Monday, December 5, 2016

Rising Yields and Dollar Revaluation, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Private Fixed Investment, Swelling Undistributed Corporate Profits, Stagnating Real Disposable Income per Capita, Financial Repression, Twenty Four Million Unemployed or Underemployed, Insufficient Job Creation, Stagnating Real Wages, World Cyclical Slow Growth and Global Recession Risk: Part V

 

Rising Yields and Dollar Revaluation, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Private Fixed Investment, Swelling Undistributed Corporate Profits, Stagnating Real Disposable Income per Capita, Financial Repression, Twenty Four Million Unemployed or Underemployed, Insufficient Job Creation, Stagnating Real Wages, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016

I Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend

IA Mediocre Cyclical United States Economic Growth

IA1 Stagnating Real Private Fixed Investment

IA2 Swelling Undistributed Corporate Profits

II Stagnating Real Disposable Income and Consumption Expenditures

IB1 Stagnating Real Disposable Income and Consumption Expenditures

IB2 Financial Repression

I Twenty Four 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

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 2015 and the growth rate of real GDP of the world and selected regional countries from 2015 to 2018. 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 3.2 percent in 2015 and 3.1 percent in 2016 but accelerating to 3.4 percent in 2017 and 3.6 percent in 2018. Slow-speed recovery occurs in the “major advanced economies” of the G7 that account for $34.171 billion of world output of $73,599 billion, or 46.4 percent, but are projected to grow at much lower rates than world output, 1.7 percent on average from 2015 to 2018, in contrast with 3.3 percent for the world as a whole. While the world would grow 14.0 percent in the four years from 2015 to 2017, the G7 as a whole would grow 6.9 percent. The difference in dollars of 2015 is high: growing by 14.0 percent would add around $10.3 trillion of output to the world economy, or roughly, two times the output of the economy of Japan of $4,124 billion but growing by 6.9 percent would add $5.1 trillion of output to the world, or about the output of Japan in 2015. 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 2019 of $29,039 billion, or 39.5 percent of world output. The EMDEs would grow cumulatively 18.8 percent or at the average yearly rate of 4.4 percent, contributing $5.5 trillion from 2015 to 2017 or the equivalent of somewhat more than one half the GDP of $11,182 billion of China in 2014. 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 2015 adds to $16,354 billion, or 22.2 percent of world output, which is equivalent to 47.9 percent of the combined output of the major advanced economies of the G7.

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

 

GDP USD 2015

Real GDP ∆%
2015

Real GDP ∆%
2016

Real GDP ∆%
2017

Real GDP ∆%
2018

World

73,599

3.2

3.1

3.4

3.6

G7

34,171

1.9

1.4

1.7

1.7

Canada

1,551

1.1

1.2

1.9

1.9

France

2,420

1.3

1.3

1.4

1.6

DE

3,365

1.5

1.7

1.4

1.4

Italy

1,816

0.8

0.8

0.9

1.1

Japan

4,124

0.5

0.5

0.6

0.5

UK

2,858

2.2

1.8

1.1

1.7

US

18,037

2.6

1.6

2.2

2.1

Euro Area

11,601

2.1

1.7

1.5

1.6

DE

3,365

1.5

1.7

1.4

1.4

France

2,420

1.3

1.3

1.4

1.6

Italy

1,816

0.8

0.8

0.9

1.1

POT

199

1.5

1.1

1.1

1.2

Ireland

283

26.3

4.9

3.2

3.1

Greece

195

-0.2

0.1

2.8

3.1

Spain

1,200

3.2

3.1

2.2

1.9

EMDE

29,039

4.0

4.2

4.6

4.8

Brazil

1,773

-3.8

-3.3

0.5

1.5

Russia

1,326

-3.7

-0.8

1.1

1.2

India

2,073

7.6

7.6

7.6

7.7

China

11,182

6.9

6.6

6.2

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/2016/02/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/2016/02/weodata/index.aspx). Table V-2 is constructed with the WEO database to provide rates of unemployment from 2014 to 2018 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, 24.4 percent for Spain and 12.6 percent for Italy, which is lower but still high. The G7 rate of unemployment is 6.4 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 2014

% Labor Force 2015

% Labor Force 2016

% Labor Force 2017

% Labor Force 2018

World

NA

NA

NA

NA

NA

G7

6.4

5.8

5.5

5.4

5.4

Canada

6.9

6.9

7.0

7.1

6.9

France

10.3

10.4

9.8

9.6

9.3

DE

5.0

4.6

4.3

4.5

4.6

Italy

12.6

11.9

11.5

11.2

10.8

Japan

3.6

3.4

3.2

3.2

3.2

UK

6.2

5.4

5.0

5.2

5.4

US

6.2

5.3

5.0

4.8

4.7

Euro Area

11.7

10.9

10.0

9.7

9.3

DE

5.0

4.6

4.3

4.5

4.6

France

10.3

10.4

9.8

9.6

9.3

Italy

12.6

11.9

11.5

11.2

10.8

POT

13.9

12.4

11.2

10.7

10.3

Ireland

11.3

9.5

8.3

7.7

7.2

Greece

26.5

25.0

23.3

21.5

20.7

Spain

24.4

22.1

19.4

18.0

17.0

EMDE

NA

NA

NA

NA

NA

Brazil

6.8

8.5

11.2

11.5

11.1

Russia

5.2

5.6

5.8

5.9

5.5

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/2016/02/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 IIQ2016 available now for all countries. There are preliminary estimates for all countries for IIIQ2016. Growth is weak throughout most of the world.

  • Japan. The GDP of Japan increased 0.9 percent in IQ2012, 3.7 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 0.4 percent in IIQ2012 at the seasonally adjusted annual rate (SAAR) of minus 1.5 percent, which is much lower than 3.7 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 0.5 percent in IIIQ2012 at the SAAR of minus 2.0 percent and increased 0.2 percent relative to a year earlier. Japan’s GDP changed 0.0 percent in IVQ2012 at the SAAR of minus 0.1 percent and changed 0.0 percent relative to a year earlier. Japan grew 1.0 percent in IQ2013 at the SAAR of 4.1 percent and increased 0.3 percent relative to a year earlier. Japan’s GDP increased 0.7 percent in IIQ2013 at the SAAR of 2.8 percent and increased 1.1 percent relative to a year earlier. Japan’s GDP grew 0.4 percent in IIIQ2013 at the SAAR of 1.8 percent and increased 2.0 percent relative to a year earlier. In IVQ2013, Japan’s GDP decreased 0.1 percent at the SAAR of minus 0.2 percent, increasing 2.1 percent relative to a year earlier. Japan’s GDP increased 1.3 percent in IQ2014 at the SAAR of 5.2 percent and increased 2.7 percent relative to a year earlier. In IIQ2014, Japan’s GDP fell 2.0 percent at the SAAR of minus 7.8 percent and fell 0.3 percent relative to a year earlier. Japan’s GDP contracted 0.7 percent in IIIQ2014 at the SAAR of minus 2.8 percent and fell 1.5 percent relative to a year earlier. In IVQ2014, Japan’s GDP grew 0.6 percent, at the SAAR of 2.3 percent, decreasing 0.9 percent relative to a year earlier. The GDP of Japan increased 1.2 percent in IQ2015 at the SAAR of 5.0 percent and decreased 1.0 percent relative to a year earlier. Japan’s GDP decreased 0.3 percent in IIQ2015 at the SAAR of minus 1.3 percent and increased 0.8 percent relative to a year earlier. The GDP of Japan increased 0.4 percent in IIIQ2015 at the SAAR of 1.6 percent and increased 1.9 percent relative to a year earlier. Japan’s GDP contracted 0.4 percent in IVQ2015 at the SAAR of minus 1.6 percent and grew 0.7 percent relative to a year earlier. In IQ2016, the GDP of Japan increased 0.5 percent at the SAAR of 2.1 percent and increased 0.2 percent relative to a year earlier. Japan’s GDP increased 0.2 percent in IIQ2016 at the SAAR of 0.7 percent and increased 0.6 percent relative to a year earlier. In IIIQ2016, the GDP of Japan increased 0.5 percent at the SAAR of 2.2 percent and increased 0.9 percent relative to a year earlier.
  • China. China’s GDP grew 1.9 percent in IQ2012, annualizing to 7.8 percent, and 8.1 percent relative to a year earlier. The GDP of China grew at 2.2 percent in IIQ2012, which annualizes to 9.1 percent, and 7.6 percent relative to a year earlier. China grew at 1.8 percent in IIIQ2012, which annualizes at 7.4 percent, and 7.5 percent relative to a year earlier. In IVQ2012, China grew at 1.9 percent, which annualizes at 7.8 percent, and 8.1 percent in IVQ2012 relative to IVQ2011. In IQ2013, China grew at 1.9 percent, which annualizes at 7.8 percent, and 7.9 percent relative to a year earlier. In IIQ2013, China grew at 1.7 percent, which annualizes at 7.0 percent, and 7.6 percent relative to a year earlier. China grew at 2.1 percent in IIIQ2013, which annualizes at 8.7 percent, and increased 7.9 percent relative to a year earlier. China grew at 1.6 percent in IVQ2013, which annualized to 6.6 percent, and 7.7 percent relative to a year earlier. China’s GDP grew 1.7 percent in IQ2014, which annualizes to 7.0 percent, and 7.4 percent relative to a year earlier. China’s GDP grew 1.8 percent in IIQ2014, which annualizes at 7.4 percent, and 7.5 percent relative to a year earlier. China’s GDP grew 1.8 percent in IIIQ2014, which is equivalent to 7.4 percent in a year, and 7.1 percent relative to a year earlier. The GDP of China grew 1.8 percent in IVQ2014, which annualizes at 7.4 percent, and 7.2 percent relative to a year earlier. The GDP of China grew at 1.6 percent in IQ2015, which annualizes at 6.6 percent, and 7.0 percent relative to a year earlier. The GDP of China grew 1.9 percent in IIQ2015, which annualizes at 7.8 percent, and increased 7.0 percent relative to a year earlier. In IIIQ2015, China’s GDP grew at 1.7 percent, which annualizes at 7.0 percent, and increased 6.9 percent relative to a year earlier. The GDP of China grew at 1.6 percent in IVQ2015, which annualizes at 6.6 percent, and increased 6.8 percent relative to a year earlier. The GDP of China grew 1.2 percent in IQ2016, which annualizes at 4.9 percent, and increased 6.7 percent relative to a year earlier. In IIQ2016, the GDP of China increased 1.9 percent, which annualizes to 7.8 percent, and increased 6.7 percent relative to a year earlier. The GDP of China increased at 1.8 percent in IIIQ2016, which annualizes at 7.4 percent, and increased 6.7 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 2016.
  • 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 1.0 percent relative to a year earlier. In IVQ2012, euro area GDP fell 0.4 percent relative to the prior quarter and fell 1.1 percent relative to a year earlier. In IQ2013, the GDP of the euro area fell 0.3 percent and decreased 1.2 percent relative to a year earlier. The GDP of the euro area increased 0.4 percent in IIQ2013 and fell 0.4 percent relative to a year earlier. In IIIQ2013, euro area GDP increased 0.3 percent and changed 0.0 percent relative to a year earlier. The GDP of the euro area increased 0.2 percent in IVQ2013 and increased 0.7 percent relative to a year earlier. In IQ2014, the GDP of the euro area increased 0.3 percent and increased 1.3 percent relative to a year earlier. The GDP of the euro area increased 0.2 percent in IIQ2014 and increased 1.0 percent relative to a year earlier. The euro area’s GDP increased 0.4 percent in IIIQ2014 and increased 1.1 percent relative to a year earlier. The GDP of the euro area increased 0.4 percent in IVQ2014 and increased 1.3 percent relative to a year earlier. Euro area GDP increased 0.8 percent in IQ2015 and increased 1.8 percent relative to a year earlier. The GDP of the euro area increased 0.4 percent in IIQ2015 and increased 2.0 percent relative to a year earlier. The euro area’s GDP increased 0.3 percent in IIIQ2015 and increased 2.0 percent relative to a year earlier. Euro area GDP increased 0.4 percent in IVQ2015 and increased 2.0 percent relative to a year earlier. Euro area’s GDP increased 0.5 percent in IQ2016 and increased 1.7 percent relative to a year earlier. The GDP of the euro area increased 0.3 percent in IIQ2016 and increased 1.6 percent relative to a year earlier. In IIIQ2016, the GDP of the euro area increased 0.3 percent and increased 1.6 percent relative to a year earlier.
  • Germany. The GDP of Germany increased 0.4 percent in IQ2012 and increased 1.6 percent relative to a year earlier. In IIQ2012, Germany’s GDP increased 0.1 percent and increased 0.4 percent relative to a year earlier but 0.9 percent relative to a year earlier when adjusted for calendar (CA) effects. In IIIQ2012, Germany’s GDP increased 0.2 percent and 0.2 percent relative to a year earlier. Germany’s GDP contracted 0.5 percent in IVQ2012 and decreased 0.1 percent relative to a year earlier. In IQ2013, Germany’s GDP decreased 0.2 percent and fell 1.5 percent relative to a year earlier. In IIQ2013, Germany’s GDP increased 0.9 percent and grew 0.9 percent relative to a year earlier. The GDP of Germany increased 0.4 percent in IIIQ2013 and grew 1.2 percent relative to a year earlier. In IVQ2013, Germany’s GDP increased 0.4 percent and increased 1.4 percent relative to a year earlier. The GDP of Germany increased 0.6 percent in IQ2014 and grew 2.6 percent relative to a year earlier. In IIQ2014, Germany’s GDP decreased 0.1 percent and increased 0.9 percent relative to a year earlier. The GDP of Germany increased 0.3 percent in IIIQ2014 and increased 1.2 percent relative to a year earlier. Germany’s GDP increased 0.8 percent in IVQ2014 and increased 1.7 percent relative to a year earlier. The GDP of Germany increased 0.2 percent in IQ2015 and increased 1.3 percent relative to a year earlier. Germany’s GDP increased 0.5 percent in IIQ2015 and grew 1.8 percent relative to a year earlier. The GDP of Germany increased 0.2 percent in IIIQ2015 and grew 1.8 percent relative to a year earlier. Germany’s GDP increased 0.4 percent in IVQ2015 and grew 2.1 percent relative to a year earlier. In IQ2016, the GDP of Germany increased 0.7 percent and grew 1.5 percent relative to a year earlier. Germany’s GDP increased 0.4 percent in IIQ2016 and increased 3.1 percent relative to a year earlier. In IIIQ2016, the GDP of Germany increased 0.2 percent and grew 1.5 percent relative to a year earlier.
  • United States. Growth of US GDP in IQ2012 was 0.7 percent, at SAAR of 2.7 percent and higher by 2.8 percent relative to IQ2011. US GDP increased 0.5 percent in IIQ2012, 1.9 percent at SAAR and 2.5 percent relative to a year earlier. In IIIQ2012, US GDP grew 0.1 percent, 0.5 percent at SAAR and 2.4 percent relative to IIIQ2011. In IVQ2012, US GDP grew 0.0 percent, 0.1 percent at SAAR and 1.3 percent relative to IVQ2011. In IQ2013, US GDP grew at 2.8 percent SAAR, 0.7 percent relative to the prior quarter and 1.3 percent relative to the same quarter in 2012. In IIQ2013, US GDP grew at 0.8 percent in SAAR, 0.2 percent relative to the prior quarter and 1.0 percent relative to IIQ2012. US GDP grew at 3.1 percent in SAAR in IIIQ2013, 0.8 percent relative to the prior quarter and 1.7 percent relative to the same quarter a year earlier (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html). In IVQ2013, US GDP grew 1.0 percent at 4.0 percent SAAR and 2.7 percent relative to a year earlier. In IQ2014, US GDP decreased 0.3 percent, increased 1.6 percent relative to a year earlier and fell 1.2 percent at SAAR. In IIQ2014, US GDP increased 1.0 percent at 4.0 percent SAAR and increased 2.4 percent relative to a year earlier. US GDP increased 1.2 percent in IIIQ2014 at 5.0 percent SAAR and increased 2.9 percent relative to a year earlier. In IVQ2014, US GDP increased 0.6 percent at SAAR of 2.3 percent and increased 2.5 percent relative to a year earlier. GDP increased 0.5 percent in IQ2015 at SAAR of 2.0 percent and grew 3.3 percent relative to a year earlier. US GDP grew at SAAR 2.6 percent in IIQ2015, increasing 0.6 percent in the quarter and 3.0 percent relative to a year earlier. GDP increased 0.5 percent in IIIQ2015 at SAAR of 2.0 percent and grew 2.2 percent in IIIQ2015 relative to a year earlier. US GDP grew at SAAR of 0.9 percent in IVQ2015, increasing 0.2 percent in the quarter and 1.9 percent relative to a year earlier. In IQ2016, US GDP grew 0.2 percent at SAAR of 0.8 percent and increased 1.6 percent relative to a year earlier. US GDP grew at SAAR of 1.4 percent in IIQ2016, increasing 0.4 percent in the quarter and 1.3 percent relative to a year earlier. In IIIQ2016, US GDP grew 0.8 percent at SAAR of 3.2 percent and increased 1.6 percent relative to a year earlier
  • United Kingdom. In IQ2012, UK GDP increased 0.4 percent and increased 1.2 percent relative to a year earlier. In IIQ2012, GDP fell 0.1 percent relative to IQ2012 and increased 1.0 percent relative to a year earlier. In IIIQ2012, GDP increased 1.1 percent and increased 1.8 percent relative to the same quarter a year earlier. In IVQ2012, GDP fell 0.2 percent and increased 1.3 percent relative to a year earlier. Fiscal consolidation in an environment of weakening economic growth is much more challenging. GDP increased 1.5 percent in IQ2013 relative to a year earlier and 0.6 percent in IQ2013 relative to IVQ2012. In IIQ2013, GDP increased 0.5 percent and 2.1 percent relative to a year earlier. GDP increased 0.8 percent in IIIQ2013 and 1.7 percent relative to a year earlier. GDP increased 0.5 percent in IVQ2013 and 2.4 percent relative to a year earlier. In IQ2014, GDP increased 0.8 percent and 2.6 percent relative to a year earlier. GDP increased 0.9 percent in IIQ2014 and 3.1 percent relative to a year earlier. GDP increased 0.8 percent in IIIQ2013 and 3.1 percent relative to a year earlier. In IVQ2014, GDP increased 0.8 percent and 3.5 percent relative to a year earlier. GDP increased 0.3 percent in IQ2015 and increased 2.8 percent relative to a year earlier. GDP increased 0.5 percent in IIQ2015 and increased 2.4 percent relative to a year earlier. UK GDP increased 0.3 percent in IIIQ2015 and increased 1.9 percent relative to a year earlier. GDP increased 0.7 percent in IVQ2015 and increased 1.7 percent relative to a year earlier. GDP increased 0.4 percent in IQ2016 and increased 1.9 percent relative to a year earlier. GDP increased 0.7 percent in IIQ2016 and grew 2.1 percent relative to a year earlier. UK GDP increased 0.5 percent in IIIQ2016 and increased 2.3 percent relative to a year earlier.
  • Italy. Italy’s GDP increased 0.3 percent in IIIQ2016 and increased 1.0 percent relative to a year earlier. In IIQ2016, GDP increased 0.1 percent and increased 0.8 percent relative to a year earlier. GDP increased 0.4 percent in IQ2016 and increased 1.0 percent relative to a year earlier. GDP increased 0.2 percent in IVQ2015 and increased 0.9 percent relative to a year earlier. In IIIQ2015, GDP increased 0.1 percent and increased 0.6 percent relative to a year earlier. GDP increased 0.3 percent in IIQ2015 and 0.6 percent relative to a year earlier. GDP increased 0.3 percent in IQ2015 and increased 0.4 percent relative to a year earlier. GDP changed 0.0 percent in IVQ2014 and increased 0.1 percent relative to a year earlier. GDP changed 0.0 percent in IIIQ2014 and changed 0.0 percent relative to a year earlier. Italy’s GDP increased 0.1 percent in IIQ2014 and increased 0.3 percent relative to a year earlier. The GDP of Italy changed 0.0 percent in IQ2014 and increased 0.3 percent relative to a year earlier. Italy’s GDP changed 0.0 percent in IVQ2013 and fell 0.7 percent relative to a year earlier. The GDP of Italy increased 0.3 percent in IIIQ2013 and fell 1.3 percent relative to a year earlier. Italy’s GDP changed 0.0 in IIQ2013 and fell 2.1 percent relative to a year earlier. Italy’s GDP fell 1.0 percent in IQ2013 and declined 2.8 percent relative to IQ2012. GDP had been growing during six consecutive quarters but at very low rates from IQ2010 to IIQ2011. Italy’s GDP fell in seven consecutive quarters from IIIQ2011 to IQ2013 at increasingly higher rates of contraction from 0.5 percent in IIIQ2011 to 1.0 percent in IVQ2011, 1.0 percent in IQ2012, 0.7 percent in IIQ2012 and 0.5 percent in IIIQ2012. The pace of decline accelerated to minus 0.6 percent in IVQ2012 and minus 1.0 percent in IQ2013. GDP contracted cumulatively 5.2 percent in seven consecutive quarterly contractions from IIIQ2011 to IQ2013 at the annual equivalent rate of minus 3.0 percent. The yearly rate has fallen from 2.2 percent in IVQ2010 to minus 2.8 percent in IVQ2012, minus 2.8 percent in IQ2013, minus 2.1 percent in IIQ2013 and minus 1.3 percent in IIIQ2013. GDP fell 0.7 percent in IVQ2013 relative to a year earlier. GDP increased 0.3 percent in IQ2014 relative to a year earlier and increased 0.3 percent in IIQ2014 relative to a year earlier. GDP changed 0.0 percent in IIIQ2014 relative to a year earlier and increased 0.1 percent in IVQ2014 relative to a year earlier. GDP increased 0.4 percent in IQ2015 relative to a year earlier and increased 0.6 percent in IIQ2015 relative to a year earlier. GDP increased 0.6 percent in IIIQ2015 relative to a year earlier and increased 0.9 percent in IVQ2015 relative to a year earlier. GDP increased 1.0 percent in IQ2016 relative to a year earlier and increased 0.8 percent in IIQ2016 relative to a year earlier. GDP increased 1.0 percent in IIIQ2016 relative to a year earlier. Using seasonally and calendar adjusted chained volumes in the dataset of EUROSTAT (http://ec.europa.eu/eurostat), the GDP of Italy in IIIQ2016 of €392,303.4 million is lower by 7.7 percent relative to €424,823.8 million in IQ2008. Using seasonally and calendar adjusted chained volumes in the dataset of EUROSTAT (http://ec.europa.eu/eurostat), the GDP of Italy increased from €367,664.4 million in IQ1998 to €424,823.8 million in IQ2008 at the annual equivalent rate of 1.5 percent. The fiscal adjustment of Italy is significantly more difficult with the economy not growing especially on the prospects of increasing government revenue. The strategy is for reforms to improve productivity, facilitating future fiscal consolidation.
  • France. France’s GDP decreased 0.1 percent in IQ2012 and increased 0.4 percent relative to a year earlier. France’s GDP decreased 0.2 percent in IIQ2012 and increased 0.3 percent relative to a year earlier. In IIIQ2012, France’s GDP increased 0.2 percent and increased 0.2 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 decreased 0.1 percent and changed 0.0 percent relative to a year earlier. The GDP of France increased 0.7 percent in IIQ2013 and increased 0.9 percent relative to a year earlier. France’s GDP changed 0.0 percent in IIIQ2013 and increased 0.7 percent relative to a year earlier. The GDP of France increased 0.3 percent in IVQ2013 and increased 0.9 percent relative to a year earlier. In IQ2014, France’s GDP decreased 0.1 percent and increased 0.9 percent relative to a year earlier. In IIQ2014, France’s GDP increased 0.2 percent and increased 0.4 percent relative to a year earlier. France’s GDP increased 0.4 percent in IIIQ2014 and increased 0.7 percent relative to a year earlier. The GDP of France increased 0.2 percent in IVQ2014 and increased 0.6 percent relative to a year earlier. France’s GDP increased 0.6 percent in IQ2015 and increased 1.3 percent relative to a year earlier. In IIQ2015, France’s GDP changed 0.0 percent and increased 1.1 percent relative to a year earlier. France’s GDP increased 0.4 percent in IIIQ2015 and increased 1.1 percent relative to a year earlier. In IVQ2015, the GDP of France increased 0.4 percent and increased 1.3 percent relative to a year earlier. France’s GDP increased 0.6 percent in IQ2016 and increased 1.4 percent relative to a year earlier. The GDP of France decreased 0.1 percent in IIQ2016 and increased 1.2 percent relative to a year earlier. France’s GDP increased 0.2 percent in IIIQ2016 and increased 1.1 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: 0.7       

SAAR: 2.7

2.8

Japan

QOQ: 0.9

SAAR: 3.7

3.5

China

1.9

8.1

Euro Area

-0.2

-0.5

Germany

0.4

1.6

France

-0.1

0.4

Italy

-1.0

-2.2

United Kingdom

0.4

1.2

 

IIQ2012/IQ2012

IIQ2012/IIQ2011

United States

QOQ: 0.5        

SAAR: 1.9

2.5

Japan

QOQ: -0.4
SAAR: -1.5

3.5

China

2.2

7.6

Euro Area

-0.3

-0.8

Germany

0.1

0.4 0.9 CA

France

-0.2

0.3

Italy

-0.7

-3.2

United Kingdom

-0.1

1.0

 

IIIQ2012/ IIQ2012

IIIQ2012/ IIIQ2011

United States

QOQ: 0.1 
SAAR: 0.5

2.4

Japan

QOQ: –0.5
SAAR: –2.0

0.2

China

1.8

7.5

Euro Area

-0.1

-1.0

Germany

0.2

0.2

France

0.2

0.2

Italy

-0.5

-3.2

United Kingdom

1.1

1.8

 

IVQ2012/IIIQ2012

IVQ2012/IVQ2011

United States

QOQ: 0.0
SAAR: 0.1

1.3

Japan

QOQ: 0.0

SAAR: -0.1

0.0

China

1.9

8.1

Euro Area

-0.4

-1.1

Germany

-0.5

-0.1

France

0.0

0.0

Italy

-0.6

-2.8

United Kingdom

-0.2

1.3

 

IQ2013/IVQ2012

IQ2013/IQ2012

United States

QOQ: 0.7
SAAR: 2.8

1.3

Japan

QOQ: 1.0

SAAR: 4.1

0.3

China

1.9

7.9

Euro Area

-0.3

-1.2

Germany

-0.2

-1.5

France

-0.1

0.0

Italy

-1.0

-2.8

UK

0.6

1.5

 

IIQ2013/IQ2013

IIQ2013/IIQ2012

United States

QOQ: 0.2

SAAR: 0.8

1.0

Japan

QOQ: 0.7

SAAR: 2.8

1.1

China

1.7

7.6

Euro Area

0.4

-0.4

Germany

0.9

0.9

France

0.7

0.9

Italy

0.0

-2.1

UK

0.5

2.1

 

IIIQ2013/IIQ2013

III/Q2013/  IIIQ2012

USA

QOQ: 0.8
SAAR: 3.1

1.7

Japan

QOQ: 0.4

SAAR: 1.8

2.0

China

2.1

7.9

Euro Area

0.3

0.0

Germany

0.4

1.2

France

0.0

0.7

Italy

0.3

-1.3

UK

0.8

1.7

 

IVQ2013/IIIQ2013

IVQ2013/IVQ2012

USA

QOQ: 1.0

SAAR: 4.0

2.7

Japan

QOQ: -0.1

SAAR: -0.2

2.1

China

1.6

7.7

Euro Area

0.2

0.7

Germany

0.4

1.4

France

0.3

0.9

Italy

0.0

-0.7

UK

0.5

2.4

 

IQ2014/IVQ2013

IQ2014/IQ2013

USA

QOQ -0.3

SAAR -1.2

1.6

Japan

QOQ: 1.3

SAAR: 5.2

2.7

China

1.7

7.4

Euro Area

0.3

1.3

Germany

0.6

2.6

France

-0.1

0.9

Italy

0.0

0.3

UK

0.8

2.6

 

IIQ2014/IQ2014

IIQ2014/IIQ2013

USA

QOQ 1.0

SAAR 4.0

2.4

Japan

QOQ: -2.0

SAAR: -7.8

-0.3

China

1.8

7.5

Euro Area

0.2

1.0

Germany

-0.1

0.9

France

0.2

0.4

Italy

0.1

0.3

UK

0.9

3.1

 

IIIQ2014/IIQ2014

IIIQ2014/IIIQ2013

USA

QOQ: 1.2

SAAR: 5.0

2.9

Japan

QOQ: -0.7

SAAR: -2.8

-1.5

China

1.8

7.1

Euro Area

0.4

1.1

Germany

0.3

1.2

France

0.4

0.7

Italy

0.0

0.0

UK

0.8

3.1

 

IVQ2014/IIIQ2014

IVQ2014/IVQ2013

USA

QOQ: 0.6

SAAR: 2.3

2.5

Japan

QOQ: 0.6

SAAR: 2.3

-0.9

China

1.8

7.2

Euro Area

0.4

1.3

Germany

0.8

1.7

France

0.2

0.6

Italy

0.0

0.1

UK

0.8

3.5

 

IQ2015/IVQ2014

IQ2015/IQ2014

USA

QOQ: 0.5

SAAR: 2.0

3.3

Japan

QOQ: 1.2

SAAR: 5.0

-1.0

China

1.6

7.0

Euro Area

0.8

1.8

Germany

0.2

1.3

France

0.6

1.3

Italy

0.3

0.4

UK

0.3

2.8

 

IIQ2015/IQ2015

IIQ2015/IIQ2014

USA

QOQ: 0.6

SAAR: 2.6

3.0

Japan

QOQ: -0.3

SAAR: -1.3

0.8

China

1.9

7.0

Euro Area

0.4

2.0

Germany

0.5

1.8

France

0.0

1.1

Italy

0.3

0.6

UK

0.5

2.4

 

IIIQ2015/IIQ2015

IIIQ2015/IIIQ2014

USA

QOQ: 0.5

SAAR: 2.0

2.2

Japan

QOQ: 0.4

SAAR: 1.6

1.9

China

1.7

6.9

Euro Area

0.3

2.0

Germany

0.2

1.8

France

0.4

1.1

Italy

0.1

0.6

UK

0.3

1.9

 

IVQ2015/IIIQ2015

IVQ2015/IVQ2014

USA

QOQ: 0.2

SAAR: 0.9

1.9

Japan

QOQ: -0.4

SAAR: -1.6

0.7

China

1.6

6.8

Euro Area

0.4

2.0

Germany

0.4

2.1

France

0.4

1.3

Italy

0.2

0.9

UK

0.7

1.7

 

IQ2016/IVQ2015

IQ2016/IQ2015

USA

QOQ: 0.2

SAAR: 0.8

1.6

Japan

QOQ: 0.5

SAAR: 2.1

0.2

China

1.2

6.7

Euro Area

0.5

1.7

Germany

0.7

1.5

France

0.6

1.4

Italy

0.4

1.0

UK

0.4

1.9

 

IIQ2016/IQ2016

IIQ2016/IIQ2015

USA

QOQ: 0.4

SAAR: 1.4

1.3

Japan

QOQ: 0.2

SAAR: 0.7

0.6

China

1.9

6.7

Euro Area

0.3

1.6

Germany

0.4

3.1

France

-0.1

1.2

Italy

0.1

0.8

UK

0.7

2.1

 

IIIQ2016/IIQ2016

IIIQ2016/IIIQ2015

United States

QOQ: 0.8

SAAR: 3.2

1.6

Japan

QOQ: 0.5

SAAR: 2.2

0.9

China

1.8

6.7

Euro Area

0.3

1.6

Germany

0.2

1.5

France

0.2

1.1

Italy

0.3

1.0

UK

0.5

2.3

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 Oct 2016, China exports decreased 7.3 percent relative to a year earlier and imports decreased 1.4 percent.
  • Germany. Germany’s exports decreased 0.7 percent in the month of Sep 2016 and increased 0.9 percent in the 12 months ending in Sep 2016. Germany’s imports decreased 0.5 percent in the month of Sep 2016 and decreased 1.4 percent in the 12 months ending in Sep 2016. 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 contributed 0.0 percentage points to GDP growth in IQ2014. Net trade added 0.2 percentage points to GDP growth in IIQ2014 and added 0.5 percentage points in IIIQ2014. Net trade deducted 0.3 percentage points from GDP growth in IVQ2014 and deducted 0.1 percentage points in IQ2015. Net trade added 0.6 percentage points to GDP growth in IIQ2015 and deducted 0.5 percentage points in IIIQ2015. Net trade deducted 0.6 percentage points in IVQ2015 and contributed 0.0 percentage points in IQ2016. Net trade added 0.5 percentage points to GDP growth in IIQ2016. Net trade deducted 0.3 percentage points from GDP growth in IIIQ2016.
  • 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 0.8 percentage points to UK value added in IQ2014 and 0.3 percentage points in IIQ2014. Net trade deducted 0.7 percentage points from GDP growth in IIIQ2014 and added 0.3 percentage points in IVQ2014. Net traded deducted 0.6 percentage points from growth in IQ2015. Net trade added 0.2 percentage points to GDP growth in IIQ2015 and deducted 0.3 percentage points in IIIQ2015. Net trade added 0.4 percentage points to GDP growth in IVQ2015. Net trade deducted 0.0 percentage points from GDP growth in IQ2016. Net trade deducted 0.8 percentage points from GDP growth in IIQ2016. Net trade added 0.7 percentage points to GDP growth in IIIQ2016.
  • France. France’s exports decreased 2.2 percent in Sep 2016 while imports decreased 0.6 percent. France’s exports increased 0.9 percent in the 12 months ending in Sep 2016 and imports increased 1.8 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 0.2 percentage points in IIIQ2014. Net trade added 0.2 percentage points to France’s GDP growth in IVQ2014 and deducted 0.2 percentage points in IQ2015. Net trade added 0.4 percentage points to GDP growth in IIQ2015 and deducted 0.6 percentage points in IIIQ2015. Net trade deducted 0.5 percentage points from GDP growth in IVQ2015 and deducted 0.2 percentage points from GDP growth in IQ2016. Net trade added 0.5 percentage points to GDP in IIQ2016. Net trade deducted 0.6 percentage points from GDP in IIIQ2016.
  • United States. US exports increased 0.6 percent in Sep 2016 and goods exports decreased 5.0 percent in Jan-Sep 2016 relative to a year earlier. Imports decreased 1.3 percent in Sep 2016 and goods imports decreased 4.1 percent in Jan-Sep 2016 relative to a year earlier. Net trade added 0.28 percentage points to GDP growth in IIQ2012 and added 0.16 percentage points in IIIQ2012 and 0.58 percentage points in IVQ2012. Net trade added 0.30 percentage points to US GDP growth in IQ2013 and deducted 0.21 percentage points in IIQ2013. Net traded added 0.13 percentage points to US GDP growth in IIIQ2013. Net trade added 1.29 percentage points to US GDP growth in IVQ2013. Net trade deducted 1.16 percentage points from US GDP growth in IQ2014 and deducted 0.41 percentage points in IIQ2014. Net trade added 0.50 percentage points to GDP growth in IIIQ2014. Net trade deducted 1.14 percentage points from GDP growth in IVQ2014 and deducted 1.65 percentage points from GDP growth in IQ2015. Net trade deducted 0.08 percentage points from GDP growth in IIQ2015. Net trade deducted 0.52 percentage points from GDP growth in IIIQ2015. Net trade deducted 0.45 percentage points from GDP growth in IVQ2015. Net trade added 0.01 percentage points to GDP growth in IQ2016. Net trade added 0.18 percentage points to GDP growth in IIQ2016. Net trade added 0.87 percentage points to GDP growth in IIIQ2016. Industrial production changed 0.0 percent in Oct 2016 and decreased 0.2 percent in Sep 2016 after decreasing 0.1 percent in Aug 2016, with all data seasonally adjusted, as shown in Table I-1. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Apr 1, 2016 (http://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] Total IP is now reported to have increased about 2 1/2 percent per year, on average, from 2011 through 2014 before falling 1 1/2 percent in 2015.[2] Relative to earlier reports, the current rates of change are lower, especially for 2014 and 2015. Total IP is now estimated to have returned to its pre-recession peak in November 2014, six months later than previously estimated. Capacity for total industry is now reported to have increased about 2 percent in 2014 and 2015 after having increased only 1 percent in 2013. Compared with the previously reported estimates, the gain in 2015 is 1/2 percentage point higher, and the gain in 2013 is 1/2 percentage point lower. Industrial capacity is expected to increase 1/2 percent in 2016.” 

Manufacturing fell 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increased 16.0 percent from the trough in Apr 2009 to Dec 2015. Manufacturing grew 19.6 percent from the trough in Apr 2009 to Oct 2016. Manufacturing in Oct 2016 is lower by 7.1 percent relative to 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 IIIQ2016 would have accumulated to 29.5 percent. GDP in IIIQ2016 would be $19,414.4 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2702.3 billion than actual $16,712.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 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

0.6 Sep

-5.0

Jan-Sep

-1.3 Sep

-4.1

Jan-Sep

Japan

 

Oct 2016

-10.3

Sep 2016

-6.9

Aug 2016

9.6

Jul 2016

-14.0

Jun 2016

-7.8

May 2016

-11.3

Apr 2016

-10.1

Mar 2016

-6.8

Feb 2016

-4.0

Jan 2016

-12.9

Dec 2015

-8.0

Nov 2015

-3.3

Oct 2015

-2.1

Sep 2015

0.6

Aug

3.1

Jul 2015

7.6

Jun 2015

9.5

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

 

Oct 2016

-16.5

Sep 2016

-16.3

Aug 2016

-17.3

Jul 2016

-24.7

Jun 2016

-18.8

May 2016

-13.8

Apr 2016

-23.3

Mar 2016

-14.9

Feb 2016

-14.2

Jan 2016

-18.0

Dec 2015

-18.0

Nov 2015

-10.2

Oct 2015

-13.4

Sep 2015

-11.1

Aug

-3.1

Jul 2015

-3.2

Jun 2015

-2.9

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

Jan-Dec

2015 -2.8

2016

Oct

-7.3

Sep

-10.0

Aug

-2.8

Jul

-4.4

Jun

-4.8

May

-4.1

Apr

-1.8

Mar

11.5

Feb

-25.4

Jan

-11.2

2015

-1.4 Dec

-6.8 Nov

-6.9 Oct

-3.7 Sep

-5.5 Aug

-8.3 Jul

2.8 Jun

-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

Jan-Dec 2015 -14.1

2016

Oct

-1.4

Sep

-1.9

Aug

1.5

Jul

-12.5

Jun

-2.8

May

-0.4

Apr

-10.6

Mar

-7.6

Feb

-13.8

Jan

-18.8

2015

-7.6 Dec

-8.7 Nov

-18.8 Oct

-20.4 Sep

-13.8 Aug

-8.1 Jul

-6.1 Jun

-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

-9.8 12-M Sep

-2.1 Jan-Sep

-8.0 12-M Sep

-4.2 Jan-Sep

Germany

-0.7 Sep CSA

0.9 Sep

-0.5 Sep CSA

-1.4 Sep

France

Sep

-2.2

-0.9

-0.6

1.8

Italy Sep

-1.6

3.1

-4.5

-2.7

UK

-0.4 Sep

9.4 Jul 16-Sep 16 /Jul 15-Sep 15

2.5 Aug

9.5 Jul 16-Sep 16 /Jul 15-Sep 15

Net Trade % Points GDP Growth

Points

     

USA

IIIQ2016

0.87

IIQ2016

0.18

IQ2016

0.01

IVQ2015

-0.45

IIIQ2015

-0.52

IIQ2015

-0.08

IQ2015

-1.65

IVQ2014

-1.14

IIIQ2014

0.50

IIQ2014

-0.41

IQ2014

-1.16

IVQ2013

1.29

IIIQ2013

0.13

IIQ2013

-0.21

IQ2013

0.30

IVQ2012 +0.58

IIIQ2012

0.16

IIQ2012 0.28

IQ2012 -0.02

     

Japan

0.3

IQ2012

-1.7 IIQ2012

-1.8

IIIQ2012

-0.5 IVQ2012

1.8

IQ2013

-0.5

IIQ2013

-1.3

IIIQ2013

-1.9

IVQ2013

-0.8

IQ2014

3.3

IIQ2014

0.6

IIIQ2014

1.4

IVQ2014

0.4

IQ2015

-1.6

IIQ2015

0.8

IIIQ2015

0.2

IVQ2015

0.5

IQ2016

-1.0

IIQ2016

     

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

0.0

IIQ2014

0.2

IIIQ2014

0.5

IVQ2014

-0.3

IQ2015

-0.1

IIQ2015

0.6

IIIQ2015

-0.5

IVQ2015

-0.6

IQ2016

0.0

IIQ2016

0.5

IIIQ2016

-0.3

     

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

-0.2

IIIQ2014

0.2

IVQ2014

-0.2

IQ2015

0.4

IIQ2015

-0.6

IIIQ2015

-0.5

IVQ2015

-0.2

IQ2016

0.5

IIQ2016

-0.6

IIIQ2016

     

UK

0.7

IIQ2013

-1.7

IIIQ2013

0.1

IVQ2013

0.8

IQ2014

0.3

IIQ2014

-0.7

IIIQ2014

0.3

IVQ2014

-0.4

IQ2015

0.2

IIQ2015

-0.3

IIIQ2015

0.4

IVQ2015

0.0

IQ2016

-0.8

IIQ2016

0.7

IIIQ2016

     

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 Oct 2016. The share of Asia in Japan’s trade is close to one-half for 53.2 percent of exports and 50.8 percent of imports. Within Asia, exports to China are 18.3 percent of total exports and imports from China 26.3 percent of total imports. While exports to China decreased 9.2 percent in the 12 months ending in Oct 2016, imports from China decreased 17.9 percent. The largest export market for Japan in Oct 2016 is the US with share of 20.4 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 decreased 11.2 percent in the 12 months ending in Oct 2016 and imports from the US decreased 9.9 percent. Western Europe has share of 11.5 percent in Japan’s exports and of 13.4 percent in imports. Rates of growth of exports of Japan in Oct 2016 are minus 11.2 percent for exports to the US, minus 32.7 percent for exports to Brazil and minus 4.9 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 Oct 2016 are mixed. Imports from Asia decreased 17.4 percent in the 12 months ending in Oct 2016 while imports from China decreased 17.9 percent. Data are in millions of yen, which may have effects of recent depreciation of the yen relative to the United States dollar (USD) and revaluation of the dollar relative to the euro.

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

Oct 2016

Exports
Millions Yen

12 months ∆%

Imports Millions Yen

12 months ∆%

Total

5,869,904

-10.3

5,373,730

-16.5

Asia

3,122,100

% Total 53.2

-9.9

2,731,560 % Total 50.8

-17.4

China

1,074,786

% Total 18.3

-9.2

1,415,966 % Total 26.3

-17.9

USA

1,197,096

% Total 20.4

-11.2

616,819 % Total

11.5

-9.9

Canada

80,441

4.2

81,758

-11.9

Brazil

22,908

-32.7

52,181

-28.6

Mexico

102,579

-10.5

48,837

3.3

Western Europe

676,851 % Total 11.5

-6.9

721,009 % Total 13.4

-12.1

Germany

168,438

-4.9

196,018

-4.3

France

54,409

-3.1

88,310

-25.8

UK

104,490

-2.0

76,259

-18.2

Middle East

208,902

-26.9

481,316

-23.4

Australia

129,616

1.3

287,705

-7.4

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 decreasing growth of the volume of world trade of goods and services from 2.6 percent in 2015 to 2.3 percent in 2016, increasing to 3.8 percent in 2017. Growth improves to 4.1 percent on average from 2017 to 2021. 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 ∆%

 

2015

2016

2017

Average ∆% 2017-2021

World Trade Volume (Goods and Services)

2.6

2.3

3.8

4.1

Exports Goods & Services

2.7

2.2

3.5

4.0

Imports Goods & Services

2.4

2.3

4.0

4.2

Average Oil Price USD/Barrel

50.79

42.96

50.64

Average ∆% 2008-2017

79.16

Average Annual ∆% Export Unit Value of Manufactures

-2.9

-2.1

1.4

Average ∆% 2008-2017

0.4

Exports of Goods & Services

2015

2016

2017

Average ∆% 2008-2017

EMDE

1.3

2.9

3.6

3.7

G7

3.6

1.8

3.5

2.5

Imports Goods & Services

       

EMDE

-0.6

2.3

4.1

4.5

G7

4.2

2.4

3.9

2.1

Terms of Trade of Goods & Services

       

EMDE

-4.1

-1.0

-0.1

-0.1

G7

1.8

0.9

0.1

0.1

Terms of Trade of Goods

       

EMDE

-4.0

-1.0

0.1

-0.1

G7

1.8

1.2

0.2

0.0

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/2016/02/weodata/index.aspx

The JP Morgan Global All-Industry Output Index of the JP Morgan Manufacturing and Services PMI, produced by JP Morgan and HIS Markit in association with ISM and IFPSM, with high association with world GDP, increased to 53.3 in Oct from 51.7 in Sep, indicating expansion at the rate (https://www.markiteconomics.com/Survey/PressRelease.mvc/dffc698018984829af58ec503a114e9d). This index has remained above the contraction territory of 50.0 during 47 consecutive months. The employment index increased from 50.6 in Sep to 50.9 in Oct with input prices rising at faster rate, new orders increasing at faster rate and output increasing at faster rate (https://www.markiteconomics.com/Survey/PressRelease.mvc/dffc698018984829af58ec503a114e9d). David Hensley, Director of Global Economic Coordination at JP Morgan, finds moderate growth with recent improvement (https://www.markiteconomics.com/Survey/PressRelease.mvc/dffc698018984829af58ec503a114e9d). The JP Morgan Global Manufacturing PMI, produced by JP Morgan and Markit in association with ISM and IFPSM, increased to 52.0 in Oct from 51.0 in Sep (https://www.markiteconomics.com/Survey/PressRelease.mvc/ed078da8ffb0443593d4ffa2bffd8de9). New export orders increased. David Hensley, Director of Global Economic Coordination at JP Morgan, higher growth (https://www.markiteconomics.com/Survey/PressRelease.mvc/ed078da8ffb0443593d4ffa2bffd8de9). The Markit Brazil Composite Output Index decreased from 46.1 in Sep to 44.9 in Oct, indicating contraction in activity of Brazil’s private sector (https://www.markiteconomics.com/Survey/PressRelease.mvc/e93a402c92ff4ee19c7a214dab7aa977). The Markit Brazil Services Business Activity index, compiled by Markit, decreased from 45.3 in Sep to 43.9 in Oct, indicating contracting services activity (https://www.markiteconomics.com/Survey/PressRelease.mvc/e93a402c92ff4ee19c7a214dab7aa977). Pollyanna de Lima, Economist at Markit, finds continuing weakness (https://www.markiteconomics.com/Survey/PressRelease.mvc/e93a402c92ff4ee19c7a214dab7aa977). The Markit Brazil Purchasing Managers’ IndexTM (PMI) increased from 46.0 in Sep to 46.3 in Oct, indicating contraction in manufacturing (https://www.markiteconomics.com/Survey/PressRelease.mvc/5346bb35700c48d682490e93548e6a4c). Pollyanna De Lima, Economist at IHS Markit, finds contraction in manufacturing (https://www.markiteconomics.com/Survey/PressRelease.mvc/5346bb35700c48d682490e93548e6a4c).

VA United States. The Markit Flash US Manufacturing Purchasing Managers’ Index (PMI) seasonally adjusted increased to 53.9 in Nov from 53.4 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/0fb4df36eb034211aa664489c45eb6e0). New export orders increased. Chris Williamson, Chief Business Economist at IHS Markit, finds improvement (https://www.markiteconomics.com/Survey/PressRelease.mvc/0fb4df36eb034211aa664489c45eb6e0). The Markit Flash US Services PMI™ Business Activity Index decreased from 54.8 in Oct to 54.7 in Nov (https://www.markiteconomics.com/Survey/PressRelease.mvc/21666382963f437e9d5232550c13a48d). The Markit Flash US Composite PMI™ Output Index did not change from 54.9 in Oct to 54.9 in Nov. Chris Williamson, Chief Business Economist at IHS Markit, finds that the surveys are consistent with growth at around 2.5 percent in IVQ2016 (https://www.markiteconomics.com/Survey/PressRelease.mvc/21666382963f437e9d5232550c13a48d). The Markit US Composite PMI™ Output Index of Manufacturing and Services increased to 54.9 in Oct from 52.3 in Sep (https://www.markiteconomics.com/Survey/PressRelease.mvc/1ad0a291b1c2475c9592acedd84595c5). The Markit US Services PMI™ Business Activity Index increased from 52.3 in Sep to 54.8 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/1ad0a291b1c2475c9592acedd84595c5). Chris Williamson, Chief Economist at IHS Markit, finds the indexes suggesting faster economic growth (https://www.markiteconomics.com/Survey/PressRelease.mvc/1ad0a291b1c2475c9592acedd84595c5). The Markit US Manufacturing Purchasing Managers’ Index (PMI) increased to 53.4 in Oct from 51.5 in Sep (https://www.markiteconomics.com/Survey/PressRelease.mvc/4f0a49e69e2b4681a90fbff2bcc9b4a3). New foreign orders increased. Chris Williamson, Chief Economist at Markit, finds improving manufacturing (https://www.markiteconomics.com/Survey/PressRelease.mvc/4f0a49e69e2b4681a90fbff2bcc9b4a3). The purchasing managers’ index (PMI) of the Institute for Supply Management (ISM) Report on Business® increased 0.4-percentage points from 51.5 in Sep to 51.9 in Oct, which indicates faster growth (https://www.instituteforsupplymanagement.org/ismreport/mfgrob.cfm?SSO=1). The index of new orders decreased 3.0 percentage points from 55.1 in Sep to 52.1 in Oct. The index of new exports increased 0.5 percentage points from 52.0 in Sep to 52.5 in Oct, expanding at faster rate. The Non-Manufacturing ISM Report on Business® PMI decreased 2.3 percentage points from 57.1 in Sep to 54.8 in Oct, indicating growth of business activity/production during 87 consecutive months, while the index of new orders decreased 2.3 percentage points from 60.0 in Sep to 57.7 in Oct (https://www.instituteforsupplymanagement.org/ISMReport/NonMfgROB.cfm?navItemNumber=30620). Table USA provides the country economic indicators for the US.

Table USA, US Economic Indicators

Consumer Price Index

Oct 12 months NSA ∆%: 1.6; ex food and energy ∆%: 2.1 Oct month SA ∆%: 0.4; ex food and energy ∆%: 0.1
Blog 11/20/16

Producer Price Index

Finished Goods

Oct 12-month NSA ∆%: 0.6; ex food and energy ∆% 1.6
Oct month SA ∆% = 0.4; ex food and energy ∆%: 0.1

Final Demand

Oct 12-month NSA ∆%: 0.8; ex food and energy ∆% 1.2
Oct month SA ∆% = 0.0; ex food and energy ∆%: -0.2
Blog 11/20/16

PCE Inflation

Oct 12-month NSA ∆%: headline 1.4; ex food and energy ∆% 1.7
Blog 12/4/16

Employment Situation

Household Survey: Oct Unemployment Rate SA 4.6%
Blog calculation People in Job Stress Oct: 23.6 million NSA, 14.0% of Labor Force
Establishment Survey:
Oct Nonfarm Jobs +178,000; Private +156,000 jobs created 
Oct 12-month Average Hourly Earnings Inflation Adjusted ∆%: 1.9
Blog 12/4/16

Nonfarm Hiring

Nonfarm Hiring fell from 63.3 million in 2006 to 58.7 million in 2014 or by 4.7 million and to 61.7 million in 2015 or by 1.7 million
Private-Sector Hiring Sep 2016 5.186 million lower by 5.7 percent than 5.502 million in Sep 2006 while population grew 24.7 million or 10.8 percent
Blog 11/13/16

GDP Growth

BEA Revised National Income Accounts
IQ2012/IQ2011 ∆%: 2.8

IIQ2012/IIQ2011 2.5

IIIQ2012/IIIQ2011 2.4

IVQ2012/IVQ2011 1.3

IQ2013/IQ2012 1.3

IIQ2013/IIQ2012 1.0

IIIQ2013/IIIQ2012 1.7

IVQ2013/IVQ2012 2.7

IQ2014/IQ2013 1.6

IIQ2014/IIQ2013 2.4

IIIQ2014/IIIQ2013 2.9

IVQ2014/IVQ2013 2.5

IQ2015/IQ2014 3.3

IIQ2015/IIQ2014 3.0

IIIQ2015/IIIQ2014 2.2

IVQ2015/IVQ2014 1.9

IQ2016/IQ2015 1.6

IIQ2016/IIQ2015 1.3

IIIQ2016/IIIQ2015: 1.6

IQ2012 SAAR 2.7

IIQ2012 SAAR 1.9

IIIQ2012 SAAR 0.5

IVQ2012 SAAR 0.1

IQ2013 SAAR 2.8

IIQ2013 SAAR 0.8

IIIQ2013 SAAR 3.1

IVQ2013 SAAR 4.0

IQ2014 SAAR -1.2

IIQ2014 SAAR 4.0

IIIQ2014 SAAR 5.0

IVQ2014 SAAR 2.3

IQ2015 SAAR 2.0

IIQ2015 SAAR: 2.6

IIIQ2015 SAAR: 2.0

IVQ2015 SAAR: 0.9

IQ2016 SAAR: 0.8

IIQ2016 SAAR: 1.4

IIIQ2016 SAAR: 3.2
Blog 12/04/16

Real Private Fixed Investment

SAAR IIIQ2016 ∆% -0.8 IVQ2007 to IIIQ2016: 7.2% Blog 12/4/16

Corporate Profits

IIIQ2016 SAAR: Corporate Profits 6.6; Undistributed Profits 4.8 Blog 12/4/16

Personal Income and Consumption

Oct month ∆% SA Real Disposable Personal Income (RDPI) SA ∆% 0.4
Real Personal Consumption Expenditures (RPCE): 0.1
12-month Oct NSA ∆%:
RDPI: 2.7; RPCE ∆%: 2.8
Blog 12/4/16

Quarterly Services Report

IIQ16/IQ15 NSA ∆%:
Information 3.8

Financial & Insurance 4.0

Earlier Data:
Blog 3/22/15

Employment Cost Index

Compensation Private IIIQ2016 SA ∆%: 0.5 Sep 12 months ∆%: 2.3

Earlier Data:
Blog 2/1/15

Industrial Production

Oct month SA ∆%: 0.0
Oct 12 months SA ∆%: -0.9

Manufacturing Oct SA 0.2 ∆% Oct 12 months SA ∆% -0.2, NSA -0.1
Capacity Utilization: 75.3
Blog 11/20/16

Productivity and Costs

Nonfarm Business Productivity IIIQ2016∆% SAAE 3.1; IIIQ2016/IIIQ2015 ∆% 0.0; Unit Labor Costs SAAE IIIQ2016 ∆% 0.3; IIIQ2016/IIIQ2015 ∆%: 2.3

Blog 11/6/16

New York Fed Manufacturing Index

General Business Conditions From Oct -6.8 to Nov 1.5
New Orders: From Oct -5.6 to Nov minus 3.1
Blog 11/20/16

Philadelphia Fed Business Outlook Index

General Index from Oct 9.7 to Nov 7.6
New Orders from Oct 16.3 to Nov 18.6
Blog 11/20/16

Manufacturing Shipments and Orders

Sep Orders SA ∆% 0.3 Ex Transport 0.6

Jan-Sep 16/Jan-Sep 15 NSA New Orders ∆% minus 2.3 Ex transport minus 2.9

Earlier data:
Blog 4/5/15

Durable Goods

Oct New Orders SA ∆%: 4.8; ex transport ∆%: 1.0
Jan-Oct 16/Jan-Oct 15 New Orders NSA ∆%: -0.2; ex transport ∆% -0.9

Earlier Data:
Blog 4/26/15

Sales of New Motor Vehicles

Nov 2016 14,479,364; Nov 2015 14,508,727. Nov 16 SAAR 17.87 million, Oct 16 SAAR 18.02 million, Nov 2015 SAAR 18.25 million

Blog 12/4/16

Sales of Merchant Wholesalers

Jan-Sep 2016/Jan-Sep 2015 NSA ∆%: Total -1.2; Durable Goods: minus 0.2; Nondurable
Goods: -2.5

EARLIER DATA:
Blog 4/12/15

Sales and Inventories of Manufacturers, Retailers and Merchant Wholesalers

Sep 16 12-M NSA ∆%: Sales Total Business 1.0; Manufacturers -0.6
Retailers 3.5; Merchant Wholesalers 0.5
Blog 11/20/16

Sales for Retail and Food Services

Jan-Oct 2016/Jan-Oct 2015 ∆%: Retail and Food Services 2.9; Retail ∆% 2.5
Blog 11/20/16

Value of Construction Put in Place

SAAR month SA Sep ∆%: minus 0.4 Jan-Sep 16/Jan-Sep 15 NSA: 4.4

Earlier Data:
Blog 4/5/15

Case-Shiller Home Prices

Aug 2016/ Aug 2015 ∆% NSA: 10 Cities 4.3; 20 Cities: 5.1; National: 5.3
∆% Aug SA: 10 Cities 0.2 ; 20 Cities: 0.2
Blog 10/30/16

FHFA House Price Index Purchases Only

Sep SA ∆% 0.6;
12 month NSA ∆%: 6.1
Blog 11/27/16

New House Sales

Oct 2016 month SAAR ∆%: minus 1.9
Jan-Oct 2016/Jan-Oct 2015 NSA ∆%: 13.1
Blog 11/27/16

Housing Starts and Permits

Oct Starts month SA ∆% 25.5; Permits ∆%: 0.3
Jan-Oct 2016/Jan-Oct 2015 NSA ∆% Starts 5.9; Permits  ∆% 0.7

Earlier Data:
Blog 4/19/15

Rate of Homeownership

IIQ2016: 63.5

Blog 10/30/16

Trade Balance

Balance Sep SA -$36,440 million versus Aug -$40,462 million
Exports Sep SA ∆%: 0.6 Imports Sep SA ∆%: -1.3
Goods Exports Jan-Sep 2016/Jan-Sep 2015 NSA ∆%: minus 5.0
Goods Imports Jan-Sep 2016/Jan-Sep 2015 NSA ∆%: minus 4.1
Blog 11/13/16

Export and Import Prices

Oct 12-month NSA ∆%: Imports -0.2; Exports -1.1

Earlier Data:
Blog 4/12/15

Consumer Credit

Sep ∆% annual rate: Total 6.3; Revolving 5.2; Nonrevolving 6.7

Earlier Data:
Blog 5/10/15

Net Foreign Purchases of Long-term Treasury Securities

Sep Net Foreign Purchases of Long-term US Securities: minus $63.3 billion
Major Holders of Treasury Securities: China $1157.0 billion; Japan $1136.4 billion; Total Foreign US Treasury Holdings Sep $6154.7 billion
Blog 11/20/16

Treasury Budget

Fiscal Year 2017/2016 ∆% Oct: Receipts 5.0; Outlays minus 23.5; Individual Income Taxes 11.3
Deficit Fiscal Year 2011 $1,300 billion

Deficit Fiscal Year 2012 $1,087 billion

Deficit Fiscal Year 2013 $680 billion

Deficit Fiscal Year 2014 $485 billion

Deficit Fiscal Year 2015 $438 billion

Deficit Fiscal Year 2016 $587

Blog 11/13/2016

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 72.6% GDP

2014 Deficit $485 B 2.8% GDP Debt $12,780 B 74.4% GDP

2015 Deficit $438 B 2.5% GDP Debt $13,117 B 73.6% GDP

2026 Deficit $1,343B, 4.9% GDP Debt $23,672B 85.6% GDP

2046: Long-term Debt/GDP 141.1%

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 6/21/15 1/3/16 4/10/16 7/24/16

Commercial Banks Assets and Liabilities

Oct 2016 SAAR ∆%: Securities 11.6 Loans 6.3 Cash Assets -77.4 Deposits minus 0.6

Blog 11/27/16

Flow of Funds Net Worth of Families and Nonprofits

IIQ2016 ∆ since 2007

Assets +$22,869.5 BN

Nonfinancial 3346.9 BN

Real estate $2331.3 BN

Financial +19,522.5 BN

Net Worth +$22,577.4 BN

Blog 9/25/16

Current Account Balance of Payments

IIQ2016 -108,806 MM

% GDP 2.6

Blog 9/25/16

Collapse of United States Dynamism of Income Growth and Employment Creation

Blog 11/27/16

IMF View

World Real Economic Growth 2016 ∆% 3.1 Blog 10/16/16

Income, Poverty and Health Insurance in the United States

43.123 Million Below Poverty in 2015, 13.5% of Population

Median Family Income CPI-2015 Adjusted $56,516 in 2015 back to 1999 Levels

Uncovered by Health Insurance 28.966 Million in 2015

Blog 9/25/16

Monetary Policy and Cyclical Valuation of Risk Financial Assets

Blog 1/17/2016

Links to blog comments in Table USA: 11/27/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-rising-yields-and.html

11/20/16 http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html

11/13/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html

11/6/16 http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html

10/30/16 http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html

10/16/16 http://cmpassocregulationblog.blogspot.com/2016/10/imf-view-of-world-economy-and-finance.html

9/25/16 http://cmpassocregulationblog.blogspot.com/2016/09/the-economic-outlook-is-inherently.html

9/4/16 http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html

7/24/16 http://cmpassocregulationblog.blogspot.com/2016/07/unresolved-us-balance-of-payments.html

4/10/16 http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-reducing.html

1/17/16 http://cmpassocregulationblog.blogspot.com/2016/01/unconventional-monetary-policy-and.html

1/3/16 http://cmpassocregulationblog.blogspot.com/2016/01/weakening-equities-and-dollar.html

10/11/15 http://cmpassocregulationblog.blogspot.com/2015/10/interest-rate-policy-uncertainty-imf.html

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

3/22/15 http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.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 Nov 2016, light vehicle sales accumulated to 15,859,922 million, which is higher by 0.1 percent relative to 15,839,783 a year earlier (http://motorintelligence.com/m_frameset.html). The seasonally adjusted annual rate of light vehicle sales in the US reached 17.87 million in Nov 2016, lower than 18.02 million in Oct 2016 and lower than 18.25 million in Nov 2015 (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 2016. Output virtually stagnated since the late 1990s with recent increase.

clip_image001

Chart VA-1, US, Motor Vehicles and Parts Output, 1972-2016

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, 2015 and IIQ2016. The data show the strong shock to US wealth during the contraction. Assets fell from $81.0 trillion in 2007 to $77.1 trillion in 2011 even after nine consecutive quarters of growth beginning in IIIQ2009 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html), for decline of $3.8 trillion or 4.7 percent. Assets stood at $101.7 trillion in 2015 for gain of $20.8 trillion relative to $81.0 trillion in 2007 or increase by 25.7 percent. Assets increased to $103.8 trillion in IIQ2016 by $22.9 trillion relative to 2007 or 28.3 percent. Liabilities declined from $14.4 trillion in 2007 to $13.6 trillion in 2011 or by $807.3 billion equivalent to decline by 5.6 percent. Liabilities increased $114.1 billion or 0.8 percent from 2007 to 2015. Liabilities increased from $14.4 trillion in 2007 to $14.7 trillion in IIQ2016, by $292.2 billion or increase of 2.0 percent. Net worth shrank from $66.6 trillion in 2007 to $63.5 trillion in 2011, that is, $3.0 trillion equivalent to decline of 4.5 percent. Net worth increased from $66,485.3 billion in 2007 to $89,062.7 billion in IIQ2016 by $22,577.4 billion or 34.0 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 241.038 in Jun 2016 (http://www.bls.gov/cpi/data.htm) or 14.8 percent. Net worth adjusted by CPI inflation increased 16.7 percent from 2007 to IIQ2016. Nonfinancial assets increased $3346.9 billion from $28,072.9 billion in 2007 to $31,419.8 billion in IIQ2016 or 11.9 percent. There was increase from 2007 to IIQ2016 of $2331.3 billion in real estate assets or by 10.0 percent. Real estate assets adjusted for CPI inflation fell 4.1 percent between 2007 and IIQ2016. 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

2015

IIQ2016

Assets

80,880.8

77,098.3

101,679.8

103,750.3

Nonfinancial

28,072.9

23,274.4

30,462.6

31,419.8

  Real Estate

23,263.4

18,148.8

24,756.0

25,594.7

  Durable Goods

  4,476.0

4,723.3

  5,236.8

5,347.4

Financial

52,807.9

53,823.9

71,217.1

72,330.4

  Deposits

  7,562.3

8,702.3

  10,752.5

10,853.6

  Debt Secs.

  4,080.6

4,580.9

  4,568.6

4,242.2

  Mutual Fund Shares

   4,319.1

4,436.5

   6,519.4

6,672.9

  Equities Corporate

   10,046.4

8,403.2

   14,158.2

14,524.3

  Equity Noncorporate

   8,814.8

7,412.8

   10,747.6

10,978.7

  Pension

15,074.8

17,301.3

21,247.6

21,733.0

Liabilities

14,395.4

13,588,1

14,509.5

14,687.6

  Home Mortgages

10,613.0

9,702.2

  9,479.6

9,553.2

  Consumer Credit

   2,609.9

2,758.3

   3,535.7

3,605.3

Net Worth

66,485.3

63,510.1

87,170.2

89,062.7

Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: second quarter 2016. Washington, DC, Federal Reserve System, Sep 16. http://www.federalreserve.gov/releases/z1/.

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

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

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

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

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

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

W = Y/r (1)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

According to Pinto (2008) in testimony to Congress:

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

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

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

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

Table IIA-1 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 95.5 percent in the 10-city composite of the Case-Shiller home price index, 80.5 percent in the 20-city composite and 65.8 percent in the US national home price index between Sep 2000 and Sep 2005. Prices rose around 100 percent from Sep 2000 to Sep 2006, increasing 103.0 percent for the 10-city composite, 88.2 percent for the 20-city composite and 71.9 percent in the US national index. House prices rose 39.2 percent between Sep 2003 and Sep 2005 for the 10-city composite, 34.9 percent for the 20-city composite and 29.6 percent for the US national propelled by low fed funds rates of 1.0 percent between Sep 2003 and Sep 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Sep 2004 until Sep 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 Sep 2003 and Sep 2006, the 10-city index gained 44.5 percent; the 20-city index increased 40.7 percent; and the US national 34.4 percent. House prices have fallen from Sep 2006 to Sep 2016 by 8.8 percent for the 10-city composite and 6.8 percent for the 20-city composite, increasing 0.3 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Sep 2016, house prices increased 4.3 percent in the 10-city composite, increasing 5.1 percent in the 20-city composite and 5.5 percent in the US national. Table IIA-6 also shows that house prices increased 85.5 percent between Sep 2000 and Sep 2016 for the 10-city composite, increasing 75.4 percent for the 20-city composite and 72.5 percent for the US national. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The 10-city composite fell 9.1 percent from the peak in Jun 2006 to Sep 2016 and the 20-city composite fell 7.1 percent from the peak in Jul 2006 to Sep 2016. The US national increased 0.1 percent from the peak of the 10-city composite to Jul 2016 and 0.1 percent from the peak of the 20-city composite to Jul 2016. The final part of Table II-2 provides average annual percentage rates of growth of the house price indexes of Standard & Poor’s Case-Shiller. The average annual growth rate between Dec 1987 and Dec 2015 for the 10-city composite was 3.8 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 2015 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 2015 was 3.7 percent while the rate of the 20-city composite was 3.3 percent and 3.2 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

∆% Sep 2000 to Sep 2003

40.5

33.8

27.9

∆% Sep 2000 to Sep 2005

95.5

80.5

65.8

∆% Sep 2003 to Sep 2005

39.2

34.9

29.6

∆% Sep 2000 to Sep 2006

103.0

88.2

71.9

∆% Sep 2003 to Sep 2006

44.5

40.7

34.4

∆% Sep 2005 to Sep 2016

-5.1

-2.8

4.0

∆% Sep 2006 to Sep 2016

-8.6

-6.8

0.3

∆% Sep 2009 to Sep 2016

29.6

30.8

23.5

∆% Sep 2010 to Sep 2016

27.8

30.2

27.8

∆% Sep 2011 to Sep 2016

32.2

35.1

31.8

∆% Sep 2012 to Sep 2016

29.5

31.1

28.0

∆% Sep 2013 to Sep 2016

14.3

15.8

15.7

∆% Sep 2014 to Sep 2016

9.3

10.6

10.4

∆% Sep 2015 to Sep 2016

4.3

5.1

5.5

∆% Sep 2000 to Sep 2016

85.5

75.4

72.5

∆% Peak Jun 2006 Sep 2016

-9.1

 

0.1

∆% Peak Jul 2006 Sep 2016

 

-7.1

0.1

Average ∆% Dec 1987-Dec 2015

3.8

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 2015

3.7

3.3

3.2

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

Price increases measured by the Case-Shiller house price indices show in data for Sep 2016 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/443948_cshomeprice-release-1129.pdf?force_download=true). Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the 10- and 20-city composites, as shown in Table IIA-2. In Jan 2013, the seasonally adjusted 10-city composite increased 0.8 percent and the 20-city increased 0.9 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city changed 0.0 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. With the exception of Mar through Apr 2012, house prices seasonally adjusted declined in most months for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table IIA-2. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. Without seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Aug 2011 but fell in every month from Sep 2011 to Feb 2012. The not seasonally adjusted index registers decline in Mar 2012 of 0.1 percent for the 10-city composite and is flat for the 20-city composite. Not seasonally adjusted house prices increased 1.4 percent in Apr 2012 and at high monthly percentage rates until Sep 2012. House prices not seasonally adjusted stalled from Oct 2012 to Jan 2013 and surged from Feb to Sep 2013, decelerating in Oct 2013-Feb 2014. House prices grew at fast rates in Mar 2014. The 10-city NSA index increased 0.1 percent in Sep 2016 and the 20-city increased 0.1 percent. The 10-city SA increased 0.2 percent in Sep 2016 and the 20-city composite SA increased 0.4 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

Sep 2016

0.2

0.1

0.4

0.1

Aug

0.3

0.4

0.3

0.4

Jul

0.0

0.5

0.0

0.6

Jun

-0.1

0.7

-0.1

0.8

May

-0.2

0.7

0.0

0.9

Apr

-0.3

1.0

-0.3

1.1

Mar

1.1

0.9

1.2

1.0

Feb

0.6

0.2

0.7

0.2

Jan

0.6

-0.1

0.7

0.0

Dec 2015

0.5

-0.1

0.6

0.0

Nov

0.8

0.0

0.8

0.0

Oct

0.8

-0.1

0.7

0.0

Sep

0.2

0.1

0.4

0.1

Aug

0.1

0.2

0.2

0.3

Jul

0.0

0.6

0.1

0.6

Jun

0.0

0.9

0.1

1.0

May

0.0

1.0

0.1

1.1

Apr

-0.2

1.1

-0.3

1.2

Mar

1.0

0.8

1.1

0.9

Feb

0.9

0.5

0.9

0.5

Jan

0.6

-0.1

0.6

-0.1

Dec 2014

0.7

0.0

0.7

0.0

Nov

0.5

-0.3

0.6

-0.2

Oct

0.8

-0.1

0.7

-0.1

Sep

0.0

-0.1

0.2

-0.1

Aug

0.0

0.2

0.1

0.2

Jul

-0.1

0.6

-0.1

0.6

Jun

0.1

1.0

0.0

1.0

May

0.0

1.1

0.1

1.1

Apr

-0.2

1.1

-0.2

1.2

Mar

1.0

0.8

1.1

0.9

Feb

0.5

0.0

0.5

0.0

Jan

0.7

-0.1

0.6

-0.1

Dec 2013

0.6

-0.1

0.6

-0.1

Nov

0.8

0.0

0.8

-0.1

Oct

1.1

0.2

1.0

0.2

Sep

0.9

0.7

1.0

0.7

Aug

1.1

1.3

1.2

1.3

Jul

1.1

1.9

1.1

1.8

Jun

1.1

2.2

1.1

2.2

May

1.3

2.5

1.3

2.5

Apr

1.5

2.6

1.4

2.6

Mar

1.5

1.3

1.5

1.3

Feb

1.0

0.3

0.9

0.2

Jan

0.8

0.0

0.9

0.0

Dec 2012

0.9

0.2

0.9

0.2

Nov

0.6

-0.3

0.7

-0.2

Oct

0.7

-0.2

0.7

-0.1

Sep

0.5

0.3

0.6

0.3

Aug

0.6

0.8

0.7

0.9

Jul

0.6

1.5

0.7

1.6

Jun

1.0

2.1

1.1

2.3

May

1.0

2.2

1.1

2.4

Apr

0.4

1.4

0.4

1.4

Mar

0.2

-0.1

0.2

0.0

Feb

-0.1

-0.9

0.0

-0.8

Jan

-0.2

-1.1

-0.2

-1.0

Dec 2011

-0.5

-1.2

-0.4

-1.1

Nov

-0.6

-1.4

-0.5

-1.3

Oct

-0.5

-1.3

-0.5

-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

0.0

1.0

Jun

-0.1

1.0

-0.1

1.2

May

-0.2

1.0

-0.2

1.0

Apr

-0.2

0.6

-0.2

0.6

Mar

-0.6

-1.0

-0.7

-1.0

Feb

-0.4

-1.3

-0.3

-1.2

Jan

-0.3

-1.1

-0.3

-1.1

Dec 2010

-0.2

-0.9

-0.2

-1.0

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

Table IIA-4 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2008 and 2009. Total assets fell $10.8 trillion or 13.4 percent from 2007 to 2008 and $9.0 trillion or 11.1 percent to 2009. Net worth fell $10.7 trillion from 2007 to 2008 or 16.1 percent and $8.7 trillion to 2009 or 13.0 percent. Subsidies to housing prolonged over decades together with interest rates at 1.0 percent from Jun 2003 to Jun 2004 inflated valuations of real estate and risk financial assets such as equities. The increase of fed funds rates by 25 basis points until 5.25 percent in Jun 2006 reversed carry trades through exotic vehicles such as subprime adjustable rate mortgages (ARM) and world financial markets. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9).

Table IIA-4, Difference of Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars from 2007 to 2008 and 2009

 

2007

2008

Change to 2008

2009

Change to 2009

A

80,880.8

70,043.0

-10,837.8

71898.4

-8,982.4

Non
FIN

28,072.9

24,376.9

-3,696.0

23,388.0

-4,684.9

RE

23,263.4

19,442.6

-3,820.8

18,431.5

-4,831.9

FIN

52,807.9

45,666.2

-7,141.7

48,510.4

-4,297.5

LIAB

14,395.4

14,279.7

-115.7

14,073.3

-322.1

NW

66,485.3

55,763.3

-10,722.0

57,825.1

-8,660.2

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

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: second quarter 2016. Washington, DC, Federal Reserve System, Sep 16. http://www.federalreserve.gov/releases/z1/.

The apparent improvement in Table IIA-4A is mostly because of increases in valuations of risk financial assets by the carry trade from zero interest rates to leveraged exposures in risk financial assets such as stocks, high-yield bonds, emerging markets, commodities and so on. Zero interest rates also act to increase net worth by reducing debt or liabilities. The net worth of households has become an instrument of unconventional monetary policy by zero interest rates in the theory that increases in net worth increase consumption that accounts for 68.9 percent of GDP in IIQ2016 (http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is_28.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IIQ2016, real estate increased in value by $2331.3 billion and financial assets increased $19,522.5 billion for net gain of real estate and financial assets of $17,191.2 billion, explaining most of the increase in net worth of $22,577.4 billion obtained by deducting the increase in liabilities of $292.2 billion from the increase of assets of $22,869.5 billion. Net worth increased from $66,485.3 billion in 2007 to $89,062.7 billion in IIQ2016 by $22,577.4 billion or 34.0 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 241.038 in Jun 2016 (http://www.bls.gov/cpi/data.htm) or 14.8 percent. Net worth adjusted by CPI inflation increased 16.7 percent from 2007 to IIQ2016. Real estate assets adjusted for CPI inflation fell 4.1 percent from 2007 to IIQ2016. There are multiple complaints that unconventional monetary policy concentrates income on wealthier individuals because of their holdings of financial assets while the middle class has gained less because of fewer holdings of financial assets and higher share of real estate in family wealth. There is nothing new in these arguments. Interest rate ceilings on deposits and loans have been commonly used. The Banking Act of 1933 imposed prohibition of payment of interest on demand deposits and ceilings on interest rates on time deposits. These measures were justified by arguments that the banking panic of the 1930s was caused by competitive rates on bank deposits that led banks to engage in high-risk loans (Friedman, 1970, 18; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 74-5). The objective of policy was to prevent unsound loans in banks. Savings and loan institutions complained of unfair competition from commercial banks that led to continuing controls with the objective of directing savings toward residential construction. Friedman (1970, 15) argues that controls were passive during periods when rates implied on demand deposit were zero or lower and when Regulation Q ceilings on time deposits were above market rates on time deposits. The Great Inflation or stagflation of the 1960s and 1970s changed the relevance of Regulation Q. Friedman (1970, 26-7) predicted the future:

“The banks have been forced into costly structural readjustments, the European banking system has been given an unnecessary competitive advantage, and London has been artificially strengthened as a financial center at the expense of New York.”

In short, Depression regulation exported the US financial system to London and offshore centers. What is vividly relevant currently from this experience is the argument by Friedman (1970, 27) that the controls affected the most people with lower incomes and wealth who were forced into accepting controlled-rates on their savings that were lower than those that would be obtained under freer markets. As Friedman (1970, 27) argues:

“These are the people who have the fewest alternative ways to invest their limited assets and are least sophisticated about the alternatives.” Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 29 quarters from IIIQ2009 to IIIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IIIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp3q16_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2016 would have accumulated to 29.5 percent. GDP in IIIQ2016 would be $19,414.4 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2702.3 billion than actual $16,712.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html and earlier http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html). US GDP in IIIQ2016 is 13.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,712.1 billion in IIIQ2016 or 11.5 percent at the average annual equivalent rate of 1.2 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Oct 1919 to Oct 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.6752 in Oct 2016. The actual index NSA in Oct 2016 is 104.5714, which is 26.2 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 130.0944 in Oct 2016. The output of manufacturing at 104.5714 in Oct 2016 is 19.6 percent below trend under this alternative calculation.

Table IIA-4A, US, Difference of Balance Sheet of Households and Nonprofit Organizations Billions of Dollars from 2007 to 2011, 2015 and IQ2016

 

Value 2007

Change to 2011

Change to 2015

Change to IIQ2016

Assets

80,880.8

-3,782.5

20,799.0

22,869.5

Nonfinancial

28,072.9

-4,798.5

2,389.7

3,346.9

Real Estate

23,263.4

-5,114.6

1,492.6

2,331.3

Financial

52,807.9

1,016

18,409.2

19,522.5

Liabilities

14,395.4

-807.3

114.1

292.2

Net Worth

66,485.3

-2,975.2

20,684.9

22,577.4

Net Worth = Assets – Liabilities

Source: Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2016. Flow of funds, balance sheets and integrated macroeconomic accounts: second quarter 2016. Washington, DC, Federal Reserve System, Sep 16. http://www.federalreserve.gov/releases/z1/.

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 2015. 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 1.4 percent in 2013 and stagnated in 2014 at 0.0. The GDP of Japan increased 0.6 percent in 2015. 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 2015 is 1.0 percent higher than in calendar year 2007. Japan’s real GDP grew 8.1 percent from the trough of 2009 to 2015 at the average yearly rate of 1.3 percent (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

1.4

2014

0.0

2015

0.6

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/mopo/outlook/gor1510b.pdf) with changes on Apr 29, 2016 (https://www.boj.or.jp/en/mopo/outlook/gor1604b.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 2015, the forecast is of growth of GDP between 0.7 to 0.7 percent, with the all items CPI less fresh food of 0.0 percent (https://www.boj.or.jp/en/mopo/outlook/gor1604b.pdf). The critical difference is forecast of the CPI excluding fresh food of 0.0 to 0.2 percent in 2016 and 1.8 to 3.0 percent in 2017 (https://www.boj.or.jp/en/mopo/outlook/gor1604b.pdf). Consumer price inflation in Japan excluding fresh food was 0.1 percent in Mar 2016 and minus 0.3 percent in 12 months (http://www.stat.go.jp/english/data/cpi/1581.htm). The CPI increased 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).
  6. Quantitative and Qualitative Monetary Easing (QQE) with Negative Nominal Interest Rate. On January 29, 2016, the Policy Board of the Bank of Japan introduced a new policy to attain the “price stability target of 2 percent at the earliest possible time” (https://www.boj.or.jp/en/announcements/release_2016/k160129a.pdf). The new framework consists of three dimensions: quantity, quality and interest rate. The interest rate dimension consists of rates paid to current accounts that financial institutions hold at the Bank of Japan of three tiers zero, positive and minus 0.1 percent. The quantitative dimension consists of increasing the monetary base at the annual rate of 80 trillion yen. The qualitative dimension consists of purchases by the Bank of Japan of Japanese government bonds (JGBs), exchange traded funds (ETFs) and Japan real estate investment trusts (J-REITS).
  7. Quantitative and Qualitative Easing with Yield Curve Control. The Bank of Japan introduced a new approach, QQE with Yield Curve Control (“Quantitative and Qualitative Easing with Yield Curve Control”) at its policy meeting on Sep 21, 2016 (https://www.boj.or.jp/en/announcements/release_2016/k160921a.pdf). The policy consists of two measures. First “yield curve control” consists of controlling the long-term and short-term interest rates. The bank will fix the interest rates of policy balances held by financial institutions at the BOJ at minus 0.1 percent and will purchase Japanese Government Bonds (JGB) in the amount required to maintain the yield of the 10-year JGB at around zero percent. Second, “the inflation-overshooting commitment” consists of increasing base money to maintain the CPI price stability target above 2 percent.

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

     

Feb 2016

+0.7 to +0.7

[+0.7]

0.0

 

Jan 2016

+1.0 to +1.3

[+1.1]

0.0 to 0.2

[+0.1]

 

Oct 2015

+0.8 to +1.4

[+1.2]

0.0 to +0.4

[+0.1

 

Jul 2015

+1.5 to +1.9

[+1.7]

+0.3 to +1.0

[+0.7]

 

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

     

Jul 2016

+0.8 to +1.0

[+1.0]

0.0 to +0.3

[0.5]

0.0 to +0.3

[0.5]

Apr 2016

+0.8 to +1.4

[+1.2]

0.0 to +0.8

[+0.5]

0.0 to +0.8

[+0.5]

Jan 2016

+1.0 to +1.7

[+1.5]

0.2 to +1.2

[+0.8]

 

Oct 2015

+1.2 to +1.6

[+1.4]

+0.8 to +1.5

[+1.4]

 

Jul 2015

+1.5 to 1.7

[+1.5]

+1.2 to +2.1

[+1.9]

 

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

     

Jul 2016

1.0 to +1.5
[+1.3]

+0.8 to +1.8
[+1.7]

+0.8 to +1.8
[+1.7]

Apr 2016

0.0 to + +0.3

[+0.1]

1.8 to +3.0

[+2.7]

0.8 to +2.0

[+1.7

Jan 2016

+0.1 to + 0.5

[+0.3]

+2.0 to +3.1

[+2.8]

+ 1.0 to +2.1

[+1.8]

Oct 2015

+0.1 to +0.5

[+0.3]

+2.5 to +3.4

[+3.1]

+1.2 to 2.1

[+1.8]

Jul 2015

+0.1 to +0.5

[+0.2]

+2.7 to +3.4

[+3.1]

+1.4 to +2.1

[+1.8]

Apr 2015

+0.1 to +0.5

[+0.2]

+2.7 to +3.4

[+3.2]

+1.4 to +2.1

[+1.9]

2018

     

Jul 2016

+0.8 to +1.0
[+0.9]

+1.0 to +2.0
[+1.9]

+1.0 to +2.0
[+1.9]

Apr 2016

+0.6 to +1.2

[+1.0]

+1.0 to +2.1

[+1.9]

+1.0 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

https://www.boj.or.jp/en/mopo/outlook/gor1510b.pdf

https://www.boj.or.jp/en/mopo/outlook/gor1601b.pdf

https://www.boj.or.jp/en/mopo/outlook/gor1604b.pdf

https://www.boj.or.jp/en/mopo/outlook/gor1607b.pdf

The Nikkei Flash Japan Manufacturing PMI Index™ with the Flash Japan

Manufacturing PMI™ decreased from 51.4 in Oct to 51.1 in Nov and the Flash Japan

Manufacturing Output Index™ decreased from 53.3 in Oct to 52.2 in Nov

(https://www.markiteconomics.com/Survey/PressRelease.mvc/009dc4ad244944ae88372f371c15c572). New export orders increased. Amy Brownbill, Economist at IHS

Markit, finds improving conditions

(https://www.markiteconomics.com/Survey/PressRelease.mvc/c40b1f2a7a294bffadc542ae2307cb8d).The Nikkei Composite Output PMI Index increased from 48.9 in Sep to 51.3 in Oct, indicating strengthening business activity (https://www.markiteconomics.com/Survey/PressRelease.mvc/ab4a6193c5cc4a4595889676b4025d92). The Nikkei Business Activity Index of Services increased to 50.5 in Oct from 48.2 in Sep (https://www.markiteconomics.com/Survey/PressRelease.mvc/ab4a6193c5cc4a4595889676b4025d92). Amy Brownbill, Ecoomist at IHS Markit and author of the report, finds improving business activity (https://www.markiteconomics.com/Survey/PressRelease.mvc/ab4a6193c5cc4a4595889676b4025d92). The Nikkei Purchasing Managers’ Index (PMI™), seasonally adjusted, increased from 50.4 in Sep to 51.4 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/6bd7d9f007ff4b4897f9043950811805). New orders increased while new foreign orders expanded. Amy Brownbill, Economist at IHS Markit, finds improving output in manufacturing (https://www.markiteconomics.com/Survey/PressRelease.mvc/6bd7d9f007ff4b4897f9043950811805).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

Oct ∆% -0.1
12 months ∆% -2.7
Blog 11/13/16

Consumer Price Index

Oct NSA ∆% 0.6; Oct 12 months NSA ∆% 0.1
Blog 11/27/16

Real GDP Growth

IIIQ2016 ∆%: 0.5 on IIQ2016;  IIIQ2016 SAAR 2.2;
∆% 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 8/23/15 9/13/15 11/22/15 12/13/15 2/21/16 3/13/16 5/22/16 6/12/16 8/21/16 9/11/16 11/20/16

Employment Report

Oct Unemployed 1.95 million

Change in unemployed since last year: -130 thousand
Unemployment rate: 3.0%
Blog 12/4/16

All Industry Indices

Aug month SA ∆% 0.2
12-month NSA ∆% 1.7

Earlier Data:

Blog 4/26/15

Industrial Production

Aug SA month ∆%: 1.5
Aug 12-month NSA ∆% 4.6

Earlier Data:
Blog 3/29/15

Machine Orders

Total Sep ∆% 0.9

Private ∆%: -0.7 Sep ∆% Excluding Volatile Orders minus 3.3

Earlier Data:
Blog 4/19/15

Tertiary Index

Jul month SA ∆% 0.3
Jul 12 months NSA ∆% 0.1

Earlier Data:
Blog 4/26/15

Wholesale and Retail Sales

Aug 12 months:
Total ∆%: -3.1
Wholesale ∆%: -3.6
Retail ∆%: -2.1

Earlier Data:
Blog 3/29/15

Family Income and Expenditure Survey

Sep 12-month ∆% total nominal consumption -2.6, real -2.1

Earlier Data:

Blog 3/29/15

Trade Balance

Exports Oct 12 months ∆%: minus 10.3 Imports Oct 12 months ∆% -16.5

Earlier Data:

Blog 4/26/15

Links to blog comments in Table JPY: 11/27/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-rising-yields-and.html

11/20/16 http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html

11/13/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html

10/30/16 http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html

9/11/16 http://cmpassocregulationblog.blogspot.com/2016/09/interest-rate-uncertainty-and-valuation.html

8/21/16 http://cmpassocregulationblog.blogspot.com/2016/08/interest-rate-policy-uncertainty-and.html

6/12/16 http://cmpassocregulationblog.blogspot.com/2016/06/considerable-uncertainty-about-economic.html

5/22/16 http://cmpassocregulationblog.blogspot.com/2016/05/most-fomc-participants-judged-that-if.html

3/13/16 http://cmpassocregulationblog.blogspot.com/2016/03/monetary-policy-and-fluctuations-of_13.html

12/13/15 http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-interest-rates-with-volatile_17.html

11/22/15 http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-liftoff-followed-by.html

9/13/15 http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what_13.html

08/23/15 http://cmpassocregulationblog.blogspot.com/2015/08/global-decline-of-values-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

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

Table VB-1 provides the employment report of Japan in Oct 2016. The rate of unemployment not seasonally adjusted reached 2.9 percent, decreasing 0.2 percentage points from a year earlier. Population changed 0.0 percent from a year earlier. The labor force increased 0.8 percent from a year earlier and the labor participation rate stood at 60.4, increasing 0.5 percentage points from a year earlier. The employment rate moved to 58.6 percent, increasing 0.6 percentage points relative to a year earlier.

Table VB-1, Japan, Employment Report Oct 2016

Oct 2016 Unemployed

1.95 million

Change since last year

-130 thousand; ∆% -6.3

Unemployment rate

SA 3.0%, 0.0 from earlier month;

NSA 2.9%, -0.2 from earlier year

Population ≥ 15 years

110.83 million

Change since last year

∆% 0.0

Labor Force

66.90 million

Change since last year

∆% 0.8

Employed

64.95 million

Change since last year

∆% 1.0

Labor force participation rate

60.4

Change since last year

0.5

Employment rate

58.6%

Change since last year

0.6

Source: Japan, Statistics Bureau, Ministry of Internal Affairs and Communications

http://www.stat.go.jp/english/data/roudou/results/month/index.htm

Table VB-2 provides the rate of unemployment of Japan seasonally adjusted that decreased to 3.4 percent in Dec 2014 from 4.4 percent in Jul 2012. The rate of unemployment SA fell 0.2 percentage points from 3.2 percent in Oct 2015 to 3.0 percent in Oct 2016.

Table VB-2, Japan, Unemployment Rate, SA

 

Unemployment Rate SA

Oct 2016

3.0

Sep

3.0

Aug

3.1

Jul

3.0

Jun

3.1

May

3.2

Apr

3.2

Mar

3.2

Feb

3.3

Jan

3.2

Dec 2015

3.3

Nov

3.3

Oct

3.2

Sep

3.4

Aug

3.4

Jul

3.3

Jun

3.4

May

3.3

Apr

3.4

Mar

3.4

Feb

3.5

Jan

3.5

Dec 2014

3.4

Nov

3.5

Oct

3.6

Sep

3.5

Aug

3.5

Jul

3.7

Jun

3.7

May

3.6

Apr

3.6

Mar

3.6

Feb

3.6

Jan

3.7

Dec 2013

3.7

Nov

3.9

Oct

4.0

Sep

4.0

Aug

4.1

Jul

3.8

Jun

3.9

May

4.1

Apr

4.1

Mar

4.1

Feb

4.3

Jan

4.2

Dec 2012

4.3

Nov

4.1

Oct

4.1

Sep

4.3

Aug

4.2

Jul

4.4

Jun

4.3

May

4.4

Source: Source: Japan, Statistics Bureau, Ministry of Internal Affairs and Communications

http://www.stat.go.jp/english/data/roudou/results/month/index.htm

Chart VB-1 of Japan’s Statistics Bureau at the Ministry of Internal Affairs and Communications provides the unemployment rate of Japan from 2012 to 2016. There is clear trend of decline with multiple oscillations and increase in Jun-Jul 2014. The rate increased in Sep 2014 and fell in Oct 2014, stabilizing in Nov 2014 and declining in Dec 2014. The rate decreased in Feb-Apr 2015, stabilizing in May 2015. The rate increased in Jun 2015 and fell in Jul 2015, increasing in Aug 2015 and stabilizing in Sep 2015. The rate fell in Oct 2015, increasing in Nov 2015, remaining unchanged in Dec 2015 and decreasing in Jan 2016. The rate increased in Feb 2016 and decreased in Mar 2016, stabilizing in Apr-May 2016. The rate decreased in Jun-Jul 2016, increasing in Aug 2016. The rate decreased in Sep 2016, stabilizing in Oct 2016.

clip_image002

Chart VB-1, Japan, Unemployment Rate, Seasonally Adjusted

Source: Japan, Statistics Bureau, Ministry of Internal Affairs and Communications

http://www.stat.go.jp/english/data/roudou/results/month/index.htm

During the “lost decade” of the 1990s from 1991 to 2002 (Pelaez and Pelaez, The Global Recession Risk (2007), 82-3), Japan’s GDP grew at the average yearly rate of 1.0 percent, the CPI at 0.1 percent and the implicit deflator at minus 0.8 percent. Japan’s growth rate from the mid-1970s to 1992 was 4 percent (Ito 2004). Table VB-3 provides Japan’s rates of unemployment, participation in labor force and employment for selected years from 1953 to 1985 and yearly from 1990 to 2014. The rate of unemployment jumped from 2.1 percent in 1991 to 5.4 percent in 2002, which was a year of global economic weakness. The participation rate dropped from 64.0 percent in 1992 to 61.2 percent in 2002 and the employment rate fell from 62.6 percent in 1992 to 57.9 percent in 2002. The rate of unemployment rose from 3.9 percent in 2007 to 5.1 percent in 2010, falling to 4.6 percent in 2011, 4.3 percent in 2012 and 3.6 percent in 2014. The rate of unemployment fell to 3.4 percent in 2015. The participation rate fell from 60.4 percent in 2007 to 59.6 percent in 2010, falling to 59.3 percent in 2011 and 59.1 in 2012 and increasing to 59.4 percent in 2014. The participation rate increased to 59.6 in 2015. The employment rate fell from 58.1 in percent in 2007 to 56.6 percent in 2010 and 56.5 percent in 2011 and 2012, increasing to 57.3 percent in 2014. The employment rate increased to 57.6 in 2015. The global recession adversely affected labor markets in advanced economies.

Table VB-3, Japan, Rates of Unemployment, Participation in Labor Force and Employment, %

 

Participation
Rate

Employment Rate

Unemployment Rate

1953

70.0

68.6

1.9

1960

69.2

68.0

1.7

1965

65.7

64.9

1.2

1970

65.4

64.6

1.1

1975

63.0

61.9

1.9

1980

63.3

62.0

2.0

1985

63.0

61.4

2.6

1990

63.3

61.9

2.1

1991

63.8

62.4

2.1

1992

64.0

62.6

2.2

1993

63.8

62.2

2.5

1994

63.6

61.8

2.9

1995

63.4

61.4

3.2

1996

63.5

61.4

3.4

1997

63.7

61.5

3.4

1998

63.3

60.7

4.1

1999

62.9

59.9

4.7

2000

62.4

59.5

4.7

2001

62.0

58.9

5.0

2002

61.2

57.9

5.4

2003

60.8

57.6

5.3

2004

60.4

57.6

4.7

2005

60.4

57.7

4.4

2006

60.4

57.9

4.1

2007

60.4

58.1

3.9

2008

60.2

57.8

4.0

2009

59.9

56.9

5.1

2010

59.6

56.6

5.1

2011

59.3

56.5

4.6

2012

59.1

56.5

4.3

2013

59.3

56.9

4.0

2014

59.4

57.3

3.6

2015

59.6

57.6

3.4

Source: Japan, Statistics Bureau, Ministry of Internal Affairs and Communications

http://www.stat.go.jp/english/data/roudou/results/month/index.htm

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 54.0 in Oct 2016. 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 50.9 in Oct 2016.

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

 

Total Index

New Orders

Interm.
Input Prices

Subs Prices

Exp

Oct 2016

54.0

50.9

53.7

51.5

60.6

Sep

53.7

51.4

51.7

50.1

61.1

Aug

53.5

49.8

52.6

50.4

59.4

Jul

53.9

49.9

51.4

49.5

59.5

Jun

53.7

50.8

51.6

50.6

58.6

May

53.1

49.2

51.6

49.8

57.8

Apr

53.5

48.7

52.1

49.1

59.1

Mar

53.8

50.8

51.4

49.5

59.0

Feb

52.7

48.7

50.5

48.3

59.5

Jan

53.5

49.6

49.9

47.7

58.4

Dec2015

54.4

51.7

49.0

48.2

58.3

Nov

53.6

50.2

49.3

47.7

60.0

Oct

53.1

51.2

51.2

48.8

61.1

Sep

53.4

50.2

50.8

47.9

60.0

Aug

53.4

49.6

49.6

47.8

59.7

Jul

53.9

50.1

48.9

47.4

60.0

Jun

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 54.0 in Oct 2016.

clip_image003

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 50.3 in Jul 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 51.2 in Oct 2016. 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 52.8 in Oct 2016.

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

 

IPM

PI

NOI

INV

EMP

SDEL

2016

           

Oct

51.2

53.3

52.8

48.1

48.6

50.2

Sep

50.4

52.8

50.9

47.4

48.6

49.9

Aug

50.4

52.6

51.3

47.6

48.4

50.6

Jul

49.9

52.1

50.4

47.3

48.2

50.5

Jun

50.0

52.5

50.5

47.0

47.9

50.7

May

50.1

52.3

50.7

47.6

48.2

50.4

Apr

50.1

52.2

51.0

47.4

47.8

50.1

Mar

50.2

52.3

51.4

48.2

48.1

51.3

Feb

49.0

50.2

48.6

48.0

47.6

49.8

Jan

49.4

51.4

49.5

46.8

47.8

50.5

2015

           

Dec

49.7

52.2

50.2

47.6

47.4

50.7

Nov

49.6

51.9

49.8

47.1

47.6

50.6

Oct

49.8

52.2

50.3

47.2

47.8

50.6

Sep

49.8

52.3

50.2

47.5

47.9

50.8

Aug

49.7

51.7

49.7

48.3

47.9

50.6

Jul

50.0

52.4

49.9

48.4

48.0

50.4

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 51.2 in Oct 2016.

clip_image004

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

Source: National Bureau of Statistics of China

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

Growth of China’s GDP in IIIQ2016 relative to the same period in 2015 was 6.7 percent and cumulative growth to IIIQ2016 was 6.7 percent, as shown in Table VC-GDP. Secondary industry accounts for 39.5 percent of cumulative GDP in IIIQ2016. In cumulative IIIQ2016, industry accounts for 33.4 percent of GDP and construction for 6.3 percent. Tertiary industry accounts for 52.8 percent of cumulative GDP in IIIQ2016 and primary industry for 7.7 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 by increasing growth of services. The bottom block of Table VC-1 provides quarter-on-quarter growth rates of GDP and their annual equivalent. China’s GDP growth decelerated significantly from annual equivalent 10.0 percent in IQ2011 to 6.1 percent in IVQ2011 and 7.8 percent in IQ2012, rebounding to 9.1 percent in IIQ2012, 7.4 percent in IIIQ2012 and 7.8 percent in IVQ2012. Annual equivalent growth in IQ2013 eased to 7.8 percent and to 7.0 percent in IIQ2013, rebounding to 8.7 percent in IIIQ2013. Annual equivalent growth was 6.6 percent in IVQ2013, increasing to 7.0 percent in IQ2014 and increasing to 7.4 percent in IIQ2014. Annual equivalent growth stabilized 7.4 percent in IIIQ2014 and 7.4 percent in IVQ2014. Growth slowed to annual equivalent 6.6 percent in IQ2015, increasing to 7.8 percent in IIQ2015 and 7.0 percent in IIIQ2015. Growth slowed to 6.6 percent in annual equivalent in IVQ2015 and 4.9 percent in IQ2016. Growth increased to annual equivalent 7.8 percent in IIQ2016 and 7.4 percent in IIIQ2016.

Table VC-1 China, Quarterly Growth of GDP, Current CNY 100 Million and Inflation Adjusted ∆%

Cumulative GDP IIIQ2015

Value Current CNY Billion IIIQ2016

Value Current CNY Billion IQ2016 to IIIQ2016

IIIQ2016 Year-on-Year Constant Prices ∆%

Cumulative to IIIQ2016

∆%

GDP

18,933.4

52,997.1

6.7

6.7

Primary Industry

1,856.9

4,066.6

4.0

3.5

Farming

1,918.4

4,211.6

4.1

3.7

Secondary Industry

7,516.5

20,941.5

6.1

6.1

Industry

6,251.8

17,710.1

6.1

6.0

Construction

1,331.5

3,319.3

6.0

6.9

Tertiary Industry

9,560.1

27,989.0

7.6

7.6

Transport, Storage, Post

862.4

2,416.0

6.5

5.3

Wholesale, Retail Trades

1,785.0

5,119.1

7.0

6.4

Accommodation and Restaurants

339.0

954.1

6.5

6.8

Finance

1,527.4

4,649.3

5.6

6.3

Real Estate

1,204.3

3,453.7

8.8

8.9

Other

3,749.7

11,163.9

8.8

8.9

Growth in Quarter Relative to Prior Quarter

∆% on Prior Quarter

 

∆% Annual Equivalent

∆% Year-on-Year

2016

       

IIIQ2016

1.8

 

7.4

6.7

IIQ2016

1.9

 

7.8

6.7

IQ2016

1.2

 

4.9

6.7

2015

       

IVQ2015

1.6

 

6.6

6.8

IIIQ2015

1.7

 

7.0

6.9

IIQ2015

1.9

 

7.8

7.0

IQ2015

1.6

 

6.6

7.0

2014

       

IVQ2014

1.8

 

7.4

7.2

IIIQ2014

1.8

 

7.4

7.1

IIQ2014

1.8

 

7.4

7.5

IQ2014

1.7

 

7.0

7.4

2013

       

IVQ2013

1.6

 

6.6

7.7

IIIQ2013

2.1

 

8.7

7.9

IIQ2013

1.7

 

7.0

7.6

IQ2013

1.9

 

7.8

7.9

2012

       

IVQ2012

1.9

 

7.8

8.1

IIIQ2012

1.8

 

7.4

7.5

IIQ2012

2.2

 

9.1

7.6

IQ2012

1.9

 

7.8

8.1

2011

       

IVQ2011

1.5

 

6.1

8.8

IIIQ2011

1.9

 

7.8

9.4

IIQ2011

2.4

 

10.0

10.0

IQ2011

2.4

 

10.0

10.2

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

Growth of China’s GDP in IIIQ2016 relative to the same period in 2015 was 6.7 percent and cumulative growth to IIIQ2016 was 6.7 percent, as shown in Table VC-GDP. Secondary industry accounts for 39.5 percent of cumulative GDP in IIIQ2016. In cumulative IIIQ2016, industry accounts for 33.4 percent of GDP and construction for 6.3 percent. Tertiary industry accounts for 52.8 percent of cumulative GDP in IIIQ2016 and primary industry for 7.7 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 by increasing growth of services. Table VC-GDPA shows that growth decelerated from 12.1 percent in IQ2010 and 11.2 percent in IIQ2010 to 7.9 percent in IQ2013, 7.6 percent in IIQ2013 and 7.9 percent in IIIQ2013. GDP grew 7.7 percent in IVQ2013 relative to a year earlier and 1.6 percent relative to IIIQ2013, which is equivalent to 6.6 percent per year. GDP grew 7.4 percent in IQ2014 relative to a year earlier and 1.7 percent in IQ2014 that is equivalent to 7.0 percent per year. GDP grew 7.5 percent in IIQ2014 relative to a year earlier and 1.8 percent relative to the prior quarter, which is annual equivalent 7.4 percent. In IIIQ2014, GDP grew 7.1 percent relative to a year earlier and 1.8 percent relative to the prior quarter, which is 7.4 percent in annual equivalent. GDP grew 1.8 percent in IVQ2014, which is 7.4 percent in annual equivalent and 7.2 percent relative to a year earlier. In IQ2015, GDP grew 1.6 percent, which is equivalent to 6.6 in a year and 7.0 percent relative to a year earlier. GDP grew 1.9 percent in IIQ2015, which is equivalent to 7.8 percent in a year, and grew 7.0 percent relative to a year earlier. GDP grew at 1.7 percent in IIIQ2015, which is equivalent to 7.0 percent in a year, and grew 6.9 percent relative to a year earlier. GDP grew at 1.6 percent in IVQ2015, which is equivalent to 6.6 percent in a year and increased 6.8 percent relative to a year earlier. In IQ2016, GDP grew at 1.2 percent, which is equivalent to 4.9 percent, and increased 6.7 percent relative to a year earlier. GDP grew at 1.9 percent in IIQ2016, which is annual equivalent to 7.8 percent, and increased 6.7 percent relative to a year earlier. In IIIQ2016, GDP grew at 1.8 percent, which is equivalent to 7.4 percent in a year and increased 6.7 percent relative to a year earlier.

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

 

IQ2015

IIQQ2015

IIIQ2015

IVQ2015

IQ2016

IIQ2016

IIIQ2016

 

GDP

7.0

7.0

6.9

6.8

6.7

6.7

6.7

 

Primary Industry

3.2

3.5

3.8

4.1

2.9

3.1

3.5

 

Secondary Industry

6.4

6.1

6.0

6.1

5.8

6.3

6.1

 

Tertiary Industry

7.9

8.4

8.4

8.2

7.6

7.5

7.6

 

GDP ∆% Relative to a Prior Quarter

1.6

1.9

1.7

1.6

1.2

1.9

1.8

 
 

IQ 2013

IIQ 2013

IIIQ 2013

IVQ 2013

IQ

2014

IIQ 2014

IIIQ 2014

IVQ

2014

GDP

7.9

7.6

7.9

7.7

7.4

7.5

7.1

7.2

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

1.9

1.7

2.1

1.6

1.7

1.8

1.8

1.8

 

IQ 2011

IIQ 2011

IIIQ 2011

IVQ 2011

IQ 

2012

IIQ 2012

IIIQ 2012

IVQ 2012

GDP

10.2

10.0

9.4

8.8

8.1

7.6

7.5

8.1

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

2.4

2.4

1.9

1.5

1.9

2.2

1.8

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.

clip_image005

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

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.

clip_image006

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.

clip_image007

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 Caixin Flash China General Manufacturing Purchasing Managers’ Index (PMI) compiled by Markit (http://www.markiteconomics.com/Survey//PressRelease.mvc/883014a121534f51bc42e5060845f727) is mixed. The overall Flash Caixin China General Manufacturing PMI decreased from 47.3 in Aug to 47.0 in Sep, while the Flash Caixin China General Manufacturing Output Index decreased from 46.4 in Aug to 45.7 in Aug, indicating weaker conditions. He Fan, Chief Economist at Caixin Insight Group finds need of fiscal and monetary policy (http://www.markiteconomics.com/Survey//PressRelease.mvc/883014a121534f51bc42e5060845f727). The Caixin China General Services PMI, compiled by Markit, shows the Caixin Composite Output, combining manufacturing and services, increasing from 51.4 in Sep to 52.9 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/a472974d580444bd95a6aa45e9363881). Zhengsheng Zhong, Director of Macroeconomic Analysis at CEBM Group, finds improving activity (https://www.markiteconomics.com/Survey/PressRelease.mvc/a472974d580444bd95a6aa45e9363881). The Caixin General Manufacturing PMI increased to 51.2 in Oct from 50.1 in Se[, indicating growth conditions in manufacturing (https://www.markiteconomics.com/Survey/PressRelease.mvc/635032b6e6ad4649af59753f2e0acea2). Zhengsheng Zhong, Director of Macroeconomic Analysis at CEBM Group, finds improving conditions (https://www.markiteconomics.com/Survey/PressRelease.mvc/635032b6e6ad4649af59753f2e0acea2). Table CNY provides the country data table for China.

Table CNY, China, Economic Indicators

Price Indexes for Industry

Oct 12-month ∆%: 0.7

Oct month ∆%: 1.2
Blog 11/13/16

Consumer Price Index

Oct 12-month ∆%: 2.1 Oct month ∆%: -0.1
Blog 11/13/16

Value Added of Industry

Aug month ∆%: 0.53

Jan-Aug 2016/Jan-Aug 2015 ∆%: 6.0

Earlier Data
Blog 4/19/15

GDP Growth Rate

Year IIIQ2016 ∆%: 6.7

III Quarter 2016 ∆%: 1.8
Quarter IIIQ2016 AE ∆%: 7.4
Blog 11/6/16

Investment in Fixed Assets

Total Jan-Aug 2015 ∆%: 8.1

Real estate development: 5.4

Earlier Data:
Blog 4/19/15

Retail Sales

Aug month ∆%: 0.83
Jan-Aug 2016 ∆%:10.3

Earlier Data:
Blog 4/19/15

Trade Balance

Oct balance $49.06 billion
Exports 12M ∆% -7.3
Imports 12M ∆% -1.4

2015 Exports ∆% -2.8

2015 Imports ∆% -14.1

Cumulative Oct 2016: $441.6 billion

Cumulative Oct 2015: $485.9

Earlier Data:
Blog 4/19/15

Links to blog comments in Table CNY: 11/13/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html

11/6/16 http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.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 (19 countries) fell 5.7 percent from IQ2008 to IIQ2009. The GDP of the euro area (19 countries) increased 7.6 percent from IIIQ2009 to IIQ2016 at the annual equivalent rate of 1.0 percent.  The GDP of the euro area (19 countries) is higher by 1.4 percent in IIQ2016 relative to the pre-recession peak in IQ2008, growing at annual equivalent rate of 0.2 percent. 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 3.2 percent in 2006 and 3.0 percent in 2007. The global recession had strong impact with growth of only 0.4 percent in 2008 and decline of 4.5 percent in 2009. Recovery was at lower growth rates of 2.1 percent in 2010 and 1.5 percent in 2011. EUROSTAT estimates growth of GDP of the euro area of minus 0.9 percent in 2012 and minus 0.3 percent in 2013. Euro Area GDP grew 1.1 percent in 2014 and grew 2.0 percent in 2015.

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

3.0

2000

2.2

8.9

3.8

2001

2.4

8.3

2.1

2002

2.3

8.6

1.0

2003

2.1

9.1

0.7

2004

2.2

9.3

2.3

2005

2.2

9.1

1.7

2006

2.2

8.4

3.2

2007

2.2

7.5

3.0

2008

3.3

7.6

0.4

2009

0.3

9.6

-4.5

2010

1.6

10.2

2.1

2011

2.7

10.2

1.5

2012

2.5

11.4

-0.9

2013

1.3

12.0

-0.3

2014

0.4

11.6

1.1

2015

0.0

10.9

2.0

http://ec.europa.eu/eurostat

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

The GDP of the euro area in 2014 in current US dollars in the dataset of the World Economic Outlook (WEO) of the International Monetary Fund (IMF) is $13,429.8 billion or 17.4 percent of world GDP of $77,825.3 billion (http://www.imf.org/external/pubs/ft/weo/2016/01/weodata/index.aspx). The sum of the GDP of France $2833.7 billion with the GDP of Germany of $3874.4 billion, Italy of $2141.9 billion and Spain $1383.5 billion is $10,233.5 billion or 76.2 percent of total euro area GDP and 13.1 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 2015. 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

2015

2.0

1.7

1.3

0.8

3.2

2014

1.1

1.6

0.6

-0.3

1.4

2013

-0.3

0.5

0.6

-1.7

-1.7

2012

-0.9

0.5

0.2

-2.8

-2.6

2011

1.5

3.7

2.1

0.6

-1.0

2010

2.1

4.1

2.0

1.7

0.0

2009

-4.5

-5.6

-2.9

-5.5

-3.6

2008

0.4

1.1

0.2

-1.1

1.1

2007

3.0

3.3

2.4

1.5

3.8

2006

3.2

3.7

2.4

2.0

4.2

2005

1.7

0.7

1.6

0.9

3.7

2004

2.3

1.2

2.8

1.6

3.2

2003

0.7

-0.7

0.8

0.2

3.2

2002

1.0

0.0

1.1

0.2

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

3.0

2.0

3.4

1.6

4.5

1998

2.9

2.0

3.6

1.6

4.3

Average 1999-2015

1.2

1.2

1.3

0.2

1.7

Average 1999-2007

2.2

1.6

2.1

1.5

3.8

1997

2.6

1.8

2.3

1.8

3.7

1996

1.7

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 53.3 in Oct to 54.1 in Nov (https://www.markiteconomics.com/Survey/PressRelease.mvc/ca3130e2929640b48f03eb12b475b913). Chris Williamson, Chief Business Economist at IHS Markit, finds that the Markit Flash Eurozone PMI index suggests GDP growth about 0.4 percent in IVQ2016 (https://www.markiteconomics.com/Survey/PressRelease.mvc/ca3130e2929640b48f03eb12b475b913). The Markit Eurozone PMI® Composite Output Index, combining services and manufacturing activity with close association with GDP increased from 52.6 in Sep to 53.3 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/ff4a40e5fd5243de8eea258ece0dd9e6). Chris Williamson, Chief Economist at IHS Markit, finds potential for growth of about 0.3 percent in IVQ2016 (https://www.markiteconomics.com/Survey/PressRelease.mvc/ff4a40e5fd5243de8eea258ece0dd9e6). The Markit Eurozone Services Business Activity Index increased from 52.2 in Sep to 52.8 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/ff4a40e5fd5243de8eea258ece0dd9e6). The Markit Eurozone Manufacturing PMI® increased from 52.6 in Sep to 53.5 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/4c1efe8463314bccb50184929c4a8e80). New export orders increased. Rob Dobson, Senior Economist at IHS Markit, finds sronger industrial growth (https://www.markiteconomics.com/Survey/PressRelease.mvc/4c1efe8463314bccb50184929c4a8e80). Table EUR provides the data table for the euro area.

Table EUR, Euro Area Economic Indicators

GDP

IIIQ2016 ∆% 0.3; IIIQ2016/IIQ2015 ∆% 1.6 Blog 9/13/15 11/22/15 12/13/15 2/14/16 3/13/16 5/1/16 5/15/16 6/12/16 8/7/16 8/14/16 9/11/16 11/20/16

Unemployment 

Sep 2016: 10.0 % unemployment rate; Aug 2016: 16.181 million unemployed

Blog 11/6/16

HICP

Oct month ∆%: 0.2

12 months Oct ∆%: 0.5
Blog 11/20//16

Producer Prices

Euro Zone industrial producer prices Sep ∆%: 0.1
Sep 12-month ∆%: -1.5
Blog 11/13/16

Industrial Production

Jul Month ∆%: -1.1; 12 months ∆%: -0.5

Earlier Data:
Blog 4/19/15

Retail Sales

Sep month ∆%: -0.2
Sep 12 months ∆%: 1.1

Earlier Data:
Blog 3/15/15

Confidence and Economic Sentiment Indicator

Sentiment 106.3 Oct 2016

Consumer minus 8.0 Oct 2016

Earlier Data:

Blog 4/5/15

Trade

Jan-Sep 2016/Jan-Sep 2015 Exports ∆%: -0.4
Imports ∆%: -3.1

Sep 2016 12-month Exports ∆% 2.0 Imports ∆% -2.5

Earlier Data:
Blog 4/19/15

Links to blog comments in Table EUR: 11/20/16 http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html

11/13/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html

11/6/16 http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html

9/11/16 http://cmpassocregulationblog.blogspot.com/2016/09/interest-rate-uncertainty-and-valuation.html

8/14/16 http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.html

8/7/16 http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html

6/12/16 http://cmpassocregulationblog.blogspot.com/2016/06/considerable-uncertainty-about-economic.html

5/15/16 http://cmpassocregulationblog.blogspot.com/2016/05/recovery-without-hiring-ten-million.html

5/1/16 http://cmpassocregulationblog.blogspot.com/2016/05/economic-activity-appears-to-have.html

3/13/16 http://cmpassocregulationblog.blogspot.com/2016/03/monetary-policy-and-fluctuations-of_13.html

3/6/16 http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html

2/14/16 http://cmpassocregulationblog.blogspot.com/2016/02/subdued-foreign-growth-and-dollar.html

12/13/15 http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-interest-rates-with-volatile_17.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

VE Germany. Table VE-DE provides yearly growth rates of the German economy from 1971 to 2015, 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, 3.7 percent in 2011 and 0.5 percent in 2012. Growth stabilized to 0.5 percent in 2013, increasing to 1.6 percent in 2014. The German economy grew at 1.7 percent in 2015.

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 ∆% 1991-2015

1.3

 

Average ∆% 1991-1999

1.5

 

Average ∆% 2000-2007

1.4

 

Average ∆% 2003-2007

2.2

 

Average ∆% 2007-2015

0.9

 

Average ∆% 2009-2015

2.0

 

2015

1.7

1.5

2014

1.6

1.6

2013

0.5

0.6

2012

0.5

0.7

2011

3.7

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

1.8

1997

1.8

1.9

1996

0.8

0.9

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

4.0

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/PressServices/Press/pr/2015/08/PE15_293_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2015/08/PE15_305_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2015/11/PE15_419_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2015/11/PE15_430_811.html

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

https://www.destatis.de/EN/PressServices/Press/pr/2016/02/PE16_056_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2016/02/PE16_044_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2016/05/PE16_162_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2016/05/PE16_171_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2016/08/PE16_279_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2016/08/PE16_291_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2016/11/PE16_403_811.html

https://www.destatis.de/EN/PressServices/Press/pr/2016/11/PE16_413_811.html

The Flash Germany Composite Output Index of the Markit Flash Germany PMI®, combining manufacturing and services, decreased from 55.1 in Oct to 54.9 in Nov. The index of manufacturing output reached 54.7 in Nov, decreasing from 56.8 in Oct, while the index of services increased to 55.0 in Nov from 54.2 in Oct. The overall Flash Germany Manufacturing PMI® decreased from 55.0 in Oct to 54.4 in Nov (https://www.markiteconomics.com/Survey/PressRelease.mvc/0ba096067aff4f4ab8dbfcba800c7c04). New orders and new export orders in manufacturing increased. Oliver Kolodseike, Economist at IHS Markit, finds stronger growth of the private sector of Germany (https://www.markiteconomics.com/Survey/PressRelease.mvc/0ba096067aff4f4ab8dbfcba800c7c04). 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 52.8 in Sep to 55.1 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/fd8a8554991f4f8e8bf5f5137ee16551). Oliver Kolodseike, Economist at IHS Markit and author of the report, finds improving growth of the services sector of Germany (https://www.markiteconomics.com/Survey/PressRelease.mvc/fd8a8554991f4f8e8bf5f5137ee16551). The Germany Services Business Activity Index increased from 50.9 in Sep to 54.2 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/fd8a8554991f4f8e8bf5f5137ee16551). The Markit/BME Germany Purchasing Managers’ Index® (PMI®), showing close association with Germany’s manufacturing conditions, increased from 54.3 in Sep to 55.0 in

Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/371487878bc3427baa6efa144250ee25). New export orders increased. Oliver Kolodseike, Economist at IHS Markit and author of the report, finds continuing growth conditions (https://www.markiteconomics.com/Survey/PressRelease.mvc/371487878bc3427baa6efa144250ee25).Table DE provides the country data table for Germany.

Table DE, Germany, Economic Indicators

GDP

IIIQ2016 0.2 ∆%; IIIQ2016/IIIQ2015 ∆% 1.5

2015/2014: 1.7%

GDP ∆% 1970-2015

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 8/16/15 8/30/15 11/22/15 11/29/15 2/14/16 2/28/16 5/15/16 5/29/16 8/14/16 8/28/16 11/20/16 11/27/16

Consumer Price Index

Oct month NSA ∆%: 0.2
Oct 12-month NSA ∆%: 0.8
Blog 11/13/16

Producer Price Index

Oct month ∆%: 0.7 NSA, 0.5 CSA
12-month NSA ∆%: -0.4
Blog 11/20/16

Industrial Production

MFG Sep month CSA ∆%: minus 1.7
12-month NSA: 1.6

Earlier Data:
Blog 4/12/15

Machine Orders

MFG Sep month ∆%: -0.6
Sep 12-month ∆%: 2.6

Earlier Data:
Blog 4/12/15

Retail Sales

Aug Month ∆% -0.4 Jul 0.5

12-Month Aug % 3.7 Jul -1.5

Earlier Data:

Blog 4/5/15

Employment Report

Unemployment Rate SA Sep 4.1%
Blog 11/6/16

Trade Balance

Exports Sep 12-month NSA ∆%: 0.9
Imports Sep 12 months NSA ∆%: -1.4
Exports Sep month CSA ∆%: minus -0.7; Imports Sep month CSA -0.5

Earlier Data:

Blog 4/12/15

Links to blog comments in Table DE: 11/27/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-rising-yields-and.html

11/20/16 http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html

11/13/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-and-valuations-of.html

11/6/16 http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html

8/28/16 http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html

8/14/16 http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.html

5/29/16 http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.html

5/15/16 http://cmpassocregulationblog.blogspot.com/2016/05/recovery-without-hiring-ten-million.html

2/28/16 http://cmpassocregulationblog.blogspot.com/2016/02/mediocre-cyclical-united-states.html

2/14/16 http://cmpassocregulationblog.blogspot.com/2016/02/subdued-foreign-growth-and-dollar.html

11/29/15 http://cmpassocregulationblog.blogspot.com/2015/11/dollar-revaluation-constraining.html

11/22/15 http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-liftoff-followed-by.html

08/30/15 http://cmpassocregulationblog.blogspot.com/2015/08/fluctuations-of-global-financial.html

08/16/15 http://cmpassocregulationblog.blogspot.com/2015/08/exchange-rate-and-financial-asset.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

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 IIIQ2016 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 2.1 percent in the 1990s and 1.8 percent from 2000 to 2007. The average growth rate from 2000 to 2015, using fourth quarter data, is 1.1 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 ∆%

1949-2016

3.2

2007-2016**

0.5

2007-2015*

0.5

2007-2014

0.3

2000-2015

1.1

2000-2014

1.1

2000-2007

1.8

1990-1999

2.1

1980-1989

2.6

1970-1979

3.7

1960-1969

5.7

1950-1959

4.2

*IVQ2007 to IVQ2015 **IVQ2007 to IIIQ2016

Source: Institut National de la Statistique et des Études Économiques

https://www.insee.fr/en/statistiques/2510832

https://www.insee.fr/en/statistiques?debut=0&theme=27

The Markit Flash France Composite Output Index increased from 51.6 in Oct to 52.3 in Nov (https://www.markiteconomics.com/Survey/PressRelease.mvc/9a652a716c5542c2afb3df525c4c74e8). Alex Gill, Economist at IHS Markit and author of the report, finds improving activity (https://www.markiteconomics.com/Survey/PressRelease.mvc/9a652a716c5542c2afb3df525c4c74e8). The Markit France Composite Output Index, combining services and manufacturing with close association with French GDP, decreased from 52.7 in Sep to 51.6 in Oct, indicating slower activity of the private sector (https://www.markiteconomics.com/Survey/PressRelease.mvc/6e8f19f0d65645e4abbeea9257337749). Alex Gill, Senior Economist at IHS Markit and author of the France Services PMI®, finds slowing growth (https://www.markiteconomics.com/Survey/PressRelease.mvc/dbfc2d5436c64886b7d465c86472c447). The Markit France Services Activity index decreased from 53.3 in Sep to 51.4 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/6e8f19f0d65645e4abbeea9257337749). The Markit France Manufacturing Purchasing Managers’ Index® increased to 51.8 in Oct from 49.7 in Sep (https://www.markiteconomics.com/Survey/PressRelease.mvc/4c11986ae44145aa925e38ae66b77510). Alex Gill, Economist at IHS Markit and author of the France Manufacturing PMI®, finds improving manufacturing (https://www.markiteconomics.com/Survey/PressRelease.mvc/4c11986ae44145aa925e38ae66b77510). Table FR provides the country data table for France.

Table FR, France, Economic Indicators

CPI

Oct month ∆% 0.0
12 months ∆%: 0.4
11/20/16

PPI

Sep month ∆%: 0.1
Sep 12 months ∆%: -1.7

Blog 11/6/16

GDP Growth

IIIQ2016/IIQ2016 ∆%: 0.2
IIIQ2016/IIIQ2015 ∆%: 1.1
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 8/16/15 9/27/15 11/15/15 12/27/15 1/31/16 2/28/16 3/27/16 5/1/16 6/5/16 06/26/16 8/7/16 9/4/16 9/25/16 10/30/16 12/4/16

Industrial Production

Sep ∆%:
Manufacturing -1.1 Quarter ∆%: 0.2 YOY 0.0

Earlier Data:
Blog 4/12/15

Consumer Spending

Manufactured Goods
Aug ∆%: 1.0 Aug 12-Month Manufactured Goods
∆%: 1.6

Earlier Data:
Blog 4/5/15

Employment

Unemployment Rate: IIIQ2016 9.7%
Blog 11/20/16

Trade Balance

Sep Exports ∆%: month -2.2 12 months -0.9

Imports ∆%: month -0.6, 12 months 1.8

Earlier Data:

Blog 4/12/15

Confidence Indicators

Historical average 100

Nov Mfg Business Climate 103

Earlier Data:

Blog 3/29/15

Links to blog comments in Table FR: 11/20/16 http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html

11/6/16 http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html

10/30/16 http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html

9/25/16 http://cmpassocregulationblog.blogspot.com/2016/09/the-economic-outlook-is-inherently.html

9/4/16 http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html

8/7/16 http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html

6/26/16 http://cmpassocregulationblog.blogspot.com/2016/06/of-course-considerable-uncertainty.html

6/5/16 http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html

5/1/16 http://cmpassocregulationblog.blogspot.com/2016/05/economic-activity-appears-to-have.html

3/27/16 http://cmpassocregulationblog.blogspot.com/2016/03/contraction-of-united-states-corporate.html

2/28/16 http://cmpassocregulationblog.blogspot.com/2016/02/mediocre-cyclical-united-states.html

1/31/16 http://cmpassocregulationblog.blogspot.com/2016/01/closely-monitoring-global-economic-and.html

12/27/15 http://cmpassocregulationblog.blogspot.com/2015/12/dollar-revaluation-and-decreasing.html

11/15/15 http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-policy-conundrum-recovery.html

9/27/15 http://cmpassocregulationblog.blogspot.com/2015/09/monetary-policy-designed-on-measurable.html

08/16/15 http://cmpassocregulationblog.blogspot.com/2015/08/exchange-rate-and-financial-asset.html

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

Growth of GDP in a quarter relative to the prior quarter for France is in Table VF-1. GDP changed 0.0 percent in IVQ2012 and decreased 0.1 percent in IQ2013, rebounding with growth of 0.7 percent in IIQ2013. GDP changed 0.0 percent in IIIQ2013. GDP increased 0.3 percent in IVQ2013. GDP decreased 0.1 percent in IQ2014. GDP increased 0.2 percent in IIQ2014. GDP increased 0.4 percent in IIIQ2014 and increased 0.2 in IVQ2014. GDP increased 0.6 percent in IQ2015 and changed 0.0 percent in IIQ2015. GDP increased 0.4 percent in IIIQ2015 and increased 0.4 percent in IVQ2015. GDP increased 0.6 percent in IQ2016. GDP decreased 0.1 percent in IIQ2016. GDP increased 0.2 percent in IIIQ2016. The French economy grew 0.2 percent in IVQ2011, decreasing 0.1 percent in IQ2012, contracting 0.2 percent in IIQ2012 and growing 0.2 percent in IIIQ2012. In the four quarters of 2012 and the first quarter of 2013, France’s GDP contracted in three quarters and stagnated in one quarter. Growth in the ten quarters of expansion from IIIQ2009 to IVQ2011 accumulated 4.7 percent at the annual equivalent rate of 1.9 percent. Recovery has been much weaker than the cumulative 2.3 percent in the four quarters of 2006. The GDP of France contracted 3.9 percent from the pre-recession peak in IQ2008 at €508,776 million SA-WDA (seasonally adjusted working day adjusted volumes chained at previous year prices) to the trough in IIQ2009 at €488,754 million SA-WDA. The GDP of France increased 4.2 percent from the pre-recession peak in IQ2008 at €508,776 million SA-WDA to €530,010 million SA-WDA in IIIQ2016 at the annual equivalent rate of 0.5 percent. French GDP increased 8.4 percent from €488,754 million SA-WDA in IIQ2009 to €530,010 million SA-WDA in IIIQ2016 at the annual equivalent rate of 1.1 percent. French GDP in IIIQ2016 is 10.5 percent below trend at average 1.8 percent from 2000 to 2007. Weak recoveries in advanced economies have prevented full utilization of labor, capital and productive resources.

Table VF-1, France, Quarterly Real GDP Growth, Quarter on Prior Quarter ∆%

 

IQ

IIQ

IIIQ

IVQ

2016

0.6

-0.1

0.2

 

2015

0.6

0.0

0.4

0.4

2014

-0.1

0.2

0.4

0.2

2013

-0.1

0.7

0.0

0.3

2012

-0.1

-0.2

0.2

0.0

2011

1.1

0.0

0.3

0.2

2010

0.5

0.6

0.5

0.6

2009

-1.7

-0.1

0.2

0.6

2008

0.3

-0.5

-0.3

-1.4

2007

0.8

0.7

0.3

0.3

2006

0.8

0.8

0.0

0.7

2005

0.3

0.1

0.5

0.7

2004

0.9

0.6

0.4

0.7

2003

0.2

-0.1

0.7

0.7

2002

0.4

0.4

0.4

-0.1

2001

0.5

0.2

0.3

0.0

2000

1.0

0.8

0.7

0.8

1999

0.6

0.9

1.2

1.3

Source: Institut National de la Statistique et des Études Économiques

https://www.insee.fr/en/statistiques/2510832

https://www.insee.fr/en/statistiques?debut=0&theme=27

Growth rates of France’s real GDP in a quarter relative to the same quarter a year earlier are in Table VF-2. France has not recovered the rates of growth in excess of 2 percent prior to the global recession. GDP fell 3.8 percent in IQ2009, 3.5 percent in IIQ2009, 3.1 percent in IIIQ2009 and 1.0 percent in IVQ2009. Growth in IVQ2011 relative to IVQ2010 was 1.6 percent and GDP growth declined to 0.4 percent in IQ2012, 0.3 percent in IIQ2012 relative to the same quarter a year earlier, 0.2 percent in IIIQ2012 relative to a year earlier and 0.0 percent in IVQ2012 relative to a year earlier. Growth in IQ2013 relative to a year earlier was 0.0 percent. France’s GDP increased 0.9 percent in IIQ2013 relative to a year earlier and 0.7 percent in IIIQ2013 relative to a year earlier. GDP increased 0.9 percent in IVQ2013 relative to a year earlier. France’s GDP increased 0.9 percent in IQ2014 relative to a year earlier and increased 0.4 percent in IIQ2014 relative to a year earlier. GDP increased 0.7 percent in IIIQ2014 relative to a year earlier and increased 0.6 percent in IVQ2014 relative to a year earlier. GDP increased 1.3 percent in IQ2015 relative to a year earlier and increased 1.1 percent in IIQ2015 relative to a year earlier. GDP increased 1.1 percent in IIIQ2015 relative to a year earlier and increased 1.3 percent in IVQ2015 relative to a year earlier. GDP increased 1.4 percent in IQ2016 relative to a year earlier and increased 1.2 percent in IIQ2014 relative to a year earlier. GDP increased 1.1 percent in IIIQ2016 relative to a year earlier.

Table VF-2, France, Real GDP Growth Current Quarter Relative to Same Quarter Year Earlier ∆%

 

IQ

IIQ

IIIQ

IVQ

2016

1.4

1.2

1.1

 

2015

1.3

1.1

1.1

1.3

2014

0.9

0.4

0.7

0.6

2013

0.0

0.9

0.7

0.9

2012

0.4

0.3

0.2

0.0

2011

2.8

2.1

1.9

1.6

2010

1.2

1.9

2.2

2.2

2009

-3.8

-3.5

-3.1

-1.0

2008

1.7

0.5

-0.1

-1.8

2007

2.4

2.3

2.6

2.2

2006

2.2

2.9

2.4

2.4

2005

1.9

1.5

1.6

1.7

2004

2.2

3.0

2.6

2.5

2003

0.9

0.3

0.7

1.5

2002

0.9

1.1

1.2

1.1

2001

2.9

2.2

1.8

1.0

2000

4.4

4.4

4.0

3.4

1999

2.9

3.0

3.3

3.9

Source: Institut National de la Statistique et des Études Économiques

https://www.insee.fr/en/statistiques/2510832

https://www.insee.fr/en/statistiques?debut=0&theme=27

Chart VF-1 of the Institut National de la Statistique et des Études Économiques provides France’s quarterly real GDP from IQ1949 to IIIQ2016. France’s economy has grown dynamically over decades. Recovery from the global recession in 2008-2009 slowed with marginal increase.

clip_image008

Chart VF-1, France, Quarterly Real GDP, Seasonally and Working Day Adjusted, IQ1949-IIIQ2016

Source: Institut National de la Statistique et des Études Économiques

https://www.insee.fr/en/statistiques/2510832

https://www.insee.fr/en/statistiques?debut=0&theme=27

Percentage changes and contributions of segments of GDP in France are in Table VF-3. Internal demand added 0.3 percentage points to growth in IVQ2015. Internal demand added 0.9 percentage point to GDP growth in IQ2016 and contributed 0.1 percentage points to GDP growth in IIQ2016. Internal demand added 0.1 percentage points to GDP growth in IIIQ2016. Net trade deducted 0.5 percentage points in IVQ2015. Net trade deducted 0.2 percentage points from GDP growth in IQ2016. Net trade added 0.5 percentage points in IIQ2016 and deducted 0.6 percentage points in IIIQ2016.

Table VF-3, France, Contributions to GDP Growth, Calendar and Seasonally Adjusted, %

∆% from Prior Period

IVQ
2015

IQ
2016

IIQ 2016

IIIQ 2016

2015

2016

GDP

0.4

0.6

-0.1

0.2

1.2

1.1

Imports

2.3

0.3

-1.7

2.5

6.4

2.7

Household Consump.

-0.1

1.1

0.0

0.0

1.5

1.4

Govt.
Consump.

0.4

0.4

0.4

0.3

1.4

1.4

GFCF

1.2

1.2

0.0

0.2

0.9

2.6

General Government

1.5

-0.1

0.4

1.1

-3.9

2.2

Exports

0.7

-0.5

-0.1

0.5

6.0

0.5

% Point
Contribs
.

           

Internal Demand ex Inventory Changes

0.3

0.9

0.1

0.1

1.3

1.6

Inventory Changes

0.5

-0.1

-0.7

0.7

0.2

0.2

Net Foreign Trade

-0.5

-0.2

0.5

-0.6

-0.3

-0.7

Notes: Consump.: Consumption; Gvt.: Government; GFCF: Gross Fixed Capital Formation; Contribus.: Contributions; OVHG: “annual growth rate carried over at the mid-year point.”

Source:  Institut National de la Statistique et des Études Économiques

https://www.insee.fr/en/statistiques/2510832

https://www.insee.fr/en/statistiques?debut=0&theme=27

Chart VF-2 of France’s Institut National de la Statistique et des Études Économiques provides percentage point contributions to GDP growth. The economy was driven in IQ2013 by consumption with net trade and gross fixed capital formation (GFCF) deducting from growth.  Final consumption drove the economy in IIQ2013 together with contribution by net trade and capital formation. Gross fixed capital formation and net trade constrained the economy in IIIQ2013. Inventory changed deducted from growth in IVQ2013 with contributions by consumption and net trade. Inventory change contributed to growth in IQ2014 with deductions by consumption, GFCF and net foreign trade. Consumption contributed to growth in IIQ2014 with deductions by GFCF and net trade. Consumption and inventory change drove the economy in IIIQ2014 with deduction by net trade. Consumption and net trade drove the economy in IVQ2014 with deductions by GFCF and inventory change. Consumption, GFCF and inventory change drove the economy in IQ2015 with net trade deducting from growth. Net trade and consumption drove the economy in IIQ2015 with inventory change and GFCF deducting from growth. Consumption and inventory change drove the economy in IIIQ2015 with minor contribution by GFCF and significant deduction by net trade. Inventory change, consumption and GFCF drove the economy in IVQ2015 with deduction by net trade. Consumption and GFCF drove the economy in IQ2016 with deductions by inventory change and net trade. Consumption and net trade drove the economy in IIQ2016 with deductions by inventory change and GFCF. Inventory change, consumption and GFCF drove the economy in IIIQ2016 with deduction by net trade.

clip_image009

Chart VF-2, France, Percentage Point Contributions to GDP Growth

Source: Institut National de la Statistique et des Études Économiques

https://www.insee.fr/en/statistiques/2510832

https://www.insee.fr/en/statistiques?debut=0&theme=27

VG Italy. Table VG-IT provides revised percentage changes of GDP in Italy of quarter on prior quarter and quarter on same quarter a year earlier. Italy’s GDP increased 0.3 percent in IIIQ2016 and increased 1.0 percent relative to a year earlier. In IIQ2016, GDP increased 0.1 percent and increased 0.8 percent relative to a year earlier. GDP increased 0.4 percent in IQ2016 and increased 1.0 percent relative to a year earlier. GDP increased 0.2 percent in IVQ2015 and increased 0.9 percent relative to a year earlier. In IIIQ2015, GDP increased 0.1 percent and increased 0.6 percent relative to a year earlier. GDP increased 0.3 percent in IIQ2015 and 0.6 percent relative to a year earlier. GDP increased 0.3 percent in IQ2015 and increased 0.4 percent relative to a year earlier. GDP changed 0.0 percent in IVQ2014 and increased 0.1 percent relative to a year earlier. GDP changed 0.0 percent in IIIQ2014 and changed 0.0 percent relative to a year earlier. Italy’s GDP increased 0.1 percent in IIQ2014 and increased 0.3 percent relative to a year earlier. The GDP of Italy changed 0.0 percent in IQ2014 and increased 0.3 percent relative to a year earlier. Italy’s GDP changed 0.0 percent in IVQ2013 and fell 0.7 percent relative to a year earlier. The GDP of Italy increased 0.3 percent in IIIQ2013 and fell 1.3 percent relative to a year earlier. Italy’s GDP changed 0.0 in IIQ2013 and fell 2.1 percent relative to a year earlier. Italy’s GDP fell 1.0 percent in IQ2013 and declined 2.8 percent relative to IQ2012. GDP had been growing during six consecutive quarters but at very low rates from IQ2010 to IIQ2011. Italy’s GDP fell in seven consecutive quarters from IIIQ2011 to IQ2013 at increasingly higher rates of contraction from 0.5 percent in IIIQ2011 to 1.0 percent in IVQ2011, 1.0 percent in IQ2012, 0.7 percent in IIQ2012 and 0.5 percent in IIIQ2012. The pace of decline accelerated to minus 0.6 percent in IVQ2012 and minus 1.0 percent in IQ2013. GDP contracted cumulatively 5.2 percent in seven consecutive quarterly contractions from IIIQ2011 to IQ2013 at the annual equivalent rate of minus 3.0 percent. The yearly rate has fallen from 2.2 percent in IVQ2010 to minus 2.8 percent in IVQ2012, minus 2.8 percent in IQ2013, minus 2.1 percent in IIQ2013 and minus 1.3 percent in IIIQ2013. GDP fell 0.7 percent in IVQ2013 relative to a year earlier. GDP increased 0.3 percent in IQ2014 relative to a year earlier and increased 0.3 percent in IIQ2014 relative to a year earlier. GDP changed 0.0 percent in IIIQ2014 relative to a year earlier and increased 0.1 percent in IVQ2014 relative to a year earlier. GDP increased 0.4 percent in IQ2015 relative to a year earlier and increased 0.6 percent in IIQ2015 relative to a year earlier. GDP increased 0.6 percent in IIIQ2015 relative to a year earlier and increased 0.9 percent in IVQ2015 relative to a year earlier. GDP increased 1.0 percent in IQ2016 relative to a year earlier and increased 0.8 percent in IIQ2016 relative to a year earlier. GDP increased 1.0 percent in IIIQ2016 relative to a year earlier. Using seasonally and calendar adjusted chained volumes in the dataset of EUROSTAT (http://ec.europa.eu/eurostat), the GDP of Italy in IIIQ2016 of €392,303.4 million is lower by 7.7 percent relative to €424,823.8 million in IQ2008. Using seasonally and calendar adjusted chained volumes in the dataset of EUROSTAT (http://ec.europa.eu/eurostat), the GDP of Italy increased from[CP1] €367,664.4 million in IQ1998 to €424,823.8 million in IQ2008 at the annual equivalent rate of 1.5 percent. The fiscal adjustment of Italy is significantly more difficult with the economy not growing especially on the prospects of increasing government revenue. The strategy is for reforms to improve productivity, facilitating future fiscal consolidation.

Table VG-IT, Italy, GDP ∆%

 

Quarter ∆% Relative to Preceding Quarter

Quarter ∆% Relative to Same Quarter Year Earlier

IIIQ2016

0.3

1.0

IIQ2016

0.1

0.8

IQ2016

0.4

1.0

IVQ2015

0.2

0.9

IIIQ2015

0.1

0.6

IIQ2015

0.3

0.6

IQ2015

0.3

0.4

IVQ2014

0.0

0.1

IIIQ2014

0.0

0.0

IIQ2014

0.1

0.3

IQ2014

0.0

0.3

IVQ2013

0.0

-0.7

IIIQ2013

0.3

-1.3

IIQ2013

0.0

-2.1

IQ2013

-1.0

-2.8

IVQ2012

-0.6

-2.8

IIIQ2012

-0.5

-3.2

IIQ2012

-0.7

-3.2

IQ2012

-1.0

-2.2

IVQ2011

-1.0

-1.1

IIIQ2011

-0.5

0.5

IIQ2011

0.2

1.5

IQ2011

0.3

2.0

IVQ2010

0.5

2.2

IIIQ2010

0.6

1.9

IIQ2010

0.7

1.9

IQ2010

0.4

0.6

IVQ2009

0.2

-2.7

IIIQ2009

0.5

-5.2

IIQ2009

-0.6

-6.9

IQ2009

-2.9

-7.1

IVQ2008

-2.3

-3.5

IIIQ2008

-1.3

-1.3

IIQ2008

-0.8

-0.1

IQ2008

0.8

0.7

IV2007

-0.1

0.1

IIIQ2007

-0.1

1.2

IIQ2007

0.0

1.7

IQ2007

0.2

2.3

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/193549

The Markit Italy Business Activity Index increased from 50.7 in Sep to 51.0 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/770c76b8fdc340e78da3b34b71e072ff). Phil Smith, Economist at IHS Markit and author of the Italy Services PMI®, finds stabilizing conditions (https://www.markiteconomics.com/Survey/PressRelease.mvc/770c76b8fdc340e78da3b34b71e072ff). The Markit Italy Purchasing Managers’ Index® (PMI®), decreased from 51.0 in Sep to 50.9 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/208527be7ca1481fbede73fe113b369f). New export orders continued to increase. Phil Smith, Economist at Markit and author of the Italian Manufacturing PMI®, finds softness in manufacturing (https://www.markiteconomics.com/Survey/PressRelease.mvc/208527be7ca1481fbede73fe113b369f). Table IT provides the country data table for Italy.

Table IT, Italy, Economic Indicators

Consumer Price Index

Oct month ∆% -0.1
12 months ∆%: -0.2
11/20/16

Producer Price Index

Sep month ∆%: -0.1
Sep 12-month ∆%: -0.8

Blog 11/6/16

GDP Growth

IIIQ2016/IIQ2016 SA ∆%: 0.3
IIIQ2016/IIIQ2015 NSA ∆%: 1.0
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 8/16/15 9/6/15 11/15/15 12/6/15 2/14/16 3/6/16 5/15/16 6/5/16 8/14/16 9/11/16 11/20/16 12/4/16

Labor Report

Sep 2016

Participation rate 65.2%

Employment ratio 57.5%

Unemployment rate 11.7%

Youth Unemployment 37.1%

Blog 11/6/16

Industrial Production

Sep month ∆%: -0.8
12 months CA ∆%: 1.8

Earlier Data:
Blog 4/19/15

Retail Sales

Jul month ∆%: -0.3

Jul 12-month ∆%: -0.2

Earlier Data:

Blog 4/26/15

Business Confidence

Mfg Nov 102.0, Jul 103.0

Construction Nov 124.2, Jul 126.2

Earlier Data:

Blog 4/5/15

Trade Balance

Balance Sep SA €4685 million
Exports Sep month SA ∆%: -1.6; Imports month ∆%: -4.5
Exports 12 months Sep NSA ∆%: 3.1 Imports 12 months NSA ∆%: -2.7

Earlier Data:
Blog 4/19/15

Links to blog comments in Table IT: 11/20/16 http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html

11/6/16 http://cmpassocregulationblog.blogspot.com/2016/11/the-case-for-increase-in-federal-funds.html

9/11/16 http://cmpassocregulationblog.blogspot.com/2016/09/interest-rate-uncertainty-and-valuation.html

8/14/16 http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.html

6/5/16 http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html

5/15/16 http://cmpassocregulationblog.blogspot.com/2016/05/recovery-without-hiring-ten-million.html

3/6/16 http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html

2/14/16 http://cmpassocregulationblog.blogspot.com/2016/02/subdued-foreign-growth-and-dollar.html

12/6/15 http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-fed-funds-rate-followed-by.html

11/15/15 http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-policy-conundrum-recovery.html

9/6/15 http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html

08/16/15 http://cmpassocregulationblog.blogspot.com/2015/08/exchange-rate-and-financial-asset.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

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

Table VG-1 provides revised percentage changes of GDP in Italy of quarter on prior quarter and quarter on same quarter a year earlier. Italy’s GDP increased 0.3 percent in IIIQ2016 and increased 1.0 percent relative to a year earlier. In IIQ2016, GDP increased 0.1 percent and increased 0.8 percent relative to a year earlier. GDP increased 0.4 percent in IQ2016 and increased 1.0 percent relative to a year earlier. GDP increased 0.2 percent in IVQ2015 and increased 0.9 percent relative to a year earlier. In IIIQ2015, GDP increased 0.1 percent and increased 0.6 percent relative to a year earlier. GDP increased 0.3 percent in IIQ2015 and 0.6 percent relative to a year earlier. GDP increased 0.3 percent in IQ2015 and increased 0.4 percent relative to a year earlier. GDP changed 0.0 percent in IVQ2014 and increased 0.1 percent relative to a year earlier. GDP changed 0.0 percent in IIIQ2014 and changed 0.0 percent relative to a year earlier. Italy’s GDP increased 0.1 percent in IIQ2014 and increased 0.3 percent relative to a year earlier. The GDP of Italy changed 0.0 percent in IQ2014 and increased 0.3 percent relative to a year earlier. Italy’s GDP changed 0.0 percent in IVQ2013 and fell 0.7 percent relative to a year earlier. The GDP of Italy increased 0.3 percent in IIIQ2013 and fell 1.3 percent relative to a year earlier. Italy’s GDP changed 0.0 in IIQ2013 and fell 2.1 percent relative to a year earlier. Italy’s GDP fell 1.0 percent in IQ2013 and declined 2.8 percent relative to IQ2012. GDP had been growing during six consecutive quarters but at very low rates from IQ2010 to IIQ2011. Italy’s GDP fell in seven consecutive quarters from IIIQ2011 to IQ2013 at increasingly higher rates of contraction from 0.5 percent in IIIQ2011 to 1.0 percent in IVQ2011, 1.0 percent in IQ2012, 0.7 percent in IIQ2012 and 0.5 percent in IIIQ2012. The pace of decline accelerated to minus 0.6 percent in IVQ2012 and minus 1.0 percent in IQ2013. GDP contracted cumulatively 5.2 percent in seven consecutive quarterly contractions from IIIQ2011 to IQ2013 at the annual equivalent rate of minus 3.0 percent. The yearly rate has fallen from 2.2 percent in IVQ2010 to minus 2.8 percent in IVQ2012, minus 2.8 percent in IQ2013, minus 2.1 percent in IIQ2013 and minus 1.3 percent in IIIQ2013. GDP fell 0.7 percent in IVQ2013 relative to a year earlier. GDP increased 0.3 percent in IQ2014 relative to a year earlier and increased 0.3 percent in IIQ2014 relative to a year earlier. GDP changed 0.0 percent in IIIQ2014 relative to a year earlier and increased 0.1 percent in IVQ2014 relative to a year earlier. GDP increased 0.4 percent in IQ2015 relative to a year earlier and increased 0.6 percent in IIQ2015 relative to a year earlier. GDP increased 0.6 percent in IIIQ2015 relative to a year earlier and increased 0.9 percent in IVQ2015 relative to a year earlier. GDP increased 1.0 percent in IQ2016 relative to a year earlier and increased 0.8 percent in IIQ2016 relative to a year earlier. GDP increased 1.0 percent in IIIQ2016 relative to a year earlier. Using seasonally and calendar adjusted chained volumes in the dataset of EUROSTAT (http://ec.europa.eu/eurostat), the GDP of Italy in IIIQ2016 of €392,303.4 million is lower by 7.7 percent relative to €424,823.8 million in IQ2008. Using seasonally and calendar adjusted chained volumes in the dataset of EUROSTAT (http://ec.europa.eu/eurostat), the GDP of Italy increased from €367,664.4 million in IQ1998 to €424,823.8 million in IQ2008 at the annual equivalent rate of 1.5 percent. The fiscal adjustment of Italy is significantly more difficult with the economy not growing especially on the prospects of increasing government revenue. The strategy is for reforms to improve productivity, facilitating future fiscal consolidation.

Table VG-1, Italy, GDP ∆%

 

Quarter ∆% Relative to Preceding Quarter

Quarter ∆% Relative to Same Quarter Year Earlier

IIIQ2016

0.3

1.0

IIQ2016

0.1

0.8

IQ2016

0.4

1.0

IVQ2015

0.2

0.9

IIIQ2015

0.1

0.6

IIQ2015

0.3

0.6

IQ2015

0.3

0.4

IVQ2014

0.0

0.1

IIIQ2014

0.0

0.0

IIQ2014

0.1

0.3

IQ2014

0.0

0.3

IVQ2013

0.0

-0.7

IIIQ2013

0.3

-1.3

IIQ2013

0.0

-2.1

IQ2013

-1.0

-2.8

IVQ2012

-0.6

-2.8

IIIQ2012

-0.5

-3.2

IIQ2012

-0.7

-3.2

IQ2012

-1.0

-2.2

IVQ2011

-1.0

-1.1

IIIQ2011

-0.5

0.5

IIQ2011

0.2

1.5

IQ2011

0.3

2.0

IVQ2010

0.5

2.2

IIIQ2010

0.6

1.9

IIQ2010

0.7

1.9

IQ2010

0.4

0.6

IVQ2009

0.2

-2.7

IIIQ2009

0.5

-5.2

IIQ2009

-0.6

-6.9

IQ2009

-2.9

-7.1

IVQ2008

-2.3

-3.5

IIIQ2008

-1.3

-1.3

IIQ2008

-0.8

-0.1

IQ2008

0.8

0.7

IV2007

-0.1

0.1

IIIQ2007

-0.1

1.2

IIQ2007

0.0

1.7

IQ2007

0.2

2.3

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/193549

Contributions to quarterly growth of GDP in Italy are in Table VG-2. GDP grew at 0.3 percent in IIIQ2016. Final national consumption contributed 0.1 percentage points. Inventory investment added 0.1 percentage points. Net traded deducted 0.1 percentage points and fixed investment contributed 0.1 percentage points.

Table VG-2, Italy, Contributions to Quarterly Change of GDP, %

 

IVQ2015

IQ2016

IIQ2016

IIIQ2016

Internal Demand Net of Stocks

0.5

0.4

-0.1

0.3

Final National Consumption

0.3

0.3

0.1

0.1

Fixed Investment

0.2

0.1

0.0

0.1

Change in Stocks

-0.3

0.1

-0.2

0.1

Net Exports

0.1

-0.1

0.3

-0.1

GDP

0.2

0.4

0.1

0.3

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/193549

Levels and rates of growth of GDP in Italy in IIIQ2016 are in Table VG-3. GFCF (Gross Fixed Capital formation) increased 0.8 percent in IIIQ2016, increasing 2.3 percent relative to a year earlier. Final consumption increased 0.2 percent in IIIQ2016, increasing 1.0 percent relative to a year earlier.

Table VG-3, Italy, GDP in Chained Volumes SCA Euro and ∆%

Aggregate

Chained Volumes Million Euro

∆% IIIQ2016/

IIQ2016

∆% IIIQ2016/

IIIQ2015

GDP

392,303

0.3

1.0

Imports

109,920

0.7

2.2

Final Consumption

315,673

0.2

1.0

Household and NPISH

237,221

0.1

1.1

Government

78,401

0.2

0.6

GFCF

66,760

0.8

2.3

Equipment

30,236

0.7

0.1

Transport

4.650

8.8

33.8

Construction

31,933

-0.2

1.0

Change in Inventories

-

-

-

Exports

119,129

0.1

2.5

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/193549

Chart VG-1 of the Italian National Institute of Statistics (ISTAT) provides growth of GDP of Italy at market prices. The year on year rate of growth pulled strongly out of the contraction. There is evident trend of deceleration with increasingly sharper contraction and mild moderation in 2013 and 2014. GDP increased in IQ2015, IIQ2015, IIIQ2015 and IVQ2015. GDP increased in IQ2016 and stabilized in IIQ2016, increasing in IIIQ2016.

clip_image010

Chart VG-1, Italy, GDP at Market Prices, ∆% on Same Quarter Year Earlier

Source: Istituto Nazionale di Statistica

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

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 0.6 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 1.5 percent in 2011 and 1.3 percent in 2012. Growth increased to 1.9 percent in 2013 and 3.1 percent in 2014. Growth fell to 2.2 percent in 2015.  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 2015, which is relatively high for an advanced economy. The growth rate of GDP between 2000 and 2007 is higher at 2.7 percent. Growth in the current cyclical expansion from 2010 to 2015 has been only at 2.0 percent as advanced economies struggle with weak internal demand and world trade. GDP in 2015 is higher by 7.0 percent relative to 2007 while it would have been 23.8 higher at trend of 2.7 percent as from 2000 to 2007.

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

 

∆% on Prior Year

1998

3.2

1999

3.3

2000

3.7

2001

2.7

2002

2.4

2003

3.5

2004

2.5

2005

3.0

2006

2.5

2007

2.6

2008

-0.6

2009

-4.3

2010

1.9

2011

1.5

2012

1.3

2013

1.9

2014

3.1

2015

2.2

Average Growth Rates ∆% per Year

 

1948-2015

2.6

1950-1959

3.1

1960-1969

3.1

1970-1979

2.6

1980-1989

3.2

1990-1999

2.2

2000-2007

2.7

2007-2013*

1.6

2007-2014*

4.7

2007-2015

0.8

2000-2015

1.7

*Absolute change from 2007 to 2013 and 2007 to 2014

Source: UK Office for National Statistics

https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/secondestimateofgdp/quarter3julytosept2016

The Markit Flash UK PMI® Composite Output Index fell from 52.4 in Jun to 47.7 in Jul, which is the lowest in 87 months (https://www.markiteconomics.com/Survey//PressRelease.mvc/b68c3686a48c40198505b81e4e55cd81). Chris Williamson, Chief Economist at Markit, finds the index suggests pace of contraction of GDP at 0.4 percent in IIIQ2016 (https://www.markiteconomics.com/Survey//PressRelease.mvc/b68c3686a48c40198505b81e4e55cd81). The Business Activity Index of the Markit/CIPS UK Services PMI® increased from 52.6 in Sep to 54.5 in Oct (https://www.markiteconomics.com/Survey/PressRelease.mvc/d2b6f4d1be494f72b908da3af2a5cdf0). Chris Williamson, Chief Economist at Markit, finds the combined indices consistent with the UK economy growing 0.4 to 0.5 percent in IVQ2016 (https://www.markiteconomics.com/Survey/PressRelease.mvc/d2b6f4d1be494f72b908da3af2a5cdf0). The Markit/CIPS UK Manufacturing Purchasing Managers’ Index® (PMI®) increased to 55.4 in Sep from 53.4 in Aug (https://www.markiteconomics.com/Survey/PressRelease.mvc/f55855e5e87b4e9dadc0e3cbea1c285f). New export orders increased. Rob Dobson, Senior Economist at IHS Markit that compiles the Markit/CIPS Manufacturing PMI®, finds rebounding manufacturing with currency depreciation (https://www.markiteconomics.com/Survey/PressRelease.mvc/f55855e5e87b4e9dadc0e3cbea1c285f). Table UK provides the economic indicators for the United Kingdom.

Table UK, UK Economic Indicators

CPI

Oct month ∆%: 0.1
Oct 12-month ∆%: 0.9
Blog 11/20/16

Output/Input Prices

Output Prices: Oct 12-month NSA ∆%: 2.1; excluding food, petroleum ∆%: 1.9
Input Prices: Oct 12-month NSA
∆%: 12.2
Excluding ∆%: 9.9
Blog 11/20/16

GDP Growth

IIIQ2016 prior quarter ∆% 0.5; year earlier same quarter ∆%: 2.3
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 8/2/15 9/6/15 10/4/15 11/1/15 11/29/15 12/27/15 1/31/16 2/28/16 4/3/16 5/1/16 5/29/16 7/3/16 7/31/16 9/4/16 10/9/16 10/30/16 11/27/16

Industrial Production

Sep 2016/Sep 2015 ∆%: Production Industries 0.3; Manufacturing 0.2

Earlier Data:
Blog 4/12/15

Retail Sales

Oct month ∆%: 1.9
Oct 12-month ∆%: 7.4

Earlier Data:
Blog 4/26/15

Labor Market

Jul-Sep 2016 Unemployment Rate: 4.8%
Blog 11/20/16 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 Sep minus ₤5221 million
Exports Sep ∆%: -0.4; Jul-Sep ∆%: 9.4
Imports Sep ∆%: 2.5 Jul-Sep ∆%: 9.5

EARLIER DATA:
Blog 4/12/15

Links to blog comments in Table UK: 11/27/16 http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-rising-yields-and.html

11/20/16 http://cmpassocregulationblog.blogspot.com/2016/11/interest-rate-increase-could-well.html

10/30/16 http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html

10/9/16 http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html

9/4/16 http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html

7/31/16 http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.html

7/3/16 http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.html

5/29/16 http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.html

5/1/16 http://cmpassocregulationblog.blogspot.com/2016/05/economic-activity-appears-to-have.html

4/3/16 http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-monetary.html

2/28/16 http://cmpassocregulationblog.blogspot.com/2016/02/mediocre-cyclical-united-states.html

1/31/16 http://cmpassocregulationblog.blogspot.com/2016/01/closely-monitoring-global-economic-and.html

12/27/15 http://cmpassocregulationblog.blogspot.com/2015/12/dollar-revaluation-and-decreasing.html

11/29/15 http://cmpassocregulationblog.blogspot.com/2015/11/dollar-revaluation-constraining.html

11/1/15 http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-increase-considered.html

10/4/15 http://cmpassocregulationblog.blogspot.com/2015/10/labor-market-uncertainty-and-interest.html

9/6/15 http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html

08/02/15 http://cmpassocregulationblog.blogspot.com/2015/08/turbulence-of-valuations-of-financial.html

7/5/15 http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.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

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016.

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