CMP Associates Regulation Blog: Dollar Revaluation Constraining Corporate Profits, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Private Fixed Investment, Swelling Undistributed Corporate Profits, Stating Real Disposable Income, Financial Repression, United States Housing Collapse, United States Commercial Banks, World Cyclical Slow Growth and Global Recession Risk: Part III

Dollar Revaluation Constraining Corporate Profits, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Stagnating Real Private Fixed Investment, Swelling Undistributed Corporate Profits, Stating Real Disposable Income, Financial Repression, United States Housing Collapse, United States Commercial Banks, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

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

IA Mediocre Cyclical United States Economic Growth

IA1 Stagnating Real Private Fixed Investment

IA2 Swelling Undistributed Corporate Profits

II Stagnating Real Disposable Income and Consumption Expenditures

IB1 Stagnating Real Disposable Income and Consumption Expenditures

IB2 Financial Repression

II United States Housing Collapse

IIB United States House Prices

IIA United States Commercial Banks Assets and Liabilities

IA Transmission of Monetary Policy

IB Functions of Banking

IC United States Commercial Banks Assets and Liabilities

ID Theory and Reality of Economic History, Cyclical Slow growth not Secular Stagnation and Monetary Policy Based on Fear of Deflation

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 IB 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/2015/11/interest-rate-liftoff-followed-by.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 7.7 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 8.3 percent annual equivalent, NDPI at 9.6 percent and NPCE at 4.3 percent. Real disposable income (RDPI) is more dynamic in the revisions, growing at 4.9 percent annual equivalent and RPCE at 2.1 percent. The policy of repressing savings with zero interest rates stimulated growth of nominal consumption (NPCE) at the annual equivalent rate of 4.3 percent and real consumption (RPCE) at 2.1 percent. In the fifth wave in Apr-Jul 2012, NPI increased at annual equivalent 1.2 percent, NDPI at 1.2 percent and RDPI at 0.9 percent. Financial repression failed to stimulate consumption with NPCE growing at 1.2 percent annual equivalent and RPCE at 0.9 percent. In the sixth wave in Aug-Oct 2012, in another wave of carry trades into commodity futures, NPI increased at 8.3 percent annual equivalent and NDPI increased at 7.9 percent while real disposable income (RDPI) increased at 3.7 percent annual equivalent. NPCE increased at 4.1 percent and RPCE changed at 0.0 percent. 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 25.3 percent in Nov-Dec 2012, nominal disposable income at 25.3 percent and real disposable personal income at 26.0 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 5.4 percent in Jan 2013 or at the annual equivalent rate of decline of 48.6 percent; nominal disposable personal income fell 6.3 percent or at the annual equivalent rate of decline of 54.2 percent; real disposable income fell 6.4 percent or at the annual rate of decline of 54.8 percent; nominal personal consumption expenditures increased 0.4 percent or at the annual equivalent rate of 4.9 percent; and real personal consumption expenditures increased 0.3 percent or at the annual equivalent rate of 3.7 percent. The savings rate fell significantly from 11.0 percent in Dec 2012 to 4.6 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 4.3 percent and nominal disposable income at 4.3 percent annual equivalent, while real disposable income increased at 2.4 percent annual equivalent. Nominal personal consumption expenditures grew at 3.0 percent annual equivalent and real personal consumption expenditures at 1.2 percent annual equivalent. The savings rate collapsed from 7.8 percent in Oct 2012, 8.8 percent in Nov 2012 and 11.0 percent in Dec 2012 to 4.6 percent in Jan 2013, 4.6 percent in Feb 2013 and 4.7 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 3.2 percent. Real disposable income grew at 2.8 percent annual equivalent and real personal consumption expenditures at 2.0 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 3.7 percent annual equivalent and real personal consumption expenditures at 2.4 percent. In the twelfth wave, nominal personal income increased at 4.9 percent annual equivalent in Nov 2013, nominal disposable income at 4.9 percent and nominal personal consumption expenditures at 6.2 percent. Real disposable income increased at annual equivalent 3.7 percent and real personal consumption expenditures at 6.2 percent. In the thirteenth wave, nominal personal income increased at 3.7 percent annual equivalent in Dec 2013 and nominal disposable income at 2.4 percent while real disposable income increased at 1.2 percent annual equivalent. Nominal personal consumption expenditures increased at 3.7 percent annual equivalent and 1.2 percent for real personal consumption expenditures. In the fourteenth wave, nominal personal income increased at 7.0 percent annual equivalent in Jan-Mar 2014, nominal disposable income at 6.6 percent and nominal consumption expenditures at 3.6 percent. Real disposable personal income increased at 4.9 percent and real personal consumption expenditures at 2.4 percent. In the fifteenth wave, nominal personal income increased at 4.7 percent in annual equivalent in Apr-Aug 2014 and nominal disposable income at 4.4 percent. Real disposable income increased at 2.9 percent in annual equivalent in Apr-Aug 2014. Nominal personal consumption increased at 5.2 percent annual equivalent in Apr-Aug 2014 and real personal consumption expenditures increased at 3.4 percent. In the sixteenth wave, nominal personal income increased at 4.6 percent annual equivalent in Sep-Dec 2014, nominal disposable income at 4.3 percent and nominal personal consumption at 2.7 percent. Real disposable income increased at 4.9 percent in Sep-Dec 2014 and real personal consumption expenditure at 3.3 percent. In the seventeenth wave, nominal personal income increased at 3.0 percent annual equivalent in Jan-Feb 2015 and nominal disposable income at 1.2 percent while nominal personal consumption expenditures fell at 1.2 percent. Real disposable income increased at 3.7 percent and real personal consumption expenditures at 0.6 percent. In the eighteenth wave, nominal personal income (NPI) increased at 4.9 percent and nominal disposable personal income (NDPI) increased at 4.5 percent annual equivalent in Mar-Jun 2015. Real disposable income (RDPI) increased at 2.0 percent. Nominal consumption expenditures (NPCE) increased at 7.0 percent and real personal consumption expenditures (RPCE) increased at 4.9 percent. In the nineteenth wave, nominal personal income (NPI) increased at 5.3 percent in Jun-Aug 2015 and nominal disposable personal income (NDPI) at 5.7 percent. Real disposable income (RDPI) increased at 4.1 percent, nominal personal consumption expenditures (NPCE) at 4.1 percent and real persona consumption expenditures (RPCE) at 2.4 percent. In the twentieth wave, nominal personal income (NPI) increased at 3.7 percent annual equivalent in Sep-Oct 2015, nominal disposable personal income (NDPI) at 3.7 percent and nominal personal consumption expenditures (NPCE) at 1.2 percent. Real disposable personal income grew at 4.3 percent annual equivalent and real personal consumption expenditures at 1.2 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 2.2 percent on average in the cyclical expansion in the 25 quarters from IIIQ2009 to IIIQ2015. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IIIQ2015 (http://www.bea.gov/newsreleases/national/gdp/2015/pdf/gdp3q15_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-increase-considered.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/monetary-policy-designed-on-measurable.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989 and at 7.8 percent from IQ1983 to IVQ1983 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-increase-considered.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/monetary-policy-designed-on-measurable.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 IIIQ2015 would have accumulated to 25.7 percent. GDP in IIIQ2015 would be $18,844.7 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,426.9 billion than actual $16,417.8 billion. There are about two trillion dollars of GDP less than at trend, explaining the 24.3 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.6 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2015/11/live-possibility-of-interest-rates.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/labor-market-uncertainty-and-interest.html). US GDP in IIIQ2015 is 12.9 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,417.8 billion in IIIQ2015 or 9.5 percent at the average annual equivalent rate of 1.2 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Oct 1919 to Oct 2015. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 107.6075 in Dec 2007 to 137.7209 in Oct 2015. The actual index NSA in Oct 2015 is 107.4128, which is 22.0 percent below trend. Manufacturing output grew at average 2.2 percent between Dec 1986 and Dec 2014. Using trend growth of 2.2 percent per year, the index would increase to 127.6069 in Oct 2015. The output of manufacturing at 107.4128 in Oct 2015 is 15.8 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
2015
Oct	0.4	0.4	0.4	0.1	0.1
Sep	0.2	0.2	0.3	0.1	0.1
AE ∆% Sep-Oct	3.7	3.7	4.3	1.2	1.2
Aug	0.4	0.4	0.4	0.3	0.3
Jul	0.4	0.5	0.4	0.3	0.2
Jun	0.5	0.5	0.2	0.3	0.1
AE ∆% Jun-Aug	5.3	5.7	4.1	3.7	2.4
May	0.6	0.5	0.2	0.9	0.6
Apr	0.6	0.6	0.5	0.3	0.3
Mar	0.0	0.0	-0.2	0.5	0.3
AE ∆% Mar-Jun	4.9	4.5	2.0	7.0	4.9
Feb	0.3	0.3	0.2	0.2	0.0
Jan	0.2	-0.1	0.4	-0.4	0.1
AE ∆% Jan-Feb	3.0	1.2	3.7	-1.2	0.6
2014
Dec	0.3	0.3	0.5	-0.1	0.2
Nov	0.5	0.5	0.6	0.3	0.4
Oct	0.5	0.4	0.4	0.5	0.4
Sep	0.2	0.2	0.1	0.2	0.1
AE ∆% Sep-Dec	4.6	4.3	4.9	2.7	3.3
Aug	0.4	0.4	0.4	0.6	0.6
Jul	0.3	0.2	0.1	0.2	0.1
Jun	0.5	0.5	0.4	0.6	0.4
May	0.4	0.4	0.2	0.3	0.1
Apr	0.3	0.3	0.1	0.4	0.2
AE ∆% Apr-Aug	4.7	4.4	2.9	5.2	3.4
Mar	0.5	0.5	0.3	0.6	0.4
Feb	0.6	0.6	0.5	0.7	0.7
Jan	0.6	0.5	0.4	-0.4	-0.5
AE ∆% Jan-Mar	7.0	6.6	4.9	3.6	2.4
2013
Dec	0.3	0.2	0.1	0.3	0.1
AE ∆% Dec	3.7	2.4	1.2	3.7	1.2
Nov	0.4	0.4	0.3	0.5	0.5
AE ∆% Nov	4.9	4.9	3.7	6.2	6.2
Oct	-0.1	-0.2	-0.3	0.3	0.2
AE ∆% Oct	-1.2	-2.4	-3.5	3.7	2.4
Sep	0.3	0.4	0.3	0.6	0.5
Aug	0.4	0.4	0.3	0.1	0.0
Jul	0.0	0.1	0.0	0.2	0.1
Jun	0.4	0.4	0.2	0.4	0.2
May	0.6	0.6	0.5	0.4	0.2
Apr	0.1	0.0	0.1	-0.1	0.0
AE ∆% Apr-Sep	3.7	3.9	2.8	3.2	2.0
Mar	0.2	0.1	0.2	0.0	0.1
Feb	0.5	0.6	0.2	0.5	0.1
AE ∆% Feb-Mar	4.3	4.3	2.4	3.0	1.2
Jan	-5.4	-6.3 (0.1)^a	-6.4	0.4	0.3
AE ∆% Jan	-48.6	-54.2 (3.7)^a	-54.8	4.9	3.7
2012
∆% Jan-Dec 2012***	8.5	8.6	6.8	3.3	2.3
Dec	2.6	2.6 (0.3)*	2.6 (0.5)*	0.2	0.2
Nov	1.2	1.2 (0.6)*	1.3 (0.9)*	0.2	0.3
AE ∆% Nov-Dec	25.3	25.3 (5.5)*	26.0 (8.7)*	2.4	3.0
Oct	0.9	0.9	0.6	0.1	-0.2
Sep	0.9	0.8	0.5	0.7	0.4
Aug	0.2	0.2	-0.2	0.2	-0.2
AE ∆% Aug-Oct	8.3	7.9	3.7	4.1	0.0
Jul	-0.2	-0.2	-0.3	0.3	0.3
Jun	0.2	0.2	0.2	-0.1	-0.1
May	0.0	0.0	0.1	-0.1	0.0
Apr	0.4	0.4	0.3	0.3	0.1
AE ∆% Apr-Jul	1.2	1.2	0.9	1.2	0.9
Mar	0.5	0.5	0.3	0.1	-0.1
Feb	0.8	0.8	0.6	0.6	0.4
Jan	0.7	1.0	0.7	0.7	0.4
AE ∆% Jan-Mar	8.3	9.6	4.9	4.3	2.1
2011
∆% Jan-Dec 2011*	5.1	4.1	1.6	3.7	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	0.2	0.2	-0.1	0.7	0.3
Feb	0.5	0.6	0.3	0.4	0.1
Jan	1.6	0.7	0.5	0.4	0.1
AE ∆% Jan-Apr	7.7	5.2	1.2	5.9	1.5
2010
∆% Jan-Dec 2010**	5.2	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	1.9	1.2	1.5	1.0
IVQ2010 AE ∆%	7.9	7.9	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 minus 1.4 percent in Oct 2013 and minus 2.4 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 4.9 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 2.1 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 3.9 percent in the 12 months ending in Oct 2015.

RPCE growth decelerated less sharply from close to 3 percent in IVQ 2010 to 2.7 percent in Oct 2015. 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 4.8 to 9.9 percent from Oct 2014 to Oct 2015. RPCEG growth rates have fallen from around 5 percent late in 2010 and early Jan-Feb 2011 to the range of 3.1 to 5.3 percent from Oct 2014 to Oct 2015. In Oct 2015, RPCEG increased 3.7 percent in 12 months and RPCEGD 5.6 percent while RPCES increased 2.2 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
2015
Oct	3.9	2.7	3.7	5.6	2.2
Sep	3.9	3.1	4.0	6.0	2.6
Aug	3.7	3.0	3.6	4.9	2.8
Jul	3.7	3.3	4.0	6.0	3.0
Jun	3.4	3.2	3.5	4.8	3.0
May	3.5	3.5	4.4	6.9	3.1
Apr	3.5	3.1	3.1	6.0	3.0
Mar	3.0	3.0	3.4	5.6	2.8
Feb	3.6	3.2	3.2	6.5	3.1
Jan	4.0	3.8	5.3	9.9	3.1
2014
Dec	4.0	3.2	4.0	8.1	2.8
Nov	3.5	3.2	4.2	7.4	2.7
Oct	3.2	3.2	3.8	6.9	3.0
Sep	2.5	3.0	3.3	7.0	2.8
Aug	2.6	3.4	4.7	7.8	2.7
Jul	2.5	2.7	3.2	6.1	2.4
Jun	2.4	2.7	3.5	6.2	2.3
May	2.2	2.4	2.9	5.8	2.2
Apr	2.6	2.6	3.7	5.7	2.1
Mar	2.6	2.4	3.4	6.3	1.8
Feb	2.4	2.0	2.0	2.4	2.0
Jan	2.1	1.5	0.6	0.5	1.9
2013
Dec	-4.9	2.3	2.8	2.5	2.0
Nov	-2.4	2.4	3.4	5.1	1.8
Oct	-1.4	2.1	3.5	6.2	1.5
Sep	-0.5	1.8	2.9	4.0	1.2
Aug	-0.3	1.7	2.7	6.1	1.2
Jul	-0.8	1.6	3.4	6.6	0.6
Jun	-1.0	1.8	3.6	7.1	0.9
May	-1.0	1.5	3.1	6.5	0.7
Apr	-1.4	1.3	2.5	5.7	0.7
Mar	-1.2	1.4	2.6	5.5	0.8
Feb	-1.1	1.2	3.0	6.8	0.2
Jan	-0.7	1.5	3.5	7.4	0.4
2012
Dec	6.8	1.6	3.6	8.7	0.6
Nov	4.9	1.4	2.8	7.7	0.7
Oct	3.4	1.0	1.9	5.2	0.5
Sep	2.9	1.4	3.4	8.5	0.4
Aug	2.1	1.3	3.4	8.5	0.3
Jul	2.2	1.4	2.8	7.5	0.7
Jun	2.9	1.4	2.5	8.3	0.8
May	3.1	1.7	3.1	7.9	1.0
Apr	3.0	1.6	2.5	7.0	1.2
Mar	2.4	1.4	2.3	5.9	1.0
Feb	2.0	1.8	2.5	7.1	1.5
Jan	1.8	1.5	1.9	5.9	1.3
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 2015. 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 1999-2015

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 in Chart IB-2 from 1995 to 2015. 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-five 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 1995-2015

Source: US Bureau of Economic Analysis

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

Personal income and its disposition are in Table IB-3. The latest estimates and revisions have changed movements in five forms. (1) Increase in Oct 2015 of personal income by $68.1 billion or 0.4 percent and increase of disposable income of $56.7billion or 0.4 percent with increase of wages and salaries of 0.6 percent. (2) Increase of personal income of $746.1 billion from Dec 2013 to Dec 2014 or 5.2 percent while disposable income increased $603.3 billion or 4.8 percent. Wages and salaries increased $413.1 billion or 5.7 percent. (3) Decrease of personal income of $354.8 billion from Dec 2012 to Dec 2013 or by 2.4 percent and decrease of disposable income of $458.7 billion or by 3.3 percent. Wages and salaries increased $66.5 billion from Dec 2012 to Dec 2013 or by 0.9 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 $1150.5 billion or 8.5 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. (4) Increase of $656.0 billion of personal income in 2011 or by 5.1 percent with increase of wages and salaries of 2.7 percent and disposable income of 4.1 percent. (5) 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 and 11.0 percent in Dec 2012, decreasing to 4.3 percent in Dec 2013. The savings rate increased to 5.0 percent in Dec 2014, 5.3 percent in Sep 2015 and 5.6 percent in Oct 2015.

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 %
Oct 2015	15,573.8	7,952.8	1,971.9	13,601.9	5.6
Sep 2015	15,505.7	7,907.8	1,960.5	13,545.2	5.3
Change Oct 2015/ Sep 2015	68.1 ∆% 0.4	45.0 ∆% 0.6	11.4 ∆% 0.6	56.7 ∆% 0.4
Dec 2014	15,014.2	7,664.2	1,850.9	13,163.4	5.0
Change Dec 2014/Dec 2013	746.1 ∆% 5.2	413.1 ∆% 5.7	142.9 ∆% 8.4	603.3 ∆% 4.8
Dec 2013	14,268.1	7,251.1	1,708.0	12,560.1	4.3
Dec 2012	14,622.9	7,184.6	1,604.1	13,018.8	11.0
Change Dec 2013/ Dec 2012	-354.8 ∆% -2.4	66.5 ∆% 0.9	103.9 ∆% 6.5	-458.7 ∆% -3.5
Change Dec 2012/ Dec 2011	1150.5 ∆% 8.5	501.7 ∆% 7.5	120.3 ∆% 8.1	1030.2 ∆% 8.6
Dec 2011	13,472.4	6,682.9	1,483.8	11,988.6	6.4
Dec 2010	12,816.4	6,506.0	1,301.9	11,514.5	5.9
Change Dec 2011/ Dec 2010	656.0 ∆% 5.1	176.9 ∆% 2.7	181.9 ∆% 14.0	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 growth of real disposable income of 3.2 percent per year on average from 1929 to 2014 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 2014 and 1.3 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 2014 and real disposable income per capita at 0.6 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 ∆%
1929-2014	3.2
1947-1999	3.7
1999-2014	2.3
1999-2006	3.2
1980-1989	3.5
2006-2014	1.4
RDPIPC Average ∆%
1929-2014	2.0
1947-1999	2.3
1999-2014	1.3
1999-2006	2.2
1980-1989	2.6
2006-2014	0.6

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 (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 http://cmpassocregulationblog.blogspot.com/2014/07/financial-irrational-exuberance.html http://cmpassocregulationblog.blogspot.com/2014/07/world-inflation-waves-united-states.html). 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 13.3 percent and real disposable personal income at 10.9 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 11.4 percent; real personal income excluding current transfer receipts at minus 11.9 percent; and real disposable personal income at minus 15.9 percent (Table 14 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi0615.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 IQ2014, personal income grew at 6.1 percent in nominal terms and 4.7 percent in real terms excluding current transfer receipts while nominal disposable income grew at 5.6 percent and real disposable income at 4.0 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi0815.pdf). In IIQ2014, personal income grew at 5.1 percent and 2.6 percent in real terms excluding current transfers. Nominal disposable income grew at 5.2 percent and at 3.0 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi1015.pdf). In IIIQ2014, personal income grew at 4.5 percent, real personal income excluding current transfers at 2.8 percent, nominal disposable income at 3.9 percent and real disposable personal income at 2.7 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi1015.pdf). In IVQ2014, personal income grew at 5.0 percent in nominal terms and at 6.0 percent in real terms excluding current transfers while nominal disposable income grew at 4.2 percent in nominal terms and at 4.7 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi1015.pdf). In IQ2015, nominal personal income grew at 3.4 percent and at 4.3 percent in real terms excluding current transfer receipts while nominal disposable income grew at 1.9 percent and at 3.9 percent in real terms (Table 6 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi1015.pdf). In IIQ2015, nominal personal income grew at 5.3 percent and at 3.3 percent in real terms excluding current transfer receipts while nominal disposable income grew at 4.9 percent and real disposable income grew at 2.6 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi1015.pdf). In IIIQ2015, nominal personal income grew at 5.1 percent and 4.1 percent excluding transfer receipts while nominal disposable income grew at 5.1 percent and real disposable income grew at 3.9 percent (Table 6 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi1015.pdf).

Chart IB-4, US, Personal Income, Current Billions of Dollars, Quarterly Seasonally Adjusted at Annual Rates, 2007-2015

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 2015. In IVQ2012, nominal disposable personal income grew at the SAAR of 13.3 percent and real disposable personal income at 10.9 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).

Chart IB-6, US, Real Disposable Income, Billions of Chained 2009 Dollars, Quarterly Seasonally Adjusted at Annual Rates, 2007-2015

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 2015. 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 13.3 percent and real disposable personal income at 10.9 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).

Chart, IB-8, US, Real Disposable Income, Percentage Change from Preceding Period at Seasonally-Adjusted Annual Rates, 2007-2015

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 Oct 2015 at the seasonally adjusted annual rate of $15,573.8 billion, as shown in Table IB-3 above (see Table 1 at http://www.bea.gov/newsreleases/national/pi/2015/pdf/pi1015.pdf). The major portion of personal income is compensation of employees of $9,804.9 billion, or 63.0 percent of the total. Wages and salaries are $7,952.8 billion, of which $6,674,9 billion by private industries and supplements to wages and salaries of $1,852.1 billion (contributions to social insurance are $574.2 billion). In Apr 1989 (at the comparable month after the 25^th quarter of cyclical expansion), US personal income was $4,582.2 billion at SAAR (http://www.bea.gov/iTable/index_nipa.cfm). Compensation of employees was $3,117.9 billion, or 68.0 percent of the total. Wages and salaries were $2,566.8 billion of which $2,092.2 billion by private industries. Supplements to wages and salaries were $551.1 billion with employer contributions to pension and insurance funds of $358.3 billion and $192.8 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, US, Wage and Salary Disbursement, Private Industries, Quarterly, Seasonally Adjusted at Annual Rates, Billions of Dollars 2007-2015

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 2015. 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 2007-2015

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 24.8 percent from Dec 1979 to Apr 1989. In the comparable period in the current cycle from Dec 2007 to Oct 2015, real per capita disposable income increased 7.2 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	0.7	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	3.2	1.7
1/1988	20.6	2.6	7/2014	3.3	1.8
2/1988	21.2	2.6	8/2014	3.6	1.9
3/1988	21.6	2.9	9/2014	3.6	1.7
4/1988	21.9	7.4	10/2014	3.9	2.5
5/1988	22.0	3.3	11/2014	4.5	2.7
6/1988	22.3	3.9	12/2014	5.0	3.2
7/1988	22.7	4.0	1/2015	5.3	3.2
8/1988	23.0	3.8	2/2015	5.4	2.9
9/1988	23.1	4.0	3/2015	5.1	2.3
10/1988	23.6	3.9	4/2015	5.6	2.7
11/1988	23.6	3.5	5/2015	5.8	2.8
12/1988	24.2	3.2	6/2015	6.0	2.7
1/1989	24.7	3.4	7/2015	6.3	3.0
2/1989	25.0	3.2	8/2015	6.7	3.0
3/1989	25.6	3.3	9/2015	6.9	3.2
4/1989	24.8	2.4	10/2015	7.2	3.1

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 2015. 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 2007-2015

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 14.0 percent from Dec 2007 to Oct 2015 (column RDPI ∆% 12/07). In the same period, real disposable income per capita increased 7.2 percent (column RDPI-PC ∆% 12/07). The annual equivalent rate of increase of real disposable income per capita is 0.9 percent, only a fraction of 2.0 percent on average from 1929 to 2014, and 1.7 percent for real disposable income, much lower than 3.2 percent on average from 1929 to 2014.

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	3.3	0.7	2.9	0.7	0.6	2.1
6/11	4.1	0.4	2.3	1.2	0.4	1.5
12/11	5.0	0.8	1.6	1.6	0.7	0.8
6/12	7.2	0.2	2.9	3.4	0.2	2.2
10/12	7.9	0.6	3.4	3.7	0.5	2.7
11/12	9.3	1.3	4.9	5.0	1.3	4.1
12/12	12.1	2.6	6.8	7.7	2.6	6.0
6/13	6.1	0.2	-1.0	1.6	0.1	-1.7
12/13	6.7	0.1	-4.9	1.7	0.0	-5.6
1/14	7.1	0.4	2.1	2.0	0.3	1.3
2/14	7.6	0.5	2.4	2.5	0.4	1.6
3/14	8.0	0.3	2.6	2.8	0.3	1.8
4/14	8.1	0.1	2.6	2.8	0.1	1.8
5/14	8.3	0.2	2.2	2.9	0.1	1.5
6/14	8.7	0.4	2.4	3.2	0.3	1.7
7/14	8.8	0.1	2.5	3.3	0.0	1.8
8/14	9.2	0.4	2.6	3.6	0.3	1.9
9/14	9.3	0.1	2.5	3.6	0.0	1.7
10/14	9.7	0.4	3.2	3.9	0.3	2.5
11/14	10.4	0.6	3.5	4.5	0.5	2.7
12/14	10.9	0.5	4.0	5.0	0.5	3.2
1/15	11.4	0.4	4.0	5.3	0.3	3.2
2/15	11.6	0.2	3.6	5.4	0.1	2.9
3/15	11.3	-0.2	3.0	5.1	-0.3	2.3
4/15	11.9	0.5	3.5	5.6	0.5	2.7
5/15	12.1	0.2	3.5	5.8	0.2	2.8
6/15	12.4	0.2	3.4	6.0	0.2	2.7
7/15	12.8	0.4	3.7	6.3	0.3	3.0
8/15	13.3	0.4	3.7	6.7	0.3	3.0
9/15	13.6	0.3	3.9	6.9	0.2	3.2
10/15	14.0	0.4	3.9	7.2	0.3	3.1

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). Theory and evidence support the role of financial institutions in efficiency and growth (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 22-6, Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 37-44). 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). Banking was important in facilitating economic growth in historical periods (Cameron 1961, 1967, 1972; Cameron et al. 1992). Banking is also important currently because small- and medium-size business may have no other form of financing than banks in contrast with many options for larger and more mature companies that have access to capital markets. Calomiris and Haber (2014) find that broad voting rights and institutions restricting coalitions of bankers and populists ensure stable banking systems and access to credit. Summerhill (2015) finds compelling evidence that sovereign credibility is insufficient to develop financial intermediation required for economic growth in the presence of inadequate political institutions. 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 0.2 percent in the 12 months ending in Oct 2015 (http://www.bls.gov/cpi/) but rising during waves of carry trades from zero interest rates to commodity futures exposures (http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-liftoff-followed-by.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/interest-rate-policy-quagmire-world.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 2015. There was a long-term downward sloping trend from 12 percent in the early 1980s to 1.9 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 because of the “fiscal cliff” episode followed by another decline because of the pain of the opportunity cost of zero remuneration for hard-earned savings. There are multiple recent oscillations during expectations of increase or “liftoff” of the fed funds rate in the United States followed by “shallow” monetary policy.

Chart IB-14, US, Personal Savings as a Percentage of Disposable Personal Income, Quarterly, 1980-2015

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 2014. 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, 1929-2014

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 6.3 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 2.6 percent in 2005. Savings as percent of disposable personal income was 4.8 percent in 2013 while real disposable income fell 1.4 percent. The savings rate was 4.8 percent of GDP in 2014 with growth of real disposable income of 2.7 percent. The average ratio of savings as percent of disposable income fell from 9.3 percent in 1980 to 1989 to 5.3 percent on average from 2007 to 2014. Real disposable income grew on average at 3.5 percent from 1980 to 1989 and at 1.4 percent on average from 2007 to 2014.

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	-6.3
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	4.5	3.6
2005	2.6	1.5
2006	3.3	4.0
2007	2.9	2.1
2008	4.9	1.5
2009	6.1	-0.4
2010	5.6	1.0
2011	6.0	2.5
2012	7.6	3.2
2013	4.8	-1.4
2014	4.8	2.7
Average Savings Ratio
1980-1989	9.3
2007-2014	5.3
Average Yearly ∆% Real Disposable Income
1980-1989		3.5
2007-2014		1.5

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 Oct 2015. 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 5.6 percent in Nov 2011. This was followed by an upward trend with 7.6 percent in Jun 2012 but decline to 7.1 percent in Aug 2012 followed by jump to 11.0 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 11.0 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 4.6 percent. Real disposable personal income fell 6.4 percent and real disposable per capita income fell from $38,638 in Dec 2012 to $36,137 in Jan 2013 or by 6.5 percent (http://www.bea.gov/iTable/index_nipa.cfm), 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 2007-2015

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 change 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 increased to 5.6 percent in Oct 2015 with cumulative growth of real disposable income of 14.0 percent since Dec 2007 at the rate of 1.7 percent annual equivalent, which is much lower than 3.2 percent over the long term from 1929 to 2014.

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

	Personal Saving 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	7.6	7.2	0.2	2.9
Aug 2012	7.1	6.7	-0.2	2.1
Dec 2012	11.0	12.1	2.6	6.8
Jan 2013	4.6	4.9	-6.4	-0.7
Feb 2013	4.6	5.1	0.2	-1.1
Mar 2013	4.7	5.3	0.2	-1.2
Apr 2013	4.7	5.4	0.1	-1.4
May 2013	5.0	5.9	0.5	-1.0
Jun 2013	5.1	6.1	0.2	-1.0
Jul 2013	5.0	6.1	0.0	-0.8
Aug 2013	5.2	6.4	0.3	-0.3
Sep 2013	5.0	6.7	0.3	-0.5
Oct 2013	4.5	6.3	-0.3	-1.4
Nov 2013	4.4	6.6	0.3	-2.4
Dec 2013	4.3	6.7	0.1	-4.9
Jan 2014	5.1	7.1	0.4	2.1
Feb 2014	5.0	7.6	0.5	2.4
Mar 2014	4.9	8.0	0.3	2.6
Apr 2014	4.8	8.1	0.1	2.6
May 2014	4.9	8.3	0.2	2.2
Jun 2014	4.8	8.7	0.4	2.4
Jul 2014	4.8	8.8	0.1	2.5
Aug 2014	4.6	9.2	0.4	2.6
Sep 2014	4.6	9.3	0.1	2.5
Oct 2014	4.5	9.7	0.4	3.2
Nov 2014	4.6	10.4	0.6	3.5
Dec 2014	5.0	10.9	0.5	4.0
Jan 2015	5.3	11.4	0.4	4.0
Feb 2015	5.4	11.6	0.2	3.6
Mar 2015	4.9	11.3	-0.2	3.0
Apr 2015	5.1	11.9	0.5	3.5
May 2015	4.8	12.1	0.2	3.5
Jun 2015	5.0	12.4	0.2	3.4
Jul 2015	5.1	12.8	0.4	3.7
Aug 2015	5.2	13.3	0.4	3.7
Sep 2015	5.3	13.6	0.3	3.9
Oct 2015	5.6	14.0	0.4	3.9

Source: US Bureau of Economic Analysis

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

II United States Housing Collapse. Data and other information continue to provide depressed conditions in the US housing market in a longer perspective, with recent improvement at the margin. Table IIB-1 shows sales of new houses in the US at seasonally adjusted annual equivalent rate (SAAR). House sales fell in 21 of 58 months from Jan 2011 to Oct 2015 with monthly declines of 5 in 2011, 4 in 2012, 4 in 2013, 5 in 2014 and 3 in 2015. In Jan-Apr 2012, house sales increased at the annual equivalent rate of 11.8 percent and at 22.3 percent in May-Sep 2012. There was significant strength in Sep-Dec 2011 with annual equivalent rate of 48.4 percent. Sales of new houses fell 7.0 percent in Oct 2012 with increase of 9.5 percent in Nov 2012. Sales of new houses rebounded 10.8 percent in Jan 2013 with annual equivalent rate of 51.5 percent from Oct 2012 to Jan 2013 because of the increase of 10.8 percent in Jan 2013. New house sales increased at annual equivalent 9.9 percent in Feb-Mar 2013. New house sales weakened, decreasing at 2.3 percent in annual equivalent from Apr to Dec 2013 with significant volatility illustrated by decline of 18.8 percent in Jul 2013 and increase of 11.3 percent in Oct 2013. New house sales fell 1.1 percent in Dec 2013. New house sales increased 1.1 percent in Jan 2014 and fell 6.5 percent in Feb 2014 and 1.7 percent in Mar 2014. New house sales changed 0.0 percent in Apr 2014 and increased 11.5 percent in May 2014. New house sales fell 10.7 percent in Jun 2014 and decreased 1.2 percent in Jul 2014. New house sales jumped 12.7 percent in Aug 2014 and increased 1.1 percent in Sep 2014. New House sales increased 2.8 percent in Oct 2014 and fell 4.9 percent in Nov 2014. House sales fell at the annual equivalent rate of 4.6 percent in Sep-Nov 2014. New house sales increased 10.2 percent in Dec 2014 and increased 5.3 percent in Jan 2015. Sales of new houses increased 4.6 percent in Feb 2015 and fell 11.0 percent in Mar 2015. House sales increased 4.7 percent in Apr 2015. The annual equivalent rate in Dec 2014-Apr 2015 was 34.4 percent. New house sales increased 1.0 percent in May 2015 and fell 8.6 percent in Jun 2015, increasing 6.6 percent in Jul 2015. New house sales fell at annual equivalent 1.6 percent in May-Jul 2015. New house sales increased 2.6 percent in Aug 2015 and fell 12.9 percent in Sep 2015. New house sales increased 10.7 percent in Oct 2015. New house sales decreased at the annual equivalent rate of 1.1 percent Aug-Oct 2015. There are with wide monthly oscillations. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), analyze how builders have provided financial assistance to home buyers, including those short of cash and with weaker credit background, explaining the rise in new home sales and the highest gap between prices of new and existing houses. The 30-year conventional mortgage rate increased from 3.40 on Apr 25, 2013 to 4.58 percent on Aug 22, 2013 (http://www.federalreserve.gov/releases/h15/data.htm), which could also be a factor in recent weakness with improvement after the rate fell to 4.26 in Nov 2013. The conventional mortgage rate rose to 4.48 percent on Dec 26, 2013 and fell to 4.32 percent on Jan 30, 2014. The conventional mortgage rate increased to 4.37 percent on Feb 26, 2014 and 4.40 percent on Mar 27, 2014. The conventional mortgage rate fell to 4.14 percent on Apr 22, 2014, stabilizing at 4.14 on Jun 26, 2014. The conventional mortgage rate stood at 3.93 percent on Aug 20, 2015 and at 3.91 percent on Sep 17, 2015. The conventional mortgage rate was at 3.79 percent on Oct 22, 2015. The conventional mortgage rate was 3.97 percent on Nov 20, 2015. The conventional mortgage rate measured in a survey by Freddie Mac (http://www.freddiemac.com/pmms/release.html) is the “contract interest rate on commitments for fixed-rate first mortgages” (http://www.federalreserve.gov/releases/h15/data.htm).

Table IIB-1, US, Sales of New Houses at Seasonally-Adjusted (SA) Annual Equivalent Rate, Thousands and %

	SA Annual Rate Thousands	∆%
Oct 2015	495	10.7
Sep	447	-12.9
Aug	513	2.6
AE ∆% Aug-Oct		-4.2
Jul	500	6.6
Jun	469	-8.6
May	513	1.0
AE ∆% May-Jul		-6.2
Apr	508	4.7
Mar	485	-11.0
Feb	545	4.6
Jan	521	5.3
Dec 2014	495	10.2
AE ∆% Dec-Apr		34.4
Nov	449	-4.9
Oct	472	2.8
Sep	459	1.1
AE ∆% Sep-Nov		-4.6
Aug	454	12.7
Jul	403	-1.2
Jun	408	-10.7
May	457	11.5
Apr	410	0.0
Mar	410	-1.7
Feb	417	-6.5
Jan	446	1.1
AE ∆% Jan-Aug		4.6
Dec 2013	441	-1.1
Nov	446	0.5
Oct	444	11.3
Sep	399	5.0
Aug	380	1.1
Jul	376	-18.8
Jun	463	7.7
May	430	-4.7
Apr	451	0.4
AE ∆% Apr-Dec		-2.3
Mar	449	2.3
Feb	439	-0.7
AE ∆% Feb-Mar		9.9
Jan	442	10.8
Dec 2012	399	1.8
Nov	392	9.5
Oct	358	-7.0
AE ∆% Oct-Jan		51.5
Sep	385	2.7
Aug	375	1.6
Jul	369	2.5
Jun	360	-2.7
May	370	4.5
AE ∆% May-Sep		22.3
Apr	354	0.0
Mar	354	-3.3
Feb	366	9.3
Jan	335	-1.8
AE ∆% Jan-Apr		11.8
Dec 2011	341	4.0
Nov	328	3.8
Oct	316	3.9
Sep	304	1.7
AE ∆% Sep-Dec		48.4
Aug	299	1.0
Jul	296	-1.7
Jun	301	-1.3
May	305	-1.6
AE ∆% May-Aug		-10.3
Apr	310	3.3
Mar	300	11.1
Feb	270	-12.1
Jan	307	-5.8
AE ∆% Jan-Apr		-14.2
Dec 2010	326	13.6

AE: Annual Equivalent

Source: US Census Bureau

http://www.census.gov/construction/nrs/

There is additional information of the report of new house sales in Table IIB-2. The stock of unsold houses fell from rates of 6 to 7 percent of sales in 2011 to 4 to 5 percent in 2013 and 5.5 percent in Oct 2015. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), find that inventories of houses have declined as investors acquire distressed houses of higher quality. Median and average house prices oscillate. In Oct 2015, median prices of new houses sold not seasonally adjusted (NSA) decreased 8.5 percent after increasing 4.5 percent in Sep 2015. Average prices decreased 1.0 percent in Oct 2015 and increased 7.0 percent in Sep 2015. Between Dec 2010 and Oct 2015, median prices increased 16.7 percent, partly concentrated in increases of 4.5 percent in Sep 2015, 2.4 percent in Jul 2015, 14.5 percent in Oct 2014, 4.0 percent in Aug 2014, 4.0 percent in May 2014 and 5.2 percent in Mar 2014. Average prices increased 25.5 percent between Dec 2010 and Oct 2015, with increases of 7.0 percent in Sep 2015, 3.8 percent in Jul 2015 and 20.3 percent in Oct 2014. Between Dec 2010 and Dec 2012, median prices increased 7.1 percent and average prices increased 2.6 percent. Price increases concentrated in 2012 with increase of median prices of 18.2 percent from Dec 2011 to Dec 2012 and of average prices of 13.8 percent. Median prices increased 16.9 percent from Dec 2012 to Dec 2014, with increase of 14.5 percent in Oct 2014, while average prices increased 24.8 percent, with increase of 20.3 percent in Oct 2014. Robbie Whelan, writing on “New homes hit record as builders cap supply,” on May 24, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323475304578500973445311276.html?mod=WSJ_economy_LeftTopHighlights), finds that homebuilders are continuing to restrict the number of new homes for sale. Restriction of available new homes for sale increases prices paid by buyers.

Table IIB-2, US, New House Stocks and Median and Average New Homes Sales Price

	Unsold* Stocks in Equiv. Months of Sales SA %	Median New House Sales Price USD NSA	Month ∆%	Average New House Sales Price USD NSA	Month ∆%
Oct 2015	5.5	281,500	-8.5	366,000	-1.0
Sep	6.0	307,800	4.5	369,600	7.0
Aug	5.1	294,600	-0.5	345,300	1.0
Jul	5.2	296,000	2.4	341,900	3.8
Jun	5.6	289,200	0.6	329,300	-3.4
May	4.9	287,400	-1.8	340,800	1.8
Apr	4.9	292,700	-0.2	334,700	-5.1
Mar	5.1	293,400	-0.2	352,700	-0.9
Feb	4.5	293,900	0.7	355,900	0.0
Jan	4.8	292,000	-3.3	356,000	-4.7
Dec 2014	5.1	302,000	-0.2	373,500	4.1
Nov	5.6	302,700	1.1	358,800	-6.6
Oct	5.3	299,400	14.5	384,000	20.3
Sep	5.5	261,500	-10.4	319,100	-10.4
Aug	5.4	291,700	4.0	356,200	3.2
Jul	6.1	280,400	-2.3	345,200	2.1
Jun	5.8	287,000	0.5	338,100	4.5
May	5.1	285,600	4.0	323,500	-0.5
Apr	5.6	274,500	-2.8	325,100	-1.9
Mar	5.6	282,300	5.2	331,500	1.7
Feb	5.4	268,400	-0.5	325,900	-3.4
Jan	5.1	269,800	-2.1	337,300	5.0
Dec 2013	5.1	275,500	-0.6	321,200	-4.3
Nov	5.0	277,100	4.8	335,600	0.0
Oct	4.9	264,300	-2.0	335,700	4.4
Sep	5.5	269,800	5.7	321,400	3.4
Aug	5.5	255,300	-2.6	310,800	-5.8
Jul	5.4	262,200	0.9	329,900	7.8
Jun	4.1	259,800	-1.5	306,100	-2.5
May	4.5	263,700	-5.6	314,000	-6.8
Apr	4.3	279,300	8.5	337,000	12.3
Mar	4.1	257,500	-2.9	300,200	-3.9
Feb	4.2	265,100	5.4	312,500	1.8
Jan	4.0	251,500	-2.6	306,900	2.6
Dec 2012	4.5	258,300	5.4	299,200	2.9
Nov	4.6	245,000	-0.9	290,700	1.9
Oct	4.9	247,200	-2.9	285,400	-4.1
Sep	4.5	254,600	0.6	297,700	-2.6
Aug	4.6	253,200	6.7	305,500	8.2
Jul	4.6	237,400	2.1	282,300	3.9
Jun	4.8	232,600	-2.8	271,800	-3.2
May	4.7	239,200	1.2	280,900	-2.4
Apr	4.9	236,400	-1.4	287,900	1.5
Mar	4.9	239,800	0.0	283,600	3.5
Feb	4.8	239,900	8.2	274,000	3.1
Jan	5.3	221,700	1.4	265,700	1.1
Dec 2011	5.3	218,600	2.0	262,900	5.2
Nov	5.7	214,300	-4.7	250,000	-3.2
Oct	6.0	224,800	3.6	258,300	1.1
Sep	6.3	217,000	-1.2	255,400	-1.5
Aug	6.5	219,600	-4.5	259,300	-4.1
Jul	6.7	229,900	-4.3	270,300	-1.0
Jun	6.6	240,200	8.2	273,100	4.0
May	6.6	222,000	-1.2	262,700	-2.3
Apr	6.7	224,700	1.9	268,900	3.1
Mar	7.2	220,500	0.2	260,800	-0.8
Feb	8.1	220,100	-8.3	262,800	-4.7
Jan	7.3	240,100	-0.5	275,700	-5.5
Dec 2010	7.0	241,200	9.8	291,700	3.5

*Percent of new houses for sale relative to houses sold

Source: US Census Bureau

http://www.census.gov/construction/nrs/

The depressed level of residential construction and new house sales in the US is evident in Table IIB-3 providing new house sales not seasonally adjusted in Jan-Oct of various years. Sales of new houses are higher in Jan-Oct 2015 relative to Jan-Oct 2014 with increase of 15.0 percent. Sales of new houses in Jan-Oct 2015 are substantially lower than in any year between 1964 and 2014 with the exception of the years from 2009 to 2014. There are only five increases of 17.2 percent relative to Jan-Oct 2013, 37.1 percent relative to Jan-Oct 2012, 66.3 percent relative to Jan-Oct 2011, 53.8 percent relative to Jan-Oct 2010 and 32.4 percent relative to Jan-Oct 2009. Sales of new houses in Jan-Oct 2015 are lower by 0.8 percent relative to Jan-Oct 2008, 37.6 percent relative to 2007, 52.9 percent relative to 2006 and 61.4 percent relative to 2005. The housing boom peaked in 2005 and 2006 when increases in fed funds rates to 5.25 percent in Jun 2006 from 1.0 percent in Jun 2004 affected subprime mortgages that were programmed for refinancing in two or three years on the expectation that price increases forever would raise home equity. Higher home equity would permit refinancing under feasible mortgages incorporating full payment of principal and interest (Gorton 2009EFM; see other references in http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Sales of new houses in Jan-Oct 2015 relative to the same period in 2004 fell 58.6 percent and 54.2 percent relative to the same period in 2003. Similar percentage declines are also observed for 2015 relative to years from 2000 to 2004. Sales of new houses in Jan-Oct 2015 fell 25.3 per cent relative to the same period in 1995. The population of the US was 179.3 million in 1960 and 281.4 million in 2000 (Hobbs and Stoops 2002, 16). Detailed historical census reports are available from the US Census Bureau at (http://www.census.gov/population/www/censusdata/hiscendata.html). The US population reached 308.7 million in 2010 (http://2010.census.gov/2010census/data/). The US population increased by 129.4 million from 1960 to 2010 or 72.2 percent. The final row of Table IIB-3 reveals catastrophic data: sales of new houses in Jan-Oct 2015 of 429 thousand units are lower by 12.4 percent relative to 490 thousand units of houses sold in Jan-Oct 1963, the first year when data become available. The civilian noninstitutional population increased from 122.416 million in 1963 to 247.947 million in 2014, or 102.5 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

Table IIB-3, US, Sales of New Houses Not Seasonally Adjusted, Thousands and %

	Not Seasonally Adjusted Thousands
Jan-Oct 2015	429
Jan-Oct 2014	373
∆% Jan-Oct 2015/Jan-Oct 2014	15.0
Jan-Oct 2013	366
∆% Jan-Oct 2015/Jan-Oct 2013	17.2
Jan-Oct 2012	313
∆% Jan-Oct 2015/Jan-Oct 2012	37.1
Jan-Oct 2011	258
∆% Jan-Oct 2015/Jan-Oct 2011	66.3
Jan-Oct 2010	279
∆% Jan-Oct 2015/ Jan-Oct 2010	53.8
Jan-Oct 2009	324
∆% Jan-Oct 2015/ Jan-Oct 2009	32.4
Jan-Oct 2008	432
∆% Jan-Oct 2015/ Jan-Oct 2008	-0.7
Jan-Oct 2007	687
∆% Jan-Oct 2015/ Jan-Oct 2007	-37.6
Jan-Oct 2006	910
∆% Jan-Oct 2015/Jan-Oct 2006	-52.9
Jan-Oct 2005	1,110
∆% Jan-Oct 2015/Jan-Oct 2005	-61.4
Jan-Oct 2004	1036
∆% Jan-Oct 2015/Jan-Oct 2004	-58.6
Jan-Oct 2003	937
∆% Jan-Oct 2015/ Jan-Oct 2003	-54.2
Jan-Oct 2002	829
∆% Jan-Oct 2015/ Jan-Oct 2002	-48.3
Jan-Oct 2001	776
∆% Jan-Oct 2015/ Jan-Oct 2001	-44.7
Jan-Oct 2000	749
∆% Jan-Oct 2015/ Jan-Oct 2000	-42.7
Jan-Oct 1995	574
∆% Jan-Oct 2015/ Jan-Oct 1995	-25.3
Jan-Oct 1963	490
∆% Jan-Oct 2015/ Jan-Oct 1963	-12.4

*Computed using unrounded data

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Table IIB-4 provides the entire available annual series of new house sales from 1963 to 2014. The revised level of 306 thousand new houses sold in 2011 is the lowest since 560 thousand in 1963 in the 48 years of available data while the level of 368 thousand in 2012 is only higher than 323 thousand in 2010. The level of sales of new houses of 437 thousand in 2014 is the lowest from 1963 to 2009 with exception of 412 thousand in 1982 and 436 thousand in 1981. The population of the US increased 129.4 million from 179.3 million in 1960 to 308.7 million in 2010, or 72.2 percent. The civilian noninstitutional population of the US increased from 122.416 million in 1963 to 247.947 million in 2014 or 102.5 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

The civilian noninstitutional population is the universe of the labor force. In fact, there is no year from 1963 to 2013 in Table IIA-4 with sales of new houses below 400 thousand with the exception of the immediately preceding years of 2009, 2010, 2011 and 2012.

Table IIB-4, US, New Houses Sold, NSA, Thousands

Period	Sold During Period
1963	560
1964	565
1965	575
1966	461
1967	487
1968	490
1969	448
1970	485
1971	656
1972	718
1973	634
1974	519
1975	549
1976	646
1977	819
1978	817
1979	709
1980	545
1981	436
1982	412
1983	623
1984	639
1985	688
1986	750
1987	671
1988	676
1989	650
1990	534
1991	509
1992	610
1993	666
1994	670
1995	667
1996	757
1997	804
1998	886
1999	880
2000	877
2001	908
2002	973
2003	1,086
2004	1,203
2005	1,283
2006	1,051
2007	776
2008	485
2009	375
2010	323
2011	306
2012	368
2013	429
2014	437

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-1 of the US Bureau of the Census shows the sharp decline of sales of new houses in the US. Sales rose temporarily until about mid 2010 but then declined to a lower plateau followed by increase and stability.

Chart IIB-1, US, New One-Family Houses Sold in the US, SAAR (Seasonally Adjusted Annual Rate)

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr051.html

Percentage changes and average rates of growth of new house sales for selected periods are shown in Table IIB-5. The percentage change of new house sales from 1963 to 2014 is minus 22.0 percent. Between 1991 and 2001, sales of new houses rose 78.4 percent at the average yearly rate of 6.0 percent. Between 1995 and 2005 sales of new houses increased 92.4 percent at the yearly rate of 6.8 percent. There are similar rates in all years from 2000 to 2005. The boom in housing construction and sales began in the 1980s and 1990s. The collapse of real estate culminated several decades of housing subsidies and policies to lower mortgage rates and borrowing terms (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 42-8). Sales of new houses sold in 2014 fell 34.5 percent relative to the same period in 1995 and 65.9 percent relative to 2005.

Table IIB-5, US, Percentage Change and Average Yearly Rate of Growth of Sales of New One-Family Houses

	∆%	Average Yearly % Rate
1963-2014	-22.0	NA
1991-2001	78.4	6.0
1995-2005	92.4	6.8
2000-2005	46.3	7.9
1995-2014	-34.5	NA
2000-2014	-50.2	NA
2005-2014	-65.9	NA

NA: Not Applicable

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-2 of the US Bureau of the Census provides the entire monthly sample of new houses sold in the US between Jan 1963 and Oct 2015 without seasonal adjustment. The series is almost stationary until the 1990s. There is sharp upward trend from the early 1990s to 2005-2006 after which new single-family houses sold collapse to levels below those in the beginning of the series.

Chart IIB-2, US, New Single-family Houses Sold, NSA, 1963-2015

Source: US Census Bureau

http://www.census.gov/construction/nrs/

The available historical annual data of median and average prices of new houses sold in the US between 1963 and 2014 is provided in Table IIB-6. On a yearly basis, median and average prices reached a peak in 2007 and then fell substantially. There is recovery in 2012-2014.

Table IIB-6, US, Median and Average Prices of New Houses Sold, Annual Data

Period	Median	Average
1963	$18,000	$19,300
1964	$18,900	$20,500
1965	$20,000	$21,500
1966	$21,400	$23,300
1967	$22,700	$24,600
1968	$24,700	$26,600
1969	$25,600	$27,900
1970	$23,400	$26,600
1971	$25,200	$28,300
1972	$27,600	$30,500
1973	$32,500	$35,500
1974	$35,900	$38,900
1975	$39,300	$42,600
1976	$44,200	$48,000
1977	$48,800	$54,200
1978	$55,700	$62,500
1979	$62,900	$71,800
1980	$64,600	$76,400
1981	$68,900	$83,000
1982	$69,300	$83,900
1983	$75,300	$89,800
1984	$79,900	$97,600
1985	$84,300	$100,800
1986	$92,000	$111,900
1987	$104,500	$127,200
1988	$112,500	$138,300
1989	$120,000	$148,800
1990	$122,900	$149,800
1991	$120,000	$147,200
1992	$121,500	$144,100
1993	$126,500	$147,700
1994	$130,000	$154,500
1995	$133,900	$158,700
1996	$140,000	$166,400
1997	$146,000	$176,200
1998	$152,500	$181,900
1999	$161,000	$195,600
2000	$169,000	$207,000
2001	$175,200	$213,200
2002	$187,600	$228,700
2003	$195,000	$246,300
2004	$221,000	$274,500
2005	$240,900	$297,000
2006	$246,500	$305,900
2007	$247,900	$313,600
2008	$232,100	$292,600
2009	$216,700	$270,900
2010	$221,800	$272,900
2011	$227,200	$267,900
2012	$245,200	$292,200
2013	$268,900	$324,500
2014	$282,800	$345,800

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Percentage changes of median and average prices of new houses sold in selected years are shown in Table IIB-7. Prices rose sharply between 2000 and 2005. In fact, prices in 2014 are higher than in 2000. Between 2006 and 2014, median prices of new houses sold increased 14.7 percent and average prices increased 13.0 percent. Between 2013 and 2014, median prices increased 5.2 percent and average prices increased 6.6 percent.

Table IIB-7, US, Percentage Change of New Houses Median and Average Prices, NSA, ∆%

	Median New Home Sales Prices ∆%	Average New Home Sales Prices ∆%
∆% 2000 to 2003	15.4	19.0
∆% 2000 to 2005	42.5	43.5
∆% 2000 to 2014	67.7	66.8
∆% 2005 to 2014	17.4	16.4
∆% 2000 to 2006	45.9	47.8
∆% 2006 to 2014	14.7	13.0
∆% 2009 to 2014	30.5	27.6
∆% 2010 to 2014	27.5	26.7
∆% 2011 to 2014	24.5	29.1
∆% 2012 to 2014	15.3	18.3
∆% 2013 to 2014	5.2	6.6

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-3 of the US Census Bureau provides the entire series of new single-family sales median prices from Jan 1963 to Oct 2015. There is long-term sharp upward trend with few declines until the current collapse. Median prices increased sharply during the Great Inflation of the 1960s and 1970s and paused during the savings and loans crisis of the late 1980s and the recession of 1991. Housing subsidies throughout the 1990s caused sharp upward trend of median new house prices that accelerated after the fed funds rate of 1 percent from 2003 to 2004. There was sharp reduction of prices after 2006 with recovery recently toward earlier prices.

Chart IIB-3, US, Median Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1963-2015

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-4 of the US Census Bureau provides average prices of new houses sold from the mid-1970s to Oct 2015. There is similar behavior as with median prices of new houses sold in Chart IIB-3. The only stress occurred in price pauses during the savings and loans crisis of the late 1980s and the collapse after 2006 with recent recovery.

Chart IIB-4, US, Average Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1975-2015

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-5 of the Board of Governors of the Federal Reserve System provides the rate for the 30-year conventional mortgage, the yield of the 30-year Treasury bond and the rate of the overnight federal funds rate, monthly, from 1954 to 2015. All rates decline throughout the period from the Great Inflation of the 1970s through the following Great Moderation and until currently. In Apr 1971, the fed funds rate was 4.15 percent and the conventional mortgage rate 7.31 percent. In November 2012, the fed funds rate was 0.16 percent, the yield of the 30-year Treasury 2.80 percent and the conventional mortgage rate 3.35. The final segment shows an increase in the yield of the 30-year Treasury to 3.61 percent in July 2013 with the fed funds rate at 0.09 percent and the conventional mortgage at 4.37 percent. The final data point shows marginal decrease of the conventional mortgage rate to 3.80 percent in Oct 2015 with the yield of the 30-year Treasury bond at 2.89 percent and overnight rate on fed funds at 0.12 percent. The recent increase in interest rates if sustained could affect the US real estate market. Shayndi Raice and Nick Timiraos, writing on “Banks cut as mortgage boom ends,” on Jan 9, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303754404579310940019239208), analyze the drop in mortgage applications to a 13-year low, as measured by the Mortgage Bankers Association. Nick Timiraos, writing on “Demand for home loans plunges,” on Apr 24, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304788404579522051733228402?mg=reno64-wsj), analyzes data in Inside Mortgage Finance that mortgage lending of $235 billion in IQ2014 is 58 percent lower than a year earlier and 23 percent below IVQ2013. Mortgage lending collapsed to the lowest level in 14 years. In testimony before the Committee on the Budget of the US Senate on May 8, 2004, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm): “One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.”

Chart IIB-5, US, Thirty-year Conventional Mortgage, Thirty-year Treasury Bond and Overnight Federal Funds Rate, Monthly, 1954-2015

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

Table IIB-8 provides the monthly data in Chart IIB-5 from Dec 2012 to Sep 2015. While the fed funds rate fell from 0.16 percent in Dec 2012 to 0.07 percent in Jan 2014, the yield of the constant maturity 30-year Treasury bond rose from 2.88 percent in Dec 2012 to 3.77 percent in Jan 2014 and the conventional mortgage rate increased from 3.35 percent in Dec 2012 to 4.43 percent in Jan 2014. In Oct 2015, the fed funds rate stabilized at 0.12 percent with decrease to 2.89 percent of the 30-year yield and decrease at 3.80 percent of the conventional mortgage rate.

Table IIB-8, US, Fed Funds Rate, Thirty Year Treasury Bond and Conventional Mortgage Rate, Monthly, Percent per Year, Dec 2012 to Oct 2015

	Fed Funds Rate	Yield of Thirty Year Constant Maturity Bond	Conventional Mortgage Rate
2012-12	0.16	2.88	3.35
2013-01	0.14	3.08	3.41
2013-02	0.15	3.17	3.53
2013-03	0.14	3.16	3.57
2013-04	0.15	2.93	3.45
2013-05	0.11	3.11	3.54
2013-06	0.09	3.40	4.07
2013-07	0.09	3.61	4.37
2013-08	0.08	3.76	4.46
2013-09	0.08	3.79	4.49
2013-10	0.09	3.68	4.19
2013-11	0.08	3.80	4.26
2013-12	0.09	3.89	4.46
2014-01	0.07	3.77	4.43
2014-02	0.07	3.66	4.30
2014-03	0.08	3.62	4.34
2014-04	0.09	3.52	4.34
2014-05	0.09	3.39	4.19
2014-06	0.1	3.42	4.16
2014-07	0.09	3.33	4.13
2014-08	0.09	3.20	4.12
2014-09	0.09	3.26	4.16
2014-10	0.09	3.04	4.04
2014-11	0.09	3.04	4.00
2014-12	0.12	2.83	3.86
2015-01	0.11	2.46	3.71
2015-02	0.11	2.57	3.71
2015-03	0.11	2.63	3.77
2015-04	0.12	2.59	3.67
2015-05	0.12	2.96	3.84
2015-06	0.13	3.11	3.98
2015-07	0.13	3.07	4.05
2015-08	0.14	2.86	3.91
2015-09	0.14	2.95	3.89
2015-10	0.12	2.89	3.80

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

IIB2 United States House Prices. The Federal Housing Finance Agency (FHFA), which regulates Fannie Mae and Freddie Mac, provides the FHFA House Price Index (HPI) that “is calculated using home sales price information from Fannie Mae and Freddie Mac-acquired mortgages” (http://fhfa.gov/webfiles/24216/q22012hpi.pdf 1). The Federal Housing Finance Agency (FHFA), which regulates Fannie Mae and Freddie Mac, provides the FHFA House Price Index (HPI) that “is calculated using home sales price information from Fannie Mae and Freddie Mac-acquired mortgages” (http://fhfa.gov/webfiles/24216/q22012hpi.pdf 1). Table IIA2-1 provides the FHFA HPI for purchases only, which shows behavior similar to that of the Case-Shiller index but with lower magnitudes. House prices catapulted from 2000 to 2003, 2005 and 2006. From IVQ2000 to IVQ2006, the index for the US as a whole rose 55.0 percent, with 62.1 percent for New England, 72.0 percent for Middle Atlantic, 71.2 percent for South Atlantic but only by 33.1 percent for East South Central. Prices fell relative to 2014 for the US and all regions from 2006 with exception of increase of 2.6 percent for East South Central. Prices for the US increased 4.9 percent in IVQ2014 relative to IVQ2013 and 12.9 percent from IVQ2012 to IVQ2014. From IVQ2000 to IVQ2014, prices rose for the US and the four regions in Table IIA2-1.

Table IIA2-1, US, FHFA House Price Index Purchases Only NSA ∆%

	United States	New England	Middle Atlantic	South Atlantic	East South Central
IVQ2000 to IVQ2003	24.0	40.6	35.8	25.9	11.0
IVQ2000 to IVQ2005	50.5	65.0	67.6	62.9	25.4
IVQ2000 to IVQ2006	55.0	62.1	72.0	71.2	33.1
IVQ2005 to IVQ2014	-1.5	-8.7	-2.3	-7.4	8.9
IVQ2006 to IVQ2014	-4.4	-7.1	-4.8	-11.9	2.6
IVQ2007 to IVQ2014	-1.9	-5.1	-5.0	-8.6	0.7
IVQ2011 to IVQ2014	18.9	7.3	6.9	19.9	11.8
IVQ2012 to IVQ2014	12.9	6.8	5.7	13.8	8.6
IVQ2013 to IVQ2014	4.9	2.5	2.2	5.1	4.2
IVQ2000 to IVQ2014	48.3 144.27	50.6 138.40	63.7 127.30	50.9 140.28	36.6 146.07

Source: Federal Housing Finance Agency

http://www.fhfa.gov/KeyTopics/Pages/House-Price-Index.aspx

Data of the FHFA HPI for the remaining US regions are in Table IIA2-2. Behavior is not very different from that in Table IIA2-1 with the exception of East North Central. House prices in the Pacific region doubled between 2000 and 2006. Although prices of houses declined sharply from 2005 and 2006 to 2014 with exception of West South Central and West North Central, there was still appreciation relative to 2000.

Table IIA2-2, US, FHFA House Price Index Purchases Only NSA ∆%

	West South Central	West North Central	East North Central	Mountain	Pacific
IVQ2000 to IVQ2003	11.1	18.3	14.7	18.9	44.6
IVQ2000 to IVQ2005	23.9	31.0	23.8	58.0	107.7
IVQ2000 to IVQ2006	31.6	33.7	23.7	68.6	108.7
IVQ2005 to IVQ2014	26.6	4.7	-5.4	-2.6	-14.7
IVQ2006 to IVQ2014	19.1	2.6	-5.4	-8.7	-15.1
IVQ2007 to IVQ2014	15.2	3.2	-2.1	-5.6	-6.0
IVQ2011 to IVQ2014	18.1	13.5	14.2	32.9	37.6
IVQ2012 to IVQ2014	12.1	8.9	11.1	17.9	24.4
IVQ2013 to IVQ2014	5.9	4.0	4.6	5.5	7.3
IVQ2000 to IVQ2014	56.8 145.53	37.1 158.59	17.1 155.13	53.9 172.46	77.1 132.21

Source: Federal Housing Finance Agency

http://www.fhfa.gov/KeyTopics/Pages/House-Price-Index.aspx

Monthly and 12-month percentage changes of the FHFA House Price Index are in Table IIA2-3. Percentage monthly increases of the FHFA index were positive from Apr to Jul 2011 with exception of declines in May and Aug 2011 while 12 months percentage changes improved steadily from around minus 6 percent in Mar to May 2011 to minus 4.4 percent in Jun 2011. The FHFA house price index fell 0.5 percent in Oct 2011 and fell 3.0 percent in the 12 months ending in Oct 2011. There was significant recovery in Nov 2012 with increase in the house price index of 0.4 percent and reduction of the 12-month rate of decline to 2.3 percent. The house price index rose 0.34 percent in Dec 2011 and the 12-month percentage change improved to minus 1.2 percent. There was further improvement with revised change of minus 0.1 percent in Jan 2012 and decline of the 12-month percentage change to minus 1.1 percent. The index improved to positive change of 0.1 percent in Feb 2012 and increase of 0.2 percent in the 12 months ending in Feb 2012. There was strong improvement in Mar 2012 with gain in prices of 1.0 percent and 2.2 percent in 12 months. The house price index of FHFA increased 0.6 percent in Apr 2012 and 2.7 percent in 12 months and improvement continued with increase of 0.6 percent in May 2012 and 3.6 percent in the 12 months ending in May 2012. Improvement consolidated with increase of 0.4 percent in Jun 2012 and 3.6 percent in 12 months. In Jul 2012, the house price index increased 0.2 percent and 3.5 percent in 12 months. Strong increase of 0.5 percent in Aug 2012 pulled the 12-month change to 4.2 percent. There was another increase of 0.7 percent in Oct and 5.3 percent in 12 months followed by increase of 0.5 percent in Nov 2012 and 5.5 percent in 12 months. The FHFA house price index increased 0.8 percent in Jan 2013 and 6.4 percent in 12 months. Improvement continued with increase of 0.5 percent in Apr 2013 and 7.2 percent in 12 months. In May 2013, the house price indexed increased 0.7 percent and 7.3 percent in 12 months. The FHFA house price index increased 0.6 percent in Jun 2013 and 7.6 percent in 12 months. In Jul 2013, the FHFA house price index increased 0.7 percent and 8.2 percent in 12 months. Improvement continued with increase of 0.5 percent in Aug 2013 and 8.1 percent in 12 months. In Sep 2013, the house price index increased 0.5 percent and 8.1 percent in 12 months. The house price index increased 0.5 percent in Oct 2013 and 7.9 percent in 12 months. In Nov 2013, the house price index changed 0.0 percent and increased 7.3 percent in 12 months. The house price index rose 0.6 percent in Dec 2013 and 7.5 percent in 12 months. Improvement continued with increase of 0.6 percent in Jan 2014 and 7.3 percent in 12 months. In Feb 2014, the house price index increased 0.4 percent and 7.1 percent in 12 months. The house price index increased 0.5 percent in Mar 2014 and 6.4 percent in 12 months. In Apr 2014, the house price index increased 0.2 percent and increased 6.0 percent in 12 months. The house price index increased 0.3 percent in May 2014 and 5.5 percent in 12 months. In Jun 2014, the house price index increased 0.4 percent and 5.3 percent in 12 months. The house price index increased 0.3 percent in Jul 2014 and 4.9 percent in 12 months. In Sep 2014, the house price index increased 0.1 percent and increased 4.6 percent in 12 months. The house price index increased 0.6 percent in Oct 2014 and 4.7 percent in 12 months. In Nov 2014, the house price index increased 0.7 percent and 5.3 percent in 12 months. The house price index increased 0.7 percent in Dec 2014 and increased 5.5 percent in 12 months. In Feb 2015, the house price index increased 0.7 percent and increased 5.5 percent in 12 months. The house price index increased 0.4 percent in Mar 2015 and 5.5 percent in 12 months. In Apr 2015, the house price index increased 0.5 percent and 5.7 percent in 12 months. The house price index increased 0.5 percent in May 2015 and 5.9 percent in 12 months. House prices increased 0.2 percent in Jun 2015 and 5.6 percent in 12 months. The house price index increased 0.5 percent in Jul 2015 and increased 5.8 percent in 12 months. House prices increased 0.3 percent in Aug 2015 and increased 5.5 percent in 12 months. In Sep 2015, the house price index increased 0.8 percent and increased 6.1 percent in 12 months.

Table IIA2-3, US, FHFA House Price Index Purchases Only SA. Month and NSA 12-Month ∆%

	Month ∆% SA	12 Month ∆% NSA
Sep 2015	0.8	6.1
Aug	0.3	5.5
Jul	0.5	5.8
Jun	0.2	5.6
May	0.5	5.9
Apr	0.5	5.7
Mar	0.4	5.5
Feb	0.7	5.5
Jan	0.3	5.2
Dec 2014	0.7	5.5
Nov	0.7	5.3
Oct	0.6	4.7
Sep	0.1	4.6
Aug	0.6	5.0
Jul	0.3	4.9
Jun	0.4	5.3
May	0.3	5.5
Apr	0.2	6.0
Mar	0.5	6.4
Feb	0.4	7.1
Jan	0.6	7.3
Dec 2013	0.6	7.5
Nov	0.0	7.3
Oct	0.5	7.9
Sep	0.5	8.1
Aug	0.5	8.1
Jul	0.7	8.2
Jun	0.6	7.6
May	0.7	7.3
Apr	0.5	7.2
Mar	1.2	7.4
Feb	0.6	6.9
Jan	0.8	6.4
Dec 2012	0.5	5.5
Nov	0.4	5.3
Oct	0.7	5.3
Sep	0.5	4.1
Aug	0.5	4.2
Jul	0.2	3.5
Jun	0.4	3.6
May	0.6	3.6
Apr	0.6	2.7
Mar	1.0	2.2
Feb	0.1	0.2
Jan	-0.1	-1.1
Dec 2011	0.4	-1.2
Nov	0.4	-2.3
Oct	-0.5	-3.0
Sep	0.6	-2.4
Aug	-0.2	-3.7
Jul	0.3	-3.5
Jun	0.4	-4.4
May	-0.2	-5.9
Apr	0.2	-5.7
Mar	-0.9	-5.9
Feb	-1.1	-5.1
Jan	-0.3	-4.5
Dec 2010		-3.9
Dec 2009		-2.0
Dec 2008		-10.3
Dec 2007		-3.2
Dec 2006		2.5
Dec 2005		9.8
Dec 2004		10.2
Dec 2003		8.0
Dec 2002		7.8
Dec 2001		6.7
Dec 2000		7.2
Dec 1999		6.1
Dec 1998		5.9
Dec 1997		3.4
Dec 1996		2.8
Dec 1995		3.0
Dec 1994		2.6
Dec 1993		3.1
Dec 1992		2.4

Source: Federal Housing Finance Agency

http://www.fhfa.gov/DataTools

The bottom part of Table IIA2-3 provides 12-month percentage changes of the FHFA house price index since 1992 when data become available for 1991. Table IIA2-4 provides percentage changes and average rates of percent change per year for various periods. Between 1992 and 2014, the FHFA house price index increased 107.6 percent at the yearly average rate of 3.4 percent. In the period 1992-2000, the FHFA house price index increased 39.3 percent at the average yearly rate of 4.2 percent. The average yearly rate of price increase accelerated to 7.5 percent in the period 2000-2003, 8.5 percent in 2000-2005 and 7.5 percent in 2000-2006. At the margin, the average rate jumped to 10.0 percent in 2003-2005 and 7.4 percent in 2003-2006. House prices measured by the FHFA house price index declined 3.3 percent between 2006 and 2014 and 0.9 percent between 2005 and 2014.

Table IIA2-4, US, FHFA House Price Index, Percentage Change and Average Rate of Percentage Change per Year, Selected Dates 1992-2013

Dec	∆%	Average ∆% per Year
1992-2014	107.6	3.4
1992-2000	39.3	4.2
2000-2003	24.2	7.5
2000-2005	50.4	8.5
2003-2005	21.1	10.0
2005-2014	-0.9	NA
2000-2006	54.1	7.5
2003-2006	24.0	7.4
2006-2014	-3.3	NA

Source: Federal Housing Finance Agency

http://www.fhfa.gov/DataTools

Table IIA-4 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2008 and 2009. Total assets fell $10.4 trillion or 12.8 percent from 2007 to 2008 and $8.8 trillion or 10.8 percent to 2009. Net worth fell $10.2 trillion from 2007 to 2008 or 15.3 percent and $8.5 trillion to 2009 or 12.6 percent. Subsidies to housing prolonged over decades together with interest rates at 1.0 percent from Jun 2003 to Jun 2004 inflated valuations of real estate and risk financial assets such as equities. The increase of fed funds rates by 25 basis points until 5.25 percent in Jun 2006 reversed carry trades through exotic vehicles such as subprime adjustable rate mortgages (ARM) and world financial markets. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9).

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

	2007	2008	Change to 2008	2009	Change to 2009
A	81,232.7	70,868.9	-10,363.8	72,453.5	-8,779.2
Non FIN	28,158.3	24,796.1	-3,362.2	23,727.4	-4,430.9
RE	23,348.9	19,861.9	-3,487.0	18,771.1	-4,577.8
FIN	53,074.3	46,072.8	-7,001.5	48,726.1	-4,348.2
LIAB	14,395.0	14,278.7	-116.3	14,062.8	-332.2
NW	66,837.6	56,590.1	-10,247.5	58,390.8	-8,446.8

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

Source: Board of Governors of the Federal Reserve System. 2015. Flow of funds, balance sheets and integrated macroeconomic accounts: second quarter 2015. Washington, DC, Federal Reserve System, Sep 18. http://www.federalreserve.gov/releases/z1/

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

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

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

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

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

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

W = Y/r (1)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

According to Pinto (2008) in testimony to Congress:

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

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

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

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

Table IIA-1 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 95.5 percent in the 10-city composite of the Case-Shiller home price index, 80.5 percent in the 20-city composite and 65.8 percent in the US national home price index between Sep 2000 and Sep 2005. Prices rose around 100 percent from Sep 2000 to Sep 2006, increasing 103.0 percent for the 10-city composite, 88.2 percent for the 20-city composite and 73.9 percent in the US national index. House prices rose 39.2 percent between Sep 2003 and Sep 2005 for the 10-city composite, 34.9 percent for the 20-city composite and 29.6 percent for the US national propelled by low fed funds rates of 1.0 percent between Sep 2003 and Sep 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Sep 2004 until Sep 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Sep 2003 and Sep 2006, the 10-city index gained 44.5 percent, the 20-city index increased 40.7 percent and the US national 34.4 percent. House prices have fallen from Sep 2006 to Sep 2015 by 12.1 percent for the 10-city composite, 11.1 percent for the 20-city composite and 4.7 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Sep 2015, house prices increased 5.0 percent in the 10-city composite, increased 5.5 percent in the 20-city composite and 4.9 percent in the US national. Table IIA-6 also shows that house prices increased 78.4 percent between Sep 2000 and Sep 2015 for the 10-city composite, increased 67.3 percent for the 20-city composite and 63.8 percent for the US national. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The 10-city composite fell 12.6 percent from the peak in Jun 2006 to Sep 2015 and the 20-city composite fell 11.4 percent from the peak in Jul 2006 to Sep 2015. The US national fell 4.9 percent from the peak of the 10-city composite to Sep 2015 and 5.0 percent from the peak of the 20-city composite to Sep 2015. The final part of Table II-2 provides average annual percentage rates of growth of the house price indexes of Standard & Poor’s Case-Shiller. The average annual growth rate between Dec 1987 and Dec 2014 for the 10-city composite was 3.7 percent and 3.4 percent for the US national. Data for the 20-city composite are available only beginning in Jan 2000. House prices accelerated in the 1990s with the average rate of the 10-city composite of 5.0 percent between Dec 1992 and Dec 2000 while the average rate for the period Dec 1987 to Dec 2000 was 3.8 percent. The average rate for the US national was 3.4 percent from Dec 1987 to Dec 2014 and 3.6 percent from Dec 1987 to Dec 2000. Although the global recession affecting the US between IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly above 30 percent, the average annual growth rate of the 10-city composite between Dec 2000 and Dec 2014 was 3.7 percent while the rate of the 20-city composite was 3.2 percent and 3.1 percent for the US national.

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

	10-City Composite	20-City Composite	US National
∆% Sep 2000 to Sep 2003	40.5	33.8	27.9
∆% Sep 2000 to Sep 2005	95.5	80.5	65.8
∆% Sep 2003 to Sep 2005	39.2	34.9	29.6
∆% Sep 2000 to Sep 2006	103.0	88.2	71.9
∆% Sep 2003 to Sep 2006	44.5	40.7	34.4
∆% Sep 2005 to Sep 2015	-8.7	-7.3	-1.2
∆% Sep 2006 to Sep 2015	-12.1	-11.1	-4.7
∆% Sep 2009 to Sep 2015	24.6	24.7	17.3
∆% Sep 2010 to Sep 2015	22.9	24.2	21.4
∆% Sep 2011 to Sep 2015	27.1	28.8	25.2
∆% Sep 2012 to Sep 2015	24.5	25.1	21.5
∆% Sep 2013 to Sep 2015	9.9	10.5	9.8
∆% Sep 2014 to Sep 2015	5.0	5.5	4.9
∆% Sep 2000 to Sep 2015	78.4	67.3	63.8
∆% Peak Jun 2006 Sep 2015	-12.6		-4.9
∆% Peak Jul 2006 Sep 2015		-11.4	-5.0
Average ∆% Dec 1987-Dec 2014	3.7	NA	3.4
Average ∆% Dec 1987-Dec 2000	3.8	NA	3.6
Average ∆% Dec 1992-Dec 2000	5.0	NA	4.5
Average ∆% Dec 2000-Dec 2014	3.7	3.2	3.1

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

Price increases measured by the Case-Shiller house price indices show that “home prices continued their rise across the country over the last 12 months” (https://www.spice-indices.com/idpfiles/spice-assets/resources/public/documents/265782_cshomeprice-release-1124.pdf?force_download=true). Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the 10- and 20-city composites, as shown in Table IIA-2. In Jan 2013, the seasonally adjusted 10-city composite increased 0.8 percent and the 20-city increased 0.9 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city changed 0.0 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. With the exception of Mar through Apr 2012, house prices seasonally adjusted declined in most month for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table IIA-2. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. Without seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Aug 2011 but fell in every month from Sep 2011 to Feb 2012. The not seasonally adjusted index registers decline in Mar 2012 of 0.1 percent for the 10-city composite and is flat for the 20-city composite. Not seasonally adjusted house prices increased 1.4 percent in Apr 2012 and at high monthly percentage rates until Sep 2012. House prices not seasonally adjusted stalled from Oct 2012 to Jan 2013 and surged from Feb to Sep 2013, decelerating in Oct 2013-Feb 2014. House prices grew at fast rates in Mar 2014. The 10-city NSA index increased 0.2 percent in Sep 2015 and the 20-city increased 0.2 percent. The 10-city SA increased 0.6 percent in Sep 2015 and the 20-city composite SA increased 0.6 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

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

	10-City Composite SA	10-City Composite NSA	20-City Composite SA	20-City Composite NSA
Sep 2015	0.6	0.2	0.6	0.2
Aug	0.1	0.3	0.1	0.3
Jul	-0.2	0.6	-0.1	0.7
Jun	-0.1	0.9	-0.1	1.0
May	-0.1	1.1	-0.1	1.1
Apr	-0.1	1.1	0.0	1.2
Mar	1.0	0.8	1.0	0.9
Feb	1.1	0.5	1.1	0.5
Jan	0.7	-0.1	0.7	-0.1
Dec 2014	0.8	0.0	0.8	0.0
Nov	0.7	-0.3	0.7	-0.2
Oct	0.6	-0.1	0.7	-0.1
Sep	0.2	-0.1	0.3	-0.1
Aug	-0.1	0.1	0.0	0.2
Jul	-0.3	0.6	-0.3	0.6
Jun	-0.1	1.0	-0.1	1.0
May	-0.1	1.1	-0.1	1.1
Apr	-0.1	1.1	0.0	1.2
Mar	1.1	0.8	1.0	0.9
Feb	0.6	0.0	0.6	0.0
Jan	0.8	-0.1	0.7	-0.1
Dec 2013	0.7	-0.1	0.7	-0.1
Nov	0.9	0.0	0.9	-0.1
Oct	1.0	0.2	1.0	0.2
Sep	1.0	0.7	1.1	0.7
Aug	1.1	1.3	1.1	1.3
Jul	0.9	1.9	0.9	1.8
Jun	1.1	2.2	1.0	2.2
May	1.2	2.5	1.2	2.5
Apr	1.6	2.6	1.5	2.6
Mar	1.6	1.3	1.5	1.3
Feb	1.1	0.3	1.0	0.2
Jan	0.8	0.0	0.9	0.0
Dec 2012	1.0	0.2	0.9	0.2
Nov	0.7	-0.3	0.8	-0.2
Oct	0.7	-0.2	0.7	-0.1
Sep	0.5	0.3	0.6	0.3
Aug	0.5	0.8	0.6	0.9
Jul	0.5	1.5	0.5	1.6
Jun	1.0	2.1	1.1	2.3
May	0.9	2.2	1.0	2.4
Apr	0.4	1.4	0.5	1.4
Mar	0.3	-0.1	0.2	0.0
Feb	-0.1	-0.9	0.0	-0.8
Jan	-0.2	-1.1	-0.1	-1.0
Dec 2011	-0.5	-1.2	-0.4	-1.1
Nov	-0.5	-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	-0.2	0.1	-0.3	0.1
Jul	-0.1	0.9	-0.1	1.0
Jun	-0.1	1.0	0.0	1.2
May	-0.2	1.0	-0.3	1.0
Apr	-0.2	0.6	-0.2	0.6
Mar	-0.5	-1.0	-0.7	-1.0
Feb	-0.4	-1.3	-0.3	-1.2
Jan	-0.2	-1.1	-0.3	-1.1
Dec 2010	-0.2	-0.9	-0.2	-1.0

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

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Sunday, November 29, 2015

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