CMP Associates Regulation Blog: Growth Uncertainties, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Disposable Income and Consumption Expenditures World Cyclical Slow Growth and Global Recession Risk: Part II

Growth Uncertainties, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Disposable Income and Consumption Expenditures World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

Note: The complete analysis of the world economy and finance will resume after a brief sabbatical. Selected sections will be available until resumption of the complete analysis.

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

IA Mediocre Cyclical United States Economic Growth

IA1 Contracting 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

II Stagnating Real Disposable Income and Consumption Expenditures. The Bureau of Economic Analysis (BEA) provides important revisions and enhancements of data on personal income and outlays since 1929 (http://www.bea.gov/iTable/index_nipa.cfm). There are waves of changes in personal income and expenditures in Table IB-1 that correspond somewhat to inflation waves observed worldwide (http://cmpassocregulationblog.blogspot.com/2014/10/financial-oscillations-world-inflation.html) because of the influence through price indexes. Data are distorted in Nov and Dec 2012 by the rush to realize income of all forms in anticipation of tax increases beginning in Jan 2013. There is major distortion in Jan 2013 because of higher contributions in payrolls to government social insurance that caused sharp reduction in personal income and disposable personal income. The Bureau of Economic Analysis (BEA) explains as follows (page 3 http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

“The February and January [2013] changes in disposable personal income (DPI) mainly reflected the effect of special factors in January, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to November and to December [2012] in anticipation of changes in individual tax rates.”

In the first wave in Jan-Apr 2011 with relaxed risk aversion, nominal personal income (NPI) increased at the annual equivalent rate of 8.1 percent, nominal disposable personal income (NDPI) at 5.2 percent and nominal personal consumption expenditures (NPCE) at 5.9 percent. Real disposable income (RDPI) increased at the annual equivalent rate of 1.2 percent and real personal consumption expenditures (RPCE) rose at annual equivalent 1.5 percent. In the second wave in May-Aug 2011 under risk aversion, NPI rose at annual equivalent 4.9 percent, NPDI at 4.9 percent and NPCE at 3.7 percent. RDPI increased at 1.8 percent annual equivalent and RPCE at 0.9 percent annual equivalent. With mixed shocks of risk aversion in the third wave from Sep to Dec 2011, NPI rose at 2.4 percent annual equivalent, NDPI at 2.4 percent and NPCE at 2.1 percent. RDPI increased at 1.5 percent annual equivalent and RPCE at 1.5 percent annual equivalent. In the fourth wave from Jan to Mar 2012, NPI increased at 9.6 percent annual equivalent and NDPI at 8.7 percent. Real disposable income (RDPI) is more dynamic in the revisions, growing at 5.7 percent annual equivalent and RPCE at 3.7 percent. The policy of repressing savings with zero interest rates stimulated growth of nominal consumption (NPCE) at the annual equivalent rate of 6.2 percent and real consumption (RPCE) at 3.7 percent. In the fifth wave in Apr-Jul 2012, NPI increased at annual equivalent 0.9 percent, NDPI at 0.9 percent and RDPI at 0.0 percent. Financial repression failed to stimulate consumption with NPCE growing at 2.1 percent annual equivalent and RPCE at 1.8 percent. In the sixth wave in Aug-Oct 2012, in another wave of carry trades into commodity futures, NPI increased at 7.9 percent annual equivalent and NDPI increased at 7.0 percent while real disposable income (RDPI) increased at 3.7 percent annual equivalent. Data for Nov-Dec 2012 have illusory increases: “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf). In the seventh wave, anticipations of tax increases in Jan 2013 caused exceptional income gains that increased personal income to annual equivalent 28.3 percent in Nov-Dec 2012, nominal disposable income at 27.5 percent and real disposable personal income at 28.3 percent with likely effects on nominal personal consumption that increased at 2.4 percent and real personal consumption at 3.0 percent with subdued prices. The numbers in parentheses show that without the exceptional effects NDPI (nominal disposable personal income) increased at 5.5 percent and RDPI (real disposable personal income) at 8.7 percent. In the eighth wave, nominal personal income fell 5.1 percent in Jan 2013 or at the annual equivalent rate of decline of 46.6 percent; nominal disposable personal income fell 5.8 percent or at the annual equivalent rate of decline of 51.2 percent; real disposable income fell 5.5 percent or at the annual rate of decline of 51.8 percent; nominal personal consumption expenditures increased 0.5 percent or at the annual equivalent rate of 6.2 percent; and real personal consumption expenditures increased 0.4 percent or at the annual equivalent rate of 4.9 percent. The savings rate fell significantly from 10.5 percent in Dec 2012 to 4.5 percent in Jan 2013. The Bureau of Economic Analysis explains as follows (http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0113.pdf 3):

“Contributions for government social insurance -- a subtraction in calculating personal income -- increased $126.7 billion in January, compared with an increase of $6.3 billion in December. The

Further explanation is provided by the Bureau of Economic Analysis (http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf 2-3):

“Contributions for government social insurance -- a subtraction in calculating personal income --increased $6.4 billion in February, compared with an increase of $126.8 billion in January. The

January estimate reflected increases in both employer and employee contributions for government social insurance. The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base; together, these changes added $12.9 billion to January. Employer contributions were boosted $5.9 billion in January, which reflected increases in the social security taxable wage base (from $110,100 to $113,700), in the tax rates paid by employers to state unemployment insurance, and in employer contributions for the federal unemployment tax and for pension guaranty. The total contribution of special factors to the January change in contributions for government social insurance was $132.9 billion. The January change in disposable personal income (DPI) mainly reflected the effect of special factors, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to December in anticipation of changes in individual tax rates. Excluding these special factors and others, which are discussed more fully below, DPI increased $46.8 billion in February, or 0.4 percent, after increasing $15.8 billion, or 0.1 percent, in January.”

The increase was provided in the “fiscal cliff” law H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf). In the ninth wave in Feb-Mar 2013, nominal personal income increased at 7.4 percent and nominal disposable income at 6.8 percent annual equivalent, while real disposable income increased at 5.5 percent annual equivalent. Nominal personal consumption expenditures grew at 4.3 percent annual equivalent and real personal consumption expenditures at 2.4 percent annual equivalent. The savings rate collapsed from 7.1 percent in Oct 2012, 8.2 percent in Nov 2012 and 10.5 percent in Dec 2012 to 4.5 percent in Jan 2013, 4.7 percent in Feb 2013 and 4.9 percent in Mar 2013. In the tenth wave from Apr to Sep 2013, personal income grew at 3.7 percent annual equivalent, nominal disposable income increased at annual equivalent 3.9 percent and nominal personal consumption expenditures at 2.8 percent. Real disposable income grew at 3.2 percent annual equivalent and real personal consumption expenditures at 2.2 percent. In the eleventh wave, nominal personal income fell at 1.2 percent annual equivalent in Oct 2013, nominal disposable income at 2.4 percent and real disposable income at 3.5 percent. Nominal personal consumption expenditures increased at 4.9 percent annual equivalent and real personal consumption expenditures at 3.7 percent. In the twelfth wave, nominal personal income increased at 3.7 percent annual equivalent in Nov 2013, nominal disposable income at 2.4 percent and nominal personal consumption expenditures at 7.4 percent. Real disposable income increased at annual equivalent 7.4 percent and real personal consumption expenditures at 6.2 percent. In the thirteenth wave, nominal personal income changed at 0.0 percent annual equivalent in Dec 2013 and nominal disposable income fell at 1.2 percent while real disposable income fell at 2.4 percent annual equivalent. Nominal personal consumption expenditures increased at 1.2 percent annual equivalent and 0.0 percent for real personal consumption expenditures. In the fourteenth wave, nominal personal income increased at 5.7 percent annual equivalent in Jan-Aug 2014, nominal disposable income at 5.9 percent and nominal consumption expenditures at 3.8 percent. Real disposable personal income increased at 4.3 percent and real personal consumption expenditures at 2.3 percent. In the fifteenth wave, nominal personal income increased at 2.4 percent in annual equivalent in Sep 2014 and nominal disposable income at 1.2 percent. Real disposable income changed at 0.0 percent in annual equivalent in Sep 2014. Nominal personal consumption fell at 2.4 percent annual equivalent in Sep 2014 and real personal consumption expenditures fell at 2.4 percent.

The United States economy has grown at the average yearly rate of 3 percent per year and 2 percent per year in per capita terms from 1870 to 2010, as measured by Lucas (2011May). An important characteristic of the economic cycle in the US has been rapid growth in the initial phase of expansion after recessions.

Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design. 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. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 21 quarters from IIIQ2009 to IIIQ2014. 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 first estimate of GDP for IIIQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp3q14_adv.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/2014/09/financial-volatility-mediocre-cyclical.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 IQ1988 and at 7.8 percent from IQ1983 to IVQ1983 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/09/financial-volatility-mediocre-cyclical.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 IIIQ2014 would have accumulated to 23.0 percent. GDP in IIIQ2014 would be $18,438.0 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,287.4 billion than actual $16,150.6 billion. There are about two trillion dollars of GDP less than at trend, explaining the 26.5 million unemployed or underemployed equivalent to actual unemployment of 16.1 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/10/world-financial-turbulence-twenty-seven.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/competitive-monetary-policy-and.html). US GDP in IIIQ2014 is 12.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,150.6 billion in IIIQ2014 or 7.7 percent at the average annual equivalent rate of 1.1 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. The long-term trend is growth at average 3.3 percent per year from Jan 1919 to Sep 2014. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 123.5550 in Sep 2014. The actual index NSA in Sep 2014 is 102.0228, which is 17.4 percent below trend. Manufacturing output grew at average 2.3 percent between Dec 1986 and Dec 2013, raising the index at trend to 115.7028 in Sep 2014. The output of manufacturing at 102.0228 in Sep 2014 is 11.8 percent below trend under this alternative calculation. The output of manufacturing at 101.5145 in Aug 2014 is 13.8 percent below trend under this alternative calculation.

Table IB-1, US, Percentage Change from Prior Month Seasonally Adjusted of Personal Income, Disposable Income and Personal Consumption Expenditures %

	NPI	NDPI	RDPI	NPCE	RPCE
2014
Sep	0.2	0.1	0.0	-0.2	-0.2
AE ∆% Sep	2.4	1.2	0.0	-2.4	-2.4
Aug	0.3	0.3	0.3	0.5	0.5
Jul	0.3	0.2	0.1	0.0	0.0
Jun	0.5	0.5	0.3	0.5	0.3
May	0.5	0.5	0.3	0.3	0.1
Apr	0.4	0.5	0.3	0.2	-0.1
Mar	0.6	0.6	0.5	0.8	0.6
Feb	0.6	0.6	0.5	0.4	0.4
Jan	0.5	0.6	0.5	-0.2	-0.3
AE ∆% Jan-Aug	5.7	5.9	4.3	3.8	2.3
2013
Dec	0.0	-0.1	-0.2	0.1	0.0
AE ∆% Dec	0.0	-1.2	-2.4	1.2	0.0
Nov	0.3	0.2	0.1	0.6	0.5
AE ∆% Nov	3.7	2.4	1.2	7.4	6.2
Oct	-0.1	-0.2	-0.3	0.4	0.3
AE ∆% Oct	-1.2	-2.4	-3.5	4.9	3.7
Sep	0.4	0.4	0.3	0.4	0.3
Aug	0.4	0.4	0.4	0.2	0.2
Jul	0.0	0.0	-0.1	0.2	0.1
Jun	0.4	0.5	0.2	0.5	0.2
May	0.4	0.5	0.4	0.3	0.2
Apr	0.2	0.1	0.2	0.0	0.1
AE ∆% Apr-Sep	3.7	3.9	2.8	3.2	2.2
Mar	0.3	0.3	0.4	0.1	0.1
Feb	0.9	0.8	0.5	0.6	0.3
AE ∆% Feb-Mar	7.4	6.8	5.5	4.3	2.4
Jan	-5.1	-5.8 (0.1)^a	-5.9	0.5	0.4
AE ∆% Jan	-46.6	-51.2 (3.7)^a	-51.8	6.2	4.9
2012
∆% Jan-Dec 2012***	9.0	8.6	7.0	3.9	2.3
Dec	2.8	2.8 (0.3)*	2.8 (0.5)*	0.2	0.2
Nov	1.4	1.3 (0.6)*	1.4 (0.9)*	0.2	0.3
AE ∆% Nov-Dec	28.3	27.5 (5.5)*	28.3 (8.7)*	2.4	3.0
Oct	0.8	0.8	0.6	0.2	-0.1
Sep	0.9	0.8	0.5	0.7	0.4
Aug	0.2	0.1	-0.2	0.3	0.0
AE ∆% Aug-Oct	7.9	7.0	3.7	4.9	1.2
Jul	-0.2	-0.2	-0.3	0.4	0.4
Jun	0.2	0.2	0.1	0.0	0.0
May	0.0	0.0	0.0	0.0	0.0
Apr	0.3	0.3	0.2	0.3	0.2
AE ∆% Apr-Jul	0.9	0.9	0.0	2.1	1.8
Mar	0.5	0.4	0.2	0.1	-0.1
Feb	0.8	0.7	0.5	0.7	0.5
Jan	1.0	1.0	0.7	0.7	0.5
AE ∆% Jan-Mar	9.6	8.7	5.7	6.2	3.7
2011
∆% Jan-Dec 2011*	5.1	4.1	1.2	4.3	1.8
Dec	0.8	0.8	0.8	0.0	0.0
Nov	0.0	0.0	-0.1	0.0	-0.1
Oct	0.1	0.1	0.1	0.3	0.3
Sep	-0.1	-0.1	-0.3	0.4	0.3
AE ∆% Sep-Dec	2.4	2.4	1.5	2.1	1.5
Aug	0.2	0.2	-0.1	0.2	-0.1
Jul	0.6	0.6	0.4	0.5	0.3
Jun	0.5	0.5	0.4	0.2	0.2
May	0.3	0.3	-0.1	0.3	-0.1
AE ∆% May-Aug	4.9	4.9	1.8	3.7	0.9
Apr	0.2	0.2	-0.3	0.4	0.0
Mar	0.3	0.2	-0.1	0.7	0.3
Feb	0.6	0.6	0.3	0.4	0.1
Jan	1.5	0.7	0.5	0.4	0.1
AE ∆% Jan-Apr	8.1	5.2	1.2	5.9	1.5
2010
∆% Jan-Dec 2010**	4.9	4.3	2.9	4.4	2.9
Dec	0.9	0.9	0.7	0.3	0.1
Nov	0.5	0.5	0.3	0.5	0.4
Oct	0.5	0.5	0.2	0.7	0.5
IVQ2010∆%	1.9	1.8	1.2	1.5	1.0
IVQ2010 AE ∆%	7.9	7.4	4.9	6.2	4.1

Notes: *Excluding exceptional income gains in Nov and Dec 2012 because of anticipated tax increases in Jan 2013 ((page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf). ^aExcluding employee contributions for government social insurance (pages 1-2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0113.pdf )Excluding NPI: current dollars personal income; NDPI: current dollars disposable personal income; RDPI: chained (2005) dollars DPI; NPCE: current dollars personal consumption expenditures; RPCE: chained (2005) dollars PCE; AE: annual equivalent; IVQ2010: fourth quarter 2010; A: annual equivalent

Percentage change month to month seasonally adjusted

*∆% Dec 2011/Dec 2010 **∆% Dec 2010/Dec 2009 *** ∆% Dec 2012/Dec 2011

Source: US Bureau of Economic http://bea.gov/iTable/index_nipa.cfm

The rates of growth of real disposable income decline in the final quarter of 2013 because of the increases in the last two months of 2012 in anticipation of the tax increases of the “fiscal cliff” episode. The increase was provided in the “fiscal cliff” law H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf).

The 12-month rate of increase of real disposable income fell to 0.0 percent in Oct 2013 and minus 1.3 percent in Nov 2013 partly because of the much higher level in late 2012 in anticipation of incomes to avoid increases in taxes in 2013. Real disposable income fell 4.2 percent in the 12 months ending in Dec 2013 primarily because of the much higher level in late 2012 in anticipation of income to avoid increases in taxes in 2013. Real disposable income increased 2.3 percent in the 12 months ending in Jan 2014, partly because of the low level in Jan 2013 after anticipation of incomes in late 2012 in avoiding the fiscal cliff episode. Real disposable income increased 2.5 percent in the 12 months ending in Sep 2014.

RPCE growth decelerated less sharply from close to 3 percent in IVQ 2010 to 2.1 percent in Sep 2014. Subdued growth of RPCE could affect revenues of business. Growth rates of personal consumption have weakened. Goods and especially durable goods have been driving growth of PCE as shown by the much higher 12-month rates of growth of real goods PCE (RPCEG) and durable goods real PCE (RPCEGD) than services real PCE (RPCES). Growth of consumption of goods and, in particular, of consumer durable goods drives the faster expansion of the economy while growth of consumption of services is much more moderate. The 12-month rates of growth of RPCEGD have fallen from around 10 percent and even higher in several months from Sep 2010 to Feb 2011 to the range of 2.0 to 8.3 percent from Jan to Sep 2014. RPCEG growth rates have fallen from around 5 percent late in 2010 and early Jan-Feb 2011 to the range of 1.2 to 4.1 percent from Jan to Sep 2014. In Sep 2014, RPCEG increased 2.8 percent in 12 months and RPCEGD 7.1 percent while RPCES increased only 1.7 percent. There are limits to sustained growth based on financial repression in an environment of weak labor markets and real labor remuneration.

Table IB-2, Real Disposable Personal Income and Real Personal Consumption Expenditures

Percentage Change from the Same Month a Year Earlier %

	RDPI	RPCE	RPCEG	RPCEGD	RPCES
2014
Sep	2.5	2.1	2.8	7.1	1.7
Aug	2.7	2.6	4.1	8.3	1.9
Jul	2.8	2.2	3.3	7.0	1.7
Jun	2.5	2.4	3.5	7.0	1.8
May	2.4	2.3	3.2	7.2	1.9
Apr	2.5	2.4	3.8	6.5	1.7
Mar	2.4	2.5	3.8	8.2	1.9
Feb	2.3	2.0	2.1	3.6	2.0
Jan	2.3	1.9	1.2	2.0	2.3
2013
Dec	-4.2	2.7	3.1	3.5	2.4
Nov	-1.3	2.9	3.9	6.8	2.4
Oct	0.0	2.7	3.8	7.4	2.2
Sep	0.9	2.3	3.2	5.0	1.9
Aug	1.1	2.4	3.3	7.7	2.0
Jul	0.6	2.2	3.7	7.5	1.5
Jun	0.4	2.5	3.8	8.1	1.8
May	0.4	2.3	3.5	7.5	1.7
Apr	0.0	2.1	2.7	6.8	1.8
Mar	0.0	2.3	2.9	5.8	1.9
Feb	-0.2	2.0	3.3	7.0	1.4
Jan	-0.1	2.2	3.8	8.0	1.5
2012
Dec	7.0	2.3	3.8	8.8	1.6
Nov	4.8	2.0	3.1	8.2	1.5
Oct	3.2	1.6	2.2	5.4	1.3
Sep	2.7	1.9	3.5	8.5	1.1
Aug	1.9	1.8	3.5	8.7	0.9
Jul	2.0	1.8	2.8	7.3	1.3
Jun	2.7	1.7	2.6	8.4	1.2
May	3.0	1.9	3.0	7.6	1.3
Apr	2.9	1.8	2.4	6.5	1.5
Mar	2.4	1.5	2.2	5.8	1.2
Feb	2.1	1.9	2.4	6.9	1.7
Jan	1.8	1.5	1.8	5.8	1.4
Dec 2011	1.6	1.2	1.4	5.0	1.1
Dec 2010	2.9	2.9	4.7	8.4	2.1

Notes: RDPI: real disposable personal income; RPCE: real personal consumption expenditures (PCE); RPCEG: real PCE goods; RPCEGD: RPCEG durable goods; RPCES: RPCE services

Numbers are percentage changes from the same month a year earlier

Source: US Bureau of Economic Analysis http://bea.gov/iTable/index_nipa.cfm

Chart IB-1 shows US real personal consumption expenditures (RPCE) between 1999 and 2014. There is an evident drop in RPCE during the global recession in 2007 to 2009 but the slope is flatter during the current recovery than in the period before 2007.

Chart IB-1, US, Real Personal Consumption Expenditures, Quarterly Seasonally Adjusted at Annual Rates 1999-2014

Source: US Bureau of Economic Analysis

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

Percent changes from the prior period in seasonally adjusted annual equivalent quarterly rates (SAAR) of real personal consumption expenditures (RPCE) are provided in Chart IB-2 from 1995 to 2014. The average rate could be visualized as a horizontal line. Although there are not yet sufficient observations, it appears from Chart IB-2 that the average rate of growth of RPCE was higher before the recession than during the past twenty quarters of expansion that began in IIIQ2009.

Chart IB-2, Percent Change from Prior Period in Real Personal Consumption Expenditures, Quarterly Seasonally Adjusted at Annual Rates 1995-2014

Source: US Bureau of Economic Analysis

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

Personal income and its disposition are shown in Table IB-3. The latest estimates and revisions have changed movements in five forms. (1) Increase in Sep 2014 of personal income by $22.7 billion or 0.2 percent and increase of disposable income of $15.7 billion or 0.1 percent with increase of wages and salaries of 0.2 percent. (2) Decrease of personal income of $302.9 billion from Dec 2012 to Dec 2013 or by 2.1 percent and decrease of disposable income of $397.7 billion or by 3.1 percent. Wages and salaries increased $30.8 billion from Dec 2012 to Dec 2013 or by 0.4 percent. Large part of these declines occurred because of the comparison of high levels in late 2012 in anticipation of tax increases in 2013. In 2012, personal income increased $1203.0 billion or 9.0 percent while wages and salaries increased 7.5 percent and disposable income 8.6 percent. Significant part of these gains occurred in Dec 2012 in anticipation of incomes because of tax increases beginning in Jan 2013. (3) Increase of $651.3 billion of personal income in 2011 or by 5.1 percent with increase of salaries of 2.7 percent and disposable income of 4.1 percent. (4) Increase of the rate of savings as percent of disposable income from 5.9 percent in Dec 2010 to 6.4 percent in Dec 2011, decreasing to 4.1 percent in Dec 2013. (5) Increase of personal income of $587.8 billion or 4.1 percent from Sep 2013 to Sep 2014. Nominal disposable income increased $497.9 billion or 3.9 percent while salaries and wages increased $366.9 billion or 5.1 percent.

Table IB-3, US, Personal Income and its Disposition, Seasonally Adjusted at Annual Rates USD Billions

	Personal Income	Wages & Salaries	Personal Taxes	DPI	Savings Rate %
Sep 2014	14,892.6	7,540.9	1,785.5	13,134.1	5.6
Aug 2014	14,869.9	7,527.0	1,751.5	13,118.4	5.4
Change Sep 2014/ Aug 2014	22.7 ∆% 0.2	13.9 ∆% 0.2	34.0 ∆% 1.9	15.7 ∆% 0.1
Sep 2013	14,304.8	7,174.0	1,668.6	12,636.2	5.2
Change Sep 2014/Sep 2013	587.8 ∆% 4.1	366.9 ∆% 5.1	116.9 ∆% 7.0	497.9 ∆% 3.9
Dec 2013	14,320.0	7,214.1	1,695.3	12,624.8	4.1
Dec 2012	14,622.9	7,183.3	1,600.4	13,022.5	10.5
Change Dec 2013/ Dec 2012	-302.9 ∆% -2.1	30.8 ∆% 0.4	94.9 ∆% 5.9	-397.7 ∆% -3.1
Change Dec 2012/ Dec 2011	1203.0 ∆% 9.0	500.4 ∆% 7.5	169.1 ∆% 11.8	1033.9 ∆% 8.6
Dec 2011	13,419.9	6,682.9	1,431.3	11,988.6	6.4
Dec 2010	12,768.6	6,506.0	1,254.2	11,514.5	5.9
Change Dec 2011/ Dec 2010	651.3 ∆% 5.1	176.9 ∆% 2.7	177.1 ∆% 14.1	474.1 ∆% 4.1

Source: US Bureau of Economic Analysis

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

The Bureau of Economic Analysis (BEA) provides a wealth of revisions and enhancements of US personal income and outlays since 1929 (http://www.bea.gov/iTable/index_nipa.cfm). Table IB-4 provides growth rates of real disposable income and real disposable income per capita in the long-term and selected periods. Real disposable income consists of after-tax income adjusted for inflation. Real disposable income per capita is income per person after taxes and inflation. There is remarkable long-term trend of real disposable income of 3.2 percent per year on average from 1929 to 2013 and 2.0 percent in real disposable income per capita. Real disposable income increased at the average yearly rate of 3.7 percent from 1947 to 1999 and real disposable income per capita at 2.3 percent. These rates of increase broadly accompany rates of growth of GDP. Institutional arrangements in the United States provided the environment for growth of output and income after taxes, inflation and population growth. There is significant break of growth by much lower 2.3 percent for real disposable income on average from 1999 to 2013 and 1.4 percent in real disposable per capita income. Real disposable income grew at 3.5 percent from 1980 to 1989 and real disposable per capita income at 2.6 percent. In contrast, real disposable income grew at only 1.4 percent on average from 2006 to 2013 and real disposable income per capita at 0.5 percent. The United States has interrupted its long-term and cyclical dynamism of output, income and employment growth. Recovery of this dynamism could prove to be a major challenge. Cyclical uncommonly slow growth explains weakness in the current whole cycle instead of the allegation of secular stagnation.

Table IB-4, Average Annual Growth Rates of Real Disposable Income (RDPI) and Real Disposable Income per Capita (RDPIPC), Percent per Year

RDPI Average ∆%
1929-2013	3.2
1947-1999	3.7
1999-2013	2.3
1999-2006	3.2
1980-1989	3.5
2006-2013	1.4
RDPIPC Average ∆%
1929-2013	2.0
1947-1999	2.3
1999-2013	1.4
1999-2006	2.2
1980-1989	2.6
2006-2013	0.5

Source: Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

Chart IB-3 provides personal income in the US between 1980 and 1989. These data are not adjusted for inflation that was still high in the 1980s in the exit from the Great Inflation of the 1960s and 1970s. Personal income grew steadily during the 1980s after recovery from two recessions from Jan IQ1980 to Jul IIIQ1980 and from Jul IIIQ1981 to Nov IVQ1982.

Chart IB-3, US, Personal Income, Billion Dollars, Quarterly Seasonally Adjusted at Annual Rates, 1980-1989

Source: US Bureau of Economic Analysis

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

A different evolution of personal income is shown in Chart IB-4. Personal income also fell during the recession from Dec IVQ2007 to Jun IIQ2009 (http://www.nber.org/cycles.html). Growth of personal income during the expansion has been tepid even with the new revisions. In IVQ2012, nominal disposable personal income grew at the SAAR of 13.8 percent and real disposable personal income at 11.8 percent (Table 2.1 http://bea.gov/iTable/index_nipa.cfm). The BEA explains as follows: “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf pages 1-2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0113.pdf). The Bureau of Economic Analysis explains as (http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf 2-3): “The January estimate of employee contributions for government social insurance reflected the expiration of the “payroll tax holiday,” that increased the social security contribution rate for employees and self-employed workers by 2.0 percentage points, or $114.1 billion at an annual rate. For additional information, see FAQ on “How did the expiration of the payroll tax holiday affect personal income for January 2013?” at www.bea.gov. The January estimate of employee contributions for government social insurance also reflected an increase in the monthly premiums paid by participants in the supplementary medical insurance program, in the hospital insurance provisions of the Patient Protection and Affordable Care Act, and in the social security taxable wage base.”

The increase was provided in the “fiscal cliff” law H.R. 8 American Taxpayer Relief Act of 2012 (http://www.gpo.gov/fdsys/pkg/BILLS-112hr8eas/pdf/BILLS-112hr8eas.pdf).

In IQ2013, personal income fell at the SAAR of minus 8.6 percent; real personal income excluding current transfer receipts at minus 11.9 percent; and real disposable personal income at minus 12.6 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0814.pdf). The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

“The February and January changes in disposable personal income (DPI) mainly reflected the effect of special factors in January, such as the expiration of the “payroll tax holiday” and the acceleration of bonuses and personal dividends to November and to December in anticipation of changes in individual tax rates.”

In IIQ2013, personal income grew at 4.5 percent, real personal income excluding current transfer receipts at 4.6 percent and real disposable income at 3.8 percent (http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0914.pdf). In IIIQ2013, personal income grew at 3.3 percent, real personal income excluding current transfers at 1.5 percent and real disposable income at 2.0 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0914.pdf). In IVQ2013, personal income grew at 1.8 percent and real disposable income at 0.2 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0814.pdf). In IQ2014, personal income grew at 4.9 percent in nominal terms and 3.2 percent in real terms excluding current transfer receipts while nominal disposable income grew at 4.8 percent and real disposable income at 3.4 percent (http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0914.pdf). In IIQ2014, personal income grew at 6.3 percent and 3.8 percent in real terms excluding current transfers. Nominal disposable income grew at 6.8 percent and at 4.4 percent in real terms (http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0914.pdf). In IIIQ2014, personal income grew at 4.2 percent, real personal income excluding current transfers at 2.3 percent and real disposable personal income at 2.7 percent (http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0914.pdf).

Chart IB-4, US, Personal Income, Current Billions of Dollars, Quarterly Seasonally Adjusted at Annual Rates, 2007-2014

Source: US Bureau of Economic Analysis

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

Real or inflation-adjusted disposable personal income is provided in Chart IB-5 from 1980 to 1989. Real disposable income after allowing for taxes and inflation grew steadily at high rates during the entire decade.

Chart IB-5, US, Real Disposable Income, Billions of Chained 2009 Dollars, Quarterly Seasonally Adjusted at Annual Rates 1980-1989

Source: US Bureau of Economic Analysis

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

Chart IB-6 provides real disposable income from 2007 to 2014. In IQ2013, personal income fell at the SAAR of minus 8.6 percent; real personal income excluding current transfer receipts at minus 11.9 percent; and real disposable personal income at minus 12.6 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0814.pdf). The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

Chart IB-6, US, Real Disposable Income, Billions of Chained 2009 Dollars, Quarterly Seasonally Adjusted at Annual Rates, 2007-2014

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

Chart IB-7 provides percentage quarterly changes in real disposable income from the preceding period at seasonally adjusted annual rates from 1980 to 1989. Rates of changes were high during the decade with few negative changes.

Chart IB-7, US, Real Disposable Income Percentage Change from Preceding Period at Quarterly Seasonally-Adjusted Annual Rates, 1980-1989

Source: US Bureau of Economic Analysis

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

Chart IB-8 provides percentage quarterly changes in real disposable income from the preceding period at seasonally adjusted annual rates from 2007 to 2013. There has been a period of positive rates followed by decline of rates and then negative and low rates in 2011. Recovery in 2012 has not reproduced the dynamism of the brief early phase of expansion. In IVQ2012, nominal disposable personal income grew at the SAAR of 13.8 percent and real disposable personal income at 11.8 percent (Table 2.1 http://bea.gov/iTable/index_nipa.cfm). The BEA explains as: “Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf). The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

Personal income fell at 8.6 percent in IQ2013; nominal disposable personal income fell at 11.7 percent and real disposable income fell at 12.6 percent. In IIQ2013, personal income increased at 4.5 percent, real personal income excluding current transfer receipts at 4.6 percent and real disposable income at 3.8 percent. In IIIQ2013, personal income increased at 3.3 percent, real personal income excluding current transfer receipts at 1.5 percent and real disposable income at 2.0 percent. In IVQ2013, nominal personal income increased at 1.8 percent, nominal disposable income at 1.2 percent, real personal income excluding current transfers at 1.0 percent and real disposable income at 0.2 percent. In IQ2014, nominal personal income grew at 4.9 percent, nominal disposable income at 4.8 percent, real personal income excluding current transfers at 3.2 percent and real disposable personal income at 3.4 percent. In IIQ2014, nominal personal income grew at 6.3 percent and 3.8 percent in real terms excluding current transfers while nominal disposable income grew at 6.8 percent and at 4.4 percent in real terms. In IIIQ2014, nominal personal income grew at 4.2 percent and 2.3 percent in real terms excluding current transfers while nominal disposable income grew at 4.0 percent and 2.7 percent in real terms.

Chart, IB-8, US, Real Disposable Income, Percentage Change from Preceding Period at Seasonally-Adjusted Annual Rates, 2007-2014

Source: US Bureau of Economic Analysis

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

The Bureau of Economic Analysis (BEA) estimates US personal income in Sep 2014 at the seasonally adjusted annual rate of $14,892,6 billion, as shown in Table IB-3 above (see Table 1 at http://www.bea.gov/newsreleases/national/pi/2014/pdf/pi0714.pdf). The major portion of personal income is compensation of employees of $9,329.3 billion, or 62.6 percent of the total. Wages and salaries are $7,540.9 billion, of which $6,316.6 billion by private industries and supplements to wages and salaries of $1,788.4 billion (contributions to social insurance are $554.2 billion). In Feb 1988 (at the comparable month after the end of the 20^th quarter of cyclical expansion), US personal income was $4,125.5 billion at SAAR (http://www.bea.gov/iTable/index_nipa.cfm). Compensation of employees was $2,862.4 billion, or 69.4 percent of the total. Wages and salaries were $2,368.6 billion of which $1925.7 billion by private industries. Supplements to wages and salaries were $493.7 billion with employer contributions to pension and insurance funds of $314.0 billion and $179.7 billion to government social insurance. Chart IB-9 provides US wages and salaries by private industries in the 1980s. Growth was robust after the interruption of the recessions.

Chart IB-9, US, Wages and Salaries, Private Industries, Quarterly, Seasonally Adjusted at Annual Rates Billions of Dollars, 1980-1989

Source: US Bureau of Economic Analysis

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

Chart IB-10 shows US wages and salaries of private industries from 2007 to 2014. There is a drop during the contraction followed by initial recovery in 2010 and then the current much weaker relative performance in 2011, 2012, 2013 and 2014.

Chart IB-10, US, Wage and Salary Disbursement, Private Industries, Quarterly, Seasonally Adjusted at Annual Rates, Billions of Dollars 2007-2014

Source: US Bureau of Economic Analysis

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

Chart IB-11 provides finer detail with monthly wages and salaries of private industries from 2007 to 2014. Anticipations of income in late 2012 to avoid tax increases in 2013 cloud comparisons.

Chart IB-11, US, Wages and Salaries, Private Industries, Monthly, Seasonally Adjusted at Annual Rates, Billions of Dollars 2007-2014

Source: US Bureau of Economic Analysis

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

Chart IB-12 provides monthly real disposable personal income per capita from 1980 to 1989. This is the ultimate measure of wellbeing in receiving income by obtaining the value per inhabitant. The measure cannot adjust for the distribution of income. Real disposable personal income per capita grew rapidly during the expansion after 1983 and continued growing during the rest of the decade.

Chart IB-12, US, Real Disposable Per Capita Income, Monthly, Seasonally Adjusted at Annual Rates, Chained 2009 Dollars 1980-1989

Source: US Bureau of Economic Analysis

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

Table IB-5 provides the comparison between the cycle of the 1980s and the current cycle. Real per capita disposable income (RDPI-PC) increased 21.6 percent from Dec 1979 to Mar 1988. In the comparable period in the actual cycle, real per capital disposable income increased 5.1 percent.

Table IB-5, Percentage Changes of Real Disposable Personal Income Per Capita

Month	RDPI-PC ∆% 12/79	RDPI-PC ∆% YOY	Month	RDPI-PC ∆% 12/07	RDPI-PC ∆% YOY
11/1982	2.4	0.6	6/2009	-0.6	-2.4
12/1982	2.9	1.3	9/2009	-1.3	-0.6
12/1983	7.8	4.8	6/2010	-0.4	0.2
12/1987	20.4	2.7	6/2014	4.7	1.8
1/1988	20.6	2.6	7/2014	4.8	2.0
2/1988	21.2	2.6	8/2014	5.1	2.0
3/1988	21.6	2.9	9/2014	5.1	1.8

RDPI: Real Disposable Personal Income; RDPI-PC, Real Disposable Personal Income Per Capita

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

National Bureau of Economic Research

http://www.nber.org/cycles.html

Chart IB-13 provides monthly real disposable personal income per capita from 2007 to 2014. There was initial recovery from the drop during the global recession followed by stagnation.

Chart IB-13, US, Real Disposable Per Capita Income, Monthly, Seasonally Adjusted at Annual Rates, Chained 2009 Dollars 2007-2014

Source: US Bureau of Economic Analysis

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

Table IB-6 provides data for analysis of the current cycle. Real disposable income (RDPI) increased 10.7 percent from Dec 2007 to Sep 2014 (column RDPI ∆% 12/07). In the same period, real disposable income per capita increased 5.1 percent (column RDPI-PC ∆% 12/07). The annual equivalent rate of increase of real disposable income per capita is 0.7 percent, only a fraction of 2.0 percent on average from 1929 to 2013, and 1.8 percent for real disposable income, much lower than 3.2 percent on average from 1929 to 2013.

Table IB-6, Percentage Changes of Real Disposable Personal Income and Real Disposable Personal Income Per Capita

Month	RDPI ∆% 12/07	RDPI ∆% Month	RDPI ∆% YOY	RDPI-PC ∆% 12/07	RDPI-PC ∆% Month	RDPI-PC ∆% YOY
6/09	0.8	-1.7	-1.5	-0.6	-1.8	-2.4
9/09	0.3	0.1	0.3	-1.3	0.1	-0.6
6/10	1.8	0.0	1.0	-0.4	0.0	0.2
12/10	3.4	0.7	2.9	0.8	0.6	2.1
6/11	4.2	0.4	2.3	1.2	0.4	1.6
12/11	5.0	0.8	1.6	1.6	0.7	0.9
6/12	6.9	0.1	2.7	3.2	0.1	1.9
10/12	7.7	0.6	3.2	3.6	0.5	2.5
11/12	9.2	1.4	4.8	5.0	1.4	4.1
12/12	12.3	2.8	7.0	8.0	2.8	6.2
6/13	7.4	0.2	0.4	2.9	0.1	-0.3
12/13	7.6	-0.2	-4.2	2.7	-0.3	-4.9
1/14	8.1	0.5	2.3	3.1	0.4	1.6
2/14	8.6	0.5	2.3	3.6	0.4	1.6
3/14	9.1	0.5	2.4	4.0	0.4	1.7
4/14	9.5	0.3	2.5	4.3	0.3	1.8
5/14	9.8	0.3	2.4	4.5	0.2	1.7
6/14	10.1	0.3	2.5	4.7	0.2	1.8
7/14	10.2	0.1	2.8	4.8	0.1	2.0
8/14	10.6	0.3	2.7	5.1	0.3	2.0
9/14	10.7	0.0	2.5	5.1	0.0	1.8

RDPI: Real Disposable Personal Income; RDPI-PC, Real Disposable Personal Income Per Capita

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

National Bureau of Economic Research

http://www.nber.org/cycles.html

IA2 Financial Repression. McKinnon (1973) and Shaw (1974) argue that legal restrictions on financial institutions can be detrimental to economic development. “Financial repression” is the term used in the economic literature for these restrictions (see Pelaez and Pelaez, Globalization and the State, Vol. II (2008b), 81-6; for historical analysis see Pelaez 1975). Excessive official regulation frustrates financial development required for growth (Haber 2011). Emphasis on disclosure can reduce bank fragility and corruption, empowering investors to enforce sound governance (Barth, Caprio and Levine 2006). 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.

Most regulatory actions trigger compensatory measures by the private sector that result in outcomes that are different from those intended by regulation (Kydland and Prescott 1977). Banks offered services to their customers and loans at rates lower than market rates to compensate for the prohibition to pay interest on demand deposits (Friedman 1970, 24). The prohibition of interest on demand deposits was eventually lifted in recent times. In the second half of the 1960s, already in the beginning of the Great Inflation (DeLong 1997), market rates rose above the ceilings of Regulation Q because of higher inflation. Nobody desires savings allocated to time or savings deposits that pay less than expected inflation. This is a fact currently with zero interest rates and consumer price inflation of 1.5 percent in the 12 months ending in Mar 2013 (http://www.bls.gov/cpi/) but rising during waves of carry trades from zero interest rates to commodity futures exposures (http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html). Funding problems motivated compensatory measures by banks. Money-center banks developed the large certificate of deposit (CD) to accommodate increasing volumes of loan demand by customers. As Friedman (1970, 25) finds:

“Large negotiable CD’s were particularly hard hit by the interest rate ceiling because they are deposits of financially sophisticated individuals and institutions who have many alternatives. As already noted, they declined from a peak of $24 billion in mid-December, 1968, to less than $12 billion in early October, 1969.”

Banks created different liabilities to compensate for the decline in CDs. As Friedman (1970, 25; 1969) explains:

“The most important single replacement was almost surely ‘liabilities of US banks to foreign branches.’ Prevented from paying a market interest rate on liabilities of home offices in the United States (except to foreign official institutions that are exempt from Regulation Q), the major US banks discovered that they could do so by using the Euro-dollar market. Their European branches could accept time deposits, either on book account or as negotiable CD’s at whatever rate was required to attract them and match them on the asset side of their balance sheet with ‘due from head office.’ The head office could substitute the liability ‘due to foreign branches’ for the liability ‘due on CDs.”

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.”

Chart IB-14 of the Bureau of Economic Analysis (BEA) provides quarterly savings as percent of disposable income or the US savings rate from 1980 to 2014. There was a long-term downward sloping trend from 12 percent in the early 1980s to 2.0 percent in Jul 2005. The savings rate then rose during the contraction and in the expansion. In 2011 and into 2012 the savings rate declined as consumption is financed with savings in part because of the disincentive or frustration of receiving a few pennies for every $10,000 of deposits in a bank. The savings rate increased in the final segment of Chart IB-14 in 2012 followed by another decline because of the pain of the opportunity cost of zero remuneration for hard-earned savings.

Chart IB-14, US, Personal Savings as a Percentage of Disposable Personal Income, Quarterly, 1980-2014

Source: US Bureau of Economic Analysis

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

Chart IB-14A provides the US personal savings rate, or personal savings as percent of disposable personal income, on an annual basis from 1929 to 2013. The US savings rate shows decline from around 10 percent in the 1960s to around 5 percent currently.

Chart IB-14A, US, Personal Savings as a Percentage of Disposable Personal Income, Annual, 1929-2013

Source: US Bureau of Economic Analysis

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

Table IB-7 provides personal savings as percent of disposable income and annual change of real disposable personal income in selected years since 1930. Savings fell from 4.4 percent of disposable personal income in 1930 to minus 0.8 percent in 1933 while real disposable income contracted 5.3 percent in 1930 and 2.9 percent in 1933. Savings as percent of disposable personal income swelled during World War II to 27.9 percent in 1944 with increase of real disposable income of 3.1 percent. Savings as percent of personal disposable income fell steadily over decades from 11.5 percent in 1982 to 2.5 percent in 2005. Savings as percent of disposable personal income was 4.9 percent in 2013 while real disposable income fell 0.2 percent. The average ratio of savings as percent of disposable income fell from 9.3 percent from 1980 to 1989 to 5.4 percent on average from 2007 to 2013. Real disposable income grew on average at 3.5 percent from 1980 to 1989 and at 1.2 percent on average from 2007 to 2013.

Table IB-7, US, Personal Savings as Percent of Disposable Personal Income, Annual, Selected Years 1929-1913

	Personal Savings as Percent of Disposable Personal Income	Annual Change of Real Disposable Personal Income
1930	4.4	-5.3
1933	-0.8	-2.9
1944	27.9	3.1
1947	6.3	-4.1
1954	10.3	1.4
1958	11.4	1.1
1960	10.0	2.6
1970	12.6	4.6
1975	13.0	2.5
1982	11.5	2.1
1989	7.8	3.0
1992	8.9	4.3
2002	5.0	3.1
2003	4.8	2.7
2004	4.6	3.6
2005	2.5	1.5
2006	3.3	4.0
2007	3.0	2.1
2008	4.9	1.5
2009	6.1	-0.4
2010	5.6	1.0
2011	6.0	2.5
2012	7.2	3.0
2013	4.9	-0.2
Average Savings Ratio
1980-1989	9.3
2007-2013	5.4
Average Yearly ∆% Real Disposable Income
1980-1989		3.5
2007-2013		1.2

Source: US Bureau of Economic Analysis

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

Chart IB-15 of the US Bureau of Economic Analysis provides personal savings as percent of personal disposable income, or savings ratio, from Jan 2007 to Sep 2014. The uncertainties caused by the global recession resulted in sharp increase in the savings ratio that peaked at 7.9 percent in May 2008 (http://www.bea.gov/iTable/index_nipa.cfm). The second peak occurred at 8.1 percent in May 2009. There was another rising trend until 5.9 percent in Jun 2010 and then steady downward trend until 5.3 percent in Nov 2011. This was followed by an upward trend with 7.1 percent in Jun 2012 but decline to 6.4 percent in Aug 2012 followed by jump to 10.5 percent in Dec 2012. Swelling realization of income in Oct-Dec 2012 in anticipation of tax increases in Jan 2013 caused the jump of the savings rate to 10.5 percent in Dec 2012. The BEA explains as: Personal income in November and December was boosted by accelerated and special dividend payments to persons and by accelerated bonus payments and other irregular pay in private wages and salaries in anticipation of changes in individual income tax rates. Personal income in December was also boosted by lump-sum social security benefit payments” (page 2 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi1212.pdf). There was a reverse effect in Jan 2013 with decline of the savings rate to 3.6 percent. Real disposable personal income fell 5.1 percent and real disposable per capita income fell from $38,175 in Dec 2012 to $36,195 in Jan 2013 or by 5.2 percent, which is explained by the Bureau of Economic Analysis as follows (page 3 http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0213.pdf):

“Contributions for government social insurance -- a subtraction in calculating personal income --increased $6.4 billion in February, compared with an increase of $126.8 billion in January. The

Chart IB-15, US, Personal Savings as a Percentage of Disposable Income, Monthly 2007-2014

Source: US Bureau of Economic Analysis

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

Table IB-8 provides personal saving as percent of disposable income, change of real disposable income relative to Dec 2007 (RDPI ∆% 12/07), monthly percentage change of real disposable income (RDPI ∆% Month) and percentage of real disposable income in a month relative to the same month a year earlier (RDPI ∆% YOY). The ratio of personal saving to disposable income eased to 5.6 percent in Sep 2014 with cumulative growth of real disposable income of 10.7 percent since Dec 2007 at the rate of 1.5 percent in annual equivalent that is much lower than 3.2 percent over the long-term from 1929 to 2013.

Table IB-8, US, Savings Ratio and Real Disposable Income, % and ∆%

	Personal Income as % Disposable Income	RDPI ∆% 12/07	RDPI ∆% Month	RDPI ∆% YOY
May 2008	7.9	5.1	4.8	5.7
May 2009	8.1	2.5	1.6	-2.5
Jun 2010	5.9	1.8	0.0	1.0
Nov 2011	5.6	4.2	-0.1	1.5
Jun 2012	7.1	6.9	0.1	2.7
Aug 2012	6.4	6.5	-0.2	1.9
Dec 2012	10.5	12.3	2.8	7.0
Jan 2013	4.5	5.6	-5.9	-0.1
Feb 2013	4.7	6.2	0.5	-0.2
Mar 2013	4.9	6.5	0.4	0.0
Apr 2013	5.1	6.8	0.2	0.0
May 2013	5.2	7.2	0.4	0.4
Jun 2013	5.3	7.4	0.2	0.4
Jul 2013	5.1	7.3	-0.1	0.6
Aug 2013	5.3	7.7	0.4	1.1
Sep 2013	5.2	8.0	0.3	0.9
Oct 2013	4.7	7.7	-0.3	0.0
Nov 2013	4.3	7.8	0.1	-1.3
Dec 2013	4.1	7.6	-0.2	-4.2
Jan 2014	4.9	8.1	0.5	2.3
Feb 2014	5.0	8.6	0.5	2.3
Mar 2014	4.8	9.1	0.5	2.4
Apr 2014	5.2	9.5	0.3	2.5
May 2014	5.4	9.8	0.3	2.4
Jun 2014	5.4	10.1	0.3	2.5
Jul 2014	5.6	10.2	0.1	2.8
Aug 2014	5.4	10.6	0.3	2.7
Sep 2014	5.6	10.7	0.0	2.5

Source: US Bureau of Economic Analysis

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

The revisions and enhancements of United States GDP and personal income accounts by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) also provide critical information in assessing indexes of prices of personal consumption. There are waves of inflation similar to those worldwide (http://cmpassocregulationblog.blogspot.com/2014/10/financial-oscillations-world-inflation.html) in inflation of personal consumption expenditures (PCE) in Table IV-5. These waves are in part determined by commodity price shocks originating in the carry trade from zero interest rates to positions in risk financial assets, in particular in commodity futures, which increase the prices of food and energy when there is relaxed risk aversion. Return of risk aversion causes collapse in prices. Resulting fluctuations of prices confuse risk/return decisions, inducing financial instability with adverse financial and economic consequences. The first wave is in Jan-Apr 2011 when headline PCE inflation increased at the average annual equivalent rate of 4.0 percent and PCE inflation excluding food and energy (PCEX) at 1.8 percent. The drivers of inflation were increases in food prices (PCEF) at the annual equivalent rate of 7.8 percent and of energy prices (PCEE) at 30.1 percent. This behavior will prevail under zero interest rates and relaxed risk aversion because of carry trades from zero interest rates to leveraged positions in commodity futures. The second wave occurred in May-Jun 2011 when risk aversion from the European sovereign risk crisis interrupted the carry trade. PCE prices increased 1.8 percent in annual equivalent and 1.8 percent excluding food and energy. The third wave is captured by the annual equivalent rates in Jul-Sep 2011 of headline PCE inflation of 2.4 percent with subdued PCE inflation excluding food and energy of 2.0 percent while PCE food rose at 6.2 percent and PCE energy increased at 5.3 percent. In the fourth wave in Oct-Dec 2011, increased risk aversion explains the fall of the annual equivalent rate of inflation to 0.8 percent for headline PCE inflation and 1.6 percent for PCEX excluding food and energy. PCEF of prices of food rose at the annual equivalent rate of 1.2 percent in Oct-Dec 2011 while PCEE of prices of energy fell at the annual equivalent rate of 10.3 percent. In the fifth wave in Jan-Mar 2012, headline PCE in annual equivalent was 2.8 percent and 2.0 percent excluding food and energy (PCEX). Energy prices of personal consumption (PCEE) increased at the annual equivalent rate of 12.2 percent because of the jump of 1.6 percent in Feb 2012 followed by 0.7 percent in Mar 2012. In the sixth wave, renewed risk aversion caused reversal of carry trades with headline PCE inflation at the annual equivalent rate of 0.6 percent in Apr-May 2012 while PCE inflation excluding food and energy increased at the annual equivalent rate of 1.2 percent. In the seventh wave, further shocks of risk aversion resulted in headline PCE annual equivalent inflation at 0.0 percent in Jun-Jul 2012 with core PCE excluding food and energy at 1.8 percent. In the eighth wave, temporarily relaxed risk aversion with zero interest rates resulted in central PCE inflation at 3.7 percent annual equivalent in Aug-Sep 2012 with PCEX excluding food and energy at 0.6 percent while PCEE energy jumped at 63.8 percent annual equivalent. The program of outright monetary transactions (OTM) of the European Central Bank induced relaxed risk aversion (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html). In the ninth wave, prices collapsed with reversal of carry trade positions in a new episode of risk aversion with central PCE at annual equivalent 0.6 percent in Oct 2012 to Jan 2013 and PCEX at 1.5 percent while energy prices fell at minus 13.6 percent. In the tenth wave, central PCE increased at annual equivalent 3.7 percent in Feb 2013, PCEX at 1.2 percent and PCEE at 63.8 percent. In the eleventh wave, renewed risk aversion resulted in decline in annual equivalent of general PCE prices at 1.2 percent in Mar-Apr 2013 while PCEX increased at 0.6 percent and energy prices fell at 29.3 percent. In the twelfth wave, central PCE increased at 1.6 percent annual equivalent in May-Nov 2013 with PCEX increasing at 1.4 percent, food PCEF increasing at 0.2 percent and energy PCEE increasing at 2.6 percent with the jump of 1.9 percent in Jun 2013. In the thirteenth wave, central PCE increased at annual equivalent 1.8 percent in Dec 2013-Mar 2014 and PCEX at 1.2 percent. PCEE increased at 4.6 percent annual equivalent. In the fourteenth wave, central PCE inflation was 2.1 percent in annual equivalent in Apr-Jul 2014 with PCEX at 2.1 percent and energy prices at 8.1 percent. In the fifteenth wave, central PCE changed at annual equivalent 0.0 percent in Aug-Sep 2014 while PCEX increased at 1.2 percent. PCEF increased at 3.0 percent while PCEE fell at 19.1 percent. Commodity prices have moderated with reallocation of financial investments to carry trades in equities.

Table IV-5, US, Percentage Change from Prior Month of Prices of Personal Consumption

Expenditures, Seasonally Adjusted Monthly ∆%

	PCE	PCEG	PCEG -D	PCES	PCEX	PCEF	PCEE
2014
Sep	0.1	0.0	-0.1	0.1	0.1	0.2	-0.8
Aug	-0.1	-0.4	-0.2	0.1	0.1	0.3	-2.7
∆% AE Aug-Sep	0.0	-2.4	-1.8	1.2	1.2	3.0	-19.1
Jul	0.1	0.0	-0.2	0.1	0.1	0.3	-0.3
Jun	0.2	0.4	-0.1	0.1	0.2	0.0	1.7
May	0.2	0.2	-0.3	0.3	0.2	0.6	0.8
Apr	0.2	0.3	0.0	0.2	0.2	0.3	0.4
∆% AE Apr-Jul	2.1	2.7	-1.8	2.1	2.1	3.7	8.1
Mar	0.2	-0.2	-0.3	0.3	0.1	0.5	-0.1
Feb	0.1	-0.1	-0.2	0.2	0.1	0.3	-0.5
Jan	0.1	0.0	-0.1	0.2	0.1	0.0	0.4
2013
Dec	0.2	0.1	-0.4	0.2	0.1	0.1	1.7
∆% AE Dec-Mar	1.8	-0.6	-3.0	2.7	1.2	2.7	4.6
Nov	0.1	-0.2	-0.3	0.2	0.1	0.0	-0.4
Oct	0.1	-0.2	-0.2	0.2	0.1	0.0	-0.9
Sep	0.1	-0.1	-0.1	0.2	0.1	-0.1	0.2
Aug	0.1	0.0	-0.3	0.1	0.1	0.1	-0.4
Jul	0.1	0.1	-0.3	0.1	0.1	0.1	0.3
Jun	0.3	0.4	-0.1	0.2	0.2	0.2	1.9
May	0.1	-0.1	-0.1	0.2	0.1	-0.2	0.8
∆% AE May-Nov	1.6	-0.2	-2.4	2.1	1.4	0.2	2.6
Apr	-0.1	-0.5	-0.3	0.1	0.0	0.1	-2.4
Mar	-0.1	-0.6	-0.2	0.2	0.1	0.1	-3.3
∆% AE Mar-Apr	-1.2	-6.4	-3.0	1.8	0.6	1.2	-29.3
Feb	0.3	0.7	0.0	0.2	0.1	0.1	4.2
∆% AE Feb	3.7	8.7	0.0	2.4	1.2	1.2	63.8
Jan	0.1	-0.1	0.0	0.2	0.2	0.0	-0.9
2012
Dec	0.0	-0.4	-0.2	0.2	0.0	0.2	-1.4
Nov	-0.1	-0.6	-0.1	0.2	0.1	0.3	-3.3
Oct	0.2	0.2	-0.1	0.3	0.2	0.2	0.8
∆% AE Oct-Jan	0.6	-2.7	-1.2	2.7	1.5	2.1	-13.6
Sep	0.3	0.6	-0.2	0.1	0.1	-0.1	3.8
Aug	0.3	0.6	-0.2	0.1	0.0	0.0	4.6
∆% AE Aug-Sep	3.7	7.4	-2.4	1.2	0.6	-0.6	63.8
Jul	0.0	-0.1	-0.2	0.1	0.1	0.0	-1.1
Jun	0.0	-0.3	-0.2	0.2	0.2	0.2	-2.1
∆% AE Jun-Jul	0.0	-2.4	-2.4	2.4	1.8	1.2	-17.6
May	0.0	-0.5	-0.1	0.2	0.1	0.0	-2.8
Apr	0.1	0.0	-0.2	0.2	0.1	0.1	0.0
∆% AE Apr- May	0.6	-3.0	-1.8	2.4	1.2	0.6	-15.7
Mar	0.2	0.3	-0.1	0.2	0.2	0.2	0.7
Feb	0.2	0.3	-0.1	0.1	0.1	0.0	1.6
Jan	0.3	0.3	0.1	0.2	0.2	0.2	0.6
∆% AE Jan- Mar	2.8	3.7	-0.4	2.0	2.0	1.6	12.2
2011
Dec	0.0	-0.2	-0.2	0.2	0.1	0.2	-1.7
Nov	0.1	0.1	-0.2	0.2	0.2	0.0	0.1
Oct	0.1	-0.1	0.0	0.1	0.1	0.1	-1.1
∆% AE Oct- Dec	0.8	-0.8	-1.6	2.0	1.6	1.2	-10.3
Sep	0.2	0.2	-0.4	0.2	0.1	0.5	1.0
Aug	0.2	0.2	-0.2	0.2	0.2	0.6	0.1
Jul	0.2	0.2	-0.1	0.2	0.2	0.4	0.2
∆% AE Jul-Sep	2.4	2.4	-2.8	2.4	2.0	6.2	5.3
Jun	0.0	-0.1	0.1	0.1	0.1	0.2	-1.6
May	0.3	0.5	0.1	0.3	0.2	0.5	1.4
∆% AE May-Jun	1.8	2.4	1.2	2.4	1.8	4.3	-1.3
Apr	0.4	0.8	0.3	0.3	0.2	0.4	3.3
Mar	0.4	0.7	-0.1	0.2	0.1	0.9	3.2
Feb	0.3	0.4	0.2	0.2	0.2	0.6	1.3
Jan	0.2	0.4	0.0	0.1	0.1	0.6	1.1
∆% AE Jan-Apr	4.0	7.1	1.2	2.4	1.8	7.8	30.1
2010
Dec	0.2	0.6	-0.3	0.1	0.0	0.1	4.1
Nov	0.2	0.2	-0.2	0.1	0.1	0.2	1.1
Oct	0.2	0.4	-0.2	0.1	0.1	0.1	3.1
Sep	0.1	0.2	-0.1	0.1	0.0	0.2	0.6
Aug	0.1	0.3	0.1	0.1	0.1	0.1	1.0
Jul	0.1	0.1	-0.3	0.1	0.1	0.1	1.2
Jun	0.1	-0.1	-0.4	0.1	0.1	-0.1	-0.5
May	0.0	-0.2	-0.2	0.2	0.1	0.1	-1.2
Apr	0.0	-0.3	-0.2	0.1	0.0	0.1	-0.8
Mar	0.1	-0.1	0.0	0.2	0.1	0.2	-0.5
Feb	0.0	-0.2	-0.3	0.1	0.1	0.1	-1.2
Jan	0.2	0.3	-0.1	0.1	0.1	0.1	1.7

Notes: percentage changes in price index relative to the same month a year earlier of PCE: personal consumption expenditures; PCEG: PCE goods; PCEG-D: PCE durable goods; PCES: PCE services; PCEX: PCE excluding food and energy; PCEF: PCE food; PCEE: PCE energy goods and services. AE: annual equivalent.

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

The charts of PCE inflation are also instructive. Chart IV-1 provides the monthly change of headline PCE price index. There is significant volatility in the monthly changes but excluding outliers fluctuations have been in a tight range between 1999 and 2014 around 0.2 percent per month.

Chart IV-1, US, Percentage Change of PCE Price Index from Prior Month, 1999-2014

Source: US Bureau of Economic Analysis

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

There is much less volatility in the PCE index excluding food and energy shown in Chart IV-2 with monthly percentage changes from 1999 to 2014. With the exception of 2001, there are no negative changes and again changes around 0.2 percent when excluding outliers.

Chart IV-2, US, Percentage Change of PCE Price Index Excluding Food and Energy from Prior Month, 1999-2014

Source: US Bureau of Economic Analysis

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

Fluctuations in the PCE index of food are much wider as shown in Chart IV-3 by monthly percentage changes from 1999 to 2014. There are also multiple negative changes and positive changes even exceeding 1.0 percent in three months.

Chart IV-3, US, Percentage Change of PCE Price Index Food from Prior Month, 1999-2014

Source: US Bureau of Economic Analysis

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

The band of fluctuation of the PCE price index of energy in Chart IV-4 is much wider. An interesting feature is the abundance of negative changes and large percentages.

Chart IV-4, US, Percentage Change of PCE Price Index Energy from Prior Month, 1999-2014

Source: US Bureau of Economic Analysis

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

Table IV-6 provides 12-month rates of PCE inflation from Jan 2012 to Sep 2014, annual inflation rates from 2000 to 2013 and average yearly rates of PCE inflation for various periods since 1929. Headline 12-month PCE inflation decreased from 2.5 percent in in the 12 months ending in Jan 2012 to 1.4 percent in the 12 months ending in Sep 2014. PCE inflation excluding food and energy (PCEX), used as indicator in monetary policy, decreased from 2.1 percent in the 12 months ending in Jan 2012 to 1.5 percent in the 12 months ending in Sep 2014, which is still below or at the tolerable maximum of 2.0-2.5 percent in monetary policy. The unintended effect of shocks of commodity prices from zero interest rates captured by PCE food prices (PCEF) and energy (PCEE) in the absence of risk aversion should be weighed in design and implementation of monetary policy. Annual PCE inflation in the second part of Table IV-6 shows significant fluctuations. Headline PCE inflation rose during the period of 1 percent interest rates from Jun 2003 to Jun 2005, reaching 2.9 percent in 2005. PCEE rose at very high two-digit rates after 2003. Headline PCE inflation increased 3.1 percent in 2008 while PCEE energy increased 14.3 percent in carry trades from zero interest rates to commodity derivatives during deep global recession. Flight away from risk financial assets to US government obligations fueled by proposals of TARP in Congress (Cochrane and Zingales 2009) caused decline of PCEE of 19.0 percent in 2009 and minus 0.1 percent in headline PCE. There is no deflation in the US economy. Carry trades from zero interest rates to commodity exposures mixed with portfolio reallocations among risk financial assets caused wide recent oscillations. Headline PCE inflation increased at the average rate of 2.9 percent from 1929 to 2013, as shown in Table IV-6 using the revisions by the BEA. PCE inflation was 6.1 percent on average during the Great Inflation episode from 1965 to 1981 (see http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html and Appendix I The Great Inflation; see Taylor 1993, 1997, 1998LB, 1999, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB and http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). PCE inflation was 3.2 percent on average from 1947 to 2013 and 3.2 percent on average for PCEX. The long-term charts of PCEE and PCEX show almost identical behavior.

Table IV-6, US, Percentage Change in 12 Months of Prices of Personal Consumption

Expenditures ∆%

	PCE	PCEG	PCEG -D	PCES	PCEX	PCEF	PCEE
2014
Sep	1.4	-0.1	-2.3	2.2	1.5	2.5	-0.9
Aug	1.4	-0.2	-2.2	2.3	1.5	2.2	0.1
Jul	1.6	0.2	-2.4	2.2	1.5	2.0	2.5
Jun	1.6	0.3	-2.6	2.3	1.5	1.8	3.1
May	1.7	0.3	-2.5	2.3	1.5	2.0	3.3
Apr	1.5	0.1	-2.3	2.3	1.4	1.2	3.3
Mar	1.2	-0.8	-2.6	2.2	1.3	1.0	0.4
Feb	1.0	-1.2	-2.5	2.1	1.2	0.7	-2.8
Jan	1.2	-0.5	-2.3	2.1	1.2	0.6	1.8
2013
Dec	1.2	-0.5	-2.2	2.1	1.3	0.6	0.5
Nov	1.0	-1.0	-2.0	2.1	1.3	0.7	-2.6
Oct	0.9	-1.4	-1.9	2.0	1.3	1.0	-5.4
Sep	1.0	-1.0	-1.8	2.1	1.3	1.2	-3.8
Aug	1.2	-0.4	-1.9	2.0	1.3	1.2	-0.3
Jul	1.5	0.3	-1.8	2.0	1.3	1.2	4.7
Jun	1.4	0.1	-1.7	2.0	1.3	1.0	3.2
May	1.1	-0.6	-1.8	2.0	1.3	1.0	-0.8
Apr	1.0	-1.0	-1.8	2.0	1.3	1.2	-4.3
Mar	1.2	-0.5	-1.7	2.1	1.4	1.1	-1.9
Feb	1.5	0.4	-1.6	2.1	1.5	1.2	2.1
Jan	1.4	0.0	-1.7	2.1	1.5	1.0	-0.5
2012
Dec	1.5	0.4	-1.6	2.1	1.6	1.3	1.1
Nov	1.6	0.5	-1.6	2.1	1.6	1.3	0.9
Oct	1.8	1.3	-1.6	2.1	1.7	1.0	4.4
Sep	1.6	1.0	-1.5	2.0	1.7	0.9	2.4
Aug	1.5	0.6	-1.7	2.0	1.6	1.5	-0.3
Jul	1.5	0.1	-1.7	2.1	1.8	2.0	-4.6
Jun	1.6	0.4	-1.6	2.2	1.9	2.4	-3.3
May	1.6	0.7	-1.3	2.1	1.9	2.4	-2.9
Apr	2.0	1.6	-1.1	2.2	2.0	2.9	1.3
Mar	2.3	2.4	-0.6	2.2	2.1	3.3	4.6
Feb	2.5	2.8	-0.6	2.3	2.0	3.9	7.3
Jan	2.5	3.0	-0.4	2.3	2.1	4.6	7.0
Annual ∆%
2013	1.2	-0.5	-1.8	2.1	1.3	1.0	-0.8
2012	1.8	1.2	-1.3	2.1	1.8	2.3	1.4
2011	2.5	3.7	-0.9	1.8	1.5	4.0	16.0
2010	1.7	1.6	-1.4	1.7	1.3	0.3	10.1
2009	-0.1	-2.3	-1.7	1.1	1.2	1.2	-19.0
2008	3.1	3.0	-1.9	3.1	2.1	6.1	14.3
2007	2.5	1.1	-2.0	3.2	2.2	3.9	6.0
2006	2.7	1.4	-1.6	3.4	2.2	1.7	11.3
2005	2.9	2.0	-1.0	3.3	2.2	1.7	17.3
2004	2.4	1.4	-1.9	3.0	1.9	3.1	11.3
2003	2.0	-0.1	-3.6	3.1	1.5	1.9	12.6
2002	1.3	-0.9	-2.5	2.6	1.7	1.5	-5.8
2001	1.9	-0.1	-2.0	3.1	1.8	2.9	2.5
2000	2.5	2.0	-1.8	2.8	1.7	2.3	18.3
Average ∆%
2000-2013	2.0	0.9	-21.3*	2.6	1.7	2.4	5.5
1929-2013	2.9	2.3	1.4	3.3	2.8	2.9	3.3
1947-2013	3.2	2.3	1.1	3.9	3.2	3.0	4.2
1965-1981	6.1	5.6	4.3	6.5	5.7	6.3	9.3

*Percentage change from 2000 to 2012.

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

The headline PCE index is shown in Chart IV-5 from 1999 to 2014. There is an evident upward trend with the carry-trade bump in 2008-2009 during the global recession.

Chart IV-5, US, Price Index of Personal Consumption Expenditures 1999-2014

Source: US Bureau of Economic Analysis

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

The consumer price index in Chart IV-6 mirrors the behavior of the PCE price index in Chart IV-6. There is the same upward trend with the carry-trade bump in 2008 during the global recession.

Chart IV-6, US, Consumer Price Index, NSA, 1999-2014

Source: US Bureau of Labor Statistics

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

Chart IV-7 provides the PCE price index excluding food and energy. There is milder upward trend with fewer oscillations.

Chart IV-7, US, Price Index of Personal Consumption Expenditures Excluding Food and Energy 1999-2014

Source: US Bureau of Economic Analysis

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

The core consumer price index, excluding food and energy, is shown in Chart IV-8. There is also an upward trend but with fluctuations.

Chart IV-8, US, Consumer Price Index Excluding Food and Energy, NSA, 1999-2014

Source: US Bureau of Labor Statistics

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

The PCE price index of food is shown in Chart IV-9. There is a more pronounced upward trend and sharper fluctuations.

Chart IV-9, US, Price Index of Personal Consumption Expenditures Food 1999-2014

Source: US Bureau of Economic Analysis

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

There is similar behavior in the consumer price index of food in Chart IV-10. There is an upward trend from 1999 to 2011 with a major bump in 2009 when commodity futures positions were unwound. Zero interest rates with bouts of risk aversion dominate the trend into 2011. Risk aversion softens the trend toward the end of 2011 and in 2012-2014.

Chart IV-10, US, Consumer Price Index, Food, NSA, 1999-2014

Source: US Bureau of Labor Statistics

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

The most pronounced trend of PCE price indexes is that of energy in Chart IV-11. It is impossible to explain the hump in 2008 in the middle of the global recession without the carry trade from zero interest rates to leveraged positions in commodity futures. Risk aversion after Sep 2008 caused flight to the safe haven of government obligations. Cochrane and Zingales (2009) explain the flight by public allegations of toxic assets in banks during the request of funding from Congress for the Troubled Asset Relief Program (TARP). The return of risk appetite with zero interest rates caused a first wave of carry trades with another upward trend interrupted by the first European sovereign risk crisis in Apr-Jul 2010. Zero interest rates with risk appetite caused another sharp upward trend of commodity prices interrupted by risk aversion from the second sovereign crisis. In the absence of risk aversion, carry trades from zero interest rates to positions in risk financial assets will continue to cause distortions such as commodity price trends and fluctuations.

Chart IV-11, US, Price Index of Personal Consumption Expenditures Energy Goods and Services 1999-2014

Source: US Bureau of Economic Analysis

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

Chart IV-12 provides the consumer price index of energy commodities. Unconventional monetary policy of zero or near zero interest rates causes upward trends in commodity prices reflected in (1) increase from 2003 to 2007; (2) sharp increase during the global contraction in 2008; (3) collapse from 2008 into 2009 as positions in commodity futures were unwound in a flight to government obligations; (4) new upward trend after 2010; and (5) episodes of decline during risk aversion shocks such as the more recent segment during the worsening European debt crisis in Nov and Dec of 2011 and with new strength of commodity prices in the beginning of 2012 followed by softness in another episode of risk aversion and increases during risk appetite.

Chart IV-12, US, Consumer Price Index, Energy, NSA, 1999-2014

Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Chart IV-13 of the US Energy Information Administration provides prices of the crude oil futures contract. Unconventional monetary policy of very low interest rates and quantitative easing with suspension of the 30-year bond to lower mortgage rates caused a sharp upward trend of oil prices. There is no explanation for the jump of oil prices to $149/barrel in 2008 during a sharp global recession other than carry trades from zero interest rates to commodity futures. The peak in Chart IV-13 is $145.18 on Jul 14, 2008, in the midst of deep global recession, falling to $33.87/barrel on Dec 19, 2008 (data from the US Energy Information Administration (http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RCLC1&f=D). Prices collapsed in the flight to government obligations caused by proposals for withdrawing “toxic assets” in the Troubled Asset Relief Program (TARP) as analyzed by Cochrane and Zingales (2009). Risk appetite with zero interest rates after stress tests of US banks resulted in another upward trend of commodity prices after 2009 with fluctuations during periods of risk aversion. All price indexes are affected by unconventional monetary policy.

Chart IV-13, US, Crude Oil Futures Contract

Source: US Energy Information Administration

http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RCLC1&f=D

Table IV-14 provides the annual PCE price index from the revised and enhanced dataset of the Bureau of Economic Analysis (BEA). The annual PCEE index increased at the average rate of 2.9 percent from 1929 to 2013. There is no support for fear of deflation.

Chart IV-14, US, Price Index of Personal Consumption Expenditures, Annual, 1929-2013

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

Chart IV-15 of the Bureau of Labor Statistics (BLS) provides the consumer price index from 1915 to 2014. There is long-term inflation and no evidence in support of fear of deflation.

Chart IV-15, US, Consumer Price Index, Annual, 1915-2014

Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Chart IV-16 provides the BEA annual index of PCE prices excluding food and energy. The average rate of increase from 1929 to 2013 is 2.8 percent.

Chart IV-16, US, Price Index of Personal Consumption Expenditures Excluding Food and Energy, Annual, 1929-2013

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

Chart IV-17 of the Bureau of Labor Statistics (BLS) provides the annual consumer price index excluding food and energy from 1957 to 2013. There is long-term, fluctuating inflation.

Chart IV-17, US, Consumer Price Index Excluding Food and Energy, Annual, 1957-2013

Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Chart IV-18 provides annual percentage changes of the index of prices of personal consumption expenditures. With the exception of the Great Depression of the 1930s, the index was negative only after World War II high inflation and the speculative carry trades on commodities induced by zero interest rates in 2008. Deflation fear does not have support in reality.

Chart IV-18, US, Price Index of Personal Consumption Expenditures, Annual Percentage Changes 1930-2013

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

Chart IV-19 provides annual percentage changes of the US consumer price index since 1914. Besides the Great Depression, the index of consumer prices all items fell only after World War II, the Korean War and the episode of speculative carry trades induced by zero interest rates during the global recession in 2008.

Chart IV-19, US, Consumer Price Index, Annual Percentage Changes, 1915-2013

Source: US bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Chart IV-20 provides annual percentage changes of the price index of personal consumption expenditures excluding food and energy since 1930. Besides the episode of the Great Depression, there are no negative changes with the lowest reading after fast inflation during World War II.

Chart IV-20, US, Price Index of Personal Consumption Expenditures Excluding Food and Energy, Annual Percentage Changes, 1930-2013

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

Chart IV-21 provides annual percentage changes of the PCE index excluding food and energy. There are no negative changes in the history of the index that would support fear of deflation justifying unconventional monetary policy.

Chart IV-21, US, Consumer Price Index Excluding Food and Energy, Annual Percentage Changes, 1958-2013

Source: US bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Manufacturers’ shipments of durable goods increased 0.1 percent in Sep 2014, decreasing 1.8 percent in Aug 2014 and increasing 3.7 percent in Jul 2014. New orders decreased 1.3 percent in Sep 2014 after decreasing 18.3 percent in Aug 2014 and increasing 22.5 percent in Jul 2014, as shown in Table VA-1. These data are very volatile. Volatility is illustrated by decrease of 12.9 percent in Nov 2012 after increase of orders for nondefense aircraft of 2642.2 percent in Sep 2012 after decrease of 97.2 percent in Aug and increases of 51.1 percent in Jul 2012 and 32.5 percent in Jun 2012. Nondefense aircraft new orders decreased 16.1 percent in Sep 2014 after decreasing 74.0 percent in Aug 2014 and increasing 311.5 percent in Jul 2014. New orders excluding transportation equipment decreased 0.2 percent in Sep 2014, increasing 0.7 percent in Aug 2014 and decreasing 0.6 percent in Jul 2014. Capital goods new orders, indicating investment, decreased 4.2 percent in Sep 2014, decreasing 34.1 percent in Aug 2014 and increasing 52.5 percent in Jul 2014. New orders of nondefense capital goods decreased 5.4 percent in Sep 2014, after decreasing 36.5 percent in Aug 2014 and increasing 60.9 percent in Jul 2014. Capital goods orders excluding volatile aircraft decreased 1.7 percent in Sep 2014, increasing 0.3 percent in Aug 2014 and decreasing 0.1 percent in Jul 2014.

Table VA-1, US, Durable Goods Value of Manufacturers’ Shipments and New Orders, SA, Month ∆%

	Sep 2014 ∆%	Aug 2014 ∆%	Jul 2014 ∆%
Total
S	0.1	-1.8	3.7
NO	-1.3	-18.3	22.5
Excluding Transport
S	0.0	-0.1	1.9
NO	-0.2	0.7	-0.6
Excluding Defense
S	0.1	-1.9	3.7
NO	-1.5	-19.1	24.9
Machinery
S	-0.4	0.1	3.3
NO	-2.8	1.1	-1.4
Computers & Electronic Products
S	-1.4	-1.2	3.1
NO	-2.5	1.7	-0.8
Computers
S	-5.7	-10.2	-5.6
NO	-5.3	-11.7	-7.7
Transport Equipment
S	0.3	-5.4	8.0
NO	-3.7	-42.4	73.3
Motor Vehicles
S	0.2	-7.1	10.1
NO	-0.1	-6.6	10.0
Nondefense Aircraft
S	1.6	-1.5	4.0
NO	-16.1	-74.0	315.6
Capital Goods
S	0.3	0.4	1.9
NO	-4.2	-34.1	52.5
Nondefense Capital Goods
S	0.5	0.2	1.9
NO	-5.4	-36.5	60.9
Capital Goods ex Aircraft
S	-0.2	0.1	2.0
NO	-1.7	0.3	-0.1

Note: Mfg: manufacturing; S: shipments; NO: new orders; Transport: transportation

Source: US Census Bureau

http://www.census.gov/manufacturing/m3/

Chart VA-1 of the US Census Bureau provides new orders of durable goods seasonally adjusted since Jan 1992. New orders fell sharply during the global recession. New orders recovered at faster rates and then flattened together with the rest of the economy after 2012. There are also downward effects of lower inflation because data are nominal without adjustment for inflation.

Chart VA-1, US, Durable Goods New orders, SA

Source: US Census Bureau

http://www.census.gov/manufacturing/m3/

Chart VA-2 provides monthly changes in durable goods new orders. There is significant volatility in these data, preventing clear identification of trends.

Chart VA-2, US, Manufacturers’ Durable Goods New Orders 2013-2014

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr021.html

Additional perspective on manufacturers’ shipments and new orders of durable goods is in Table VA-2. Values are cumulative millions of dollars in Jan-Sep 2014 not seasonally adjusted (NSA) and without adjustment for inflation. Shipments of durable goods of all manufacturing industries in Jan-Sep 2014 total $1,166.9 billion and new orders total $2,198.4 billion, growing respectively by 5.0 percent and 7.6 percent relative to the same period in 2013. Excluding transportation equipment, shipments grew 5.3 percent and new orders increased 5.4 percent. Excluding defense, shipments grew 5.5 percent and new orders grew 7.7 percent. Important information not in Table VA-2 is the large share of nondurable goods. Capital goods have relatively high value of $779.3 billion for shipments, growing 4.6 percent, and new orders $860.5 billion, increasing 9.9 percent. Excluding aircraft, capital goods shipments reached $779.3 billion, growing by 4.6 percent, and new orders $860.5 billion, increasing 9.9 percent. Data weakened in 2013 with effects of lower inflation on nominal values with recovery later in the year.

Table VA-2, US, Value of Manufacturers’ Shipments and New Orders of Durable Goods, NSA, Millions of Dollars

Jan-Sep 2014	Shipments	∆% 2014/ 2013	New Orders	∆% 2014/ 2013
Total	2,166,971	5.0	2,198,404	7.6
Excluding Transport	1,531,969	5.3	1,492,152	5.4
Excluding Defense	2,062,453	5.5	2,097,011	7.7
Machinery	325,953	5.7	337,889	7.9
Computers & Electronic Products	257,991	4.9	197,518	4.4
Computers & Related Products	19,434	-4.5	20,039	-2.0
Transport Equipment	635,002	4.3	706,252	12.8
Motor Vehicles	420,816	4.4	421,379	4.7
Nondefense Aircraft	108,574	10.8	180,914	39.6
Capital Goods	779,298	4.6	860,461	9.9
Nondefense Capital Goods	693,899	5.6	777,632	10.1
Capital Goods ex Aircraft	618,263	4.9	640,059	5.0

Note: Transport: transportation

Source: US Census Bureau

http://www.census.gov/manufacturing/m3/

Chart VA-3 of the US Census Bureau provides new orders of durable goods not seasonally adjusted since Jan 1992. New orders are oscillating around the highest value before the global recession, which could be lower in real terms because of continuing inflation.

Chart VA-3, US, Durable Goods New orders, NSA

Source: US Census Bureau

http://www.census.gov/manufacturing/m3/

Chart VA-4 of the Board of Governors of the Federal Reserve System shows that output of durable manufacturing accelerated in the 1980s and 1990s with slower growth in the 2000s perhaps because processes matured. Growth was robust after the major drop during the global recession but appears to vacillate in the final segment.

Chart VA-4, US, Output of Durable Manufacturing, 1972-2014

Source: Board of Governors of the Federal Reserve System

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

Manufacturing jobs not seasonally adjusted increased 157,000 from Sep 2013 to
Sep 2014 or at the average monthly rate of 13,083. There are effects of the weaker economy and international trade together with the yearly adjustment of labor statistics. Industrial production increased 1.0 percent in Sep 2014 and decreased 0.2 percent in Aug 2014 after increasing 0.2 percent in Jul 2014, as shown in Table I-1, with all data seasonally adjusted. The Federal Reserve completed its annual revision of industrial production and capacity utilization on Mar 28, 2014 (http://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm). The report of the Board of Governors of the Federal Reserve System states (http://www.federalreserve.gov/releases/g17/Current/default.htm):

“Industrial production increased 1.0 percent in September and advanced at an annual rate of 3.2 percent in the third quarter of 2014, roughly its average quarterly increase since the end of 2010. In September, manufacturing output moved up 0.5 percent, while the indexes for mining and for utilities climbed 1.8 percent and 3.9 percent, respectively. For the third quarter as a whole, manufacturing production rose at an annual rate of 3.5 percent and mining output increased at an annual rate of 8.7 percent. The output of utilities fell at an annual rate of 8.5 percent for a second consecutive quarterly decline. At 105.1 percent of its 2007 average, total industrial production in September was 4.3 percent above its level of a year earlier. The capacity utilization rate for total industry moved up 0.6 percentage point in September to 79.3 percent, a rate that is 1.0 percentage point above its level of 12 months earlier but 0.8 percentage point below its long-run (1972–2013) average.”

In the six months ending in Sep 2014, United States national industrial production accumulated increase of 1.9 percent at the annual equivalent rate of 3.9 percent, which is lower than growth of 4.3 percent in the 12 months ending in Sep 2014. Excluding growth of 1.0 percent in Sep 2014, growth in the remaining five months from Apr to Aug 2014 accumulated to 0.9 percent or 2.2 percent annual equivalent. Industrial production declined in one of the past six months. Industrial production expanded at annual equivalent 4.1 percent in the most recent quarter from Jul to Sep 2014 and at 3.7 percent in the prior quarter Apr-Jun 2014. Business equipment accumulated growth of 2.2 percent in the six months from Apr to Sep 2014 at the annual equivalent rate of 4.5 percent, which is close growth of 4.6 percent in the 12 months ending in Sep 2014. The Fed analyzes capacity utilization of total industry in its report (http://www.federalreserve.gov/releases/g17/Current/default.htm): “The capacity utilization rate for total industry moved up 0.6 percentage point in September to 79.3 percent, a rate that is 1.0 percentage point above its level of 12 months earlier but 0.8 percentage point below its long-run (1972–2013) average.” United States industry apparently decelerated to a lower growth rate with possible acceleration in past months.

Manufacturing by 21.9 from the peak in Jun 2007 to the trough in Apr 2009 and increased by 19.9 percent from the trough in Apr 2009 to Dec 2013. Manufacturing grew 26.8 percent from the trough in Apr 2009 to Sep 2014. Manufacturing output in Sep 2014 is 1.0 percent below the peak in Jun 2007. Growth at trend in the entire cycle from IVQ2007 to IIQ2014 would have accumulated to 22.1 percent. GDP in IIQ2014 would be $18,305.0 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,294.6 billion than actual $16,010.4 billion. There are about two trillion dollars of GDP less than at trend, explaining the 26.5 million unemployed or underemployed equivalent to actual unemployment of 16.1 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/10/world-financial-turbulence-twenty-seven.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/competitive-monetary-policy-and.html). US GDP in IIQ2014 is 12.5 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,010.4 billion in IIQ2014 or 6.8 percent at the average annual equivalent rate of 1.0 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. The long-term trend is growth at average 3.3 percent per year from Jan 1919 to Sep 2014. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 123.5550 in Sep 2014. The actual index NSA in Sep 2014 is 102.0228, which is 17.4 percent below trend. Manufacturing output grew at average 2.3 percent between Dec 1986 and Dec 2013, raising the index at trend to 115.7028 in Sep 2014. The output of manufacturing at 102.0228 in Sep 2014 is 11.8 percent below trend under this alternative calculation.

Table I-13 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 87.3 percent in IIQ2014. Most of US national income is in the form of services. In Sep 2014, there were 139.752 million nonfarm jobs NSA in the US, according to estimates of the establishment survey of the Bureau of Labor Statistics (BLS) (http://www.bls.gov/news.release/empsit.nr0.htm Table B-1). Total private jobs of 117.940 million NSA in Sep 2014 accounted for 84.4 percent of total nonfarm jobs of 139.752 million, of which 12.222 million, or 10.4 percent of total private jobs and 8.7 percent of total nonfarm jobs, were in manufacturing. Private service-producing jobs were 98.463 million NSA in Sep 2014, or 70.5 percent of total nonfarm jobs and 83.5 percent of total private-sector jobs. Manufacturing has share of 11.3 percent in US national income in IIQ2014 and durable goods 6.4 percent, as shown in Table I-13. Most income in the US originates in services. Subsidies and similar measures designed to increase manufacturing jobs will not increase economic growth and employment and may actually reduce growth by diverting resources away from currently employment-creating activities because of the drain of taxation.

Table I-13, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total

	SAAR IQ2014	% Total	SAAR IIQ2014	% Total
National Income WCCA	14,982.0	100.0	15,276.2	100.0
Domestic Industries	14,771.0	98.6	15,062.8	98.6
Private Industries	13,055.8	87.1	13,342.0	87.3
Agriculture	161.0	1.1	178.6	1.2
Mining	273.1	1.8	260.5	1.7
Utilities	209.1	1.4	215.7	1.4
Construction	660.3	4.4	666.8	4.4
Manufacturing	1642.5	11.0	1721.4	11.3
Durable Goods	950.2	6.3	982.0	6.4
Nondurable Goods	692.3	4.6	739.3	4.8
Wholesale Trade	908.7	6.1	925.1	6.1
Retail Trade	1029.8	6.9	1051.9	6.9
Transportation & WH	465.6	3.1	478.0	3.1
Information	560.5	3.7	578.0	3.8
Finance, Insurance, RE	2638.0	17.6	2661.9	17.4
Professional & Business Services	2026.8	13.5	2086.1	13.7
Education, Health Care	1461.8	9.8	1487.5	9.7
Arts, Entertainment	593.9	4.0	605.2	4.0
Other Services	424.7	2.8	425.4	2.8
Government	1715.1	11.4	1720.8	11.3
Rest of the World	211.0	1.4	213.5	1.4

Notes: SSAR: Seasonally-Adjusted Annual Rate; WCCA: Without Capital Consumption Adjustment by Industry; WH: Warehousing; RE, includes rental and leasing: Real Estate; Art, Entertainment includes recreation, accommodation and food services; BS: business services

Source: US Bureau of Economic Analysis

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

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-2 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 94.5 percent in the 10-city composite of the Case-Shiller home price index and 79.5 percent in the 20-city composite between Aug 2000 and Aug 2005. Prices rose around 100 percent from Aug 2000 to Aug 2006, increasing 104.9 percent for the 10-city composite and 89.8 percent for the 20-city composite. House prices rose 39.4 percent between Aug 2003 and Aug 2005 for the 10-city composite and 34.9 percent for the 20-city composite 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 Aug 2003 and Aug 2006, the 10-city index gained 46.8 percent and the 20-city index increased 42.6 percent. House prices have fallen from Aug 2006 to Aug 2014 by 16.4 percent for the 10-city composite and 15.8 percent for the 20-city composite. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Aug 2014, house prices increased 5.5 percent in the 10-city composite and increased 5.6 percent in the 20-city composite. Table IIA-2 also shows that house prices increased 71.3 percent between Aug 2000 and Aug 2014 for the 10-city composite and increased 59.8 percent for the 20-city composite. 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 16.7 percent from the peak in Jun 2006 to Aug 2014 and the 20-city composite fell 15.9 percent from the peak in Jul 2006 to Aug 2014. The final part of Table I-4 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 2013 for the 10-city composite was 3.7 percent. 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. 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 2013 was 3.6 percent while the rate of the 20-city composite was 3.1 percent.

Table IIA-2, US, Percentage Changes of Standard & Poor’s Case-Shiller Home Price Indices, Not Seasonally Adjusted, ∆%

	10-City Composite	20-City Composite
∆% Aug 2000 to Aug 2003	39.6	33.1
∆% Aug 2000 to Aug 2005	94.5	79.5
∆% Aug 2003 to Aug 2005	39.4	34.9
∆% Aug 2000 to Aug 2006	104.9	89.8
∆% Aug 2003 to Aug 2006	46.8	42.6
∆% Aug 2005 to Aug 2014	-11.9	-10.9
∆% Aug 2006 to Aug 2014	-16.4	-15.8
∆% Aug 2009 to Aug 2014	19.3	18.9
∆% Aug 2010 to Aug 2014	16.4	17.0
∆% Aug 2011 to Aug 2014	20.5	21.5
∆% Aug 2012 to Aug 2014	19.0	19.1
∆% Aug 2013 to Aug 2014	5.5	5.6
∆% Aug 2000 to Aug 2014	71.3	59.8
∆% Peak Jun 2006 Aug 2014	-16.7
∆% Peak Jul 2006 Aug 2014		-15.9
Average ∆% Dec 1987-Dec 2013	3.7	NA
Average ∆% Dec 1987-Dec 2000	3.8	NA
Average ∆% Dec 1992-Dec 2000	5.0	NA
Average ∆% Dec 2000-Dec 2013	3.6	3.1

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

Price increases measured by the Case-Shiller house price indices are decelerating (http://www.housingviews.com/wp-content/uploads/2014/10/CSHomePrice_Release_Aug2014-results.pdf). Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the 10- and 20-city composites. In Jan 2013, the seasonally adjusted 10-city composite increased 0.9 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 Feb through Apr 2012, house prices seasonally adjusted declined in every month for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table IIA-3. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. Without seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Aug 2011 but fell in every month from Sep 2011 to Feb 2012. The not seasonally adjusted index registers decline in Mar 2012 of 0.1 percent for the 10-city composite and is flat for the 20-city composite. Not seasonally adjusted house prices increased 1.4 percent in Apr 2012 and at high monthly percentage rates until Sep 2012. House prices not seasonally adjusted stalled from Oct 2012 to Jan 2013 and surged from Feb to Sep 2013, decelerating in Oct 2013-Feb 2014. House prices grew at fast rates in Mar 2014. The 10-city NSA index increased 0.2 percent in Aug 2014 and the 20-city 0.3 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

Table IIA-3, 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
Aug 2014	-0.2	0.2	-0.1	0.2
Jul	-0.5	0.6	-0.5	0.6
Jun	-0.2	1.0	-0.3	1.0
May	-0.3	1.1	-0.3	1.1
Apr	0.1	1.1	0.1	1.2
Mar	1.0	0.8	1.1	0.9
Feb	1.0	0.0	1.0	0.0
Jan	0.8	-0.1	0.8	-0.1
Dec 2013	0.7	-0.1	0.7	-0.1
Nov	0.9	0.0	0.9	-0.1
Oct	1.1	0.2	1.1	0.2
Sep	1.0	0.7	1.1	0.7
Aug	0.9	1.3	0.9	1.3
Jul	0.8	1.9	0.7	1.8
Jun	0.9	2.2	0.9	2.2
May	1.1	2.5	1.0	2.5
Apr	1.6	2.6	1.5	2.6
Mar	1.6	1.3	1.6	1.3
Feb	1.3	0.3	1.3	0.2
Jan	0.9	0.0	0.9	0.0
Dec 2012	1.0	0.2	1.0	0.2
Nov	0.7	-0.3	0.8	-0.2
Oct	0.7	-0.2	0.8	-0.1
Sep	0.5	0.3	0.6	0.3
Aug	0.4	0.8	0.5	0.9
Jul	0.3	1.5	0.4	1.6
Jun	0.9	2.1	1.0	2.3
May	0.8	2.2	0.9	2.4
Apr	0.5	1.4	0.5	1.4
Mar	0.3	-0.1	0.4	0.0
Feb	0.1	-0.9	0.1	-0.8
Jan	-0.2	-1.1	-0.1	-1.0
Dec 2011	-0.5	-1.2	-0.4	-1.1
Nov	-0.5	-1.4	-0.5	-1.3
Oct	-0.5	-1.3	-0.5	-1.4
Sep	-0.4	-0.6	-0.4	-0.7
Aug	-0.3	0.1	-0.3	0.1
Jul	-0.2	0.9	-0.2	1.0
Jun	-0.2	1.0	-0.1	1.2
May	-0.3	1.0	-0.3	1.0
Apr	-0.2	0.6	-0.3	0.6
Mar	-0.5	-1.0	-0.6	-1.0
Feb	-0.3	-1.3	-0.3	-1.2
Jan	-0.2	-1.1	-0.2	-1.1
Dec 2010	-0.2	-0.9	-0.2	-1.0

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

Industrial production in Japan increased 2.7 percent in Sep 2014 and increased 0.6 percent in 12 months, as shown in Table VB-1. Industrial production decreased 1.9 percent in Aug 2014 and fell 3.3 percent in 12 months. Industrial production increased 0.4 percent in Jul 2014 and fell 0.7 percent in 12 months. Japan’s industrial production fell 3.4 percent in Jun 2014 an increased 3.1 percent in 12 months. In May 2014, industrial production in Japan increased 0.7 percent, rebounding from the increase in the sales tax, and increased 1.0 percent in the 12 months ending in May 2014. Industrial production fell 2.8 percent in Apr 2014, mostly because of the increase in the tax on value added of consumption in Apr 2014, and increased 3.8 percent in 12 months. Decline of 2.8 percent in Jun 2013 interrupted four consecutive monthly increases from Feb through May 2013. Another interruption occurred in Aug 2013 with decrease of 0.5 percent and decline of 0.6 percent in 12 months. There was a third interruption with decline of 2.3 percent in Feb 2014 but increase of 7.0 percent in 12 months. Japan’s industrial production is strengthening with growth of 1.4 percent in Dec 2012, 0.9 percent in Feb 2013, 0.3 percent in Mar 2013, 0.6 percent in Apr 2013, 2.1 percent in May 2013, 2.7 percent in Jul 2013, 1.5 percent in Sep 2013, 0.6 percent in Oct 2013 and 0.5 percent in Dec 2013. Improvement continued with 3.9 percent in Jan 2014 and rebound of 0.7 percent in May 2014 from the drop of 2.8 percent in Apr caused by the increases in the sales tax. Growth in 12 months improved from minus 10.0 percent in Feb 2013 to 7.2 percent in Dec 2013, 10.6 percent in Jan 2014, 7.0 percent in Feb 2014 and 7.4 percent in Mar 2014. The sales tax of Apr 2014 interrupted improvement but growth in 12 months was positive at 1.0 percent in May 2014 and 3.1 percent in Jun 2014. Industrial production fell 21.9 percent in 2009 after falling 3.4 percent in 2008 but recovered by 15.6 percent in 2010. The annual average in calendar year 2011 fell 2.8 percent largely because of the Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011. Industrial production increased 0.6 percent in 2012 and fell 0.8 percent in 2013.

Table VB-1, Japan, Industrial Production ∆%

	∆% Month SA	∆% 12 Months NSA
Sep 2014	2.7	0.6
Aug	-1.9	-3.3
Jul	0.4	-0.7
Jun	-3.4	3.1
May	0.7	1.0
Apr	-2.8	3.8
Mar	0.7	7.4
Feb	-2.3	7.0
Jan	3.9	10.6
Dec 2013	0.5	7.2
Nov	0.3	4.8
Oct	0.6	5.4
Sep	1.5	5.3
Aug	-0.5	-0.6
Jul	2.7	1.9
Jun	-2.8	-4.7
May	2.1	-1.0
Apr	0.6	-3.2
Mar	0.3	-7.0
Feb	0.9	-10.0
Jan	-0.7	-6.4
Dec 2012	1.4	-7.6
Nov	-1.0	-5.5
Oct	0.3	-4.7
Sep	-2.2	-7.6
Aug	-1.4	-4.1
Jul	-0.5	0.1
Jun	-0.8	-0.6
May	-1.8	7.6
Apr	-0.5	15.1
Mar	0.2	16.6
Calendar Year
2013		-0.8
2012		0.6
2011		-2.8
2010		15.6

Source: Japan, Ministry of Economy, Trade and Industry (METI)

http://www.meti.go.jp/english/statistics/index.html

Japan is experiencing weak internal demand as in most advanced economies, interrupted by strong growth in IQ2012 but renewed weakening at the end of IIQ2012, beginning of IIIQ2012 and in IVQ2012. There was recovery in IQ2013, IIQ2013 and IIIQ2013. Recovery interrupted in IVQ2013, accelerating in IQ2014. There was weakening again in IIQ2014. Table VB-6 provides Japan’s wholesale and retail sales. There is strong performance in May 2013 with growth of 0.8 percent for retail sales followed by 1.6 percent in Jun 2013. Retail sales fell 0.3 percent in Jul 2013, rebounding 1.1 percent in Aug 2013. Retail sales increased 3.0 percent in the 12 months ending in Sep 2013 and 2.4 percent in the 12 months ending in Oct 2013. Retail sales increased 4.1 percent in the 12 months ending in Nov 2013 and 2.5 percent in the 12 months ending in Dec 2013. Retail sales grew 4.4 percent in the 12 months ending in Jan 2014 and 3.6 percent in the 12 months ending in Feb 2014. Japan’s retail sales increased 11.0 percent in the 12 months ending in Mar 2014 in part anticipating the increase in the tax on the value added of consumption. Retail sales fell 4.3 percent in Apr 2014 after the increase in the sales tax. Retail sales fell 0.4 percent in the 12 months ending in May 2014 and fell 0.6 percent in the 12 months ending in Jun 2014. Retail sales increased 0.6 percent in the 12 months ending in Jul 2014 and 1.2 percent in the 12 months ending in Aug 2014. Retail sales increased 2.3 percent in the 12 months ening in Sep 2014. Retail sales are recovering from deep drops in Mar and Apr 2011 following the Tōhoku or Great East Earthquake and Tsunami of Mar 11, 2011. Retail sales have been increasing in 12-month percentage changes from Dec 2011 through May 2012. Retail sales fell again by 1.3 percent in Jul 2012, increasing 1.3 percent in Aug 2012 and 0.4 percent in Sep 2012 but declining 1.2 percent in Oct 2012, rebounding by 0.9 percent in Nov 2012 and only 0.2 percent in Dec 2012 but contracting 1.1 percent in Jan 2013 and 2.2 percent in Feb 2013.

Table VB-6, Japan, Wholesale and Retail Sales 12 Month ∆%

	Total	Wholesale	Retail
Sep 2014	1.5	1.2	2.3
Aug	-1.6	-2.8	1.2
Jul	0.1	-0.1	0.6
Jun	-0.6	-0.5	-0.6
May	-1.0	-1.3	-0.4
Apr	-3.4	-3.0	-4.3
Mar	8.5	7.5	11.0
Feb	2.5	2.0	3.6
Jan	4.4	4.4	4.4
Dec 2013	2.8	2.9	2.5
Nov	2.9	2.4	4.1
Oct	2.0	1.8	2.4
Sep	2.8	2.7	3.0
Aug	0.6	0.4	1.1
Jul	1.3	2.0	-0.3
Jun	0.5	0.1	1.6
May	0.6	0.5	0.8
Apr	-0.1	-0.1	-0.2
Mar	-1.3	-1.8	-0.3
Feb	-1.6	-1.3	-2.2
Jan	-0.3	0.1	-1.1
Dec 2012	-1.7	-2.5	0.2
Nov	-0.9	-1.6	0.9
Oct	-1.6	-1.8	-1.2
Sep	-3.6	-5.1	0.4
Aug	-2.7	-4.4	1.3
Jul	-3.1	-4.0	-1.3
Jun	-2.6	-3.6	-0.2
May	2.7	2.6	3.0
Apr	1.8	0.4	5.0
Mar	3.2	0.9	9.3
Feb	-0.1	-1.3	3.1
Jan	-2.1	-3.8	1.6
Dec 2011	-0.8	-2.0	2.5
Nov	-2.3	-2.4	-2.2
Oct	1.1	0.8	1.9
Sep	0.3	0.8	-1.1
Aug	3.1	5.2	-2.6
Jul	2.3	3.0	0.6
Jun	3.1	3.8	1.2
May	1.3	2.3	-1.3
Apr	-2.6	-1.7	-4.8
Mar	-1.3	1.2	-8.3
Feb	5.3	7.2	0.1
Jan	3.3	4.6	0.1
Dec 2010	3.5	5.7	-2.1
Calendar Year
2013	0.9	0.8	1.0
2012	-0.9	-2.0	1.8
2011	1.0	1.9	-1.0
2010	2.4	2.3	2.6
2009	-20.5	-25.6	-2.3
2008	1.2	1.5	0.3

Source: Japan, Ministry of Economy, Trade and Industry (METI)

http://www.meti.go.jp/english/statistics/index.html

Germany’s labor market continues to show strength not found in most of the advanced economies, as shown in Table VE-1. The number unemployed, not seasonally adjusted, decreased from 2.20 million in Sep 2013 to 2.09 million in Sep 2014, or 5.0 percent, while the unemployment rate increased from 3.9 percent in Sep 2013 to 4.9 percent in Sep 2014. The number of persons in employment, not seasonally adjusted, decreased from 40.78 million in Sep 2013 to 40.63 million in Sep 2014, or 0.9 percent, while the employment rate decreased from 64.8 percent in Sep 2013 to 64.6 percent in Sep 2014. The number unemployed, seasonally adjusted, stabilized from 2.15 million in Aug 2014 to 2.14 million in Sep 2014, while the unemployment rate was unchanged at 5.0 percent in Sep 2014 relative to 5.0 percent in Aug 2014. The number of persons in employment, seasonally adjusted, stabilized from 40.57 million in Aug 2014 to 40.58 million in Sep 2014, or change of 0.0 percent. The employment rate seasonally adjusted did not change from 64.6 in Aug 2014 to 64.5 in Sep 2014.

Table VE-1, Germany, Unemployment Labor Force Survey

	Sep 2014	Aug 2014	Sep 2013
NSA
Number Unemployed Millions	2.09 ∆% Sep 2014 /Aug 2014: -2.8 ∆% Sep 2014/Sep 2013: -5.0	2.15	2.20
% Rate Unemployed	4.9	5.0	3.9
Persons in Employment Millions	40.63 ∆% Sep 2014/Aug 2014: -0.9 ∆% Sep 2014/Sep 2013: -0.4	41.00	40.78
Employment Rate	64.6	65.3	64.8
SA
Number Unemployed Millions	2.14 ∆% Sep 2014/Aug 2014: -0.5 ∆% Sep 2014/Sep 2013: –4.0	2.15	2.23
% Rate Unemployed	5.0	5.0	5.2
Persons in Employment Millions	40.58 ∆% Sep 2014/Aug 2014: 0.0 ∆% Sep 2014/Sep 2013: 0.4	40.57	40.40
Employment Rate	64.5	64.6	64.2

NSA: not seasonally adjusted; SA: seasonally adjusted

Source: Statistisches Bundesamt Deutschland

https://www.destatis.de/EN/PressServices/Press/pr/2014/10/PE14_378_132.html

The unemployment rate in Germany as percent of the labor force in Table VE-2 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. The rate is much lower than 11.1 percent in 2005 and 9.6 percent in 2006.

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

Oct 2014	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-1 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.

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

Source: Statistisches Bundesamt Deutschland

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

Italy’s index of business confidence in manufacturing and construction is provided in Table VG-3. There has been oscillation of manufacturing confidence below the historical average of 100 from 99.4 in Jun 2014 to 99.0 in Jul 2014 with decline to 96.0 in Oct 2014. Order books weakened from minus 21 in Jun 2014 to minus 24 in Aug 2014 with deterioration to minus 25 in Oct 2014. There is deterioration in construction with the index moving from 81.1 in Jun 2014 to 77.5 in Oct 2014.

Table VG-3, Italy, Index of Business Confidence in Manufacturing and Construction 2005=100

	Oct 2014	Sep 2014	Aug 2014	Jul 2014	Jun 2014
Mfg Confidence	96.0	95.5	95.6	99.0	99.4
Order Books	-25	-26	-24	-23	-21
Stocks Finished Products	3	3	3	0	0
Production Expectation	2	2	1	7	5
Construction Confidence	77.5	75.5	76.8	82.9	81.1
Order Books	-50	-48	-48	-45	-44
Employment	-21	-23	-22	-14	-22

Mfg: manufacturing

Source: Istituto Nazionale di Statistica

http://www.istat.it/it/archivio/136621

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Wednesday, November 5, 2014

Growth Uncertainties, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Disposable Income and Consumption Expenditures World Cyclical Slow Growth and Global Recession Risk: Part II

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