Monetary Policy Designed on “Measurable Risks” or “Unmeasurable Uncertainty,” Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth, Unresolved US Balance of Payments Deficits and Fiscal Imbalance, United States Housing, World Cyclical Slow Growth and Global Recession Risk: Part III

 

Monetary Policy Designed on “Measurable Risks” or “Unmeasurable Uncertainty,” Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth, Unresolved US Balance of Payments Deficits and Fiscal Imbalance, United States Housing, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

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

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 Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth

IIA Unresolved US Balance of Payments Deficits and Fiscal Imbalance Threatening Risk Premium on Treasury Securities

II United States Housing Collapse

IIB United States House Prices

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

IIA Unresolved US Balance of Payments Deficits and Fiscal Imbalance Threatening Risk Premium on Treasury Securities. Table IIA1-1 of the CBO (2012NovMBR, 2013BEOFeb5, 2013HBDFFeb5, 2013MEFFeb5, 2013Aug12, CBO, Feb 2014, CBO, Apr 2014, CBO, Jan 2015) shows the significant worsening of United States fiscal affairs from 2007-2008 to 2009-2012 with marginal improvement in 2013-2014 but with much higher debt relative to GDP. The deficit of $1.1 trillion in fiscal year 2012 was the fourth consecutive federal deficit exceeding one trillion dollars. All four deficits are the highest in share of GDP since 1946 (CBO 2012MBR, 2013HBDFeb5, 2013Aug12, 2013AugHBD, CBO, Jan 2015).

Table IAI-1, US, Budget Fiscal Year Totals, Billions of Dollars and % GDP

	2007	2008	2009	2010	2011	2012	2013	2014
Receipts	2568	2524	2105	2163	2304	2450	2775	3021
Outlays	2729	2983	3518	3457	3603	3537	3455	3504
Deficit	-161	-459	1413	1294	1300	1087	680	-483
% GDP	-1.1	-3.1	-9.8	-8.7	-8.5	-6.8	-4.1	-2.8

Source: CBO (2012NovMBR), CBO (2013BEOFeb5), CBO (2013HBDFeb5), CBO (2013Aug12). CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb. CBO, Historical Budget Data—April 2014, Washington DC, Congressional Budget Office, Apr 14. CBO, Historical budget data—August 2014 release. Washington, DC, Congressional Budget Office, Aug 27. CBO, Monthly budget review: summary of fiscal year 2014. Washington, DC, Congressional Budget Office, Nov 10, 2014. CBO, Historical Budget Data, January 2015 Baseline from Budget and economic outlook: 2015 to 2025. Washington, DC, CBO, Jan 26.

Table IIA1-2 provides additional information required for understanding the deficit/debt situation of the United States. The table is divided into four parts: Treasury budget in the 2015 fiscal year beginning on Oct 1, 2014 and ending on Sep 30, 2015; federal fiscal data for the years from 2009 to 2014; federal fiscal data for the years from 2005 to 2008; and Treasury debt held by the public from 2005 to 2014. Receipts increased 8.0 percent in the cumulative fiscal year 2015 ending in Aug 2015 relative to the cumulative in fiscal year 2014. Individual income taxes increased 11.8 percent relative to the same fiscal period a year earlier. Outlays increased 4.8 percent relative to a year earlier. There are also receipts, outlays, deficit and debt for fiscal years 2013 and 2014. Total revenues of the US from 2009 to 2012 accumulate to $9021 billion, or $9.0 trillion, while expenditures or outlays accumulate to $14,109 billion, or $14.1 trillion, with the deficit accumulating to $5090 billion, or $5.1 trillion. Revenues decreased 6.5 percent from $9653 billion in the four years from 2005 to 2008 to $9021 billion in the years from 2009 to 2012. Decreasing revenues were caused by the global recession from IVQ2007 (Dec) to IIQ2009 (Jun) and also by growth of only 2.2 percent on average in the cyclical expansion from IIIQ2009 to IIQ2015. In contrast, the expansion from IQ1983 to IIIQ1988 was at the average annual growth rate of 4.8 percent and at 7.8 percent from IQ1983 to IVQ1983 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuations-of-global-financial.html). Because of mediocre GDP growth, there are 25.2 million unemployed or underemployed in the United States for an effective unemployment/underemployment rate of 15.2 percent (http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuating-risk-financial-assets.html). Weakness of growth and employment creation is analyzed in II Collapse of United States Dynamism of Income Growth and Employment Creation (http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/oscillating-valuations-of-risk.html). In contrast with the decline of revenue, outlays or expenditures increased 30.2 percent from $10,839 billion, or $10.8 trillion, in the four years from 2005 to 2008, to $14,109 billion, or $14.1 trillion, in the four years from 2009 to 2012. Increase in expenditures by 30.2 percent while revenue declined by 6.5 percent caused the increase in the federal deficit from $1186 billion in 2005-2008 to $5090 billion in 2009-2012. Federal revenue was 14.9 percent of GDP on average in the years from 2009 to 2012, which is well below 17.4 percent of GDP on average from 1965 to 2014. Federal outlays were 23.3 percent of GDP on average from 2009 to 2012, which is well above 20.1 percent of GDP on average from 1965 to 2014. The lower part of Table IIA1-2 shows that debt held by the public swelled from $5803 billion in 2008 to $12,779 billion in 2014, by $6976 billion or 120.2 percent. Debt held by the public as percent of GDP or economic activity jumped from 39.3 percent in 2008 to 74.1 percent in 2014, which is well above the average of 38.2 percent from 1965 to 2014. The United States faces tough adjustment because growth is unlikely to recover, creating limits on what can be obtained by increasing revenues, while continuing stress of social programs restricts what can be obtained by reducing expenditures.

Table IIA1-2, US, Treasury Budget in Fiscal Year to Date Million Dollars

Aug	Fiscal Year 2015	Fiscal Year 2014	∆%
Receipts	2,883,250	2,669,126	8.0
Outlays	3,413,210	3,258,288	4.8
Deficit	-529,960	-589,162
Individual Income Tax	1,379,255	1,233,274	11.8
Corporation Income Tax	268,387	247,200	8.6
Social Insurance	705,156	674,338	4.6
	Receipts	Outlays	Deficit (-), Surplus (+)
$ Billions
Fiscal Year 2014	3,021	3,504	-483
% GDP	17.5	20.3	2.8
Fiscal Year 2013	2,775	3,455	-680
% GDP	16.7	20.8	-4.1
Fiscal Year 2012	2,450	3,537	-1,087
% GDP	15.2	22.0	-6.8
Fiscal Year 2011	2,304	3,603	-1,300
% GDP	15.0	23.4	-8.4
Fiscal Year 2010	2,163	3,457	-1,294
% GDP	14.6	23.4	-8.8
Fiscal Year 2009	2,105	3,518	-1,413
% GDP	14.6	24.4	-9.8
Total 2009-2012	9,021	14,109	-5,090
Average % GDP 2009-2012	14.9	23.3	-8.4
Fiscal Year 2008	2,524	2,983	-459
% GDP	17.1	20.2	-3.1
Fiscal Year 2007	2,568	2,729	-161
% GDP	17.9	19.0	-1.1
Fiscal Year 2006	2,407	2,655	-248
% GDP	17.6	19.4	-1.8
Fiscal Year 2005	2,154	2,472	-318
% GDP	16.7	19.2	-2.5
Total 2005-2008	9,653	10,839	-1,186
Average % GDP 2005-2008	17.3	19.5	-2.1
Debt Held by the Public	Billions of Dollars	Percent of GDP
2005	4,592	35.6
2006	4,829	35.3
2007	5,035	35.1
2008	5,803	39.3
2009	7,545	52.3
2010	9,019	61.0
2011	10,128	65.8
2012	11,281	70.1
2013	11,982	72.0
2014	12,779	74.1

Source: http://www.fiscal.treasury.gov/fsreports/rpt/mthTreasStmt/mthTreasStmt_home.htm CBO (2012NovMBR). CBO (2011AugBEO); Office of Management and Budget 2011. Historical Tables. Budget of the US Government Fiscal Year 2011. Washington, DC: OMB; CBO. 2011JanBEO. Budget and Economic Outlook. Washington, DC, Jan. CBO. 2012AugBEO. Budget and Economic Outlook. Washington, DC, Aug 22. CBO. 2012Jan31. Historical budget data. Washington, DC, Jan 31. CBO. 2012NovCDR. Choices for deficit reduction. Washington, DC. Nov. CBO. 2013HBDFeb5. Historical budget data—February 2013 baseline projections. Washington, DC, Congressional Budget Office, Feb 5. CBO. 2013HBDFeb5. Historical budget data—February 2013 baseline projections. Washington, DC, Congressional Budget Office, Feb 5. CBO (2013Aug12). 2013AugHBD. Historical budget data—August 2013. Washington, DC, Congressional Budget Office, Aug. CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb. CBO, Historical budget data—April 2014 release. Washington, DC, Congressional Budget Office, Apr. Congressional Budget Office, August 2014 baseline: an update to the budget and economic outlook: 2014 to 2024. Washington, DC, CBO, Aug 27, 2014. CBO, Monthly budget review: summary of fiscal year 2014. Washington, DC, Congressional Budget Office, Nov 10, 2014. CBO, The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015.

Total outlays of the federal government of the United States have grown to extremely high levels. Table IIA1-4 of the CBO (2014Feb, Apr 2014, CBO, Jan 2015) provides total outlays in 2006 and 2014. Total outlays of $3504.2 billion in 2014, or $3.5 trillion, are higher by $849.1 billion, or $0.8 trillion, relative to $2655.1 billion in 2006, or $2.7 trillion. Outlays have grown from 19.4 percent of GDP in 2006 to 20.3 percent of GDP in 2013. Outlays as percent of GDP were on average 20.1 percent from 1965 to 2014 and receipts as percent of GDP were on average 17.4 percent of GDP. It has proved extremely difficult to increase receipts above 19 percent of GDP. Mandatory outlays increased from $1411.8 billion in 2006 to $2031.8 billion in 2014, by $620 billion. The first to the final row shows that the total of social security, Medicare, Medicaid, Income Security, net interest and defense absorbs 82.3 percent of US total outlays, which is equal to 16.7 percent of GDP. There has been no meaningful constraint of spending, which is quite difficult because of the rigid structure of social programs.

Table IIA1-4, US, Central Government Total Revenue and Outlays, Billions of Dollars and Percent

	2006	% Total	2014	% Total
I TOTAL REVENUE $B	2406.9	100.0	3020.8	100.0
% GDP	17.6		17.5
Individual Income Taxes $B	1043.9		1394.6
% GDP	7.6		8.1
Corporate Income Taxes $B	353.9		320.7
% GDP	2.6		1.9
Social Insurance Taxes	837.8		1023.9
% GDP	6.1		5.9
II TOTAL OUTLAYS	2655.1		3504.2
% GDP	19.4		20.3
Discretionary	1016.6		1178.7
% GDP	7.4		6.8
Defense	520.0		595.8
% GDP	3.8		3.5
Nondefense	496.7		582.9
% GDP	3.6		3.4
Mandatory	1411.8		2031.8
% GDP	10.3		12.2
Social Security	543.9		844.9
% GDP	4.0		4.9
Medicare	376.8		599.9
% GDP	2.8		3.5
Medicaid	180.6		301.5
% GDP	1.3		1.7
Income Security	200.0		311.1
% GDP	1.5		1.8
Offsetting Receipts	-144.3		-276.3
% GDP	-1.1		-1.6
Net Interest	226.6		229.2
% GDP	1.7		1.3
Defense +Social Security          +Medicare +Medicaid +Income Security +Net interest	2047.9	77.1*	2882.4	82.3*
% GDP	15.1		16.7

*Percent of Total Outlays

Source: CBO (2013Aug12). 2013AugHBD. Historical budget data—August 2013. Washington, DC, Congressional Budget Office, Aug. CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb. CBO, Historical budget data—April 2014 release. Washington, DC, Congressional Budget Office, Apr. CBO, Historical budget data—August 2014 release. Washington, DC, Congressional Budget Office, Aug 27. CBO, Historical budget data—August 2014 release. Washington, DC, Congressional Budget Office, Aug 27. CBO, The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015.

The US is facing a major fiscal challenge. Table IIA1-5 provides federal revenues, expenditures, deficit and debt as percent of GDP and the yearly change in GDP in the more than eight decades from 1930 to 2014. The most recent period of debt exceeding 90 percent of GDP based on yearly observations in Table IIA1-5 is between 1944 and 1948. The data in Table IIA-15 use the earlier GDP estimates of the Bureau of Economic Analysis (BEA) until 1972 for the ratios to GDP of revenue, expenditures, deficit and debt and the revised CBO (2013Aug12) after 1973 that incorporate the new BEA GDP estimates (http://www.bea.gov/iTable/index_nipa.cfm). The percentage change of GDP is based on the new BEA estimates for all years. The debt/GDP ratio actually rose to 106.2 percent of GDP in 1945 and to 108.7 percent of GDP in 1946. GDP fell revised 11.6 percent in 1946, which is only matched in Table I-5 by the decline of revised 12.9 percent in 1932. Part of the decline is explained by the bloated US economy during World War II, growing at revised 17.7 percent in 1941, 18.9 percent in 1942 and 17.0 percent in 1943. Expenditures as a share of GDP rose to their highest in the series: 43.6 percent in 1943, 43.6 percent in 1944 and 41.9 percent in 1945. The repetition of 43.6 percent in 1943 and 1944 is in the original source of Table IIA1-5. During the Truman administration from Apr 1945 to Jan 1953, the federal debt held by the public fell systematically from the peak of 108.7 percent of GDP in 1946 to 61.6 percent of GDP in 1952. During the Eisenhower administration from Jan 1953 to Jan 1961, the federal debt held by the public fell from 58.6 percent of GDP in 1953 to 45.6 percent of GDP in 1960. The Truman and Eisenhower debt reductions were facilitated by diverse factors such as low interest rates, lower expenditure/GDP ratios that could be attained again after lowering war outlays and less rigid structure of mandatory expenditures than currently. There is no subsequent jump of debt as the one from revised 39.3 percent of GDP in 2008 to 65.9 percent of GDP in 2011, 70.4 percent in 2012, 72.3 percent in 2013 and 74.1 percent in 2014.

Table IIA1-5, United States Central Government Revenue, Expenditure, Deficit, Debt and GDP Growth 1930-2011

	Rev % GDP	Exp % GDP	Deficit % GDP	Debt % GDP	GDP ∆%
1930	4.2	3.4	0.8		-8.5
1931	3.7	4.3	-0.6		-6.4
1932	2.8	6.9	-4.0		-12.9
1933	3.5	8.0	-4.5		-1.3
1934	4.8	10.7	-5.9		10.8
1935	5.2	9.2	-4.0		8.9
1936	5.0	10.5	-5.5		12.9
1937	6.1	8.6	-2.5		5.1
1938	7.6	7.7	-0.1		-3.3
1939	7.1	10.3	-3.2		8.0
1940s
1940	6.8	9.8	-3.0	44.2	8.8
1941	7.6	12.0	-4.3	42.3	17.7
1942	10.1	24.3	-14.2	47.0	18.9
1943	13.3	43.6	-30.3	70.9	17.0
1944	20.9	43.6	-22.7	88.3	8.0
1945	20.4	41.9	-21.5	106.2	-1.0
1946	17.7	24.8	-7.2	108.7	-11.6
1947	16.5	14.8	1.7	96.2	-1.1
1948	16.2	11.6	4.6	84.3	4.1
1949	14.5	14.3	0.2	79.0	-0.5
1950s
1950	14.4	15.6	-1.1	80.2	8.7
1951	16.1	14.2	1.9	66.9	8.1
1952	19.0	19.4	-0.4	61.6	4.1
1953	18.7	20.4	-1.7	58.6	4.7
1954	18.5	18.8	-0.3	59.5	-0.6
1955	16.5	17.3	-0.8	57.2	7.1
1956	17.5	16.5	0.9	52.0	2.1
1957	17.7	17.0	0.8	48.6	2.1
1958	17.3	17.9	-0.6	49.2	-0.7
1959	16.2	18.8	-2.6	47.9	6.9
1960s
1960	17.8	17.8	0.1	45.6	2.6
1961	17.8	18.4	-0.6	45.0	2.6
1962	17.6	18.8	-1.3	43.7	6.1
1963	17.8	18.6	-0.8	42.4	4.4
1964	17.6	18.5	-0.9	40.0	5.8
1965	16.4	16.6	-0.2	36.7	6.5
1966	16.7	17.2	-0.5	33.7	6.6
1967	17.8	18.8	-1.0	31.8	2.7
1968	17.0	19.8	-2.8	32.2	4.9
1969	19.0	18.7	0.3	28.3	3.1
1970s
1970	18.4	18.7	-0.3	27.0	0.2
1971	16.7	18.8	-2.1	27.1	3.3
1972	17.0	18.9	-1.9	26.4	5.2
1973	17.0	18.1	-1.1	25.1	5.6
1974	17.7	18.1	-0.4	23.1	-0.5
1975	17.3	20.6	-3.3	24.5	-0.2
1976	16.6	20.8	-4.1	26.7	5.4
1977	17.5	20.2	-2.6	27.1	4.6
1978	17.5	20.1	-2.6	26.6	5.6
1979	18.0	19.6	-1.6	24.9	3.2
1980s
1980	18.5	21.1	-2.6	25.5	-0.2
1981	19.1	21.6	-2.5	25.2	2.6
1982	18.6	22.5	-3.9	27.9	-1.9
1983	17.0	22.8	-5.9	32.1	4.6
1984	16.9	21.5	-4.7	33.1	7.3
1985	17.2	22.2	-5.0	35.3	4.2
1986	17.0	21.8	-4.9	38.4	3.5
1987	17.9	21.0	-3.1	39.5	3.5
1988	17.6	20.6	-3.0	39.8	4.2
1989	17.8	20.5	-2.7	39.3	3.7
1990s
1990	17.4	21.2	-3.7	40.8	1.9
1991	17.3	21.7	-4.4	44.0	-0.1
1992	17.0	21.5	-4.5	46.6	3.6
1993	17.0	20.7	-3.8	47.8	2.7
1994	17.5	20.3	-2.8	47.7	4.0
1995	17.8	20.0	-2.2	47.5	2.7
1996	18.2	19.6	-1.3	46.8	3.8
1997	18.6	18.9	-0.3	44.5	4.5
1998	19.2	18.5	0.8	41.6	4.5
1999	19.2	17.9	1.3	38.2	4.7
2000s
2000	20.0	17.6	2.3	33.6	4.1
2001	18.8	17.6	1.2	31.4	1.0
2002	17.0	18.5	-1.5	32.6	1.8
2003	15.7	19.1	-3.3	34.5	2.8
2004	15.6	19.0	-3.4	35.5	3.8
2005	16.7	19.2	-2.5	35.6	3.3
2006	17.6	19.4	-1.8	35.3	2.7
2007	17.9	19.1	-1.1	35.2	1.8
2008	17.1	20.2	-3.1	39.3	-0.3
2009	14.6	24.4	-9.8	52.3	-2.8
2010s
2010	14.6	23.4	-8.7	60.9	2.5
2011	15.0	23.4	-8.5	65.9	1.6
2012	15.3	22.1	-6.8	70.4	2.3
2013	16.7	20.8	-4.1	72.3	2.2
2014	17.5	20.3	-2.8	74.1	2.4

Sources:

Office of Management and Budget. 2011. Historical Tables. Budget of the US Government Fiscal Year 2011. Washington, DC: OMB. CBO (2012JanBEO). CBO (2012Jan31). CBO (2012AugBEO). CBO (2013BEOFeb5). CBO2013HBDFeb5), CBO (2013Aug12). CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb. CBO, Historical budget data—April 2014 release. Washington, DC, Congressional Budget Office, Apr 14, 2014. Congressional Budget Office, August 2014 baseline: an update to the budget and economic outlook: 2014 to 2024. Washington, DC, CBO, Aug 27, 2014. CBO, Historical Budget Data, January 2015 Baseline from Budget and economic outlook: 2015 to 2025. Washington, DC, CBO, Jan 26.

Table IIA1-6 of the US, Congressional Budget Office, provides 40-Year averages of revenues and outlays before and after revision of the US National Income Accounts by the Bureau of Economic Analysis.

Table IIA1-6, US, Congressional Budget Office, 40-Year Averages of Revenues and Outlays Before and After Update of the US National Income Accounts by the Bureau of Economic Analysis, % of GDP 

	Before Update	After Update
Revenues
Individual Income Taxes	8.2	7.9
Social Insurance Taxes	6.2	6.0
Corporate Income Taxes	1.9	1.9
Other	1.6	1.6
Total Revenues	17.9	17.4
Outlays
Mandatory	10.2	9.9
Discretionary	8.6	8.4
Net Interest	2.2	2.2
Total Outlays	21.0	20.4
Deficit	-3.1	-3.0
Debt Held by the Public	39.2	38.0

Source: CBO (2013Aug12Av). Kim Kowaleski and Amber Marcellino.

Table IIA1-7 provides the latest exercise by the CBO (2013BEOFeb5, 2012AugBEO, CBO2012NovCDR, 2013Sep11, CBO Feb2014, CBO Apr2014, CBOAug2014, CBO Jan 26, 2015) of projecting the fiscal accounts of the US. Table IIA1-7 extends data back to 1995 with the projections of the CBO from 2015 to 2025, using the new estimates of the Bureau of Economic Analysis of US GDP (http://www.bea.gov/iTable/index_nipa.cfm). Budget analysis in the US uses a ten-year horizon. The significant event in the data before 2011 is the budget surpluses from 1998 to 2001, from 0.8 percent of GDP in 1998 to 2.3 percent of GDP in 2000 and 1.2 percent of GDP in 2001. Debt held by the public fell from 47.5 percent of GDP in 1995 to 31.4 percent of GDP in 2001.

Table IIA1-7, US, CBO Baseline Budget Outlook 2015-2025

	Out $B	Out % GDP	Deficit $B	Deficit % GDP	Debt	Debt % GDP
1995	1,516	20.0	-164	-2.2	3,604	47.5
1996	1,560	19.6	-107	-1.3	3,734	46.8
1997	1,601	18.9	-22	-0.3	3,772	44.5
1998	1,652	18.5	+69	+0.8	3,721	41.6
1999	1,702	17.9	+126	+1.3	3,632	38.2
2000	1,789	17.6	+236	+2.3	3,410	33.6
2001	1,863	17.6	+128	+1.2	3,320	31.4
2002	2,011	18.5	-158	-1.5	3,540	32.6
2003	2,159	19.1	-378	-3.3	3,913	34.5
2004	2,293	19.0	-413	-3.4	4,295	35.5
2005	2,472	19.2	-318	-2.5	4,592	35.6
2006	2,655	19.4	-248	-1.8	4,829	35.3
2007	2,729	19.1	-161	-1.1	5,035	35.2
2008	2,983	20.2	-459	-3.1	5,803	39.3
2009	3,518	24.4	-1,413	-9.8	7,545	52.3
2010	3,457	23.4	-1,294	-8.7	9,019	60.9
2011	3,603	23.4	-1,300	-8.5	10,128	65.9
2012	3,537	22.1	-1,087	-6.8	11,281	70.4
2013	3,455	20.8	-680	-4.1	11,983	72.3
2014	3,504	20.3	-483	-2.8	12,779	74.1
2015	3,656	20.3	-468	-2.6	13,359	74.2
2016	3,926	20.8	-467	-2.5	13,905	73.8
2017	4,076	20.7	-489	-2.5	14,466	73.4
2018	4,255	20.7	-540	-2.6	15,068	73.3
2019	4,517	21.1	-652	-3.0	15,782	73.7
2020	4,765	21.4	-739	-3.3	16,580	74.3
2021	5,018	21.6	-814	-3.5	17,451	75.0
2022	5,337	22.0	-948	-3.9	18,453	76.1
2023	5,544	21.9	-953	-3.8	19,458	76.9
2024	5,754	21.8	-951	-3.6	20,463	77.7
2025	6,117	22.3	-1,088	-4.0	21,605	78.7
2016 to 2020	21,540	21.0	-2,887	-2.8	NA	NA
2016 to 2025	49,310	21.5	-7,641	-3.3	NA	NA

Note: Out = outlays

Sources: CBO (2011AugBEO); Office of Management and Budget. 2011. Historical Tables. Budget of the US Government Fiscal Year 2011. Washington, DC: OMB; CBO. 2011JanBEO. Budget and Economic Outlook. Washington, DC, Jan. CBO. 2012AugBEO. Budget and Economic Outlook. Washington, DC, Aug 22. CBO. 2012Jan31. Historical budget data. Washington, DC, Jan 31. CBO. 2012NovCDR. Choices for deficit reduction. Washington, DC. Nov. CBO. 2013HBDFeb5. Historical budget data—February 2013 baseline projections. Washington, DC, Congressional Budget Office, Feb 5. CBO. 2013HBDFeb5. Historical budget data—February 2013 baseline projections. Washington, DC, Congressional Budget Office, Feb 5. CBO (2013Sep11). CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb. CBO, The Budget and Economic Outlook 2014 to 2024. Washington, DC, Congressional Budget Office, Feb 2014. CBO, Historical budget data—April 2014 release. Washington, DC, Congressional Budget Office, Apr 14, 2014. CBO, Updated Budget Projections: 2014 to 2024. Washington, DC, Congressional Budget Office, Apr 14, 2014.

Congressional Budget Office, August 2014 baseline: an update to the budget and economic outlook: 2014 to 2024. Washington, DC, CBO, Aug 27, 2014. CBO, The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015.

Chart IIA1-1 of the Congressional Budget Office (CBO) provides the deficits of the US as percent of GDP from 1965 to 2014 followed on the right with the projections of the CBO in Jan 2015. Large deficits from 2009 to 2013, all above the average from 1965 to 2014, doubled the debt held by the public. Fiscal adjustment is now more challenging with rigidities in revenues and expenditures. The projections of the CBO in Jan 2015 for the years from 2015 to 2025 show lower deficits in proportion of GDP in the initial years that eventually become larger than the average in the second half of the ten-year window.

Chart IIA1-1, US, Actual, Average and Projected Revenues and Outlays

Source: Congressional Budget Office

The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015.

http://www.cbo.gov/publication/49892

Table IIA1-8 provides baseline CBO projections of federal revenues, outlays, deficit and debt as percent of GDP. The adjustment depends on increasing revenues from 15.0 percent of GDP in 2011 and 17.5 percent in 2015 to 18.3 percent of GDP in 2025, which is above the average of 17.4 percent of GDP from 1965 to 2014. Outlays fall from 23.4 percent of GDP in 2011 and 20.3 percent of GDP in 2014 to 22.3 percent of GDP in 2025, which is much higher than 20.1 percent on average from 1965 to 2014. The last row of Table IIA1-8 provides the CBO estimates of averages for 1965 to 2014 of 17.4 percent for revenues/GDP, 20.4 percent for outlays/GDP and 38.0 percent for debt/GDP. The debt/GDP ratio increases to 78.7 percent of GDP in 2025. The United States faces tough adjustment of its fiscal accounts. There is an additional source of pressure on financing the current account deficit of the balance of payments.

Table IIA1-8, US, Baseline CBO Projections of Federal Government Revenues, Outlays, Deficit and Debt as Percent of GDP

	Revenues % GDP	Outlays % GDP	Deficit % GDP	Debt GDP
2011	15.0	23.4	-8.5	65.9
2012	15.3	22.1	-6.8	70.4
2013	16.7	20.8	-4.1	72.3
2014	17.5	20.3	-2.8	74.1
2015	17.7	20.3	-2.6	74.2
2016	18.4	20.8	-2.5	73.8
2017	18.2	20.7	-2.5	73.4
2018	18.1	20.7	-2.6	73.3
2019	18.1	21.1	-3.0	73.7
2020	18.0	21.4	-3.3	74.3
2021	18.1	21.6	-3.5	75.0
2022	18.1	22.0	-3.9	76.1
2023	18.2	21.9	-3.8	76.9
2024	18.2	21.8	-3.6	77.7
2025	18.3	22.3	-4.0	78.7
Total 2016-2020	18.1	21.0	-2.8	NA
Total 2016-2025	18.2	21.5	-3.3	NA
Average 1965-2014	17.4	20.1	-2.7	38.2

Source: CBO (2012AugBEO). CBO (2012NovCDR). CBO (2013BEOFeb5). CBO 2013HBDFeb5), CBO (2013Sep11), CBO (2013Aug12Av). Kim Kowaleski and Amber Marcellino. CBO, Historical Budget Data—February 2014, Washington, DC, Congressional Budget Office, Feb. CBO, The Budget and Economic Outlook 2014 to 2024. Washington, DC, Congressional Budget Office, Feb 2014. CBO, Historical budget data—April 2014 release. Washington, DC, Congressional Budget Office, Apr 14, 2014. CBO, Updated Budget Projections: 2014 to 2024. Washington, DC, Congressional Budget Office, Apr 14, 2014. CBO, The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015.

Chart IIA1-2 of the Congressional Budget Office (CBO) provides the actual federal debt as percent of GDP from 1940 to 2014 and the projected path by the CBO from 2015 to 2025. The federal debt exceeded 100 percent of GDP because of the war effort during World War II. Adjustment was swift and continuous during rapid economic growth in large part because of less rigid structures of expenditures and revenues. The jump of the federal debt from 35.1 percent of GDP in 2007 to 74.1 percent of GDP in 2014 with CBO projection of 78.7 percent of GDP in 2025 poses a major challenge of fiscal adjustment.

Chart IIA1-2, US, Federal Debt Held by the Public

Source: Congressional Budget Office

CBO, The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015.

http://www.cbo.gov/publication/49892

Table IIA1-9 provides the long-term budget outlook of the CBO for 2015, 2025 and 2040. Revenues increase from 17.7 percent of GDP in 2015 to 19.4 percent in 2040. The growing stock of debt raises net interest spending from 1.3 percent of GDP in 2015 to 3.0 percent in 2025 and 4.3 percent 2040. Total spending increases from 20.5 percent of GDP in 2015 to 25.3 percent in 2040. Federal debt held by the public rises to 103.0 percent of GDP in 2040. US fiscal affairs are in an unsustainable path with tough rigidities in spending and revenues.

Table IIA1-9, Congressional Budget Office, Long-term Budget Outlook, % of GDP

	2015	2025	2040
Revenues	17.7	18.3	19.4
Total Noninterest Spending	19.2	19.2	21.1
Social Security	4.9	5.7	6.2
Medicare	3.0	3.6	5.1
Medicaid, CHIP and Exchange Subsidies	2.2	2.5	2.9
Other	9.1	7.4	6.9
Net Interest	1.3	3.0	4.3
Total Spending	20.5	22.2	25.3
Revenues Minus Total Noninterest Spending	-1.5	-0.9	-1.6
Revenues Minus Total Spending	-2.7	-3.8	-5.9
Federal Debt Held by the Public	74.0	78.0	103.0

Source: CBO (2015Jun15). The 2015 long-term budget outlook. Washington, DC, Congressional Budget Office, Jun 16.

Chart IIA1-3 provides actual federal debt held by the public as percent of GDP from 1790 to 2014 and projected by the CBO (2013Sep17) from 2015 to 2040. The ratio of debt to GDP climbed from 42.3 percent in 1941 to a peak of 108.7 percent in 1946 because of the Second World War. The ratio of debt to GDP declined to 80.2 percent in 1950 and 66.9 percent in 1951 because of unwinding war effort, economy growing to capacity and less rigid mandatory expenditures. The ratio of debt to GDP of 74.1 percent in 2014 is the highest in the United States since 1950. The CBO (2015BEOJun17) projects the ratio of debt of GDP of the United States to reach 103.0 percent in 2040, which will be more than double the average ratio of 39.7 percent in 1973-2014. The misleading debate on the so-called “fiscal cliff” has disguised the unsustainable path of United States fiscal affairs.

Chart IIA1-3, Congressional Budget Office, Federal Debt Held by the Public, Extended Baseline Projection, % of GDP

Source: CBO (2015Jun15). The 2015 long-term budget outlook. Washington, DC, Congressional Budget Office, Jun 16.

Chart IIIA1-4 of the Congressional Budget Office provides actual and extended baseline projections of federal debt held by the public, spending and revenues. The excess of spending over revenues increases from 2.7 percent in 2015 to 3.8 percent in 2025 and 5.9 percent in 2040. Federal debt held by the public rises from 74.0 percent of GDP in 2015 to 78.0 percent of GDP in 2025 and 103 percent of GDP in 2040.

Chart IIA1-4, Congressional Budget Office, Federal Debt Held by the Public, % of GDP

Source: Source: CBO (2015Jun15). The 2015 long-term budget outlook. Washington, DC, Congressional Budget Office, Jun 16.

Chart IIA1-5 of the Congressional Budget Office provides actual and baseline projections of components of federal spending, illustrating the rigidity of US federal government spending. The combined spending in social security, Medicare and Medicaid increases from 10.1 percent of GDP in 2015 to 14.2 percent of GDP in 2040. Interest spending on a rising federal debt increases from 1.3 percent of GDP in 2015 to 4.3 percent of GDP in 2040.

Chart IIA1-5, Congressional Budget Office, Actual and Extended Baseline Projections of Components of Total Spending, % of GDP

Source: CBO (2014Jul25). The 2014 long-term budget outlook. Washington, DC, Congressional Budget Office, Jul 25.

Chart IIA1-6 of the Congressional Budget Office provides similar rigidity in the components of federal revenues. Individual income taxes increase from 8.0 percent of GDP in 2014 to 10.5 percent of GDP in 2039. Corporate income taxes decrease from 2.0 percent of GDP in 2014 to 1.8 percent of GDP in 2039. Payroll (social insurance) taxes decrease from 6.0 percent of GDP in 2014 to 5.7 percent of GDP in 2039. Other revenue sources decrease from 1.5 percent of GDP in 2014 to 1.4 percent of GDP in 2039. There is limited space for reduction of expenditures and increases of revenue.

Chart IIA1-6, Congressional Budget Office, Actual and Extended Baseline Projections of Components of Total Revenue, % of GDP

Source: CBO (2014Jul25). The 2014 long-term budget outlook. Washington, DC, Congressional Budget Office, Jul 25.

IIA2 Unresolved US Balance of Payments Deficits. The current account of the US balance of payments is provided in Table IIA2-1 for IIQ2014 and IIQ2015. The Bureau of Economic Analysis analyzes as follows (http://www.bea.gov/newsreleases/international/transactions/2015/pdf/trans215.pdf):

“The U.S. current-account deficit—a net measure of transactions between the United States and the rest of the world in goods, services, primary income (investment income and compensation), and secondary income (current transfers)— decreased to $109.7 billion (preliminary) in the second quarter of 2015 from $118.3 billion (revised) in the first quarter. The deficit decreased to 2.5 percent of current dollar gross domestic product (GDP) from 2.7 percent in the first quarter. The decrease in the current-account deficit was largely accounted for by decreases in the deficits on goods and secondary income. Increases in the surpluses on primary income and services also contributed to the decrease in the current-account deficit.”

The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US not seasonally adjusted increased from $99.3 billion in IIQ2014 to $117.3 billion in IIQ2015. The current account deficit seasonally adjusted at annual rate increased from 2.1 percent of GDP in IIQ2014 to 2.7 percent of GDP in IQ2015, decreasing to 2.5 percent of GDP in IIQ2015. The ratio of the current account deficit to GDP has stabilized below 3 percent of GDP compared with much higher percentages before the recession but is combined now with much higher imbalance in the Treasury budget (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71).

Table IIA2-1, US, Balance of Payments, Millions of Dollars NSA

	IIQ2014	IIQ2015	Difference
Goods Balance	-190,998	-189,195	-1,803
X Goods	414,005	390,400	-5.7 ∆%
M Goods	-605,003	-579,595	-4.2 ∆%
Services Balance	51,963	49,886	-2,077
X Services	175,117	175,981	0.5 ∆%
M Services	-123,154	-126,095	2.4 ∆%
Balance Goods and Services	-139,035	-139,309	274
Exports of Goods and Services and Income Receipts	838,590	803,037
Imports of Goods and Services and Income Payments	-937,920	-920,295
Current Account Balance	-99,330	-117,258	17,928
% GDP	IIQ2014	IIQ2015	IQ2015
	2.1	2.5	2.7

X: exports; M: imports

Balance on Current Account = Exports of Goods and Services – Imports of Goods and Services and Income Payments

Source: Bureau of Economic Analysis

http://www.bea.gov/international/index.htm#bop

In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):

“Imagine that fiscal policy dominates monetary policy. The fiscal authority independently sets its budgets, announcing all current and future deficits and surpluses and thus determining the amount of revenue that must be raised through bond sales and seignorage. Under this second coordination scheme, the monetary authority faces the constraints imposed by the demand for government bonds, for it must try to finance with seignorage any discrepancy between the revenue demanded by the fiscal authority and the amount of bonds that can be sold to the public. Suppose that the demand for government bonds implies an interest rate on bonds greater than the economy’s rate of growth. Then if the fiscal authority runs deficits, the monetary authority is unable to control either the growth rate of the monetary base or inflation forever. If the principal and interest due on these additional bonds are raised by selling still more bonds, so as to continue to hold down the growth of base money, then, because the interest rate on bonds is greater than the economy’s growth rate, the real stock of bonds will growth faster than the size of the economy. This cannot go on forever, since the demand for bonds places an upper limit on the stock of bonds relative to the size of the economy. Once that limit is reached, the principal and interest due on the bonds already sold to fight inflation must be financed, at least in part, by seignorage, requiring the creation of additional base money.”

The alternative fiscal scenario of the CBO (2012NovCDR, 2013Sep17) resembles an economic world in which eventually the placement of debt reaches a limit of what is proportionately desired of US debt in investment portfolios. This unpleasant environment is occurring in various European countries.

The current real value of government debt plus monetary liabilities depends on the expected discounted values of future primary surpluses or difference between tax revenue and government expenditure excluding interest payments (Cochrane 2011Jan, 27, equation (16)). There is a point when adverse expectations about the capacity of the government to generate primary surpluses to honor its obligations can result in increases in interest rates on government debt.

First, Unpleasant Monetarist Arithmetic. Fiscal policy is described by Sargent and Wallace (1981, 3, equation 1) as a time sequence of D(t), t = 1, 2,…t, …, where D is real government expenditures, excluding interest on government debt, less real tax receipts. D(t) is the real deficit excluding real interest payments measured in real time t goods. Monetary policy is described by a time sequence of H(t), t=1,2,…t, …, with H(t) being the stock of base money at time t. In order to simplify analysis, all government debt is considered as being only for one time period, in the form of a one-period bond B(t), issued at time t-1 and maturing at time t. Denote by R(t-1) the real rate of interest on the one-period bond B(t) between t-1 and t. The measurement of B(t-1) is in terms of t-1 goods and [1+R(t-1)] “is measured in time t goods per unit of time t-1 goods” (Sargent and Wallace 1981, 3). Thus, B(t-1)[1+R(t-1)] brings B(t-1) to maturing time t. B(t) represents borrowing by the government from the private sector from t to t+1 in terms of time t goods. The price level at t is denoted by p(t). The budget constraint of Sargent and Wallace (1981, 3, equation 1) is:

D(t) = {[H(t) – H(t-1)]/p(t)} + {B(t) – B(t-1)[1 + R(t-1)]} (1)

Equation (1) states that the government finances its real deficits into two portions. The first portion, {[H(t) – H(t-1)]/p(t)}, is seigniorage, or “printing money.” The second part,

{B(t) – B(t-1)[1 + R(t-1)]}, is borrowing from the public by issue of interest-bearing securities. Denote population at time t by N(t) and growing by assumption at the constant rate of n, such that:

N(t+1) = (1+n)N(t), n>-1 (2)

The per capita form of the budget constraint is obtained by dividing (1) by N(t) and rearranging:

B(t)/N(t) = {[1+R(t-1)]/(1+n)}x[B(t-1)/N(t-1)]+[D(t)/N(t)] – {[H(t)-H(t-1)]/[N(t)p(t)]} (3)

On the basis of the assumptions of equal constant rate of growth of population and real income, n, constant real rate of return on government securities exceeding growth of economic activity and quantity theory equation of demand for base money, Sargent and Wallace (1981) find that “tighter current monetary policy implies higher future inflation” under fiscal policy dominance of monetary policy. That is, the monetary authority does not permanently influence inflation, lowering inflation now with tighter policy but experiencing higher inflation in the future.

Second, Unpleasant Fiscal Arithmetic. The tool of analysis of Cochrane (2011Jan, 27, equation (16)) is the government debt valuation equation:

(M_t + B_t)/P_t = E_t∫(1/R_{t, t+τ})s_t+τdτ (4)

Equation (4) expresses the monetary, M_t, and debt, B_t, liabilities of the government, divided by the price level, P_t, in terms of the expected value discounted by the ex-post rate on government debt, R_{t, t+τ}, of the future primary surpluses s_t+τ, which are equal to T_t+τ – G_t+τ or difference between taxes, T, and government expenditures, G. Cochrane (2010A) provides the link to a web appendix demonstrating that it is possible to discount by the ex post R_{t, t+τ}. The second equation of Cochrane (2011Jan, 5) is:

M_tV(i_t, ·) = P_tY_t (5)

Conventional analysis of monetary policy contends that fiscal authorities simply adjust primary surpluses, s, to sanction the price level determined by the monetary authority through equation (5), which deprives the debt valuation equation (4) of any role in price level determination. The simple explanation is (Cochrane 2011Jan, 5):

“We are here to think about what happens when [4] exerts more force on the price level. This change may happen by force, when debt, deficits and distorting taxes become large so the Treasury is unable or refuses to follow. Then [4] determines the price level; monetary policy must follow the fiscal lead and ‘passively’ adjust M to satisfy [5]. This change may also happen by choice; monetary policies may be deliberately passive, in which case there is nothing for the Treasury to follow and [4] determines the price level.”

An intuitive interpretation by Cochrane (2011Jan 4) is that when the current real value of government debt exceeds expected future surpluses, economic agents unload government debt to purchase private assets and goods, resulting in inflation. If the risk premium on government debt declines, government debt becomes more valuable, causing a deflationary effect. If the risk premium on government debt increases, government debt becomes less valuable, causing an inflationary effect.

There are multiple conclusions by Cochrane (2011Jan) on the debt/dollar crisis and Global recession, among which the following three:

(1) The flight to quality that magnified the recession was not from goods into money but from private-sector securities into government debt because of the risk premium on private-sector securities; monetary policy consisted of providing liquidity in private-sector markets suffering stress

(2) Increases in liquidity by open-market operations with short-term securities have no impact; quantitative easing can affect the timing but not the rate of inflation; and purchase of private debt can reverse part of the flight to quality

(3) The debt valuation equation has a similar role as the expectation shifting the Phillips curve such that a fiscal inflation can generate stagflation effects similar to those occurring from a loss of anchoring expectations.

This analysis suggests that there may be a point of saturation of demand for United States financial liabilities without an increase in interest rates on Treasury securities. A risk premium may develop on US debt. Such premium is not apparent currently because of distressed conditions in the world economy and international financial system. Risk premiums are observed in the spread of bonds of highly indebted countries in Europe relative to bonds of the government of Germany.

The issue of global imbalances centered on the possibility of a disorderly correction (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). Such a correction has not occurred historically but there is no argument proving that it could not occur. The need for a correction would originate in unsustainable large and growing United States current account deficits (CAD) and net international investment position (NIIP) or excess of financial liabilities of the US held by foreigners net relative to financial liabilities of foreigners held by US residents. The IMF estimated that the US could maintain a CAD of two to three percent of GDP without major problems (Rajan 2004). The threat of disorderly correction is summarized by Pelaez and Pelaez, The Global Recession Risk (2007), 15):

“It is possible that foreigners may be unwilling to increase their positions in US financial assets at prevailing interest rates. An exit out of the dollar could cause major devaluation of the dollar. The depreciation of the dollar would cause inflation in the US, leading to increases in American interest rates. There would be an increase in mortgage rates followed by deterioration of real estate values. The IMF has simulated that such an adjustment would cause a decline in the rate of growth of US GDP to 0.5 percent over several years. The decline of demand in the US by four percentage points over several years would result in a world recession because the weakness in Europe and Japan could not compensate for the collapse of American demand. The probability of occurrence of an abrupt adjustment is unknown. However, the adverse effects are quite high, at least hypothetically, to warrant concern.”

The United States could be moving toward a situation typical of heavily indebted countries, requiring fiscal adjustment and increases in productivity to become more competitive internationally. The CAD and NIIP of the United States are not observed in full deterioration because the economy is well below trend. There are two complications in the current environment relative to the concern with disorderly correction in the first half of the past decade. In the release of Jun 14, 2013, the Bureau of Economic Analysis (http://www.bea.gov/newsreleases/international/transactions/2013/pdf/trans113.pdf) informs of revisions of US data on US international transactions since 1999:

“The statistics of the U.S. international transactions accounts released today have been revised for the first quarter of 1999 to the fourth quarter of 2012 to incorporate newly available and revised source data, updated seasonal adjustments, changes in definitions and classifications, and improved estimating methodologies.”

The BEA introduced new concepts and methods (http://www.bea.gov/international/concepts_methods.htm) in comprehensive restructuring on Jun 18, 2014 (http://www.bea.gov/international/modern.htm):

“BEA introduced a new presentation of the International Transactions Accounts on June 18, 2014 and will introduce a new presentation of the International Investment Position on June 30, 2014. These new presentations reflect a comprehensive restructuring of the international accounts that enhances the quality and usefulness of the accounts for customers and bring the accounts into closer alignment with international guidelines.”

Table IIA2-3 provides data on the US fiscal and balance of payments imbalances incorporating all revisions and methods. In 2007, the federal deficit of the US was $161 billion corresponding to 1.1 percent of GDP while the Congressional Budget Office estimates the federal deficit in 2012 at $1087 billion or 6.8 percent of GDP. The estimate of the deficit for 2013 is $680 billion or 4.1 percent of GDP. The combined record federal deficits of the US from 2009 to 2012 are $5090 billion or 31.6 percent of the estimate of GDP for fiscal year 2012 implicit in the CBO (CBO 2013Sep11) estimate of debt/GDP. The deficits from 2009 to 2012 exceed one trillion dollars per year, adding to $5.094 trillion in four years, using the fiscal year deficit of $1087 billion for fiscal year 2012, which is the worst fiscal performance since World War II. Federal debt in 2007 was $5035 billion, slightly less than the combined deficits from 2009 to 2012 of $5094 billion. Federal debt in 2012 was 70.4 percent of GDP (CBO 2015Jan26) and 72.3 percent of GDP in 2013 (http://www.cbo.gov/). This situation may worsen in the future (CBO 2013Sep17):

“Between 2009 and 2012, the federal government recorded the largest budget deficits relative to the size of the economy since 1946, causing federal debt to soar. Federal debt held by the public is now about 73 percent of the economy’s annual output, or gross domestic product (GDP). That percentage is higher than at any point in U.S. history except a brief period around World War II, and it is twice the percentage at the end of 2007. If current laws generally remained in place, federal debt held by the public would decline slightly relative to GDP over the next several years, CBO projects. After that, however, growing deficits would ultimately push debt back above its current high level. CBO projects that federal debt held by the public would reach 100 percent of GDP in 2038, 25 years from now, even without accounting for the harmful effects that growing debt would have on the economy. Moreover, debt would be on an upward path relative to the size of the economy, a trend that could not be sustained indefinitely.

The gap between federal spending and revenues would widen steadily after 2015 under the assumptions of the extended baseline, CBO projects. By 2038, the deficit would be 6½ percent of GDP, larger than in any year between 1947 and 2008, and federal debt held by the public would reach 100 percent of GDP, more than in any year except 1945 and 1946. With such large deficits, federal debt would be growing faster than GDP, a path that would ultimately be unsustainable.

Incorporating the economic effects of the federal policies that underlie the extended baseline worsens the long-term budget outlook. The increase in debt relative to the size of the economy, combined with an increase in marginal tax rates (the rates that would apply to an additional dollar of income), would reduce output and raise interest rates relative to the benchmark economic projections that CBO used in producing the extended baseline. Those economic differences would lead to lower federal revenues and higher interest payments. With those effects included, debt under the extended baseline would rise to 108 percent of GDP in 2038.”

The most recent CBO long-term budget on Jun 16, 2015, projects US federal debt at 103 percent of GDP in 2040 (CBO (2015Jun15). The 2015 long-term budget outlook. Washington, DC, Congressional Budget Office, Jun 16).

Table VI-3B, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and %

	2007	2008	2009	2010	2011	2012	2013	2014
Goods & Services	-705	-709	-384	-495	-549	-538	-478	-508
Primary Income	101	146	124	178	221	212	225	238
Secondary Income	-114	-128	-124	-125	-133	-125	-123	-119
Current Account	-719	-691	-384	-442	-460	-450	-377	-390
NGDP	14478	14719	14419	14964	15518	16163	16768	17419
Current Account % GDP	-5.0	-4.7	-2.7	-3.0	-3.0	-2.8	-2.2	-2.2
NIIP	-1279	-3995	-2628	-2512	-4455	-4578	-5383	-6915
US Owned Assets Abroad	20705	19423	19426	21768	22209	22520	23710	24693
Foreign Owned Assets in US	21984	23418	22054	24280	26664	27098	29093	31608
NIIP % GDP	-8.8	-27.1	-18.2	-16.8	-28.7	-28.3	-32.1	-39.7
Exports Goods, Services and Income	2569	2751	2286	2631	2988	3085	3179	3291
NIIP % Exports Goods, Services and Income	-50	-145	-115	-95	-149	-148	-169	-210
DIA MV	5858	3707	4945	5486	5215	5938	7080	7162
DIUS MV	4134	3091	3619	4099	4199	4671	5791	6253
Fiscal Balance	-161	-459	-1413	-1294	-1300	-1087	-680	-483
Fiscal Balance % GDP	-1.1	-3.1	-9.8	-8.7	-8.5	-6.8	-4.1	-2.8
Federal   Debt	5035	5803	7545	9019	10128	11281	11983	12779
Federal Debt % GDP	35.1	39.3	52.3	61.0	65.8	70.1	72.0	74.1
Federal Outlays	2729	2983	3518	3457	3603	3537	3455	3504
∆%	2.8	9.3	17.9	-1.7	4.2	-1.8	-2.3	1.4
% GDP	19.1	20.2	24.4	23.4	23.4	22.1	20.8	20.3
Federal Revenue	2568	2524	2105	2163	2304	2450	2775	3021
∆%	6.7	-1.7	-16.6	2.7	6.5	6.3	13.3	8.9
% GDP	17.9	17.1	14.6	14.6	15.0	15.3	16.7	17.5

Sources: 

Notes: NGDP: nominal GDP or in current dollars; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value. There are minor discrepancies in the decimal point of percentages of GDP between the balance of payments data and federal debt, outlays, revenue and deficits in which the original number of the CBO source is maintained. See Bureau of Economic Analysis, US International Economic Accounts: Concepts and Methods. 2014. Washington, DC: BEA, Department of Commerce, Jun 2014 http://www.bea.gov/international/concepts_methods.htm These discrepancies do not alter conclusions. Budget http://www.cbo.gov/ Balance of Payments and NIIP http://www.bea.gov/international/index.htm#bop Gross Domestic Product, Bureau of Economic Analysis (BEA) http://www.bea.gov/iTable/index_nipa.cfm

Table VI-3C provides quarterly estimates NSA of the external imbalance of the United States. The current account deficit seasonally adjusted decreases from 2.3 percent of GDP in IQ2014 to 2.1 percent in IIQ2014. The current account deficit increases to 2.2 percent of GDP in IIIQ2014 and increases to 2.3 percent of GDP in IVQ2014. The deficit increases to 2.7 percent of GDP in IQ2015. The net international investment position increases from $5.4 trillion in IQ2014 to $5.5 trillion in IIQ2014, increasing at $6.2 trillion in IIIQ2014. The net international investment position increases to 7.0 trillion in IVQ2014 and decreases to $6.8 trillion in IQ2015.

Table VI-3C, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and % NSA

	IQ2014	IIQ2014	IIIQ2014	IVQ2014	IQ2015
Goods & Services	-100	-139	-143	-126	-109
Primary Income	57	59	63	59	50
Secondary Income	-30	-20	-35	-34	-34
Current Account	-73	-99	-115	-102	-93
Current Account % GDP	-2.3	-2.1	-2.2	-2.3	-2.7
NIIP	-5483	-5519	-6205	-7020	-6794
US Owned Assets Abroad	24081	24987	24597	24595	25324
Foreign Owned Assets in US	-29564	-30506	-30802	-31615	-32118
DIA MV	7183	7481	7232	7124	7261
DIA MV Equity	6120	6413	6156	6052	6187
DIUS MV	5684	5935	6023	6229	6394
DIUS MV Equity	4371	4603	4639	4839	4981

Notes: NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value. See Bureau of Economic Analysis, US International Economic Accounts: Concepts and Methods. 2014. Washington, DC: BEA, Department of Commerce, Jun 2014 http://www.bea.gov/international/concepts_methods.htm

Chart VI-10 of the Board of Governors of the Federal Reserve System provides the overnight Fed funds rate on business days from Jul 1, 1954 at 1.13 percent through Jan 10, 1979, at 9.91 percent per year, to Sep 24, 2015, at 0.14 percent per year. US recessions are in shaded areas according to the reference dates of the NBER (http://www.nber.org/cycles.html). In the Fed effort to control the “Great Inflation” of the 1930s (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), the fed funds rate increased from 8.34 percent on Jan 3, 1979 to a high in Chart VI-10 of 22.36 percent per year on Jul 22, 1981 with collateral adverse effects in the form of impaired savings and loans associations in the United States, emerging market debt and money-center banks (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 72-7; Pelaez 1986, 1987). Another episode in Chart VI-10 is the increase in the fed funds rate from 3.15 percent on Jan 3, 1994, to 6.56 percent on Dec 21, 1994, which also had collateral effects in impairing emerging market debt in Mexico and Argentina and bank balance sheets in a world bust of fixed income markets during pursuit by central banks of non-existing inflation (Pelaez and Pelaez, International Financial Architecture (2005), 113-5). Another interesting policy impulse is the reduction of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of equally non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85), followed by increments of 25 basis points from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006 in Chart VI-10. Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. 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 interest rates close to zero, 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 with the objective of purchasing 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). A final episode in Chart VI-10 is the reduction of the fed funds rate from 5.41 percent on Aug 9, 2007, to 2.97 percent on October 7, 2008, to 0.12 percent on Dec 5, 2008 and close to zero throughout a long period with the final point at 0.14 percent on Sep 24, 2015. Evidently, this behavior of policy would not have occurred had there been theory, measurements and forecasts to avoid these violent oscillations that are clearly detrimental to economic growth and prosperity without inflation. The Chair of the Board of Governors of the Federal Reserve System, Janet L. Yellen, stated on Jul 10, 2015 that (http://www.federalreserve.gov/newsevents/speech/yellen20150710a.htm):

“Based on my outlook, I expect that it will be appropriate at some point later this year to take the first step to raise the federal funds rate and thus begin normalizing monetary policy. But I want to emphasize that the course of the economy and inflation remains highly uncertain, and unanticipated developments could delay or accelerate this first step. I currently anticipate that the appropriate pace of normalization will be gradual, and that monetary policy will need to be highly supportive of economic activity for quite some time. The projections of most of my FOMC colleagues indicate that they have similar expectations for the likely path of the federal funds rate. But, again, both the course of the economy and inflation are uncertain. If progress toward our employment and inflation goals is more rapid than expected, it may be appropriate to remove monetary policy accommodation more quickly. However, if progress toward our goals is slower than anticipated, then the Committee may move more slowly in normalizing policy.”

There is essentially the same view in the Testimony of Chair Yellen in delivering the Semiannual Monetary Policy Report to the Congress on Jul 15, 2015 (http://www.federalreserve.gov/newsevents/testimony/yellen20150715a.htm).

It is a forecast mandate because of the lags in effect of monetary policy impulses on income and prices (Romer and Romer 2004). The intention is to reduce unemployment close to the “natural rate” (Friedman 1968, Phelps 1968) of around 5 percent and inflation at or below 2.0 percent. If forecasts were reasonably accurate, there would not be policy errors. A commonly analyzed risk of zero interest rates is the occurrence of unintended inflation that could precipitate an increase in interest rates similar to the Himalayan rise of the fed funds rate from 9.91 percent on Jan 10, 1979, at the beginning in Chart VI-10, to 22.36 percent on Jul 22, 1981. There is a less commonly analyzed risk of the development of a risk premium on Treasury securities because of the unsustainable Treasury deficit/debt of the United States (Section II and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html

and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2014/02/theory-and-reality-of-cyclical-slow.html and earlier (http://cmpassocregulationblog.blogspot.com/2013/02/united-states-unsustainable-fiscal.html). There is not a fiscal cliff or debt limit issue ahead but rather free fall into a fiscal abyss. The combination of the fiscal abyss with zero interest rates could trigger the risk premium on Treasury debt or Himalayan hike in interest rate.

Chart VI-10, US, Fed Funds Rate, Business Days, Jul 1, 1954 to Sep 24, 2015, Percent per Year

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/h15/update/

There is a false impression of the existence of a monetary policy “science,” measurements and forecasting with which to steer the economy into “prosperity without inflation.” Market participants are remembering the Great Bond Crash of 1994 shown in Table VI-7G when monetary policy pursued nonexistent inflation, causing trillions of dollars of losses in fixed income worldwide while increasing the fed funds rate from 3 percent in Jan 1994 to 6 percent in Dec. The exercise in Table VI-7G shows a drop of the price of the 30-year bond by 18.1 percent and of the 10-year bond by 14.1 percent. CPI inflation remained almost the same and there is no valid counterfactual that inflation would have been higher without monetary policy tightening because of the long lag in effect of monetary policy on inflation (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). The pursuit of nonexistent deflation during the past ten years has resulted in the largest monetary policy accommodation in history that created the 2007 financial market crash and global recession and is currently preventing smoother recovery while creating another financial crash in the future. The issue is not whether there should be a central bank and monetary policy but rather whether policy accommodation in doses from zero interest rates to trillions of dollars in the fed balance sheet endangers economic stability.

Table VI-7G, Fed Funds Rates, Thirty and Ten Year Treasury Yields and Prices, 30-Year Mortgage Rates and 12-month CPI Inflation 1994

1994	FF	30Y	30P	10Y	10P	MOR	CPI
Jan	3.00	6.29	100	5.75	100	7.06	2.52
Feb	3.25	6.49	97.37	5.97	98.36	7.15	2.51
Mar	3.50	6.91	92.19	6.48	94.69	7.68	2.51
Apr	3.75	7.27	88.10	6.97	91.32	8.32	2.36
May	4.25	7.41	86.59	7.18	88.93	8.60	2.29
Jun	4.25	7.40	86.69	7.10	90.45	8.40	2.49
Jul	4.25	7.58	84.81	7.30	89.14	8.61	2.77
Aug	4.75	7.49	85.74	7.24	89.53	8.51	2.69
Sep	4.75	7.71	83.49	7.46	88.10	8.64	2.96
Oct	4.75	7.94	81.23	7.74	86.33	8.93	2.61
Nov	5.50	8.08	79.90	7.96	84.96	9.17	2.67
Dec	6.00	7.87	81.91	7.81	85.89	9.20	2.67

Notes: FF: fed funds rate; 30Y: yield of 30-year Treasury; 30P: price of 30-year Treasury assuming coupon equal to 6.29 percent and maturity in exactly 30 years; 10Y: yield of 10-year Treasury; 10P: price of 10-year Treasury assuming coupon equal to 5.75 percent and maturity in exactly 10 years; MOR: 30-year mortgage; CPI: percent change of CPI in 12 months

Sources: yields and mortgage rates http://www.federalreserve.gov/releases/h15/data.htm CPI ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.t

Chart VI-14 provides the overnight fed funds rate, the yield of the 10-year Treasury constant maturity bond, the yield of the 30-year constant maturity bond and the conventional mortgage rate from Jan 1991 to Dec 1996. In Jan 1991, the fed funds rate was 6.91 percent, the 10-year Treasury yield 8.09 percent, the 30-year Treasury yield 8.27 percent and the conventional mortgage rate 9.64 percent. Before monetary policy tightening in Oct 1993, the rates and yields were 2.99 percent for the fed funds, 5.33 percent for the 10-year Treasury, 5.94 for the 30-year Treasury and 6.83 percent for the conventional mortgage rate. After tightening in Nov 1994, the rates and yields were 5.29 percent for the fed funds rate, 7.96 percent for the 10-year Treasury, 8.08 percent for the 30-year Treasury and 9.17 percent for the conventional mortgage rate.

Chart VI-14, US, Overnight Fed Funds Rate, 10-Year Treasury Constant Maturity, 30-Year Treasury Constant Maturity and Conventional Mortgage Rate, Monthly, Jan 1991 to Dec 1996

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/h15/update/

Chart VI-15 of the Bureau of Labor Statistics provides the all items consumer price index from Jan 1991 to Dec 1996. There does not appear acceleration of consumer prices requiring aggressive tightening.

Chart VI-15, US, Consumer Price Index All Items, Jan 1991 to Dec 1996

Source: Bureau of Labor Statistics

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

Chart IV-16 of the Bureau of Labor Statistics provides 12-month percentage changes of the all items consumer price index from Jan 1991 to Dec 1996. Inflation collapsed during the recession from Jul 1990 (III) and Mar 1991 (I) and the end of the Kuwait War on Feb 25, 1991 that stabilized world oil markets. CPI inflation remained almost the same and there is no valid counterfactual that inflation would have been higher without monetary policy tightening because of the long lag in effect of monetary policy on inflation (see Culbertson 1960, 1961, Friedman 1961, Batini and Nelson 2002, Romer and Romer 2004). Policy tightening had adverse collateral effects in the form of emerging market crises in Mexico and Argentina and fixed income markets worldwide.

Chart VI-16, US, Consumer Price Index All Items, Twelve-Month Percentage Change, Jan 1991 to Dec 1996

Source: Bureau of Labor Statistics

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

  The Congressional Budget Office (CBO 2014BEOFeb4) estimates potential GDP, potential labor force and potential labor productivity provided in Table IB-3. The CBO estimates average rate of growth of potential GDP from 1950 to 2014 at 3.3 percent per year. The projected path is significantly lower at 2.1 percent per year from 2015 to 2025. The legacy of the economic cycle expansion from IIIQ2009 to IQ2015 at 2.2 percent on average is in contrast with 4.8 percent on average in the expansion from IQ1983 to IIIQ1988 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuations-of-global-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/turbulence-of-valuations-of-financial.html).). Subpar economic growth may perpetuate unemployment and underemployment estimated at 25.2 million or 15.1 percent of the effective labor force in Aug 2015 (http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuating-risk-financial-assets.html) with much lower hiring than in the period before the current cycle (http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what_13.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/exchange-rate-and-financial-asset.html).

Table IB-3, US, Congressional Budget Office History and Projections of Potential GDP of US Overall Economy, ∆%

	Potential GDP	Potential Labor Force	Potential Labor Productivity*
Average Annual ∆%
1950-1973	4.0	1.6	2.4
1974-1981	3.3	2.5	0.8
1982-1990	3.2	1.6	1.6
1991-2001	3.2	1.3	1.9
2002-2007	2.8	0.9	1.9
2008-2014	1.4	0.5	0.9
Total 1950-2014	3.3	1.5	1.8
Projected Average Annual ∆%
2015-2019	2.1	0.5	1.6
2019-2025	2.2	0.6	1.6
2015-2025	2.1	0.5	1.6

*Ratio of potential GDP to potential labor force

Source: CBO (2014BEOFeb4), CBO, Key assumptions in projecting potential GDP—February 2014 baseline. Washington, DC, Congressional Budget Office, Feb 4, 2014. CBO, The budget and economic outlook: 2015 to 2025. Washington, DC, Congressional Budget Office, Jan 26, 2015.

Chart IB-1A of the Congressional Budget Office provides historical and projected potential and actual US GDP. The gap between actual and potential output closes by 2017. Potential output expands at a lower rate than historically. Growth is even weaker relative to trend.

Chart IB-1A, Congressional Budget Office, Estimate of Potential GDP and Gap

Source: Congressional Budget Office

https://www.cbo.gov/publication/49890

Chart IB-1 of the Congressional Budget Office (CBO 2013BEOFeb5) provides actual and potential GDP of the United States from 2000 to 2011 and projected to 2024. Lucas (2011May) estimates trend of United States real GDP of 3.0 percent from 1870 to 2010 and 2.2 percent for per capita GDP. The United States successfully returned to trend growth of GDP by higher rates of growth during cyclical expansion as analyzed by Bordo (2012Sep27, 2012Oct21) and Bordo and Haubrich (2012DR). Growth in expansions following deeper contractions and financial crises was much higher in agreement with the plucking model of Friedman (1964, 1988). The unusual weakness of growth at 2.2 percent on average from IIIQ2009 to IIQ2015 during the current economic expansion in contrast with 4.8 percent on average in the cyclical expansion from IQ1983 to IVQ1988 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuations-of-global-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/turbulence-of-valuations-of-financial.html) cannot be explained by the contraction of 4.2 percent of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 25.2 million or 15.1 percent of the labor force as estimated for Aug 2015 (http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuating-risk-financial-assets.html). There is no exit from unemployment/underemployment and stagnating real wages because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what_13.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/exchange-rate-and-financial-asset.html). The US economy and labor markets collapsed without recovery. Abrupt collapse of economic conditions can be explained only with cyclic factors (Lazear and Spletzer 2012Jul22) and not by secular stagnation (Hansen 1938, 1939, 1941 with early dissent by Simons 1942).

Chart IB-1, US, Congressional Budget Office, Actual and Projections of Potential GDP, 2000-2024, Trillions of Dollars

Source: Congressional Budget Office, CBO (2013BEOFeb5). The last year in common in both projections is 2017. The revision lowers potential output in 2017 by 7.3 percent relative to the projection in 2007.

Chart IB-2 provides differences in the projections of potential output by the CBO in 2007 and more recently on Feb 4, 2014, which the CBO explains in CBO (2014Feb28).

Chart IB-2, Congressional Budget Office, Revisions of Potential GDP

Source: Congressional Budget Office, 2014Feb 28. Revisions to CBO’s Projection of Potential Output since 2007. Washington, DC, CBO, Feb 28, 2014.

Chart IB-3 provides actual and projected potential GDP from 2000 to 2024. The gap between actual and potential GDP disappears at the end of 2017 (CBO2014Feb4). GDP increases in the projection at 2.5 percent per year.

Chart IB-3, Congressional Budget Office, GDP and Potential GDP

Source: CBO (2013BEOFeb5), CBO, Key assumptions in projecting potential GDP—February 2014 baseline. Washington, DC, Congressional Budget Office, Feb 4, 2014.

Chart IIA2-3 of the Bureau of Economic Analysis of the Department of Commerce shows on the lower negative panel the sharp increase in the deficit in goods and the deficits in goods and services from 1960 to 2012. The upper panel shows the increase in the surplus in services that was insufficient to contain the increase of the deficit in goods and services. The adjustment during the global recession has been in the form of contraction of economic activity that reduced demand for goods.

Chart IIA2-3, US, Balance of Goods, Balance on Services and Balance on Goods and Services, 1960-2013, Millions of Dollars

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

Chart IIA2-4 of the Bureau of Economic Analysis shows exports and imports of goods and services from 1960 to 2012. Exports of goods and services in the upper positive panel have been quite dynamic but have not compensated for the sharp increase in imports of goods. The US economy apparently has become less competitive in goods than in services.

Chart IIA2-4, US, Exports and Imports of Goods and Services, 1960-2013, Millions of Dollars

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

Chart IIA2-5 of the Bureau of Economic Analysis shows the US balance on current account from 1960 to 2012. The sharp devaluation of the dollar resulting from unconventional monetary policy of zero interest rates and elimination of auctions of 30-year Treasury bonds did not adjust the US balance of payments. Adjustment only occurred after the contraction of economic activity during the global recession.

Chart IIA2-5, US, Balance on Current Account, 1960-2013, Millions of Dollars

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

Chart IIA2-6 of the Bureau of Economic Analysis provides real GDP in the US from 1960 to 2014. The contraction of economic activity during the global recession was a major factor in the reduction of the current account deficit as percent of GDP.

Chart IIA2-6, US, Real GDP, 1960-2014, Billions of Chained 2009 Dollars

Source: Bureau of Economic Analysis

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

Chart IIA-7 provides the US current account deficit on a quarterly basis from 1980 to IQ1983. The deficit is at a lower level because of growth below potential not only in the US but worldwide. The combination of high government debt and deficit with external imbalance restricts potential prosperity in the US.

Chart IIA-7, US, Balance on Current Account, Quarterly, 1980-2013

Source: Bureau of Economic Analysis

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

Risk aversion channels funds toward US long-term and short-term securities that finance the US balance of payments and fiscal deficits benefitting from risk flight to US dollar denominated assets. There are now temporary interruptions because of fear of rising interest rates that erode prices of US government securities because of mixed signals on monetary policy and exit from the Fed balance sheet of four trillion dollars of securities held outright. Net foreign purchases of US long-term securities (row C in Table VA-4) eased from $86.8 billion in Jun 2015 to minus $7.9 billion in Jul 2015. Foreign (residents) purchases minus sales of US long-term securities (row A in Table VA-4) in Jun 2015 of $87.2 billion eased to $4.0 billion in Jul 2015. Net US (residents) purchases of long-term foreign securities (row B in Table VA-4) eased from $15.9 billion in Jun 2015 to $3.7 billion in Jul 2015. Other transactions (row C2 in Table VA-4) decreased from $86.8 billion in Jun 2015 to minus $7.9 billion in Jul 2015. In Jul 2015,

C = A + B + C2 = $4.0 billion + $3.7 billion -$15.6 = -$7.9 billion

There are minor rounding errors. There is weakening demand in Table VA-3 in Jul in A1 private purchases by residents overseas of US long-term securities of $21.5 billion of which weakening in A11 Treasury securities of minus $8.4 billion, weakening in A12 of 7.8 billion in agency securities, strengthening of $18.1 billion of corporate bonds and strengthening of $3.9 billion in equities. Worldwide risk aversion causes flight into US Treasury obligations with significant oscillations. Official purchases of securities in row A2 decreased $17.5 billion with decrease of Treasury securities of $20.3 billion in Jul 2015. Official purchases of agency securities increased $2.6 billion in Jul 2015. Row D shows decrease in Jul 2015 of $10.4 billion in purchases of short-term dollar denominated obligations. Foreign private holdings of US Treasury bills increased $2.7 billion (row D11) with foreign official holdings decreasing $9.5 billion while the category “other” decreased $3.6 billion. Foreign private holdings of US Treasury bills increased $2.7 billion in what could be arbitrage of duration exposures. Risk aversion of default losses in foreign securities dominates decisions to accept zero interest rates in Treasury securities with no perception of principal losses. In the case of long-term securities, investors prefer to sacrifice inflation and possible duration risk to avoid principal losses with significant oscillations in risk perceptions.

Table VA-4, Net Cross-Borders Flows of US Long-Term Securities, Billion Dollars, NSA

	Jul 2014 12 Months	Jul 2015 12 Months	Jun 2015	Jul 2015
A Foreign Purchases less Sales of US LT Securities	157.7	377.4	87.2	4.0
A1 Private	118.2	446.6	92.6	21.5
A11 Treasury	146.5	224.5	80.7	-8.4
A12 Agency	7.5	136.1	18.0	7.8
A13 Corporate Bonds	-30.7	142.5	16.0	18.1
A14 Equities	-5.2	-56.5	-22.1	3.9
A2 Official	39.5	-69.2	-5.4	-17.5
A21 Treasury	27.0	-122.8	-10.9	-20.3
A22 Agency	21.3	50.1	7.6	2.6
A23 Corporate Bonds	8.1	5.9	-2.2	0.6
A24 Equities	-16.8	-2.5	0.0	-0.2
B Net US Purchases of LT Foreign Securities	-197.7	184.7	15.9	3.7
B1 Foreign Bonds	-31.9	274.4	29.3	20.4
B2 Foreign Equities	-165.8	-89.7	-13.4	-16.7
C1 Net Transactions	-40.0	562.1	103.1	7.7
C2 Other	-110.7	-272.0	-16.3	-15.6
C Net Foreign Purchases of US LT Securities	-150.7	290.1	86.8	-7.9
D Increase in Foreign Holdings of Dollar Denominated Short-term	-23.2	48.7	-7.5	-10.4
D1 US Treasury Bills	-33.9	73.7	0.0	-6.9
D11 Private	-3.7	47.7	8.7	2.7
D12 Official	-30.2	26.0	-8.7	-9.5
D2 Other	10.7	-25.0	-7.5	-3.6

C1 = A + B; C = C1+C2

A = A1 + A2

A1 = A11 + A12 + A13 + A14

A2 = A21 + A22 + A23 + A24

B = B1 + B2

D = D1 + D2

Sources: United States Treasury

http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/ticpress.aspx

http://www.treasury.gov/press-center/press-releases/Pages/jl2609.aspx

Table VA-5 provides major foreign holders of US Treasury securities. China is the largest holder with $1240.8 billion in Jul 2015, decreasing 2.4 percent from $1271.2 billion in May 2015 while decreasing $24.1 billion from Jul 2014 or 1.9 percent. The United States Treasury estimates US government debt held by private investors at $10,043 billion in Dec 2014. China’s holding of US Treasury securities represent 12.4 percent of US government marketable interest-bearing debt held by private investors (http://www.fms.treas.gov/bulletin/index.html). Min Zeng, writing on “China plays a big role as US Treasury yields fall,” on Jul 16, 2004, published in the Wall Street Journal (http://online.wsj.com/articles/china-plays-a-big-role-as-u-s-treasury-yields-fall-1405545034?tesla=y&mg=reno64-wsj), finds that acceleration in purchases of US Treasury securities by China has been an important factor in the decline of Treasury yields in 2014. Japan decreased its holdings from $1219.0 billion in Jul 2014 to $1197.5 billion in Jul 2015 or 1.8 percent. The combined holdings of China and Japan in Jul 2015 add to $2438.3 billion, which is equivalent to 24.3 percent of US government marketable interest-bearing securities held by investors of $10,043 billion in Dec 2014 (http://www.fms.treas.gov/bulletin/index.html). Total foreign holdings of Treasury securities rose from $6002.6 billion in Jul 2014 to $6076.6 billion in Jul 2015, or 1.2 percent. The US continues to finance its fiscal and balance of payments deficits with foreign savings (see Pelaez and Pelaez, The Global Recession Risk (2007)). A point of saturation of holdings of US Treasury debt may be reached as foreign holders evaluate the threat of reduction of principal by dollar devaluation and reduction of prices by increases in yield, including possibly risk premium. Shultz et al (2012) find that the Fed financed three-quarters of the US deficit in fiscal year 2011, with foreign governments financing significant part of the remainder of the US deficit while the Fed owns one in six dollars of US national debt. Concentrations of debt in few holders are perilous because of sudden exodus in fear of devaluation and yield increases and the limit of refinancing old debt and placing new debt. In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):

“Imagine that fiscal policy dominates monetary policy. The fiscal authority independently sets its budgets, announcing all current and future deficits and surpluses and thus determining the amount of revenue that must be raised through bond sales and seignorage. Under this second coordination scheme, the monetary authority faces the constraints imposed by the demand for government bonds, for it must try to finance with seignorage any discrepancy between the revenue demanded by the fiscal authority and the amount of bonds that can be sold to the public. Suppose that the demand for government bonds implies an interest rate on bonds greater than the economy’s rate of growth. Then if the fiscal authority runs deficits, the monetary authority is unable to control either the growth rate of the monetary base or inflation forever. If the principal and interest due on these additional bonds are raised by selling still more bonds, so as to continue to hold down the growth of base money, then, because the interest rate on bonds is greater than the economy’s growth rate, the real stock of bonds will growth faster than the size of the economy. This cannot go on forever, since the demand for bonds places an upper limit on the stock of bonds relative to the size of the economy. Once that limit is reached, the principal and interest due on the bonds already sold to fight inflation must be financed, at least in part, by seignorage, requiring the creation of additional base money.”

Table VA-5, US, Major Foreign Holders of Treasury Securities $ Billions at End of Period

	Jul 2015	Jun 2015	Jul 2014
Total	6076.6	6175.2	6002.6
China	1240.8	1271.2	1264.9
Japan	1197.5	1197.1	1219.0
Caribbean Banking Centers	324.5	318.5	249.6
Oil Exporters	298.3	296.7	261.3
Brazil	256.7	256.3	258.6
Switzerland	217.5	217.1	184.1
Ireland	216.6	217.7	174.7
United Kingdom	212.6	214.7	173.0
Luxembourg	185.2	184.0	145.6
Hong Kong	182.3	181.3	158.7
Taiwan	168.6	175.6	175.4
Belgium	155.4	207.7	352.6
India	116.3	117.0	79.7
Foreign Official Holdings	4116.6	4164.3	4111.7
A. Treasury Bills	358.7	368.3	332.7
B. Treasury Bonds and Notes	3757.8	3796.0	3779.0

Source: United States Treasury

http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/ticpress.aspx

http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/index.aspx

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 20 of 56 months from Jan 2011 to Aug 2015 with monthly declines of 5 in 2011, 4 in 2012, 4 in 2013, 5 in 2014 and 2 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 9.2 percent in Jun 2015, increasing 12.0 percent in Jul 2015. New house sales increased 5.7 percent in Aug 2015. New house sales increased at the annual equivalent rate of 28.0 percent May-Aug 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 ag 3.91 percent on Sep 17, 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	∆%
Aug 2015	552	5.7
Jul	522	12.0
Jun	466	-9.2
May	513	1.0
AE ∆% May-Aug		28.0
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 4.7 percent in Aug 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 Aug 2015, median prices of new houses sold not seasonally adjusted (NSA) increased 0.5 percent after increasing 5.9 percent in Jul 2015. Average prices increased 2.5 percent in Aug 2015 and increased 5.9 percent in Jul 2015. Between Dec 2010 and Aug 2015, median prices increased 21.4 percent, partly concentrated in increases of 5.9 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 21.2 percent between Dec 2010 and Aug 2015, with increase of 8.1 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 ∆%
Aug 2015	4.7	292,700	0.5	353,400	2.5
Jul	4.9	291,100	5.9	344,800	8.1
Jun	5.5	274,800	-4.4	319,000	-6.4
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-Aug of various years. Sales of new houses are higher in Jan-Aug 2015 relative to Jan-Aug 2014 with increase of 19.8 percent. Sales of new houses in Jan-Aug 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 19.4 percent relative to Jan-Aug 2013, 40.6 percent relative to Jan-Aug 2012, 70.8 percent relative to Jan-Aug 2011, 54.5 percent relative to Jan-Aug 2010 and 36.8 percent relative to Jan-Aug 2009. Sales of new houses in Jan-Aug 2015 are lower by 2.2 percent relative to Jan-Aug 2008, 38.1 percent relative to 2007, 52.8 percent relative to 2006 and 60.6 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-Aug 2015 relative to the same period in 2004 fell 57.6 percent and 53.0 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-Aug 2015 fell 23.4 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-Aug 2015 of 357 thousand units are lower by 10.1 percent relative to 397 thousand units of houses sold in Jan-Aug 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-Aug 2015	357
Jan-Aug 2014	298
∆% Jan-Aug 2015/Jan-Aug 2014	19.8
Jan-Aug 2013	299
∆% Jan-Aug 2015/Jan-Aug 2013	19.4
Jan-Aug 2012	254
∆% Jan-Aug 2015/Jan-Aug 2012	40.6
Jan-Aug 2011	209
∆% Jan-Aug 2015/Jan-Aug 2011	70.8
Jan-Aug 2010	231
∆% Jan-Aug 2015/  Jan-Aug 2010	54.5
Jan-Aug 2009	261
∆% Jan-Aug 2015/  Jan-Aug 2009	36.8
Jan-Aug 2008	365
∆% Jan-Aug 2015/  Jan-Aug 2008	-2.2
Jan-Aug 2007	577
∆% Jan-Aug 2015/ Jan-Aug 2007	-38.1
Jan-Aug 2006	756
∆% Jan-Aug 2015/Jan-Aug 2006	-52.8
Jan-Aug 2005	906
∆% Jan-Aug 2015/Jan-Aug 2005	-60.6
Jan-Aug 2004	841
∆% Jan-Aug 2015/Jan-Aug 2004	-57.6
Jan-Aug 2003	759
∆% Jan-Aug 2015/ Jan-Aug  2003	-53.0
Jan-Aug 2002	670
∆% Jan-Aug 2015/ Jan-Aug 2002	-46.7
Jan-Aug 2001	644
∆% Jan-Aug 2015/ Jan-Aug 2001	-44.6
Jan-Aug 2000	608
∆% Jan-Aug 2015/ Jan-Aug 2000	-41.3
Jan-Aug 1995	466
∆% Jan-Aug 2015/ Jan-Aug 1995	-23.4
Jan-Aug 1963	397
∆% Jan-Aug 2015/ Jan-Aug 1963	-10.1

*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 Aug 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 Aug 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 Aug 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 3.91 percent in Aug 2015 with the yield of the 30-year Treasury bond at 2.86 percent and overnight rate on fed funds at 0.14 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 Aug 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 Aug 2015, the fed funds rate stabilized at 0.14 percent with decrease to 2.86 percent of the 30-year yield and decrease at 3.91 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 Aug 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	3.4	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	3.8	4.26
2013-12	0.09	3.89	4.46
2014-01	0.07	3.77	4.43
2014-02	0.07	3.66	4.3
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	3.2	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
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

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). 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 0.6 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 0.4 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 0.2 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 0.9 percent and 2.3 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 0.1 percent and 3.5 percent in 12 months. Strong increase of 0.5 percent in Aug 2012 pulled the 12-month change to 4.3 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 5.3 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 7.4 percent in 12 months. The FHFA house price index increased 0.7 percent in Jun 2013 and 7.7 percent in 12 months. In Jul 2013, the FHFA house price index increased 0.7 percent and 8.3 percent in 12 months. Improvement continued with increase of 0.4 percent in Aug 2013 and 8.2 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 decreased 0.1 percent and increased 7.3 percent in 12 months. The house price index rose 0.7 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 7.0 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 0.2 percent in May 2014 and 5.5 percent in 12 months. In Jun 2014, the house price index increased 0.5 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 0.2 percent and increased 4.6 percent in 12 months. The house price index increased 0.5 percent in Oct 2014 and 4.6 percent in 12 months. In Nov 2014, the house price index increased 0.7 percent and 5.4 percent in 12 months. The house price index increased 0.8 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 0.4 percent and 5.6 percent in 12 months. The house price index increased 0.4 percent in May 2015 and 5.8 percent in 12 months. House prices increased 0.2 percent in Jun 2015 and 5.5 percent in 12 months. The house price index increased 0.6 percent in Jul 2015 and increased 5.8 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
Jul 2015	0.6	5.8
Jun	0.2	5.5
May	0.4	5.8
Apr	0.4	5.6
Mar	0.4	5.5
Feb	0.7	5.5
Jan	0.3	5.2
Dec 2014	0.8	5.5
Nov	0.7	5.4
Oct	0.5	4.6
Sep	0.2	4.6
Aug	0.6	5.0
Jul	0.3	4.9
Jun	0.5	5.3
May	0.2	5.5
Apr	0.2	6.0
Mar	0.5	6.4
Feb	0.4	7.0
Jan	0.7	7.3
Dec 2013	0.7	7.5
Nov	-0.1	7.3
Oct	0.5	7.9
Sep	0.5	8.1
Aug	0.4	8.2
Jul	0.7	8.3
Jun	0.7	7.7
May	0.7	7.4
Apr	0.5	7.2
Mar	1.2	7.4
Feb	0.7	6.9
Jan	0.8	6.4
Dec 2012	0.5	5.5
Nov	0.5	5.3
Oct	0.7	5.3
Sep	0.5	4.1
Aug	0.5	4.3
Jul	0.1	3.5
Jun	0.4	3.6
May	0.6	3.6
Apr	0.6	2.7
Mar	0.9	2.3
Feb	0.2	0.2
Jan	-0.1	-1.1
Dec 2011	0.4	-1.2
Nov	0.4	-2.3
Oct	-0.6	-3.0
Sep	0.6	-2.3
Aug	-0.3	-3.8
Jul	0.3	-3.5
Jun	0.4	-4.4
May	-0.2	-5.9
Apr	0.2	-5.8
Mar	-1.0	-5.9
Feb	-1.1	-5.0
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 107.8 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 3.2 percent between 2006 and 2014 and 0.8 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	107.8	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	-0.8	NA
2000-2006	54.1	7.5
2003-2006	24.1	7.4
2006-2014	-3.2	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 93.7 percent in the 10-city composite of the Case-Shiller home price index, 78.1 percent in the 20-city composite and 64.0 percent in the US national home price index between Jun 2000 and Jun 2005. Prices rose around 100 percent from Jun 2000 to Jun 2006, increasing 110.5 percent for the 10-city composite, 93.3 percent for the 20-city composite and 76.0 percent in the US national index. House prices rose 39.5 percent between Jun 2003 and Jun 2005 for the 10-city composite, 34.5 percent for the 20-city composite and 29.1 percent for the US national propelled by low fed funds rates of 1.0 percent between Jun 2003 and Jun 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Aprket Committee (FOMC) from Jun 2004 until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Jun 2003 and Jun 2006, the 10-city index gained 51.6 percent, the 20-city index increased 46.0 percent and the US national 38.5 percent. House prices have fallen from Jun 2006 to Jun 2015 by 13.7 percent for the 10-city composite, 12.4 percent for the 20-city composite and 5.8 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 Jun 2015, house prices increased 4.6 percent in the 10-city composite, increased 5.0 percent in the 20-city composite and 4.5 percent in the US national. Table IIA-6 also shows that house prices increased 81.7 percent between Jun 2000 and Jun 2015 for the 10-city composite, increased 69.4 percent for the 20-city composite and 65.8 percent for the US national. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The 10-city composite fell 13.4 percent from the peak in Jun 2006 to Jun 2015 and the 20-city composite fell 12.4 percent from the peak in Jul 2006 to Jun 2015. The US national fell 5.8 percent from the peak of the 10-city composite to Jun 2015 and 5.8 percent from the peak of the 20-city composite to Jun 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
∆% Jun 2000 to Jun 2003	38.8	32.4	27.1
∆% Jun 2000 to Jun 2005	93.7	78.1	64.0
∆% Jun 2003 to Jun 2005	39.5	34.5	29.1
∆% Jun 2000 to Jun 2006	110.5	93.3	76.0
∆% Jun 2003 to Jun 2006	51.6	46.0	38.5
∆% Jun 2005 to Jun 2015	-6.2	-4.9	1.1
∆% Jun 2006 to Jun 2015	-13.7	-12.4	-5.8
∆% Jun 2009 to Jun 2015	27.7	27.4	16.0
∆% Jun 2010 to Jun 2015	21.6	22.2	17.7
∆% Jun 2011 to Jun 2015	26.5	27.8	22.5
∆% Jun 2012 to Jun 2015	26.4	27.1	21.4
∆% Jun 2013 to Jun 2015	13.1	13.4	11.1
∆% Jun 2014 to Jun 2015	4.6	5.0	4.5
∆% Jun 2000 to Jun 2015	81.7	69.4	65.8
∆% Peak Jun 2006 Jun 2015	-13.4		-5.8
∆% Peak Jul 2006 Jun 2015		-12.4	-5.8
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/226352_cshomeprice-release-0825.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 0.9 percent and the 20-city increased 1.0 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city changed 0.0 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. With the exception of Mar through Apr 2012, house prices seasonally adjusted declined in 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 0.9 percent in Jun 2015 and the 20-city increased 1.0 percent. The 10-city SA decreased 0.1 percent in Jun 2015 and the 20-city composite SA decreased 0.1 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
Jun 2015	-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	0.7	0.8	0.9	0.9
Feb	1.2	0.5	1.2	0.5
Jan	0.8	-0.1	0.8	-0.1
Dec 2014	0.8	0.1	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	0.2	0.0	0.2
Jul	-0.3	0.6	-0.4	0.6
Jun	-0.1	1.0	-0.1	1.0
May	-0.2	1.1	-0.2	1.1
Apr	0.1	1.1	0.0	1.2
Mar	0.8	0.8	0.9	0.9
Feb	0.8	0.0	0.7	0.0
Jan	0.8	-0.1	0.8	-0.1
Dec 2013	0.7	-0.1	0.7	-0.1
Nov	0.9	0.0	0.9	-0.1
Oct	1.0	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	0.8	1.8
Jun	1.1	2.2	1.0	2.2
May	1.2	2.5	1.2	2.5
Apr	1.7	2.6	1.5	2.6
Mar	1.3	1.3	1.4	1.3
Feb	1.1	0.3	1.1	0.2
Jan	0.9	0.0	1.0	0.0
Dec 2012	1.0	0.2	1.0	0.2
Nov	0.7	-0.3	0.8	-0.2
Oct	0.6	-0.2	0.7	-0.1
Sep	0.5	0.3	0.6	0.3
Aug	0.5	0.8	0.6	0.9
Jul	0.4	1.5	0.5	1.6
Jun	0.9	2.1	1.0	2.3
May	0.9	2.2	1.0	2.4
Apr	0.5	1.4	0.5	1.4
Mar	0.1	-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	-0.6	-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	-0.3	1.0	-0.3	1.0
Apr	-0.2	0.6	-0.2	0.6
Mar	-0.6	-1.0	-0.7	-1.0
Feb	-0.4	-1.3	-0.3	-1.2
Jan	-0.2	-1.1	-0.2	-1.1
Dec 2010	-0.2	-0.9	-0.2	-1.0

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

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