Financial Asset Values Rebound from BREXIT, 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, Financial Repression, World Cyclical Slow Growth and Global Recession Risk: Part V

 

Financial Asset Values Rebound from BREXIT, 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, Financial Repression, 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

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 2014 and the growth rate of real GDP of the world and selected regional countries from 2014 to 2017. The data illustrate the concept often repeated of “two-speed recovery” of the world economy from the recession of 2007 to 2009. The IMF has changed its forecast of the world economy to 3.4 percent in 2014 and 3.1 percent in 2015 but accelerating to 3.2 percent in 2016 and 3.5 percent in 2017. Slow-speed recovery occurs in the “major advanced economies” of the G7 that account for $35,570 billion of world output of $77,825 billion, or 45.7 percent, but are projected to grow at much lower rates than world output, 1.8 percent on average from 2014 to 2017 in contrast with 3.3 percent for the world as a whole. While the world would grow 13.9 percent in the four years from 2014 to 2017, the G7 as a whole would grow 7.4 percent. The difference in dollars of 2014 is high: growing by 13.9 percent would add around $10.8 trillion of output to the world economy, or roughly, two times the output of the economy of Japan of $4,596 billion but growing by 7.4 percent would add $5.8 trillion of output to the world, or about the output of Japan in 2014. 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 2014 of $30,690 billion, or 39.4 percent of world output. The EMDEs would grow cumulatively 18.6 percent or at the average yearly rate of 4.4 percent, contributing $5.7 trillion from 2014 to 2017 or the equivalent of somewhat more than one half the GDP of $10,431 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 2014 adds to $16,921 billion, or 21.7 percent of world output, which is equivalent to 47.5 percent of the combined output of the major advanced economies of the G7.

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

	GDP USD 2014	Real GDP ∆% 2014	Real GDP ∆% 2015	Real GDP ∆% 2016	Real GDP ∆% 2017
World	77,825	3.4	3.1	3.2	3.5
G7	35,570	1.7	1.8	1.8	1.9
Canada	1,784	2.5	1.2	1.5	1.9
France	2,834	0.2	1.1	1.1	1.3
DE	3,874	1.6	1.5	1.5	1.6
Italy	2,142	-0.3	0.8	1.0	1.2
Japan	4,596	0.0	0.5	0.5	-0.1
UK	2,992	2.9	2.2	1.9	2.2
US	17,348	2.4	2.4	2.4	2.5
Euro Area	13,430	0.9	1.6	1.5	1.6
DE	3,874	1.6	1.5	1.5	1.6
France	2,834	0.2	1.1	1.1	1.3
Italy	2,142	-0.3	0.8	1.0	1.2
POT	230	0.9	1.5	1.4	1.3
Ireland	251	5.2	7.8	5.0	3.6
Greece	236	0.7	-0.2	-0.6	2.7
Spain	1,384	1.4	3.2	2.6	2.3
EMDE	30,690	4.6	4.0	4.1	4.7
Brazil	2,417	0.1	-3.8	-3.8	0.0
Russia	2,030	0.7	-3.7	-1.8	0.8
India	2,043	7.2	7.3	7.5	7.5
China	10,431	7.3	6.9	6.5	6.2

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/2016/01/weodata/index.aspx

Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (http://www.imf.org/external/pubs/ft/weo/2016/01/weodata/index.aspx). Table V-2 is constructed with the WEO database to provide rates of unemployment from 2013 to 2017 for major countries and regions. In fact, unemployment rates for 2014 in Table I-2 are high for all countries: unusually high for countries with high rates most of the time and unusually high for countries with low rates most of the time. The rates of unemployment are particularly high in 2014 for the countries with sovereign debt difficulties in Europe: 13.9 percent for Portugal (POT), 11.3 percent for Ireland, 26.5 percent for Greece, 24.5 percent for Spain and 12.6 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 V-2, IMF World Economic Outlook Database Projections of Unemployment Rate as Percent of Labor Force

	% Labor Force 2013	% Labor Force 2014	% Labor Force 2015	% Labor Force 2016	% Labor Force 2017
World	NA	NA	NA	NA	NA
G7	7.1	6.4	5.8	5.5	5.5
Canada	7.1	6.9	6.9	7.3	7.4
France	10.3	10.3	10.4	10.1	10.0
DE	5.2	5.0	4.6	4.6	4.8
Italy	12.2	12.6	11.9	11.4	10.9
Japan	4.0	3.6	3.4	3.3	3.3
UK	7.6	6.2	5.4	5.0	5.0
US	7.4	6.2	5.3	4.9	4.8
Euro Area	12.0	11.6	10.9	10.3	9.9
DE	5.2	5.0	4.6	4.6	4.8
France	10.3	10.3	10.4	10.1	10.0
Italy	12.2	12.6	11.9	11.4	10.9
POT	16.2	13.9	12.4	11.6	11.1
Ireland	13.0	11.3	9.4	8.3	7.5
Greece	27.5	26.5	25.0	25.0	23.4
Spain	26.1	24.5	22.1	19.7	18.3
EMDE	NA	NA	NA	NA	NA
Brazil	5.4	4.8	6.8	9.2	10.2
Russia	5.5	5.2	5.6	6.5	6.3
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/2016/01/weodata/index.aspx

Table V-3 provides the latest available estimates of GDP for the regions and countries followed in this blog from IQ2012 to IIIQ2015 available now for all countries. There are preliminary estimates for all countries for IQ2016. Growth is weak throughout most of the world.

• Japan. The GDP of Japan increased 1.0 percent in IQ2012, 3.9 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 1.6 percent, which is much lower than 3.5 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 0.2 percent and changed 0.0 percent relative to a year earlier. Japan grew 1.0 percent in IQ2013 at the SAAR of 4.2 percent and increased 0.3 percent relative to a year earlier. Japan’s GDP increased 0.7 percent in IIQ2013 at the SAAR of 2.7 percent and increased 1.1 percent relative to a year earlier. Japan’s GDP grew 0.5 percent in IIIQ2013 at the SAAR of 1.9 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 0.3 percent, increasing 2.1 percent relative to a year earlier. Japan’s GDP increased 1.3 percent in IQ2014 at the SAAR of 5.3 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 7.9 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 2.7 percent and fell 1.5 percent relative to a year earlier. In IVQ2014, Japan’s GDP grew 0.5 percent, at the SAAR of 2.1 percent, decreasing 1.0 percent relative to a year earlier. The GDP of Japan increased 1.3 percent in IQ2015 at the SAAR of 5.2 percent and decreased 1.0 percent relative to a year earlier. Japan’s GDP decreased 0.4 percent in IIQ2015 at the SAAR of minus 1.7 percent and increased 0.7 percent relative to a year earlier. The GDP of Japan increased 0.4 percent in IIIQ2015 at the SAAR of 1.7 percent and increased 1.8 percent relative to a year earlier. Japan’s GDP contracted 0.4 percent in IVQ2015 at the SAAR of minus 1.8 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 1.9 percent and increased 0.1 percent relative to a year earlier.
• China. China’s GDP grew 1.8 percent in IQ2012, annualizing to 7.4 percent, and 8.0 percent relative to a year earlier. The GDP of China grew at 2.1 percent in IIQ2012, which annualizes to 8.7 percent and 7.5 percent relative to a year earlier. China grew at 1.8 percent in IIIQ2012, which annualizes at 7.4 percent and 7.4 percent relative to a year earlier. In IVQ2012, China grew at 1.9 percent, which annualizes at 7.8 percent, and 8.0 percent in IVQ2012 relative to IVQ2011. In IQ2013, China grew at 1.8 percent, which annualizes at 7.4 percent and 7.8 percent relative to a year earlier. In IIQ2013, China grew at 1.7 percent, which annualizes at 7.0 percent and 7.5 percent relative to a year earlier. China grew at 2.2 percent in IIIQ2013, which annualizes at 9.1 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 7.6 percent relative to a year earlier. China’s GDP grew 1.7 percent in IQ2014, which annualizes to 7.0 percent, and 7.3 percent relative to a year earlier. China’s GDP grew 1.8 percent in IIQ2014, which annualizes at 7.4 percent, and 7.4 percent relative to a year earlier. China’s GDP grew 1.9 percent in IIIQ2014, which is equivalent to 7.8 percent in a year, and 7.1 percent relative to a year earlier. The GDP of China grew 1.7 percent in IVQ2014, which annualizes at 7.0 percent, and 7.2 percent relative to a year earlier. The GDP of China grew at 1.4 percent in IQ2015, which annualizes at 5.7 percent, and 7.0 percent relative to a year earlier. The GDP of China grew 1.8 percent in IIQ2015, which annualizes at 7.4 percent, and increased 7.0 percent relative to a year earlier. In IIIQ2015, China’s GDP grew at 1.8 percent, which annualizes at 7.4 percent and increased 6.9 percent relative to a year earlier. The GDP of China grew at 1.5 percent in IVQ2015, which annualizes at 6.1 percent and increased 6.8 percent relative to a year earlier. The GDP of China grew 1.1 percent in IQ2016, which annualizes at 4.5 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 2015.
• Euro Area. GDP fell 0.2 percent in the euro area in IQ2012 and decreased 0.5 in IQ2012 relative to a year earlier. Euro area GDP contracted 0.3 percent IIQ2012 and fell 0.8 percent relative to a year earlier. In IIIQ2012, euro area GDP fell 0.1 percent and declined 0.9 percent relative to a year earlier. In IVQ2012, euro area GDP fell 0.4 percent relative to the prior quarter and fell 1.0 percent relative to a year earlier. In IQ2013, the GDP of the euro area fell 0.3 percent and decreased 1.1 percent relative to a year earlier. The GDP of the euro area increased 0.4 percent in IIQ2013 and fell 0.4 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 0.6 percent relative to a year earlier. In IQ2014, the GDP of the euro area increased 0.2 percent and increased 1.1 percent relative to a year earlier. The GDP of the euro area increased 0.1 percent in IIQ2014 and increased 0.8 percent relative to a year earlier. The euro area’s GDP increased 0.3 percent in IIIQ2014 and increased 0.8 percent relative to a year earlier. The GDP of the euro area increased 0.4 percent in IVQ2014 and increased 1.0 percent relative to a year earlier. Euro area GDP increased 0.6 percent in IQ2015 and increased 1.3 percent relative to a year earlier. The GDP of the euro area increased 0.4 percent in IIQ2015 and increased 1.6 percent relative to a year earlier. The euro area’s GDP increased 0.3 percent in IIIQ2015 and increased 1.6 percent relative to a year earlier. Euro area GDP increased 0.4 percent in IVQ2015 and increased 1.7 percent relative to a year earlier. Euro area’s GDP increased 0.6 percent in IQ2016 and increased 1.7 percent relative to a year earlier.
• Germany. The GDP of Germany increased 0.4 percent in IQ2012 and increased 1.5 percent relative to a year earlier. In IIQ2012, Germany’s GDP increased 0.1 percent and increased 0.3 percent relative to a year earlier but 0.8 percent relative to a year earlier when adjusted for calendar (CA) effects. In IIIQ2012, Germany’s GDP increased 0.2 percent and 0.1 percent relative to a year earlier. Germany’s GDP contracted 0.5 percent in IVQ2012 and decreased 0.3 percent relative to a year earlier. In IQ2013, Germany’s GDP decreased 0.3 percent and fell 1.7 percent relative to a year earlier. In IIQ2013, Germany’s GDP increased 0.9 percent and grew 0.7 percent relative to a year earlier. The GDP of Germany increased 0.4 percent in IIIQ2013 and grew 1.0 percent relative to a year earlier. In IVQ2013, Germany’s GDP increased 0.3 percent and increased 1.2 percent relative to a year earlier. The GDP of Germany increased 0.7 percent in IQ2014 and grew 2.6 percent relative to a year earlier. In IIQ2014, Germany’s GDP contracted 0.1 percent and increased 1.0 percent relative to a year earlier. The GDP of Germany increased 0.2 percent in IIIQ2014 and increased 1.2 percent relative to a year earlier. Germany’s GDP increased 0.6 percent in IVQ2014 and increased 1.6 percent relative to a year earlier. The GDP of Germany increased 0.4 percent in IQ2015 and increased 1.3 percent relative to a year earlier. Germany’s GDP increased 0.4 percent in IIQ2015 and grew 1.6 percent relative to a year earlier. The GDP of Germany increased 0.3 percent in IIIQ2015 and grew 1.7 percent relative to a year earlier. Germany’s GDP increased 0.3 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 1.3 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 1.9 percent SAAR, 0.5 percent relative to the prior quarter and 1.1 percent relative to the same quarter in 2013. In IIQ2013, US GDP grew at 1.1 percent in SAAR, 0.3 percent relative to the prior quarter and 0.9 percent relative to IIQ2012. US GDP grew at 3.0 percent in SAAR in IIIQ2013, 0.7 percent relative to the prior quarter and 1.5 percent relative to the same quarter a year earlier (Section I and earlier http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/05/economic-activity-appears-to-have.html). In IVQ2013, US GDP grew 0.9 percent at 3.8 percent SAAR and 2.5 percent relative to a year earlier. In IQ2014, US GDP decreased 0.2 percent, increased 1.7 percent relative to a year earlier and fell 0.9 percent at SAAR. In IIQ2014, US GDP increased 1.1 percent at 4.6 percent SAAR and increased 2.6 percent relative to a year earlier. US GDP increased 1.1 percent in IIIQ2014 at 4.3 percent SAAR and increased 2.9 percent relative to a year earlier. In IVQ2014, US GDP increased 0.5 percent at SAAR of 2.1 percent and increased 2.5 percent relative to a year earlier. GDP increased 0.2 percent in IQ2015 at SAAR of 0.6 percent and grew 2.9 percent relative to a year earlier. US GDP grew at SAAR 3.9 percent in IIQ2015, increasing 1.0 percent in the quarter and 2.7 percent relative to a year earlier. GDP increased 0.5 percent in IIIQ2015 at SAAR of 2.0 percent and grew 2.1 percent in IIIQ2015 relative to a year earlier. US GDP grew at SAAR of 1.4 percent in IVQ2015, increasing 0.3 percent in the quarter and 2.0 percent relative to a year earlier. In IQ2016, US GDP grew 0.3 percent at SAAR of 1.1 percent and increased 2.1 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. Growth 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 2.9 percent relative to a year earlier. GDP increased 0.4 percent in IIQ2015 and increased 2.3 percent relative to a year earlier. UK GDP increased 0.4 percent in IIIQ2015 and increased 2.0 percent relative to a year earlier. GDP increased 0.7 percent in IVQ2015 and increased 1.8 percent relative to a year earlier. GDP increased 0.4 percent in IQ2016 and increased 2.0 percent relative to a year earlier.
• Italy. The GDP of Italy increased 0.3 percent in IQ2016 and grew 1.0 percent relative to a year earlier. GDP increased 0.2 percent in IVQ2015 and increased 1.1 percent relative to a year earlier. In IIIQ2015, GDP increased 0.2 percent and increased 0.8 percent relative to a year earlier. GDP increased 0.3 percent in IIQ2015 and 0.6 percent relative to a year earlier. GDP increased 0.4 percent in IQ2015 and increased 0.1 percent relative to a year earlier. GDP decreased 0.1 percent in IVQ2014 and fell 0.4 percent relative to a year earlier. GDP decreased 0.1 percent in IIIQ2014 and fell 0.4 percent relative to a year earlier. Italy’s GDP fell 0.1 percent in IIQ2014 and declined 0.2 percent relative to a year earlier. The GDP of Italy decreased 0.1 percent in IQ2014 and fell 0.1 percent relative to a year earlier. Italy’s GDP decreased 0.1 percent in IVQ2013 and fell 0.9 percent relative to a year earlier. The GDP of Italy increased 0.2 percent in IIIQ2013 and fell 1.4 percent relative to a year earlier. Italy’s GDP decreased 0.1 percent in IIQ2013, continuing eight consecutive quarterly declines, and fell 2.0 percent relative to a year earlier. Italy’s GDP fell 0.9 percent in IQ2013 and declined 2.7 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 eight consecutive quarters from IIIQ2011 to IIQ2013 at increasingly higher rates of contraction from 0.5 percent in IIIQ2011 to 1.0 percent in IVQ2011, 0.9 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 0.9 percent in IQ2013. GDP contracted cumulatively 5.1 percent in eight consecutive quarterly contractions from IIIQ2011 to IIQ2013 at the annual equivalent rate of minus 2.6 percent. The total contraction in the 13 quarters including IVQ2013, IQ2014, IIQ2014, IIIQ2014 and IVQ2014 accumulates to 5.6 percent. The yearly rate has fallen from 2.3 percent in IVQ2010 to minus 2.7 percent in IVQ2012, minus 2.7 percent in IQ2013, minus 2.0 percent in IIQ2013 and minus 1.4 percent in IIIQ2013. GDP fell 0.9 percent in IVQ2013 relative to a year earlier. GDP fell 0.1 percent in IQ2014 relative to a year earlier and fell 0.2 percent in IIQ2014 relative to a year earlier. GDP fell 0.4 percent in IIIQ2014 relative to a year earlier and fell 0.4 percent in IVQ2014 relative to a year earlier. GDP increased 0.1 percent in IQ2015 relative to a year earlier and increased 0.6 percent in IIQ2015 relative to a year earlier. GDP increased 0.8 percent in IIIQ2015 relative to a year earlier and increased 1.1 percent in IVQ2015 relative to a year earlier. GDP increased 1.0 percent in IQ2016 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 IQ2016 is lower by 8.5 percent relative to IQ2008. The GDP of the euro zone is 0.5 percent higher in IQ2016 relative to IQ2008. The GDP of Italy increased at the annual equivalent rate of 1.5 percent from IQ1999 to IQ2008, which is lower than 2.3 percent for the euro zone as a whole in the same period. 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 changed 0.0 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 0.6 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 changed 0.0 percent and increased 0.9 percent relative to a year earlier. In IIQ2014, France’s GDP increased 0.1 percent and increased 0.4 percent relative to a year earlier. France’s GDP increased 0.3 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 decreased 0.1 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 1.3 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: 1.0 SAAR: 3.9	3.5
China	1.8	8.0
Euro Area	-0.2	-0.5
Germany	0.4	1.5
France	-0.1	0.4
Italy	-0.9	-2.3
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: -1.6	3.5
China	2.1	7.5
Euro Area	-0.3	-0.8
Germany	0.1	0.3 0.8 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	7.4
Euro Area	-0.1	-0.9
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: -0.2	0.0
China	1.9	8.0
Euro Area	-0.4	-1.0
Germany	-0.5	-0.3
France	0.0	0.0
Italy	-0.6	-2.7
United Kingdom	-0.2	1.3
	IQ2013/IVQ2012	IQ2013/IQ2012
United States	QOQ: 0.5 SAAR: 1.9	1.1
Japan	QOQ: 1.0 SAAR: 4.2	0.3
China	1.8	7.8
Euro Area	-0.3	-1.1
Germany	-0.3	-1.7
France	0.0	0.0
Italy	-0.9	-2.7
UK	0.6	1.5
	IIQ2013/IQ2013	IIQ2013/IIQ2012
United States	QOQ: 0.3 SAAR: 1.1	0.9
Japan	QOQ: 0.7 SAAR: 2.7	1.1
China	1.7	7.5
Euro Area	0.4	-0.4
Germany	0.9	0.7
France	0.7	0.9
Italy	-0.1	-2.0
UK	0.5	2.1
	IIIQ2013/IIQ2013	III/Q2013/  IIIQ2012
USA	QOQ: 0.7 SAAR: 3.0	1.5
Japan	QOQ: 0.5 SAAR: 1.9	2.0
China	2.2	7.9
Euro Area	0.3	0.0
Germany	0.4	1.0
France	0.0	0.6
Italy	0.2	-1.4
UK	0.8	1.7
	IVQ2013/IIIQ2013	IVQ2013/IVQ2012
USA	QOQ: 0.9 SAAR: 3.8	2.5
Japan	QOQ: -0.1 SAAR: -0.3	2.1
China	1.6	7.6
Euro Area	0.2	0.6
Germany	0.3	1.2
France	0.3	0.9
Italy	-0.1	-0.9
UK	0.5	2.4
	IQ2014/IVQ2013	IQ2014/IQ2013
USA	QOQ -0.2 SAAR -0.9	1.7
Japan	QOQ: 1.3 SAAR: 5.3	2.7
China	1.7	7.3
Euro Area	0.2	1.1
Germany	0.7	2.6
France	0.0	0.9
Italy	-0.1	-0.1
UK	0.8	2.6
	IIQ2014/IQ2014	IIQ2014/IIQ2013
USA	QOQ 1.1 SAAR 4.6	2.6
Japan	QOQ: -2.0 SAAR: -7.9	-0.3
China	1.8	7.4
Euro Area	0.1	0.8
Germany	-0.1	1.0
France	0.1	0.4
Italy	-0.1	-0.2
UK	0.9	3.1
	IIIQ2014/IIQ2014	IIIQ2014/IIIQ2013
USA	QOQ: 1.1 SAAR: 4.3	2.9
Japan	QOQ: -0.7 SAAR: -2.7	-1.5
China	1.9	7.1
Euro Area	0.3	0.8
Germany	0.2	1.2
France	0.3	0.7
Italy	-0.1	-0.4
UK	0.8	3.1
	IVQ2014/IIIQ2014	IVQ2014/IVQ2013
USA	QOQ: 0.5 SAAR: 2.1	2.5
Japan	QOQ: 0.5 SAAR: 2.1	-1.0
China	1.7	7.2
Euro Area	0.4	1.0
Germany	0.6	1.6
France	0.2	0.6
Italy	-0.1	-0.4
UK	0.8	3.5
	IQ2015/IVQ2014	IQ2015/IQ2014
USA	QOQ: 0.2 SAAR: 0.6	2.9
Japan	QOQ: 1.3 SAAR: 5.2	-1.0
China	1.4	7.0
Euro Area	0.6	1.3
Germany	0.4	1.3
France	0.6	1.3
Italy	0.4	0.1
UK	0.3	2.9
	IIQ2015/IQ2015	IIQ2015/IIQ2014
USA	QOQ: 1.0 SAAR: 3.9	2.7
Japan	QOQ: -0.4 SAAR: -1.7	0.7
China	1.8	7.0
Euro Area	0.4	1.6
Germany	0.4	1.6
France	-0.1	1.1
Italy	0.3	0.6
UK	0.4	2.3
	IIIQ2015/IIQ2015	IIIQ2015/IIIQ2014
USA	QOQ: 0.5 SAAR: 1.7	2.1
Japan	QOQ: 0.4 SAAR: 1.7	1.8
China	1.8	6.9
Euro Area	0.3	1.6
Germany	0.3	1.7
France	0.4	1.1
Italy	0.2	0.8
UK	0.4	2.0
	IVQ2015/IIIQ2015	IVQ2015/IVQ2014
USA	QOQ: 0.3 SAAR: 1.4	2.0
Japan	QOQ: -0.4 SAAR: -1.8	0.7
China	1.5	6.8
Euro Area	0.4	1.7
Germany	0.3	2.1
France	0.4	1.3
Italy	0.2	1.1
UK	0.7	1.8
	IQ2016/IVQ2015	IQ2016/IQ2015
USA	QOQ: 0.3 SAAR: 1.1	2.1
Japan	QOQ: 0.5 SAAR: 1.9	0.1
China	1.1	6.7
Euro Area	0.6	1.7
Germany	0.7	1.3
France	0.6	1.3
Italy	0.3	1.0
UK	0.4	2.0

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.

• Japan. Japan provides the most worrisome data (http://cmpassocregulationblog.blogspot.com/2015/08/global-decline-of-values-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/valuation-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/imf-view-of-economy-and-finance-united.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/02/financial-and-international.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier (http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/08/monetary-policy-world-inflation-waves.html and earlier http://cmpassocregulationblog.blogspot.com/2014/07/world-inflation-waves-united-states.html and earlier (http://cmpassocregulationblog.blogspot.com/2014/06/valuation-risks-world-inflation-waves.html and earlier http://cmpassocregulationblog.blogspot.com/2014/05/united-states-commercial-banks-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/05/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html and earlier http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html and earlier http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-zero-interest-rates-world.html http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-world-inflation.html http://cmpassocregulationblog.blogspot.com/2013/09/duration-dumping-and-peaking-valuations_8763.html http://cmpass ocregulationblog.blogspot.com/2013/08/interest-rate-risks-duration-dumping.html and earlier http://cmpassocregulationblog.blogspot.com/2013/07/duration-dumping-steepening-yield-curve.html and earlier http://cmpassocregulationblog.blogspot.com/2013/06/paring-quantitative-easing-policy-and_4699.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/05/united-states-commercial-banks-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2013/04/world-inflation-waves-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2013/03/united-states-commercial-banks-assets.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/02/world-inflation-waves-united-states.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2012/12/mediocre-and-decelerating-united-states_24.html and earlier http://cmpassocregulationblog.blogspot.com/2012/11/contraction-of-united-states-real_25.html and for GDP http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what_13.html). In May 2016, Japan’s exports decreased 11.3 percent in 12 months while imports decreased 13.8 percent. The second part of Table V-4 shows that net trade deducted 1.7 percentage points from Japan’s growth of GDP in IIQ2012, deducted 1.9 percentage points from GDP growth in IIIQ2012 and deducted 0.5 percentage points from GDP growth in IVQ2012. Net trade added 0.4 percentage points to GDP growth in IQ2012, 1.9 percentage points in IQ2013 and deducted 0.3 percentage points in IIQ2013. In IIIQ2013, net trade deducted 1.5 percentage points from GDP growth in Japan. Net trade ducted 1.9 percentage points from GDP growth in Japan in IVQ2013. Net trade deducted 0.8 percentage points from GDP growth of Japan in IQ2014. Net trade added 3.5 percentage points to GDP growth in IIQ2014. Net trade added 0.2 percentage points to GDP growth in IIIQ2014 and added 1.5 percentage points in IVQ2014. Net trade added 0.4 percentage points to GDP growth in IQ2015 and deducted 1.4 percentage points in IIQ2015. Net trade added 0.5 percentage points to GDP growth in IIIQ2015 and added 0.3 percentage points in IVQ2015. Net trade added 0.7 percentage points to GDP growth in IQ2016.

• China. In May 2016, China exports decreased 4.1 percent relative to a year earlier and imports decreased 0.4 percent.
• Germany. Germany’s exports changed 0.0 percent in the month of Apr 2016 and increased 3.8 percent in the 12 months ending in Apr 2016. Germany’s imports decreased 0.2 percent in the month of Apr 2016 and changed 0.0 percent in the 12 months ending in Apr 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 0.2 percentage points in IQ2015. Net trade added 0.6 percentage points to GDP growth in IIQ2015 and deducted 0.3 percentage points in IIIQ2015. Net trade deducted 0.5 percentage points in IVQ2015 and deducted 0.1 percentage points in IQ2016.
• 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 0.6 percentage points to GDP growth in IIQ2015 and deducted 0.5 percentage points in IIIQ2015. Net trade added 0.1 percentage points to GDP growth in IVQ2015. Net trade deducted 0.2 percentage points from GDP growth in IQ2016.
• France. France’s exports increased 1.8 percent in Apr 2016 while imports increased 4.1 percent. France’s exports decreased 3.4 percent in the 12 months ending in Apr 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 0.7 percentage points in IIIQ2015. Net trade deducted 0.6 percentage points from GDP growth in IVQ2015 and deducted 0.2 percentage points from GDP growth in IQ2016.
• United States. US exports increased 1.5 percent in Apr 2016 and goods exports decreased 6.9 percent in Jan-Apr 2016 relative to a year earlier. Imports increased 2.1 percent in Apr 2016 and goods imports decreased 6.2 percent in Jan-Apr 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 deducted 0.01 percentage points from US GDP growth in IQ2013 and deducted 0.24 percentage points in IIQ2013. Net traded added 0.16 percentage points to US GDP growth in IIIQ2013. Net trade added 1.26 percentage points to US GDP growth in IVQ2013. Net trade deducted 1.39 percentage points from US GDP growth in IQ2014 and deducted 0.24 percentage points in IIQ2014. Net trade added 0.39 percentage points to GDP growth in IIIQ2014. Net trade deducted 0.89 percentage points from GDP growth in IVQ2014 and deducted 1.92 percentage points from GDP growth in IQ2015. Net trade added 0.18 percentage points to GDP growth in IIQ2015. Net trade deducted 0.26 percentage points from GDP growth in IIIQ2015. Net trade deducted 0.14 percentage points from GDP growth in IVQ2015. Net trade added 0.12 percentage points to GDP growth in IQ2016. Industrial production decreased 0.4 percent in May 2016 and increased 0.6 percent in Apr 2016 after decreasing 1.0 percent in Mar 2016, with all data seasonally adjusted. 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 17.9 percent from the trough in Apr 2009 to May 2016. Manufacturing in May 2016 is lower by 8.4 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. There are about two trillion dollars of GDP less than at trend, explaining the 24.0 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.3 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html). US GDP in IQ2016 is 13.7 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,514.6 billion in IQ2016 or 10.2 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 3.2 percent per year from May 1919 to May 2016. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0886 in May 2016. The actual index NSA in May 2016 is 103.0898, which is 26.9 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 128.9038 in May 2016. The output of manufacturing at 103.0898 in May 2016 is 20.0 percent below trend under this alternative calculation.

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

	Exports M ∆%	Exports 12 M ∆%	Imports M ∆%	Imports 12 M ∆%
USA	1.5 Apr	-6.9 Jan-Apr	2.1 Apr	-6.2 Jan-Apr
Japan		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		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 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 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	-0.9 12-M Apr	-1.0 Jan-Apr	-5.4 12-M Apr	-3.4 Jan-Apr
Germany	0.0 Apr CSA	3.8 Apr	-0.2 Apr CSA	0.0 Apr
France Apr	1.8	-3.4	4.1	1.8
Italy Apr	2.7	-1.0	3.9	-4.3
UK	5.3 Apr	1.3 Feb 16-Apr 16 /Feb 15-Apr 15	4.4 Apr	2.1 Feb 16-Apr 16 /Feb 15-Apr 15
Net Trade % Points GDP Growth	Points
USA	IQ2016 0.12 IVQ2015 -0.14 IIIQ2015 -0.26 IIQ2015 0.18 IQ2015 -1.92 IVQ2014 -0.89 IIIQ2014 0.39 IIQ2014 -0.24 IQ2014 -1.39 IVQ2013 1.26 IIIQ2013 0.16 IIQ2013 -0.24 IQ2013 -0.01 IVQ2012 +0.58 IIIQ2012 0.16 IIQ2012 0.28 IQ2012 -0.02
Japan	0.4 IQ2012 -1.7 IIQ2012 -1.9 IIIQ2012 -0.5 IVQ2012 1.9 IQ2013 -0.3 IIQ2013 -1.5 IIIQ2013 -1.9 IVQ2013 -0.8 IQ2014 3.5 IIQ2014 0.2 IIIQ2014 1.5 IVQ2014 0.4 IQ2015 -1.4 IIQ2015 0.5 IIIQ2015 0.3 IVQ2015 0.7 IQ2016
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 -0.2 IIQ2015 0.6 IIIQ2015 -0.3 IVQ2015 -0.5 IQ2016 -0.1
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 -0.7 IIIQ2015 -0.6 IVQ2015 -0.2 IQ2016
UK	0.7 IIQ2013 -1.7 IIIQ2013 0.1 IVQ2013 0.8 IQ2014 0.3 IIQ2014 -0.7 IIIQ2014 0.3 IVQ2014 -0.6 IQ2015 0.6 IIQ2015 -0.5 IIIQ2015 0.1 IVQ2015 -0.2 IQ2016

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

The geographical breakdown of exports and imports of Japan with selected regions and countries is in Table V-5 for May 2016. The share of Asia in Japan’s trade is close to one-half for 54.4 percent of exports and 49.8 percent of imports. Within Asia, exports to China are 17.7 percent of total exports and imports from China 25.4 percent of total imports. While exports to China decreased 14.9 percent in the 12 months ending in May 2016, imports from China decreased 9.7 percent. The largest export market for Japan in May 2016 is the US with share of 19.1 percent of total exports, which is close to that of China, and share of imports from the US of 12.2 percent in total imports. Japan’s exports to the US decreased 10.7 percent in the 12 months ending in May 2016 and imports from the US decreased 8.5 percent. Western Europe has share of 11.6 percent in Japan’s exports and of 13.5 percent in imports. Rates of growth of exports of Japan in May 2016 are minus 10.7 percent for exports to the US, minus 25.3 percent for exports to Brazil and 5.7 percent for exports to Germany. Comparisons relative to 2011 may have some bias because of the effects of the Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011. Deceleration of growth in China and the US and threat of recession in Europe can reduce world trade and economic activity. Growth rates of imports in the 12 months ending in May 2016 are mixed. Imports from Asia decreased 10.7 percent in the 12 months ending in May 2016 while imports from China decreased 9.7 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

May 2016	Exports Millions Yen	12 months ∆%	Imports Millions Yen	12 months ∆%
Total	5,090,953	-11.3	5,131,673	-13.8
Asia	2,769,048 % Total 54.4	-13.0	2,553,167 % Total 49.8	-10.7
China	901,038 % Total 17.7	-14.9	1,303,031 % Total 25.4	-9.7
USA	969,869 % Total 19.1	-10.7	624,234 % Total 12.2	-8.5
Canada	64,404	-9.3	76,110	-9.5
Brazil	25,661	-25.3	56,459	-13.0
Mexico	81,377	-0.2	46,211	11.7
Western Europe	588,231 % Total 11.6	-3.5	694,484 % Total 13.5	-4.3
Germany	140,562	-5.7	198,234	11.1
France	47,924	-3.1	95,542	-1.2
UK	108,773	-0.7	54,639	-3.9
Middle East	179,996	-10.7	497,461	-30.7
Australia	121,205	-3.7	228,649	-24.0

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 3.5 percent in 2014 to 2.8 percent in 2015 and 3.1 percent in 2016. Growth improves to 4.2 percent on average from 2017 to 2019. World trade would be slower for advanced economies while emerging and developing economies (EMDE) experience faster growth. World economic slowdown would be more challenging with lower growth of world trade.

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

	2014	2015	2016	Average ∆% 2017-2021
World Trade Volume (Goods and Services)	3.5	2.8	3.1	4.2
Exports Goods & Services	3.4	2.8	3.0	4.0
Imports Goods & Services	3.6	2.9	3.3	4.3
Average Oil Price USD/Barrel	96.25	50.79	34.75	Average ∆% 2008-2017 77.37
Average Annual ∆% Export Unit Value of Manufactures	-0.7	-4.0	-2.7	Average ∆% 2008-2017 0.1
Exports of Goods & Services	2014	2015	2016	Average ∆% 2008-2017
EMDE	3.1	1.7	3.8	3.9
G7	3.5	3.4	2.5	2.5
Imports Goods & Services
EMDE	3.7	0.5	3.0	4.6
G7	3.5	4.3	3.4	2.2
Terms of Trade of Goods & Services
EMDE	-0.4	-3.9	-2.3	-0.2
G7	0.3	1.9	1.1	0.1
Terms of Trade of Goods
EMDE	-0.4	-4.1	-1.9	-0.2
G7	0.1	1.8	1.2	-0.1

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

Source: International Monetary Fund World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2016/01/weodata/index.aspx

The JP Morgan Global All-Industry Output Index of the JP Morgan Manufacturing and Services PMI^™, produced by JP Morgan and Markit in association with ISM and IFPSM, with high association with world GDP, decreased to 51.1 in May from 51.6 in Apr, indicating expansion at slower rate (https://www.markiteconomics.com/Survey//PressRelease.mvc/7dbf0ebff0284f2688cd91765242ce6e). This index has remained above the contraction territory of 50.0 during 43 consecutive months. The employment index decreased from 51.1 in Apr to 51.0 in May with input prices rising at faster rate, new orders increasing at slower rate and output increasing at slower rate (https://www.markiteconomics.com/Survey//PressRelease.mvc/7dbf0ebff0284f2688cd91765242ce6e). David Hensley, Director of Global Economic Coordination at JP Morgan, finds slowing growth at the beginning of 2016 (https://www.markiteconomics.com/Survey//PressRelease.mvc/7dbf0ebff0284f2688cd91765242ce6e). The JP Morgan Global Manufacturing PMI^™, produced by JP Morgan and Markit in association with ISM and IFPSM, decreased to 50.0 in May from 50.1 in Apr (https://www.markiteconomics.com/Survey//PressRelease.mvc/48096d48ab73436888622d011aa2d435). New export orders decrease at faster rate. David Hensley, Director of Global Economic Coordination at JP Morgan, weak growth around stagnation levels (https://www.markiteconomics.com/Survey//PressRelease.mvc/48096d48ab73436888622d011aa2d435). The Markit Brazil Composite Output Index decreased from 39.0 in Apr to 38.3 in May, indicating contraction in activity of Brazil’s private sector (https://www.markiteconomics.com/Survey//PressRelease.mvc/f84121ad2bb443f99061c8540b586ed4). The Markit Brazil Services Business Activity index, compiled by Markit, decreased from 37.4 in Apr to 37.3 in May, indicating contracting services activity (https://www.markiteconomics.com/Survey//PressRelease.mvc/f84121ad2bb443f99061c8540b586ed4). Pollyanna de Lima, Economist at Markit, finds deteriorating conditions (https://www.markiteconomics.com/Survey//PressRelease.mvc/f84121ad2bb443f99061c8540b586ed4). The Markit Brazil Purchasing Managers’ Index^TM (PMI^™) decreased from 46.0 in Mar to 42.6 in Apr, indicating deterioration in manufacturing (https://www.markiteconomics.com/Survey//PressRelease.mvc/144432a0dc69424eb86aa8386818327c). Pollyanna De Lima, Economist at Markit, finds stress in manufacturing (https://www.markiteconomics.com/Survey//PressRelease.mvc/144432a0dc69424eb86aa8386818327c).

VA United States. The Markit Flash US Manufacturing Purchasing Managers’ Index^™ (PMI^™) seasonally adjusted increased to 51.4 in Jun from 50.7 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/3620c611f31f462c9e91226c0d33032b). New export orders increased. Chris Williamson, Chief Economist at Markit, finds improvement with challenges (https://www.markiteconomics.com/Survey//PressRelease.mvc/3620c611f31f462c9e91226c0d33032b). The Markit Flash US Services PMI™ Business Activity Index decreased from 52.8 in Apr to 51.2 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/66fa263b5a2943daaebf9518ad1c63be). The Markit Flash US Composite PMI™ Output Index decreased from 52.4 in Apr to 50.8 in May. Chris Williamson, Chief Economist at Markit, finds that the surveys are consistent with growth at annual rate of 0.7 percent in IIQ2016 (https://www.markiteconomics.com/Survey//PressRelease.mvc/66fa263b5a2943daaebf9518ad1c63be). The Markit US Composite PMI™ Output Index of Manufacturing and Services decreased to 50.9 in May from 52.4 in Apr (https://www.markiteconomics.com/Survey//PressRelease.mvc/1ee25280d8e94db7a6ffa42d29b3ff91). The Markit US Services PMI™ Business Activity Index increased from 52.8 in Apr to 51.3 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/1ee25280d8e94db7a6ffa42d29b3ff91). Chris Williamson, Chief Economist at Markit, finds the indexes suggesting stagnating growth with annual growth at 0.7 to 0.8 percent in IIQ2016 (https://www.markiteconomics.com/Survey//PressRelease.mvc/1ee25280d8e94db7a6ffa42d29b3ff91). The Markit US Manufacturing Purchasing Managers’ Index^™ (PMI^™) decreased to 50.7 in May from 50.8 in Apr, which indicates expansion at slower rate (https://www.markiteconomics.com/Survey//PressRelease.mvc/94b2d66aab544244b5d497c58d37abaf). New foreign orders decreased. Chris Williamson, Chief Economist at Markit, finds contraction of factory output at annual rate of 3.0 percent and heavy losses in manufacturing jobs (https://www.markiteconomics.com/Survey//PressRelease.mvc/94b2d66aab544244b5d497c58d37abaf). The purchasing managers’ index (PMI) of the Institute for Supply Management (ISM) Report on Business^® increased 0.5-percentage points from 50.8 in Apr to 51.3 in May, which indicates faster expansion (https://www.instituteforsupplymanagement.org/ISMReport/MfgROB.cfm?). The index of new orders decreased 0.1 percentage points from 55.8 in Mar to 55.7 in May. The index of new exports changed 0.0 percentage points from 52.0 in Apr to 52.0 in May, expanding at the same rate. The Non-Manufacturing ISM Report on Business^® PMI decreased 2.8 percentage points from 55.7 in Apr to 52.9 in May, indicating growth of business activity/production during 82 consecutive months, while the index of new orders decreased 5.7 percentage points from 59.9 in Apr to 54.2 in May (https://www.instituteforsupplymanagement.org/ISMReport/NonMfgROB.cfm?). Table USA provides the country economic indicators for the US.

Table USA, US Economic Indicators

Consumer Price Index	May 12 months NSA ∆%: 1.0; ex food and energy ∆%: 2.2 May month SA ∆%: 0.2; ex food and energy ∆%: 0.2 Blog 6/19/16
Producer Price Index	Finished Goods May 12-month NSA ∆%: -2.3; ex food and energy ∆% 1.6 May month SA ∆% = 0.5; ex food and energy ∆%: 0.1 Final Demand May 12-month NSA ∆%: -0.1; ex food and energy ∆% 1.2 May month SA ∆% = 0.4; ex food and energy ∆%: 0.3 Blog 6/19/16
PCE Inflation	May 12-month NSA ∆%: headline 0.9; ex food and energy ∆% 1.6 Blog 7/1/16
Employment Situation	Household Survey: May Unemployment Rate SA 4.7% Blog calculation People in Job Stress Apr: 24.0 million NSA, 14.3% of Labor Force Establishment Survey: Apr Nonfarm Jobs +38,000; Private +25,000 jobs created  Apr 12-month Average Hourly Earnings Inflation Adjusted ∆%: 1.2 Blog 6/5/16
Nonfarm Hiring	Nonfarm Hiring fell from 63.5 million in 2006 to 58.6 million in 2014 or by 4.9 million and to 61.7 million in 2015 or by 1.8 million Private-Sector Hiring Apr 2016 5.212 million lower by 2.6 percent than 5.352 million in Apr 2006 Blog 6/12/16
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 1.1 IIQ2013/IIQ2012 0.9 IIIQ2013/IIIQ2012 1.5 IVQ2013/IVQ2012 2.5 IQ2014/IQ2013 1.7 IIQ2014/IIQ2013 2.6 IIIQ2014/IIIQ2013 2.9 IVQ2014/IVQ2013 2.5 IQ2015/IQ2014 2.9 IIQ2015/IIQ2014 2.7 IIIQ2015/IIIQ2014 2.1 IVQ2015/IVQ2014 2.0 IQ2016/IQ2015 2.1 IQ2012 SAAR 2.7 IIQ2012 SAAR 1.9 IIIQ2012 SAAR 0.5 IVQ2012 SAAR 0.1 IQ2013 SAAR 1.9 IIQ2013 SAAR 1.1 IIIQ2013 SAAR 3.0 IVQ2013 SAAR 3.8 IQ2014 SAAR -0.9 IIQ2014 SAAR 4.6 IIIQ2014 SAAR 4.3 IVQ2014 SAAR 2.1 IQ2015 SAAR 0.6 IIQ2015 SAAR: 3.9 IIIQ2015 SAAR: 2.0 IVQ2015 SAAR: 1.4 IQ2016 SAAR: 1.1 Blog 7/1/16
Real Private Fixed Investment	SAAR IQ2016 ∆% -0.4 IVQ2007 to IQ2016: 6.4% Blog 7/1/16
Corporate Profits	IQ2016 SAAR: Corporate Profits 1.8; Undistributed Profits 4.5 Blog 7/1/16
Personal Income and Consumption	May month ∆% SA Real Disposable Personal Income (RDPI) SA ∆% 0.1 Real Personal Consumption Expenditures (RPCE): 0.3 12-month May NSA ∆%: RDPI: 3.2; RPCE ∆%: 2.3 Blog 7/1/16
Quarterly Services Report	IQ16/IQ15 NSA ∆%: Information 5.8 Financial & Insurance 3.1 Earlier Data: Blog 3/22/15
Employment Cost Index	Compensation Private IQ2016 SA ∆%: 0.6 Mar 12 months ∆%: 2.8 Earlier Data: Blog 2/1/15
Industrial Production	May month SA ∆%: -0.4 May 12 months SA ∆%: -1.4 Manufacturing May SA -0.4 ∆% May 12 months SA ∆% minus 0.1, NSA minus 0.2 Capacity Utilization: 74.9 Blog 6/19/16
Productivity and Costs	Nonfarm Business Productivity IQ2016∆% SAAE -0.6; IQ2016/IQ2015 ∆% 0.7; Unit Labor Costs SAAE IQ2016 ∆% 4.5; IQ2016/IQ2015 ∆%: 3.0 Blog 6/12/16
New York Fed Manufacturing Index	General Business Conditions From May minus 9.02 to Jun 6.01 New Orders: From May minus 5.54 to Jun 10.9 Blog 6/19/16
Philadelphia Fed Business Outlook Index	General Index from May -1.8 to Jun 4.7 New Orders from May minus 1.9 to Jun minus 3.0 Blog 6/19/16
Manufacturing Shipments and Orders	Apr Orders SA ∆% 1.9 Ex Transport 0.5 Jan-Apr 16/Jan-Apr 15 NSA New Orders ∆% minus 2.3 Ex transport minus 3.6 Earlier data: Blog 4/5/15
Durable Goods	May New Orders SA ∆%: minus 2.2; ex transport ∆%: minus 0.3 Jan-May 16/Jan-May 15 New Orders NSA ∆%: 1.7; ex transport ∆% -0.5 Earlier Data: Blog 4/26/15
Sales of New Motor Vehicles	Jun 2016 8,645,016; Jun 2015 8,521,260. Jun 16 SAAR 16.66 million, May 16 SAAR 17.45 million, Jun 2015 SAAR 17.00 million Blog 7/1/16
Sales of Merchant Wholesalers	Jan-Apr 2016/Jan-Apr 2015 NSA ∆%: Total -2.8; Durable Goods: minus 1.3; Nondurable Goods: -4.1 EARLIER DATA: Blog 4/12/15
Sales and Inventories of Manufacturers, Retailers and Merchant Wholesalers	Apr 16 12-M NSA ∆%: Sales Total Business -2.9; Manufacturers -4.7 Retailers 2.1; Merchant Wholesalers -5.1 Blog 6/19/16
Sales for Retail and Food Services	Jan-May 2016/Jan-May 2015 ∆%: Retail and Food Services 3.2; Retail ∆% 2.7 Blog 6/19/16
Value of Construction Put in Place	SAAR month SA May ∆%: minus 0.8 Jan-May 16/Jan-May 15 NSA: 8.2 Earlier Data: Blog 4/5/15
Case-Shiller Home Prices	Apr 2016/ Apr 2015 ∆% NSA: 10 Cities 4.7; 20 Cities: 5.4; National: 5.0 ∆% Apr SA: 10 Cities 0.3 ; 20 Cities: 0.5 Blog 6/5/16
FHFA House Price Index Purchases Only	Apr SA ∆% 0.2; 12 month NSA ∆%: 5.9 Blog 6/26/16
New House Sales	May 2016 month SAAR ∆%: minus 6.0 Jan-May 2016/Jan-May 2015 NSA ∆%: 7.1 Blog 6/26/16
Housing Starts and Permits	May Starts month SA ∆% -0.3; Permits ∆%: 0.7 Jan-May 2016/Jan-May 2015 NSA ∆% Starts 10.2; Permits  ∆% 2.9 Earlier Data: Blog 4/19/15
Rate of Homeownership	IQ2016: 63.5 Blog 5/1/16
Trade Balance	Balance Apr SA -$37,436 million versus Mar -$35,536 million Exports Apr SA ∆%: 1.5 Imports Apr SA ∆%: 2.1 Goods Exports Jan-Apr 2016/Jan-Apr 2015 NSA ∆%: minus 6.9 Goods Imports Jan-Apr 2016/Jan-Apr 2015 NSA ∆%: minus 6.2 Blog 6/12/16
Export and Import Prices	May 12-month NSA ∆%: Imports -5.0; Exports -4.5 Earlier Data: Blog 4/12/15
Consumer Credit	Apr ∆% annual rate: Total 4.5; Revolving 2.1; Nonrevolving 5.4 Earlier Data: Blog 5/10/15
Net Foreign Purchases of Long-term Treasury Securities	Apr Net Foreign Purchases of Long-term US Securities: minus $91.5 billion Major Holders of Treasury Securities: China $1242.8 billion; Japan $1142.8 billion; Total Foreign US Treasury Holdings Nov $6238.5 billion Blog 6/19/16
Treasury Budget	Fiscal Year 2016/2015 ∆% May: Receipts 1.7; Outlays 3.1; Individual Income Taxes 2.3 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 Blog 6/12/2016
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 2040: Long-term Debt/GDP 103% Blog 8/26/12 11/18/12 2/10/13 9/22/13 2/16/14 8/24/14 9/14/14 3/1/15 6/21/15 1/3/16 4/10/16
Commercial Banks Assets and Liabilities	May 2016 SAAR ∆%: Securities 10.0 Loans 6.6 Cash Assets -5.3 Deposits 5.2 Blog 6/26/16
Flow of Funds Net Worth of Families and Nonprofits	IQ2016 ∆ since 2007 Assets +$21,657.7 BN Nonfinancial 3355.5 BN Real estate $2407.3 BN Financial +18,302.1 BN Net Worth +$21,509.6 BN Blog 6/26/16
Current Account Balance of Payments	IVQ2015 -127,927 MM % GDP 2.8 Blog 4/10/16
Collapse of United States Dynamism of Income Growth and Employment Creation	Blog 6/26/16
IMF View	World Real Economic Growth 2016 ∆% 3.2 Blog 4/24/16
Income, Poverty and Health Insurance in the United States	46.657 Million Below Poverty in 2014, 14.8% of Population Median Family Income CPI-2014 Adjusted $53,657 in 2014 back to 1996 Levels Uncovered by Health Insurance 32.968 Million in 2014 Blog 10/11/15
Monetary Policy and Cyclical Valuation of Risk Financial Assets	Blog 1/17/2016

Links to blog comments in Table USA: 6/26/16 http://cmpassocregulationblog.blogspot.com/2016/06/of-course-considerable-uncertainty.html

6/19/2016 http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html

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

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

4/10/16 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 Jun 2016, light vehicle sales accumulated to 8,645,016 million, which is higher by 1.5 percent relative to 8,521,260 a year earlier (http://motorintelligence.com/m_frameset.html). The seasonally adjusted annual rate of light vehicle sales in the US reached 16.66 million in Jun 2016, lower than 17.45 million in May 2016 and lower than 17.00 million in Jun 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.

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

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

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

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

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

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

W = Y/r (1)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

According to Pinto (2008) in testimony to Congress:

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

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

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

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

Table IIA-1 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 94.7 percent in the 10-city composite of the Case-Shiller home price index, 78.0 percent in the 20-city composite and 62.9 percent in the US national home price index between Apr 2000 and Apr 2005. Prices rose around 100 percent from Mar 2000 to Mar 2006, increasing 116.3 percent for the 10-city composite, 97.9 percent for the 20-city composite and 79.1 percent in the US national index. House prices rose 38.3 percent between Apr 2003 and Apr 2005 for the 10-city composite, 33.0 percent for the 20-city composite and 28.0 percent for the US national propelled by low fed funds rates of 1.0 percent between Jun 2003 and Jun 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Jun 2004 until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Apr 2003 and Apr 2006, the 10-city index gained 53.6 percent; the 20-city index increased 47.8 percent; and the US national 40.7 percent. House prices have fallen from Apr 2006 to Apr 2016 by 10.8 percent for the 10-city composite, 8.9 percent for the 20-city composite and 2.7 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Apr 2016, house prices increased 4.7 percent in the 10-city composite, increasing 5.4 percent in the 20-city composite and 5.0 percent in the US national. Table IIA-6 also shows that house prices increased 93.0 percent between Apr 2000 and Apr 2016 for the 10-city composite, increasing 80.3 percent for the 20-city composite and 74.3 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 11.3 percent from the peak in Jun 2006 to Apr 2016 and the 20-city composite fell 9.6 percent from the peak in Jul 2006 to Apr 2016. The US national fell 3.2 percent from the peak of the 10-city composite to Apr 2016 and 3.2 percent from the peak of the 20-city composite to Apr 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
∆% Apr 2000 to Apr 2003	40.8	33.9	27.3
∆% Apr 2000 to Apr 2005	94.7	78.0	62.9
∆% Apr 2003 to Apr 2005	38.3	33.0	28.0
∆% Apr 2000 to Apr 2006	116.3	97.9	79.1
∆% Apr 2003 to Apr 2006	53.6	47.8	40.7
∆% Apr 2005 to Apr 2016	-0.9	1.3	7.0
∆% Apr 2006 to Apr 2016	-10.8	-8.9	-2.7
∆% Apr 2009 to Apr 2016	33.5	34.0	21.6
∆% Apr 2010 to Apr 2016	27.6	29.1	22.9
∆% Apr 2011 to Apr 2016	32.3	34.8	28.4
∆% Apr 2012 to Apr 2016	35.3	37.2	29.0
∆% Apr 2013 to Apr 2016	21.4	22.6	18.3
∆% Apr 2014 to Apr 2016	9.5	10.6	9.6
∆% Apr 2015 to Apr 2016	4.7	5.4	5.0
∆% Apr 2000 to Apr 2016	93.0	80.3	74.3
∆% Peak Jun 2006 Apr 2016	-11.3		-3.2
∆% Peak Jul 2006 Apr 2016		-9.6	-3.2
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-case-shiller

Price increases measured by the Case-Shiller house price indices show in data for Apr 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/367344_cshomeprice-release-0628.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 1.0 percent in Apr 2016 and the 20-city increased 1.1 percent. The 10-city SA increased 0.3 percent in Mar 2016 and the 20-city composite SA increased 0.5 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

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

	10-City Composite SA	10-City Composite NSA	20-City Composite SA	20-City Composite NSA
Apr 2016	0.3	1.0	0.5	1.1
Mar	0.6	0.9	0.8	1.0
Feb	0.6	0.2	0.7	0.2
Jan	0.7	0.0	0.8	0.0
Dec 2015	0.6	-0.1	0.7	0.0
Nov	0.8	0.0	0.8	0.0
Oct	0.6	-0.1	0.7	0.0
Sep	0.5	0.1	0.5	0.1
Aug	0.1	0.2	0.2	0.3
Jul	0.0	0.6	0.0	0.6
Jun	-0.1	0.9	0.0	0.9
May	-0.2	1.1	-0.5	1.1
Apr	0.3	1.1	0.5	1.1
Mar	0.5	0.8	0.8	0.9
Feb	1.0	0.5	1.0	0.5
Jan	0.7	-0.1	0.7	-0.1
Dec 2014	0.8	0.0	0.8	0.0
Nov	0.6	-0.3	0.6	-0.2
Oct	0.6	-0.1	0.6	-0.1
Sep	0.3	-0.1	0.3	-0.1
Aug	0.0	0.2	0.1	0.2
Jul	-0.1	0.6	-0.1	0.6
Jun	0.0	1.0	0.0	1.0
May	-0.2	1.1	-0.4	1.1
Apr	0.3	1.1	0.4	1.2
Mar	0.7	0.8	0.8	0.9
Feb	0.6	0.0	0.6	0.0
Jan	0.7	-0.1	0.7	-0.1
Dec 2013	0.7	-0.1	0.7	-0.1
Nov	0.8	0.0	0.8	-0.1
Oct	0.9	0.2	1.0	0.2
Sep	1.1	0.7	1.1	0.7
Aug	1.1	1.3	1.1	1.3
Jul	1.1	1.9	1.1	1.8
Jun	1.1	2.2	1.0	2.2
May	1.1	2.5	0.9	2.5
Apr	1.8	2.6	1.8	2.6
Mar	1.3	1.3	1.3	1.3
Feb	1.0	0.3	1.0	0.2
Jan	0.8	0.0	0.9	0.0
Dec 2012	1.0	0.2	0.9	0.2
Nov	0.6	-0.3	0.7	-0.2
Oct	0.6	-0.2	0.7	-0.1
Sep	0.6	0.3	0.6	0.3
Aug	0.6	0.8	0.6	0.9
Jul	0.6	1.5	0.7	1.6
Jun	1.0	2.1	1.1	2.3
May	0.9	2.2	0.8	2.4
Apr	0.6	1.4	0.7	1.4
Mar	0.1	-0.1	0.1	0.0
Feb	-0.1	-0.9	0.0	-0.8
Jan	-0.2	-1.1	-0.1	-1.0
Dec 2011	-0.5	-1.2	-0.4	-1.1
Nov	-0.6	-1.4	-0.5	-1.3
Oct	-0.6	-1.3	-0.6	-1.4
Sep	-0.4	-0.6	-0.4	-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	-0.3	1.0	-0.4	1.0
Apr	-0.2	0.6	0.0	0.6
Mar	-0.6	-1.0	-0.8	-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-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 $10.5 trillion or 12.9 percent from 2007 to 2008 and $8.8 trillion or 10.9 percent to 2009. Net worth fell $10.4 trillion from 2007 to 2008 or 15.6 percent and $8.5 trillion to 2009 or 12.7 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	80,967.0	70,487.1	-10,470.9	72,160.0	-8,807.0
Non FIN	28,191.1	24,849.1	-3,342.0	23,743.9	-4,447.2
RE	23,381.6	19,914.9	-3,466.7	18,787.5	-4,594.1
FIN	52,776.0	45,638.0	-7,138.0	48,416.1	-4,359.9
LIAB	14,389.7	14,272.8	-116.9	14,065.6	-324.1
NW	66,577.3	56,214.4	-10,362.9	58,094.4	-8,482.9

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: first quarter 2016. Washington, DC, Federal Reserve System, Jun 9. 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 68.6 percent of GDP in IQ2016 (http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IQ2016, real estate increased in value by $2407.3 billion and financial assets increased $18,302.1 billion for net gain of real estate and financial assets of $15,894.8 billion, explaining most of the increase in net worth of $21,509.6 billion obtained by deducting the increase in liabilities of $148.1 billion to the increase of assets of $21,657.7 billion. Net worth increased from $66,577.3 billion in 2007 to $88,086.9 billion in IQ2016 by $21,509.6 billion or 32.3 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 238.132 in Mar 2016 (http://www.bls.gov/cpi/data.htm) or 13.4 percent. Net worth adjusted by CPI inflation increased 16.7 percent from 2007 to IQ2015. Real estate assets adjusted for CPI inflation fell 2.7 percent from 2007 to IQ2016. 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 27 quarters from IIIQ2009 to IQ2016. 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 third estimate of GDP for IQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp1q16_3rd.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/2016/05/appropriate-for-fed-to-increase.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/05/economic-activity-appears-to-have.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 and at 7.8 percent from IQ1983 to IVQ1983 (Section I and earlier (http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/05/economic-activity-appears-to-have.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 IQ2016 would have accumulated to 27.6 percent. GDP in IQ2016 would be $19,129.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2614.9 billion than actual $16,514.6 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.0 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.3 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html). US GDP in IQ2016 is 13.7 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,514.6 billion in IQ2016 or 10.2 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 3.2 percent per year from May 1919 to May 2016. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0886 in May 2016. The actual index NSA in May 2016 is 103.0898, which is 26.9 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 128.9038 in May 2016. The output of manufacturing at 103.0898 in May 2016 is 20.0 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 IQ2016
Assets	80,967.0	-3,3842.9	20,802.6	21,657.7
Nonfinancial	28,191.1	-4,737.7	2,799.9	3,355.5
Real Estate	23,381.6	-5,053.9	1,908.9	2,407.3
Financial	52,776.0	894.7	18,002.6	18,302.1
Liabilities	14,389.7	-810.2	130.3	148.1
Net Worth	66,577.3	-3,032.8	20,672.2	21,509.6

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: first quarter 2016. Washington, DC, Federal Reserve System, Jun 9. 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 0.5 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 8.0 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	0.5

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).

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
Apr 2016	+0.8 to +1.4 [+1.2]	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
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
Apr 2016	+0.6 to +1.2 [+1.0]	+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

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

Manufacturing PMI™ increased from 47.7 in May to 47.8 in Jun and the Flash Japan

Manufacturing Output Index™ increased from 46.3 in May to 47.8 in Jun

(https://www.markiteconomics.com/Survey//PressRelease.mvc/1f640e443cfc46c2a8e35fb1dcdfe4a3). New export orders decreased at slower rate. Amy Brownbill, Economist at

Markit, finds slowing conditions in Japan’s manufacturing with adverse effects from the earthquakes in Apr 2016

(https://www.markiteconomics.com/Survey//PressRelease.mvc/1f640e443cfc46c2a8e35fb1dcdfe4a3).The Nikkei Composite Output PMI Index increased from 48.9 in Apr to 49.2 in May, indicating decrease of business activity (https://www.markiteconomics.com/Survey//PressRelease.mvc/a8585c05d45d449c99137b54da329a58). The Nikkei Business Activity Index of Services increased to 50.4 in May from 49.3 in Apr (https://www.markiteconomics.com/Survey//PressRelease.mvc/a8585c05d45d449c99137b54da329a58). Amy Brownbill, Ecoomist at Markit and author of the report, find moderate deterioration (https://www.markiteconomics.com/Survey//PressRelease.mvc/a8585c05d45d449c99137b54da329a58). The Nikkei Purchasing Managers’ Index^™ (PMI™), seasonally adjusted, decreased from 48.2 in Apr to 47.7 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/00c94b0cec8247b6b3ca07cdc668a026). New orders contracted from home and abroad. Amy Brownbill, Economist at Markit, finds deteriorating conditions in manufacturing (https://www.markiteconomics.com/Survey//PressRelease.mvc/00c94b0cec8247b6b3ca07cdc668a026).Table JPY provides the country data table for Japan.

Table JPY, Japan, Economic Indicators

Historical GDP and CPI	1981-2010 Real GDP Growth and CPI Inflation 1981-2010 Blog 8/9/11 Table 26
Corporate Goods Prices	May ∆% 0.2 12 months ∆% -4.2 Blog 6/12/16
Consumer Price Index	May NSA ∆% 0.1; May 12 months NSA ∆% -0.4 Blog 7/1/16
Real GDP Growth	IQ2016 ∆%: 0.5 on IVQ2015;  IQ2016 SAAR 1.9; ∆% from quarter a year earlier: 0.1 % 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
Employment Report	May Unemployed 2.16 million Change in unemployed since last year: -80 thousand Unemployment rate: 3.2 % Blog 7/1/16
All Industry Indices	Apr month SA ∆% 1.3 12-month NSA ∆% 0.1 Earlier Data: Blog 4/26/15
Industrial Production	May SA month ∆%: -2.3 May 12-month NSA ∆% -0.1 Earlier Data: Blog 3/29/15
Machine Orders	Total Apr ∆% -12.8 Private ∆%: -20.2 Apr ∆% Excluding Volatile Orders minus 11.0 Earlier Data: Blog 4/19/15
Tertiary Index	Apr month SA ∆% 1.4 Apr 12 months NSA ∆% 1.1 Earlier Data: Blog 4/26/15
Wholesale and Retail Sales	May 12 months: Total ∆%: -5.1 Wholesale ∆%: -6.6 Retail ∆%: -1.9 Earlier Data: Blog 3/29/15
Family Income and Expenditure Survey	May 12-month ∆% total nominal consumption -1.6, real -1.1 Earlier Data: Blog 3/29/15
Trade Balance	Exports May 12 months ∆%: minus 11.3 Imports May 12 months ∆% -13.8 Earlier Data: Blog 4/26/15

Links to blog comments in Table JPY: 6/12/16 http://cmpassocregulationblog.blogspot.com/2016/06/considerable-uncertainty-about-economic.html

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

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

The employment report for Japan in May 2016 is in Table VB-1. The number unemployed reached 2.16 million in May 2016, decreasing 80 thousand from a year earlier or 3.6 percent. The rate of unemployment not seasonally adjusted reached 3.2 percent, decreasing 0.2 percentage points from a year earlier. Population changed 0.0 percent from a year earlier. The labor force increased 0.6 percent from a year earlier and the labor participation rate stood at 60.1, increasing 0.3 percentage points from a year earlier. The employment rate moved to 58.2 percent, increasing 0.4 percentage points relative to a year earlier.

Table VB-1, Japan, Employment Report May 2016

May 2016 Unemployed	2.16 million
Change since last year	-80 thousand; ∆% -3.6
Unemployment rate	SA 3.2%, 0.0 from earlier month; NSA 3.2%, -0.2 from earlier year
Population ≥ 15 years	110.76 million
Change since last year	∆% 0.0
Labor Force	66.62 million
Change since last year	∆% 0.6
Employed	64.46 million
Change since last year	∆% 0.7
Labor force participation rate	60.1
Change since last year	0.3
Employment rate	58.2%
Change since last year	0.4

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 0.1 percentage points from 3.3 percent in May 2015 to 3.2 percent in May 2016.

Table VB-2, Japan, Unemployment Rate, SA

	Unemployment Rate SA
May 2016	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.

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 53.1 in May 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 49.2 in May 2016.

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

	Total Index	New Orders	Interm. Input Prices	Subs Prices	Exp
May 2016	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 53.1 in May 2016.

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

Source: National Bureau of Statistics of China

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

Table CIPMMFG provides the index of purchasing managers of manufacturing seasonally adjusted of the National Bureau of Statistics of China. The general index (IPM) rose from 50.5 in Jan 2012 to 53.3 in Apr 2012, falling to 49.2 in Aug 2012, rebounding to 50.6 in Dec 2012. The index fell to 50.1 in Jun 2013, barely above the neutral frontier at 50.0, recovering to 51.4 in Nov 2013 but falling to 51.0 in Dec 2013. The index fell to 50.5 in Jan 2014, 50.1 in Dec 2014 and 50.1 in May 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 50.7 in May 2016.

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

	IPM	PI	NOI	INV	EMP	SDEL
2016
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 50.1 in May 2016.

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 IQ2016 relative to the same period in 2015 was 6.7 percent and cumulative growth to IQ2016 was 6.7 percent, as shown in Table VC-GDP. Secondary industry accounts for 37.5 percent of cumulative GDP in IQ2016. In cumulative IQ2016, industry accounts for 33.0 percent of GDP and construction for 4.7 percent. Tertiary industry accounts for 56.9 percent of cumulative GDP in IQ2016 and primary industry for 5.6 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 10.4 percent in IQ2011 to 6.1 percent in IVQ2011 and 7.4 percent in IQ2012, rebounding to 8.7 percent in IIQ2012, 7.4 percent in IIIQ2012 and 7.8 percent in IVQ2012. Annual equivalent growth in IQ2013 eased to 7.4 percent and to 7.0 percent in IIQ2013, rebounding to 9.1 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 increased to 7.8 percent in IIIQ2014 and slowed to 7.0 percent in IVQ2014. Growth slowed to annual equivalent 5.7 percent in IQ2015, increasing to 7.4 percent in IIQ2015 and 7.4 percent in IIIQ2015. Growth slowed to 6.1 percent in annual equivalent in IVQ2015 and 4.5 percent in IQ2016.

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

Cumulative GDP IQ2016	Value Current CNY Billion IQ2016	Value Current CNY Billion IQ2016 to IQ2016	IQ2016 Year-on-Year Constant Prices ∆%	Cumulative to IQ2016 ∆%
GDP	15,852.6	15,852.6	6.7	6.7
Primary Industry	880.3	880.3	2.9	2.9
Farming	915.3	915.3	3.1	3.1
Secondary Industry	5,951.0	5,951.0	5.8	5.8
Industry	5,233.5	5,233.5	5.5	5.5
Construction	743.8	743.8	7.8	7.8
Tertiary Industry	9,021.4	9,021.4	7.6	7.6
Transport, Storage, Post	724.9	724.9	3.3	3.3
Wholesale, Retail Trades	1,629.3	1,629.3	5.8	5.8
Accommodation and Restaurants	311.3	311.3	7.0	7.0
Finance	1,579.1	1,579.1	8.1	8.1
Real Estate	1,081.9	1,081.9	9.1	9.1
Other	3,633.6	3,633.6	8.7	8.7
Growth in Quarter Relative to Prior Quarter	∆% on Prior Quarter		∆% Annual Equivalent	∆% Year-on-Year
2016
IQ2016	1.1		4.5	6.7
2015
IVQ2015	1.5		6.1	6.8
IIIQ2015	1.8		7.4	6.9
IIQ2015	1.8		7.4	7.0
IQ2015	1.4		5.7	7.0
2014
IVQ2014	1.7		7.0	7.2
IIIQ2014	1.9		7.8	7.1
IIQ2014	1.8		7.4	7.4
IQ2014	1.7		7.0	7.3
2013
IVQ2013	1.6		6.6	7.6
IIIQ2013	2.2		9.1	7.9
IIQ2013	1.7		7.0	7.5
IQ2013	1.8		7.4	7.8
2012
IVQ2012	1.9		7.8	8.0
IIIQ2012	1.8		7.4	7.4
IIQ2012	2.1		8.7	7.5
IQ2012	1.8		7.4	8.0
2011
IVQ2011	1.5		6.1	8.7
IIIQ2011	2.0		8.2	9.4
IIQ2011	2.4		10.0	9.9
IQ2011	2.5		10.4	10.2

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

Growth of China’s GDP in IQ2016 relative to the same period in 2015 was 6.7 percent and cumulative growth to IQ2016 was 6.7 percent, as shown in Table VC-GDP. Secondary industry accounts for 37.5 percent of cumulative GDP in IQ2016. In cumulative IQ2016, industry accounts for 33.0 percent of GDP and construction for 4.7 percent. Tertiary industry accounts for 56.9 percent of cumulative GDP in IQ2016 and primary industry for 5.6 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 7.8 percent in IQ2013, 7.5 percent in IIQ2013 and 7.9 percent in IIIQ2013. GDP grew 7.6 percent in IVQ2013 relative to a year earlier and 1.6 percent relative to IIIQ2013, which is equivalent to 6.6 percent per year. GDP grew 7.3 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 7.4 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 1.9 percent relative to the prior quarter, which is 7.8 percent in annual equivalent. GDP grew 1.7 percent in IVQ2014, which is 7.0 percent in annual equivalent and 7.2 percent relative to a year earlier. In IQ2015, GDP grew 1.4 percent, which is equivalent to 5.7 in a year and 7.0 percent relative to a year earlier. GDP grew 1.8 percent in IIQ2015, which is equivalent to 7.4 percent in a year, and grew 7.0 percent relative to a year earlier. GDP grew at 1.8 percent in IIIQ2015, which is equivalent to 7.4 percent in a year, and grew 6.9 percent relative to a year earlier. GDP grew at 1.5 percent in IVQ2015, which is equivalent to 6.1 percent in a year and increased 6.8 percent relative to a year earlier. In IQ2016, GDP grew at 1.1 percent, which is equivalent to 4.5 percent, 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
GDP	7.0	7.0	6.9	6.8	6.7
Primary Industry	3.2	3.5	3.8	4.1	2.9
Secondary Industry	6.4	6.1	6.0	6.1	5.8
Tertiary Industry	7.9	8.4	8.4	8.2	7.6
GDP ∆% Relative to a Prior Quarter	1.4	1.8	1.8	1.5	1.1
	IQ 2013	IIQ 2013	IIIQ 2013	IVQ 2013	IQ 2014	IIQ 2014	IIIQ 2014	IVQ 2014
GDP	7.8	7.5	7.9	7.6	7.3	7.4	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	1.8	1.7	2.2	1.6	1.7	1.8	1.9	1.7
	IQ 2011	IIQ 2011	IIIQ 2011	IVQ 2011	IQ  2012	IIQ 2012	IIIQ 2012	IVQ 2012
GDP	10.2	9.9	9.4	8.7	8.0	7.5	7.4	8.0
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	2.5	2.4	2.0	1.5	1.8	2.1	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.

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

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

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

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.

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, decreasing from 50.8 in Apr to 50.5 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/c3891b1d01224baea751de40579bacbe). He Fan, Chief Economist at Caixin Insight Group, finds challenging services activity (https://www.markiteconomics.com/Survey//PressRelease.mvc/c3891b1d01224baea751de40579bacbe). The Caixin General Manufacturing PMI^™ decreased to 49.2 in May from 49.4 in Apr, indicating moderate deterioration in manufacturing (https://www.markiteconomics.com/Survey//PressRelease.mvc/e35e1bd270db4a16a24474a718ff8861). He Fan, Chief Economist at Caixin Insight Group, finds headwinds (https://www.markiteconomics.com/Survey//PressRelease.mvc/e35e1bd270db4a16a24474a718ff8861). Table CNY provides the country data table for China.

Table CNY, China, Economic Indicators

Price Indexes for Industry	May 12-month ∆%: minus 2.8 May month ∆%: 0.5 Blog 6/19/16
Consumer Price Index	May 12-month ∆%: 2.0 May month ∆%: -0.5 Blog 6/19/16
Value Added of Industry	Apr month ∆%: 0.47 Jan-Apr 2016/Jan-Apr 2015 ∆%: 5.8 Earlier Data Blog 4/19/15
GDP Growth Rate	Year IQ2016 ∆%: 6.7 First Quarter 2016 ∆%: 1.1 Quarter IQ2016 AE ∆%: 4.5 Blog 4/24/16
Investment in Fixed Assets	Total Jan-Apr 2015 ∆%: 10.5 Real estate development: 7.2 Earlier Data: Blog 4/19/15
Retail Sales	Apr month ∆%: 0.80 Jan-Apr 2016 ∆%:10.3 Earlier Data: Blog 4/19/15
Trade Balance	May balance $49.98 billion Exports 12M ∆% -4.1 Imports 12M ∆% -0.4 2015 Exports ∆% -2.8 2015 Imports ∆% -14.1 Cumulative May 2016: $221.28 billion Cumulative May 2015: $216.72 Earlier Data: Blog 4/19/15

Links to blog comments in Table CNY: 6/19/2016 http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html

4/24/16 http://cmpassocregulationblog.blogspot.com/2016/04/imf-view-of-world-economy-and-finance.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 6.6 percent from IIIQ2009 to IQ2016 at the annual equivalent rate of 1.0 percent. The GDP of the euro area (19 countries) is higher by 0.5 percent in IQ2016 relative to the pre-recession peak in IQ2008. The GDP of the euro area (18) countries increased at the average yearly rate of 2.3 percent from IQ1999 to IQ2008 while that of the euro area (19 countries) increased at 2.3 percent. Table VD-EUR provides yearly growth rates of the combined GDP of the members of the European Monetary Union (EMU) or euro area since 1999. Growth was very strong at 3.2 percent in 2006 and 3.1 percent in 2007. The global recession had strong impact with growth of only 0.5 percent in 2008 and decline of 4.5 percent in 2009. Recovery was at lower growth rates of 2.1 percent in 2010 and 1.6 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 0.9 percent in 2014 and grew 1.7 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	3.1
2008	3.3	7.6	0.5
2009	0.3	9.6	-4.5
2010	1.6	10.2	2.1
2011	2.7	10.2	1.6
2012	2.5	11.4	-0.9
2013	1.3	12.0	-0.3
2014	0.4	11.6	0.9
2015	0.0	10.9	1.7

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	1.7	1.7	1.3	0.8	3.2
2014	0.9	1.6	0.6	-0.3	1.4
2013	-0.3	0.3	0.6	-1.7	-1.7
2012	-0.9	0.4	0.2	-2.8	-2.6
2011	1.6	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	0.5	1.1	0.2	-1.1	1.1
2007	3.1	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

Table EUR, Euro Area Economic Indicators

GDP	IQ2015 ∆% 0.6; IQ2016/IQ2015 ∆% 1.7 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
Unemployment	May 2016: 10.1 % unemployment rate; May 2016: 16.267 million unemployed Blog 7/1/16
HICP	May month ∆%: 0.4 12 months May ∆%: -0.1 Blog 6/19/16
Producer Prices	Euro Zone industrial producer prices Apr ∆%: -0.3 Apr 12-month ∆%: -4.4 Blog 6/5/16
Industrial Production	Mar Month ∆%: -0.8; 12 months ∆%: 0.2 Earlier Data: Blog 4/19/15
Retail Sales	Apr month ∆%: 0.0 Apr 12 months ∆%: 1.4 Earlier Data: Blog 3/15/15
Confidence and Economic Sentiment Indicator	Sentiment 104.4 Jun 2016 Consumer minus 7.3 Jun 2016 Earlier Data: Blog 4/5/15
Trade	Jan-Apr 2016/Jan-Apr 2015 Exports ∆%: -1.0 Imports ∆%: -3.4 Apr 2016 12-month Exports ∆% -0.9 Imports ∆% -5.4 Earlier Data: Blog 4/19/15

Links to blog comments in Table EUR: 6/19/2016 http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html

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

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

EUROSTAT estimates the rate of unemployment in the euro area at 10.1 percent in

May 2016, as shown in Table VD-1A. The number of unemployed in May 2016 was 16.267 million, which was 1.440 million lower than 17.707 million in May 2015. The rate of unemployment fell from 11.0 percent in May 2015 to 10.1 percent in May 2016.

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

	Unemployment Rate %	Number Unemployed Millions
May 2015	10.1	16.267
Apr	10.2	16.379
Mar	10.2	16.454
Feb	10.3	16.673
Jan	10.4	16.722
Dec 2015	10.4	16.818
Nov	10.5	16.887
Oct	10.6	17.032
Sep	10.6	17.111
Aug	10.7	17.207
Jul	10.8	17.343
Jun	11.0	17.639
May	11.0	17.707
Apr	11.0	17.717
Mar	11.2	17.883
Feb	11.2	17.898
Jan	11.2	18.020
Dec 2014	11.3	18.187
Nov	11.5	18.514
Oct	11.5	18.519
Sep	11.5	18.541
Aug	11.5	18.445
Jul	11.6	18.619
Jun	11.5	18.512
May	11.6	18.681
Apr	11.7	18.727
Mar	11.8	18.864
Feb	11.8	18.952
Jan	11.9	18.992
Dec 2013	11.9	18.953
Nov	11.9	19.026
Oct	11.9	19.118
Sep	12.0	19.272
Aug	12.0	19.283
Jul	12.1	19.328
Jun	12.1	19.333
May	12.1	19.305
Apr	12.1	19.316
Mar	12.0	19.253
Feb	12.0	19.234
Jan	12.0	19.186
Dec 2012	11.9	18.998
Nov	11.8	18.916
Oct	11.7	18.813
Sep	11.6	18.580
Aug	11.5	18.425
Jul	11.5	18.357
Jun	11.4	18.245
May	11.3	18.053
Apr	11.2	17.881
Mar	11.1	17.652
Feb	10.9	17.385
Jan	10.8	17.124
Dec 2011	10.7	17.060
Nov	10.6	16.892
Oct	10.5	16.633
Sep	10.4	16.484
Aug	10.2	16.243
Jul	10.1	16.096
Jun	10.0	15.924
May	10.0	15.845
Apr	9.9	15.729
Mar	10.0	15.817
Feb	10.0	15.824
Jan	10.1	15.902
Dec 2010	10.1	16.003

Source: EUROSTAT

http://ec.europa.eu/eurostat

Table VD-2A shows the disparity in rates of unemployment in the euro area with 10.1 percent for the region as a whole and 16.267 million unemployed but 4.2 percent in Germany and 1.807 million unemployed. At the other extreme is Spain with rate of unemployment of 19.8 percent and 4.525 million unemployed. The rate of unemployment of the European Union in May 2016 is 8.6 percent with 21.084 million unemployed.

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

May 2016	Unemployment Rate %	Unemployed Millions
Euro Zone	10.1	16.267
Germany	4.2	1.807
France	9.9	2.903
Netherlands	6.3	0.560
Finland	9.0	0.242
Portugal	11.6	0.587
Ireland	7.8	0.170
Italy	11.5	2.950
Greece	24.1*	1.153*
Spain	19.8	4.525
Belgium	8.4	0.411
European Union	8.6	21.084

*Mar 2016

Source: EUROSTAT

http://ec.europa.eu/eurostat

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

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

Source: EUROSTAT

http://ec.europa.eu/eurostat

VE Germany. Table VE-DE provides yearly growth rates of the German economy from 1971 to 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 0.4 percent in 2012. Growth decelerated to 0.3 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	1.9
2015	1.7	1.4
2014	1.6	1.6
2013	0.3	0.4
2012	0.4	0.6
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

The Flash Germany Composite Output Index of the Markit Flash Germany PMI^®, combining manufacturing and services, decreased from 54.5 in May to 54.1 in Jun. The index of manufacturing output reached 55.7 in Jun, increasing from 53.3 in May, while the index of services decreased to 53.2 in Jun from 55.2 in May. The overall Flash Germany Manufacturing PMI^® increased from 52.1 in May to 54.4 in Jun (https://www.markiteconomics.com/Survey//PressRelease.mvc/8130ad70ff3a4cca92c58f0c125df507). New orders in manufacturing increased. Oliver Kolodseike, Economist at Markit, finds moderate growth of the private sector of Germany (https://www.markiteconomics.com/Survey//PressRelease.mvc/8130ad70ff3a4cca92c58f0c125df507). 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 53.6 in Apr to 54.5 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/f4d5847e379e42e396b70eafae3f715d). Oliver Kolodseike, Economist at Markit and author of the report, finds steadying growth of the private sector of Germany (https://www.markiteconomics.com/Survey//PressRelease.mvc/f4d5847e379e42e396b70eafae3f715d). The Germany Services Business Activity Index increased from 54.5 in Apr to 55.2 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/f4d5847e379e42e396b70eafae3f715d). The Markit/BME Germany Purchasing Managers’ Index^® (PMI^®), showing close association with Germany’s manufacturing conditions, increased from 51.8 in Apr to 52.1 in

May (https://www.markiteconomics.com/Survey//PressRelease.mvc/c56852acbda74f7eb9ccc818a759288e). New export orders increased. Oliver Kolodseike, Economist at Markit and author of the report, finds modest growth (https://www.markiteconomics.com/Survey//PressRelease.mvc/c56852acbda74f7eb9ccc818a759288e).Table DE provides the country data table for Germany.

Table DE, Germany, Economic Indicators

GDP	IQ2016 0.7 ∆%; IQ2016/IQ2015 ∆% 1.3 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
Consumer Price Index	May month NSA ∆%: 0.3 May 12-month NSA ∆%: 0.1 Blog 6/12/16
Producer Price Index	May month ∆%: 0.4 NSA, 0.0 CSA 12-month NSA ∆%: -2.7 Blog 6/26/16
Industrial Production	MFG Apr month CSA ∆%: 1.0 12-month NSA: 5.2 Earlier Data: Blog 4/12/15
Machine Orders	MFG Apr month ∆%: -2.0 Apr 12-month ∆%: 2.4 Earlier Data: Blog 4/12/15
Retail Sales	May Month ∆% 0.9 Apr -0.3 12-Month May % 2.6 Apr 2.7 Earlier Data: Blog 4/5/15
Employment Report	Unemployment Rate SA Apr 4.2% Blog 7/1/16
Trade Balance	Exports Apr 12-month NSA ∆%: 3.8 Imports Apr 12 months NSA ∆%: 0.0 Exports Apr month CSA ∆%: 0.0; Imports Apr month CSA minus 0.2 Earlier Data: Blog 4/12/15

Links to blog comments in Table DE: 6/26/16 http://cmpassocregulationblog.blogspot.com/2016/06/of-course-considerable-uncertainty.html

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

Germany’s labor market continues to show strength not found in most of the advanced economies, as shown in Table VE-1A. The number unemployed, not seasonally adjusted, decreased from 1.89 million in May 2015 to 1.78 million in May 2016, or 5.8 percent, while the unemployment rate decreased from 4.5 percent in May 2015 to 4.2 percent in May 2016. The number of persons in employment, not seasonally adjusted, increased from 39.708million in May 2015 to 40.66 million in May 2016, or 2.2 percent, while the employment rate increased from 64.7 percent in May 2015 to 65.4 percent in May 2016. The number unemployed, seasonally adjusted, decreased 0.5 percent from 1.82 million in May 2016 to 1.81 million in May 2016, while the unemployment rate decreased from 4.3 percent in Apr 2016 to 4.2 percent in May 2016. The number of persons in employment, seasonally adjusted, did not change from 40.81 million in Apr 2016 to 40.81 million in May 2016, or 0.0 percent. The employment rate seasonally adjusted decreased from 65.7 in Apr 2016 to 65.6 in May 2016.

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

	May 2016	Apr 2016	May 2015
NSA
Number Unemployed Millions	1.78 ∆% May 2016 /Apr 2016: -0.6 ∆% May 2016/May 2015: -5.8	1.79	1.89
% Rate Unemployed	4.2	4.2	4.5
Persons in Employment Millions	40.66 ∆% May 2016/Apr 2016: -0.2 ∆% May 2016/May 2015: 2.2	40.76	39.78
Employment Rate	65.4	65.6	64.7
SA
Number Unemployed Millions	1.81 ∆% May 2016/ Apr  2016: -0.5 ∆% May 2016/May 2015: –8.1	1.82	1.97
% Rate Unemployed	4.2	4.3	4.7
Persons in Employment Millions	40.81 ∆% May 2016/ Apr 2016: 0.0 ∆% May 2016/May 2015: 2.2	40.81	39.93
Employment Rate	65.6	65.7	65.0

NSA: not seasonally adjusted; SA: seasonally adjusted

Source: Statistisches Bundesamt Deutschland

https://www.destatis.de/EN/PressServices/Press/pr/2016/06/PE16_223_132.html

he unemployment rate in Germany as percent of the labor force in Table VE-2A stood at 6.5 percent in Sep, Oct and Nov 2012, increasing to 6.7 percent in Dec 2012, 7.4 percent in Jan 2013, 7.3 in Mar 2013 and 7.1 percent in Apr 2013. The unemployment rate fell to 6.8 percent in May 2013 and 6.6 percent in Jun 2013 and rose to 6.8 percent in Jul-Aug 2013. The rate fell to 6.6 percent in Sep 2013 and 6.5 percent in Oct 2013 and Nov 2013. The unemployment rate increased to 6.7 percent in Dec 2013 and 7.3 percent in Jan 2013. The unemployment rate reached 7.3 percent in Feb 2014 and 7.1 percent in Mar 2014. The unemployment rate fell to 6.8 percent in Apr 2014 and 6.6 percent in May 2014. The unemployment rate fell to 6.5 percent in Jun 2014, increasing to 6.6 percent in Jun 2014 and 6.7 percent in Aug 2014. The unemployment rate fell to 6.5 percent in Sep 2014 and 6.3 percent in Oct 2014 and Nov 2014. The unemployment rate increased to 6.4 percent in Dec 2014 and 7.0 percent in Jan 2015, falling to 6.9 percent in Feb 2015 and 6.5 percent in Apr 2015. The unemployment rate fell to 6.3 percent in May 2015 and 6.2 percent in Jun 2015. The unemployment rate increased to 6.3 percent in Jul 2015 and 6.4 percent in Aug 2015. The unemployment rate fell from 6.4 percent in Aug 2015 to 6.1 percent in Dec 2015, increasing to 6.7 percent in Jan 2016. The unemployment rate fell to 6.6 percent in Feb 2016 and 6.5 percent in Mar 2016. The unemployment rate fell to 6.3 percent in Apr 2016, decreasing to 6.0 percent in May 2016. The unemployment rate fell to 5.9 percent in Jun 2016. The rate is much lower than 11.1 percent in 2005 and 9.6 percent in 2006.

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

Jun 2016	5.9
May	6.0
Apr	6.3
Mar	6.5
Feb	6.6
Jan	6.7
Dec 2015	6.1
Nov	6.0
Oct	6.0
Sep	6.2
Aug	6.4
Jul	6.3
Jun	6.2
May	6.3
Apr	6.5
Mar	6.8
Feb	6.9
Jan	7.0
Dec 2014	6.4
Nov	6.3
Oct	6.3
Sep	6.5
Aug	6.7
Jul	6.6
Jun	6.5
May	6.6
Apr	6.8
Mar	7.1
Feb	7.3
Jan	7.3
Dec 2013	6.7
Nov	6.5
Oct	6.5
Sep	6.6
Aug	6.8
Jul	6.8
Jun	6.6
May	6.8
Apr	7.1
Mar	7.3
Feb	7.4
Jan	7.4
Dec 2012	6.7
Nov	6.5
Oct	6.5
Sep	6.5
Aug	6.8
Jul	6.8
Jun	6.6
May	6.7
Apr	7.0
Mar	7.2
Feb	7.4
Jan	7.3
Dec 2011	6.6
Nov	6.4
Oct	6.5
Sep	6.6
Aug	7.0
Jul	7.0
Jun	6.9
May	7.0
Apr	7.3
Mar	7.6
Feb	7.9
Jan	7.9
Dec 2010	7.1
Dec 2009	7.8
Dec 2008	7.4
Dec 2007	8.1
Dec 2006	9.6
Dec 2005	11.1

Source: Statistisches Bundesamt Deutschland

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

Chart VE-1A of Statistisches Bundesamt Deutschland, or Federal Statistical Office of Germany, shows the long-term decline of the rate of unemployment in Germany from more than 12 percent in early 2005 to 6.6 percent in Dec 2011, increasing to 6.7 percent in Dec 2012, 6.8 percent in Apr 2013 and 6.6 percent in May 2013. The unemployment rate rose slightly to 6.8 percent in Aug 2013, falling to 6.6 percent in Sep 2013 and 6.5 percent in Oct 2013. The rate remained at 6.5 percent in Nov 2013, increasing to 6.7 percent in Dec 2013 and 7.3 in Jan 2014. The rate remained at 7.3 percent in Feb 2014, declining to 7.1 percent in Mar 2014. The rate fell to 6.8 percent in Apr 2014, 6.6 percent in May 2014 and 6.5 percent in Jun 2014. The rate increased to 6.6 percent in Jul 2014 and 6.7 percent in Aug 2014, falling to 6.5 percent in Sep 2014. The rate fell to 6.3 percent in Oct 2014 and 6.3 percent in Nov 2014, increasing to 6.4 percent in Dec 2014. The rate increased to 7.0 percent in Jan 2015, falling to 6.9 percent in Feb 2015 and 6.8 percent in Mar 2015. The unemployment rate fell to 6.5 percent in Apr 2015 and 6.3 percent in May 2015. The unemployment rate fell to 6.2 percent in Jun 2015, increasing to 6.3 percent in Jul 2015 and 6.4 percent in Aug 2015. The unemployment rate fell to 6.2 percent in Sep 2015 and 6.0 percent in Oct 2015. The unemployment rate stabilized at 6.0 percent in Nov 2015, increasing to 6.1 percent in Dec 2015. The unemployment rate increased to 6.7 percent in Jan 2016 and fell to 6.6 percent in Feb 2016 and 6.5 percent in Mar 2016. The unemployment rate fell to 6.3 percent in Apr 2016, decreasing to 6.0 percent in May 2016 and 5.9 percent in Jun 2016.

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

Source: Statistisches Bundesamt Deutschland

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

VF France. Table VF-FR provides growth rates of GDP of France with the estimates of Institut National de la Statistique et des Études Économiques (INSEE). The long-term rate of GDP growth of France from IVQ1949 to IQ2016 is quite high at 3.2 percent. France’s growth rates were quite high in the four decades of the 1950s, 1960, 1970s and 1980s with an average growth rate of 4.0 percent compounding the average rates in the decades and discounting to one decade. The growth impulse diminished with 2.0 percent in the 1990s and 1.8 percent from 2000 to 2007. The average growth rate from 2000 to 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	2.0
1980-1989	2.6
1970-1979	3.7
1960-1969	5.7
1950-1959	4.2

*IVQ2007 to IVQ2015 **IVQ2007 to IQ2016

Source: Institut National de la Statistique et des Études Économiques

http://www.insee.fr/en/themes/info-rapide.asp?id=28&date=20160624

The Markit Flash France Composite Output Index decreased from 50.9 in May to 49.4 in Jun (https://www.markiteconomics.com/Survey//PressRelease.mvc/9e07438f358d408f91d3dd5b7a1a3a2f) Jack Kennedy, Senior Economist at Markit and author of the report, finds moderate contraction (https://www.markiteconomics.com/Survey//PressRelease.mvc/9e07438f358d408f91d3dd5b7a1a3a2f). The Markit France Composite Output Index, combining services and manufacturing with close association with French GDP, increased from 50.2 in Apr to 50.9 in May, indicating moderately improving activity of the private sector (https://www.markiteconomics.com/Survey//PressRelease.mvc/04e8e70a86f24431a9a7baa535944a2b). Jack Kennedy, Senior Economist at Markit and author of the France Services PMI^®, finds marginal growth (https://www.markiteconomics.com/Survey//PressRelease.mvc/04e8e70a86f24431a9a7baa535944a2b). The Markit France Services Activity index increased from 50.6 in Apr to 51.6 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/04e8e70a86f24431a9a7baa535944a2b). The Markit France Manufacturing Purchasing Managers’ Index^® increased to 48.4 in May from 48.0 in Apr (https://www.markiteconomics.com/Survey//PressRelease.mvc/df1c0db135b34e7398f72ab1b7745551). Jack Kennedy, Senior Economist at Markit and author of the France Manufacturing PMI^®, finds challenging conditions in manufacturing (https://www.markiteconomics.com/Survey//PressRelease.mvc/df1c0db135b34e7398f72ab1b7745551). Table FR provides the country data table for France.

Table FR, France, Economic Indicators

CPI	May month ∆% 0.4 12 months ∆%: 0.0 6/19/16
PPI	May month ∆%: 0.3 May 12 months ∆%: -3.4 Blog 7/1/16
GDP Growth	IQ2016/IVQ2015 ∆%: 0.6 IQ2016/IQ2016 ∆%: 1.3 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
Industrial Production	Apr ∆%: Manufacturing 1.3 Quarter YOY ∆%: 0.6 Earlier Data: Blog 4/12/15
Consumer Spending	Manufactured Goods May ∆%: 0.2 May 12-Month Manufactured Goods ∆%: 2.6 Earlier Data: Blog 4/5/15
Employment	Unemployment Rate: IQ2016 9.9% Blog 5/22/16
Trade Balance	Apr Exports ∆%: month 1.8, 12 months -3.4 Imports ∆%: month 4.1, 12 months 1.8 Earlier Data: Blog 4/12/15
Confidence Indicators	Historical average 100 Jun Mfg Business Climate 102.0 Earlier Data: Blog 3/29/15

Links to blog comments in Table FR: 6/26/16 http://cmpassocregulationblog.blogspot.com/2016/06/of-course-considerable-uncertainty.html

6/19/2016 http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html

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

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

3/27/16 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

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. GDP increased 0.3 percent in IQ2016 and grew 1.0 percent relative to a year earlier. GDP increased 0.2 percent in IVQ2015 and increased 1.1 percent relative to a year earlier. In IIIQ2015, GDP increased 0.2 percent and increased 0.8 percent relative to a year earlier. GDP increased 0.3 percent in IIQ2015 and 0.6 percent relative to a year earlier. GDP increased 0.4 percent in IQ2015 and increased 0.1 percent relative to a year earlier. GDP decreased 0.1 percent in IVQ2014 and fell 0.4 percent relative to a year earlier. GDP decreased 0.1 percent in IIIQ2014 and fell 0.4 percent relative to a year earlier. Italy’s GDP fell 0.1 percent in IIQ2014 and declined 0.2 percent relative to a year earlier. The GDP of Italy decreased 0.1 percent in IQ2014 and fell 0.1 percent relative to a year earlier. Italy’s GDP decreased 0.1 percent in IVQ2013 and fell 0.9 percent relative to a year earlier. The GDP of Italy increased 0.2 percent in IIIQ2013 and fell 1.4 percent relative to a year earlier. Italy’s GDP decreased 0.1 percent in IIQ2013, continuing eight consecutive quarterly declines, and fell 2.0 percent relative to a year earlier. Italy’s GDP fell 0.9 percent in IQ2013 and declined 2.7 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 eight consecutive quarters from IIIQ2011 to IIQ2013 at increasingly higher rates of contraction from 0.5 percent in IIIQ2011 to 1.0 percent in IVQ2011, 0.9 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 0.9 percent in IQ2013. GDP contracted cumulatively 5.1 percent in eight consecutive quarterly contractions from IIIQ2011 to IIQ2013 at the annual equivalent rate of minus 2.6 percent. The total contraction in the 13 quarters including IVQ2013, IQ2014, IIQ2014, IIIQ2014 and IVQ2014 accumulates to 5.6 percent. The yearly rate has fallen from 2.3 percent in IVQ2010 to minus 2.7 percent in IVQ2012, minus 2.7 percent in IQ2013, minus 2.0 percent in IIQ2013 and minus 1.4 percent in IIIQ2013. GDP fell 0.9 percent in IVQ2013 relative to a year earlier. GDP fell 0.1 percent in IQ2014 relative to a year earlier and fell 0.2 percent in IIQ2014 relative to a year earlier. GDP fell 0.4 percent in IIIQ2014 relative to a year earlier and fell 0.4 percent in IVQ2014 relative to a year earlier. GDP increased 0.1 percent in IQ2015 relative to a year earlier and increased 0.6 percent in IIQ2015 relative to a year earlier. GDP increased 0.8 percent in IIIQ2015 relative to a year earlier and increased 1.1 percent in IVQ2015 relative to a year earlier. GDP increased 1.0 percent in IQ2016 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 IQ2016 is lower by 8.5 percent relative to IQ2008. The GDP of the euro zone is 0.5 percent higher in IQ2016 relative to IQ2008. The GDP of Italy increased at the annual equivalent rate of 1.5 percent from IQ1999 to IQ2008, which is lower than 2.3 percent for the euro zone as a whole in the same period.

Table VG-IT, Italy, GDP ∆%

	Quarter ∆% Relative to Preceding Quarter	Quarter ∆% Relative to Same Quarter Year Earlier
IQ2016	0.3	1.0
IVQ2015	0.2	1.1
IIIQ2015	0.2	0.8
IIQ2015	0.3	0.6
IQ2015	0.4	0.1
IVQ2014	-0.1	-0.4
IIIQ2014	-0.1	-0.4
IIQ2014	-0.1	-0.2
IQ2014	-0.1	-0.1
IVQ2013	-0.1	-0.9
IIIQ2013	0.2	-1.4
IIQ2013	-0.1	-2.0
IQ2013	-0.9	-2.7
IVQ2012	-0.6	-2.7
IIIQ2012	-0.5	-3.2
IIQ2012	-0.7	-3.2
IQ2012	-0.9	-2.3
IVQ2011	-1.0	-1.0
IIIQ2011	-0.5	0.4
IIQ2011	0.2	1.4
IQ2011	0.3	2.1
IVQ2010	0.4	2.3
IIIQ2010	0.5	1.8
IIQ2010	0.7	1.9
IQ2010	0.5	0.7
IVQ2009	-0.1	-3.5
IIIQ2009	0.4	-5.0
IIQ2009	-0.3	-6.6
IQ2009	-3.5	-6.9
IVQ2008	-1.6	-3.0
IIIQ2008	-1.3	-1.9
IIQ2008	-0.5	-0.2
IQ2008	0.5	0.5
IV2007	-0.4	0.1
IIIQ2007	0.3	1.7
IIQ2007	0.2	2.0
IQ2007	0.0	2.4

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/186730

The Markit/ADACI Business Activity Index decreased from 52.1 in Apr to 49.8 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/773178d8850f454bb58fdbb81c07da1f). Phil Smith, Economist at Markit and author of the Italy Services PMI^®, finds slowing recovery in IIQ2016 (https://www.markiteconomics.com/Survey//PressRelease.mvc/773178d8850f454bb58fdbb81c07da1f). The Markit/ADACI Purchasing Managers’ Index^® (PMI^®), decreased from 53.9 in Apr to 52.4 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/1f8f04f4147946909e15a36e68697e8a). New export orders continued to increase. Phil Smith, Economist at Markit and author of the Italian Manufacturing PMI^®, finds slowing growth in manufacturing (https://www.markiteconomics.com/Survey//PressRelease.mvc/1f8f04f4147946909e15a36e68697e8a). Table IT provides the country data table for Italy.

Table IT, Italy, Economic Indicators

Consumer Price Index	Jun month ∆% 0.1 12 months ∆%: -0.4 7/1/16
Producer Price Index	May month ∆%: 0.7 May 12-month ∆%: -4.2 Blog 7/1/16
GDP Growth	IQ2016/IVQ2015 SA ∆%: 0.3 IQ2016/IQ2015 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
Labor Report	May 2016 Participation rate 64.7% Employment ratio 57.1% Unemployment rate 11.5% Youth Unemployment 36.9% Blog 7/1/16
Industrial Production	Apr month ∆%: 0.5 12 months CA ∆%: 1.8 Earlier Data: Blog 4/19/15
Retail Sales	Apr month ∆%: 0.1 Apr 12-month ∆%: -0.5 Earlier Data: Blog 4/26/15
Business Confidence	Mfg Jun 102.8, Feb 102.0 Construction Jun 121.6, Feb 119.3 Earlier Data: Blog 4/5/15
Trade Balance	Balance Apr SA €4403 million Exports Apr month SA ∆%: 2.7; Imports month ∆%: 3.9 Exports 12 months Apr NSA ∆%: -1.0 Imports 12 months NSA ∆%: -4.3 Earlier Data: Blog 4/19/15

Links to blog comments in Table IT: 6/19/2016 http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.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

Data on Italy’s labor market since 2004 are in Table VG-1A. The unemployment rate has risen from 6.2 percent in Dec 2006 to 11.5 percent in May 2016. The rate of youth unemployment for ages 15 to 24 years increased from 21.4 percent in Dec 2006 to 36.9 percent in May 2016. As in other advanced economies, unemployment has reached high levels.

Table VG-1, Italy, Labor Report

	Participation Rate %	Employment Ratio %	Unemployment Rate %	Unemployment Rate 15-24 Years %
May 2016	64.7	57.1	11.5	36.9
Apr	64.6	57.0	11.6	36.9
Mar	64.3	56.8	11.5	36.7
Feb	64.2	56.6	11.7	38.4
Jan	64.4	56.7	11.7	39.0
Dec 2015	64.1	56.5	11.7	38.6
Nov	64.2	56.6	11.5	38.2
Oct	64.2	56.6	11.6	39.3
Sep	64.1	56.6	11.5	39.3
Aug	64.1	56.6	11.5	39.8
Jul	63.9	56.3	11.7	39.3
Jun	64.3	56.3	12.2	42.0
May	64.0	56.0	12.3	41.2
Apr	64.0	56.1	12.1	41.4
Mar	64.0	55.9	12.4	42.2
Feb	63.9	56.0	12.2	41.6
Jan	63.9	55.9	12.2	40.9
Dec 2014	64.0	56.0	12.3	40.9
Nov	64.4	55.8	13.1	42.9
Oct	64.3	55.9	12.9	42.3
Sep	64.3	55.9	12.8	42.1
Aug	63.7	55.6	12.4	43.3
Jul	64.0	55.8	12.6	43.1
Jun	63.7	55.8	12.2	42.4
May	63.8	55.7	12.5	42.0
Apr	63.6	55.4	12.6	43.0
Mar	63.9	55.7	12.7	43.5
Feb	63.8	55.5	12.8	43.0
Jan	63.7	55.4	12.8	43.2
Dec 2013	63.5	55.5	12.5	42.7
Dec 2012	63.5	56.2	11.4	38.2
Dec 2011	62.9	56.8	9.6	31.8
Dec 2010	62.0	56.9	8.1	28.9
Dec 2009	62.2	56.9	8.4	26.5
Dec 2008	62.4	58.1	6.8	22.8
Dec 2007	62.9	58.7	6.6	21.8
Dec 2006	62.4	58.4	6.2	21.4
Dec 2005	62.6	57.8	7.5	23.1
Dec 2004	62.5	57.6	7.8	23.8

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/188580

Table VG-2A provides more detail on the labor report for Italy in May 2016. The level of employment increased 0.1 percent from Apr 2016 to May 2016 and increased 299,000 from May 2015 to May 2016. Unemployment decreased 24,000 in May 2016 and decreased 175,000 from a year earlier. A dramatic aspect found in most advanced economies is the high rate of unemployment of youth at 36.9 percent in May 2016 for ages 15 to 24 years.

Table VG-2, Italy, Labor Report, NSA

May 2016	1000s	Change from Prior Month 1000s	∆% from Prior Month	Change from Prior Year 1000s	∆% from Prior Year
EMP	22,677	21	0.1	299	1.3
UNE	2,950	-24	-0.8	-175	-5.6
INA   15-64	13,741	-27	-0.2	-305	-2.2
EMP 15-24	984	-4	-0.4	9.1	10.1
UNE 15-24	576	-2	-0.4	-50	-8.0
INA 15-24	4,346	5	0.1	-79	-1.8
EMP %	57.1		0.1		0.3*
UNE %	11.5		-0.1		-0.2*
Youth UNE %  15-24	36.9		0.0		-1.8*
INA % 15-64	35.3		-0.1		-0.3*

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

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/188580

Chart VG-1A provides the rate of unemployment in Italy that decreased from 12.3 percent in May 2015 to 11.5 percent in May 2016.

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

Source: Istituto Nazionale di Statistica

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

Chart VG-2A of the Istituto Nazionale di Statistica provides the total number of employed persons in Italy. The level of employment increased from 22.378 million in May 2015 to 22.677 million in May 2016.

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

Source: Istituto Nazionale di Statistica

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

VH United Kingdom. Annual data in Table VH-UK show the strong impact of the global recession in the UK with decline of GDP of 4.3 percent in 2009 after dropping 0.6 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	0.9
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/quarterlynationalaccounts/quarter1jantomar2016

The Business Activity Index of the Markit/CIPS UK Services PMI^® increased from 52.3 in Apr to 53.5 in May (https://www.markiteconomics.com/Survey//PressRelease.mvc/0e7d4d8767204073b2183f65e8d48f05). Chris Williamson, Chief Economist at Markit, finds the combined indices consistent with the UK economy growing at around 0.2 percent in IIQ2016 (https://www.markiteconomics.com/Survey//PressRelease.mvc/0e7d4d8767204073b2183f65e8d48f05). The Markit/CIPS UK Manufacturing Purchasing Managers’ Index^® (PMI^®) increased to 50.1 in May from 49.4 in Apr (https://www.markiteconomics.com/Survey//PressRelease.mvc/f95819f732834cc29db956d3846f3a66). New export orders decreased. Rob Dobson, Senior Economist at Markit that compiles the Markit/CIPS Manufacturing PMI^®, finds manufacturing conditions contracting at annual 0.8 percent (https://www.markiteconomics.com/Survey//PressRelease.mvc/f95819f732834cc29db956d3846f3a66). Table UK provides the economic indicators for the United Kingdom.

Table UK, UK Economic Indicators

CPI	May month ∆%: 0.2 May 12-month ∆%: 0.3 Blog 6/19/16
Output/Input Prices	Output Prices: May 12-month NSA ∆%: -0.97; excluding food, petroleum ∆%: 0.5 Input Prices: May 12-month NSA ∆%: -3.9 Excluding ∆%: -1.5 Blog 6/19/16
GDP Growth	IQ2016 prior quarter ∆% 0.4; year earlier same quarter ∆%: 2.0 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 7/1/16
Industrial Production	Apr 2016/Apr 2015 ∆%: Production Industries 1.6; Manufacturing 0.8 Earlier Data: Blog 4/12/15
Retail Sales	Apr month ∆%: 1.3 Apr 12-month ∆%: 4.3 Earlier Data: Blog 4/26/15
Labor Market	Feb-Apr 2016 Unemployment Rate: 5.0% Blog 6/19/16 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 Apr minus ₤3294 million Exports Apr ∆%: 5.3; Feb-Apr ∆%: 1.3 Imports Mar ∆%: 4.4 Jan-Apr ∆%: 2.1 EARLIER DATA: Blog 4/12/15

Links to blog comments in Table UK: 6/19/2016 http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.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

Table VH-1 provides quarter on quarter chained value measures of GDP since 1998 in the third estimate for IQ2016 (https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016). The UK Office for National Statistics provides revision of the national accounts in accordance with the European System of Accounts 2010 (ESA 2010) (http://www.ons.gov.uk/ons/rel/naa2/quarterly-national-accounts/q2-2015/index.html). GDP grew 0.4 percent in IQ2016 relative to IVQ2015. Growth of 1.1 percent in IIIQ2012 interrupted three consecutive quarters of weakness in GDP growth. Most advanced economies are underperforming relative to the period before the global recession. The UK Office for National Statistics analyzes that the decline in the impulse of growth in the UK originated in weakness in markets in the UK and worldwide. The UK Office for National Statistics data shows that GDP in IQ2016 is higher by 7.0 percent relative to the peak in IQ2008 (https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016). UK GDP in chained value measures is ₤433,710 million in IQ2008 and ₤462,139 million in IVQ2015 or increase of 6.6 percent. Growth at trend of 2.7 percent per year would bring GDP to ₤533,176 million in IVQ2015. UK GDP in IVQ2015 at ₤462,139 million is lower by ₤71,037 million relative to trend at ₤533,176 million or lower by 13.3 percent compared with trend. The UK Office for National Statistics estimates the contraction of 6.3 percent from peak to trough (https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016), which is roughly equal at 6.3 percent to compounding the quarterly rates except for rounding in Table VH-1 from IIQ2008 to IIQ2009. UK GDP is ₤433,710 million in IQ2008 declining 6.3 percent to ₤406,353 million in IIQ2009. GDP increased 13.7 percent from IIQ2009 to ₤462,139 million in IVQ2015 or at the annual equivalent rate of 2.1 percent. GDP increased 6.6 percent from IQ2008 to IVQ2015 or at the annual equivalent rate of 0.8 percent. Using the seasonally adjusted chained-value measures (https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016), GDP increased from ₤433,710 million in IQ2008 to ₤464,212 million in IQ2016, or 7.0 percent at the annual equivalent rate of 0.9 percent. UK GDP in IQ2016 at ₤464,212 million is lower by ₤73,527 million relative to trend at ₤537,739 million or lower by 13.7 percent compared with trend. UK GDP increased 14.2 percent from IIQ2009 to IQ2016 at the annual equivalent rate of 2.1 percent.

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

	IQ	IIQ	IIIQ	IV
2016	0.4
2015	0.3	0.4	0.4	0.7
2014	0.8	0.9	0.8	0.8
2013	0.6	0.5	0.8	0.5
2012	0.4	-0.1	1.1	-0.2
2011	0.6	0.1	0.4	0.2
2010	0.5	1.0	0.6	0.1
2009	-1.6	-0.2	0.1	0.4
2008	0.1	-0.7	-1.7	-2.3
2007	1.0	0.7	0.8	0.8
2006	0.3	0.2	0.1	0.4
2005	0.6	1.1	1.1	1.4
2004	0.6	0.5	0.2	0.6
2003	0.8	0.9	1.0	0.8
2002	0.4	0.7	0.8	0.9
2001	1.3	0.7	0.7	0.4
2000	1.0	0.7	0.3	0.2
1999	0.7	0.1	1.8	1.4
1998	0.6	0.6	0.7	1.0

Source: UK Office for National Statistics

https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016

Chart VH-1 of the UK Office for National Statistics provides UK GDP in chained volume measures SA from IQ1955 to IQ2016. The extrapolation of GDP after 2007 shows current levels below trend.

Chart VH-1, United Kingdom, Gross Domestic Product, CVM, SA, ₤ Million

Source: UK Office for National Statistics

https://www.ons.gov.uk/economy/grossdomesticproductgdp/timeseries/abmi/linechartimage

There are four periods in growth of GDP in a quarter relative to the same quarter a year earlier in the UK in the years from 2000 to the present as shown in Table VH-2. (1) Growth rates were quite high from 2000 to 2007. (2) There were six consecutive quarters of contraction of GDP from IIIQ2008 to IVQ2009. Contractions relative to the quarter a year earlier were quite sharp with the highest of 4.4 percent in IVQ2008, 6.1 percent in IQ2009, 5.7 percent in IIQ2009 and 4.0 percent in IIIQ2009. (3) The economy bounced strongly with 2.1 percent in IIQ2010, 2.6 percent in IIIQ2010 and 2.3 percent in IVQ2010. (4) Recovery did not continue at rates comparable to those in 2000 to 2007 and even relative to those in the final three quarters of 2010. Growth relative to the same quarter a year earlier fell from 2.3 percent in IVQ2010 to 1.3 percent in IIQ2011, 1.2 percent in IIIQ2011, 1.3 percent in IVQ2011 but only 1.2 percent in IQ2012, increase of 1.0 percent in IIQ2012 relative to IIQ2011, increase of 1.8 percent in IIIQ2012 and 1.3 percent in IVQ2012. 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. Growth 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 2.9 percent relative to a year earlier. GDP increased 0.4 percent in IIQ2015 and increased 2.3 percent relative to a year earlier. UK GDP increased 0.4 percent in IIIQ2015 and increased 2.0 percent relative to a year earlier. GDP increased 0.7 percent in IVQ2015 and increased 1.8 percent relative to a year earlier. GDP increased 0.4 percent in IQ2016 and increased 2.0 percent relative to a year earlier.

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

	IQ	IIQ	IIIQ	IVQ
2016	2.0
2015	2.9	2.3	2.0	1.8
2014	2.6	3.1	3.1	3.5
2013	1.5	2.1	1.7	2.4
2012	1.2	1.0	1.8	1.3
2011	2.3	1.3	1.2	1.3
2010	0.8	2.1	2.6	2.3
2009	-6.1	-5.7	-4.0	-1.4
2008	2.4	1.0	-1.4	-4.4
2007	1.8	2.3	2.9	3.3
2006	3.9	3.0	2.1	1.1
2005	1.9	2.5	3.4	4.2
2004	3.3	2.9	2.1	1.8
2003	3.2	3.4	3.6	3.6
2002	2.2	2.2	2.3	2.8
2001	2.5	2.5	2.9	3.1
2000	4.4	5.0	3.5	2.2
1999	3.0	2.5	3.6	4.0
1998	3.6	3.1	3.2	2.9

Source: UK Office for National Statistics

https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016

Table VH-3 provides annual percentage changes of gross value added and key components. Production fell 8.7 percent in 2009 and its most important component manufacturing fell 9.4 percent. Services fell 3.0 percent in 2009. Services grew in all years from 2010 to 2015 while manufacturing fell 1.4 percent in 2012 and fell 1.1 percent in 2013. Manufacturing resumed growth with 2.9 percent in 2014 followed by decline of 0.2 percent in 2015.

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

	TP	MFG	CONS	SERV	GVA BP	GVA EX
2013 Weights	146	103	59	788	1000	986
1998	1.1	0.4	1.5	4.2	3.4	3.4
1999	1	0.5	1.3	4.2	3.4	3.3
2000	1.8	2.3	0.9	4.6	3.8	4.3
2001	-1.5	-1.5	1.8	3.7	2.5	3
2002	-1.4	-2.2	5.7	2.6	2.1	2.3
2003	-0.6	-0.5	4.8	4.5	3.5	4
2004	0.6	1.8	5.3	2.5	2.3	2.8
2005	-0.7	0	-2.4	4.5	3.3	3.8
2006	0.6	2.2	0.8	3	2.5	2.9
2007	0.3	0.6	2.2	3.1	2.5	2.7
2008	-2.6	-2.8	-2.6	0.1	-0.4	-0.3
2009	-8.7	-9.4	-13.2	-3	-4.5	-4.4
2010	3.2	4.5	8.5	1.5	2.1	2.4
2011	-0.6	2.2	2.2	1.5	1.3	1.8
2012	-2.7	-1.4	-6.9	2.4	1	1.3
2013	-0.7	-1	1.5	1.8	1.4	1.5
2014	1.5	2.9	8	3.3	3.4	3.5
2015	1.3	-0.2	4.2	2.6	2.3	2.2

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

Source: UK Office for National Statistics

https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016

Table VH-4A shows for IQ2016 that GVA at basic prices increased 1.9 percent relative to a year earlier while gross value added with exclusions increased 1.8 percent. Total production increased 0.3 percent and manufacturing slowed with contraction at 1.0 percent. Services grew 2.5 percent relative to a year earlier.

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

	TP	MFG	CONS	SERV	GVA BP	GVA EX
2013 Weights	146	103	59	788	1000	986
1998 Q1	1.4	1.1	4.7	4.0	3.5	3.7
1998 Q2	1.9	1.1	0.1	3.9	3.3	3.1
1998 Q3	0.8	0.3	1.3	4.4	3.4	3.4
1998 Q4	0.2	-1.0	0.0	4.4	3.3	3.2
1999 Q1	-0.6	-1.5	-1.5	4.4	3.1	2.8
1999 Q2	-0.3	-1.0	1.4	3.5	2.6	2.5
1999 Q3	2.2	1.7	3.2	4.2	3.7	3.6
1999 Q4	2.9	2.8	2.1	4.8	4.3	4.3
2000 Q1	2.9	3.1	3.3	5.3	4.7	4.9
2000 Q2	3.1	3.3	2.1	6.0	5.2	5.6
2000 Q3	0.7	1.1	-1.9	4.5	3.4	4.0
2000 Q4	0.6	1.6	0.0	2.5	2.0	2.7
2001 Q1	0.1	0.8	-1.9	3.3	2.3	3.2
2001 Q2	-1.6	-1.4	1.6	3.2	2.1	2.6
2001 Q3	-1.4	-1.4	3.7	3.8	2.7	3.1
2001 Q4	-3.1	-4.0	3.8	4.4	2.8	3.0
2002 Q1	-2.3	-3.2	5.2	2.4	1.8	1.9
2002 Q2	-1.5	-2.5	3.4	2.5	1.9	1.9
2002 Q3	-1.4	-1.6	7.4	2.5	2.2	2.6
2002 Q4	-0.5	-1.5	6.9	2.9	2.6	2.7
2003 Q1	-1.4	-2.0	3.5	4.3	3.2	3.4
2003 Q2	-1.2	-0.6	5.5	4.6	3.6	4.3
2003 Q3	-0.5	-0.9	4.5	4.5	3.6	3.9
2003 Q4	0.6	1.6	5.7	4.4	3.8	4.5
2004 Q1	1.4	2.7	11.7	3.2	3.4	4.1
2004 Q2	2.0	2.8	6.8	2.6	2.7	3.1
2004 Q3	-0.5	0.6	3.5	2.3	1.9	2.3
2004 Q4	-0.3	1.0	-0.2	1.9	1.3	1.8
2005 Q1	-1.3	-0.8	-2.8	2.4	1.5	2.0
2005 Q2	-0.6	0.0	-1.7	3.4	2.5	3.0
2005 Q3	-0.2	1.0	-3.0	5.2	3.9	4.5
2005 Q4	-0.5	-0.2	-2.2	6.8	5.1	5.7
2006 Q1	1.1	1.7	-1.9	5.6	4.4	4.8
2006 Q2	-0.5	1.4	-0.6	4.1	3.0	3.6
2006 Q3	1.1	2.6	1.8	2.0	1.8	2.1
2006 Q4	0.7	3.0	3.9	0.5	0.7	1.0
2007 Q1	0.1	1.7	4.2	1.9	1.7	2.1
2007 Q2	0.6	1.0	3.0	2.7	2.4	2.5
2007 Q3	0.1	0.1	1.1	3.7	2.9	3.1
2007 Q4	0.4	-0.3	0.5	3.9	3.1	3.2
2008 Q1	-0.3	0.2	0.3	3.0	2.4	2.6
2008 Q2	-1.1	-1.5	-0.4	1.6	1.1	1.3
2008 Q3	-2.1	-2.7	-1.7	-0.9	-1.1	-1.0
2008 Q4	-6.9	-7.2	-8.7	-3.1	-4.0	-4.0
2009 Q1	-10.7	-12.4	-16.1	-4.3	-6.0	-6.1
2009 Q2	-9.8	-10.8	-16.2	-4.1	-5.7	-5.7
2009 Q3	-9.5	-9.9	-12.2	-2.5	-4.2	-4.0
2009 Q4	-4.4	-4.0	-7.8	-0.8	-1.8	-1.6
2010 Q1	1.9	2.6	3.2	0.3	0.7	0.9
2010 Q2	2.7	4.3	10.5	1.4	2.1	2.4
2010 Q3	4.1	5.9	11.0	2.1	2.9	3.0
2010 Q4	4.2	5.3	9.4	2.3	3.0	3.2
2011 Q1	1.6	4.6	6.7	2.5	2.7	3.1
2011 Q2	-0.4	3.0	1.9	1.6	1.4	1.9
2011 Q3	-1.1	1.3	-1.1	1.1	0.8	1.3
2011 Q4	-2.5	0.0	1.6	0.9	0.5	0.9
2012 Q1	-2.4	0.0	-3.3	1.4	0.5	0.8
2012 Q2	-2.6	-2.0	-7.8	2.0	0.7	0.9
2012 Q3	-2.1	-1.1	-8.6	3.3	1.7	1.9
2012 Q4	-3.8	-2.6	-7.9	3.0	1.3	1.7
2013 Q1	-2.9	-3.2	-4.9	2.6	1.3	1.6
2013 Q2	-1.0	-0.9	0.5	2.1	1.5	1.8
2013 Q3	-0.7	-1.0	5.0	0.9	0.9	1.0
2013 Q4	1.9	1.2	5.5	1.4	1.7	1.7
2014 Q1	1.9	3.0	8.4	2.0	2.4	2.4
2014 Q2	1.5	2.9	8.5	3.1	3.3	3.3
2014 Q3	1.4	2.9	8.2	3.7	3.7	3.9
2014 Q4	1.3	2.8	7.1	4.3	4.1	4.2
2015 Q1	1.2	1.1	6.7	3.5	3.3	3.3
2015 Q2	1.5	-0.1	5.7	2.6	2.5	2.4
2015 Q3	1.4	-0.8	2.1	2.2	1.9	1.7
2015 Q4	0.9	-0.9	2.5	2.1	1.7	1.5
2016 Q1	0.3	-1.0	0.2	2.5	1.9	1.8

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

Source: UK Office for National Statistics

https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016

Table VH-5 provides contributions to value added by expenditure components in a quarter relative to the prior quarter. Household final consumption expenditures contributed 0.5 percentage points in IQ2015 and 0.5 percentage points in IIQ2015. Household final consumption expenditures contributed 0.5 percentage points in IIIQ2015 and 0.4 percentage points in IVQ2015. Household final consumption contributed 0.4 percentage points in IQ2016. Net trade deducted 0.6 percentage points in IQ2015. Net trade added 0.6 percentage points in IIQ2015 and deducted 0.5 percentage points in IIIQ2015. Net trade added 0.1 percentage points in IVQ2015 and deducted 0.2 percentage points in IQ2016. Gross fixed capital formation (GFCF) added 0.3 percentage points in IQ2015. GFCF added 0.2 percentage points in IIQ2015 and added 0.1 percentage points in IIIQ2015, deducting 0.2 percentage points in IVQ2015. GFCF contributed 0.0 percentage points in IQ2016.

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

	IQ2015	IIQ2015	IIIQ2015	IVQ2015	IQ2016
HFC	0.5	0.5	0.5	0.4	0.4
NPISH	0.0	0.1	-0.1	0.0	0.1
GOVT	0.1	0.2	0.1	0.0	0.1
GCF	0.1	-0.9	0.4	0.1	-0.2
GFCF	0.3	0.2	0.1	-0.2	0.0
BI	0.2	0.0	0.2	-0.2	-0.1
Exports	0.6	-0.1	-0.1	0.9	-0.1
Less Imports	1.2	-0.7	0.4	0.8	0.0
Net Trade	-0.6	0.6	-0.5	0.1	-0.2

Components may not add because of rounding

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

Source: UK Office for National Statistics

https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016

Contributions of value added by expenditure components in a year relative to the prior year are in Table VH-6. Household final consumption added 1.0 percentage points in 2013, 1.3 percentage points in 2014 and 1.6 percentage points in 2015. Gross capital formation contributed 1.5 percentage points in 2013, 1.6 percentage points in 2014 and 0.6 percentage points in 2015. GFCF added 0.5 percentage points in 2013, 1.1 percentage points in 2014 and 0.6 percentage points in 2015. Net trade deducted 0.8 percentage points in 2013, deducting 0.4 percentage points in 2014 and deducting 0.5 percentage points in 2015.

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

	2013	2014	2015
HFC	1.0	1.3	1.6
NPISH	0.0	0.1	0.0
GOVT	0.1	0.5	0.3
GCF	1.5	1.6	0.6
GFCF	0.5	1.1	0.6
BINV	0.2	0.4	0.5
Exports	0.3	0.4	1.4
Less Imports	1.1	0.8	1.9
Net Trade	-0.8	-0.4	-0.5

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

Source: UK Office for National Statistics

https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/quarterlynationalaccounts/quarter1jantomar2016

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