0.3

France

0.0

0.0

Italy

-0.5

-2.7

United Kingdom

-0.3

0.4

 

IQ2013/IVQ2012

IQ2013/IQ2012

United States

QOQ: 0.7
SAAR: 2.7

1.7

Japan

QOQ: 1.3

SAAR: 5.3

0.4

China

1.7

7.8

Euro Area

-0.4

-1.1

Germany

-0.4

-1.8

France

0.1

0.1

Italy

-0.9

-2.6

UK

0.6

0.9

 

IIQ2013/IQ2013

IIQ2013/IIQ2012

United States

QOQ: 0.4

SAAR: 1.8

1.8

Japan

QOQ: 0.7

SAAR: 2.9

1.4

China

1.8

7.5

Euro Area

0.4

-0.5

Germany

0.8

0.5

France

0.8

1.2

Italy

0.0

-2.0

UK

0.6

1.7

 

IIIQ2013/IIQ2013

III/Q2013/  IIIQ2012

USA

QOQ: 1.1
SAAR: 4.5

2.3

Japan

QOQ: 0.5

SAAR: 2.0

2.2

China

2.3

7.9

Euro Area

0.2

-0.2

Germany

0.3

0.8

France

-0.1

0.8

Italy

0.1

-1.4

UK

0.7

1.6

 

IVQ2013/IIIQ2013

IVQ2013/IVQ2012

USA

QOQ: 0.9

SAAR: 3.5

3.1

Japan

QOQ: -0.2

SAAR: -0.9

2.3

China

1.8

7.6

Euro Area

0.3

0.5

Germany

0.4

1.0

France

0.2

1.0

Italy

0.0

-0.9

UK

0.4

2.4

 

IQ2014/IVQ2013

IQ2014/IQ2013

USA

QOQ -0.5

SAAR -2.1

1.9

Japan

QOQ: 1.1

SAAR: 4.4

2.4

China

1.6

7.4

Euro Area

0.2

1.1

Germany

0.8

2.6

France

-0.2

0.7

Italy

-0.2

-0.2

UK

0.9

2.7

 

IIQ2014/IQ2014

IIQ2014/IIQ2013

USA

QOQ 1.1

SAAR 4.6

2.6

Japan

QOQ: -1.7

SAAR: -6.8

-0.4

China

2.0

7.5

Euro Area

0.1

0.8

Germany

-0.1

1.0

France

-0.1

-0.2

Italy

-0.1

-0.3

UK

0.9

3.0

 

IIIQ2014/IIQ2014

IIIQ2014/IIIQ2013

USA

QOQ: 1.2

SAAR: 5.0

2.7

Japan

QOQ: -0.5

SAAR: -2.0

-1.4

China

1.9

7.3

Euro Area

0.2

0.8

Germany

0.1

1.2

France

0.2

0.2

Italy

-0.1

-0.5

UK

0.7

3.0

 

IVQ2014/IIIQ2014

IVQ2014/IVQ2013

USA

QOQ: 0.5

SAAR: 2.2

2.4

Japan

QOQ: 0.3

SAAR: 1.2

-1.0

China

1.5

7.3

Euro Area

0.4

0.9

Germany

0.7

1.6

France

0.1

0.0

Italy

0.0

-0.4

UK

0.8

3.4

 

IQ2015/IVQ2014

IQ2015/IQ2014

USA

QOQ: 0.0

SAAR: -0.2

2.9

Japan

QOQ: 1.0

SAAR: 3.9

-0.9

China

1.3

7.0

Euro Area

0.4

1.0

Germany

0.3

1.1

France

0.6

0.8

Italy

0.3

0.1

UK

0.4

2.9

QOQ: Quarter relative to prior quarter; SAAR: seasonally adjusted annual rate

Source: Country Statistical Agencies http://www.census.gov/aboutus/stat_int.html

Table V-4 provides two types of data: growth of exports and imports in the latest available months and in the past 12 months; and contributions of net trade (exports less imports) to growth of real GDP.

  • China. In May 2015, China exports decreased 2.5 percent relative to a year earlier and imports decreased 17.6 percent.
  • Germany. Germany’s exports increased 1.9 percent in the month of Apr 2015 and increased 7.5 percent in the 12 months ending in Apr 2015. Germany’s imports decreased 1.3 percent in the month of Apr 2015 and increased 2.8 percent in the 12 months ending in Apr. Net trade contributed 0.8 percentage points to growth of GDP in IQ2012, contributed 0.4 percentage points in IIQ2012, contributed 0.3 percentage points in IIIQ2012, deducted 0.5 percentage points in IVQ2012, deducted 0.3 percentage points in IQ2013 and added 0.1 percentage points in IIQ2013. Net traded deducted 0.5 percentage points from Germany’s GDP growth in IIIQ2013 and added 0.5 percentage points to GDP growth in IVQ2013. Net trade deducted 0.1 percentage points from GDP growth in IQ2014. Net trade added 0.2 percentage points to GDP growth in IIQ2014 and added 0.4 percentage points in IIIQ2014. Net trade deducted 0.3 percentage points to GDP growth in IVQ2014 and deducted 0.2 percentage points in IQ2015.
  • United Kingdom. Net trade contributed 0.7 percentage points in IIQ2013. In IIIQ2013, net trade deducted 1.7 percentage points from UK growth. Net trade contributed 0.1 percentage points to UK value added in IVQ2013. Net trade contributed 0.2 percentage points to UK value added in IQ2014 and 0.1 percentage points in IIQ2014. Net trade deducted 0.7 percentage points to GDP growth in IIIQ2014 and added 0.8 percentage points in IVQ2014. Net traded deducted 0.6 percentage points from growth in IQ2015.
  • France. France’s exports increased 1.4 percent in Apr 2015 while imports decreased 2.1 percent. France’s exports increased 6.5 percent in the 12 months ending in Apr 2015 and imports increased 2.6 percent relative to a year earlier. Net traded added 0.1 percentage points to France’s GDP in IIIQ2012 and 0.1 percentage points in IVQ2012. Net trade deducted 0.1 percentage points from France’s GDP growth in IQ2013 and added 0.3 percentage points in IIQ2013, deducting 1.7 percentage points in IIIQ2013. Net trade added 0.1 percentage points to France’s GDP in IVQ2013 and deducted 0.1 percentage points in IQ2014. Net trade deducted 0.2 percentage points from France’s GDP growth in IIQ2014 and deducted 0.3 percentage points in IIIQ2014. Net trade added 0.2 percentage points to France’s GDP growth in IVQ2014 and deducted 0.5 percentage points in IQ2015
  • United States. US exports increased 1.0 percent in Apr 2015 and goods exports decreased 4.6 percent in Jan-Apr 2015 relative to a year earlier. Imports decreased 3.7 percent in Apr 2015 and goods imports decreased 3.0 percent in Jan-Apr 2015 relative to a year earlier. Net trade deducted 0.04 percentage points from GDP growth in IIQ2012 and added 0.39 percentage points in IIIQ2012 and 0.79 percentage points in IVQ2012. Net trade deducted 0.08 percentage points from US GDP growth in IQ2013 and deducted 0.54 percentage points in IIQ2013. Net traded added 0.59 percentage points to US GDP growth in IIIQ2013. Net trade added 1.08 percentage points to US GDP growth in IVQ2013. Net trade deducted 1.66 percentage points from US GDP growth in IQ2014 and deducted 0.34 percentage points in IIQ2014. Net trade added 0.78 percentage points to IIIQ2014. Net trade deducted 1.03 percentage points from GDP growth in IVQ2014 and deducted 1.90 percentage points from GDP growth in IQ2015. The Federal Reserve completed its annual revision of industrial production and capacity utilization on Mar 28, 2014 (http://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm). The report of the Board of Governors of the Federal Reserve System states (http://www.federalreserve.gov/releases/g17/Current/default.htm): “Industrial production decreased 0.2 percent in May after falling 0.5 percent in April. The decline in April was larger than previously reported, but the rates of change for previous months were generally revised higher, leaving the level of the index in April slightly above its initial estimate. Manufacturing output decreased 0.2 percent in May and was little changed, on net, from its level in January. In May, the index for mining moved down 0.3 percent after declining more than 1 percent per month, on average, in the previous four months. The slower rate of decrease for mining output last month was due in part to a reduced pace of decline in the index for oil and gas well drilling and servicing. The output of utilities increased 0.2 percent in May. At 105.1 percent of its 2007 average, total industrial production in May was 1.4 percent above its year-earlier level. Capacity utilization for the industrial sector decreased 0.2 percentage point in May to 78.1 percent, a rate that is 2.0 percentage points below its long-run (1972–2014) average.” In the six months ending in May 2015, United States national industrial production accumulated change of minus 1.1 percent at the annual equivalent rate of minus 2.2 percent, which is lower than growth of 1.4 percent in the 12 months ending in May 2015. Excluding growth of 1.1 percent in Nov 2014, growth in the remaining five months from Nov 2014 to May 2015 accumulated to minus 1.1 percent or minus 2.6 percent annual equivalent. Industrial production declined in three of the past six months and changed 0.0 percent in three months. Industrial production contracted at annual equivalent 2.8 percent in the most recent quarter from Mar 2015 to May 2015 and contracted at 1.6 percent in the prior quarter Dec 2014 to Feb 2015. Business equipment accumulated contraction of 1.0 percent in the six months from Dec 2014 to May 2015 at the annual equivalent rate of minus 2.0 percent, which is lower than growth of 1.9 percent in the 12 months ending in May 2015. The Fed analyzes capacity utilization of total industry in its report (http://www.federalreserve.gov/releases/g17/Current/default.htm): “Capacity utilization for the industrial sector decreased 0.2 percentage point in May to 78.1 percent, a rate that is 2.0 percentage points below its long-run (1972–2014) average.” United States industry apparently decelerated to a lower growth rate followed by possible acceleration and weakening growth in past months.

Manufacturing fell 21.9 from the peak in Jun 2007 to the trough in Apr 2009 and increased by 25.1 percent from the trough in Apr 2009 to Dec 2014. Manufacturing grew 26.3 percent from the trough in Apr 2009 to May 2015. Manufacturing output in May 2015 is 1.4 percent below the peak in Jun 2007. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IQ2015 would have accumulated to 23.9 percent. GDP in IQ2015 would be $18,574.8 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,287.1 billion than actual $16,287.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.7 million unemployed or underemployed equivalent to actual unemployment/underemployment of 15.1 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/quite-high-equity-valuations-and.html). US GDP in IQ2015 is 12.3 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,287.7 billion in IQ2015 or 8.6 percent at the average annual equivalent rate of 1.2 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth at average 3.3 percent per year from May 1919 to May 2015. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 126.2585 in May 2015. The actual index NSA in May 2015 is 101.5858, which is 19.5 percent below trend. Manufacturing output grew at average 2.4 percent between Dec 1986 and Dec 2014. Using trend growth of 2.4 percent per year, the index would increase to 118.3245 in May 2015. The output of manufacturing at 101.5858 in May 2015 is 14.1 percent below trend under this alternative calculation.

Table V-4, Growth of Trade and Contributions of Net Trade to GDP Growth, ∆% and % Points

 

Exports
M ∆%

Exports 12 M ∆%

Imports
M ∆%

Imports 12 M ∆%

USA

1.0 Apr

-4.6

Jan-Apr

-3.7 Jan

-3.0

Jan-Mar

Japan

 

May 2015

2.4

Apr

8.0

Mar

8.5

Feb

2.4

Jan

17.0

Dec

12.9

Nov

4.9

Oct

9.6

Sep

6.9

Aug

-1.3

Jul

3.9

Jun

-2.0

May 2014

-2.7

Apr 2014

5.1

Mar 2014

1.8

Feb 2014

9.5

Jan 2014

9.5

Dec 2013

15.3

Nov 2013

18.4

Oct 2013

18.6

Sep 2013

11.5

Aug 2013

14.7

Jul 2013

12.2

Jun 2013 7.4

May 2013

10.1

Apr 2013

3.8

Mar 2013

1.1

Feb 2013

-2.9

Jan 2013 6.4

Dec -5.8

Nov -4.1

Oct -6.5

Sep -10.3

Aug -5.8

Jul -8.1

 

May 2015

-8.7

Apr

-4.2

Mar

-14.5

Feb

-3.6

Jan

-9.0

Dec

1.9

Nov

-1.7

Oct

2.7

Sep

6.2

Aug

-1.5

Jul

2.3

Jun

8.4

May 2014

-3.6

Apr 2013

3.4

Mar 2014

18.1

Feb 2014

9.0

Jan 2014

25.0

Dec 2013 24.7

Nov 2013

21.1

Oct 2013

26.1

Sep 2013

16.5

Aug 2013

16.0

Jul 2013

19.6

Jun 2013

11.8

May 2013

10.0

Apr 2013

9.4

Mar 2013

5.5

Feb 2013

7.3

Jan 2013 7.3

Dec 1.9

Nov 0.8

Oct -1.6

Sep 4.1

Aug -5.4

Jul 2.1

China

 

2015

-2.5 May

-6.4 Apr

-15.0 Mar

48.3 Feb

-3.3 Jan

2014

9.7 Dec

4.7 Nov

11.6 Oct

15.3 Sep

9.4 Aug

14.5 Jul

7.2 Jun

7.0 May

0.9 Apr

-6.6 Mar

-18.1 Feb

10.6 Jan

2013

4.3 Dec

12.7 Nov

5.6 Oct

-0.3 Sep

7.2 Aug

5.1 Jul

-3.1 Jun

1.0 May

14.7 Apr

10.0 Mar

21.8 Feb

25.0 Jan

 

2015

-17.6 May

-12.7 Mar

-20.5 Feb

-19.9 Jan

2014

-2.4 Dec

-6.7 Nov

4.6 Oct

7.0 Sep

-2.4 Aug

-1.6 Jul

5.5 Jun

-1.6 May

-0.8 Apr

-11.3 Mar

10.1 Feb

10.0 Jan

2013

8.3 Dec

5.3 Nov

7.6 Oct

7.4 Sep

7.0 Aug

10.9 Jul

-0.7 Jun

-0.3 May

16.8 Apr

14.1 Mar

-15.2 Feb

28.8 Jan

Euro Area

8.8 12 M-Apr

6.0 Jan-Apr

3.0 12-M Apr

1.0 Jan-Apr

Germany

1.9 Apr CSA

7.5 Apr

-1.3 Apr CSA

2.8 Apr

France

Apr

1.4

6.5

-2.1

2.6

Italy Apr

-0.8

4.6

0.0

4.0

UK

1.2 Apr

-1.6 Jan 15-Apr 15 /Jan 14-Apr 14

-3.1 Apr

-1.1 Jan 15-Apr 15 /Jan 14-Apr 14

Net Trade % Points GDP Growth

Points

     

USA

IQ2015

-1.90

IVQ2014

-1.03

IIIQ2014

0.78

IIQ2014

-0.34

IQ2014

-1.66

IVQ2013

1.08

IIIQ2013

0.59

IIQ2013

-0.54

IQ2013

-0.08

IVQ2012 +0.79

IIIQ2012

0.39

IIQ2012 -0.04

IQ2012 -0.11

     

Japan

0.3

IQ2012

-1.5 IIQ2012

-1.9 IIIQ2012

-0.6 IVQ2012

1.6

IQ2013

0.1

IIQ2013

-1.5

IIIQ2013

-2.1

IVQ2013

-1.3

IQ2014

4.3

IIQ2014

0.2

IIIQ2014

1.1

IVQ2014

-0.7

IQ2015

     

Germany

IQ2012

0.8 IIQ2012 0.4 IIIQ2012 0.3 IVQ2012

-0.5

IQ2013

-0.3 IIQ2013

0.1

IIIQ2013

-0.5

IVQ2013

0.5

IQ2014

-0.1

IIQ2014

0.2

IIIQ2014

0.4

IVQ2014

-0.3

IQ2015

-0.2

     

France

0.1 IIIQ2012

0.1 IVQ2012

-0.1 IQ2013

0.3

IIQ2013 -1.7

IIIQ2013

0.1

IVQ2013

-0.1

IQ2014

-0.2

IIQ2014

-0.3

IIIQ2014

0.2

IVQ2014

-0.5

IQ2015

     

UK

0.7

IIQ2013

-1.7

IIIQ2013

0.1

IVQ2013

0.2

IQ2014

0.1

IIQ2214

-0.7

IIIQ2014

0.8

IVQ2014

-0.6

IQ2015

     

Sources: Country Statistical Agencies http://www.census.gov/foreign-trade/

The geographical breakdown of exports and imports of Japan with selected regions and countries is in Table V-5 for May 2015. The share of Asia in Japan’s trade is close to one-half for 55.5 percent of exports and 48.0 percent of imports. Within Asia, exports to China are 18.5 percent of total exports and imports from China 24.2 percent of total imports. While exports to China increased 1.1 percent in the 12 months ending in May 2015, imports from China increased 1.5 percent. The largest export market for Japan in May 2015 is the US with share of 18.9 percent of total exports, which is close to that of China, and share of imports from the US of 11.5 percent in total imports. Japan’s exports to the US increased 7.4 percent in the 12 months ending in May 2015 and imports from the US increased 11.5 percent. Western Europe has share of 10.6 percent in Japan’s exports and of 12.2 percent in imports. Rates of growth of exports of Japan in May 2015 are 7.4 percent for exports to the US, minus 17.0 percent for exports to Brazil and minus 9.9 percent for exports to Germany. Comparisons relative to 2011 may have some bias because of the effects of the Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011. Deceleration of growth in China and the US and threat of recession in Europe can reduce world trade and economic activity. Growth rates of imports in the 12 months ending in May 2015 are mixed. Imports from Asia decreased 3.0 percent in the 12 months ending in May 2015 while imports from China increased 1.5 percent. Data are in millions of yen, which may have effects of recent depreciation of the yen relative to the United States dollar (USD).

Table V-5, Japan, Value and 12-Month Percentage Changes of Exports and Imports by Regions and Countries, ∆% and Millions of Yen

May 2015

Exports
Millions Yen

12 months ∆%

Imports Millions Yen

12 months ∆%

Total

5,740,473

2.4

5,956,447

-8.7

Asia

3,186,813

% Total 55.5

3.3

2,857,793 % Total 48.0

-3.0

China

1,060,662

% Total 18.5

1.1

1,442,301 % Total 24.2

1.5

USA

1,086,085

% Total 18.9

7.4

682,351 % Total

11.5

11.5

Canada

70,987

19.5

85,017

-16.3

Brazil

34,331

-17.0

63,961

-14.9

Mexico

81,544

-0.6

41,526

-12.8

Western Europe

609,376 % Total 10.6

-2.1

725,632 % Total 12.2

2.1

Germany

149,118

-9.9

178,411

-7.6

France

49,445

3.7

96,643

8.7

UK

109,575

19.1

56,900

8.8

Middle East

201,464

-6.3

715,497

-35.1

Australia

125,847

20.6

302,066

-22.9

Source: Japan, Ministry of Finance http://www.customs.go.jp/toukei/info/index_e.htm

World trade projections of the IMF are in Table V-6. There is increasing growth of the volume of world trade of goods and services from 3.5 percent in 2013 to 3.7 percent in 2015 and 5.0 percent on average from 2016 to 2019. World trade would be slower for advanced economies while emerging and developing economies (EMDE) experience faster growth. World economic slowdown would be more challenging with lower growth of world trade.

Table V-6, IMF, Projections of World Trade, USD Billions, USD/Barrel and Annual ∆%

 

2013

2014

2015

Average ∆% 2016-2019

World Trade Volume (Goods and Services)

3.5

3.4

3.7

5.0

Exports Goods & Services

3.7

3.3

4.0

5.0

Imports Goods & Services

3.3

3.4

3.4

5.1

World Trade Value of Exports Goods & Services USD Billion

23,117

23,476

21,818

Average ∆% 2007-2016

20,724

Value of Exports of Goods USD Billion

18,632

18,817

17,285

Average ∆% 2007-2016

16,612

Average Oil Price USD/Barrel

104.07

96.25

58.14

Average ∆% 2007-2016

84.21

Average Annual ∆% Export Unit Value of Manufactures

-1.4

-0.8

-3.3

Average ∆% 2007-2016

0.9

Exports of Goods & Services

2013

2014

2015

Average ∆% 2016-2019

Euro Area

2.1

4.2

4.4

4.4

EMDE

4.6

3.4

5.3

6.0

G7

2.0

3.7

4.1

4.1

Imports Goods & Services

       

Euro Area

1.0

4.3

4.3

4.3

EMDE

5.5

3.7

3.5

6.0

G7

1.6

3.7

4.1

4.6

Terms of Trade of Goods & Services

       

Euro Area

0.9

0.8

1.4

-0.5

EMDE

-0.3

-0.6

-3.7

-0.1

G7

0.9

0.5

1.4

0.05

Terms of Trade of Goods

       

Euro Area

1.2

1.0

1.7

-0.6

EMDE

-0.1

0.2

-4.0

0.3

G7

0.8

0.2

1.0

0.1

Notes: Commodity Price Index includes Fuel and Non-fuel Prices; Commodity Industrial Inputs Price includes agricultural raw materials and metal prices; Oil price is average of WTI, Brent and Dubai

Source: International Monetary Fund World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2015/01/weodata/index.aspx

The JP Morgan Global All-Industry Output Index of the JP Morgan Manufacturing and Services PMI, produced by JP Morgan and Markit in association with ISM and IFPSM, with high association with world GDP, decreased to 53.6 in mAY from 54.9 in Apr, indicating expansion at slower rate (http://www.markiteconomics.com/Survey/PressRelease.mvc/c690870f3b0d41f5bcc2647ff00ce73f). This index has remained above the contraction territory of 50.0 during 32 consecutive months. The employment index increased from 52.6 in Apr to 52.9 in May with input prices rising at faster rate, new orders increasing at slower rate and output increasing at slower rate (http://www.markiteconomics.com/Survey/PressRelease.mvc/c690870f3b0d41f5bcc2647ff00ce73f). David Hensley, Director of Global Economic Coordination at JP Morgan, finds slowing world growth with potential acceleration in IIIQ2015 (http://www.markiteconomics.com/Survey/PressRelease.mvc/c690870f3b0d41f5bcc2647ff00ce73f). The JP Morgan Global Manufacturing PMI, produced by JP Morgan and Markit in association with ISM and IFPSM, decreased to 51.0 in Jun from 51.3 in May (http://www.markiteconomics.com/Survey/PressRelease.mvc/189b1000739a404d9f423941fa328347). New export orders changed to expanding from falling. David Hensley, Director of Global Economic Coordination at JP Morgan Chase, finds mild growth in global manufacturing that could recover in the second half (http://www.markiteconomics.com/Survey/PressRelease.mvc/189b1000739a404d9f423941fa328347). The HSBC Brazil Composite Output Index, compiled by Markit, decreased from 42.9 in May to 41.0 in Jun, indicating contraction in activity of Brazil’s private sector (http://www.markiteconomics.com/Survey/PressRelease.mvc/f57ab317b67c43f283938cce9e852131). The HSBC Brazil Services Business Activity index, compiled by Markit, decreased from 42.5 in May to 39.9 in Jun, indicating contracting services activity (http://www.markiteconomics.com/Survey/PressRelease.mvc/f57ab317b67c43f283938cce9e852131). Pollyana De Lima, Economist at Markit, finds probable contraction of GDP in IIQ2015 (http://www.markiteconomics.com/Survey/PressRelease.mvc/f57ab317b67c43f283938cce9e852131). The HSBC Brazil Purchasing Managers’ IndexTM (PMI) increased from 45.9 in May to 46.5 in Jun, indicating deterioration in manufacturing (http://www.markiteconomics.com/Survey/PressRelease.mvc/bb072eebf7294ac0a3e61d08f127c78a). Pollyanna De Lima, Economist at Markit, finds decline in output and new orders (http://www.markiteconomics.com/Survey/PressRelease.mvc/bb072eebf7294ac0a3e61d08f127c78a).

VA United States. The Markit Flash US Manufacturing Purchasing Managers’ Index (PMI) seasonally adjusted decreased to 53.4 in Jun from 54.0 in May (http://www.markiteconomics.com/Survey/PressRelease.mvc/1e3df27e44c443bfbef289b16452bc4d). New export orders stabilized partly under pressure because of dollar revaluation. Chris Williamson, Chief Economist at Markit, finds that manufacturing expanding with challenges to competitiveness from the strong dollar (http://www.markiteconomics.com/Survey/PressRelease.mvc/1e3df27e44c443bfbef289b16452bc4d). The Markit Flash US Services PMI™ Business Activity Index decreased from 56.2 in May to 54.8 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/bf7741e29e5a427f9717073c9b72d185). The Markit Flash US Composite PMI™ Output Index decreased from 56.0 in May to 54.6 in Jun. Chris Williamson, Chief Economist at Markit, finds that the surveys are consistent with slowing GDP growth that may accelerate to about 3.0 percent in the second quarter (http://www.markiteconomics.com/Survey/PressRelease.mvc/bf7741e29e5a427f9717073c9b72d185). The Markit US Composite PMI™ Output Index of Manufacturing and Services decreased to 56.0 in May from 57.0 in Apr (http://www.markiteconomics.com/Survey/PressRelease.mvc/e66ed08a14684077a3da1d250160966c). The Markit US Services PMI™ Business Activity Index decreased from 57.4 in Apr to 56.2 in May (http://www.markiteconomics.com/Survey/PressRelease.mvc/e66ed08a14684077a3da1d250160966c). Chris Williamson, Chief Economist at Markit, finds the indexes suggesting the slowest growth of the US since Jan 2015 (http://www.markiteconomics.com/Survey/PressRelease.mvc/e66ed08a14684077a3da1d250160966c). The Markit US Manufacturing Purchasing Managers’ Index (PMI) decreased to 53.6 in Jun from 54.0 in May, which indicates expansion at slower rate (http://www.markiteconomics.com/Survey/PressRelease.mvc/25ce0a99fabb4e0c90907a2a5b7ef6b3). New foreign orders decreased. Chris Williamson, Chief Economist at Markit, finds that the index suggests restrain of foreign orders and corporate profits because of dollar appreciation (http://www.markiteconomics.com/Survey/PressRelease.mvc/25ce0a99fabb4e0c90907a2a5b7ef6b3). The purchasing managers’ index (PMI) of the Institute for Supply Management (ISM) Report on Business® increased 0.7 percentage points from 52.8 in May to 53.5 in Jun, which indicates growth at the faster rate (https://www.instituteforsupplymanagement.org/ISMReport/MfgROB.cfm?navItemNumber=29393). The index of new orders increased 0.2 percentage points from 55.8 in May to 56.0 in Jun. The index of new exports decreased 0.5 percentage points from 50.0 in May to 49.5 in Jun, contracting from unchanged. The Non-Manufacturing ISM Report on Business® PMI decreased 2.1 percentage points from 57.8 in Apr to 55.7 in May, indicating growth of business activity/production during 70 consecutive months, while the index of new orders decreased 1.3 percentage points from 59.2 in Apr to 57.9 in May (https://www.instituteforsupplymanagement.org/ISMReport/NonMfgROB.cfm?navItemNumber=29348). Table USA provides the country economic indicators for the US.

Table USA, US Economic Indicators

Consumer Price Index

May 12 months NSA ∆%: 0.0; ex food and energy ∆%: 1.7 May month SA ∆%: 0.4; ex food and energy ∆%: 0.1
Blog 6/21/15

Producer Price Index

Finished Goods

May 12-month NSA ∆%: -3.0; ex food and energy ∆% 2.0
May month SA ∆% = 1.5; ex food and energy ∆%: 0.3

Final Demand

May 12-month NSA ∆%: -1.1; ex food and energy ∆% 0.6
May month SA ∆% = 0.5; ex food and energy ∆%: -0.1
Blog 6/14/15 6/21/15

PCE Inflation

May 12-month NSA ∆%: headline 0.2; ex food and energy ∆% 1.2
Blog 6/28/15

Employment Situation

Household Survey: Jun Unemployment Rate SA 5.3%
Blog calculation People in Job Stress Jun: 25.0 million NSA, 15.1% of Labor Force
Establishment Survey:
May Nonfarm Jobs +223,000; Private +223,000 jobs created 
May 12-month Average Hourly Earnings Inflation Adjusted ∆%: 2.3
Blog 7/5/15

Nonfarm Hiring

Nonfarm Hiring fell from 63.3 million in 2006 to 54.2 million in 2013 or by 9.1 million and to 58.7 million in 2014 or by 4.6 million
Private-Sector Hiring Apr 2015 5.162 million lower by 0.201 million than 5.363 million in Apr 2006
Blog 6/14/15

GDP Growth

BEA Revised National Income Accounts
IQ2012/IQ2011 ∆%: 2.6

IIQ2012/IIQ2011 2.3

IIIQ2012/IIIQ2011 2.7

IVQ2012/IVQ2011 1.6

IQ2013/IQ2012 1.7

IIQ2013/IIQ2012 1.8

IIIQ2013/IIIQ2012 2.3

IVQ2013/IVQ2012 3.1

IQ2014/IQ2013 1.9

IIQ2014/IIQ2013 2.6

IIIQ2014/IIIQ2013 2.7

IVQ2014/IVQ2013 2.4

IQ2015/IVQ2014 2.9

IQ2012 SAAR 2.3

IIQ2012 SAAR 1.6

IIIQ2012 SAAR 2.5

IVQ2012 SAAR 0.1

IQ2013 SAAR 2.7

IIQ2013 SAAR 1.8

IIIQ2013 SAAR 4.5

IVQ2013 SAAR 3.5

IQ2014 SAAR -2.1

IIQ2014 SAAR 4.6

IIIQ2014 SAAR 5.0

IVQ2014 SAAR 2.2

IQ2015 SAAR -0.2
Blog 6/28/15

Real Private Fixed Investment

SAAR IQ2015 ∆% minus 0.3 IVQ2007 to IQ2015: 3.3% Blog 6/28/15

Corporate Profits

IQ2015 SAAR: Corporate Profits -5.2; Undistributed Profits -22.7 Blog 6/28/15

Personal Income and Consumption

May month ∆% SA Real Disposable Personal Income (RDPI) SA ∆% 0.2
Real Personal Consumption Expenditures (RPCE): 0.6
12-month May NSA ∆%:
RDPI: 3.5; RPCE ∆%: 2.8
Blog 6/28/15

Quarterly Services Report

IQ15/IQ14 NSA ∆%:
Information 3.0

Financial & Insurance 3.7

Earlier Data:
Blog 3/22/15

Employment Cost Index

Compensation Private IVQ2014 SA ∆%: 0.6
Dec 12 months ∆%: 2.3
Blog 2/1/15

Industrial Production

May month SA ∆%: -0.2
May 12 months SA ∆%: 1.4

Manufacturing May SA -0.2 ∆% May 12 months SA ∆% 1.8, NSA 2.0
Capacity Utilization: 78.1
Blog 6/21/15

Productivity and Costs

Nonfarm Business Productivity IQ2015∆% SAAE -3.1; IQ2015/IQ2014 ∆% 0.3; Unit Labor Costs SAAE IQ2015 ∆% 6.7; IQ2015/IQ2014 ∆%: 1.8

Blog 6/7/15

New York Fed Manufacturing Index

General Business Conditions From May 3.09 to Jun -1.98
New Orders: From May minus 3.85 to Jun -2.12
Blog 6/21/15

Philadelphia Fed Business Outlook Index

General Index from May 6.7 to Jun 15.2
New Orders from May 4.0 to Jun 15.2
Blog 6/21/15

Manufacturing Shipments and Orders

New Orders SA May ∆% -1.0 Ex Transport 0.1

Jan-May NSA New Orders ∆% minus 6.1 Ex transport minus 6.5

Earlier data:
Blog 4/5/15

Durable Goods

May New Orders SA ∆%: -1.8; ex transport ∆%: 0.5
Jan-May 15/Jan-May 14 New Orders NSA ∆%: -2.2; ex transport ∆% -1.3

Earlier Data:
Blog 4/26/15

Sales of New Motor Vehicles

Jun 2015 8,521,260; Jun 2014 8,163,942. Jun 15 SAAR 17.16 million, May 15 SAAR 17.79 million, Jun 2014 SAAR 16.90 million

Blog 7/5/15

Sales of Merchant Wholesalers

Jan-Apr 2015/Jan-Apr 2014 NSA ∆%: Total -2.7; Durable Goods: 3.5; Nondurable
Goods: -7.9

EARLIER DATA:
Blog 4/12/15

Sales and Inventories of Manufacturers, Retailers and Merchant Wholesalers

Apr 15 12-M NSA ∆%: Sales Total Business -2.5; Manufacturers -3.7
Retailers 0.4; Merchant Wholesalers -3.6
Blog 6/14/15

Sales for Retail and Food Services

Jan-May 2015/Jan-May 2014 ∆%: Retail and Food Services 1.9; Retail ∆% 1.0
Blog 6/14/15

Value of Construction Put in Place

May SAAR month SA ∆%: 0.8 Jan-May NSA: 5.9

Earlier Data:
Blog 4/5/15

Case-Shiller Home Prices

Apr 2015/ Apr 2014 ∆% NSA: 10 Cities 4.6; 20 Cities: 4.9; National: 4.2
∆% Apr SA: 10 Cities 0.4 ; 20 Cities: 0.3
Blog 7/5/15

FHFA House Price Index Purchases Only

Apr SA ∆% 0.3;
12 month NSA ∆%: 5.4
Blog 6/28/15

New House Sales

May 2015 month SAAR ∆%: 2.2
Jan-May 2015/Jan-Apr 2014 NSA ∆%: 22.8
Blog 6/28/15

Housing Starts and Permits

May Starts month SA ∆% 11.8; Permits ∆%: 10.1
Jan-May 2015/Jan-May 2014 NSA ∆% Starts 6.0; Permits  ∆% 10.5

Earlier Data:
Blog 4/19/15

Trade Balance

Balance Apr SA -$40,879 million versus Mar -$50,566 million
Exports Apr SA ∆%: 1.0 Imports Apr SA ∆%: -3.7
Goods Exports Jan-Apr 2015/Jan-Apr 2014 NSA ∆%: -4.6
Goods Imports Jan-Apr 2015/Jan-Apr 2014 NSA ∆%: -3.0
Blog 6/7/15

Export and Import Prices

May 12-month NSA ∆%: Imports -9.6; Exports -5.9

Earlier Data:
Blog 4/12/15

Consumer Credit

Apr ∆% annual rate: Total 7.3; Revolving 11.6; Nonrevolving 5.8

Earlier Data:
Blog 5/10/15

Net Foreign Purchases of Long-term Treasury Securities

Apr Net Foreign Purchases of Long-term US Securities: minus $38.1 billion
Major Holders of Treasury Securities: China $1263.4 billion; Japan $1215.7 billion; Total Foreign US Treasury Holdings Apr $6137.3 billion
Blog 6/21/15

Treasury Budget

Fiscal Year 2015/2014 ∆% May: Receipts 8.6; Outlays 4.0; Individual Income Taxes 12.4
Deficit Fiscal Year 2011 $1,300 billion

Deficit Fiscal Year 2012 $1,087 billion

Deficit Fiscal Year 2013 $680 billion

Deficit Fiscal Year 2014 $483 billion

Blog 6/14/2015

CBO Budget and Economic Outlook

2012 Deficit $1087 B 6.8% GDP Debt $11,281 B 70.4% GDP

2013 Deficit $680 B, 4.1% GDP Debt $11,983 B 72.3% GDP

2014 Deficit $483 B 2.8% GDP Debt $12,779 B 74.1% GDP

2025 Deficit $1,088B, 4.0% GDP Debt $21,605B 78.7% GDP

2040: Long-term Debt/GDP 103%

Blog 8/26/12 11/18/12 2/10/13 9/22/13 2/16/14 8/24/14 9/14/14 3/1/15 6/21/14

Commercial Banks Assets and Liabilities

May 2015 SAAR ∆%: Securities 12.8 Loans 3.3 Cash Assets minus 39.0 Deposits minus 4.3

Blog 6/14/15

Flow of Funds Net Worth of Families and Nonprofits

IQ2015 ∆ since 2007

Assets +$17,964.6 BN

Nonfinancial 1544 BN

Real estate $778.5 BN

Financial +16,415.2 BN

Net Worth +$18,202.8 BN

Blog 6/21/15

Current Account Balance of Payments

IQ2015 -88,648 MM

% GDP 2.6

Blog 6/21/15

Collapse of United States Dynamism of Income Growth and Employment Creation

Blog 6/14/15

IMF View

World Real Economic Growth 2015 ∆% 3.5 Blog 4/26/15

Links to blog comments in Table USA:

6/28/2015 http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html

6/21/15 http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html

6/14/15 http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html

6/7/15 http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html

5/31/15 http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html

5/10/15 http://cmpassocregulationblog.blogspot.com/2015/05/quite-high-equity-valuations-and.html

4/26/2015 http://cmpassocregulationblog.blogspot.com/2015/04/imf-view-of-economy-and-finance-united.html

4/19/2015 http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html

4/12/15 http://cmpassocregulationblog.blogspot.com/2015/04/dollar-revaluation-recovery-without.html

4/5/15 http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html

3/1/15 http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html

2/1/15 http://cmpassocregulationblog.blogspot.com/2015/02/financial-and-international.html

9/14/14 http://cmpassocregulationblog.blogspot.com/2014/09/geopolitics-monetary-policy-and.html

8/24/14 http://cmpassocregulationblog.blogspot.com/2014/08/monetary-policy-world-inflation-waves.html

2/16/14 http://cmpassocregulationblog.blogspot.com/2014/02/theory-and-reality-of-cyclical-slow.html

9/22/13 http://cmpassocregulationblog.blogspot.com/2013/09/duration-dumping-and-peaking-valuations.html

2/10/13 http://cmpassocregulationblog.blogspot.com/2013/02/united-states-unsustainable-fiscal.html

Motor vehicle sales and production in the US have been in long-term structural change. Table VA-1 provides the data on new motor vehicle sales and domestic car production in the US from 1990 to 2010. New motor vehicle sales grew from 14,137 thousand in 1990 to the peak of 17,806 thousand in 2000 or 29.5 percent. In that same period, domestic car production fell from 6,231 thousand in 1990 to 5,542 thousand in 2000 or -11.1 percent. New motor vehicle sales fell from 17,445 thousand in 2005 to 11,772 in 2010 or 32.5 percent while domestic car production fell from 4,321 thousand in 2005 to 2,840 thousand in 2010 or 34.3 percent. In Jun 2015, light vehicle sales accumulated to 8,521,260, which is higher by 4.4 percent relative to 8,163,942 a year earlier (http://motorintelligence.com/m_frameset.html). The seasonally adjusted annual rate of light vehicle sales in the US reached 17.16 million in Jun 2015, lower than 17.79 million in May 2015 and higher than 16.90 million in Jun 2014 (http://motorintelligence.com/m_frameset.html).

Table VA-1, US, New Motor Vehicle Sales and Car Production, Thousand Units

 

New Motor Vehicle Sales

New Car Sales and Leases

New Truck Sales and Leases

Domestic Car Production

1990

14,137

9,300

4,837

6,231

1991

12,725

8,589

4,136

5,454

1992

13,093

8,215

4,878

5,979

1993

14,172

8,518

5,654

5,979

1994

15,397

8,990

6,407

6,614

1995

15,106

8,536

6,470

6,340

1996

15,449

8,527

6,922

6,081

1997

15,490

8,273

7,218

5,934

1998

15,958

8,142

7,816

5,554

1999

17,401

8,697

8,704

5,638

2000

17,806

8,852

8,954

5,542

2001

17,468

8,422

9,046

4,878

2002

17,144

8,109

9,036

5,019

2003

16,968

7,611

9,357

4,510

2004

17,298

7,545

9,753

4,230

2005

17,445

7,720

9,725

4,321

2006

17,049

7,821

9,228

4,367

2007

16,460

7,618

8,683

3,924

2008

13,494

6,814

6.680

3,777

2009

10,601

5,456

5,154

2,247

2010

11,772

5,729

6,044

2,840

Source: US Census Bureau

http://www.census.gov/compendia/statab/cats/wholesale_retail_trade/motor_vehicle_sales.html

Chart VA-1 of the Board of Governors of the Federal Reserve provides output of motor vehicles and parts in the United States from 1972 to 2015. Output virtually stagnated since the late 1990s.

clip_image001

Chart VA-1, US, Motor Vehicles and Parts Output, 1972-2015

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/g17/Current/default.htm

The valuable report on Financial Accounts of the United States formerly Flow of Funds Accounts of the United States provided by the Board of Governors of the Federal Reserve System (http://www.federalreserve.gov/releases/z1/Current/ http://www.federalreserve.gov/apps/fof/) is rich in important information and analysis. Table IIA-1, updated in this blog for every new quarterly release, shows the balance sheet of US households combined with nonprofit organizations in 2007, 2011, 2014 and IQ2015. The data show the strong shock to US wealth during the contraction. Assets fell from $81.1 trillion in 2007 to $77.4 trillion in 2011 even after nine consecutive quarters of growth beginning in IIIQ2009 (http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/dollar-devaluation-and-carry-trade.html), for decline of $3.7 trillion or 4.5 percent. Assets stood at $97.5 trillion in 2014 for gain of $16.4 trillion relative to $81.1 trillion in 2007 or increase by 20.2 percent. Assets increased to $99.1 trillion in IQ2015 by $18.0 trillion relative to 2007 or 22.1 percent. Liabilities declined from $14.4 trillion in 2007 to $13.6 trillion in 2011 or by $824.4 billion equivalent to decline by 5.7 percent. Liabilities declined $226.4 billion or 1.6 percent from 2007 to 2014. Liabilities fell from $14.4 trillion in 2007 to $14.1 trillion in IQ2015, by $243.7 billion or decline of 1.7 percent. Net worth shrank from $66.7 trillion in 2007 to $63.9 trillion in 2011, that is, $2.8 trillion equivalent to decline of 4.3 percent. Net worth increased from $66,721.8 billion in 2007 to $84,924.6 billion in IQ2015 by $18,202.8 billion or 27.3 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 236.119 in Mar 2015 (http://www.bls.gov/cpi/data.htm) or 12.4 percent. Net worth adjusted by CPI inflation increased 13.2 percent from 2007 to IQ2015. Nonfinancial assets increased $898.5 billion from $28,149.7 billion in 2007 to $29,693.7 billion in IQ2015 or 5.5 percent. There was increase from 2007 to IQ2015 of $778.5 billion in real estate assets or by 3.3 percent. Real estate assets adjusted for CPI inflation fell 8.1 percent between 2007 and IQ2015. The National Association of Realtors estimated that the gains in net worth in homes by Americans were about $4 trillion between 2000 and 2005 (quoted in Pelaez and Pelaez, The Global Recession Risk (2007), 224-5).

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

 

2007

2011

2014

IQ2015

Assets

81,117.1

77,449.5

97,464.9

99,076.3

Nonfinancial

28,149.7

23,378.2

29,150.2

29,693.7

  Real Estate

23,340.2

18,252.6

23,615.4

24,118.7

  Durable Goods

  4,476.0

4,723.3

  5,085.5

5,121.1

Financial

52,967.4

54,071.3

68,314.7

69,382.6

  Deposits

  7,560.4

8,716.1

  10,144.1

10,287.2

  Credit   Market

  3,997.0

4,395.5

  3,314.5

3,271.4

  Mutual Fund Shares

   4,591.5

4,622.5

   7,695.3

7,918.8

  Equities Corporate

   9,912.5

8,498.4

   13,360.7

13,640.8

  Equity Noncorporate

   8,933.1

7,587.0

   9,924.7

10,156.2

  Pension

15,267.2

17,447.7

20,783.7

20,991.9

Liabilities

14,395.3

13,570.9

14,168.9

14,151.6

  Home Mortgages

10,613.3

9,695.9

  9,403.1

9,370.5

  Consumer Credit

   2,615.1

2,755.4

   3,317.2

3,321.6

Net Worth

66,721.8

63,878.6

83,296.0

84,924.6

Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2015. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2015. Washington, DC, Federal Reserve System, Jun 11. http://www.federalreserve.gov/releases/z1/.

The explanation of the sharp contraction of household wealth can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:

“On the maturity date T, the firm must either pay the promised payment of B to the debtholders or else the current equity will be valueless. Clearly, if at time T, V(T) > B, the firm should pay the bondholders because the value of equity will be V(T) – B > 0 whereas if they do not, the value of equity would be zero. If V(T) ≤ B, then the firm will not make the payment and default the firm to the bondholders because otherwise the equity holders would have to pay in additional money and the (formal) value of equity prior to such payments would be (V(T)- B) < 0.”

Pelaez and Pelaez (The Global Recession Risk (2007), 208-9) apply this analysis to the US housing market in 2005-2006 concluding:

“The house market [in 2006] is probably operating with low historical levels of individual equity. There is an application of structural models [Duffie and Singleton 2003] to the individual decisions on whether or not to continue paying a mortgage. The costs of sale would include realtor and legal fees. There could be a point where the expected net sale value of the real estate may be just lower than the value of the mortgage. At that point, there would be an incentive to default. The default vulnerability of securitization is unknown.”

There are multiple important determinants of the interest rate: “aggregate wealth, the distribution of wealth among investors, expected rate of return on physical investment, taxes, government policy and inflation” (Ingersoll 1987, 405). Aggregate wealth is a major driver of interest rates (Ibid, 406). Unconventional monetary policy, with zero fed funds rates and flattening of long-term yields by quantitative easing, causes uncontrollable effects on risk taking that can have profound undesirable effects on financial stability. Excessively aggressive and exotic monetary policy is the main culprit and not the inadequacy of financial management and risk controls.

The net worth of the economy depends on interest rates. In theory, “income is generally defined as the amount a consumer unit could consume (or believe that it could) while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is a flow that is obtained by applying a rate of return, r, to a stock of wealth, W, or Y = rW (Ibid). According to a subsequent restatement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption decisions is the long-run expected yield from wealth r*W. This yield was named permanent income: Y* = r*W” (Darby 1974, 229), where * denotes permanent. The simplified relation of income and wealth can be restated as:

W = Y/r (1)

Equation (1) shows that as r goes to zero, r →0, W grows without bound, W→∞.

Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment but the exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at close to zero interest rates, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).

The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4).

There are significant elements of the theory of bank financial fragility of Diamond and Dybvig (1983) and Diamond and Rajan (2000, 2001a, 2001b) that help to explain the financial fragility of banks during the credit/dollar crisis (see also Diamond 2007). The theory of Diamond and Dybvig (1983) as exposed by Diamond (2007) is that banks funding with demand deposits have a mismatch of liquidity (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 58-66). A run occurs when too many depositors attempt to withdraw cash at the same time. All that is needed is an expectation of failure of the bank. Three important functions of banks are providing evaluation, monitoring and liquidity transformation. Banks invest in human capital to evaluate projects of borrowers in deciding if they merit credit. The evaluation function reduces adverse selection or financing projects with low present value. Banks also provide important monitoring services of following the implementation of projects, avoiding moral hazard that funds be used for, say, real estate speculation instead of the original project of factory construction. The transformation function of banks involves both assets and liabilities of bank balance sheets. Banks convert an illiquid asset or loan for a project with cash flows in the distant future into a liquid liability in the form of demand deposits that can be withdrawn immediately.

In the theory of banking of Diamond and Rajan (2000, 2001a, 2001b), the bank creates liquidity by tying human assets to capital. The collection skills of the relationship banker convert an illiquid project of an entrepreneur into liquid demand deposits that are immediately available for withdrawal. The deposit/capital structure is fragile because of the threat of bank runs. In these days of online banking, the run on Washington Mutual was through withdrawals online. A bank run can be triggered by the decline of the value of bank assets below the value of demand deposits.

Pelaez and Pelaez (Regulation of Banks and Finance 2009b, 60, 64-5) find immediate application of the theories of banking of Diamond, Dybvig and Rajan to the credit/dollar crisis after 2007. It is a credit crisis because the main issue was the deterioration of the credit portfolios of securitized banks as a result of default of subprime mortgages. It is a dollar crisis because of the weakening dollar resulting from relatively low interest rate policies of the US. It caused systemic effects that converted into a global recession not only because of the huge weight of the US economy in the world economy but also because the credit crisis transferred to the UK and Europe. Management skills or human capital of banks are illustrated by the financial engineering of complex products. The increasing importance of human relative to inanimate capital (Rajan and Zingales 2000) is revolutionizing the theory of the firm (Zingales 2000) and corporate governance (Rajan and Zingales 2001). Finance is one of the most important examples of this transformation. Profits were derived from the charter in the original banking institution. Pricing and structuring financial instruments was revolutionized with option pricing formulas developed by Black and Scholes (1973) and Merton (1973, 1974, 1998) that permitted the development of complex products with fair pricing. The successful financial company must attract and retain finance professionals who have invested in human capital, which is a sunk cost to them and not of the institution where they work.

The complex financial products created for securitized banking with high investments in human capital are based on houses, which are as illiquid as the projects of entrepreneurs in the theory of banking. The liquidity fragility of the securitized bank is equivalent to that of the commercial bank in the theory of banking (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65). Banks created off-balance sheet structured investment vehicles (SIV) that issued commercial paper receiving AAA rating because of letters of liquidity guarantee by the banks. The commercial paper was converted into liquidity by its use as collateral in SRPs at the lowest rates and minimal haircuts because of the AAA rating of the guarantor bank. In the theory of banking, default can be triggered when the value of assets is perceived as lower than the value of the deposits. Commercial paper issued by SIVs, securitized mortgages and derivatives all obtained SRP liquidity on the basis of illiquid home mortgage loans at the bottom of the pyramid. The run on the securitized bank had a clear origin (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65):

“The increasing default of mortgages resulted in an increase in counterparty risk. Banks were hit by the liquidity demands of their counterparties. The liquidity shock extended to many segments of the financial markets—interbank loans, asset-backed commercial paper (ABCP), high-yield bonds and many others—when counterparties preferred lower returns of highly liquid safe havens, such as Treasury securities, than the risk of having to sell the collateral in SRPs at deep discounts or holding an illiquid asset. The price of an illiquid asset is near zero.”

Gorton and Metrick (2010H, 507) provide a revealing quote to the work in 1908 of Edwin R. A. Seligman, professor of political economy at Columbia University, founding member of the American Economic Association and one of its presidents and successful advocate of progressive income taxation. The intention of the quote is to bring forth the important argument that financial crises are explained in terms of “confidence” but as Professor Seligman states in reference to historical banking crises in the US the important task is to explain what caused the lack of confidence. It is instructive to repeat the more extended quote of Seligman (1908, xi) on the explanations of banking crises:

“The current explanations may be divided into two categories. Of these the first includes what might be termed the superficial theories. Thus it is commonly stated that the outbreak of a crisis is due to lack of confidence,--as if the lack of confidence was not in itself the very thing which needs to be explained. Of still slighter value is the attempt to associate a crisis with some particular governmental policy, or with some action of a country’s executive. Such puerile interpretations have commonly been confined to countries like the United States, where the political passions of democracy have had the fullest way. Thus the crisis of 1893 was ascribed by the Republicans to the impending Democratic tariff of 1894; and the crisis of 1907 has by some been termed the ‘[Theodore] Roosevelt panic,” utterly oblivious of the fact that from the time of President Jackson, who was held responsible for the troubles of 1837, every successive crisis had had its presidential scapegoat, and has been followed by a political revulsion. Opposed to these popular, but wholly unfounded interpretations, is the second class of explanations, which seek to burrow beneath the surface and to discover the more occult and fundamental causes of the periodicity of crises.”

Scholars ignore superficial explanations in the effort to seek good and truth. The problem of economic analysis of the credit/dollar crisis is the lack of a structural model with which to attempt empirical determination of causes (Gorton and Metrick 2010SB). There would still be doubts even with a well-specified structural model because samples of economic events do not typically permit separating causes and effects. There is also confusion is separating the why of the crisis and how it started and propagated, all of which are extremely important.

In true heritage of the principles of Seligman (1908), Gorton (2009EFM) discovers a prime causal driver of the credit/dollar crisis. The objective of subprime and Alt-A mortgages was to facilitate loans to populations with modest means so that they could acquire a home. These borrowers would not receive credit because of (1) lack of funds for down payments; (2) low credit rating and information; (3) lack of information on income; and (4) errors or lack of other information. Subprime mortgage “engineering” was based on the belief that both lender and borrower could benefit from increases in house prices over the short run. The initial mortgage would be refinanced in two or three years depending on the increase of the price of the house. According to Gorton (2009EFM, 13, 16):

“The outstanding amounts of Subprime and Alt-A [mortgages] combined amounted to about one quarter of the $6 trillion mortgage market in 2004-2007Q1. Over the period 2000-2007, the outstanding amount of agency mortgages doubled, but subprime grew 800%! Issuance in 2005 and 2006 of Subprime and Alt-A mortgages was almost 30% of the mortgage market. Since 2000 the Subprime and Alt-A segments of the market grew at the expense of the Agency (i.e., the government sponsored entities of Fannie Mae and Freddie Mac) share, which fell from almost 80% (by outstanding or issuance) to about half by issuance and 67% by outstanding amount. The lender’s option to rollover the mortgage after an initial period is implicit in the subprime mortgage. The key design features of a subprime mortgage are: (1) it is short term, making refinancing important; (2) there is a step-up mortgage rate that applies at the end of the first period, creating a strong incentive to refinance; and (3) there is a prepayment penalty, creating an incentive not to refinance early.”

The prime objective of successive administrations in the US during the past 20 years and actually since the times of Roosevelt in the 1930s has been to provide “affordable” financing for the “American dream” of home ownership. The US housing finance system is mixed with public, public/private and purely private entities. The Federal Home Loan Bank (FHLB) system was established by Congress in 1932 that also created the Federal Housing Administration in 1934 with the objective of insuring homes against default. In 1938, the government created the Federal National Mortgage Association, or Fannie Mae, to foster a market for FHA-insured mortgages. Government-insured mortgages were transferred from Fannie Mae to the Government National Mortgage Association, or Ginnie Mae, to permit Fannie Mae to become a publicly-owned company. Securitization of mortgages began in 1970 with the government charter to the Federal Home Loan Mortgage Corporation, or Freddie Mac, with the objective of bundling mortgages created by thrift institutions that would be marketed as bonds with guarantees by Freddie Mac (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 42-8). In the third quarter of 2008, total mortgages in the US were $12,057 billion of which 43.5 percent, or $5423 billion, were retained or guaranteed by Fannie Mae and Freddie Mac (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 45). In 1990, Fannie Mae and Freddie Mac had a share of only 25.4 percent of total mortgages in the US. Mortgages in the US increased from $6922 billion in 2002 to $12,088 billion in 2007, or by 74.6 percent, while the retained or guaranteed portfolio of Fannie and Freddie rose from $3180 billion in 2002 to $4934 billion in 2007, or by 55.2 percent.

According to Pinto (2008) in testimony to Congress:

“There are approximately 25 million subprime and Alt-A loans outstanding, with an unpaid principal amount of over $4.5 trillion, about half of them held or guaranteed by Fannie and Freddie. Their high risk activities were allowed to operate at 75:1 leverage ratio. While they may deny it, there can be no doubt that Fannie and Freddie now own or guarantee $1.6 trillion in subprime, Alt-A and other default prone loans and securities. This comprises over 1/3 of their risk portfolios and amounts to 34% of all the subprime loans and 60% of all Alt-A loans outstanding. These 10.5 million unsustainable, nonprime loans are experiencing a default rate 8 times the level of the GSEs’ 20 million traditional quality loans. The GSEs will be responsible for a large percentage of an estimated 8.8 million foreclosures expected over the next 4 years, accounting for the failure of about 1 in 6 home mortgages. Fannie and Freddie have subprimed America.”

In perceptive analysis of growth and macroeconomics in the past six decades, Rajan (2012FA) argues that “the West can’t borrow and spend its way to recovery.” The Keynesian paradigm is not applicable in current conditions. Advanced economies in the West could be divided into those that reformed regulatory structures to encourage productivity and others that retained older structures. In the period from 1950 to 2000, Cobet and Wilson (2002) find that US productivity, measured as output/hour, grew at the average yearly rate of 2.9 percent while Japan grew at 6.3 percent and Germany at 4.7 percent (see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). In the period from 1995 to 2000, output/hour grew at the average yearly rate of 4.6 percent in the US but at lower rates of 3.9 percent in Japan and 2.6 percent in the US. Rajan (2012FA) argues that the differential in productivity growth was accomplished by deregulation in the US at the end of the 1970s and during the 1980s. In contrast, Europe did not engage in reform with the exception of Germany in the early 2000s that empowered the German economy with significant productivity advantage. At the same time, technology and globalization increased relative remunerations in highly-skilled, educated workers relative to those without skills for the new economy. It was then politically appealing to improve the fortunes of those left behind by the technological revolution by means of increasing cheap credit. As Rajan (2012FA) argues:

“In 1992, Congress passed the Federal Housing Enterprises Financial Safety and Soundness Act, partly to gain more control over Fannie Mae and Freddie Mac, the giant private mortgage agencies, and partly to promote affordable homeownership for low-income groups. Such policies helped money flow to lower-middle-class households and raised their spending—so much so that consumption inequality rose much less than income inequality in the years before the crisis. These policies were also politically popular. Unlike when it came to an expansion in government welfare transfers, few groups opposed expanding credit to the lower-middle class—not the politicians who wanted more growth and happy constituents, not the bankers and brokers who profited from the mortgage fees, not the borrowers who could now buy their dream houses with virtually no money down, and not the laissez-faire bank regulators who thought they could pick up the pieces if the housing market collapsed. The Federal Reserve abetted these shortsighted policies. In 2001, in response to the dot-com bust, the Fed cut short-term interest rates to the bone. Even though the overstretched corporations that were meant to be stimulated were not interested in investing, artificially low interest rates acted as a tremendous subsidy to the parts of the economy that relied on debt, such as housing and finance. This led to an expansion in housing construction (and related services, such as real estate brokerage and mortgage lending), which created jobs, especially for the unskilled. Progressive economists applauded this process, arguing that the housing boom would lift the economy out of the doldrums. But the Fed-supported bubble proved unsustainable. Many construction workers have lost their jobs and are now in deeper trouble than before, having also borrowed to buy unaffordable houses. Bankers obviously deserve a large share of the blame for the crisis. Some of the financial sector’s activities were clearly predatory, if not outright criminal. But the role that the politically induced expansion of credit played cannot be ignored; it is the main reason the usual checks and balances on financial risk taking broke down.”

In fact, Raghuram G. Rajan (2005) anticipated low liquidity in financial markets resulting from low interest rates before the financial crisis that caused distortions of risk/return decisions provoking the credit/dollar crisis and global recession from IVQ2007 to IIQ2009. Near zero interest rates of unconventional monetary policy induced excessive risks and low liquidity in financial decisions that were critical as a cause of the credit/dollar crisis after 2007. Rajan (2012FA) argues that it is not feasible to return to the employment and income levels before the credit/dollar crisis because of the bloated construction sector, financial system and government budgets.

Table IIA-1 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 94.7 percent in the 10-city composite of the Case-Shiller home price index, 78.0 percent in the 20-city composite and 62.9 percent in the US national home price index between Apr 2000 and Apr 2005. Prices rose around 100 percent from Apr 2000 to Apr 2006, increasing 116.3 percent for the 10-city composite, 98.0 percent for the 20-city composite and 79.1 percent in the US national index. House prices rose 38.3 percent between Apr 2003 and Apr 2005 for the 10-city composite, 33.0 percent for the 20-city composite and 28.0 percent for the US national propelled by low fed funds rates of 1.0 percent between Jun 2003 and Jun 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Aprket Committee (FOMC) from Jun 2004 until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Apr 2003 and Apr 2006, the 10-city index gained 53.6 percent, the 20-city index increased 47.8 percent and the US national 40.7 percent. House prices have fallen from Apr 2006 to Apr 2015 by 14.8 percent for the 10-city composite, 13.6 percent for the 20-city composite and 7.4 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Apr 2015, house prices increased 4.6 percent in the 10-city composite, increased 4.9 percent in the 20-city composite and 4.2 percent in the US national. Table IIA-6 also shows that house prices increased 84.4 percent between Apr 2000 and Apr 2015 for the 10-city composite, increased 71.0 percent for the 20-city composite and 65.8 percent for the US national. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The 10-city composite fell 15.2 percent from the peak in Jun 2006 to Apr 2015 and the 20-city composite fell 14.3 percent from the peak in Jul 2006 to Apr 2015. The US national fell 7.9 percent from the peaks of the 10-city composite to Apr 2015 and 7.9 percent from the peak of the 20-city composite to Apr 2015. The final part of Table II-2 provides average annual percentage rates of growth of the house price indexes of Standard & Poor’s Case-Shiller. The average annual growth rate between Dec 1987 and Dec 2014 for the 10-city composite was 3.7 percent and 3.4 percent for the US national. Data for the 20-city composite are available only beginning in Jan 2000. House prices accelerated in the 1990s with the average rate of the 10-city composite of 5.0 percent between Dec 1992 and Dec 2000 while the average rate for the period Dec 1987 to Dec 2000 was 3.8 percent. The average rate for the US national was 3.4 percent from Dec 1987 to Dec 2014 and 3.6 percent from Dec 1987 to Dec 2000. Although the global recession affecting the US between IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly above 30 percent, the average annual growth rate of the 10-city composite between Dec 2000 and Dec 2014 was 3.7 percent while the rate of the 20-city composite was 3.2 percent and 3.1 percent for the US national.

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

 

10-City Composite

20-City Composite

US National

∆% Apr 2000 to Apr 2003

40.8

33.9

27.3

∆% Apr 2000 to Apr 2005

94.7

78.0

62.9

∆% Apr 2003 to Apr 2005

38.3

33.0

28.0

∆% Apr 2000 to Apr 2006

116.3

98.0

79.1

∆% Apr 2003 to Apr 2006

53.6

47.8

40.7

∆% Apr 2005 to Apr 2015

-5.3

-3.9

1.8

∆% Apr 2006 to Apr 2015

-14.8

-13.6

-7.4

∆% Apr 2009 to Apr 2015

27.5

27.1

15.7

∆% Apr 2010 to Apr 2015

21.9

22.4

16.9

∆% Apr 2011 to Apr 2015

26.4

27.9

22.2

∆% Apr 2012 to Apr 2015

29.2

30.2

22.7

∆% Apr 2013 to Apr 2015

16.0

16.3

12.6

∆% Apr 2014 to Apr 2015

4.6

4.9

4.2

∆% Apr 2000 to Apr 2015

84.4

71.0

65.8

∆% Peak Jun 2006 Apr 2015

-15.2

 

-7.9

∆% Peak Jul 2006 Apr 2015

 

-14.3

-7.9

Average ∆% Dec 1987-Dec 2014

3.7

NA

3.4

Average ∆% Dec 1987-Dec 2000

3.8

NA

3.6

Average ∆% Dec 1992-Dec 2000

5.0

NA

4.5

Average ∆% Dec 2000-Dec 2014

3.7

3.2

3.1

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

Price increases measured by the Case-Shiller house price indices show that “home prices continued their rise across the country over the last 12 months” (https://www.spice-indices.com/idpfiles/spice-assets/resources/public/documents/200749_cshomeprice-release-0630.pdf?force_download=true). Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the 10- and 20-city composites, as shown in Table IIA-7. In Jan 2013, the seasonally adjusted 10-city composite increased 0.9 percent and the 20-city increased 1.0 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city changed 0.0 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. With the exception of Mar through Apr 2012, house prices seasonally adjusted declined in every month for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table I-6. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. Without seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Aug 2011 but fell in every month from Sep 2011 to Feb 2012. The not seasonally adjusted index registers decline in Mar 2012 of 0.1 percent for the 10-city composite and is flat for the 20-city composite. Not seasonally adjusted house prices increased 1.4 percent in Apr 2012 and at high monthly percentage rates until Sep 2012. House prices not seasonally adjusted stalled from Oct 2012 to Jan 2013 and surged from Feb to Sep 2013, decelerating in Oct 2013-Feb 2014. House prices grew at fast rates in Mar 2014. The 10-city NSA index increased 1.0 percent in Apr 2015 and the 20-city increased 1.1 percent. The 10-city SA increased 0.4 percent in Apr 2015 and the 20-city composite SA increased 0.3 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

Table IIA-2, US, Monthly Percentage Change of S&P Case-Shiller Home Price Indices, Seasonally Adjusted and Not Seasonally Adjusted, ∆%

 

10-City Composite SA

10-City Composite NSA

20-City Composite SA

20-City Composite NSA

Apr 2015

0.4

1.0

0.3

1.1

Mar

0.8

0.8

1.0

0.9

Feb

1.1

0.5

1.1

0.4

Jan

0.8

-0.1

0.8

-0.1

Dec 2014

0.8

0.1

0.9

0.0

Nov

0.7

-0.3

0.7

-0.2

Oct

0.6

-0.1

0.7

-0.1

Sep

0.2

-0.1

0.3

-0.1

Aug

-0.1

0.2

0.0

0.2

Jul

-0.3

0.6

-0.3

0.6

Jun

-0.1

1.0

-0.2

1.0

May

-0.5

1.1

-0.5

1.1

Apr

0.4

1.1

0.3

1.2

Mar

0.9

0.8

1.0

0.9

Feb

0.7

0.0

0.7

0.0

Jan

0.9

-0.1

0.8

-0.1

Dec 2013

0.7

-0.1

0.7

-0.1

Nov

0.9

0.0

0.9

-0.1

Oct

1.0

0.2

1.0

0.2

Sep

1.0

0.7

1.1

0.7

Aug

1.1

1.3

1.1

1.3

Jul

0.9

1.9

0.9

1.8

Jun

1.0

2.2

0.9

2.2

May

0.9

2.5

0.9

2.5

Apr

1.9

2.6

1.7

2.6

Mar

1.4

1.3

1.5

1.3

Feb

1.1

0.3

1.0

0.2

Jan

0.9

0.0

1.0

0.0

Dec 2012

1.0

0.2

1.0

0.2

Nov

0.6

-0.3

0.7

-0.2

Oct

0.6

-0.2

0.7

-0.1

Sep

0.5

0.3

0.6

0.3

Aug

0.5

0.8

0.6

0.9

Jul

0.4

1.5

0.5

1.6

Jun

0.9

2.1

1.0

2.3

May

0.7

2.2

0.8

2.4

Apr

0.6

1.4

0.6

1.4

Mar

0.2

-0.1

0.3

0.0

Feb

-0.1

-0.9

0.0

-0.8

Jan

-0.2

-1.1

-0.1

-1.0

Dec 2011

-0.5

-1.2

-0.4

-1.1

Nov

-0.6

-1.4

-0.5

-1.3

Oct

-0.6

-1.3

-0.6

-1.4

Sep

-0.4

-0.6

-0.5

-0.7

Aug

-0.2

0.1

-0.2

0.1

Jul

-0.1

0.9

-0.1

1.0

Jun

-0.1

1.0

-0.1

1.2

May

-0.3

1.0

-0.4

1.0

Apr

-0.1

0.6

-0.2

0.6

Mar

-0.5

-1.0

-0.6

-1.0

Feb

-0.4

-1.3

-0.3

-1.2

Jan

-0.2

-1.1

-0.2

-1.1

Dec 2010

-0.2

-0.9

-0.2

-1.0

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

VB Japan. The GDP of Japan grew at 1.0 percent per year on average from 1991 to 2002, with the GDP implicit deflator falling at 0.8 percent per year on average. The average growth rate of Japan’s GDP was 4 percent per year on average from the middle of the 1970s to 1992 (Ito 2004). Low growth in Japan in the 1990s is commonly labeled as “the lost decade” (see Pelaez and Pelaez, The Global Recession Risk (2007), 81-115). Table VB-GDP provides yearly growth rates of Japan’s GDP from 1995 to 2014. Growth weakened from 1.9 per cent in 1995 and 2.6 percent in 1996 to contractions of 2.0 percent in 1998 and 0.2 percent in 1999. Growth rates were below 2 percent with exception of 2.3 percent in 2000, 2.4 percent in 2004 and 2.2 percent in 2007. Japan’s GDP contracted sharply by 1.0 percent in 2008 and 5.5 percent in 2009. As in most advanced economies, growth was robust at 4.7 percent in 2010 but mediocre at minus 0.5 percent in 2011 because of the tsunami and 1.7 percent in 2012. Japan’s GDP grew 1.6 percent in 2013 and stagnated in 2014 at minus 0.1. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). Japan’s real GDP in calendar year 2014 is 0.6 percent higher than in calendar year 2007 (http://www.esri.cao.go.jp/index-e.html).

Table VB-GDP, Japan, Yearly Percentage Change of GDP  ∆%

Calendar Year

∆%

1995

1.9

1996

2.6

1997

1.6

1998

-2.0

1999

-0.2

2000

2.3

2001

0.4

2002

0.3

2003

1.7

2004

2.4

2005

1.3

2006

1.7

2007

2.2

2008

-1.0

2009

-5.5

2010

4.7

2011

-0.5

2012

1.7

2013

1.6

2014

-0.1

Source: Source: Japan Economic and Social Research Institute, Cabinet Office

http://www.esri.cao.go.jp/index-e.html

http://www.esri.cao.go.jp/en/sna/sokuhou/sokuhou_top.html

Table VB-BOJF provides the forecasts of economic activity and inflation in Japan by the majority of members of the Policy Board of the Bank of Japan, which is part of their Outlook for Economic Activity and Prices (https://www.boj.or.jp/en/mopo/outlook/gor1504b.pdf) with changes on Jul 21, 2015 (https://www.boj.or.jp/en/announcements/release_2015/k150121a.pdf). For fiscal 2015, the forecast is of growth of GDP between 1.5 to 2.1 percent, with the all items CPI less fresh food 0.2 to 1.2 to 3.3 percent (https://www.boj.or.jp/en/mopo/outlook/gor1504b.pdf). The critical difference is forecast of the CPI excluding fresh food of 0.2 to 1.2 percent in 2015 and 1.2 to 2.2 percent in 2016 (https://www.boj.or.jp/en/mopo/outlook/gor1504b.pdf). Consumer price inflation in Japan excluding fresh food was minus 0.4 percent in Mar 2014 and 2.2 percent in 12 months (http://www.stat.go.jp/english/data/cpi/1581.htm), significantly because of the increase of the tax on value added of consumption in Apr 2014. The new monetary policy of the Bank of Japan aims to increase inflation to 2 percent. These forecasts are biannual in Apr and Oct. The Cabinet Office, Ministry of Finance and Bank of Japan released on Jan 22, 2013, a “Joint Statement of the Government and the Bank of Japan on Overcoming Deflation and Achieving Sustainable Economic Growth” (http://www.boj.or.jp/en/announcements/release_2013/k130122c.pdf) with the important change of increasing the inflation target of monetary policy from 1 percent to 2 percent:

“The Bank of Japan conducts monetary policy based on the principle that the policy shall be aimed at achieving price stability, thereby contributing to the sound development of the national economy, and is responsible for maintaining financial system stability. The Bank aims to achieve price stability on a sustainable basis, given that there are various factors that affect prices in the short run.

The Bank recognizes that the inflation rate consistent with price stability on a sustainable basis will rise as efforts by a wide range of entities toward strengthening competitiveness and growth potential of Japan's economy make progress. Based on this recognition, the Bank sets the price stability target at 2 percent in terms of the year-on-year rate of change in the consumer price index.

Under the price stability target specified above, the Bank will pursue monetary easing and aim to achieve this target at the earliest possible time. Taking into consideration that it will take considerable time before the effects of monetary policy permeate the economy, the Bank will ascertain whether there is any significant risk to the sustainability of economic growth, including from the accumulation of financial imbalances.”

The Bank of Japan also provided explicit analysis of its view on price stability in a “Background note regarding the Bank’s thinking on price stability” (http://www.boj.or.jp/en/announcements/release_2013/data/rel130123a1.pdf http://www.boj.or.jp/en/announcements/release_2013/rel130123a.htm/). The Bank of Japan also amended “Principal terms and conditions for the Asset Purchase Program” (http://www.boj.or.jp/en/announcements/release_2013/rel130122a.pdf): “Asset purchases and loan provision shall be conducted up to the maximum outstanding amounts by the end of 2013. From January 2014, the Bank shall purchase financial assets and provide loans every month, the amount of which shall be determined pursuant to the relevant rules of the Bank.”

Financial markets in Japan and worldwide were shocked by new bold measures of “quantitative and qualitative monetary easing” by the Bank of Japan (http://www.boj.or.jp/en/announcements/release_2013/k130404a.pdf). The objective of policy is to “achieve the price stability target of 2 percent in terms of the year-on-year rate of change in the consumer price index (CPI) at the earliest possible time, with a time horizon of about two years” (http://www.boj.or.jp/en/announcements/release_2013/k130404a.pdf). The main elements of the new policy are as follows:

  1. Monetary Base Control. Most central banks in the world pursue interest rates instead of monetary aggregates, injecting bank reserves to lower interest rates to desired levels. The Bank of Japan (BOJ) has shifted back to monetary aggregates, conducting money market operations with the objective of increasing base money, or monetary liabilities of the government, at the annual rate of 60 to 70 trillion yen. The BOJ estimates base money outstanding at “138 trillion yen at end-2012) and plans to increase it to “200 trillion yen at end-2012 and 270 trillion yen at end 2014” (http://www.boj.or.jp/en/announcements/release_2013/k130404a.pdf).
  2. Maturity Extension of Purchases of Japanese Government Bonds. Purchases of bonds will be extended even up to bonds with maturity of 40 years with the guideline of extending the average maturity of BOJ bond purchases from three to seven years. The BOJ estimates the current average maturity of Japanese government bonds (JGB) at around seven years. The BOJ plans to purchase about 7.5 trillion yen per month (http://www.boj.or.jp/en/announcements/release_2013/rel130404d.pdf). Takashi Nakamichi, Tatsuo Ito and Phred Dvorak, wiring on “Bank of Japan mounts bid for revival,” on Apr 4, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323646604578401633067110420.html), find that the limit of maturities of three years on purchases of JGBs was designed to avoid views that the BOJ would finance uncontrolled government deficits.
  3. Seigniorage. The BOJ is pursuing coordination with the government that will take measures to establish “sustainable fiscal structure with a view to ensuring the credibility of fiscal management” (http://www.boj.or.jp/en/announcements/release_2013/k130404a.pdf).
  4. Diversification of Asset Purchases. The BOJ will engage in transactions of exchange traded funds (ETF) and real estate investment trusts (REITS) and not solely on purchases of JGBs. Purchases of ETFs will be at an annual rate of increase of one trillion yen and purchases of REITS at 30 billion yen.
  5. Bank Lending Facility and Growth Supporting Funding Facility. At the meeting on Feb 18, the Bank of Japan doubled the scale of these lending facilities to prevent their expiration in the near future (http://www.boj.or.jp/en/announcements/release_2014/k140218a.pdf).

Table VB-BOJF provides the forecasts of economic activity and inflation in Japan by the majority of members of the Policy Board of the Bank of Japan, which is part of their Outlook for Economic Activity and Prices (https://www.boj.or.jp/en/announcements/release_2015/k150121a.pdf) with changes on Jan 21, 2015 (https://www.boj.or.jp/en/announcements/release_2015/k150121a.pdf). On Jun 19, 2015, the Bank of Japan announced a “New Framework for Monetary Policy Meetings,” which provides for quarterly release of the forecasts of the economy and prices beginning in Jan 2016 (https://www.boj.or.jp/en/announcements/release_2015/rel150619a.pdf). For fiscal 2014, the forecast is of growth of GDP between minus 0.7 to minus 0.3 percent, with the all items CPI less fresh food 2.9 to 3.3 percent (https://www.boj.or.jp/en/announcements/release_2015/k150121a.pdf). The critical difference is forecast of the CPI excluding fresh food of 0.3 to 1.4 percent in 2015 and 0.9 to 2.3 percent in 2016 (https://www.boj.or.jp/en/announcements/release_2015/k150121a.pdf). Consumer price inflation in Japan excluding fresh food was minus 0.2 percent in Dec 2014 and 2.5 percent in 12 months (http://www.stat.go.jp/english/data/cpi/1581.htm), significantly because of the increase of the tax on value added of consumption in Apr 2014. The new monetary policy of the Bank of Japan aims to increase inflation to 2 percent. These forecasts are biannual in Apr and Oct. The Cabinet Office, Ministry of Finance and Bank of Japan released on Jan 22, 2013, a “Joint Statement of the Government and the Bank of Japan on Overcoming Deflation and Achieving Sustainable Economic Growth” (http://www.boj.or.jp/en/announcements/release_2013/k130122c.pdf) with the important change of increasing the inflation target of monetary policy from 1 percent to 2 percent:

“The Bank of Japan conducts monetary policy based on the principle that the policy shall be aimed at achieving price stability, thereby contributing to the sound development of the national economy, and is responsible for maintaining financial system stability. The Bank aims to achieve price stability on a sustainable basis, given that there are various factors that affect prices in the short run.

The Bank recognizes that the inflation rate consistent with price stability on a sustainable basis will rise as efforts by a wide range of entities toward strengthening competitiveness and growth potential of Japan's economy make progress. Based on this recognition, the Bank sets the price stability target at 2 percent in terms of the year-on-year rate of change in the consumer price index.

Under the price stability target specified above, the Bank will pursue monetary easing and aim to achieve this target at the earliest possible time. Taking into consideration that it will take considerable time before the effects of monetary policy permeate the economy, the Bank will ascertain whether there is any significant risk to the sustainability of economic growth, including from the accumulation of financial imbalances.”

The Bank of Japan also provided explicit analysis of its view on price stability in a “Background note regarding the Bank’s thinking on price stability” (http://www.boj.or.jp/en/announcements/release_2013/data/rel130123a1.pdf http://www.boj.or.jp/en/announcements/release_2013/rel130123a.htm/). The Bank of Japan also amended “Principal terms and conditions for the Asset Purchase Program” (http://www.boj.or.jp/en/announcements/release_2013/rel130122a.pdf): “Asset purchases and loan provision shall be conducted up to the maximum outstanding amounts by the end of 2013. From January 2014, the Bank shall purchase financial assets and provide loans every month, the amount of which shall be determined pursuant to the relevant rules of the Bank.”

Financial markets in Japan and worldwide were shocked by new bold measures of “quantitative and qualitative monetary easing” by the Bank of Japan (http://www.boj.or.jp/en/announcements/release_2013/k130404a.pdf). The objective of policy is to “achieve the price stability target of 2 percent in terms of the year-on-year rate of change in the consumer price index (CPI) at the earliest possible time, with a time horizon of about two years” (http://www.boj.or.jp/en/announcements/release_2013/k130404a.pdf). The main elements of the new policy are as follows:

  1. Monetary Base Control. Most central banks in the world pursue interest rates instead of monetary aggregates, injecting bank reserves to lower interest rates to desired levels. The Bank of Japan (BOJ) has shifted back to monetary aggregates, conducting money market operations with the objective of increasing base money, or monetary liabilities of the government, at the annual rate of 60 to 70 trillion yen. The BOJ estimates base money outstanding at “138 trillion yen at end-2012) and plans to increase it to “200 trillion yen at end-2012 and 270 trillion yen at end 2014” (http://www.boj.or.jp/en/announcements/release_2013/k130404a.pdf).
  2. Maturity Extension of Purchases of Japanese Government Bonds. Purchases of bonds will be extended even up to bonds with maturity of 40 years with the guideline of extending the average maturity of BOJ bond purchases from three to seven years. The BOJ estimates the current average maturity of Japanese government bonds (JGB) at around seven years. The BOJ plans to purchase about 7.5 trillion yen per month (http://www.boj.or.jp/en/announcements/release_2013/rel130404d.pdf). Takashi Nakamichi, Tatsuo Ito and Phred Dvorak, wiring on “Bank of Japan mounts bid for revival,” on Apr 4, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323646604578401633067110420.html), find that the limit of maturities of three years on purchases of JGBs was designed to avoid views that the BOJ would finance uncontrolled government deficits.
  3. Seigniorage. The BOJ is pursuing coordination with the government that will take measures to establish “sustainable fiscal structure with a view to ensuring the credibility of fiscal management” (http://www.boj.or.jp/en/announcements/release_2013/k130404a.pdf).
  4. Diversification of Asset Purchases. The BOJ will engage in transactions of exchange traded funds (ETF) and real estate investment trusts (REITS) and not solely on purchases of JGBs. Purchases of ETFs will be at an annual rate of increase of one trillion yen and purchases of REITS at 30 billion yen.
  5. Bank Lending Facility and Growth Supporting Funding Facility. At the meeting on Feb 18, the Bank of Japan doubled the scale of these lending facilities to prevent their expiration in the near future (http://www.boj.or.jp/en/announcements/release_2014/k140218a.pdf).

Table VB-BOJF, Bank of Japan, Forecasts of the Majority of Members of the Policy Board, % Year on Year

Fiscal Year
Date of Forecast

Real GDP

CPI All Items Less Fresh Food

Excluding Effects of Consumption Tax Hikes

2013

     

Apr 2014

+2.2 to +2.3
[+2.2]

+0.8

 

Jan 2014

+2.5 to +2.9

[+2.7]

+0.7 to +0.9

[+0.7]

 

Oct 2013

+2.6 to +3.0

[+2.7]

+0.6 to +1.0

[+0.7]

 

Jul 2013

+2.5 to +3.0

[+2.8]

+0.5 to +0.8

[+0.6]

 

2014

     

Apr 2015

-1.0 to -0.8

[-0.9]

+2.8

+0.8

Jan 2015

-0.6 to -0.4

[-0.5]

+2.9 to +3.2

[+2.9]

+0.9 to +1.2

[+0.9]

Oct 2014

+0.2 to +0.7

[+0.5]

+3.1 to +3.4

[+3.2]

+1.1 to +1.4

[+1.2]

Jul 2014

+0.6 to +1.3

[+1.0]

+3.2 to +3.5

[+3.3]

+1.2 to +1.5

[+1.3]

Apr 2014

+0.8 to +1.3
[+1.1]

+3.0 to +3.5
[+3.3]

+1.0 to +1.5
[+1.3]

Jan 2014

+0.9 to 1.5

[+1.4]

+2.9 to +3.6

[+3.3]

+0.9 to +1.6

[+1.3]

Oct 2013

+0.9 to +1.5

[+1.5]

+2.8 to +3.6

[+3.3]

+0.8 to +1.6

[+1.3]

Jul 2013

+0.8 to +1.5

[+1.3]

+2.7 to +3.6

[+3.3]

+0.7 to +1.6

[+1.3]

2015

     

Apr 2015

+1.5 to +2.1

[+2.0]

+0.2 to 1.2

[+0.8]

+0.2 to 1.2

[+0.8]

Jan 2015

+1.8 to +2.3

[+2.1]

+0.4 to +1.3

[+1.0]

+0.4 to +1.3

[+1.0]

Oct 2014

+1.2 to +1.7

[+1.5]

+1.8 to 2.6

[+2.4]

+1.1 to +1.9

[+1.7]

Jul 2014

+1.2 to +1.6

[+1.5]

+1.9 to +2.8

[+2.6]

+1.2 to +2.1

[+1.9]

Apr 2014

+1.2 to +1.5
[+1.5]

+1.9 to +2.8
[+2.6]

+1.2 to +2.1
[+1.9]

Jan 2014

+1.2 to +1.8

[+1.5]

+1.7 to +2.9

[+2.6]

+1.0 to +2.2

[+1.9]

Oct 2013

+1.3 to +1.8

[+1.5]

+1.6 to +2.9

[+2.6]

+0.9 to +2.2

[+1.9]

Jul 2013

+1.3 to +1.9 [+1.5]

+1.6 to +2.9 [+2.6]

+0.9 to +2.2 [+1.9]

2016

     

Apr 2015

+1.4 to +1.8

[+1.5]

+1.2 to +2.2

[+2.0]

+1.2 to +2.2

[+2.0]

Jan 2015

+1.5 to +1.7

[+1.6]

+1.5 to +2.3

[+2.2]

+1.5 to +2.3

[+2.2]

Oct 2014

+1.0 to +1.4

[+1.2]

+1.9 to 3.0

[+2.8]

+1.2 to 2.3

[+2.1]

Jul 2014

+1.0 to +1.5

[+1.3]

+2.0 to +3.0

[+2.8]

+1.3 to +2.3

[+2.1]

Apr 2014

+1.0 to +1.5
[+1.3]

+2.0 to +3.0
[+2.8]

+1.3 to +2.3
[+2.1]

2017

     

Apr 2015

+0.1 to +0.5

[+0.2]

+2.7 to +3.4

[+3.2]

+1.4 to +2.1

[+1.9]

Figures in brackets are the median of forecasts of Policy Board members

Source: Policy Board, Bank of Japan

Figures in brackets are the median of forecasts of Policy Board members

Source: Policy Board, Bank of Japan

https://www.boj.or.jp/en/announcements/release_2015/k150121a.pdf

https://www.boj.or.jp/en/announcements/release_2014/k140715a.pdf

https://www.boj.or.jp/en/mopo/outlook/gor1504b.pdf

The Markit/JMMA Flash Japan Manufacturing PMI Index™ with the Flash Japan

Manufacturing PMI™ decreased from 50.9 in May to 49.9 in Jun and the Flash Japan

Manufacturing Output Index™ decreased from 51.9 in May to 50.5 in Jun

(http://www.markiteconomics.com/Survey/PressRelease.mvc/045fa40d96bc4a1785747ed6601

cf1). New export orders increased at faster pace. Amy Brownbill, Economist at

Markit, finds slightly weaker conditions in Japan’s manufacturing with exports responding to

exchange rate depreciation

(http://www.markiteconomics.com/Survey/PressRelease.mvc/045fa40d96bc4a1785747ed6601

cf1).

The Nikkei Composite Output PMI Index decreased from 51.6 in May to 51.5 in Jun, indicating

improving business activity

(http://www.markiteconomics.com/Survey/PressRelease.mvc/459a8f600cce4436b7a5e71073543df1).

The Nikkei Business Activity Index of Services increased to 51.8 in Jun from 51.5 in May (http://www.markiteconomics.com/Survey/PressRelease.mvc/459a8f600cce4436b7a5e71073543df1). Amy Brownbill, Ecoomist at Markit and author of the report, finds improved conditions with strengthening business expectations (http://www.markiteconomics.com/Survey/PressRelease.mvc/459a8f600cce4436b7a5e71073543df1). The Nikkei Purchasing Managers’ Index (PMI™), seasonally adjusted, decreased from 50.9 in May to 50.1 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/fcead8f7fe0f464391e3bcf2e748f75d). New orders decreased while growth of foreign orders continued. Amy Brownbill, Economist at Markit, finds manufacturing benefitting from strong growth of foreign orders with devaluation of the yen (http://www.markiteconomics.com/Survey/PressRelease.mvc/fcead8f7fe0f464391e3bcf2e748f75d).Table JPY provides the country data table for Japan.

Table JPY, Japan, Economic Indicators

Historical GDP and CPI

1981-2010 Real GDP Growth and CPI Inflation 1981-2010
Blog 8/9/11 Table 26

Corporate Goods Prices

May ∆% 0.3
12 months ∆% -2.1
Blog 6/14/15

Consumer Price Index

May NSA ∆% 0.3; May 12 months NSA ∆% 0.5
Blog 6/28/15

Real GDP Growth

IQ2015 ∆%: 1.0 on IVQ2014;  IVQ2014 SAAR 3.9;
∆% from quarter a year earlier: -0.9 %
Blog 6/16/13 8/18/13 9/15/13 11/17/13 12/15/13 2/23/14 3/16/14 5/18/14 6/15/14 8/17/14 9/14/14 11/23/14 12/14/14 2/22/15 3/15/15 5/24/15 6/14/15

Employment Report

May Unemployed 2.24 million

Change in unemployed since last year: minus 180 thousand
Unemployment rate: 3.3 %
Blog 6/28/15

All Industry Indices

Apr month SA ∆% 0.1
12-month NSA ∆% 1.3

Earlier Data:

Blog 4/26/15

Industrial Production

May SA month ∆%: -2.2 Apr 1.2
May 12-month NSA ∆% -4.0 Apr 0.1

Earlier Data:
Blog 3/29/15

Machine Orders

Total Apr ∆% -1.1

Private ∆%: -16.5 Apr ∆% Excluding Volatile Orders minus 3.8

Earlier Data:
Blog 4/19/15

Tertiary Index

Apr month SA ∆% -0.2
Apr 12 months NSA ∆% minus -2.0

Earlier Data:
Blog 4/26/15

Wholesale and Retail Sales

May 12 months:
Total ∆%: -2.0
Wholesale ∆%: -4.2
Retail ∆%: 3.0

Earlier Data:
Blog 3/29/15

Family Income and Expenditure Survey

May 12-month ∆% total nominal consumption 5.5, real -4.8

Earlier Data:

Blog 3/29/15

Trade Balance

Exports May 12 months ∆%: 2.4 Imports May 12 months ∆% -8.7

Earlier Data:

Blog 4/26/15

Links to blog comments in Table JPY:

6/28/2015 http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html

6/14/15 http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html

5/24/15 http://cmpassocregulationblog.blogspot.com/2015/05/interest-rate-policy-and-dollar.html

4/26/2015 http://cmpassocregulationblog.blogspot.com/2015/04/imf-view-of-economy-and-finance-united.html

4/19/2015 http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html

3/29/15 http://cmpassocregulationblog.blogspot.com/2015/03/dollar-revaluation-and-financial-risk.html

2/22/15 http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html

12/14/14 http://cmpassocregulationblog.blogspot.com/2014/12/global-financial-and-economic-risk.html

11/23/14 http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.htm

9/14/14 http://cmpassocregulationblog.blogspot.com/2014/09/geopolitics-monetary-policy-and.html

8/17/2014 http://cmpassocregulationblog.blogspot.com/2014/08/weakening-world-economic-growth.html

6/15/2014 http://cmpassocregulationblog.blogspot.com/2014/06/financialgeopolitical-risks-recovery.html

5/18/14 http://cmpassocregulationblog.blogspot.com/2014/05/world-inflation-waves-squeeze-of.html

3/16/2014 http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html

2/23/14 http://cmpassocregulationblog.blogspot.com/2014/02/squeeze-of-economic-activity-by-carry.html

12/15/13 http://cmpassocregulationblog.blogspot.com/2013/12/theory-and-reality-of-secular.html

11/17/13 http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-unwinding-monetary-policy.html

9/15/13 http://cmpassocregulationblog.blogspot.com/2013/09/recovery-without-hiring-ten-million.html

8/18/13 http://cmpassocregulationblog.blogspot.com/2013/08/duration-dumping-and-peaking-valuations.html

VC China. China estimates an index of nonmanufacturing purchasing managers based on a sample of 1200 nonmanufacturing enterprises across the country (http://www.stats.gov.cn/english/pressrelease/t20121009_402841094.htm). Table CIPMNM provides this index and components. The total index increased from 55.7 in Jan 2011 to 58.0 in Mar 2012, decreasing to 53.9 in Aug 2013. The index decreased from 56.0 in Nov 2013 to 54.6 in Dec 2013, easing to 53.4 in Jan 2014. The index moved to 53.8 in Jun 2015. The index of new orders increased from 52.2 in Jan 2012 to 54.3 in Dec 2012 but fell to 50.1 in May 2013, barely above the neutral frontier of 50.0. The index of new orders stabilized at 51.0 in Nov-Dec 2013, easing to 50.9 in Jan 2014. The index of new orders moved to 51.3 in Jun 2015.

Table CIPMNM, China, Nonmanufacturing Index of Purchasing Managers, %, Seasonally Adjusted

 

Total Index

New Orders

Interm.
Input Prices

Subs Prices

Exp

Jun 2015

53.8

51.3

50.6

48.7

59.7

May

53.2

49.5

52.8

50.4

60.1

Apr

53.4

49.1

50.8

48.9

60.0

Mar

53.7

50.3

50.0

48.4

58.8

Feb

53.9

51.2

52.5

51.2

58.7

Jan

53.7

50.2

47.6

46.9

59.6

Dec 2014

54.1

50.5

50.1

47.3

59.5

Nov

53.9

50.1

50.6

47.7

59.7

Oct

53.8

51.0

52.0

48.8

59.9

Sep

54.0

49.5

49.8

47.3

60.9

Aug

54.4

50.0

52.2

48.3

61.2

Jul

54.2

50.7

53.4

49.5

61.5

Jun

55.0

50.7

56.0

50.8

60.4

May

55.5

52.7

54.5

49.0

60.7

Apr

54.8

50.8

52.4

49.4

61.5

Mar

54.5

50.8

52.8

49.5

61.5

Feb

55.0

51.4

52.1

49.0

59.9

Jan

53.4

50.9

54.5

50.1

58.1

Dec 2013

54.6

51.0

56.9

52.0

58.7

Nov

56.0

51.0

54.8

49.5

61.3

Oct

56.3

51.6

56.1

51.4

60.5

Sep

55.4

53.4

56.7

50.6

60.1

Aug

53.9

50.9

57.1

51.2

62.9

Jul

54.1

50.3

58.2

52.4

63.9

Jun

53.9

50.3

55.0

50.6

61.8

May

54.3

50.1

54.4

50.7

62.9

Apr

54.5

50.9

51.1

47.6

62.5

Mar

55.6

52.0

55.3

50.0

62.4

Feb

54.5

51.8

56.2

51.1

62.7

Jan

56.2

53.7

58.2

50.9

61.4

Dec 2012

56.1

54.3

53.8

50.0

64.6

Nov

55.6

53.2

52.5

48.4

64.6

Oct

55.5

51.6

58.1

50.5

63.4

Sep

53.7

51.8

57.5

51.3

60.9

Aug

56.3

52.7

57.6

51.2

63.2

Jul

55.6

53.2

49.7

48.7

63.9

Jun

56.7

53.7

52.1

48.6

65.5

May

55.2

52.5

53.6

48.5

65.4

Apr

56.1

52.7

57.9

50.3

66.1

Mar

58.0

53.5

60.2

52.0

66.6

Feb

57.3

52.7

59.0

51.2

63.8

Jan

55.7

52.2

58.2

51.1

65.3

Notes: Interm.: Intermediate; Subs: Subscription; Exp: Business Expectations

Source: National Bureau of Statistics of China

http://www.stats.gov.cn/english/

Chart CIPMNM provides China’s nonmanufacturing purchasing managers’ index. The index fell from 56.0 in Oct 2013 to 53.8 in Jun 2015.

Chart CIPMNMW020150701529448881921_r75

Chart CIPMNM, China, Nonmanufacturing Index of Purchasing Managers, Seasonally Adjusted

Source: National Bureau of Statistics of China

http://www.stats.gov.cn/english

Table CIPMMFG provides the index of purchasing managers of manufacturing seasonally adjusted of the National Bureau of Statistics of China. The general index (IPM) rose from 50.5 in Jan 2012 to 53.3 in Apr 2012, falling to 49.2 in Aug 2012, rebounding to 50.6 in Dec 2012. The index fell to 50.1 in Jun 2013, barely above the neutral frontier at 50.0, recovering to 51.4 in Nov 2013 but falling to 51.0 in Dec 2013. The index fell to 50.5 in Jan 2014, 50.1 in Dec 2014 and 50.2 in Jun 2015. The index of new orders fell from 54.5 in Apr 2012 to 51.2 in Dec 2012. The index of new orders fell from 52.3 in Nov 2013 to 52.0 in Dec 2013. The index fell to 50.9 in Jan 2014 and moved to 50.4 in Dec 2014. The index moved to 50.1 in Jun 2015.

Table CIPMMFG, China, Manufacturing Index of Purchasing Managers, %, Seasonally Adjusted

 

IPM

PI

NOI

INV

EMP

SDEL

2015

           

Jun

50.2

52.9

50.1

48.7

48.1

50.3

May

50.2

52.9

50.6

48.2

48.2

50.9

Apr

50.1

52.6

50.2

48.2

48.0

50.4

Mar

50.1

52.1

50.2

48.0

48.4

50.1

Feb

49.9

51.4

50.4

48.2

47.8

49.9

Jan

49.8

51.7

50.2

47.3

47.9

50.2

2014

           

Dec

50.1

52.2

50.4

47.5

48.1

49.9

Nov

50.3

52.5

50.9

47.7

48.2

50.3

Oct

50.8

53.1

51.6

48.4

48.4

50.1

Sep

51.1

53.6

52.2

48.8

48.2

50.1

Aug

51.1

53.2

52.5

48.6

48.2

50.0

Jul

51.7

54.2

53.6

49.0

48.3

50.2

Jun

51.0

53.0

52.8

48.0

48.6

50.5

May

50.8

52.8

52.3

48.0

48.2

50.3

Apr

50.4

52.5

51.2

48.1

48.3

50.1

Mar

50.3

52.7

50.6

47.8

48.3

49.8

Feb

50.2

52.6

50.5

47.4

48.0

49.9

Jan

50.5

53.0

50.9

47.8

48.2

49.8

Dec 2013

51.0

53.9

52.0

47.6

48.7

50.5

Nov

51.4

54.5

52.3

47.8

49.6

50.6

Oct

51.4

54.4

52.5

48.6

49.2

50.8

Sep

51.1

52.9

52.8

48.5

49.1

50.8

Aug

51.0

52.6

52.4

48.0

49.3

50.4

Jul

50.3

52.4

50.6

47.6

49.1

50.1

Jun

50.1

52.0

50.4

47.4

48.7

50.3

May

50.8

53.3

51.8

47.6

48.8

50.8

Apr

50.6

52.6

51.7

47.5

49.0

50.8

Mar

50.9

52.7

52.3

47.5

49.8

51.1

Feb

50.1

51.2

50.1

49.5

47.6

48.3

Jan

50.4

51.3

51.6

50.1

47.8

50.0

Dec 2012

50.6

52.0

51.2

47.3

49.0

48.8

Nov

50.6

52.5

51.2

47.9

48.7

49.9

Oct

50.2

52.1

50.4

47.3

49.2

50.1

Sep

49.8

51.3

49.8

47.0

48.9

49.5

Aug

49.2

50.9

48.7

45.1

49.1

50.0

Jul

50.1

51.8

49.0

48.5

49.5

49.0

Jun

50.2

52.0

49.2

48.2

49.7

49.1

May

50.4

52.9

49.8

45.1

50.5

49.0

Apr

53.3

57.2

54.5

48.5

51.0

49.6

Mar

53.1

55.2

55.1

49.5

51.0

48.9

Feb

51.0

53.8

51.0

48.8

49.5

50.3

Jan

50.5

53.6

50.4

49.7

47.1

49.7

IPM: Index of Purchasing Managers; PI: Production Index; NOI: New Orders Index; EMP: Employed Person Index; SDEL: Supplier Delivery Time Index

Source: National Bureau of Statistics of China

http://www.stats.gov.cn/english/

China estimates the manufacturing index of purchasing managers on the basis of a sample of 820 enterprises (http://www.stats.gov.cn/english/pressrelease/t20121009_402841094.htm). Chart CIPMMFG provides the manufacturing index of purchasing managers. The index fell to 50.1 in Jun 2013. The index decreased from 51.4 in Nov 2013 to 51.0 in Dec 2013. The index moved to 50.2 in Jun 2015.

Chart CIPMMFGW020150701526190813034_r75

Chart CIPMMFG, China, Manufacturing Index of Purchasing Managers, Seasonally Adjusted

Source: National Bureau of Statistics of China

http://www.stats.gov.cn/english/

Cumulative growth of China’s GDP in IQ2015 relative to the same period in 2014 was 7.0 percent, as shown in Table VC-GDP. Secondary industry accounts for 42.9 percent of cumulative GDP in IQ2015. In cumulative IQ2015, industry accounts for 38.0 percent of GDP and construction for 5.1 percent. Tertiary industry accounts for 51.6 percent of cumulative GDP in IQ2015 and primary industry for 5.5 percent. China’s growth strategy consisted of rapid increases in productivity in industry to absorb population from agriculture where incomes are lower (Pelaez and Pelaez, The Global Recession Risk (2007), 56-80). The strategy is shifting to lower growth rates with improvement in living standards. The bottom block of Table VC-GDP provides quarter-on-quarter growth rates of GDP and their annual equivalent. China’s GDP growth decelerated significantly from annual equivalent 10.4 percent in IIQ2011 to 7.4 percent in IVQ2011 and 5.7 percent in IQ2012, rebounding to 8.7 percent in IIQ2012, 8.2 percent in IIIQ2012 and 7.8 percent in IVQ2012. Annual equivalent growth in IQ2013 fell to 7.0 percent and to 7.4 percent in IIQ2013, rebounding to 9.5 percent in IIIQ2013. Annual equivalent growth was 7.4 percent in IVQ2013, declining to 6.6 percent in IQ2014 and increasing to 8.2 percent in IIQ2014. Annual equivalent growth slowed to 7.8 percent in IIIQ2014 and 6.1 percent in IVQ2014. Growth slowed to annual equivalent 5.3 percent in IQ2015.

Table VC-GDP, China, Quarterly Growth of GDP, Current CNY 100 Million and Inflation Adjusted ∆%

Cumulative GDP IVQ2014

Value Current CNY Billion

IQ2015 Year-on-Year Constant Prices ∆%

GDP

14,066.7

7.0

Primary Industry

777.0

3.2

  Farming

807.9

3.3

Secondary Industry

6,029.2

6.4

  Industry

5,345.2

6.1

  Construction

715.0

8.8

Tertiary Industry

7,260.5

7.9

  Transport, Storage, Post

707.2

5.5

  Wholesale, Retail Trades

1,346.0

5.8

  Accommodation and Restaurants

255.9

5.3

  Finance

1,366.9

15.9

  Real Estate

970.3

2.0

  Other

2,552.4

9.0

Growth in Quarter Relative to Prior Quarter

∆% on Prior Quarter

∆% Annual Equivalent

2015

   

IQ2015

1.3

5.3

2014

   

IVQ2014

1.5

6.1

IIIQ2014

1.9

7.8

IIQ2014

2.0

8.2

IQ2014

1.6

6.6

2013

   

IVQ2013

1.8

7.4

IIIQ2013

2.3

9.5

IIQ2013

1.8

7.4

IQ2013

1.7

7.0

2012

   

IVQ2012

1.9

7.8

IIIQ2012

2.0

8.2

IIQ2012

2.1

8.7

IQ2012

1.4

5.7

2011

   

IVQ2011

1.8

7.4

IIIQ2011

2.2

9.1

IIQ2011

2.5

10.4

IQ2011

2.3

9.5

Source: National Bureau of Statistics of China http://www.stats.gov.cn/english/

Cumulative growth of China’s GDP in IQ2015 relative to the same period in 2014 was 7.0 percent, as shown in Table VC-GDPA. Secondary industry accounts for 42.6 percent of cumulative GDP in IVQ2014. Secondary industry accounts for 42.9 percent of cumulative GDP in IQ2015. In cumulative IQ2015, industry accounts for 38.0 percent of GDP and construction for 5.1 percent. Tertiary industry accounts for 51.6 percent of cumulative GDP in IQ2015 and primary industry for 5.5 percent. China’s growth strategy consisted of rapid increases in productivity in industry to absorb population from agriculture where incomes are lower (Pelaez and Pelaez, The Global Recession Risk (2007), 56-80). The strategy is shifting to lower growth rates with improvement in living standards. GDP growth decelerated from 12.1 percent in IQ2010 and 11.2 percent in IIQ2010 to 7.8 percent in IQ2013, 7.5 percent in IIQ2013 and 7.9 percent in IIIQ2013. GDP grew 7.6 percent in IVQ2013 relative to a year earlier and 1.8 percent relative to IIIQ2013, which is equivalent to 7.4 percent per year. GDP grew 7.4 percent in IQ2014 relative to a year earlier and 1.6 percent in IQ2014 that is equivalent to 6.6 percent per year. GP grew 7.5 percent in IIQ2014 relative to a year earlier and 2.0 percent relative to the prior quarter, which is equivalent 8.2 percent. In IIIQ2014, GDP grew 7.3 percent relative to a year earlier and 1.9 percent relative to the prior quarter, which is 7.8 percent in annual equivalent. GDP grew 1.5 percent in IVQ2014, which is 6.1 percent in annual equivalent and 7.3 percent relative to a year earlier. In IQ2015, GDP grew 1.3 percent, which is equivalent in a year to a year earlier.

Table VC-GDPA, China, Growth Rate of GDP, ∆% Relative to a Year Earlier and ∆% Relative to Prior Quarter

 

IQ2015

             

GDP

7.0

             

Primary Industry

3.2

             

Secondary Industry

6.4

             

Tertiary Industry

7.9

             

GDP ∆% Relative to a Prior Quarter

1.3

             
 

IQ 2013

IIQ 2013

IIIQ 2013

IVQ 2013

IQ

2014

IIQ 2014

IIIQ 2014

IVQ

2014

GDP

7.8

7.5

7.9

7.6

7.4

7.5

7.3

7.3

Primary Industry

3.4

3.0

3.4

4.0

3.5

3.9

4.2

4.1

Secondary Industry

7.8

7.6

7.8

7.8

7.3

7.4

7.4

7.3

Tertiary Industry

8.3

8.3

8.4

8.3

7.1

8.0

7.9

8.1

GDP ∆% Relative to a Prior Quarter

1.7

1.8

2.3

1.8

1.6

2.0

1.9

1.5

 

IQ 2011

IIQ 2011

IIIQ 2011

IVQ 2011

IQ 

2012

IIQ 2012

IIIQ 2012

IVQ 2012

GDP

9.7

9.5

9.1

8.9

8.1

7.6

7.4

7.9

Primary Industry

3.5

3.2

3.8

4.5

3.8

4.3

4.2

4.5

Secondary Industry

11.1

11.0

10.8

10.6

9.1

8.3

8.1

8.1

Tertiary Industry

9.1

9.2

9.0

8.9

7.5

7.7

7.9

8.1

GDP ∆% Relative to a Prior Quarter

2.3

2.5

2.2

1.8

1.4

2.1

2.0

1.9

 

IQ 2010

IIQ 2010

IIIQ 2010

IVQ 2010

       

GDP

12.1

11.2

10.7

12.1

       

Primary Industry

3.8

3.6

4.0

3.8

       

Secondary Industry

14.5

13.3

12.6

14.5

       

Tertiary Industry

10.5

9.9

9.7

10.5

       

Source: National Bureau of Statistics of China http://www.stats.gov.cn/english/

Chart VC-GDP of the National Bureau of Statistics of China provides annual value and growth rates of GDP. China’s GDP growth in 2013 is still high at 7.7 percent but at the lowest rhythm in five years.

ChVC-GDPW020140224376367229279

Chart VC-GDP, China, Gross Domestic Product, Million Yuan and ∆%, 2009-2013

Source: National Bureau of Statistics of China http://www.stats.gov.cn/english/

Chart VC-FXR provides China’s foreign exchange reserves. FX reserves grew from $2399.2 billion in 2009 to $3821.3 billion in 2013 driven by high growth of China’s trade surplus.

ChVC-FXRW020140224376367389226

Chart VC-FXR, China, Foreign Exchange Reserves, 2009-2013

Source: National Bureau of Statistics of China http://www.stats.gov.cn/english

Chart VC-Trade provides China’s imports and exports. Exports exceeded imports with resulting large trade balance surpluses that increased foreign exchange reserves.

ChVC-TradeW020140224376367380700

Chart VC-Trade, China, Imports and Exports of Goods, 2009-2013, $100 Million US Dollars

Source: National Bureau of Statistics of China http://www.stats.gov.cn/english

The HSBC Flash China Manufacturing Purchasing Managers’ Index (PMI) compiled by Markit (http://www.markiteconomics.com/Survey/PressRelease.mvc/842ea43078214d80b7e3752f2d6d9dfb) is mixed. The overall Flash HSBC China Manufacturing PMI increased from 49.2 in May to 49.6 in Jun, while the Flash HSBC China Manufacturing Output Index increased from 49.3 in May to 50.0 in Jun, indicating moderate conditions. Exports orders indicate contraction. Annabel Fiddes, Economist at Markit, finds moderate expectations in manufacturing (http://www.markiteconomics.com/Survey/PressRelease.mvc/842ea43078214d80b7e3752f2d6d9dfb). The HSBC China Services PMI, compiled by Markit, shows the HSBC Composite Output, combining manufacturing and services, decreasing from 51.2 in May to 50.6 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/bd989d97f17c4938a20544de2ee6e995). Annabel Fiddes, Economist at Markit, finds challenging growth conditions (http://www.markiteconomics.com/Survey/PressRelease.mvc/bd989d97f17c4938a20544de2ee6e995). The HSBC China Services Business Activity index decreased from 53.5 in May to 51.8 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/bd989d97f17c4938a20544de2ee6e995). The HSBC Purchasing Managers’ Index (PMI), compiled by Markit, increased to 49.4 in Jun from 49.2 in May, indicating moderate deterioration in manufacturing (http://www.markiteconomics.com/Survey/PressRelease.mvc/7927d2e0c3304a4593285c6db50f3c21). New export orders increased. Annabel Fiddes, Economist at Markit, finds weak manufacturing in China. (http://www.markiteconomics.com/Survey/PressRelease.mvc/7927d2e0c3304a4593285c6db50f3c21). Table CNY provides the country data table for China.

Table CNY, China, Economic Indicators

Price Indexes for Industry

May 12-month ∆%: minus 4.6

May month ∆%: -0.1
Blog 6/14/15

Consumer Price Index

May 12-month ∆%: 1.2 May month ∆%: -0.2
Blog 6/14/15

Value Added of Industry

May month ∆%: 0.52

Jan-May 2015/Jan-Apr 2014 ∆%: 6.2

Earlier Data
Blog 4/19/15

GDP Growth Rate

Year IQ2015 ∆%: 7.0

First Quarter 2015 ∆%: 7.0
Quarter IQ2015 AE ∆%: 5.3
Blog 4/26/15

Investment in Fixed Assets

Total Jan-May 2015 ∆%: 11.4

Real estate development: 5.1

Earlier Data:
Blog 4/19/15

Retail Sales

Apr month ∆%: 0.81
Jan-Apr 12 month ∆%: NA

Jan-May ∆%: 10.4

Earlier Data:
Blog 4/19/15

Trade Balance

May balance $59.1 billion
Exports 12M ∆% -2.5
Imports 12M ∆% -17.6

Cumulative May 2015: $217.16 billion

Earlier Data:
Blog 4/19/15

Links to blog comments in Table CNY:

6/14/15 http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html

4/26/2015 http://cmpassocregulationblog.blogspot.com/2015/04/imf-view-of-economy-and-finance-united.html

4/19/2015 http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html

VD Euro Area. Using calendar and seasonally adjusted data (http://ec.europa.eu/eurostat), the GDP of the euro area (18 countries) fell 5.8 percent from the high pre-recession date on IQ2008 to the trough in IIQ2009 while the GDP of the euro area (19 countries) fell 5.8 percent. The GDP of the euro area (18 countries) increased 4.5 percent from IIIQ2009 to IQ2015 at the annual equivalent rate of 0.8 percent while that of the euro area (19 countries) increased 4.5 percent at the annual equivalent rate of 0.8 percent. The GDP of the euro area (18) countries in IQ2015 is lower by 1.5 percent relative to the pre-recession peak in IQ2008 and that of the euro area (19 countries) is lower by 1.5 percent relative to the pre-recession peak in IQ2008. The GDP of the euro area (18) countries increased at the average yearly rate of 2.3 percent from IQ1999 to IQ2008 while that of the euro area (19 countries) increased at 2.3 percent. Table VD-EUR provides yearly growth rates of the combined GDP of the members of the European Monetary Union (EMU) or euro area since 1999. Growth was very strong at 3.3 percent in 2006 and 3.1 percent in 2007. The global recession had strong impact with growth of only 0.5 percent in 2008 and decline of 4.5 percent in 2009. Recovery was at lower growth rates of 2.0 percent in 2010 and 1.6 percent in 2011. EUROSTAT estimates growth of GDP of the euro area of minus 0.8 percent in 2012 and minus 0.4 percent in 2013 but 0.9 percent in 2014.

Table VD-EUR, Euro Area, Yearly Percentage Change of Harmonized Index of Consumer Prices, Unemployment and GDP ∆%

Year

HICP ∆%

Unemployment
%

GDP ∆%

1999

1.2

9.7

2.9

2000

2.2

8.9

3.8

2001

2.4

8.3

2.1

2002

2.3

8.6

0.9

2003

2.1

9.1

0.7

2004

2.2

9.3

2.2

2005

2.2

9.1

1.7

2006

2.2

8.4

3.3

2007

2.2

7.5

3.1

2008

3.3

7.6

0.5

2009

0.3

9.6

-4.5

2010

1.6

10.2

2.0

2011

2.7

10.2

1.6

2012

2.5

11.4

-0.8

2013

1.3

12.0

-0.4

2014

0.4

11.6

0.9

http://ec.europa.eu/eurostat

http://ec.europa.eu/eurostat/data/database

The GDP of the euro area in 2013 in current US dollars in the dataset of the World Economic Outlook (WEO) of the International Monetary Fund (IMF) is $12,753.7 billion or 17.1 percent of world GDP of $74,699.3 billion (http://www.imf.org/external/pubs/ft/weo/2014/02/weodata/weoselgr.aspx). The sum of the GDP of France $2807.3 billion with the GDP of Germany of $3635.9 billion, Italy of $2071.9 billion and Spain $1358.7 billion is $9873.8 billion or 77.4 percent of total euro area GDP and 13.2 percent of World GDP. The four largest economies account for slightly more than three quarters of economic activity of the euro area. Table VD-EUR1 is constructed with the dataset of EUROSTAT, providing growth rates of the euro area as a whole and of the largest four economies of Germany, France, Italy and Spain annually from 1996 to 2014. The impact of the global recession on the overall euro area economy and on the four largest economies was quite strong. There was sharp contraction in 2009 and growth rates have not rebounded to earlier growth with exception of Germany in 2010 and 2011.

Table VD-EUR1, Euro Area, Real GDP Growth Rate, ∆%

 

Euro Area

Germany

France

Italy

Spain

2014

0.9

1.6

0.4

-0.4

1.4

2013

-0.4

0.1

0.3

-1.7

-1.2

2012

-0.8

0.4

0.3

-2.8

-2.1

2011

1.6

3.6

2.1

0.6

-0.6

2010

2.0

4.1

2.0

1.7

0.0

2009

-4.5

-5.6

-2.9

-5.5

-3.6

2008

0.5

1.1

0.2

-1.0

1.1

2007

3.1

3.3

2.4

1.5

3.8

2006

3.3

3.7

2.4

2.0

4.2

2005

1.7

0.7

1.6

0.9

3.7

2004

2.2

1.2

2.8

1.6

3.2

2003

0.7

-0.7

0.8

0.2

3.2

2002

0.9

0.0

1.1

0.3

2.9

2001

2.1

1.7

2.0

1.8

4.0

2000

3.8

3.0

3.9

3.7

5.3

1999

2.9

2.0

3.4

1.6

4.5

1998

2.9

2.0

3.6

1.4

4.3

1997

2.6

1.8

2.3

1.8

3.7

1996

1.6

0.8

1.4

1.3

2.7

Source: EUROSTAT

http://ec.europa.eu/eurostat

http://ec.europa.eu/eurostat/data/database

The Flash Eurozone PMI Composite Output Index of the Markit Flash Eurozone PMI®, combining activity in manufacturing and services, increased from 53.6 in May to 54.1 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/e190997dfc504ddd8e0c0461a283a6f2). Chris Williamson, Chief Economist at Markit, finds that the Markit Flash Eurozone PMI index suggests GDP growth at around 0.4 percent in IIQ2015 (http://www.markiteconomics.com/Survey/PressRelease.mvc/e190997dfc504ddd8e0c0461a283a6f2). The Markit Eurozone PMI® Composite Output Index, combining services and manufacturing activity with close association with GDP increased from 53.6 in May to 54.2 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/922091d4bc964115b6f6329575019744). Chris Williamson, Chief Economist at Markit, finds potential for growth of 0.4 percent in IIQ2015 (http://www.markiteconomics.com/Survey/PressRelease.mvc/922091d4bc964115b6f6329575019744). The Markit Eurozone Services Business Activity Index increased from 53.8 in May to 54.4 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/922091d4bc964115b6f6329575019744). The Markit Eurozone Manufacturing PMI® increased from 52.2 in May to 52.5 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/29a9c7cea226408aa040e7e49b430842). New export orders increased. Chris Williamson, Chief Economist at Markit, finds improvement of industrial growth in the euro area at a quarterly rate of 0.3 percent (http://www.markiteconomics.com/Survey/PressRelease.mvc/29a9c7cea226408aa040e7e49b430842). Table EUR provides the data table for the euro area.

Table EUR, Euro Area Economic Indicators

GDP

IQ2015 ∆% 0.4; IQ2015/IQ2014 ∆% 1.0 Blog 6/14/15

Unemployment 

May 2015: 11.1 % unemployment rate; May 2015: 17.726 million unemployed

Blog 7/5/15

HICP

May month ∆%: 0.2

12 months Apr ∆%: 0.3
Blog 6/21/15

Producer Prices

Euro Zone industrial producer prices May ∆%: 0.0
May 12-month ∆%: -2.0
Blog 7/5/15

Industrial Production

Apr Month ∆%: 0.1; 12 months ∆%: 1.8

Earlier Data:
Blog 4/19/15

Retail Sales

May month ∆%: 0.2
May 12 months ∆%: 2.4

Earlier Data:
Blog 3/15/15

Confidence and Economic Sentiment Indicator

Sentiment 105.5 Jun 2015

Consumer minus 3.3 Jun 2015

Earlier Data:

Blog 4/5/15

Trade

Jan-Apr 2015/Jan-Mar 2014 Exports ∆%: 6.0
Imports ∆%: 1.0

Apr 2015 12-month Exports ∆% 8.8 Imports ∆% 3.0

Earlier Data:
Blog 4/19/15

Links to blog comments in Table EUR:

6/21/15 http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html

6/14/15 http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html

4/19/2015 http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html

4/5/15 http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html

3/15/15 http://cmpassocregulationblog.blogspot.com/2015/03/global-exchange-rate-struggle-recovery.html

EUROSTAT estimates the rate of unemployment in the euro area at 11.1 percent in

May 2015, as shown in Table VD-1. The number of unemployed in May 2015 was 17.726 million, which was 0.939 million lower than 18.665 million in May 2014. The rate of unemployment fell from 11.6 percent in May 2014 to 11.1 percent in May 2015.

Table VD-1, Euro Area, Unemployment Rate and Number of Unemployed, % and Millions, SA 

 

Unemployment Rate %

Number Unemployed
Millions

May 2015

11.1

17.726

Apr

11.1

17.761

Mar

11.2

17.902

Feb

11.2

17.954

Jan

11.3

18.066

Dec 2014

11.3

18.205

Nov

11.5

18.424

Oct

11.5

18.443

Sep

11.5

18.461

Aug

11.5

18.453

Jul

11.6

18.593

Jun

11.6

18.538

May

11.6

18.665

Apr

11.7

18.694

Mar

11.7

18.814

Feb

11.8

18.896

Jan

11.9

18.988

Dec 2013

11.9

18.960

Nov

11.9

19.033

Oct

11.9

19.090

Sep

12.0

19.240

Aug

12.0

19.252

Jul

12.0

19.259

Jun

12.1

19.311

May

12.1

19.334

Apr

12.1

19.328

Mar

12.0

19.270

Feb

12.0

19.264

Jan

12.0

19.219

Dec 2012

11.9

19.014

Nov

11.8

18.907

Oct

11.7

18.788

Sep

11.6

18.522

Aug

11.5

18.387

Jul

11.5

18.346

Jun

11.4

18.256

May

11.3

18.038

Apr

11.2

17.889

Mar

11.1

17.630

Feb

10.9

17.352

Jan

10.7

17.099

Dec 2011

10.7

17.038

Nov

10.6

16.899

Oct

10.5

16.632

Sep

10.4

16.488

Aug

10.2

16.260

Jul 

10.1

16.094

Jun

10.0

15.880

May

10.0

15.824

Apr

9.9

15.691

Mar

10.0

15.783

Feb

10.0

15.802

Jan

10.1

15.916

Dec 2010

10.1

15.994

Source: EUROSTAT

http://ec.europa.eu/eurostat

Table VD-2 shows the disparity in rates of unemployment in the euro area with 11.1 percent for the region as a whole and 17.726 million unemployed but 4.7 percent in Germany and 1.973 million unemployed. At the other extreme is Spain with rate of unemployment of 22.5 percent and 5.148 million unemployed. The rate of unemployment of the European Union in May 2015 is 9.6 percent with 23.348 million unemployed.

Table VD-2, Unemployed and Unemployment Rate in Countries and Regions, Millions and %

May 2015

Unemployment Rate %

Unemployed Millions

Euro Zone

11.1

17.726

Germany

4.7

1.973

France

10.3

3.012

Netherlands

6.9

0.617

Finland

9.4

0.252

Portugal

13.2

0.677

Ireland

9.8

0.210

Italy

12.4

3.157

Greece

25.6*

1.212*

Spain

22.5

5.148

Belgium

8.6

0.431

European Union

9.6

23.348

*Mar 2015

Source: EUROSTAT

http://ec.europa.eu/eurostat

Chart VD-1 of EUROSTAT illustrates the wide difference in rates of unemployment in countries and regions.

clip_image007

Chart VD-1, Unemployment Rate in Various Countries and Regions

Source: EUROSTAT

http://ec.europa.eu/eurostat

VE Germany. Table VE-DE provides yearly growth rates of the German economy from 1971 to 2014, price adjusted chain-linked and price and calendar-adjusted chain-linked. Germany’s GDP fell 5.6 percent in 2009 after growing below trend at 1.1 percent in 2008. Recovery has been robust in contrast with other advanced economies. The German economy grew at 4.1 percent in 2010, 3.6 percent in 2011 and 0.4 percent in 2012. Growth decelerated to 0.1 percent in 2013, increasing to 1.6 percent in 2014.

The Federal Statistical Agency of Germany analyzes the fall and recovery of the German economy (http://www.destatis.de/jetspeed/portal/cms/Sites/destatis/Internet/EN/Content/Statistics/VolkswirtschaftlicheGesamtrechnungen/Inlandsprodukt/Aktuell,templateId=renderPrint.psml):

“The German economy again grew strongly in 2011. The price-adjusted gross domestic product (GDP) increased by 3.0% compared with the previous year. Accordingly, the catching-up process of the German economy continued during the second year after the economic crisis. In the course of 2011, the price-adjusted GDP again exceeded its pre-crisis level. The economic recovery occurred mainly in the first half of 2011. In 2009, Germany experienced the most serious post-war recession, when GDP suffered a historic decline of 5.1%. The year 2010 was characterised by a rapid economic recovery (+3.7%).”

Table VE-DE, Germany, GDP ∆% on Prior Year

 

Price Adjusted Chain-Linked

Price- and Calendar-Adjusted Chain Linked

Average ∆% 1991-2014

1.3

 

Average ∆% 1991-1999

1.5

 

Average ∆% 2000-2007

1.4

 

Average ∆% 2003-2007

2.2

 

Average ∆% 2007-2014

0.7

 

Average ∆% 2009-2014

1.9

 

2014

1.6

1.6

2013

0.1

0.2

2012

0.4

0.6

2011

3.6

3.7

2010

4.1

3.9

2009

-5.6

-5.6

2008

1.1

0.8

2007

3.3

3.4

2006

3.7

3.9

2005

0.7

0.9

2004

1.2

0.7

2003

-0.7

-0.7

2002

0.0

0.0

2001

1.7

1.8

2000

3.0

3.2

1999

2.0

1.9

1998

2.0

1.7

1997

1.8

1.9

1996

0.8

0.8

1995

1.7

1.8

1994

2.5

2.5

1993

-1.0

-1.0

1992

1.9

1.5

1991

5.1

5.2

1990

5.3

5.5

1989

3.9

4.1

1988

3.7

3.4

1987

1.4

1.3

1986

2.3

2.3

1985

2.3

2.6

1984

2.8

2.9

1983

1.6

1.5

1982

-0.4

-0.5

1981

0.5

0.6

1980

1.4

1.3

1979

4.2

4.3

1978

3.0

3.1

1977

3.3

3.5

1976

4.9

4.5

1975

-0.9

-0.9

1974

0.9

1.0

1973

4.8

5.0

1972

4.3

4.3

1971

3.1

3.0

1970

NA

NA

Source: Statistisches Bundesamt Deutschland (Destatis)

https://www.destatis.de/EN/FactsFigures/NationalEconomyEnvironment/NationalAccounts/NationalAccounts.html

https://www.destatis.de/EN/FactsFigures/NationalEconomyEnvironment/NationalAccounts/DomesticProduct/CurrentRevision.html

https://www.destatis.de/EN/Methods/NationalAccountRevision/Revision2014_BackgroundPaper.pdf?__blob=publicationFile

https://www.destatis.de/EN/PressServices/Press/pr/2014/02/PE14_048_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2013/08/PE13_278_811.html https://www.destatis.de/EN/PressServices/Press/pr/2013/11/PE13_381_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2014/01/PE14_016_811.html

https://www.destatis.de/DE/PresseService/Presse/Pressekonferenzen/2014/BIP2013/Pressebroschuere_BIP2013.html

https://www.destatis.de/EN/PressServices/Press/pr/2014/05/PE14_167_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2014/09/PE14_306_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2014/11/PE14_401_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2015/02/PE15_048_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2015/02/PE15_61_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2015/05/PE15_173_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2015/05/PE15_187_811.html

https://www.destatis.de/EN/FactsFigures/NationalEconomyEnvironment/NationalAccounts/DomesticProduct/DomesticProduct.html

The Flash Germany Composite Output Index of the Markit Flash Germany PMI®, combining manufacturing and services, increased from 52.6 in May to 54.0 in Jun. The index of manufacturing output reached 3.5 in Jun, increasing from 53.5 in May, while the index of services increased to 54.2 in Jun from 53.0 in May. The overall Flash Germany Manufacturing PMI® increased from 51.1 in May to 51.9 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/10ba8c8e0d9a4c93ad7d6772cf4b5cdd). New orders in manufacturing expanded. Oliver Kolodseike, Economist at Markit, finds continuing GDP growth at similar rate (http://www.markiteconomics.com/Survey/PressRelease.mvc/10ba8c8e0d9a4c93ad7d6772cf4b5cdd). The Markit Germany Composite Output Index of the Markit Germany Services PMI®, combining manufacturing and services with close association with Germany’s GDP, increased from 52.6 in May to 53.7 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/87e5213c90484f9189266b50fd267b33). Oliver Kolodseike, Economist at Markit and author of the report, finds slowing improvement in 2015 (http://www.markiteconomics.com/Survey/PressRelease.mvc/87e5213c90484f9189266b50fd267b33). The Germany Services Business Activity Index increased from 53.0 in May to 53.3 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/87e5213c90484f9189266b50fd267b33). The Markit/BME Germany Purchasing Managers’ Index® (PMI®), showing close association with Germany’s manufacturing conditions, increased from 51.1 in May to 51.9 in

Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/e0f406c95af54c3c9895dc2cd120d783). New export orders increased. Oliver Kolodseike, Senior Economist at Markit and author of the report, finds accelerating growth of manufacturing (http://www.markiteconomics.com/Survey/PressRelease.mvc/e0f406c95af54c3c9895dc2cd120d783).Table DE provides the country data table for Germany.

Table DE, Germany, Economic Indicators

GDP

IQ2015 0.3 ∆%; IQ2015/IQ2014 ∆% 1.1

2014/2013: 1.6%

GDP ∆% 1970-2014

Blog 8/26/12 5/27/12 11/25/12 2/24/13 5/19/13 5/26/13 8/18/13 8/25/13 11/17/13 11/24/13 1/26/14 2/16/14 3/2/14 5/18/14 5/25/14 8/17/14 9/7/14 11/16/14 11/30/14 2/15/15 3/1/15 5/17/15 5/24/15

Consumer Price Index

May month NSA ∆%: 0.1
May 12-month NSA ∆%: 0.7
Blog 6/21/15

Producer Price Index

May month ∆%: 0.0 NSA, 0.0 CSA
12-month NSA ∆%: -1.3
Blog 6/21/15

Industrial Production

MFG Apr month CSA ∆%: 0.8
12-month NSA: 0.6

Earlier Data:
Blog 4/12/15

Machine Orders

MFG Apr month ∆%: 1.4
Apr 12-month ∆%: 0.5

Earlier Data:
Blog 4/12/15

Retail Sales

May Month ∆% 0.5 Apr 1.3

12-Month May ∆% -0.4 Apr 1.1

Earlier Data:

Blog 4/5/15

Employment Report

Unemployment Rate SA Apr 4.7%
Blog 7/5/15

Trade Balance

Exports Apr 12-month NSA ∆%: 7.5
Imports Apr 12 months NSA ∆%: 2.8
Exports Apr month CSA ∆%: 1.9; Imports Apr month CSA -1.3

Earlier Data:

Blog 4/12/15

Links to blog comments in Table DE:

6/21/15 http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html

5/24/15 http://cmpassocregulationblog.blogspot.com/2015/05/interest-rate-policy-and-dollar.html

5/17/15 http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html

4/12/15 http://cmpassocregulationblog.blogspot.com/2015/04/dollar-revaluation-recovery-without.html

4/5/15 http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html

3/1/15 http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html

2/15/15 http://cmpassocregulationblog.blogspot.com/2015/02/g20-monetary-policy-recovery-without.html

11/30/14 http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html

11/16/14 http://cmpassocregulationblog.blogspot.com/2014/11/fluctuating-financial-variables.html

9/7/14 http://cmpassocregulationblog.blogspot.com/2014/09/competitive-monetary-policy-and.html

8/17/2014 http://cmpassocregulationblog.blogspot.com/2014/08/weakening-world-economic-growth.html

5/25/14 http://cmpassocregulationblog.blogspot.com/2014/05/united-states-commercial-banks-assets.html

5/18/14 http://cmpassocregulationblog.blogspot.com/2014/05/world-inflation-waves-squeeze-of.html

3/2/14 http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html

2/16/14 http://cmpassocregulationblog.blogspot.com/2014/02/theory-and-reality-of-cyclical-slow.html

1/26/14 http://cmpassocregulationblog.blogspot.com/2014/01/capital-flows-exchange-rates-and.html

11/24/13 http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-zero-interest-rates-world.html

11/17/13 http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-unwinding-monetary-policy.html

8/25/13 http://cmpassocregulationblog.blogspot.com/2013/08/interest-rate-risks-duration-dumping.html

8/18/13 http://cmpassocregulationblog.blogspot.com/2013/08/duration-dumping-and-peaking-valuations.html

Germany’s labor market continues to show strength not found in most of the advanced economies, as shown in Table VE-1A. The number unemployed, not seasonally adjusted, decreased from 2.00 million in May 2014 to 1.90 million in May 2015, or 5.0 percent, while the unemployment rate decreased from 4.8 percent in May 2014 to 4.6 percent in May 2015. The number of persons in employment, not seasonally adjusted, decreased from 39.86 million in May 2014 to 39.70 million in May 2015, or 0.4 percent, while the employment rate decreased from 65.0 percent in May 2014 to 64.5 percent in May 2015. The number unemployed, seasonally adjusted, decreased from 1.98 million in Apr 2015 to 1.97 million in May 2015, while the unemployment rate did not change from 4.7 percent in Apr 2015 to 4.7 percent in May 2015. The number of persons in employment, seasonally adjusted, did not change from 39.89 million in Apr 2015 to 39.88 million in May 2015, or change of 0.0 percent. The employment rate seasonally adjusted did not change from 64.8 in Apr 2015 to 64.8 in May 2015.

Table VE-1A, Germany, Unemployment Labor Force Survey

 

May 2015

Apr 2015

May 2014

NSA

     

Number
Unemployed Millions

1.90

∆% May 2015 /Apr 2015: -6.9

∆% May 2015/May 2014: -5.0

2.04

2.00

% Rate Unemployed

4.6

4.9

4.8

Persons in Employment Millions

39.70

∆% May 2015/ Apr 2015: 0.2

∆% May 2015/May 2014: -0.4

39.61

39.86

Employment Rate

64.5

64.4

65.0

SA

     

Number
Unemployed Millions

1.97

∆% May 2015/ Apr  2015: -0.5

∆% May 2015/May 2014: –5.7

1.98

2.09

% Rate Unemployed

4.7

4.7

5.0

Persons in Employment Millions

39.88

∆% May 2015/ Apr 2015: 0.0

∆% May 2015/May 2014: 0.4

39.89

39.74

Employment Rate

64.8

64.8

64.8

NSA: not seasonally adjusted; SA: seasonally adjusted

Source: Statistisches Bundesamt Deutschland

https://www.destatis.de/EN/PressServices/Press/pr/2015/06/PE15_240_132.html

The unemployment rate in Germany as percent of the labor force in Table VE-2A stood at 6.5 percent in Sep, Oct and Nov 2012, increasing to 6.7 percent in Dec 2012, 7.4 percent in Jan 2013, 7.3 in Mar 2013 and 7.1 percent in Apr 2013. The unemployment rate fell to 6.8 percent in May 2013 and 6.6 percent in Jun 2013 and rose to 6.8 percent in Jul-Aug 2013. The rate fell to 6.6 percent in Sep 2013 and 6.5 percent in Oct 2013 and Nov 2013. The unemployment rate increased to 6.7 percent in Dec 2013 and 7.3 percent in Jan 2013. The unemployment rate reached 7.3 percent in Feb 2014 and 7.1 percent in Mar 2014. The unemployment rate fell to 6.8 percent in Apr 2014 and 6.6 percent in May 2014. The unemployment rate fell to 6.5 percent in Jun 2014, increasing to 6.6 percent in Jun 2014 and 6.7 percent in Aug 2014. The unemployment rate fell to 6.5 percent in Sep 2014 and 6.3 percent in Oct 2014 and Nov 2014. The unemployment rate increase to 6.4 percent in Dec 2014 and 7.0 percent in Jan 2015, falling to 6.9 percent in Feb 2015 and 6.5 percent in Apr 2015. The unemployment rate fell to 6.3 percent in May 2015 and 6.2 percent in Jun 2015. The rate is much lower than 11.1 percent in 2005 and 9.6 percent in 2006.

Table VE-2A, Germany, Unemployment Rate in Percent of Labor Force

Jun 2015

6.2

May

6.3

Apr

6.5

Mar

6.8

Feb

6.9

Jan

7.0

Dec 2014

6.4

Nov

6.3

Oct

6.3

Sep

6.5

Aug

6.7

Jul

6.6

Jun

6.5

May

6.6

Apr

6.8

Mar

7.1

Feb

7.3

Jan

7.3

Dec 2013

6.7

Nov

6.5

Oct

6.5

Sep

6.6

Aug

6.8

Jul

6.8

Jun

6.6

May

6.8

Apr

7.1

Mar

7.3

Feb

7.4

Jan

7.4

Dec 2012

6.7

Nov

6.5

Oct

6.5

Sep

6.5

Aug

6.8

Jul

6.8

Jun

6.6

May

6.7

Apr

7.0

Mar

7.2

Feb

7.4

Jan

7.3

Dec 2011

6.6

Nov

6.4

Oct

6.5

Sep

6.6

Aug

7.0

Jul

7.0

Jun

6.9

May

7.0

Apr

7.3

Mar

7.6

Feb

7.9

Jan

7.9

Dec 2010

7.1

Dec 2009

7.8

Dec 2008

7.4

Dec 2007

8.1

Dec 2006

9.6

Dec 2005

11.1

Source: Statistisches Bundesamt Deutschland

https://www.destatis.de/EN/FactsFigures/Indicators/ShortTermIndicators/ShortTermIndicators.html

Chart VE-1A of Statistisches Bundesamt Deutschland, or Federal Statistical Office of Germany, shows the long-term decline of the rate of unemployment in Germany from more than 12 percent in early 2005 to 6.6 percent in Dec 2011, increasing to 6.7 percent in Dec 2012, 6.8 percent in Apr 2013 and 6.6 percent in May 2013. The unemployment rate rose slightly to 6.8 percent in Aug 2013, falling to 6.6 percent in Sep 2013 and 6.5 percent in Oct 2013. The rate remained at 6.5 percent in Nov 2013, increasing to 6.7 percent in Dec 2013 and 7.3 in Jan 2014. The rate remained at 7.3 percent in Feb 2014, declining to 7.1 percent in Mar 2014. The rate fell to 6.8 percent in Apr 2014, 6.6 percent in May 2014 and 6.5 percent in Jun 2014. The rate increased to 6.6 percent in Jul 2014 and 6.7 percent in Aug 2014, falling to 6.5 percent in Sep 2014. The rate fell to 6.3 percent in Oct 2014 and 6.3 percent in Nov 2014, increasing to 6.4 percent in Dec 2014. The rate increased to 7.0 percent in Jan 2015, falling to 6.9 percent in Feb 2015 and 6.8 percent in Mar 2015. The unemployment rate fell to 6.5 percent in Apr 2015 and 6.3 percent in May 2015. The unemployment rate fell to 6.2 percent in May 2015.

clip_image008

Chart VE-1A, Germany, Unemployment Rate, Unadjusted, Percent

Source: Statistisches Bundesamt Deutschland

https://www.destatis.de/EN/FactsFigures/Indicators/ShortTermIndicators/ShortTermIndicators.html

VF France. Table VF-FR provides growth rates of GDP of France with the estimates of Institut National de la Statistique et des Études Économiques (INSEE). The long-term rate of GDP growth of France from IVQ1949 to IVQ2014 is quite high at 3.2 percent. France’s growth rates were quite high in the four decades of the 1950s, 1960, 1970s and 1980s with an average growth rate of 4.0 percent compounding the average rates in the decades and discounting to one decade. The growth impulse diminished with 2.0 percent in the 1990s and 1.8 percent from 2000 to 2007. The average growth rate from 2000 to 2014, using fourth quarter data, is 1.0 percent because of the sharp impact of the global recession from IVQ2007 to IIQ2009. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in US fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in the G7 in Japan and France in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Lucas (2011May) compares growth of the G7 economies (US, UK, Japan, Germany, France, Italy and Canada) and Spain, finding that catch-up growth with earlier rates for the US and UK stalled in the 1970s.

Table VF-FR, France, Average Growth Rates of GDP Fourth Quarter, 1949-2014

Period

Average ∆%

1949-2014

3.2

2007-2015*

0.3

2007-2014

0.3

2000-2014

1.0

2000-2013

1.1

2000-2007

1.8

1990-1999

2.0

1980-1989

2.6

1970-1979

3.7

1960-1969

5.7

1950-1959

4.2

*IVQ2007 to IQ2015

Source: Institut National de la Statistique et des Études Économiques

http://www.insee.fr/en/themes/info-rapide.asp?id=28&date=20150624

The Markit Flash France Composite Output Index increased from 52.0 in May to 53.4 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/79afa07f182f43e3a59eb088e424a956). Jack Kennedy, Senior Economist at Markit and author of the report, finds continuing growth (http://www.markiteconomics.com/Survey/PressRelease.mvc/79afa07f182f43e3a59eb088e424a956). The Markit France Composite Output Index, combining services and manufacturing with close association with French GDP, increased from 52.0 in May to 53.3 in Jun, indicating expansion at faster pace (http://www.markiteconomics.com/Survey/PressRelease.mvc/33b630575b3d4d50b98a25af3b24b31a). Jack Kennedy, Senior Economist at Markit and author of the France Services PMI®, finds improving business activity and GDP performance (http://www.markiteconomics.com/Survey/PressRelease.mvc/33b630575b3d4d50b98a25af3b24b31a). The Markit France Services Activity index increased from 52.8 in May to 54.1 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/33b630575b3d4d50b98a25af3b24b31a). The Markit France Manufacturing Purchasing Managers’ Index® increased to 50.7 in Jun from 49.4 in May (http://www.markiteconomics.com/Survey/PressRelease.mvc/5afa0d2c44ca4c3cbbfc5f2871494740). Jack Kennedy, Senior Economist at Markit and author of the France Manufacturing PMI®, finds stabilizing manufacturing (http://www.markiteconomics.com/Survey/PressRelease.mvc/5afa0d2c44ca4c3cbbfc5f2871494740). Table FR provides the country data table for France.

Table FR, France, Economic Indicators

CPI

May month ∆% 0.2
12 months ∆%: 0.3
6/14/15

PPI

May month ∆%: -0.6
May 12 months ∆%: -1.7

Blog 7/5/15

GDP Growth

IQ2015/IVQ2014 ∆%: 0.6
IQ2015/IQ2014 ∆%: 0.8
Blog 3/31/13 5/19/12 6/30/13 9/29/13 11/17/13 12/29/13 2/16/14 4/6/14 5/18/14 6/29/14 8/17/14 9/28/14 11/16/14 12/28/14 2/15/15 3/29/15 5/17/15 6/28/15

Industrial Production

Apr ∆%:
Manufacturing -1.0 12-Month ∆%: 0.2

Earlier Data:
Blog 4/12/15

Consumer Spending

Manufactured Goods
May ∆%: 0.0 May 12-Month Manufactured Goods
∆%: 2.6

Earlier Data:
Blog 4/5/15

Employment

Unemployment Rate: IQ2014 10.0%
Blog 6/7/15

Trade Balance

Apr Exports ∆%: month 1.4, 12 months 6.5

Imports ∆%: month -2.1, 12 months 2.6

Earlier Data:

Blog 4/12/15

Confidence Indicators

Historical average 100

Jun Mfg Business Climate 100.0

Earlier Data:

Blog 3/29/15

Links to blog comments in Table FR:

6/28/2015 http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html

6/14/15 http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html

6/7/15 http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html

5/17/15 http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html

4/12/15 http://cmpassocregulationblog.blogspot.com/2015/04/dollar-revaluation-recovery-without.html

4/5/15 http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html

3/29/15 http://cmpassocregulationblog.blogspot.com/2015/03/dollar-revaluation-and-financial-risk.html

2/15/15 http://cmpassocregulationblog.blogspot.com/2015/02/g20-monetary-policy-recovery-without.html

12/28/14 http://cmpassocregulationblog.blogspot.com/2014/12/valuations-of-risk-financial-assets.html

11/16/14 http://cmpassocregulationblog.blogspot.com/2014/11/fluctuating-financial-variables.html

9/28/14 http://cmpassocregulationblog.blogspot.com/2014/09/financial-volatility-mediocre-cyclical.html

8/17/2014 http://cmpassocregulationblog.blogspot.com/2014/08/weakening-world-economic-growth.html

6/29/14 http://cmpassocregulationblog.blogspot.com/2014/06/financial-indecision-mediocre-cyclical.html

5/18/14 http://cmpassocregulationblog.blogspot.com/2014/05/world-inflation-waves-squeeze-of.html

4/6/14 http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html

2/16/14 http://cmpassocregulationblog.blogspot.com/2014/02/theory-and-reality-of-cyclical-slow.html

12/29/13 http://cmpassocregulationblog.blogspot.com/2013/12/collapse-of-united-states-dynamism-of.html

11/17/13 http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-unwinding-monetary-policy.html

9/29/13 http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html

6/30/13 http://cmpassocregulationblog.blogspot.com/2013/06/tapering-quantitative-easing-policy-and.html

5/19/13 http://cmpassocregulationblog.blogspot.com/2013/05/word-inflation-waves-squeeze-of.html

The Markit/ADACI Business Activity Index decreased from 52.5 in May to 53.4 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/665f98f60f95426f8d849d33426360c1). Phil Smith, Economist at Markit and author of the Italy Services PMI®, finds signs of expansion of private sector activity with potential for growth higher than 0.3 percent in IIQ2015 (http://www.markiteconomics.com/Survey/PressRelease.mvc/665f98f60f95426f8d849d33426360c1). The Markit/ADACI Purchasing Managers’ Index® (PMI®), decreased from 54.8 in May to 54.1 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/28b19e1871e8470d8fd185ae9315393d). New export orders continued to increase. Phil Smith, Economist at Markit and author of the Italian Manufacturing PMI®, finds strengthening conditions in manufacturing (http://www.markiteconomics.com/Survey/PressRelease.mvc/28b19e1871e8470d8fd185ae9315393d). Table IT provides the country data table for Italy.

Table IT, Italy, Economic Indicators

Consumer Price Index

Jun month ∆%: 0.1
Jun 12-month ∆%: 0.1
Blog 7/5/15

Producer Price Index

May month ∆%: 0.2
May 12-month ∆%: -2.7

Blog 7/5/15

GDP Growth

IQ2015/IVQ2014 SA ∆%: 0.3
IQ2015/IQ2014 NSA ∆%: 0.1
Blog 3/17/13 6/16/13 8/11/13 9/15/13 11/17/13 12/15/13 2/16/14 3/16/14 5/18/14 6/15/14 8/10/14 8/31/14 10/19/14 11/16/14 12/7/14 2/15/15 3/15/15 5/17/15 5/31/15

Labor Report

May 2015

Participation rate 64.0%

Employment ratio 55.9%

Unemployment rate 12.4%

Youth Unemployment 41.5%

Blog 7/5/15

Industrial Production

Apr month ∆%: 0.3
12 months CA ∆%: 0.1

Earlier Data:
Blog 4/19/15

Retail Sales

Apr month ∆%: 0.7

Apr 12-month ∆%: 0.0

Earlier Data:

Blog 4/26/15

Business Confidence

Mfg Jun 103.9, Feb 100.4

Construction Jun 119.7, Feb 108.5

Earlier Data:

Blog 4/5/15

Trade Balance

Balance Apr SA €3523 million
Exports Apr month SA ∆%: -0.8; Imports month ∆%: 0.0
Exports 12 months Apr NSA ∆%: 4.6 Imports 12 months NSA ∆%: 4.0

Earlier Data:
Blog 4/19/15

Links to blog comments in Table IT:

5/31/15 http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html

5/17/15 http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html

4/26/2015 http://cmpassocregulationblog.blogspot.com/2015/04/imf-view-of-economy-and-finance-united.html

4/19/2015 http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html

4/5/15 http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html

3/15/15 http://cmpassocregulationblog.blogspot.com/2015/03/global-exchange-rate-struggle-recovery.html

2/15/15 http://cmpassocregulationblog.blogspot.com/2015/02/g20-monetary-policy-recovery-without.html

12/7/14 http://cmpassocregulationblog.blogspot.com/2014/12/financial-risks-twenty-six-million.html

11/16/14 http://cmpassocregulationblog.blogspot.com/2014/11/fluctuating-financial-variables.html

10/19/14 http://cmpassocregulationblog.blogspot.com/2014/10/imf-view-squeeze-of-economic-activity.html

8/31/14 http://cmpassocregulationblog.blogspot.com/2014/09/geopolitical-and-financial-risks.html

8/10/14 http://cmpassocregulationblog.blogspot.com/2014/08/volatility-of-valuations-of-risk_10.html

6/15/2014 http://cmpassocregulationblog.blogspot.com/2014/06/financialgeopolitical-risks-recovery.html

5/18/14 http://cmpassocregulationblog.blogspot.com/2014/05/world-inflation-waves-squeeze-of.html

3/16/2014 http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html

2/16/14 http://cmpassocregulationblog.blogspot.com/2014/02/theory-and-reality-of-cyclical-slow.html

12/15/13 http://cmpassocregulationblog.blogspot.com/2013/12/theory-and-reality-of-secular.html

11/17/13 http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-unwinding-monetary-policy.html

9/15/13 http://cmpassocregulationblog.blogspot.com/2013/09/recovery-without-hiring-ten-million.html

8/11/13 http://cmpassocregulationblog.blogspot.com/2013/08/recovery-without-hiring-loss-of-full.html

6/16/13 http://cmpassocregulationblog.blogspot.com/2013/06/recovery-without-hiring-seven-million.html

3/17/13 http://cmpassocregulationblog.blogspot.com/2013/03/recovery-without-hiring-ten-million.html

Data on Italy’s labor market since 2004 are provided in Table VG-1. The unemployment rate has risen from 6.2 percent in Dec 2006 to 12.4 percent in May 2015. The rate of youth unemployment for ages 15 to 24 years increased from 21.2 percent in Dec 2006 to 41.5 percent in May 2015. As in other advanced economies, unemployment has reached high levels.

Table VG-1, Italy, Labor Report

 

Participation Rate %

Employment Ratio %

Unemployment Rate %

Unemployment
Rate 15-24 Years %

May 2015

64.0

55.9

12.4

41.5

Apr

64.1

56.1

12.4

41.5

Mar

63.9

55.8

12.6

42.4

Feb

63.9

55.9

12.4

42.1

Jan

63.9

55.9

12.3

41.3

Dec 2014

63.9

55.8

12.4

41.0

Nov

64.1

55.6

13.0

42.9

Oct

64.2

55.8

12.8

42.1

Sep

64.2

55.8

12.8

42.0

Aug

63.9

55.7

12.6

43.1

Jul

64.0

55.7

12.8

42.9

Jun

63.9

55.8

12.4

42.5

May

63.8

55.6

12.6

42.4

Apr

63.5

55.4

12.5

43.0

Mar

63.8

55.7

12.5

43.8

Feb

63.6

55.4

12.7

42.9

Jan

63.6

55.4

12.8

43.4

Dec 2013

63.6

55.5

12.5

42.8

Dec 2012

63.5

56.1

11.4

38.1

Dec 2011

62.7

56.7

9.5

31.4

Dec 2010

61.9

56.8

8.1

28.4

Dec 2009

62.2

56.9

8.4

26.7

Dec 2008

62.5

58.2

6.8

23.1

Dec 2007

63.0

58.8

6.6

22.4

Dec 2006

62.4

58.5

6.2

21.2

Dec 2005

62.5

57.8

7.5

23.0

Dec 2004

62.4

57.5

7.8

23.7

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/163162

Table VG-2 provides more detail on the labor report for Italy in May 2015. The level of employment decreased 0.3 percent from Apr 2015 to May 2015 and increased 60,000 from May 2014 to May 2015. Unemployment decreased 1,000 in May 2015 and decreased 59,000 from a year earlier. A dramatic aspect found in most advanced economies is the high rate of unemployment of youth at 41.5 percent in May 2015 for ages 15 to 24 years.

Table VG-2, Italy, Labor Report, NSA

May 2015

1000s

Change from Prior Month 1000s

∆% from Prior Month

Change from Prior Year 1000s

∆% from Prior Year

EMP

22,330

-63

-0.3

60

0.3

UNE

3,157

-1

0.0

-59

-1.8

INA   15-64

14,050

36

0.3

-135

-0.9

EMP 15-24

893

-26

-2.8

-66

-6.9

UNE 15-24

632

20

-3.1

-74

-10.4

INA 15-24

4,420

43

1.0

106

2.5

EMP %

55.9

 

-0.1

 

0.1*

UNE %

12.4

 

0.0

 

0.1*

Youth UNE %  15-24

41.5

 

-0.1

 

0.3*

INA % 15-64

36.0

 

0.1

 

-0.2

Notes: EMP: Employed; UNE: Unemployed; INA 15-64: Inactive aged 15 to 64; EMP %: Employment Rate; UNE %: Unemployment Rate; Youth UNE % 15-24: Youth Unemployment Rate aged 15 to 24; INA % 15-64: Inactive Rate aged 15 to 64. *Percentage change from prior quarter to current quarter

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/163162

Chart VG-1 provides the rate of unemployment in Italy that decreased from 12.6 percent in May 2014 to 12.4 percent in May 2015.

clip_image009

Chart VG-1, Italy, Rate of Unemployment, %

Source: Istituto Nazionale di Statistica

http://www.istat.it/en/

Chart VG-2 of the Istituto Nazionale di Statistica provides the total number of employed persons in Italy. The level of employment increased from 22.270 million in May 2014 to 22.330 million in May 2015.

clip_image010

Chart VG-2, Italy, Total Number of Employed Persons, Millions, SA

Source: Istituto Nazionale di Statistica

http://www.istat.it/en/

VH United Kingdom. Annual data in Table VH-UK show the strong impact of the global recession in the UK with decline of GDP of 4.3 percent in 2009 after dropping 0.3 percent in 2008. Recovery of 1.9 percent in 2010 is relatively low in comparison with annual growth rates in 2007 and earlier years. Growth was only 1.6 percent in 2011 and 0.7 percent in 2012. Growth increased to 1.7 percent in 2013 and 2.8 percent in 2014. The bottom part of Table VH-UK provides average growth rates of UK GDP since 1948. The UK economy grew at 2.6 percent per year on average between 1948 and 2014, which is relatively high for an advanced economy. The growth rate of GDP between 2000 and 2007 is higher at 2.9 percent. Growth in the current cyclical expansion from 2010 to 2014 has been only at 1.7 percent as advanced economies struggle with weak internal demand and world trade. GDP in 2014 higher by 4.1 percent relative to 2007 while it would have been 22.2 higher at trend of 2.9 percent as from 2000 to 2007.

Table VH-UK, UK, Gross Domestic Product, ∆%

 

∆% on Prior Year

1998

3.5

1999

3.2

2000

3.8

2001

2.7

2002

2.5

2003

4.3

2004

2.5

2005

2.8

2006

3.0

2007

2.6

2008

-0.3

2009

-4.3

2010

1.9

2011

1.6

2012

0.7

2013

1.7

2014

3.0

Average Growth Rates ∆% per Year

 

1948-2014

2.6

1950-1959

3.1

1960-1969

3.1

1970-1979

2.6

1980-1989

3.1

1990-1999

2.2

2000-2007

2.9

2007-2013*

1.1

2007-2014*

4.1

2000-2014

1.7

*Absolute change from 2007 to 2013 and from 2007 to 2014

Source: UK Office for National Statistics

http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html

The Business Activity Index of the Markit/CIPS UK Services PMI® increased from 56.5 in May to 58.5 in Jun (http://www.markiteconomics.com/Survey/PressRelease.mvc/a8ffc58477b54b92b4b23bb8abb1072a). Chris Williamson, Chief Economist at Markit, finds the combined indices consistent with the UK economy growing at around 0.5 percent in IIQ2015 (http://www.markiteconomics.com/Survey/PressRelease.mvc/a8ffc58477b54b92b4b23bb8abb1072a). The Markit/CIPS UK Manufacturing Purchasing Managers’ Index® (PMI®) decreased to 51.4 in Jun from 51.9 in May (http://www.markiteconomics.com/Survey/PressRelease.mvc/e4122c0d1c284c1282fa2e20d86e566f). New export orders decreased. Rob Dobson, Senior Economist at Markit that compiles the Markit/CIPS Manufacturing PMI®, finds weakening manufacturing conditions (http://www.markiteconomics.com/Survey/PressRelease.mvc/e4122c0d1c284c1282fa2e20d86e566f). Table UK provides the economic indicators for the United Kingdom.

Table UK, UK Economic Indicators

CPI

May month ∆%: 0.2
May 12-month ∆%: 0.1
Blog 6/21/15

Output/Input Prices

Output Prices: May 12-month NSA ∆%: -1.6; excluding food, petroleum ∆%: 0.1
Input Prices: May 12-month NSA
∆%: -12.0
Excluding ∆%: -3.4
Blog 6/21/15

GDP Growth

IQ2015 prior quarter ∆% 0.4; year earlier same quarter ∆%: 2.9
Blog 3/31/13 4/28/13 5/26/13 7/28/13 8/25/13 9/29/13 10/27/13 12/1/13 12/22/13 2/2/14 3/2/14 4/6/14 5/4/14 5/25/14 6/29/14 7/27/14 8/17/14 10/5/14 10/26/14 11/30/14 12/28/14 2/1/15 3/1/15 4/5/15 5/3/15 5/31/15 7/5/15

Industrial Production

Apr 2015/Apr 2014 ∆%: Production Industries 1.2; Manufacturing 0.2

Earlier Data:
Blog 4/12/15

Retail Sales

May month ∆%: 0.2
May 12-month ∆%: 4.6

Earlier Data:
Blog 4/26/15

Labor Market

Feb-Apr Unemployment Rate: 5.5%
Blog 6/21/15 LMGDP 5/17/15

GDP and the Labor Market

IQ2015 Employment 104.8

IQ2008 =100

GDP IQ15=104.0 IQ2008=100

Blog 5/17/14

Trade Balance

Balance SA Apr minus ₤1202 million
Exports Apr%: 1.2; Jan-Apr ∆%: -1.6
Imports Apr ∆%: -3.1 Jan-Apr ∆%: -1.1

EARLIER DATA:
Blog 4/12/15

Links to blog comments in Table UK:

6/21/15 http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html

5/31/15 http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html

5/31/15 http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html

5/17/15 http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html

5/3/15 http://cmpassocregulationblog.blogspot.com/2015/05/dollar-devaluation-and-carry-trade.html

4/26/2015 http://cmpassocregulationblog.blogspot.com/2015/04/imf-view-of-economy-and-finance-united.html

4/12/15 http://cmpassocregulationblog.blogspot.com/2015/04/dollar-revaluation-recovery-without.html

4/5/15 http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html

3/1/15 http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html

2/1/15 http://cmpassocregulationblog.blogspot.com/2015/02/financial-and-international.html

12/28/14 http://cmpassocregulationblog.blogspot.com/2014/12/valuations-of-risk-financial-assets.html

11/30/14 http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html

10/26/14 http://cmpassocregulationblog.blogspot.com/2014/10/financial-oscillations-world-inflation.html

10/5/14 http://cmpassocregulationblog.blogspot.com/2014/10/world-financial-turbulence-twenty-seven.html

8/17/2014 http://cmpassocregulationblog.blogspot.com/2014/08/weakening-world-economic-growth.html

7/27/14 http://cmpassocregulationblog.blogspot.com/2014/07/world-inflation-waves-united-states.html

6/29/14 http://cmpassocregulationblog.blogspot.com/2014/06/financial-indecision-mediocre-cyclical.html

5/25/14 http://cmpassocregulationblog.blogspot.com/2014/05/united-states-commercial-banks-assets.html

5/4/2014 http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html

4/6/14 http://cmpassocregulationblog.blogspot.com/2014/04/interest-rate-risks-twenty-eight.html

3/2/14 http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html

2/2/14 http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html

12/22/13 http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html

12/1/13 http://cmpassocregulationblog.blogspot.com/2013/12/exit-risks-of-zero-interest-rates-world.html

10/27/13 http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html

9/29/13 http://cmpassocregulationblog.blogspot.com/2013/09/mediocre-and-decelerating-united-states.html

8/25/13 http://cmpassocregulationblog.blogspot.com/2013/08/interest-rate-risks-duration-dumping.html

7/28/13 http://cmpassocregulationblog.blogspot.com/2013/07/duration-dumping-steepening-yield-curve.html

5/26/13 http://cmpassocregulationblog.blogspot.com/2013/05/united-states-commercial-banks-assets.html

4/28/13 http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html

03/31/13 http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html

Table VH-1 provides quarter on quarter chained value measures of GDP since 1998 in the second estimate for IQ2015 (http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html). The UK Office for National Statistics provides revision of the national accounts in accordance with the European System of Accounts 2010 (ESA 2010) (http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q2-2014/index.html). GDP grew 0.4 percent in IQ2015 relative to IVQ2014. Growth of 0.8 percent in IIIQ2012 interrupted three consecutive quarters of weakness in GDP growth. Most advanced economies are underperforming relative to the period before the global recession. The UK Office for National Statistics analyzes that the decline in the impulse of growth in the UK originated in weakness in markets in the UK and worldwide. The UK Office for National Statistics estimates that GDP in IQ2015 is higher by 4.0 percent relative to the peak in IQ2008 (http://www.ons.gov.uk/ons/rel/gva/gross-domestic-product--preliminary-estimate/q1-2015/index.html). UK GDP in chained value measures is ₤414,424 million in IQ2008 and ₤431,386 million in IVQ2014 or increase of 4.1 percent. Growth at trend of 2.9 percent per year would bring GDP to ₤502,630 million in 2014. UK GDP in IVQ2014 at ₤431,386 million is lower by ₤71,244 million relative to trend at ₤502,630 million or lower by 14.2 percent compared with trend. The UK Office for National Statistics estimates the contraction of 6.0 percent from peak to trough (http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q2-2014/index.html), which is roughly equal at 6.1 percent to compounding the quarterly rates except for rounding in Table VH-1 from IIQ2008 to IIQ2009. UK GDP is ₤414,424 million in IQ2008 declining 6.0 percent to ₤389,388 million in IIQ2009. GDP increased 11.2 percent from IIQ2009 to ₤432,995 million in IQ2015 or at the annual equivalent rate of 1.9 percent. GDP increased 4.5 percent from IQ2008 to IQ2015 or at the annual equivalent rate of 0.6 percent. Using the seasonally adjusted chained-value measures (http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html), GDP increased from ₤414,424 million in IQ2008 to ₤432,995 million in IQ2015, 4.5% at the annual equivalent rate of 0.6 percent. UK GDP in IQ2015 at ₤432,995 million is lower by ₤73,240 million relative to trend at ₤506,235 million or lower by 14.5 percent compared with trend.

Table VH-1, UK, Percentage Change of GDP from Prior Quarter, Chained Value Measures ∆%

 

IQ

IIQ

IIIQ

IV

2015

0.4

     

2014

0.9

0.9

0.7

0.8

2013

0.6

0.6

0.7

0.4

2012

0.1

-0.2

0.8

-0.3

2011

0.5

0.2

0.7

0.0

2010

0.5

1.0

0.6

0.0

2009

-1.8

-0.3

0.2

0.4

2008

0.3

-0.2

-1.7

-2.2

2007

0.8

0.6

0.8

0.5

2006

0.6

0.5

0.2

0.8

2005

0.7

1.0

1.0

1.3

2004

0.3

0.3

0.1

0.4

2003

1.0

1.4

1.3

1.0

2002

0.5

0.8

0.9

0.9

2001

1.1

0.8

0.5

0.3

2000

1.0

0.7

0.4

0.3

1999

0.5

0.2

1.6

1.3

1998

0.6

0.8

0.7

1.0

Source: UK Office for National Statistics

http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html

There are four periods in growth of GDP in a quarter relative to the same quarter a year earlier in the UK in the years from 2000 to the present as shown in Table VH-2. (1) Growth rates were quite high from 2000 to 2007. (2) There were six consecutive quarters of contraction of GDP from IIIQ2008 to IVQ2009. Contractions relative to the quarter a year earlier were quite sharp with the highest of 3.8 percent in IVQ2008, 5.8 percent in IQ2009, 5.8 percent in IIQ2009 and 4.0 percent in IIIQ2009. (3) The economy bounced strongly with 2.1 percent in IIQ2010, 2.5 percent in IIIQ2010 and 2.2 percent in IVQ2010. (4) Recovery in 2011 did not continue at rates comparable to those in 2000 to 2007 and even relative to those in the final three quarters of 2010. Growth relative to the same quarter a year earlier fell from 2.2 percent in IVQ2010 to 1.4 percent in IIQ2011, 1.5 percent in IIIQ2011, 1.5 percent in IVQ2011 but only 1.0 percent in IQ2012, increase of 0.6 percent in IIQ2012 relative to IIQ2011, increase of 0.7 percent in IIIQ2012 and 0.4 percent in IVQ2012. In IQ2012, GDP increased 0.1 percent and increased 1.0 percent relative to a year earlier. In IIQ2012, GDP fell 0.2 percent relative to IQ2012 and increased 0.6 percent relative to a year earlier. In IIIQ2012, GDP increased 0.8 percent and increased 0.7 percent relative to the same quarter a year earlier. In IVQ2012, GDP fell 0.3 percent and increased 0.4 percent relative to a year earlier. Fiscal consolidation in an environment of weakening economic growth is much more challenging. Growth increased to 0.9 percent in IQ2013 relative to a year earlier and 0.6 percent in IQ2013 relative to IVQ2012. In IIQ2013, GDP increased 0.6 percent and 1.7 percent relative to a year earlier. GDP increased 0.7 percent in IIIQ2013 and 1.6 percent relative to a year earlier. GDP increased 0.4 percent in IVQ2013 and 2.4 percent relative to a year earlier. In IQ2014, GDP increased 0.9 percent and 2.7 percent relative to a year earlier. GDP increased 0.9 percent in IIQ2014 and 3.0 percent relative to a year earlier. GDP increased 0.7 percent in IIIQ2013 and 3.0 percent relative to a year earlier. In IVQ2014, GDP increased 0.8 percent and 3.4 percent relative to a year earlier. GDP increased 0.4 percent in IQ2015 and increased 2.9 percent relative to a year earlier.

Table VH-2, UK, Percentage Change of GDP from Same Quarter a Year Earlier, Chained Value Measures ∆%

 

IQ

IIQ

IIIQ

IV

2015

2.9

     

2014

2.7

3.0

3.0

3.4

2013

0.9

1.7

1.6

2.4

2012

1.0

0.6

0.7

0.4

2011

2.2

1.4

1.5

1.5

2010

0.8

2.1

2.5

2.2

2009

-5.8

-5.8

-4.0

-1.5

2008

2.2

1.4

-1.1

-3.8

2007

2.2

2.3

3.0

2.7

2006

4.0

3.5

2.6

2.0

2005

1.6

2.3

3.2

4.2

2004

4.0

2.9

1.8

1.2

2003

3.6

4.2

4.6

4.7

2002

2.1

2.1

2.5

3.1

2001

2.5

2.6

2.8

2.8

2000

4.3

4.8

3.5

2.5

1999

3.0

2.5

3.4

3.7

1998

3.9

3.5

3.5

3.2

Source: UK Office for National Statistics

http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html

Table VH-3 provides annual percentage changes of gross value added and key components. Production fell 8.8 percent in 2009 and its most important component manufacturing fell 9.4 percent. Services fell 2.9 percent in 2009. Services grew in all years from 2010 to 2014 while manufacturing fell 1.3 percent in 2012 and 0.7 percent in 2013. Manufacturing resumed growth with 3.1 percent in 2014.

Table VH-3, UK, Gross Value Added by Components, ∆% on Prior Year

 

TP

MFG

CONS

SERV

GVA BP

GVA EX

2011 Weights

146

101

64

784

1000

981

1998

1.1

0.4

1.5

4.8

3.7

3.7

1999

1.1

0.5

1.3

4.1

3.3

3.1

2000

1.9

2.3

0.9

4.7

3.8

4.3

2001

-1.6

-1.6

1.8

3.7

2.4

2.9

2002

-1.7

-2.6

5.7

2.8

2.2

2.3

2003

-0.7

-0.6

4.8

5.8

4.5

5.0

2004

0.8

1.9

5.3

2.3

2.2

2.7

2005

-0.7

-0.1

-2.4

4.3

3.1

3.6

2006

0.7

2.2

0.8

3.8

3.0

3.5

2007

0.3

0.7

2.2

3.1

2.5

2.7

2008

-2.7

-2.9

-2.6

0.6

-0.1

-

2009

-8.8

-9.4

-13.2

-2.9

-4.5

-4.4

2010

3.1

4.7

8.5

1.4

2.1

2.3

2011

-0.8

1.8

2.2

2.1

1.7

2.2

2012

-2.7

-1.3

-7.5

2.0

0.7

1.0

2013

-0.5

-0.7

1.4

1.9

1.5

1.7

2014

1.7

3.1

9.5

3.0

3.0

3.0

Note: TP: Total Production; MFG: Manufacturing; CONS: Construction; SERV: Services; GVA BP: Gross Value Added at Basic Prices; GVA EX: Gross Value Added excluding Oil and Gas

Source: UK Office for National Statistics

http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html

Percentage changes of gross value added and components in a quarter relative to the same quarter a year earlier are in Table VH-4A. Gross value added increased 2.8 percent in IQ2015 relative to a year earlier while services increased 3.1 percent. Manufacturing increased 1.4 percent in IQ2015 relative to a year earlier.

Table VH-4A, UK, Gross Value Added by Components, ∆% on Same Quarter of Previous Year

 

TP

MFG

CONS

SERV

GVA BP

GVA EX

2011 Weights

146

101

64

784

1000

981

1998 Q1

1.4

1.1

4.8

4.6

3.8

4.1

1998 Q2

2.0

1.2

0.1

4.7

3.8

3.6

1998 Q3

0.9

0.3

1.2

4.9

3.7

3.8

1998 Q4

0.2

-1.1

-

4.9

3.5

3.4

1999 Q1

-0.5

-1.5

-1.5

4.7

3.2

3.0

1999 Q2

-0.4

-1.0

1.3

3.7

2.7

2.6

1999 Q3

2.3

1.7

3.2

3.9

3.6

3.3

1999 Q4

3.0

2.9

2.1

4.0

3.7

3.7

2000 Q1

2.9

3.1

3.3

4.7

4.2

4.3

2000 Q2

3.2

3.4

2.1

5.4

4.7

5.1

2000 Q3

0.8

1.1

-1.9

4.9

3.6

4.3

2000 Q4

0.7

1.7

-

3.6

2.7

3.5

2001 Q1

-

0.7

-1.9

4.0

2.7

3.7

2001 Q2

-1.6

-1.5

1.6

3.9

2.5

3.1

2001 Q3

-1.5

-1.5

3.8

3.4

2.3

2.7

2001 Q4

-3.2

-4.1

3.7

3.5

2.0

2.2

2002 Q1

-2.6

-3.5

5.2

2.3

1.6

1.7

2002 Q2

-1.8

-3.0

3.5

2.3

1.6

1.6

2002 Q3

-1.7

-2.0

7.2

2.8

2.3

2.7

2002 Q4

-0.8

-1.8

7.0

3.7

3.1

3.3

2003 Q1

-1.5

-2.2

3.5

4.9

3.5

3.7

2003 Q2

-1.3

-0.7

5.4

5.9

4.5

5.3

2003 Q3

-0.5

-1.0

4.6

6.3

4.9

5.3

2003 Q4

0.5

1.4

5.7

6.0

5.0

5.8

2004 Q1

1.4

2.8

11.6

4.3

4.2

5.0

2004 Q2

2.2

3.0

6.9

2.5

2.7

3.0

2004 Q3

-0.3

0.8

3.4

1.6

1.3

1.8

2004 Q4

-0.1

1.2

-0.3

1.0

0.7

1.2

2005 Q1

-1.2

-0.7

-2.7

2.3

1.4

1.9

2005 Q2

-0.7

-0.1

-1.8

3.6

2.6

3.1

2005 Q3

-0.4

0.8

-2.9

5.0

3.6

4.3

2005 Q4

-0.7

-0.3

-2.2

6.4

4.7

5.3

2006 Q1

1.0

1.6

-2.0

5.6

4.3

4.7

2006 Q2

-0.3

1.6

-0.5

4.6

3.4

4.1

2006 Q3

1.2

2.7

1.8

3.0

2.6

2.9

2006 Q4

0.9

3.1

3.9

2.0

1.9

2.2

2007 Q1

0.2

1.9

4.1

2.3

2.0

2.4

2007 Q2

0.7

1.0

3.0

2.7

2.3

2.5

2007 Q3

-

0.1

1.0

3.8

3.0

3.1

2007 Q4

0.3

-0.3

0.5

3.5

2.8

2.8

2008 Q1

-0.3

0.1

0.3

3.1

2.4

2.6

2008 Q2

-1.2

-1.5

-0.4

2.1

1.5

1.7

2008 Q3

-2.3

-2.7

-1.7

-0.5

-0.8

-0.7

2008 Q4

-6.9

-7.3

-8.6

-2.4

-3.4

-3.3

2009 Q1

-10.9

-12.6

-16.1

-3.7

-5.7

-5.7

2009 Q2

-10.0

-10.9

-16.2

-4.0

-5.8

-5.8

2009 Q3

-9.5

-9.7

-12.2

-2.7

-4.4

-4.2

2009 Q4

-4.4

-3.9

-7.8

-1.0

-2.0

-1.8

2010 Q1

1.9

3.0

3.7

0.3

0.7

1.0

2010 Q2

2.6

4.5

10.1

1.4

2.1

2.4

2010 Q3

3.9

6.0

11.0

2.1

2.9

3.0

2010 Q4

3.9

5.3

9.3

1.8

2.6

2.8

2011 Q1

1.5

4.3

6.8

2.0

2.3

2.7

2011 Q2

-0.7

2.6

2.2

1.8

1.5

2.1

2011 Q3

-1.3

0.9

-0.7

2.1

1.5

2.0

2011 Q4

-2.8

-0.4

0.7

2.4

1.5

2.0

2012 Q1

-2.8

-0.5

-4.7

2.5

1.2

1.5

2012 Q2

-2.5

-1.8

-8.5

2.1

0.7

0.9

2012 Q3

-2.0

-0.9

-9.2

2.0

0.7

0.9

2012 Q4

-3.5

-2.0

-7.7

1.6

0.2

0.6

2013 Q1

-2.6

-2.4

-5.0

1.6

0.7

1.0

2013 Q2

-1.0

-0.8

0.9

2.0

1.6

1.8

2013 Q3

-0.4

-0.8

5.0

1.6

1.5

1.6

2013 Q4

1.9

1.3

5.1

2.4

2.3

2.3

2014 Q1

2.3

3.1

10.1

2.5

2.6

2.6

2014 Q2

1.9

3.2

9.9

3.0

2.9

3.0

2014 Q3

1.3

3.1

9.0

3.1

2.9

3.1

2014 Q4

1.3

2.9

8.9

3.4

3.4

3.5

2015 Q1

1.0

1.4

4.5

3.1

2.8

2.9

Note: TP: Total Production; MFG: Manufacturing; CONS: Construction; SERV: Services; GVA BP: Gross Value Added at Basic Prices; GVA EX: Gross Value Added excluding Oil and Gas

Source: UK Office for National Statistics

http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html

Table VH-5 provides contributions to value added by expenditure components in a quarter relative to the prior quarter. Household final consumption expenditure contributed 0.4 percentage points in IQ2014 and 0.5 percentage points in IIQ2014. Household final consumption contributed 0.6 percentage points in IIIQ2014 and 0.4 percentage points in IVQ2014. Household final consumption expenditures contributed 0.5 percentage points in IQ2015. In IQ2014, net trade contributed 0.2 percentage points, contributing 0.1 percentage points in IIQ2014 and deducting 0.7 percentage points in IIIQ2014. Net trade added 0.8 percentage points in IVQ2014 and deducted 0.6 percentage points in IQ2015. Gross fixed capital formation (GFCF) added 0.6 percentage points in IQ2014, 0.2 percentage points in IIQ2014 and 0.3 percentage points in IIIQ2014. GFCF did not contribute percentage points in IVQ2014 and added 0.3 percentage points in IQ2015.

Table VH-5, UK, Contribution to Quarter on Prior Quarter of Growth of Value Added by Expenditure Components, %

 

IQ2014

IIQ2014

IIIQ2014

IVQ2014

IQ2015

HFC

0.4

0.5

0.6

0.4

0.5

NPISH

0.0

0.1

0.0

-0.1

0.1

GOVT

0.1

0.3

0.0

0.0

0.2

GCF

0.2

0.0

0.7

-0.3

0.2

     GFCF

0.6

0.2

0.3

0.0

0.3

     BI

0.1

0.4

0.0

0.0

0.2

Exports

0.5

–0.1

-0.2

1.3

0.1

Less Imports

0.3

–0.2

0.4

0.5

0.7

Net Trade

0.2

0.1

-0.7

0.8

-0.6

Components may not add because of rounding

HFC: Household Final Consumption; NPISH: NPISH Final Consumption; GOVT: General Government; GCF: Gross Capital Formation; GFCF: Gross Fixed Capital Formation; BINV: Business Investment; EXP: Exports; IMP: Less Imports

Source: UK Office for National Statistics

http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html

Contributions of value added by expenditure components in a year relative to the prior year are in Table VH-6. Household final consumption added 1.1 percentage points in 2013 and 1.6 percentage points in 2014. Gross capital formation contributed 0.8 percentage points in 2013 and 1.6 percentage points in 2014. GFCF added 0.5 percentage points in 2013 and 1.4 percentage points in 2014.

VH-6, UK, Contribution to Growth on Prior Year of Value Added by Expenditure Components, %

 

2013

2014

HFC

1.1

1.6

NPISH

0.0

0.0

GOVT

-0.1

0.3

GCF

0.8

1.6

     GFCF

0.5

1.4

     BINV

0.5

0.8

Exports

0.5

0.1

Less Imports

0.5

0.8

Net Trade

0.0

-0.6

HFC: Household Final Consumption; NPISH: NPISH Final Consumption; GOVT: General Government; GCF: Gross Capital Formation; GFCF: Gross Fixed Capital Formation; BINV: Business Investment; EXP: Exports; IMP: Less Imports

Source: UK Office for National Statistics

http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q1-2015/index.html

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015.

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