Tapering Quantitative Easing, Mediocre and Decelerating US Economic Growth, World Inflation Waves, Unresolved US Balance of Payments Deficits and Fiscal Imbalance, Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates, Theory and Reality of Secular Stagnation and Productivity Growth, US Industrial Production, World Economic Slowdown and Global Recession Risk
Carlos M. Pelaez
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013
Executive Summary
I Mediocre and Decelerating United States Economic Growth
IA Mediocre and Decelerating United States Economic Growth
IA1 Contracting Real Private Fixed Investment
IA2 Swelling Undistributed Corporate Profits
II World Inflation Waves
IIA Appendix: Transmission of Unconventional Monetary Policy
IB1 Theory
IB2 Policy
IB3 Evidence
IB4 Unwinding Strategy
IIB United States Inflation
IIC Long-term US Inflation
IID Current US Inflation
IIE Theory and Reality of Economic History and Monetary Policy Based on Fear of Deflation
IIF United States Industrial Production and External and Fiscal Imbalances
IIA Unresolved US Balance of Payments Deficits and Fiscal Imbalance Threatening Risk Premium on Treasury Securities
IIA1 United States Unsustainable Deficit/Debt
IIA2 Unresolved US Balance of Payments Deficits
IIF United States Industrial Production
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
ID Current US Inflation. Consumer price inflation has fluctuated in recent months. Table I-3 provides 12-month consumer price inflation in Nov 2013 and annual equivalent percentage changes for the months of Sep-Nov 2013 of the CPI and major segments. The final column provides inflation from Oct 2013 to Nov 2013. CPI inflation in the 12 months ending in Nov 2013 reached 1.2 percent, the annual equivalent rate Sep to Nov 2013 was 0.4 percent in the new episode of reversing carry trades from zero interest rates to commodities exposures and the monthly inflation rate of 0.0 percent annualizes at 0.0 percent with oscillating carry trades at the margin. These inflation rates fluctuate in accordance with inducement of risk appetite or frustration by risk aversion of carry trades from zero interest rates to commodity futures. At the margin, the decline in commodity prices in sharp recent risk aversion in commodities markets caused lower inflation worldwide (with return in some countries in Dec 2012 and Jan-Feb 2013) that followed a jump in Aug-Sep 2012 because of the relaxed risk aversion resulting from the bond-buying program of the European Central Bank or Outright Monetary Transactions (OMT) (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html). Carry trades moved away from commodities into stocks with resulting weaker commodity prices and stronger equity valuations. There is reversal of exposures in commodities but with preferences of equities by investors. With zero interest rates, commodity prices would increase again in an environment of risk appetite. Excluding food and energy, CPI inflation was 1.7 percent in the 12 months ending in Nov 2013 and 1.6 percent in annual equivalent in Sep to Nov 2013. There is no deflation in the US economy that could justify further quantitative easing, which is now open-ended or forever with zero interest rates and potential tapering bond-buying by the central bank, or QE→∞, even if the economy grows back to potential. Financial repression of zero interest rates is now intended as a permanent distortion of resource allocation by clouding risk/return decisions, preventing the economy from expanding along its optimal growth path. Consumer food prices in the US have risen 1.2 percent in 12 months ending in Nov 2013 and at 0.8 percent in annual equivalent in Sep to Nov 2013. Monetary policies stimulating carry trades of commodities futures that increase prices of food constitute a highly regressive tax on lower income families for whom food is a major portion of the consumption basket especially with wage increases below inflation in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2013/12/theory-and-reality-of-secular.html) and without jobs (http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.htm). Energy consumer prices decreased 2.4 percent in 12 months, decreased 7.4 percent in annual equivalent in Sep to Nov 2013 and decreased 1.0 percent in Nov 2013 or at minus 11.4 percent in annual equivalent. Waves of inflation are induced by carry trades from zero interest rates to commodity futures, which are unwound and repositioned during alternating risk aversion and risk appetite originating in the European debt crisis and increasingly in growth and politics in China. For lower income families, food and energy are a major part of the family budget. Inflation is not persistently low or threatening deflation in annual equivalent in Sep to Nov 2013 in any of the categories in Table I-2 but simply reflecting waves of inflation originating in carry trades. Carry trades from zero interest rates induce commodity futures positions with episodes of risk aversion causing fluctuations determine an upward trend of prices.
Table I-3, US, Consumer Price Index Percentage Changes 12 months NSA and Annual Equivalent ∆%
| % RI | ∆% 12 Months Nov 2013/Nov | ∆% Annual Equivalent Sep 2013 to Nov 2013 SA | ∆% Nov 2013/Oct 2013 SA | |
| CPI All Items | 100.000 | 1.2 | 0.4 | 0.0 |
| CPI ex Food and Energy | 76.179 | 1.7 | 1.6 | 0.2 |
| Food | 14.218 | 1.2 | 0.8 | 0.1 |
| Food at Home | 8.508 | 0.6 | 0.4 | 0.0 |
| Food Away from Home | 5.710 | 2.1 | 2.0 | 0.3 |
| Energy | 9.603 | -2.4 | -7.4 | -1.0 |
| Gasoline | 5.270 | -5.8 | -14.0 | -1.6 |
| Electricity | 2.926 | 2.9 | 3.7 | 0.3 |
| Commodities less Food and Energy | 19.431 | -0.2 | -1.2 | -0.1 |
| New Vehicles | 3.142 | 0.6 | 0.0 | -0.1 |
| Used Cars and Trucks | 1.877 | 2.0 | 1.6 | 0.1 |
| Medical Care Commodities | 1.710 | 0.8 | 1.6 | 0.0 |
| Apparel | 3.654 | -0.1 | -5.5 | -0.4 |
| Services Less Energy Services | 56.748 | 2.4 | 2.8 | 0.3 |
| Shelter | 31.797 | 2.4 | 2.4 | 0.3 |
| Rent of Primary Residence | 6.577 | 2.8 | 2.4 | 0.2 |
| Owner’s Equivalent Rent of Residences | 24.089 | 2.4 | 2.8 | 0.3 |
| Transportation Services | 5.847 | 2.6 | 5.3 | 0.3 |
| Medical Care Services | 5.491 | 2.6 | 0.8 | 0.0 |
% RI: Percent Relative Importance
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
The weights of the CPI, US city average for all urban consumers representing about 87 percent of the US population (http://www.bls.gov/cpi/cpiovrvw.htm#item1), are shown in Table I-4 with the BLS update for Dec 2012 (http://www.bls.gov/cpi/cpiri2012.pdf). Housing has a weight of 41.021 percent. The combined weight of housing and transportation is 57.867 percent or more than one-half of consumer expenditures of all urban consumers. The combined weight of housing, transportation and food and beverages is 73.128 percent of the US CPI. Table I-3 provides relative importance of key items in Nov 2013.
Table I-4, US, Relative Importance, 2009-2010 Weights, of Components in the Consumer Price Index, US City Average, Dec 2012
| All Items | 100.000 |
| Food and Beverages | 15.261 |
| Food | 14.312 |
| Food at home | 8.898 |
| Food away from home | 5.713 |
| Housing | 41.021 |
| Shelter | 31.681 |
| Rent of primary residence | 6.545 |
| Owners’ equivalent rent | 22.622 |
| Apparel | 3.564 |
| Transportation | 16.846 |
| Private Transportation | 15.657 |
| New vehicles | 3.189 |
| Used cars and trucks | 1.844 |
| Motor fuel | 5.462 |
| Gasoline | 5.274 |
| Medical Care | 7.163 |
| Medical care commodities | 1.714 |
| Medical care services | 5.448 |
| Recreation | 5.990 |
| Education and Communication | 6.779 |
| Other Goods and Services | 3.376 |
Refers to all urban consumers, covering approximately 87 percent of the US population (see http://www.bls.gov/cpi/cpiovrvw.htm#item1). Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/cpiri2011.pdf http://www.bls.gov/cpi/cpiriar.htm http://www.bls.gov/cpi/cpiri2012.pdf
Chart I-18 provides the US consumer price index for housing from 2001 to 2013. Housing prices rose sharply during the decade until the bump of the global recession and increased again in 2011-2012 with some stabilization. The CPI excluding housing would likely show much higher inflation. The commodity carry trades resulting from unconventional monetary policy have compressed income remaining after paying for indispensable shelter.
Chart I-18, US, Consumer Price Index, Housing, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm
Chart I-19 provides 12-month percentage changes of the housing CPI. Percentage changes collapsed during the global recession but have been rising into positive territory in 2011 and 2012-2013 but with the rate declining and then increasing.
Chart I-19, US, Consumer Price Index, Housing, 12-Month Percentage Change, NSA, 2001-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/cpi/data.htm
There have been waves of consumer price inflation in the US in 2011 and into 2012 (Section IA and earlier at http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-zero-interest-rates-world.html) that are illustrated in Table I-5. The first wave occurred in Jan-Apr 2011 and was caused by the carry trade of commodity prices induced by unconventional monetary policy of zero interest rates. Cheap money at zero opportunity cost in environment of risk appetite was channeled into financial risk assets, causing increases in commodity prices. The annual equivalent rate of increase of the all-items CPI in Jan-Apr 2011 was 4.6 percent and the CPI excluding food and energy increased at annual equivalent rate of 2.1 percent. The second wave occurred during the collapse of the carry trade from zero interest rates to exposures in commodity futures because of risk aversion in financial markets created by the sovereign debt crisis in Europe. The annual equivalent rate of increase of the all-items CPI dropped to 3.0 percent in May-Jun 2011 while the annual equivalent rate of the CPI excluding food and energy increased at 3.0 percent. In the third wave in Jul-Sep 2011, annual equivalent CPI inflation rose to 3.3 percent while the core CPI increased at 2.0 percent. The fourth wave occurred in the form of increase of the CPI all-items annual equivalent rate to 0.6 percent in Oct-Nov 2011 with the annual equivalent rate of the CPI excluding food and energy remaining at 2.4 percent. The fifth wave occurred in Dec 2011 to Jan 2012 with annual equivalent headline inflation of 1.2 percent and core inflation of 2.4 percent. In the sixth wave, headline CPI inflation increased at annual equivalent 3.7 percent in Feb-Mar 2012 and core CPI inflation at 1.8 percent but including Apr 2012, the annual equivalent inflation of the headline CPI was 2.4 percent in Feb-Apr 2012 and 2.0 percent for the core CPI. The seventh wave in May-Jul occurred with annual equivalent inflation of 0.0 percent for the headline CPI in May-Jul 2012 and 2.0 percent for the core CPI. The eighth wave is with annual equivalent inflation of 6.2 percent in Aug-Sep 2012 but 4.9 percent including Oct. In the ninth wave, annual equivalent inflation in Nov 2012 was minus 2.4 percent under the new shock of risk aversion and 0.0 percent in Dec 2012 with annual equivalent of minus 0.8 percent in Nov 2012-Jan 2013 and 2.0 percent for the core CPI. In the tenth wave, annual equivalent of headline CPI was 8.7 percent in Feb 2013 and 2.4 percent for the core CPI. In the eleventh wave, annual equivalent was minus 3.5 percent in Mar-Apr 2013 and 1.2 percent for the core index. In the twelfth wave, annual equivalent inflation was 2.7 percent in May-Sep 2013 and 1.9 percent for the core CPI. In the thirteenth wave, annual equivalent CPI inflation in Oct-Nov 2013 was minus 0.6 percent and 1.8 percent for the core CPI. The conclusion is that inflation accelerates and decelerates in unpredictable fashion because of shocks or risk aversion and portfolio reallocations in carry trades from zero interest rates to commodity derivatives.
Table I-5, US, Headline and Core CPI Inflation Monthly SA and 12 Months NSA ∆%
| All Items SA Month | All Items NSA 12 month | Core SA | Core NSA | |
| Nov 2013 | 0.0 | 1.2 | 0.2 | 1.7 |
| Oct | -0.1 | 1.0 | 0.1 | 1.7 |
| AE ∆% Oct-Nov | -0.6 | 1.8 | ||
| Sep | 0.2 | 1.2 | 0.1 | 1.7 |
| Aug | 0.1 | 1.5 | 0.1 | 1.8 |
| Jul | 0.2 | 2.0 | 0.2 | 1.7 |
| Jun | 0.5 | 1.8 | 0.2 | 1.6 |
| May | 0.1 | 1.4 | 0.2 | 1.7 |
| AE ∆% May-Sep | 2.7 | 1.9 | ||
| Apr | -0.4 | 1.1 | 0.1 | 1.7 |
| Mar | -0.2 | 1.5 | 0.1 | 1.9 |
| AE ∆% Mar-Apr | -3.5 | 1.2 | ||
| Feb | 0.7 | 2.0 | 0.2 | 2.0 |
| AE ∆% Feb | 8.7 | 2.4 | ||
| Jan | 0.0 | 1.6 | 0.3 | 1.9 |
| Dec 2012 | 0.0 | 1.7 | 0.1 | 1.9 |
| Nov | -0.2 | 1.8 | 0.1 | 1.9 |
| AE ∆% Nov-Jan | -0.8 | 2.0 | ||
| Oct | 0.2 | 2.2 | 0.2 | 2.0 |
| Sep | 0.5 | 2.0 | 0.2 | 2.0 |
| Aug | 0.5 | 1.7 | 0.1 | 1.9 |
| AE ∆% Aug-Oct | 4.9 | 2.0 | ||
| Jul | 0.0 | 1.4 | 0.1 | 2.1 |
| Jun | 0.1 | 1.7 | 0.2 | 2.2 |
| May | -0.1 | 1.7 | 0.2 | 2.3 |
| AE ∆% May-Jul | 0.0 | 2.0 | ||
| Apr | 0.0 | 2.3 | 0.2 | 2.3 |
| Mar | 0.3 | 2.7 | 0.2 | 2.3 |
| Feb | 0.3 | 2.9 | 0.1 | 2.2 |
| AE ∆% Feb-Apr | 2.4 | 2.0 | ||
| Jan | 0.2 | 2.9 | 0.2 | 2.3 |
| Dec 2011 | 0.0 | 3.0 | 0.2 | 2.2 |
| AE ∆% Dec-Jan | 1.2 | 2.4 | ||
| Nov | 0.1 | 3.4 | 0.2 | 2.2 |
| Oct | 0.0 | 3.5 | 0.2 | 2.1 |
| AE ∆% Oct-Nov | 0.6 | 2.4 | ||
| Sep | 0.3 | 3.9 | 0.1 | 2.0 |
| Aug | 0.3 | 3.8 | 0.2 | 2.0 |
| Jul | 0.2 | 3.6 | 0.2 | 1.8 |
| AE ∆% Jul-Sep | 3.3 | 2.0 | ||
| Jun | 0.1 | 3.6 | 0.2 | 1.6 |
| May | 0.4 | 3.6 | 0.3 | 1.5 |
| AE ∆% May-Jun | 3.0 | 3.0 | ||
| Apr | 0.3 | 3.2 | 0.2 | 1.3 |
| Mar | 0.5 | 2.7 | 0.1 | 1.2 |
| Feb | 0.4 | 2.1 | 0.2 | 1.1 |
| Jan | 0.3 | 1.6 | 0.2 | 1.0 |
| AE ∆% Jan-Apr | 4.6 | 2.1 | ||
| Dec 2010 | 0.5 | 1.5 | 0.1 | 0.8 |
| Nov | 0.2 | 1.1 | 0.1 | 0.8 |
| Oct | 0.3 | 1.2 | 0.0 | 0.6 |
| Sep | 0.1 | 1.1 | 0.1 | 0.8 |
| Aug | 0.2 | 1.1 | 0.1 | 0.9 |
| Jul | 0.2 | 1.2 | 0.1 | 0.9 |
| Jun | 0.0 | 1.1 | 0.1 | 0.9 |
| May | 0.0 | 2.0 | 0.1 | 0.9 |
| Apr | 0.0 | 2.2 | 0.0 | 0.9 |
| Mar | 0.0 | 2.3 | 0.0 | 1.1 |
| Feb | -0.1 | 2.1 | 0.1 | 1.3 |
| Jan | 0.1 | 2.6 | -0.1 | 1.6 |
Note: Core: excluding food and energy; AE: annual equivalent
Source: US Bureau of Labor Statistics
The behavior of the US consumer price index NSA from 2001 to 2013 is provided in Chart I-20. Inflation in the US is very dynamic without deflation risks that would justify symmetric inflation targets. The hump in 2008 originated in the carry trade from interest rates dropping to zero into commodity futures. There is no other explanation for the increase of the Cushing OK Crude Oil Future Contract 1 from $55.64/barrel on Jan 9, 2007 to $145.29/barrel on July 3, 2008 during deep global recession, collapsing under a panic of flight into government obligations and the US dollar to $37.51/barrel on Feb 13, 2009 and then rising by carry trades to $113.93/barrel on Apr 29, 2012, collapsing again and then recovering again to $105.23/barrel, all during mediocre economic recovery with peaks and troughs influenced by bouts of risk appetite and risk aversion (data from the US Energy Information Administration EIA, http://www.eia.gov/). The unwinding of the carry trade with the TARP announcement of toxic assets in banks channeled cheap money into government obligations (see Cochrane and Zingales 2009).
Chart I-20, US, Consumer Price Index, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
Chart I-21 provides 12-month percentage changes of the consumer price index from 2001 to 2013. There was no deflation or threat of deflation from 2008 into 2009. Commodity prices collapsed during the panic of toxic assets in banks. When stress tests in 2009 revealed US bank balance sheets in much stronger position, cheap money at zero opportunity cost exited government obligations and flowed into carry trades of risk financial assets. Increases in commodity prices drove again the all items CPI with interruptions during risk aversion originating in multiple fears but especially from the sovereign debt crisis of Europe.
Chart I-21, US, Consumer Price Index, 12-Month Percentage Change, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
The trend of increase of the consumer price index excluding food and energy in Chart I-22 does not reveal any threat of deflation that would justify symmetric inflation targets. There are mild oscillations in a neat upward trend.
Chart I-22, US, Consumer Price Index Excluding Food and Energy, NSA, 2001-2013
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
Chart I-23 provides 12-month percentage change of the consumer price index excluding food and energy. Past-year rates of inflation fell toward 1 percent from 2001 into 2003 because of the recession and the decline of commodity prices beginning before the recession with declines of real oil prices. Near zero interest rates with fed funds at 1 percent between Jun 2003 and Jun 2004 stimulated carry trades of all types, including in buying homes with subprime mortgages in expectation that low interest rates forever would increase home prices permanently, creating the equity that would permit the conversion of subprime mortgages into creditworthy mortgages (Gorton 2009EFM; see http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Inflation rose and then collapsed during the unwinding of carry trades and the housing debacle of the global recession. Carry trades into 2011 and 2012 gave a new impulse to CPI inflation, all items and core. Symmetric inflation targets destabilize the economy by encouraging hunts for yields that inflate and deflate financial assets, obscuring risk/return decisions on production, investment, consumption and hiring.
Chart I-23, US, Consumer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2001-2013
Source: US Bureau of Labor Statistics
Headline and core producer price indexes are in Table I-6. The headline PPI SA decreased 0.1 percent in Nov 2013 and increased 0.7 percent NSA in the 12 months ending in Nov 2013. The core PPI SA increased 0.1 percent in Nov 2013 and rose 1.3 percent in 12 months. Analysis of annual equivalent rates of change shows inflation waves similar to those worldwide. In the first wave, the absence of risk aversion from the sovereign risk crisis in Europe motivated the carry trade from zero interest rates into commodity futures that caused the average equivalent rate of 10.0 percent in the headline PPI in Jan-Apr 2011 and 4.0 percent in the core PPI. In the second wave, commodity futures prices collapsed in Jun 2011 with the return of risk aversion originating in the sovereign risk crisis of Europe. The annual equivalent rate of headline PPI inflation collapsed to 1.8 percent in May-Jun 2011 but the core annual equivalent inflation rate was higher at 2.4 percent. In the third wave, headline PPI inflation resuscitated with annual equivalent at 4.9 percent in Jul-Sep 2011 and core PPI inflation at 3.7 percent. Core PPI inflation was persistent throughout 2011, jumping from annual equivalent at 1.5 percent in the first four months of 2010 to 3.0 percent in 12 months ending in Dec 2011. Unconventional monetary policy is based on the proposition that core rates reflect more fundamental inflation and are thus better predictors of the future. In practice, the relation of core and headline inflation is as difficult to predict as future inflation (see IIID Supply Shocks in http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html). In the fourth wave, risk aversion originating in the lack of resolution of the European debt crisis caused unwinding of carry trades with annual equivalent headline PPI inflation of 0.6 percent in Oct-Nov 2011 and 1.8 percent in the core annual equivalent. In the fifth wave from Dec 2011 to Jan 2012, annual equivalent inflation was 0.0 percent for the headline index but 4.3 percent for the core index excluding food and energy. In the sixth wave, annual equivalent inflation in Feb-Mar 2012 was 2.4 percent for the headline PPI and 2.4 percent for the core. In the seventh wave, renewed risk aversion caused reversal of carry trades into commodity exposures with annual equivalent headline inflation of minus 4.7 percent in Apr-May 2012 while core PPI inflation was at annual equivalent 1.2 percent. In the eighth wave, annual equivalent inflation returned at 3.0 percent in Jun-Jul 2012 and 4.3 percent for the core index. In the ninth wave, relaxed risk aversion because of the announcement of the impaired bond buying program or Outright Monetary Transactions (OMT) of the European Central Bank (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html) induced carry trades that drove annual equivalent inflation of producer prices of the United States at 12.7 percent in Aug-Sep 2012 and 0.6 percent in the core index. In the tenth wave, renewed risk aversion caused annual equivalent inflation of minus 3.2 percent in Oct 2011-Dec 2012 in the headline index and 1.2 percent in the core index. In the eleventh wave, annual equivalent inflation was 5.5 percent in the headline index in Jan-Feb 2013 and 1.8 percent in the core index. In the twelfth wave, annual equivalent was minus 7.5 percent in Mar-Apr 2012 and 1.8 percent for the core index. In the thirteenth wave, annual equivalent inflation returned at 5.2 percent in May-Aug 2013 and 0.9 percent in the core index. In the fourteenth wave, portfolio reallocations away from commodities and into equities reversed commodity carry trade with annual equivalent inflation of minus 1.6 percent in Sep-Nov 2013 in the headline PPI and 1.6 percent in the core. It is almost impossible to forecast PPI inflation and its relation to CPI inflation. “Inflation surprise” by monetary policy could be proposed to climb along a downward sloping Phillips curve, resulting in higher inflation but lower unemployment (see Kydland and Prescott 1977, Barro and Gordon 1983 and past comments of this blog 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 http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). The architects of monetary policy would require superior inflation forecasting ability compared to forecasting naivety by everybody else. In practice, we are all naïve in forecasting inflation and other economic variables and events.
Table I-6, US, Headline and Core PPI Inflation Monthly SA and 12-Month NSA ∆%
| Finished | Finished | Finished Core SA | Finished Core NSA | |
| Nov 2013 | -0.1 | 0.7 | 0.1 | 1.3 |
| Oct | -0.2 | 0.3 | 0.2 | 1.4 |
| Sep | -0.1 | 0.3 | 0.1 | 1.2 |
| AE ∆% Sep-Nov | -1.6 | 1.6 | ||
| Aug | 0.4 | 1.4 | -0.1 | 1.1 |
| Jul | 0.2 | 2.1 | 0.1 | 1.3 |
| Jun | 0.6 | 2.3 | 0.2 | 1.6 |
| May | 0.5 | 1.6 | 0.1 | 1.7 |
| AE ∆% May-Aug | 5.2 | 0.9 | ||
| Apr | -0.7 | 0.5 | 0.1 | 1.7 |
| Mar | -0.6 | 1.1 | 0.2 | 1.7 |
| AE ∆% Mar-Apr | -7.5 | 1.8 | ||
| Feb | 0.7 | 1.8 | 0.1 | 1.8 |
| Jan | 0.2 | 1.5 | 0.2 | 1.8 |
| AE ∆% Jan-Feb | 5.5 | 1.8 | ||
| Dec 2012 | -0.1 | 1.4 | 0.2 | 2.1 |
| Nov | -0.5 | 1.5 | 0.1 | 2.2 |
| Oct | -0.2 | 2.3 | 0.0 | 2.2 |
| AE ∆% Oct-Dec | -3.2 | 1.2 | ||
| Sep | 1.0 | 2.1 | 0.1 | 2.4 |
| Aug | 1.0 | 1.9 | 0.0 | 2.6 |
| AE ∆% Aug-Sep | 12.7 | 0.6 | ||
| Jul | 0.4 | 0.5 | 0.5 | 2.6 |
| Jun | 0.1 | 0.7 | 0.2 | 2.6 |
| AE ∆% Jun-Jul | 3.0 | 4.3 | ||
| May | -0.6 | 0.6 | 0.1 | 2.7 |
| Apr | -0.2 | 1.8 | 0.1 | 2.7 |
| AE ∆% Apr-May | -4.7 | 1.2 | ||
| Mar | 0.1 | 2.8 | 0.2 | 2.9 |
| Feb | 0.3 | 3.4 | 0.2 | 3.1 |
| AE ∆% Feb-Mar | 2.4 | 2.4 | ||
| Jan | 0.1 | 4.1 | 0.4 | 3.1 |
| Dec 2011 | -0.1 | 4.7 | 0.3 | 3.0 |
| AE ∆% Dec-Jan | 0.0 | 4.3 | ||
| Nov | 0.4 | 5.6 | 0.1 | 3.0 |
| Oct | -0.3 | 5.8 | 0.2 | 2.9 |
| AE ∆% Oct-Nov | 0.6 | 1.8 | ||
| Sep | 0.9 | 7.0 | 0.3 | 2.8 |
| Aug | -0.3 | 6.6 | 0.1 | 2.7 |
| Jul | 0.6 | 7.1 | 0.5 | 2.7 |
| AE ∆% Jul-Sep | 4.9 | 3.7 | ||
| Jun | -0.1 | 6.9 | 0.3 | 2.3 |
| May | 0.4 | 7.1 | 0.1 | 2.1 |
| AE ∆% May-Jun | 1.8 | 2.4 | ||
| Apr | 0.7 | 6.6 | 0.3 | 2.3 |
| Mar | 0.7 | 5.6 | 0.3 | 2.0 |
| Feb | 1.1 | 5.4 | 0.3 | 1.8 |
| Jan | 0.7 | 3.6 | 0.4 | 1.6 |
| AE ∆% Jan-Apr | 10.0 | 4.0 | ||
| Dec 2010 | 0.9 | 3.8 | 0.2 | 1.4 |
| Nov | 0.6 | 3.4 | 0.0 | 1.2 |
| Oct | 0.7 | 4.3 | -0.1 | 1.6 |
| Sep | 0.4 | 3.9 | 0.2 | 1.6 |
| Aug | 0.4 | 3.3 | 0.1 | 1.3 |
| Jul | 0.3 | 4.1 | 0.1 | 1.5 |
| Jun | -0.3 | 2.7 | 0.1 | 1.1 |
| May | 0.0 | 5.1 | 0.3 | 1.3 |
| Apr | -0.2 | 5.4 | 0.0 | 0.9 |
| Mar | 0.7 | 5.9 | 0.2 | 0.9 |
| Feb | -0.7 | 4.2 | 0.0 | 1.0 |
| Jan | 1.0 | 4.5 | 0.3 | 1.0 |
Note: Core: excluding food and energy; AE: annual equivalent
Source: US Bureau of Labor Statistics
The US producer price index NSA from 2000 to 2013 is shown in Chart I-24. There are two episodes of decline of the PPI during recessions in 2001 and in 2008. Barsky and Kilian (2004) consider the 2001 episode as one in which real oil prices were declining when recession began. Recession and the fall of commodity prices instead of generalized deflation explain the behavior of US inflation in 2008.
Chart I-24, US, Producer Price Index, NSA, 2000-2013
Source: US Bureau of Labor Statistics
Twelve-month percentage changes of the PPI NSA from 2000 to 2013 are shown in Chart I-25. It may be possible to forecast trends a few months in the future under adaptive expectations but turning points are almost impossible to anticipate especially when related to fluctuations of commodity prices in response to risk aversion. In a sense, monetary policy has been tied to behavior of the PPI in the negative 12-month rates in 2001 to 2003 and then again in 2009 to 2010. Monetary policy following deflation fears caused by commodity price fluctuations would introduce significant volatility and risks in financial markets and eventually in consumption and investment.
Chart I-25, US, Producer Price Index, 12-Month Percentage Change NSA, 2000-2013
Source: US Bureau of Labor Statistics
The US PPI excluding food and energy from 2000 to 2013 is shown in Chart I-26. There is here again a smooth trend of inflation instead of prolonged deflation as in Japan.
Chart I-26, US, Producer Price Index Excluding Food and Energy, NSA, 2000-2013
Source: US Bureau of Labor Statistics
Twelve-month percentage changes of the producer price index excluding food and energy are shown in Chart I-27. Fluctuations replicate those in the headline PPI. There is an evident trend of increase of 12 months rates of core PPI inflation in 2011 but lower rates in 2012-2013.
Chart I-27, US, Producer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2000-2013
Source: US Bureau of Labor Statistics
The US producer price index of energy goods from 2000 to 2013 is in Chart I-28. There is a clear upward trend with fluctuations that would not occur under persistent deflation.
Chart I-28, US, Producer Price Index Finished Energy Goods, NSA, 2000-2013
Source: US Bureau of Labor Statistics
Chart I-29 provides 12-month percentage changes of the producer price index of energy goods from 2000 to 2013. Barsky and Kilian (2004) relate the episode of declining prices of energy goods in 2001 to 2002 to the analysis of decline of real oil prices. Interest rates dropping to zero during the global recession in 2008 induced carry trades that explain the rise of the PPI of energy goods toward 30 percent. Bouts of risk aversion with policy interest rates held close to zero explain the fluctuations in the 12-month rates of the PPI of energy goods in the expansion phase of the economy. Symmetric inflation targets induce significant instability in inflation and interest rates with adverse effects on financial markets and the overall economy.
Chart I-29, US, Producer Price Index Energy Goods, 12-Month Percentage Change, NSA, 2000-2013
Source: US Bureau of Labor Statistics
Table I-7, CPI All Items, CPI Core and CPI Housing, 12-Month Percentage Change, NSA 2001-2013
| Nov | CPI All Items | CPI Core ex Food and Energy | CPI Housing |
| 2013 | 1.2 | 1.7 | 2.1 |
| 2012 | 1.8 | 1.9 | 1.7 |
| 2011 | 3.4 | 2.2 | 1.9 |
| 2010 | 1.1 | 0.8 | 0.0 |
| 2009 | 1.8 | 1.7 | -0.3 |
| 2008 | 1.1 | 2.0 | 2.7 |
| 2007 | 4.3 | 2.3 | 3.1 |
| 2006 | 2.0 | 2.6 | 3.0 |
| 2005 | 3.5 | 2.1 | 4.0 |
| 2004 | 3.5 | 2.2 | 3.1 |
| 2003 | 1.8 | 1.1 | 2.2 |
| 2002 | 2.2 | 2.0 | 2.4 |
| 2001 | 1.9 | 2.8 | 3.1 |
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
Chart IIA2-1 provides prices of total US imports 2001-2013. Prices fell during the contraction of 2001. Import price inflation accelerated after unconventional monetary policy of near zero interest rates in 2003-2004 and quantitative easing by withdrawing supply with the suspension of 30-year Treasury bond auctions. Slow pace of adjusting fed funds rates from 1 percent by increments of 25 basis points in 17 consecutive meetings of the Federal Open Market Committee (FOMC) between Jun 2004 and Jun 2006 continued to give impetus to carry trades. The reduction of fed funds rates toward zero in 2008 fueled a spectacular global hunt for yields that caused commodity price inflation in the middle of a global recession. After risk aversion in 2009 because of the announcement of TARP (Troubled Asset Relief Program) creating anxiety on “toxic assets” in bank balance sheets (see Cochrane and Zingales 2009), prices collapsed because of unwinding carry trades. Renewed price increases returned with zero interest rates and quantitative easing. Monetary policy impulses in massive doses have driven inflation and valuation of risk financial assets in wide fluctuations over a decade.
Chart IIA2-1, US, Prices of Total US Imports 2001=100, 2001-2013
Source: Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-2 provides 12-month percentage changes of prices of total US imports from 2001 to 2013. The only plausible explanation for the wide oscillations is by the carry trade originating in unconventional monetary policy. Import prices jumped in 2008 during deep and protracted global recession driven by carry trades from zero interest rates to long, leveraged positions in commodity futures. Carry trades were unwound during the financial panic in the final quarter of 2008 that resulted in flight to government obligations. Import prices jumped again in 2009 with subdued risk aversion because US banks did not have unsustainable toxic assets. Import prices then fluctuated as carry trades were resumed during periods of risk appetite and unwound during risk aversion resulting from the European debt crisis.
Chart IIA2-2, US, Prices of Total US Imports, 12-Month Percentage Changes, 2001-2013
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
Chart IIA2-3 provides prices of US imports from 1982 to 2013. There is no similar episode to that of the increase of commodity prices in 2008 during a protracted and deep global recession with subsequent collapse during a flight into government obligations. Trade prices have been driven by carry trades created by unconventional monetary policy in the past decade.
Chart IIA2-3, US, Prices of Total US Imports, 2001=100, 1982-2013
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
Chart IIA2-4 provides 12-month percentage changes of US total imports from 1982 to 2013. There have not been wide consecutive oscillations as the ones during the global recession of IVQ2007 to IIQ2009.
Chart IIA2-4, US, Prices of Total US Imports, 12-Month Percentage Changes, 1982-2013
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
Chart IIA2-5 provides the index of US export prices from 2001 to 2013. Import and export prices have been driven by impulses of unconventional monetary policy in massive doses. The most recent segment in Chart IIA2-5 shows declining trend resulting from a combination of the world economic slowdown and the decline of commodity prices as carry trade exposures are unwound because of risk aversion to the sovereign debt crisis in Europe and slowdown in the world economy.
Chart IIA2-5, US, Prices of Total US Exports, 2001=100, 2001-2013
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
Chart IIA2-6 provides prices of US total exports from 1982 to 2013. The rise before the global recession from 2003 to 2008, driven by carry trades, is also unique in the series and is followed by another steep increase after risk aversion moderated in IQ2009.
Chart IIA2-6, US, Prices of Total US Exports, 2001=100, 1982-2013
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
Chart IIA2-7 provides 12-month percentage changes of total US exports from 1982 to 2013. The uniqueness of the oscillations around the global recession of IVQ2007 to IIQ2009 is clearly revealed.
Chart IIA2-7, US, Prices of Total US Exports, 12-Month Percentage Changes, 1982-2013
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
Twelve-month percentage changes of US prices of exports and imports are provided in Table IIA2-1. Import prices have been driven since 2003 by unconventional monetary policy of near zero interest rates influencing commodity prices according to moods of risk aversion and portfolio reallocations. In a global recession without risk aversion until the panic of Sep 2008 with flight to government obligations, import prices increased 21.4 percent in the 12 months ending in Jul 2008, 18.1 percent in the 12 months ending in Aug 2008, 13.1 percent in the 12 months ending in Sep 2008, 4.9 percent in the twelve months ending in Oct 2008. Import prices fell 5.9 percent in the 12 months ending in Nov 2008 when risk aversion developed in 2008 until mid 2009 (http://www.bls.gov/mxp/data.htm). Import prices rose again sharply in Nov 2010 by 4.1 percent and in Nov 2010 by 10.1 percent in the presence of zero interest rates with relaxed mood of risk aversion until carry trades were unwound in May 2011 and following months as shown by decrease of import prices by 1.4 percent in the 12 months ending in Nov 2012 and 2.0 percent in Dec 2012 and decrease of 0.3 percent in prices of exports in the 12 months ending in Dec 2012. Import prices increased 15.2 percent in the 12 months ending in Mar 2008, fell 14.9 percent in the 12 months ending in Mar 2009 and increased 11.2 percent in the 12 months ending in Mar 2010. Fluctuations are much sharper in imports because of the high content of oil that as all commodities futures contracts increases sharply with zero interest rates and risk appetite, contracting under risk aversion. There is similar behavior of prices of imports ex fuels, exports and exports ex agricultural goods but less pronounced than for commodity-rich prices dominated by carry trades from zero interest rates. A critical event resulting from unconventional monetary policy driving higher commodity prices by carry trades is the deterioration of the terms of trade, or export prices relative to import prices, that has adversely affected US real income growth relative to what it would have been in the absence of unconventional monetary policy. Europe, Japan and other advanced economies have experienced similar deterioration of their terms of trade. Because of unwinding carry trades of commodity futures because of risk aversion and portfolio reallocations, import prices decreased 1.5 percent in the 12 months ending in Nov 2013, export prices decreased 1.2 percent and prices of nonagricultural exports fell 1.6 percent. Imports excluding fuel fell 1.0 percent in the 12 months ending in Nov 2013. At the margin, price changes over the year in world exports and imports are decreasing or increasing moderately because of unwinding carry trades in a temporary mood of risk aversion and relative allocation of asset classes toward equities that reverses exposures in commodity futures.
Table IIA2-1, US, Twelve-Month Percentage Rates of Change of Prices of Exports and Imports
| Imports | Imports Ex Fuels | Exports | Exports Non-Ag | |
| Nov 2013 | -1.5 | -1.2 | -1.6 | -1.0 |
| Nov 2012 | -1.4 | 0.2 | 0.8 | -0.3 |
| Nov 2011 | 10.1 | 3.7 | 4.8 | 4.8 |
| Nov 2010 | 4.1 | 3.0 | 6.5 | 5.1 |
| Nov 2009 | 3.4 | -1.1 | 0.4 | 0.3 |
| Nov 2008 | -5.9 | 2.6 | -0.3 | 0.0 |
| Nov 2007 | 12.0 | 3.0 | 6.2 | 4.7 |
| Nov 2006 | 1.3 | 2.8 | 3.9 | 3.4 |
| Nov 2005 | 6.4 | 1.4 | 2.8 | 2.6 |
| Nov 2004 | 9.0 | 2.6 | 4.2 | 5.2 |
| Nov 2003 | 2.3 | 1.0 | 1.7 | 0.8 |
| Nov 2002 | 2.5 | NA | 1.0 | 0.3 |
| Nov 2001 | -8.8 | NA | -2.5 | -2.5 |
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
Table IIA2-2 provides 12-month percentage changes of the import price index all commodities from 2001 to 2013. Interest rates moving toward zero during unconventional monetary policy in 2008 induced carry trades into highly leveraged commodity derivatives positions that caused increases in 12-month percentage changes of import prices of around 20 percent. The flight into dollars and Treasury securities by fears of toxic assets in banks in the proposal of TARP (Cochrane and Zingales 2009) caused reversion of carry trades and collapse of commodity futures explaining sharp declines in trade prices in 2009. Twelve-month percentage changes of import prices at the end of 2012 and into 2013 occurred during another bout of risk aversion and portfolio reallocation.
Table IIA2-2, US, Twelve-Month Percentage Changes of Import Price Index All Commodities, 2001-2013
| Year | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
| 2001 | -0.7 | -0.8 | -2.6 | -4.1 | -4.4 | -5.6 | -7.4 | -8.8 | -9.1 |
| 2002 | -3.6 | -3.7 | -3.6 | -1.7 | -1.3 | -0.4 | 1.9 | 2.5 | 4.2 |
| 2003 | 1.8 | 1.0 | 2.2 | 2.3 | 2.0 | 0.7 | 0.8 | 2.3 | 2.4 |
| 2004 | 4.6 | 6.9 | 5.7 | 5.6 | 7.1 | 8.2 | 9.9 | 9.0 | 6.7 |
| 2005 | 8.4 | 5.9 | 7.4 | 8.2 | 8.2 | 9.9 | 8.2 | 6.4 | 8.0 |
| 2006 | 5.8 | 8.6 | 7.4 | 7.0 | 6.0 | 1.6 | -1.0 | 1.3 | 2.5 |
| 2007 | 2.1 | 1.2 | 2.3 | 2.8 | 1.9 | 4.8 | 9.1 | 12.0 | 10.6 |
| 2008 | 16.9 | 19.1 | 21.3 | 21.4 | 18.1 | 13.1 | 4.9 | -5.9 | -10.1 |
| 2009 | -16.4 | -17.3 | -17.5 | -19.1 | -15.3 | -12.0 | -5.6 | 3.4 | 8.6 |
| 2010 | 11.2 | 8.5 | 4.3 | 4.9 | 3.8 | 3.6 | 3.9 | 4.1 | 5.3 |
| 2011 | 11.9 | 12.9 | 13.6 | 13.7 | 12.9 | 12.7 | 11.1 | 10.1 | 8.5 |
| 2012 | 0.8 | -0.8 | -2.5 | -3.3 | -1.8 | -0.6 | 0.0 | -1.4 | -2.0 |
| 2013 | -2.7 | -1.8 | 0.1 | 0.9 | 0.0 | -0.7 | -1.6 | -1.5 |
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
There is finer detail in one-month percentage changes of imports of the US in Table IIA2-3. Carry trades into commodity futures induced by interest rates moving to zero in unconventional monetary policy caused sharp monthly increases in import prices for cumulative increase of 13.8 percent from Mar to Jul 2008 at average rate of 2.6 percent per month or annual equivalent in five months of 36.4 percent (3.1 percent in Mar 2008, 2.8 percent in Apr 2008, 2.8 percent in May 2008, 3.0 percent in Jun 2008 and 1.4 percent in Jul 2008, data from http://www.bls.gov/mxp/data.htm). There is no other explanation for increases in import prices during sharp global recession and contracting world trade. Import prices then fell 23.4 percent from Aug 2008 to Jan 2009 or at the annual equivalent rate of minus 41.4 percent in the flight to US government securities in fear of the need to buy toxic assets from banks in the TARP program (Cochrane and Zingales 2009). Risk aversion during the first sovereign debt crisis of the euro area in May-Jun 2010 caused decline of US import prices at the annual equivalent rate of 11.4 percent. US import prices have been driven by combinations of carry trades induced by unconventional monetary policy and bouts of risk aversion and portfolio reallocation (http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-zero-interest-rates-world.html). US import prices increased 0.5 percent in Jan 2013 and 0.9 percent in Feb 2013 for annual equivalent rate of 8.7 percent, similar to those in national price indexes worldwide, originating in carry trades from zero interest rates to commodity futures. Import prices fell 0.1 percent in Mar 2013, 0.7 percent in Apr 2013, 0.6 percent in May 2013 and 0.4 percent in Jun 2013. Import prices changed 0.1 percent in Jul 2013, increased 0.4 percent in Aug 2013 and increased 0.3 percent in Sep 2013. Portfolio reallocations into asset classes other than commodities explains declines of import prices by 0.6 percent in Oct 2013 and 0.6 percent in Nov 2013.
Table IIA2-3, US, One-Month Percentage Changes of Import Price Index All Commodities, 2001-2013
| Year | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
| 2001 | -0.5 | 0.2 | -0.4 | -1.5 | -0.1 | -0.1 | -2.3 | -1.5 | -1.0 |
| 2002 | 1.6 | 0.1 | -0.3 | 0.4 | 0.3 | 0.7 | 0.0 | -0.9 | 0.6 |
| 2003 | -3.1 | -0.7 | 0.9 | 0.5 | 0.0 | -0.5 | 0.1 | 0.5 | 0.7 |
| 2004 | 0.2 | 1.5 | -0.2 | 0.4 | 1.5 | 0.5 | 1.6 | -0.3 | -1.4 |
| 2005 | 0.9 | -0.8 | 1.2 | 1.2 | 1.4 | 2.1 | 0.1 | -1.9 | 0.0 |
| 2006 | 2.1 | 1.8 | 0.1 | 0.8 | 0.5 | -2.2 | -2.5 | 0.4 | 1.1 |
| 2007 | 1.4 | 0.9 | 1.2 | 1.3 | -0.3 | 0.6 | 1.5 | 3.2 | -0.2 |
| 2008 | 2.8 | 2.8 | 3.0 | 1.4 | -3.1 | -3.6 | -6.0 | -7.4 | -4.6 |
| 2009 | 1.1 | 1.7 | 2.7 | -0.6 | 1.5 | 0.2 | 0.8 | 1.5 | 0.2 |
| 2010 | 1.1 | -0.8 | -1.2 | 0.0 | 0.4 | 0.0 | 1.1 | 1.7 | 1.4 |
| 2011 | 2.6 | 0.1 | -0.6 | 0.1 | -0.4 | -0.1 | -0.4 | 0.7 | 0.0 |
| 2012 | -0.1 | -1.5 | -2.3 | -0.7 | 1.2 | 1.0 | 0.3 | -0.7 | -0.6 |
| 2013 | -0.7 | -0.6 | -0.4 | 0.1 | 0.4 | 0.3 | -0.6 | -0.6 |
Source: Bureau of Labor Statistics http://www.bls.gov/mxp/data.htm
Chart IIA2-8 shows the US monthly import price index of all commodities excluding fuels from 2001 to 2013. All curves of nominal values follow the same behavior under the influence of unconventional monetary policy. Zero interest rates without risk aversion result in jumps of nominal values while under strong risk aversion even with zero interest rates there are declines of nominal values.
Chart IIA2-8, US, Import Price Index All Commodities Excluding Fuels, 2001=100, 2001-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-9 provides 12-month percentage changes of the US import price index excluding fuels between 2001 and 2013. There is the same behavior of carry trades driving up without risk aversion and down with risk aversion prices of raw materials, commodities and food in international trade during the global recession of IVQ2007 to IIQ2009 and in previous and subsequent periods.
Chart IIA2-9, US, Import Price Index All Commodities Excluding Fuels, 12-Month Percentage Changes, 2002-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-10 provides the monthly US import price index ex petroleum from 2001 to 2013. Prices including or excluding commodities follow the same fluctuations and trends originating in impulses of unconventional monetary policy of zero interest rates.
Chart IIA2-10, US, Import Price Index ex Petroleum, 2001=100, 2000-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-11 provides the US import price index ex petroleum from 1985 to 2013. There is the same unique hump in 2008 caused by carry trades from zero interest rates to prices of commodities and raw materials.
Chart IIA2-11, US, Import Price Index ex Petroleum, 2001=100, 1985-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-12 provides 12-month percentage changes of the import price index ex petroleum from 1986 to 2013. The oscillations caused by the carry trade in increasing prices of commodities and raw materials without risk aversion and subsequently decreasing them during risk aversion are unique.
Chart IIA2-12, US, Import Price Index ex Petroleum, 12-Month Percentage Changes, 1986-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-13 of the US Energy Information Administration shows the price of WTI crude oil since the 1980s. Chart IA2-13 captures commodity price shocks during the past decade. The costly mirage of deflation was caused by the decline in oil prices during the recession of 2001. The upward trend after 2003 was promoted by the carry trade from near zero interest rates. The jump above $140/barrel during the global recession in 2008 at $145.29/barrel on Jul 3, 2008, can only be explained by the carry trade promoted by monetary policy of zero fed funds rate. After moderation of risk aversion, the carry trade returned with resulting sharp upward trend of crude prices. Risk aversion resulted in another drop in recent weeks followed by some recovery and renewed deterioration/increase.
Chart IIA2-13, US, Crude Oil Futures Contract
Source: US Energy Information Administration
http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RCLC1&f=D
The price index of US imports of petroleum and petroleum products in shown in Chart IIA2-14. There is similar behavior of the curves all driven by the same impulses of monetary policy.
Chart IIA2-14, US, Import Price Index of Petroleum and Petroleum Products, 2001=100, 2001-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-15 provides the price index of petroleum and petroleum products from 1982 to 2013. The rise in prices during the global recession in 2008 and the decline after the flight to government obligations is unique in the history of the series. Increases in prices of trade in petroleum and petroleum products were induced by carry trades and declines by unwinding carry trades in flight to government obligations.
Chart IIA2-15, US, Import Price Index of Petroleum and Petroleum Products, 2001=100, 1982-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-16 provides 12-month percentage changes of the price index of US imports of petroleum and petroleum products from 1982 to 2013. There were wider oscillations in this index from 1999 to 2001 (see Barsky and Killian 2004 for an explanation).
Chart IIA2-16, US, Import Price Index of Petroleum and Petroleum Products, 12-Month Percentage Changes, 1982-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
The price index of US exports of agricultural commodities is in Chart IIA2-17 from 2001 to 2013. There are similar fluctuations and trends as in all other price index originating in unconventional monetary policy repeated over a decade. The most recent segment in 2011 has declining trend in a new flight from risk resulting from the sovereign debt crisis in Europe followed by declines in Jun 2012 and Nov 2012 with stability/decline in Dec 2012 into 2013.
Chart IIA2-17, US, Exports Price Index of Agricultural Commodities, 2001=100, 2001-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-18 provides the price index of US exports of agricultural commodities from 1982 to 2013. The increase in 2008 in the middle of deep, protracted contraction was induced by unconventional monetary policy. The decline from 2008 into 2009 was caused by unwinding carry trades in a flight to government obligations. The increase into 2011 and current pause were also induced by unconventional monetary policy in waves of increases during relaxed risk aversion and declines during unwinding of positions because of aversion to financial risk.
Chart IIA2-18, US, Exports Price Index of Agricultural Commodities, 2001=100, 1982-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-19 provides 12-month percentage changes of the index of US exports of agricultural commodities from 1986 to 2013. The wide swings in 2008, 2009 and 2011 are only explained by unconventional monetary policy inducing carry trades from zero interest rates to commodity futures and reversals during risk aversion.
Chart IIA2-19, US, Exports Price Index of Agricultural Commodities, 12-Month Percentage Changes, 1986-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-20 shows the export price index of nonagricultural commodities from 2001 to 2013. Unconventional monetary policy of zero interest rates drove price behavior during the past decade. Policy has been based on the myth of stimulating the economy by climbing the negative slope of an imaginary short-term Phillips curve.
Chart IIA2-20, US, Exports Price Index of Nonagricultural Commodities, 2001=100, 2001-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Chart IIA2-21 provides a longer perspective of the price index of US nonagricultural commodities from 1982 to 2013. Increases and decreases around the global contraction after 2007 were caused by carry trade induced by unconventional monetary policy.
Chart IIA2-21, US, Exports Price Index of Nonagricultural Commodities, 2001=100, 1982-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
Finally, Chart IIA2-22 provides 12-month percentage changes of the price index of US exports of nonagricultural commodities from 1986 to 2013. The wide swings before, during and after the global recession beginning in 2007 were caused by carry trades induced by unconventional monetary policy.
Chart IIA2-22, US, Exports Price Index of Nonagricultural Commodities, 12-Month Percentage Changes, 1986-2013
Source: US Bureau of Labor Statistics
http://www.bls.gov/mxp/data.htm
IE Theory and Reality of Economic History and Monetary Policy Based on Fear of Deflation. Fear of deflation as had occurred during the Great Depression and in Japan was used as an argument for the first round of unconventional monetary policy with 1 percent interest rates from Jun 2003 to Jun 2004 and quantitative easing in the form of withdrawal of supply of 30-year securities by suspension of the auction of 30-year Treasury bonds with the intention of reducing mortgage rates (for fear of deflation see Pelaez and Pelaez, International Financial Architecture (2005), 18-28, and Pelaez and Pelaez, The Global Recession Risk (2007), 83-95). The financial crisis and global recession were caused by interest rate and housing subsidies and affordability policies that encouraged high leverage and risks, low liquidity and unsound credit (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4). Several past comments of this blog elaborate on these arguments, among which: http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html
If the forecast of the central bank is of recession and low inflation with controlled inflationary expectations, monetary policy should consist of lowering the short-term policy rate of the central bank, which in the US is the fed funds rate. The intended effect is to lower the real rate of interest (Svensson 2003LT, 146-7). The real rate of interest, r, is defined as the nominal rate, i, adjusted by expectations of inflation, π*, with all variables defined as proportions: (1+r) = (1+i)/(1+π*) (Fisher 1930). If i, the fed funds rate, is lowered by the Fed, the numerator of the right-hand side is lower such that if inflationary expectations, π*, remain unchanged, the left-hand (1+r) decreases, that is, the real rate of interest, r, declines. Expectations of lowering short-term real rates of interest by policy of the Federal Open Market Committee (FOMC) fixing a lower fed funds rate would lower long-term real rates of interest, inducing with a lag investment and consumption, or aggregate demand, that can lift the economy out of recession. Inflation also increases with a lag by higher aggregate demand and inflation expectations (Fisher 1933). This reasoning explains why the FOMC lowered the fed funds rate in Dec 2008 to 0 to 0.25 percent and left it unchanged.
The fear of the Fed is expected deflation or negative π*. In that case, (1+ π*) < 1, and (1+r) would increase because the right-hand side of the equation would be divided by a fraction. A simple numerical example explains the effect of deflation on the real rate of interest. Suppose that the nominal rate of interest or fed funds rate, i, is 0.25 percent, or in proportion 0.25/100 = 0.0025, such that (1+i) = 1.0025. Assume now that economic agents believe that inflation will remain at 1 percent for a long period, which means that π* = 1 percent, or in proportion 1/100 =0.01. The real rate of interest, using the equation, is (1+0.0025)/(1+0.01) = (1+r) = 0.99257, such that r = 0.99257 - 1 = -0.00743, which is a proportion equivalent to –(0.00743)100 = -0.743 percent. That is, Fed policy has created a negative real rate of interest of 0.743 percent with the objective of inducing aggregate demand by higher investment and consumption. This is true if expected inflation, π*, remains at 1 percent. Suppose now that expectations of deflation become generalized such that π* becomes -1 percent, that is, the public believes prices will fall at the rate of 1 percent in the foreseeable future. Then the real rate of interest becomes (1+0.0025) divided by (1-0.01) equal to (1.0025)/(0.99) = (1+r) = 1.01263, or r = (1.01263-1) = 0.01263, which results in positive real rate of interest of (0.01263)100 = 1.263 percent.
Irving Fisher also identified the impact of deflation on debts as an important cause of deepening contraction of income and employment during the Great Depression illustrated by an actual example (Fisher 1933, 346):
“By March, 1933, liquidation had reduced the debts about 20 percent, but had increased the dollar about 75 percent, so that the real debt, that is the debt measured in terms of commodities, was increased about 40 percent [100%-20%)X(100%+75%) =140%]. Unless some counteracting cause comes along to prevent the fall in the price level, such a depression as that of 1929-1933 (namely when the more the debtors pay the more they owe) tends to continue, going deeper, in a vicious spiral, for many years. There is then no tendency of the boat to stop tipping until it has capsized”
The nominal rate of interest must always be nonnegative, that is, i ≥ 0 (Hick 1937, 154-5):
“If the costs of holding money can be neglected, it will always be profitable to hold money rather than lend it out, if the rate of interest is not greater than zero. Consequently the rate of interest must always be positive. In an extreme case, the shortest short-term rate may perhaps be nearly zero. But if so, the long-term rate must lie above it, for the long rate has to allow for the risk that the short rate may rise during the currency of the loan, and it should be observed that the short rate can only rise, it cannot fall”
The interpretation by Hicks of the General Theory of Keynes is the special case in which at interest rates close to zero liquidity preference is infinitely or perfectly elastic, that is, the public holds infinitely large cash balances at that near zero interest rate because there is no opportunity cost of foregone interest. Increases in the money supply by the central bank would not decrease interest rates below their near zero level, which is called the liquidity trap. The only alternative public policy would consist of fiscal policy that would act similarly to an increase in investment, increasing employment without raising the interest rate.
An influential view on the policy required to steer the economy away from the liquidity trap is provided by Paul Krugman (1998). Suppose the central bank faces an increase in inflation. An important ingredient of the control of inflation is the central bank communicating to the public that it will maintain a sustained effort by all available policy measures and required doses until inflation is subdued and price stability is attained. If the public believes that the central bank will control inflation only until it declines to a more benign level but not sufficiently low level, current expectations will develop that inflation will be higher once the central bank abandons harsh measures. During deflation and recession the central bank has to convince the public that it will maintain zero interest rates and other required measures until the rate of inflation returns convincingly to a level consistent with expansion of the economy and stable prices. Krugman (1998, 161) summarizes the argument as:
“The ineffectuality of monetary policy in a liquidity trap is really the result of a looking-glass version of the standard credibility problem: monetary policy does not work because the public expects that whatever the central bank may do now, given the chance, it will revert to type and stabilize prices near their current level. If the central bank can credibly promise to be irresponsible—that is, convince the market that it will in fact allow prices to rise sufficiently—it can bootstrap the economy out of the trap”
This view is consistent with results of research by Christina Romer that “the rapid rates of growth of real output in the mid- and late 1930s were largely due to conventional aggregate demand stimulus, primarily in the form of monetary expansion. My calculations suggest that in the absence of these stimuli the economy would have remained depressed far longer and far more deeply than it actually did” (Romer 1992, 757-8, cited in Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 210-2). The average growth rate of the money supply in 1933-1937 was 10 percent per year and increased in the early 1940s. Romer calculates that GDP would have been much lower without this monetary expansion. The growth of “the money supply was primarily due to a gold inflow, which was in turn due to the devaluation in 1933 and to capital flight from Europe because of political instability after 1934” (Romer 1992, 759). Gold inflow coincided with the decline in real interest rates in 1933 that remained negative through the latter part of the 1930s, suggesting that they could have caused increases in spending that was sensitive to declines in interest rates. Bernanke finds dollar devaluation against gold to have been important in preventing further deflation in the 1930s (Bernanke 2002):
“There have been times when exchange rate policy has been an effective weapon against deflation. A striking example from US history is Franklin Roosevelt’s 40 percent devaluation of the dollar against gold in 1933-34, enforced by a program of gold purchases and domestic money creation. The devaluation and the rapid increase in money supply it permitted ended the US deflation remarkably quickly. Indeed, consumer price inflation in the United States, year on year, went from -10.3 percent in 1932 to -5.1 percent in 1933 to 3.4 percent in 1934. The economy grew strongly, and by the way, 1934 was one of the best years of the century for the stock market”
Fed policy is seeking what Irving Fisher proposed “that great depressions are curable and preventable through reflation and stabilization” (Fisher 1933, 350).
The President of the Federal Reserve Bank of Chicago argues that (Charles Evans 2010):
“I believe the US economy is best described as being in a bona fide liquidity trap. Highly plausible projections are 1 percent for core Personal Consumption Expenditures (PCE) inflation at the end of 2012 and 8 percent for the unemployment rate. For me, the Fed’s dual mandate misses are too large to shrug off, and there is currently no policy conflict between improving employment and inflation outcomes”
There are two types of monetary policies that could be used in this situation. First, the Fed could announce a price-level target to be attained within a reasonable time frame (Evans 2010):
“For example, if the slope of the price path is 2 percent and inflation has been underunning the path for some time, monetary policy would strive to catch up to the path. Inflation would be higher than 2 percent for a time until the path was reattained”
Optimum monetary policy with interest rates near zero could consist of “bringing the price level back up to a level even higher than would have prevailed had the disturbance never occurred” (Gauti Eggertsson and Michael Woodford 2003, 207). Bernanke (2003JPY) explains as follows:
“Failure by the central bank to meet its target in a given period leads to expectations of (and public demands for) increased effort in subsequent periods—greater quantities of assets purchased on the open market for example. So even if the central bank is reluctant to provide a time frame for meetings its objective, the structure of the price-level objective provides a means for the bank to commit to increasing its anti-deflationary efforts when its earlier efforts prove unsuccessful. As Eggertsson and Woodford show, the expectations that an increasing price level gap will give rise to intensified effort by the central bank should lead the public to believe that ultimately inflation will replace deflation, a belief that supports the central bank’s own objectives by lowering the current real rate of interest”
Second, the Fed could use its balance sheet to increase purchases of long-term securities together with credible commitment to maintain the policy until the dual mandates of maximum employment and price stability are attained.
In the restatement of the liquidity trap and large-scale policies of monetary/fiscal stimulus, Krugman (1998, 162) finds:
“In the traditional open economy IS-LM model developed by Robert Mundell [1963] and Marcus Fleming [1962], and also in large-scale econometric models, monetary expansion unambiguously leads to currency depreciation. But there are two offsetting effects on the current account balance. On one side, the currency depreciation tends to increase net exports; on the other side, the expansion of the domestic economy tends to increase imports. For what it is worth, policy experiments on such models seem to suggest that these effects very nearly cancel each other out.
Krugman (1998) uses a different dynamic model with expectations that leads to similar conclusions.
The central bank could also be pursuing competitive devaluation of the national currency in the belief that it could increase inflation to a higher level and promote domestic growth and employment at the expense of growth and unemployment in the rest of the world. An essay by Chairman Bernanke in 1999 on Japanese monetary policy received attention in the press, stating that (Bernanke 2000, 165):
“Roosevelt’s specific policy actions were, I think, less important than his willingness to be aggressive and experiment—in short, to do whatever it took to get the country moving again. Many of his policies did not work as intended, but in the end FDR deserves great credit for having the courage to abandon failed paradigms and to do what needed to be done”
Quantitative easing has never been proposed by Chairman Bernanke or other economists as certain science without adverse effects. What has not been mentioned in the press is another suggestion to the Bank of Japan (BOJ) by Chairman Bernanke in the same essay that is very relevant to current events and the contentious issue of ongoing devaluation wars (Bernanke 2000, 161):
“Because the BOJ has a legal mandate to pursue price stability, it certainly could make a good argument that, with interest rates at zero, depreciation of the yen is the best available tool for achieving its mandated objective. The economic validity of the beggar-thy-neighbor thesis is doubtful, as depreciation creates trade—by raising home country income—as well as diverting it. Perhaps not all those who cite the beggar-thy-neighbor thesis are aware that it had its origins in the Great Depression, when it was used as an argument against the very devaluations that ultimately proved crucial to world economic recovery. A yen trading at 100 to the dollar is in no one’s interest”
Chairman Bernanke is referring to the argument by Joan Robinson based on the experience of the Great Depression that: “in times of general unemployment a game of beggar-my-neighbour is played between the nations, each one endeavouring to throw a larger share of the burden upon the others” (Robinson 1947, 156). Devaluation is one of the tools used in these policies (Robinson 1947, 157). Banking crises dominated the experience of the United States, but countries that recovered were those devaluing early such that competitive devaluations rescued many countries from a recession as strong as that in the US (see references to Ehsan Choudhri, Levis Kochin and Barry Eichengreen in Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 205-9; for the case of Brazil that devalued early in the Great Depression recovering with an increasing trade balance see Pelaez, 1968, 1968b, 1972; Brazil devalued and abandoned the gold standard during crises in the historical period as shown by Pelaez 1976, Pelaez and Suzigan 1981). Beggar-my-neighbor policies did work for individual countries but the criticism of Joan Robinson was that it was not optimal for the world as a whole.
Chairman Bernanke (2013Mar 25) reinterprets devaluation and recovery from the Great Depression:
“The uncoordinated abandonment of the gold standard in the early 1930s gave rise to the idea of "beggar-thy-neighbor" policies. According to this analysis, as put forth by important contemporary economists like Joan Robinson, exchange rate depreciations helped the economy whose currency had weakened by making the country more competitive internationally. Indeed, the decline in the value of the pound after 1931 was associated with a relatively early recovery from the Depression by the United Kingdom, in part because of some rebound in exports. However, according to this view, the gains to the depreciating country were equaled or exceeded by the losses to its trading partners, which became less internationally competitive--hence, ‘beggar thy neighbor.’ Economists still agree that Smoot-Hawley and the ensuing tariff wars were highly counterproductive and contributed to the depth and length of the global Depression. However, modern research on the Depression, beginning with the seminal 1985 paper by Barry Eichengreen and Jeffrey Sachs, has changed our view of the effects of the abandonment of the gold standard. Although it is true that leaving the gold standard and the resulting currency depreciation conferred a temporary competitive advantage in some cases, modern research shows that the primary benefit of leaving gold was that it freed countries to use appropriately expansionary monetary policies. By 1935 or 1936, when essentially all major countries had left the gold standard and exchange rates were market-determined, the net trade effects of the changes in currency values were certainly small. Yet the global economy as a whole was much stronger than it had been in 1931. The reason was that, in shedding the strait jacket of the gold standard, each country became free to use monetary policy in a way that was more commensurate with achieving full employment at home.”
Nurkse (1944) raised concern on the contraction of trade by competitive devaluations during the 1930s. Haberler (1937) dwelled on the issue of flexible exchange rates. Bordo and James (2001) provide perceptive exegesis of the views of Haberler (1937) and Nurkse (1944) together with the evolution of thought by Haberler. Policy coordination among sovereigns may be quite difficult in practice even if there were sufficient knowledge and sound forecasts. Friedman (1953) provided strong case in favor of a system of flexible exchange rates.
Eichengreen and Sachs (1985) argue theoretically with measurements using a two-sector model that it is possible for series of devaluations to improve the welfare of all countries. There were adverse effects of depreciation on other countries but depreciation by many countries could be beneficial for all. The important counterfactual is if depreciations by many countries would have promoted faster recovery from the Great Depression. Depreciation in the model of Eichengreen and Sachs (1985) affected domestic and foreign economies through real wages, profitability, international competitiveness and world interest rates. Depreciation causes increase in the money supply that lowers world interest rates, promoting growth of world output. Lower world interest rates could compensate contraction of output from the shift of demand away from home goods originating in neighbor’s exchange depreciation. Eichengreen and Sachs (1985, 946) conclude:
“This much, however, is clear. We do not present a blanket endorsement of the competitive devaluations of the 1930s. Though it is indisputable that currency depreciation conferred macroeconomic benefits on the initiating country, because of accompanying policies the depreciations of the 1930s had beggar-thy-neighbor effects. Though it is likely that currency depreciation (had it been even more widely adopted) would have worked to the benefit of the world as a whole, the sporadic and uncoordinated approach taken to exchange-rate policy in the 1930s tended, other things being equal, to reduce the magnitude of the benefits.”
There could major difference in the current world economy. The initiating impulse for depreciation originates in zero interest rates on the fed funds rate. The dollar is the world’s reserve currency. Risk aversion intermittently channels capital flight to the safe haven of the dollar and US Treasury securities. In the absence of risk aversion, zero interest rates induce carry trades of short positions in dollars and US debt (borrowing) together with long leveraged exposures in risk financial assets such as stocks, emerging stocks, commodities and high-yield bonds. Without risk aversion, the dollar depreciates against every currency in the world. The dollar depreciated against the euro by 39.3 percent from USD 1.1423/EUR con Jun 26, 2003 to USD 1.5914/EUR on Jun 14, 2008 during unconventional monetary policy before the global recession (Table VI-1). Unconventional monetary policy causes devaluation of the dollar relative to other currencies, which can increases net exports of the US that increase aggregate economic activity (Yellen 2011AS). The country issuing the world’s reserve currency appropriates the advantage from initiating devaluation that in policy intends to generate net exports that increase domestic output.
Pelaez and Pelaez (Regulation of Banks and Finance (2009b), 208-209) summarize the experience of Brazil as follows:
“During 1927–9, Brazil accumulated ￡30 million of foreign exchange of which ￡20 million were deposited at its stabilization fund (Pelaez 1968, 43–4). After the decline in coffee prices and the first impact of the Great Depression in Brazil a hot money movement wiped out foreign exchange reserves. In addition, capital inflows stopped entirely. The deterioration of the terms of trade further complicated matters, as the value of exports in foreign currency declined abruptly. Because of this exchange crisis, the service of the foreign debt of Brazil became impossible. In August 1931, the federal government was forced to cancel the payment of principal on certain foreign loans. The balance of trade in 1931 was expected to yield ￡20 million whereas the service of the foreign debt alone amounted to ￡22.6 million. Part of the solution given to these problems was typical of the 1930s. In September 1931, the government of Brazil required that all foreign transactions were to be conducted through the Bank of Brazil. This monopoly of foreign exchange was exercised by the Bank of Brazil for the following three years. Export permits were granted only after the exchange derived from sales abroad was officially sold to the Bank, which in turn allocated it in accordance with the needs of the economy. An active black market in foreign exchange developed. Brazil was in the first group of countries that abandoned early the gold standard, in 1931, and suffered comparatively less from the Great Depression. The Brazilian federal government, advised by the BOE, increased taxes and reduced expenditures in 1931 to compensate a decline in custom receipts (Pelaez 1968, 40). Expenditures caused by a revolution in 1932 in the state of Sao Paulo and a drought in the northeast explain the deficit. During 1932–6, the federal government engaged in strong efforts to stabilize the budget. Apart from the deliberate efforts to balance the budget during the 1930s, the recovery in economic activity itself may have induced a large part of the reduction of the deficit (Ibid, 41). Brazil’s experience is similar to that of the United States in that fiscal policy did not promote recovery from the Great Depression.”
Is depreciation of the dollar the best available tool currently for achieving the dual mandate of higher inflation and lower unemployment? Bernanke (2002) finds dollar devaluation against gold to have been important in preventing further deflation in the 1930s (http://www.federalreserve.gov/boarddocs/speeches/2002/20021121/default.htm):
“Although a policy of intervening to affect the exchange value of the dollar is nowhere on the horizon today, it's worth noting that there have been times when exchange rate policy has been an effective weapon against deflation. A striking example from U.S. history is Franklin Roosevelt's 40 percent devaluation of the dollar against gold in 1933-34, enforced by a program of gold purchases and domestic money creation. The devaluation and the rapid increase in money supply it permitted ended the U.S. deflation remarkably quickly. Indeed, consumer price inflation in the United States, year on year, went from -10.3 percent in 1932 to -5.1 percent in 1933 to 3.4 percent in 1934.17 The economy grew strongly, and by the way, 1934 was one of the best years of the century for the stock market. If nothing else, the episode illustrates that monetary actions can have powerful effects on the economy, even when the nominal interest rate is at or near zero, as was the case at the time of Roosevelt's devaluation.”
Should the US devalue following Roosevelt? Alternatively, has monetary policy intended devaluation? Fed policy is seeking, deliberately or as a side effect, what Irving Fisher proposed “that great depressions are curable and preventable through reflation and stabilization” (Fisher, 1933, 350). The Fed has created not only high volatility of assets but also what many countries are regarding as a competitive devaluation similar to those criticized by Nurkse (1944). Yellen (2011AS, 6) admits that Fed monetary policy results in dollar devaluation with the objective of increasing net exports, which was the policy that Joan Robinson (1947) labeled as “beggar-my-neighbor” remedies for unemployment.
Friedman (1969) finds that the optimal rule for the quantity of money is deflation at a rate that results in a zero nominal interest rate (see Ireland 2003 and Cole and Kocherlakota 1998). Atkeson and Kehoe (2004) argue that central bankers are not inclined to implement policies that could result in deflation because of the interpretation of the Great Depression as closely related to deflation. They use panel data on inflation and growth of real output for 17 countries over more than 100 years. The time-series data for each individual country are broken into five-year events with deflation measured as average negative inflation and depression as average negative growth rate of real output. Atkeson and Kehoe (2004) find that the Great Depression from 1929 to 1934 is the only case of association between deflation and depression without any evidence whatsoever of such relation in any other period. Their conclusion is (Atkeson and Kehoe 2004, 99): “Our finding thus suggests that policymakers’ fear of anticipated policy-induced deflation that would result from following, say, the Friedman rule is greatly overblown.” Their conclusion on the experience of Japan is (Atkeson and Kehoe 2004, 99):
“Since 1960, Japan’s average growth rates have basically fallen monotonically, and since 1970, its average inflation rates have too. Attributing this 40-year slowdown to monetary forces is a stretch. More reasonable, we think, is that much of the slowdown is the natural pattern for a country that was far behind the world leaders and had begun to catch up.”
In the sample of Atkeson and Kehoe (2004), there are only eight five-year periods besides the Great Depression with both inflation and depression. Deflation and depression is shown in 65 cases with 21 of depression without deflation. There is no depression in 65 of 73 five-year periods and there is no deflation in 29 episodes of depression. There is a remarkable result of no depression in 90 percent of deflation episodes. Excluding the Great Depression, there is virtually no relation of deflation and depression. Atkeson and Kehoe (2004, 102) find that the average growth rate of Japan of 1.41 percent in the 1990s is “dismal” when compared with 3.20 percent in the United States but is not “dismal” when compared with 1.61 percent for Italy and 1.84 percent for France, which are also catch-up countries in modern economic growth (see Atkeson and Kehoe 1998). The conclusion of Atkeson and Kehoe (2004), without use of controls, is that there is no association of deflation and depression in their dataset.
Benhabib and Spiegel (2009) use a dataset similar to that of Atkeson and Kehoe (2004) but allowing for nonlinearity and inflation volatility. They conclude that in cases of low and negative inflation an increase of average inflation of 1 percent is associated with an increase of 0.31 percent of average annual growth. The analysis of Benhabib and Spiegel (2009) leads to the significantly different conclusion that inflation and economic performance are strongly associated for low and negative inflation. There is no claim of causality by Atkeson and Kehoe (2004) and Benhabib and Spiegel (2009).
Delfim Netto (1959) partly reprinted in Pelaez (1973) conducted two classical nonparametric tests (Mann 1945, Wallis and Moore 1941; see Kendall and Stuart 1968) with coffee-price data in the period of free markets from 1857 to 1906 with the following conclusions (Pelaez, 1976a, 280):
“First, the null hypothesis of no trend was accepted with high confidence; secondly, the null hypothesis of no oscillation was rejected also with high confidence. Consequently, in the nineteenth century international prices of coffee fluctuated but without long-run trend. This statistical fact refutes the extreme argument of structural weakness of the coffee trade.”
In his classic work on the theory of international trade, Jacob Viner (1937, 563) analyzed the “index of total gains from trade,” or “amount of gain per unit of trade,” denoted as T:
T= (∆Pe/∆Pi)∆Q
Where ∆Pe is the change in export prices, ∆Pi is the change in import prices and ∆Q is the change in export volume. Dorrance (1948, 52) restates “Viner’s index of total gain from trade” as:
“What should be done is to calculate an index of the value (quantity multiplied by price) of exports and the price of imports for any country whose foreign accounts are to be analysed. Then the export value index should be divided by the import price index. The result would be an index which would reflect, for the country concerned, changes in the volume of imports obtainable from its export income (i.e. changes in its "real" export income, measured in import terms). The present writer would suggest that this index be referred to as the ‘income terms of trade’ index to differentiate it from the other indexes at present used by economists.”
What really matters for an export activity especially during modernization is the purchasing value of goods that it exports in terms of prices of imports. For a primary producing country, the purchasing power of exports in acquiring new technology from the country providing imports is the critical measurement. The barter terms of trade of Brazil improved from 1857 to 1906 because international coffee prices oscillated without trend (Delfim Netto 1959) while import prices from the United Kingdom declined at the rate of 0.5 percent per year (Imlah 1958). The accurate measurement of the opportunity afforded by the coffee exporting economy was incomparably greater when considering the purchasing power in British prices of the value of coffee exports, or Dorrance’s (1948) income terms of trade.
The conventional theory that the terms of trade of Brazil deteriorated over the long term is without reality (Pelaez 1976a, 280-281):
“Moreover, physical exports of coffee by Brazil increased at the high average rate of 3.5 per cent per year. Brazil's exchange receipts from coffee-exporting in sterling increased at the average rate of 3.5 per cent per year and receipts in domestic currency at 4.5 per cent per year. Great Britain supplied nearly all the imports of the coffee economy. In the period of the free coffee market, British export prices declined at the rate of 0.5 per cent per year. Thus, the income terms of trade of the coffee economy improved at the relatively satisfactory average rate of 4.0 per cent per year. This is only a lower bound of the rate of improvement of the terms of trade. While the quality of coffee remained relatively constant, the quality of manufactured products improved significantly during the fifty-year period considered. The trade data and the non-parametric tests refute conclusively the long-run hypothesis. The valid historical fact is that the tropical export economy of Brazil experienced an opportunity of absorbing rapidly increasing quantities of manufactures from the "workshop" countries. Therefore, the coffee trade constituted a golden opportunity for modernization in nineteenth-century Brazil.”
Imlah (1958) provides decline of British export prices at 0.5 percent in the nineteenth century and there were no lost decades, depressions or unconventional monetary policies in the highly dynamic economy of England that drove the world’s growth impulse. Inflation in the United Kingdom between 1857 and 1906 is measured by the composite price index of O’Donoghue and Goulding (2004) at minus 7.0 percent or average rate of decline of 0.2 percent per year.
Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:
“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated. Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”
Cameron (1961) analyzes the mechanism by which the Industrial Revolution in Great Britain spread throughout Europe and Cameron (1967) analyzes the financing by banks of the Industrial Revolution in Great Britain. O’Donoghue and Goulding (2004) provide consumer price inflation in England since 1750 and MacFarlane and Mortimer-Lee (1994) analyze inflation in England over 300 years. Lucas (2004) estimates world population and production since the year 1000 with sustained growth of per capita incomes beginning to accelerate for the first time in English-speaking countries and in particular in the Industrial Revolution in Great Britain. The conventional theory is unequal distribution of the gains from trade and technical progress between the industrialized countries and developing economies (Singer 1950, 478):
“Dismissing, then, changes in productivity as a governing factor in changing terms of trade, the following explanation presents itself: the fruits of technical progress may be distributed either to producers (in the form of rising incomes) or to consumers (in the form of lower prices). In the case of manufactured commodities produced in more developed countries, the former method, i.e., distribution to producers through higher incomes, was much more important relatively to the second method, while the second method prevailed more in the case of food and raw material production in the underdeveloped countries. Generalizing, we may say -that technical progress in manufacturing industries showed in a rise in incomes while technical progress in the production of food and raw materials in underdeveloped countries showed in a fall in prices”
Temin (1997, 79) uses a Ricardian trade model to discriminate between two views on the Industrial Revolution with an older view arguing broad-based increases in productivity and a new view concentration of productivity gains in cotton manufactures and iron:
“Productivity advances in British manufacturing should have lowered their prices relative to imports. They did. Albert Imlah [1958] correctly recognized this ‘severe deterioration’ in the net barter terms of trade as a signal of British success, not distress. It is no surprise that the price of cotton manufactures fell rapidly in response to productivity growth. But even the price of woolen manufactures, which were declining as a share of British exports, fell almost as rapidly as the price of exports as a whole. It follows, therefore, that the traditional ‘old-hat’ view of the Industrial Revolution is more accurate than the new, restricted image. Other British manufactures were not inefficient and stagnant, or at least, they were not all so backward. The spirit that motivated cotton manufactures extended also to activities as varied as hardware and haberdashery, arms, and apparel.”
Phyllis Deane (1968, 96) estimates growth of United Kingdom gross national product (GNP) at around 2 percent per year for several decades in the nineteenth century. The facts that the terms of trade of Great Britain deteriorated during the period of epochal innovation and high rates of economic growth while the income terms of trade of the coffee economy of nineteenth-century Brazil improved at the average yearly rate of 4.0 percent from 1857 to 1906 disprove the hypothesis of weakness of trade as an explanation of relatively lower income and wealth. As Temin (1997) concludes, Britain did pass on lower prices and higher quality the benefits of technical innovation. Explanation of late modernization must focus on laborious historical research on institutions and economic regimes together with economic theory, data gathering and measurement instead of grand generalizations of weakness of trade and alleged neocolonial dependence (Stein and Stein 1970, 134-5):
“Great Britain, technologically and industrially advanced, became as important to the Latin American economy as to the cotton-exporting southern United States. [After Independence in the nineteenth century] Latin America fell back upon traditional export activities, utilizing the cheapest available factor of production, the land, and the dependent labor force.”
The experience of the United Kingdom with deflation and economic growth is relevant and rich. Table IE-1 uses yearly percentage changes of the composite index of prices of the United Kingdom of O’Donoghue and Goulding (2004). There are 73 declines of inflation in the 145 years from 1751 to 1896. Prices declined in 50.3 percent of 145 years. Some price declines were quite sharp and many occurred over several years. Table IE-1 also provides yearly percentage changes of the UK composite price index of O’Donoghue and Goulding (2004) from 1929 to 1934. Deflation was much sharper in continuous years in earlier periods than during the Great Depression. The United Kingdom could not have led the world in modern economic growth if there were meaningful causality from deflation to depression.
Table IE-1, United Kingdom, Negative Percentage Changes of Composite Price Index, 1751-1896, 1929-1934, Yearly ∆%
| Year | ∆% | Year | ∆% | Year | ∆% | Year | ∆% |
| 1751 | -2.7 | 1797 | -10.0 | 1834 | -7.8 | 1877 | -0.7 |
| 1753 | -2.7 | 1798 | -2.2 | 1841 | -2.3 | 1878 | -2.2 |
| 1755 | -6.0 | 1802 | -23.0 | 1842 | -7.6 | 1879 | -4.4 |
| 1758 | -0.3 | 1803 | -5.9 | 1843 | -11.3 | 1881 | -1.1 |
| 1759 | -7.9 | 1806 | -4.4 | 1844 | -0.1 | 1883 | -0.5 |
| 1760 | -4.5 | 1807 | -1.9 | 1848 | -12.1 | 1884 | -2.7 |
| 1761 | -4.5 | 1811 | -2.9 | 1849 | -6.3 | 1885 | -3.0 |
| 1768 | -1.1 | 1814 | -12.7 | 1850 | -6.4 | 1886 | -1.6 |
| 1769 | -8.2 | 1815 | -10.7 | 1851 | -3.0 | 1887 | -0.5 |
| 1770 | -0.4 | 1816 | -8.4 | 1857 | -5.6 | 1893 | -0.7 |
| 1773 | -0.3 | 1819 | -2.5 | 1858 | -8.4 | 1894 | -2.0 |
| 1775 | -5.6 | 1820 | -9.3 | 1859 | -1.8 | 1895 | -1.0 |
| 1776 | -2.2 | 1821 | -12.0 | 1862 | -2.6 | 1896 | -0.3 |
| 1777 | -0.4 | 1822 | -13.5 | 1863 | -3.6 | 1929 | -0.9 |
| 1779 | -8.5 | 1826 | -5.5 | 1864 | -0.9 | 1930 | -2.8 |
| 1780 | -3.4 | 1827 | -6.5 | 1868 | -1.7 | 1931 | -4.3 |
| 1785 | -4.0 | 1828 | -2.9 | 1869 | -5.0 | 1932 | -2.6 |
| 1787 | -0.6 | 1830 | -6.1 | 1874 | -3.3 | 1933 | -2.1 |
| 1789 | -1.3 | 1832 | -7.4 | 1875 | -1.9 | 1934 | 0.0 |
| 1791 | -0.1 | 1833 | -6.1 | 1876 | -0.3 |
Source:
O’Donoghue, Jim and Louise Goulding, 2004. Consumer Price Inflation since 1750. UK Office for National Statistics Economic Trends 604, Mar 2004, 38-46.
Lucas (2011May) estimates US economic growth in the long-term at 3 percent per year and about 2 percent per year in per capita terms. There are displacements from this trend caused by events such as wars and recessions but the economy then returns to trend. Historical US GDP data exhibit remarkable growth: Lucas (2011May) estimates an increase of US real income per person by a factor of 12 in the period from 1870 to 2010. The explanation by Lucas (2011May) of this remarkable growth experience is that government provided stability and education while elements of “free-market capitalism” were an important driver of long-term growth and prosperity. The analysis is sharpened by comparison with the long-term growth experience of G7 countries (US, UK, France, Germany, Canada, Italy and Japan) and Spain from 1870 to 2010. Countries benefitted from “common civilization” and “technology” to “catch up” with the early growth leaders of the US and UK, eventually growing at a faster rate. Significant part of this catch up occurred after World War II. If deflation causes depressions as embedded in the theory of unconventional monetary policy, the United Kingdom would not have been a growth leader in the nineteenth century while staying almost half of the time in deflation.
The eminent economist and historian Professor Rondo E. Cameron (1989, 3) searches for the answer of “why are some nations rich and others poor?” by analyzing economic history since Paleolithic times. Cameron (1989, 4) argues that:
“Policymakers and their staffs of experts, faced with the responsibility of proposing and implementing policies for development, frequently shrug off the potential contributions of historical analysis to the solution of their problems with the observation that the contemporary situation is unique and therefore history is irrelevant to their concerns. Such an attitude contains a double fallacy. In the first place, those who are ignorant of the past are not qualified to generalize about it. Second, it implicitly denies the uniformity of nature, including human behavior and the behavior of social institutions—an assumption on which all scientific inquiry is founded. Such attitudes reveal how easy it is, without historical perspective, to mistake the symptoms of a problem for its causes.”
Scholars detached from practical issues of economic policy are more likely to discover sound knowledge (Cohen and Nagel 1934). There is troublesome sacrifice of rigorous scientific objectivity in cutting the economic past by a procrustean bed fitting favored current economic policies.
There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:
“Not until the problem of full employment of our productive resources from the long-run, secular standpoint was upon us, were we compelled to give serious consideration to those factors and forces in our economy which tend to make business recoveries weak and anaemic (sic) and which tend to prolong and deepen the course of depressions. This is the essence of secular stagnation-sick recoveries which die in their infancy and depressions which feed on themselves and leave a hard and seemingly immovable core of unemployment. Now the rate of population growth must necessarily play an important role in determining the character of the output; in other words, the com-position of the flow of final goods. Thus a rapidly growing population will demand a much larger per capita volume of new residential building construction than will a stationary population. A stationary population with its larger proportion of old people may perhaps demand more personal services; and the composition of consumer demand will have an important influence on the quantity of capital required. The demand for housing calls for large capital outlays, while the demand for personal services can be met without making large investment expenditures. It is therefore not unlikely that a shift from a rapidly growing population to a stationary or declining one may so alter the composition of the final flow of consumption goods that the ratio of capital to output as a whole will tend to decline.”
The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). Youth workers would obtain employment at a premium in an economy with declining population. In fact, there is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages. This is merely another case of theory without reality with dubious policy proposals. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design.
In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):
Y = ∑isiyi (1)
This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):
∆Y = ∑i∆siy*i + ∑i∆yis*i (2)
The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:
“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”
The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. There are accentuated cyclic factors for both the entire population and the young population of ages 16 to 24 years. Table Summary provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would not be secular but immediate. All indicators of the labor market weakened sharply during the contraction and did not recover. Population continued to grow but all other variables collapsed and did not recover. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-6). Hansen (1938, 1939) finds secular stagnation in lower growth of an aging population. In the current US economy, Table Summary shows that population is dynamic while the labor market is fractured. There is key explanation in the behavior of the civilian labor force participation rate (CLFP) and the employment population ratio (EPOP) that collapsed during the global recession with inadequate recovery. Abandoning job searches are difficult to capture in labor statistics but likely explain the decline in the participation of the population in the labor force. Allowing for abandoning job searches, the total number of people unemployed or underemployed is 28.1 million or 17.2 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.html).
Table Summary Total, US, Total Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Millions and Percent
| ICP | FTE | EMP | CLF | CLFP | EPOP | UNE | |
| 2006 | 288.8 | 119.7 | 144.4 | 151.4 | 66.2 | 63.1 | 7.0 |
| 2009 | 235.8 | 112.6 | 139.9 | 154.1 | 65.4 | 59.3 | 14.3 |
| 2012 | 243.3 | 114.8 | 142.5 | 155.0 | 63.7 | 58.6 | 12.5 |
| 12/07 | 233.2 | 121.0 | 146.3 | 153.7 | 65.9 | 62.8 | 7.4 |
| 9/09 | 236.3 | 112.0 | 139.1 | 153.6 | 65.0 | 58.9 | 14.5 |
| 11/13 | 246.6 | 116.9 | 144.8 | 155.0 | 62.9 | 58.7 | 10.3 |
ICP: Total Noninstitutional Civilian Population; FT: Full-time Employment Level, EMP: Total Employment Level; CLF: Civilian Labor Force; CLFP: Civilian Labor Force Participation Rate; EPOP: Employment Population Ratio; UNE: Unemployment
Source: Bureau of Labor Statistics
The same situation is present in the labor market for young people in ages 16 to 24 years with data in Table Summary Youth. The youth noninstitutional civilian population (ICP) continued to increase during and after the global recession. There is the same disastrous labor market with decline for young people in employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP) and employment population ratio (EPOP). There are only increases for unemployment of young people (UNE) and youth unemployment rate (UNER). If aging were a factor of secular stagnation, growth of population of young people would attract a premium in remuneration in labor markets. The sad fact is that young people are also facing tough labor markets. The application of the theory of secular stagnation to the US economy and labor markets is void of reality in the form of key facts.
Table Summary Youth, US, Youth, Ages 16 to 24 Years, Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Millions and Percent
| ICP | EMP | CLF | CLFP | EPOP | UNE | UNER | |
| 2006 | 36.9 | 20.0 | 22.4 | 60.6 | 54.2 | 2.4 | 10.5 |
| 2009 | 37.6 | 17.6 | 21.4 | 56.9 | 46.9 | 3.8 | 17.6 |
| 2012 | 38.8 | 17.8 | 21.3 | 54.9 | 46.0 | 3.5 | 16.2 |
| 12/07 | 37.5 | 19.4 | 21.7 | 57.8 | 51.6 | 2.3 | 10.7 |
| 9/09 | 37.6 | 17.0 | 20.7 | 55.2 | 45.1 | 3.8 | 18.2 |
| 11/13 | 38.8 | 18.1 | 20.8 | 53.7 | 46.7 | 2.7 | 13.1 |
ICP: Youth Noninstitutional Civilian Population; EMP: Youth Employment Level; CLF: Youth Civilian Labor Force; CLFP: Youth Civilian Labor Force Participation Rate; EPOP: Youth Employment Population Ratio; UNE: Unemployment; UNER: Youth Unemployment Rate
Source: Bureau of Labor Statistics http://www.bls.gov/home.htm
Nicholas Georgescu-Rogen (1960, 1) reprinted in Pelaez (1973) argues that “the agrarian economy has to this day remained a reality without theory.” The economic history of Latin America shares with the relation of deflation and unconventional monetary policy a more frustrating intellectual misfortune: theory without reality. MacFarlane and Mortimer-Lee (1994, 159) quote in a different context a phrase by Thomas Henry Huxley in the President’s Address to the British Association for the Advancement of Science on Sep 14, 1870 that is appropriate to these issues: “The great tragedy of science—the slaying of a beautiful hypothesis by an ugly fact.”
IIA Unresolved US Balance of Payments Deficits and Fiscal Imbalance Threatening Risk Premium on Treasury Securities. There are two subsection: IIA1 United States Unsustainable Deficit/debt and IIA2 Unresolved US Balance of Payments Deficits.
IIA1 United States Unsustainable Fiscal Deficit/Debt. Table IIA1-1 of the CBO (2012NovMBR, 2013BEOFeb5, 2013HBDFFeb5, 2013MEFFeb5, 2013Aug12) shows the significant worsening of United States fiscal affairs from 2007-2008 to 2009-2012. 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).
Table IAI-1, US, Budget Fiscal Year Totals, Billions of Dollars and % GDP
| 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | |
| Receipts | 2568 | 2524 | 2105 | 2163 | 2302 | 2450 |
| Outlays | 2729 | 2983 | 3518 | 3456 | 3599 | 3538 |
| Deficit | -161 | -459 | 1413 | 1294 | 1296 | 1087 |
| % GDP | -1.1 | -3.1 | -9.8 | -8.7 | -8.4 | -6.8 |
Source: CBO (2012NovMBR), CBO (2013BEOFeb5), CBO (2013HBDFeb5), CBO (2013Aug12).
Table IIA1-2 provides additional information required for understanding the deficit/debt situation of the United States. The table is divided into three parts: federal fiscal data for the years from 2009 to 2012; federal fiscal data for the years from 2005 to 2008; and Treasury debt held by the public from 2005 to 2012. 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 IVQ2012. In contrast, the expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/09/increasing-interest-rate-risk.html). Because of mediocre GDP growth, there are 28.3 million unemployed or underemployed in the United States for an effective unemployment rate of 17.4 percent (http://cmpassocregulationblog.blogspot.com/2013/09/twenty-eight-million-unemployed-or.html). Weakness of growth and employment creation is analyzed in IB Collapse of United States Dynamism of Income Growth and Employment Creation (http://cmpassocregulationblog.blogspot.com/2013/08/interest-rate-risks-duration-dumping.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 1973 to 2012. Federal outlays were 23.3 percent of GDP on average from 2009 to 2012, which is well above 20.4 percent of GDP on average from 1973 to 2012. The lower part of Table I-2 shows that debt held by the public swelled from $5803 billion in 2008 to $11,281 billion in 2012, by $5478 billion or 94.4 percent. Debt held by the public as percent of GDP or economic activity jumped from 39.3 percent in 2008 to 70.1 percent in 2012, which is well above the average of 38.0 percent from 1973 to 2012. 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 and Debt Held by the Public, Billions of Dollars and Percent of GDP
| Receipts | Outlays | Deficit (-), Surplus (+) | |
| $ Billions | |||
| 2012 | 2,450 | 3,537 | -1,087 |
| Fiscal Year 2011 | 2,303 | 3,598 | -1,296 |
| Fiscal Year 2010 | 2,163 | 3,456 | -1,294 |
| Fiscal Year 2009 | 2,105 | 3,518 | -1,413 |
| 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 |
| Fiscal Year 2007 | 2,568 | 2,729 | -161 |
| Fiscal Year 2006 | 2,407 | 2,655 | -248 |
| Fiscal Year 2005 | 2,154 | 2,472 | -318 |
| 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 |
Source: http://www.fms.treas.gov/mts/index.html 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.
Unusually low economic growth of average 2.2 percent of GDP in the current expansion (http://cmpassocregulationblog.blogspot.com/2013/09/increasing-interest-rate-risk.html) has had adverse impact on revenue generation. The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/09/increasing-interest-rate-risk.html). Because of mediocre GDP growth, there are 28.3 million unemployed or underemployed in the United States for an effective unemployment rate of 17.4 percent (http://cmpassocregulationblog.blogspot.com/2013/09/twenty-eight-million-unemployed-or.html). The impact of low growth on employment creation and labor market hiring is discussed in Subsection IB Collapse of United States Dynamism of Income Growth and Employment (http://cmpassocregulationblog.blogspot.com/2013/08/interest-rate-risks-duration-dumping.html). Table IIAI-3 provides total United States federal receipts from 2010 to 2012. Individual income taxes of $1132 billion, or $1.1 trillion, increased 25.9 percent from 2010 to 2012 and account for 46.2 percent of US total receipts in 2012. Total receipts stood at 15.2 percent of GDP in 2012, which is lower than 17.4 percent in the past 40 years (CBO 2013Aug12Av).
Table IIA1-3, United States, Total Receipts, Billions of Dollars and ∆%
| Major Source | 2010 | 2011 | 2012 | ∆% 2011-2012 |
| Individual Income Taxes | 899 | 1092 | 1132 | 3.7 |
| Corporate Income Taxes | 191 | 181 | 242 | 33.7 |
| Social Insurance | 865 | 819 | 845 | 3.2 |
| Other | 208 | 210 | 231 | 10.0 |
| Total | 2163 | 2302 | 2450 | 6.4 |
| % of GDP | 14.6 | 15.0 | 15.2 | NA |
Source: CBO (2012NovMBR), CBO (2013BEOFeb5), CBO 2013HBDFeb5), CBO (2013Aug12).
Total outlays of the federal government of the United States have grown to extremely high levels. Table IIA1-4 of the CBO (2013Aug12) provides total outlays in 2006 and 2012. Total outlays of $3537.1 billion in 2012, or $3.5 trillion, are higher by $882 billion, or $0.9 trillion, relative to $2655.1 billion in 2006, or $2.7 trillion. Outlays have grown from 19.4 percent of GDP in 2007 to 22.0 percent of GDP in 2012. Outlays as percent of GDP were on average 20.4 percent from 1973 to 2012 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 $2031.3 billion in 2012, by $619.5 billion. The final row shows that the total of social security, Medicare, Medicaid, Income Security, net interest and defense absorbs 79.6 percent of US total outlays. 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 | 2012 | % Total | |
| I TOTAL REVENUE $B | 2406.9 | 100.0 | 2450.2 | 100.0 |
| % GDP | 17.6 | 15.2 | ||
| Individual Income Taxes $B | 1043.9 | 1132.2 | ||
| % GDP | 7.6 | 7.0 | ||
| Corporate Income Taxes $B | 353.9 | 243.2 | ||
| % GDP | 2.6 | 1.5 | ||
| Social Insurance Taxes | 837.8 | 845.3 | ||
| % GDP | 6.1 | 5.3 | ||
| II TOTAL OUTLAYS | 2655.1 | 3537.1 | ||
| % GDP | 19.4 | 22.0 | ||
| Discretionary | 1016.6 | 1285.4 | ||
| % GDP | 7.4 | 8.0 | ||
| Defense | 520.0 | 670.5 | ||
| % GDP | 3.8 | 4.2 | ||
| Nondefense | 496.7 | 614.8 | ||
| % GDP | 3.6 | 3.8 | ||
| Mandatory | 1411.8 | 2031.3 | ||
| % GDP | 10.3 | 12.6 | ||
| Social Security | 543.9 | 767.7 | ||
| % GDP | 4.0 | 4.8 | ||
| Medicare | 376.8 | 551.2 | ||
| % GDP | 2.8 | 3.4 | ||
| Medicaid | 180.6 | 250.5 | ||
| % GDP | 1.3 | 1.6 | ||
| Income Security | 200.1 | 353.7 | ||
| % GDP | 1.5 | 2.2 | ||
| Offsetting Receipts | -144.1 | -210.0 | ||
| % GDP | -1.1 | -1.3 | ||
| Net Interest | 226.6 | 220.4 | ||
| % GDP | 1.7 | 1.4 | ||
| Defense +Medicare | 2048.0 | 77.1* | 2814.0 | 79.6* |
| % GDP | 15.0 | 17.5 |
*Percent of Total Outlays
Source: CBO (2013Aug12). 2013AugHBD. Historical budget data—August 2013. Washington, DC, Congressional Budget Office, Aug.
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 eight decades from 1930 to 2011. 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. 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 65.8 percent of GDP in 2011 and at 70.1 percent in 2012.
Table IIA1-5, United States Central Government Revenue, Expenditure, Deficit, Debt and GDP Growth 1930-2011
| Rev | Exp | Deficit | Debt | 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 | 17.0 | 17.2 | -0.2 | 37.9 | 6.5 |
| 1966 | 17.3 | 17.8 | -0.5 | 34.9 | 6.6 |
| 1967 | 18.4 | 19.4 | -1.1 | 32.9 | 2.7 |
| 1968 | 17.6 | 20.5 | -2.9 | 33.9 | 4.9 |
| 1969 | 19.7 | 19.4 | 0.3 | 29.3 | 3.1 |
| 1970s | |||||
| 1970 | 19.0 | 19.3 | -0.3 | 28.0 | 0.2 |
| 1971 | 17.3 | 19.5 | -2.1 | 28.1 | 3.3 |
| 1972 | 17.6 | 19.6 | -2.0 | 27.4 | 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 | 4.4 |
| 1999 | 19.2 | 17.9 | 1.3 | 38.2 | 4.8 |
| 2000s | |||||
| 2000 | 19.9 | 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 | 32.5 | 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 | 3.4 |
| 2006 | 17.6 | 19.4 | -1.8 | 35.3 | 2.7 |
| 2007 | 17.9 | 19.0 | -1.1 | 35.1 | 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 | 61.0 | 2.5 |
| 2011 | 15.0 | 23.4 | -8.4 | 65.8 | 1.8 |
| 2012 | 15.2 | 22.0 | -6.8 | 70.1 | 2.8 |
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).
Table IIA1-6 provides 40-year average ratios of fiscal variables to GDP before and after the revision by the Bureau of Economic Analysis (BEA) in Aug 2013 (http://www.bea.gov/iTable/index_nipa.cfm). The ratios are equal or slightly higher because of the addition of intellectual property to GDP estimates. There are no major changes.
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.
The capital budgeting decision of business requires the calculation of present value of projects. This calculation consists of a projection toward the horizon of planning of revenues net of costs, which are discounted to present value by the weighted average cost of capital. Business invests in the projects with highest net present value. The nonpartisan Congressional Budget Office (CBO) provides a similar service. Congress and the administration send budget proposals and legislation for evaluation by the CBO of their effects on federal government revenues, expenditures, deficit or surpluses and debt. The CBO does not provide its own policy proposals but analyzes alternative policies. The CBO uses state of the art knowledge but significant uncertainty remains because of the hurdle of projecting financial and economic variables to the future.
Table IIA1-7 provides the latest exercise by the CBO (2013BEOFeb5, 2012AugBEO, CBO2012NovCDR, 2013Sep11) of projecting the fiscal accounts of the US. Table IIA1-7 extends data back to 1995 with the projections of the CBO from 2013 to 2023, 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. Debt held by the public fell from 46.1 percent of GDP in 1995 to 31.4 percent of GDP in 2001.
Table IIA1-7, US, CBO Baseline Budget Outlook 2013-2023
| Out | Out | Deficit | Deficit | Debt | Debt | |
| 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 | 32.5 |
| 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 | 19.0 | -161 | -1.1 | 5,035 | 35.1 |
| 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 | 3,456 | 23.4 | -1,294 | -8.7 | 9,019 | 61.0 |
| 2011 | 3,598 | 23.4 | -1,296 | -8.4 | 10,128 | 65.8 |
| 2012 | 3,537 | 22.0 | -1,087 | -6.8 | 11,281 | 70.1 |
| 2013 | 3,455 | 20.8 | -642 | -3.9 | 12,036 | 72.5 |
| 2014 | 3,602 | 20.9 | -560 | -3.3 | 12,685 | 73.6 |
| 2015 | 3,777 | 20.7 | -378 | -2.1 | 13,156 | 72.1 |
| 2016 | 4,038 | 20.8 | -432 | -2.2 | 13,666 | 70.3 |
| 2017 | 4,261 | 20.6 | -482 | -2.3 | 14,223 | 68.8 |
| 2018 | 4,485 | 20.7 | -542 | -2.5 | 14,827 | 68.4 |
| 2019 | 4,752 | 21.0 | -648 | -2.9 | 15,537 | 68.6 |
| 2020 | 5,012 | 21.2 | -733 | -3.1 | 16,330 | 69.0 |
| 2021 | 5,275 | 21.4 | -782 | -3.2 | 17,168 | 69.6 |
| 2022 | 5,620 | 21.8 | -889 | -3.5 | 18,118 | 70.4 |
| 2023 | 5,855 | 21.8 | -895 | -3.3 | 19,070 | 71.1 |
| 2014 to 2018 | 20,163 | 20.7 | -2,394 | -2.5 | NA | NA |
| 2014 | 46,677 | 21.1 | -6,340 | -2.9 | 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).
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 to 18.5 percent of GDP in 2023, which is above the 40-year average of 17.4 percent of GDP while outlays fall from 23.4 percent of GDP in 2011 to 21.8 percent of GDP in 2023. The last row of Table IIA1-8 provides the CBO estimates of averages for 1973 to 2012 of 17.4 percent for revenues/GDP, 20.4 percent for outlays/GDP and 38.0 percent for debt/GDP. The United States faces tough adjustment of its fiscal accounts.
Table IIA1-8, US, Baseline CBO Projections of Federal Government Revenues, Outlays, Deficit and Debt as Percent of GDP
| Revenues | Outlays | Deficit | Debt | |
| 2011 | 15.0 | 23.4 | -8.4 | 65.8 |
| 2012 | 15.2 | 22.0 | -6.8 | 70.1 |
| 2013 | 17.0 | 20.8 | -3.9 | 72.5 |
| 2014 | 17.7 | 20.9 | -3.3 | 73.6 |
| 2015 | 18.6 | 20.7 | -2.1 | 72.1 |
| 2016 | 18.5 | 20.8 | -2.2 | 70.3 |
| 2017 | 18.3 | 20.6 | -2.3 | 68.8 |
| 2018 | 18.2 | 20.7 | -2.5 | 68.4 |
| 2019 | 18.1 | 21.0 | -2.9 | 68.6 |
| 2020 | 18.1 | 21.2 | -3.1 | 69.0 |
| 2021 | 18.2 | 21.4 | -3.2 | 69.6 |
| 2022 | 18.4 | 21.8 | -3.5 | 70.4 |
| 2023 | 18.5 | 21.8 | -3.3 | 71.0 |
| Total 2014-2018 | 18.3 | 20.7 | -2.5 | NA |
| Total 2014-2023 | 18.3 | 21.1 | -2.9 | NA |
| Average | 17.4 | 20.4 | -3.0 | 38.0 |
Source: CBO (2012AugBEO). CBO (2012NovCDR). CBO (2013BEOFeb5). CBO 2013HBDFeb5), CBO (2013Sep11), CBO (2013Aug12Av). Kim Kowaleski and Amber Marcellino.
Table IIA1-9 provides the long-term budget outlook of the CBO for 2013, 2023 and 2038. Revenues increase from 17.0 percent of GDP in 2013 to 19.7 percent in 2038. The growing stock of debt raises net interest spending from 1.3 percent of GDP in 2013 to 3.1 percent in 2023 and 4.9 percent 2038. Total spending increases from 20.8 percent of GDP in 2013 to 26.2 percent in 2038. Federal debt held by the public rises to 100.0 percent of GDP in 2038. 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
| 2013 | 2023 | 2038 | |
| Revenues | 17.0 | 18.5 | 19.7 |
| Total Noninterest Spending | 19.5 | 18.8 | 21.3 |
| Social Security | 4.9 | 5.3 | 6.2 |
| Medicare | 3.0 | 3.3 | 4.9 |
| Medicaid, CHIP and Exchange Subsidies | 1.7 | 2.6 | 3.2 |
| Other | 10.0 | 7.6 | 7.1 |
| Net Interest | 1.3 | 3.1 | 4.9 |
| Total Spending | 20.8 | 21.8 | 26.2 |
| Revenues Minus Total Noninterest Spending | -2.5 | -0.3 | -1.6 |
| Revenues Minus Total Spending | -3.9 | -3.3 | -6.4 |
| Federal Debt Held by the Public | 73.0 | 71.0 | 100.0 |
Source: CBO (2013Sep17). The 2013 long-term budget outlook. Washington, DC, Congressional Budget Office, Sep 17.
Chart I-1 provides actual federal debt held by the public as percent of GDP from 1790 to 2012 and projected by the CBO (2013Sep17) from 2013 to 2038. 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 70.1 percent in 2012 is the highest in the United States since 1950. The CBO (2013BEOFeb5) projects the ratio of debt of GDP of the United States to reach 100.0 percent in 2038, which will be more than double the average ratio of 38.0 percent in 1973-2012. The misleading debate on the so-called “fiscal cliff” has disguised the unsustainable path of United States fiscal affairs.
Chart IIA1-1, Congressional Budget Office, Federal Debt Held by the Public, Extended Baseline Projection, % of GDP
Source: CBO. 2013Sep17. The 2013 long-term budget outlook. Washington, DC, Congressional Budget Office, Sep 17.
IIA2 Unresolved US Balance of Payments Deficits and Fiscal Imbalance Threatening Risk Premium on Treasury Securities. The current account of the US balance of payments is provided in Table IIA2-1 for IIIQ2012 and IIIQ2013. 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 decreased from $122.5 billion in IIIQ2012 to $110.1 billion in IIIQ2013. The current account deficit seasonally adjusted at annual rate fell from 2.6 percent of GDP in IIIQ2012 to 2.3 percent of GDP in IIQ2013 and 2.2 percent of GDP in IIIQ2013. The ratio of the current account deficit to GDP has stabilized around 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
| IIIQ2012 | IIIQ2013 | Difference | |
| Goods Balance | -197,538 | -197,137 | 4,010 |
| X Goods | 382,343 | 392,155 | 2.6 ∆% |
| M Goods | -579,881 | -589,292 | 1.6 ∆% |
| Services Balance | 52,940 | 61,771 | 8,813 |
| X Services | 166,800 | 177,595 | 6.5 ∆% |
| M Services | -113,860 | -115,824 | 1.7 ∆% |
| Balance Goods and Services | -144,599 | -135,366 | -9,233 |
| Balance Income | 55,269 | 60,519 | 5,250 |
| Unilateral Transfers | -33,140 | -35,208 | 2,068 |
| Current Account Balance | -122,470 | -110,055 | -12,415 |
| % GDP | IIIQ2012 | IIIQ2013 | IIQ2013 |
| 2.6 | 2.2 | 2.3 |
X: exports; M: imports
Balance on Current Account = Balance on Goods and Services + Balance on Income + Unilateral Transfers
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.
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 potential. 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.”
Table IIA2-2 provides data on the US fiscal and balance of payments imbalances. In 2007, the federal deficit of the US was $161 billion corresponding to 1.1 percent of GDP while the Congressional Budget Office (CBO 2013Sep11) estimates the federal deficit in 2012 at $1087 billion or 6.8 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 $5.090 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, less than the combined deficits from 2009 to 2012 of $5090 billion. Federal debt in 2012 was 70.1 percent of GDP (CBO 2013Sep11). 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.”
Table IIA2-2, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and %
| 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | |
| Goods & | -699 | -702 | -384 | -499 | -557 | -535 |
| Income | 101 | 146 | 124 | 178 | 233 | 224 |
| UT | -115 | -125 | -122 | -128 | -134 | -130 |
| Current Account | -713 | -681 | -382 | -449 | -458 | -440 |
| NGDP | 14480 | 14720 | 14418 | 14958 | 15534 | 16245 |
| Current Account % GDP | -4.9 | -4.6 | -2.6 | -3.0 | -2.9 | -2.7 |
| NIIP | -1796 | -3260 | -2275 | -2250 | -3730 | -3863 |
| US Owned Assets Abroad | 18400 | 19464 | 18558 | 20555 | 21636 | 21638 |
| Foreign Owned Assets in US | 20196 | 22724 | 20833 | 22805 | 25366 | 25501 |
| NIIP % GDP | -12.4 | -22.1 | -15.8 | -15.0 | -24.0 | -23.8 |
| Exports | 2487 | 2654 | 2185 | 2523 | 2874 | 2987 |
| NIIP % | -72 | -123 | -104 | -89 | -130 | -129 |
| DIA MV | 5274 | 3102 | 4322 | 4809 | 4514 | 5249 |
| DIUS MV | 3551 | 2486 | 2995 | 3422 | 3510 | 3924 |
| Fiscal Balance | -161 | -459 | -1413 | -1294 | -1296 | -1087 |
| Fiscal Balance % GDP | -1.1 | -3.1 | -9.8 | -8.7 | -8.4 | -6.8 |
| Federal Debt | 5035 | 5803 | 7545 | 9019 | 10128 | 11281 |
| Federal Debt % GDP | 35.1 | 39.3 | 52.3 | 61.0 | 65.8 | 70.1 |
| Federal Outlays | 2729 | 2983 | 3518 | 3456 | 3598 | 3537 |
| ∆% | 2.8 | 9.3 | 17.9 | -1.8 | 4.1 | -1.7 |
| % GDP | 19.0 | 20.2 | 24.4 | 23.4 | 23.4 | 22.0 |
| Federal Revenue | 2568 | 2524 | 2105 | 2162 | 2302 | 2450 |
| ∆% | 6.7 | -1.7 | -16.6 | 2.7 | 6.5 | 6.4 |
| % GDP | 17.9 | 17.1 | 14.6 | 14.6 | 15.0 | 15.2 |
Sources:
Notes: UT: unilateral transfers; 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. 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 IIA2-3 provides quarterly estimates NSA of the external and internal imbalances of the United States. The current account deficit seasonally adjusted falls from 3.0 percent of GDP in IQ2012 to 2.5 percent in IQ2013 and 2.3 percent of GDP in IIQ2013. The net international investment position increases from $3.9 trillion in IQ2012 to $4.3 trillion in IQ2013 and $4.5 trillion in IIQ2013.
Table IIA2-3, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and % NSA
| IIQ2012 | IIIQ2012 | IVQ2012 | IQ2013 | IIQ2013 | |
| Goods & | -145 | -145 | -122 | -100 | -126 |
| Income | 58 | 55 | 55 | 52 | 57 |
| UT | -31 | -33 | -32 | -34 | -33 |
| Current Account | -118 | -123 | -99 | -82 | -102 |
| Current Account % GDP | -2.7 | -2.6 | -2.5 | -2.5 | -2.3 |
| NIIP | -4332 | -4109 | -3863 | -4236 | -4504 |
| US Owned Assets Abroad | 20948 | 21551 | 21638 | 21590 | 20984 |
| Foreign Owned Assets in US | -25280 | -25660 | -25501 | -25826 | -25488 |
| DIA MV | 4679 | 5059 | 5249 | 5501 | 5430 |
| DIUS MV | 3765 | 3962 | 3924 | 4251 | 4343 |
Sources:
Notes: UT: unilateral transfers; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value..
Sources: US Bureau of Economic Analysis http://www.bea.gov/international/index.htm#bop
Chart IIA2-1 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 Dec 19, 2013, at 0.09 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 IA2-1 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 IIA2-1 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 IIA2-1. 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 IIA2-1 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 0.09 percent on Dec 19, 2013. 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. Current policy consists of forecast mandate of maintaining policy accommodation until the forecast of the rate of unemployment reaches 6.5 percent and the rate of personal consumption expenditures excluding food and energy reaches 2.5 percent (http://www.federalreserve.gov/newsevents/press/monetary/20121212a.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 IIA2-1, 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 (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 rates.
Chart IIA2-1, US, Fed Funds Rate, Business Days, Jul 1, 1954 to Dec, 2013, 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 IIA2-4 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 IIA2-4 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 IIA2-4, 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 IIA2-2 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 IIQ2013 during the current economic expansion in contrast with 5.7 percent on average in the cyclical expansion from IQ1983 to IQ1986 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.html) cannot be explained by the contraction of 4.3 percent of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 28.1 million or 17.2 percent of the labor force as estimated for Jul 2013 (http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.html). There is no exit from unemployment/underemployment and stagnating real wages because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2013/12/theory-and-reality-of-secular.html).
Chart IIA2-2, US, Congressional Budget Office, Actual and Projections of Potential GDP, 2000-2024, Trillions of Dollars
Source: Congressional Budget Office, CBO (2013BEOFeb5).
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, 1960-2012, 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, 1960-2012, 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, 1960-2012, 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 2012. 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, 1960-2012, 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 IIB-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 three trillion dollars of securities held outright. Net foreign purchases of US long-term securities (row C in Table IIA2-6) increased from $31.3 billion in Sep 2013 to $35.4 billion in Oct 2013. Foreign (residents) purchases minus sales of US long-term securities (row A in Table IIA2-6) in Sep 2013 of $63.0 billion increased to $54.7 billion in Oct 2013. Net US (residents) purchases of long-term foreign securities (row B in Table II2-6) improved from minus $31.7 billion in Sep 2013 to minus $19.2 billion in Oct 2013. In Oct 2013,
C = A + B = $54.7 billion - $19.2 billion = $35.4 billion
There are minor rounding errors. There is slowing demand in Table IIA2-6 in Oct in A1 private purchases by residents overseas of US long-term securities of $59.4 billion of which slowing in A11 Treasury securities of $41.6 billion, slowing in A12 of $1.6 billion in agency securities, slowing of $3.3 billion of corporate bonds and increase of $12.9 billion in equities. Worldwide risk aversion causes flight into US Treasury obligations with significant oscillations. Official purchases of securities in row A2 decreased $4.7 billion with decrease of Treasury securities of $1.9 billion in Oct 2013. Official purchases of agency securities increased $1.0 billion in Oct. Row D shows increase in Oct 2013 of 11.6 billion in purchases of short-term dollar denominated obligations. Foreign private holdings of US Treasury bills decreased $15.3 billion (row D11) with foreign official holdings increasing $8.1 billion while the category “other” increased $26.9 billion. Foreign private holdings of US Treasury bills decreased $23.4 billion in what could be increase 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 IIA2-6, Net Cross-Borders Flows of US Long-Term Securities, Billion Dollars, NSA
| Oct 2012 12 Months | Oct 2013 12 Months | Sep 2013 | Oct 2013 | |
| A Foreign Purchases less Sales of | 540.7 | 268.8 | 63.0 | 54.7 |
| A1 Private | 315.9 | 174.1 | 78.2 | 59.4 |
| A11 Treasury | 201.2 | 102.1 | 51.7 | 41.6 |
| A12 Agency | 135.2 | 26.3 | 10.1 | 1.6 |
| A13 Corporate Bonds | -54.2 | 16.2 | 5.4 | 3.3 |
| A14 Equities | 33.7 | 29.6 | 11.1 | 12.9 |
| A2 Official | 224.8 | 94.8 | -15.3 | -4.7 |
| A21 Treasury | 208.4 | -2.0 | -23.2 | -1.9 |
| A22 Agency | 3.6 | 79.3 | 4.7 | 1.0 |
| A23 Corporate Bonds | 3.7 | 18.0 | 1.9 | 1.3 |
| A24 Equities | 9.2 | -0.5 | 1.4 | -5.1 |
| B Net US Purchases of LT Foreign Securities | 41.7 | -192.4 | -31.7 | -19.2 |
| B1 Foreign Bonds | 59.5 | -30.3 | -24.8 | -6.5 |
| B2 Foreign Equities | -17.8 | -162.1 | -6.8 | -12.7 |
| C Net Foreign Purchases of US LT Securities | 582.4 | 76.4 | 31.3 | 35.4 |
| D Increase in Foreign Holdings of Dollar Denominated Short-term | 78.9 | -46.4 | -24.8 | 11.6 |
| D1 US Treasury Bills | 49.0 | -42.4 | -26.2 | -15.3 |
| D11 Private | 44.1 | -41.6 | -23.5 | -23.4 |
| D12 Official | 4.9 | -0.8 | -2.8 | 8.1 |
| D2 Other | 30.0 | -4.07 | 1.4 | 26.9 |
C = A + B;
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/index.aspx
Table IIA2-7 provides major foreign holders of US Treasury securities. China is the largest holder with $1304.5 billion in Oct 2013, increasing 11.5 percent from $1169.9 billion in Oct 2012 while increasing $10.7 billion from Sep 2013 or 0.8 percent. Japan increased its holdings from $1131.9 billion in Oct 2012 to $1174.4 billion in Oct 2013 or by 3.8 percent. Japan reduced its holdings from $1178.1 billion in Sep 2013 to $1174.4 billion in Oct 2013 by $3.7 billion or 0.3 percent. Total foreign holdings of Treasury securities rose from $5526.7 billion in Oct 2012 to $5653.5 billion in Oct 2013, or 2.3 percent. Foreign holdings of Treasury securities fell from $5740.4 in Mar 2013 to $5670.8 in Apr 2013 or 1.2 percent. Foreign holdings of US Treasury securities fell from $5600.6 billion in Jun 2013 to $5590.1 billion in Jul 2013, by $10.5 billion or 0.2 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-10, US, Major Foreign Holders of Treasury Securities $ Billions at End of Period
| Oct 2013 | Sep 2013 | Oct 2012 | |
| Total | 5653.5 | 5652.9 | 5526.7 |
| China | 1304.5 | 1293.8 | 1169.9 |
| Japan | 1174.4 | 1178.1 | 1131.9 |
| Caribbean Banking Centers | 290.7 | 300.9 | 276.5 |
| Brazil | 246.7 | 249.2 | 254.1 |
| Oil Exporters | 236.6 | 245.7 | 262.2 |
| Taiwan | 184.5 | 185.9 | 197.2 |
| Belgium | 180.3 | 172.5 | 136.4 |
| Switzerland | 174.3 | 177.2 | 187.8 |
| United Kingdom | 158.4 | 158.3 | 133.2 |
| Russia | 149.9 | 140.5 | 171.1 |
| Hong Kong | 136.3 | 126.5 | 138.5 |
| Luxembourg | 133.3 | 141.1 | 144.3 |
| Foreign Official Holdings | 4052.5 | 4014.5 | 3984.3 |
| A. Treasury Bills | 378.6 | 370.5 | 379.4 |
| B. Treasury Bonds and Notes | 3673.6 | 3644.1 | 3604.9 |
Source: United States Treasury
http://www.treasury.gov/resource-center/data-chart-center/tic/Pages/index.aspx
II United States Industrial Production. Industrial production increased 1.1 percent in Nov 2013 after increasing 0.1 percent in Oct 2013 and increasing 0.5 percent in Se 2013, as shown in Table I-1, with all data seasonally adjusted. The report of the Board of Governors of the Federal Reserve System states (http://www.federalreserve.gov/releases/g17/Current/default.htm):
“Industrial production increased 1.1 percent in November after having edged up 0.1 percent in October; output was previously reported to have declined 0.1 percent in October. The gain in November was the largest since November 2012, when production rose 1.3 percent. Manufacturing output increased 0.6 percent in November for its fourth consecutive monthly gain. Production at mines advanced 1.7 percent to more than reverse a decline of 1.5 percent in October. The index for utilities was up 3.9 percent in November, as colder-than-average temperatures boosted demand for heating. At 101.3 percent of its 2007 average, total industrial production was 3.2 percent above its year-earlier level. In November, industrial production surpassed for the first time its pre-recession peak of December 2007 and was 21 percent above its trough of June 2009. Capacity utilization for the industrial sector increased 0.8 percentage point in November to 79.0 percent, a rate 1.2 percentage points below its long-run (1972-2012) average.”
In the six months ending in Nov 2013, United States national industrial production accumulated increase of 2.2 percent at the annual equivalent rate of 4.5 percent, which is higher than growth of 3.2 percent in the 12 months ending in Nov 2013. Excluding growth of 1.1 percent in Nov 2013, growth in the remaining five months from Jun 2012 to Oct 2013 accumulated to 1.1 percent or 2.2 percent annual equivalent. Industrial production fell in one of the past six months. Business equipment accumulated growth of 1.4 percent in the six months from Jun to Nov 2013 at the annual equivalent rate of 2.8 percent, which is higher than growth of 2.2 percent in the 12 months ending in Nov 2013. The Fed analyzes capacity utilization of total industry in its report (http://www.federalreserve.gov/releases/g17/Current/default.htm): “Capacity utilization for the industrial sector increased 0.8 percentage point in November to 79.0 percent, a rate 1.2 percentage points below its long-run (1972-2012) average.” United States industry apparently decelerated to a lower growth rate with possible acceleration in Nov 2013.
Table I-1, US, Industrial Production and Capacity Utilization, SA, ∆%
| 2012-2013 | Nov 13 | Oct 13 | Sep 13 | Aug 13 | Jul 13 | Jun 13 | Nov 13/ Nov 12 |
| Total | 1.1 | 0.1 | 0.5 | 0.5 | -0.2 | 0.2 | 3.2 |
| Market | |||||||
| Final Products | 0.9 | 0.0 | 0.9 | 0.6 | -1.0 | 0.4 | 2.4 |
| Consumer Goods | 1.5 | -0.1 | 0.8 | 0.5 | -1.1 | 0.3 | 2.7 |
| Business Equipment | -0.5 | 0.2 | 1.1 | 0.7 | -0.8 | 0.7 | 2.2 |
| Non | 0.9 | 0.3 | 0.8 | 0.3 | 0.1 | 0.1 | 3.6 |
| Construction | 0.6 | 0.6 | 1.0 | 0.2 | 0.3 | 0.6 | 4.9 |
| Materials | 1.4 | 0.2 | 0.1 | 0.5 | 0.5 | 0.0 | 3.8 |
| Industry Groups | |||||||
| Manufacturing | 0.6 | 0.5 | 0.1 | 0.7 | -0.5 | 0.3 | 2.9 |
| Mining | 1.7 | -1.5 | 0.8 | 0.4 | 1.6 | 1.1 | 5.2 |
| Utilities | 3.9 | -0.3 | 3.2 | -0.9 | -0.2 | -2.0 | 2.8 |
| Capacity | 79.0 | 78.2 | 78.3 | 78.0 | 77.7 | 79.0 | 1.8 |
Sources: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/default.htm
Manufacturing increased 0.6 percent in No 2013 after increasing 0.5 percent in Oct 2013 and increasing 0.1 percent in Sep 2013 seasonally adjusted, increasing 3.0 percent not seasonally adjusted in 12 months ending in Nov 2013, as shown in Table I-2. Manufacturing grew cumulatively 1.7 percent in the six months ending in Nov 2013 or at the annual equivalent rate of 3.4 percent. Excluding the increase of 0.6 percent in Nov 2013, manufacturing accumulated growth of 1.1 percent from Jun 2013 to Oct 2013 or at the annual equivalent rate of 2.2 percent. Table I-2 provides a longer perspective of manufacturing in the US. There has been evident deceleration of manufacturing growth in the US from 2010 and the first three months of 2011 into more recent months as shown by 12 months rates of growth. Growth rates appeared to be increasing again closer to 5 percent in Apr-Jun 2012 but deteriorated. The rates of decline of manufacturing in 2009 are quite high with a drop of 18.2 percent in the 12 months ending in Apr 2009. Manufacturing recovered from this decline and led the recovery from the recession. Rates of growth appeared to be returning to the levels at 3 percent or higher in the annual rates before the recession but the pace of manufacturing fell steadily in the past six months with some weakness at the margin. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 22, 2013 (http://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):
“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization. Measured from fourth quarter to fourth quarter, total IP is now reported to have increased 0.7 percentage point less in 2011 than was previously published. The revisions to IP for other years were smaller: Compared to the previous estimates, industrial production fell slightly less in 2008 and 2009 and increased slightly less in 2010 and 2012. At 97.7 percent of its 2007 average, the index in the fourth quarter of 2012 now stands 0.4 percent below its previous estimate. With these revisions, IP is still estimated to have advanced about 6 percent in 2010, the first full year following the trough in June 2009 of the most recent recession, but it is now estimated to have risen about 3 percent both in 2011 and in 2012. Since the trough of the recession, total IP has reversed about 90 percent of its peak-to-trough decline.”
The bottom part of Table I-2 shows decline of manufacturing by 21.9 from the peak in Jun 2007 to the trough in Apr 2009 and increase by 16.8 percent from the trough in Apr 2009 to Dec 2012. Manufacturing grew 20.5 percent from the trough in Apr 2009 to Nov 2013. Manufacturing output in Nov 2013 is 5.9 percent below the peak in Jun 2007.
Table I-2, US, Monthly and 12-Month Rates of Growth of Manufacturing ∆%
| Month SA ∆% | 12-Month NSA ∆% | |
| Nov 2013 | 0.6 | 3.0 |
| Oct | 0.5 | 3.7 |
| Sep | 0.1 | 2.5 |
| Aug | 0.7 | 2.6 |
| Jul | -0.5 | 1.4 |
| Jun | 0.3 | 1.8 |
| May | 0.3 | 1.8 |
| Apr | -0.3 | 2.2 |
| Mar | -0.2 | 1.8 |
| Feb | 0.6 | 1.9 |
| Jan | -0.1 | 2.4 |
| Dec 2012 | 0.9 | 3.0 |
| Nov | 1.4 | 3.3 |
| Oct | -0.4 | 2.1 |
| Sep | 0.1 | 3.1 |
| Aug | -0.7 | 3.5 |
| Jul | 0.2 | 4.0 |
| Jun | 0.3 | 5.0 |
| May | -0.3 | 4.8 |
| Apr | 0.6 | 5.1 |
| Mar | -0.5 | 3.9 |
| Feb | 0.6 | 5.3 |
| Jan | 1.0 | 4.2 |
| Dec 2011 | 1.0 | 3.8 |
| Nov | 0.0 | 3.2 |
| Oct | 0.6 | 3.1 |
| Sep | 0.4 | 3.0 |
| Aug | 0.4 | 2.4 |
| Jul | 0.7 | 2.5 |
| Jun | 0.1 | 2.1 |
| May | 0.3 | 1.9 |
| Apr | -0.7 | 3.1 |
| Mar | 0.7 | 4.9 |
| Feb | 0.0 | 5.4 |
| Jan | 0.2 | 5.6 |
| Dec 2010 | 0.6 | 6.2 |
| Nov | 0.2 | 5.3 |
| Oct | 0.1 | 6.6 |
| Sep | 0.1 | 7.0 |
| Aug | 0.1 | 7.4 |
| Jul | 0.7 | 7.8 |
| Jun | 0.0 | 9.3 |
| May | 1.4 | 8.9 |
| Apr | 0.9 | 7.1 |
| Mar | 1.3 | 4.9 |
| Feb | 0.0 | 1.3 |
| Jan | 1.0 | 1.2 |
| Dec 2009 | 0.0 | -3.1 |
| Nov | 1.1 | -6.1 |
| Oct | 0.1 | -9.1 |
| Sep | 0.8 | -10.6 |
| Aug | 1.1 | -13.6 |
| Jul | 1.2 | -15.2 |
| Jun | -0.3 | -17.6 |
| May | -1.1 | -17.6 |
| Apr | -0.8 | -18.2 |
| Mar | -1.9 | -17.3 |
| Feb | -0.2 | -16.1 |
| Jan | -2.9 | -16.4 |
| Dec 2008 | -3.4 | -14.0 |
| Nov | -2.2 | -11.3 |
| Oct | -0.6 | -9.0 |
| Sep | -3.4 | -8.6 |
| Aug | -1.3 | -5.1 |
| Jul | -1.1 | -3.5 |
| Jun | -0.5 | -3.1 |
| May | -0.5 | -2.4 |
| Apr | -1.1 | -1.1 |
| Mar | -0.3 | -0.5 |
| Feb | -0.6 | 0.9 |
| Jan | -0.4 | 2.3 |
| Dec 2007 | 0.2 | 2.0 |
| Nov | 0.5 | 3.4 |
| Oct | -0.4 | 2.8 |
| Sep | 0.5 | 3.0 |
| Aug | -0.4 | 2.6 |
| Jul | 0.1 | 3.4 |
| Jun | 0.3 | 2.9 |
| May | -0.1 | 3.1 |
| Apr | 0.7 | 3.6 |
| Mar | 0.7 | 2.4 |
| Feb | 0.4 | 1.6 |
| Jan | -0.5 | 1.3 |
| Dec 2006 | 2.7 | |
| Dec 2005 | 3.4 | |
| Dec 2004 | 4.0 | |
| Dec 2003 | 1.7 | |
| Dec 2002 | 2.4 | |
| Dec 2001 | -5.5 | |
| Dec 2000 | 0.4 | |
| Dec 1999 | 5.4 | |
| Average ∆% Dec 1986-Dec 2012 | 2.3 | |
| Average ∆% Dec 1986-Dec 1999 | 4.3 | |
| Average ∆% Dec 1999-Dec 2006 | 1.3 | |
| Average ∆% Dec 1999-Dec 2012 | 0.4 | |
| ∆% Peak 103.0005 in 06/2007 to 93.9456 in 12/2012 | -8.8 | |
| ∆% Peak 103.0005 on 06/2007 to Trough 80.4617 in 4/2009 | -21.9 | |
| ∆% Trough 80.4617 in 04/2009 to 93.9456 in 12/2012 | 16.8 | |
| ∆% Trough 80.4617 in 04/2009 to 96.9199 in 11/2013 | 20.5 | |
| ∆% Peak 103.0005 on 06/2007 to Trough 96.9199 in 11/2013 | -5.9 |
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/default.htm
Chart I-1 of the Board of Governors of the Federal Reserve System provides industrial production, manufacturing and capacity since the 1970s. There was acceleration of growth of industrial production, manufacturing and capacity in the 1990s because of rapid growth of productivity in the US (Cobet and Wilson (2002); see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). The slopes of the curves flatten in the 2000s. Production and capacity have not recovered to the levels before the global recession.
Chart I-1, US, Industrial Production, Capacity and Utilization
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/ipg1.gif
The modern industrial revolution of Jensen (1993) is captured in Chart I-2 of the Board of Governors of the Federal Reserve System (for the literature on M&A and corporate control see Pelaez and Pelaez, Regulation of Banks and Finance (2009a), 143-56, Globalization and the State, Vol. I (2008a), 49-59, Government Intervention in Globalization (2008c), 46-49). The slope of the curve of total industrial production accelerates in the 1990s to a much higher rate of growth than the curve excluding high-technology industries. Growth rates decelerate into the 2000s and output and capacity utilization have not recovered fully from the strong impact of the global recession. Growth in the current cyclical expansion has been more subdued than in the prior comparably deep contractions in the 1970s and 1980s. Chart II-2 shows that the past recessions after World War II are the relevant ones for comparison with the recession after 2007 instead of common comparisons with the Great Depression (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.html). The bottom left-hand part of Chart II-2 shows the strong growth of output of communication equipment, computers and semiconductor that continued from the 1990s into the 2000s. Output of semiconductors has already surpassed the level before the global recession.
Chart I-2, US, Industrial Production, Capacity and Utilization of High Technology Industries
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/ipg3.gif
Additional detail on industrial production and capacity utilization is provided in Chart I-3 of the Board of Governors of the Federal Reserve System. Production of consumer durable goods fell sharply during the global recession by more than 30 percent and is still around the level before the contraction. Output of nondurable consumer goods fell around 10 percent and is some 5 percent below the level before the contraction. Output of business equipment fell sharply during the contraction of 2001 but began rapid growth again after 2004. An important characteristic is rapid growth of output of business equipment in the cyclical expansion after sharp contraction in the global recession. Output of defense and space only suffered reduction in the rate of growth during the global recession and surged ahead of the level before the contraction. Output of construction supplies collapsed during the global recession and is well below the level before the contraction. Output of energy materials was stagnant before the contraction but has recovered sharply above the level before the contraction.
Chart I-3, US, Industrial Production and Capacity Utilization
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/ipg2.gif
United States manufacturing output from 1919 to 2012 on a monthly basis is in Chart I-4 of the Board of Governors of the Federal Reserve System. The second industrial revolution of Jensen (1993) is quite evident in the acceleration of the rate of growth of output given by the sharper slope in the 1980s and 1990s. Growth was robust after the shallow recession of 2001 but dropped sharply during the global recession after IVQ2007. Manufacturing output recovered sharply but has not reached earlier levels and is losing momentum at the margin.
Chart I-4, US, Manufacturing Output, 1919-2013
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/default.htm
Manufacturing jobs increased 27,000 in Nov 2013 relative to Oct 2013, seasonally adjusted (http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.html and earlier http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html). Manufacturing jobs not seasonally adjusted increased 83,000 from Nov 2012 to Nov 2013 or at the average monthly rate of 6,917. There are effects of the weaker economy and international trade together with the yearly adjustment of labor statistics. Industrial production increased 1.1 percent in Nov 2013 after increasing 0.1 percent in Oct 2013 and increasing 0.5 percent in Se 2013, as shown in Table I-1, with all data seasonally adjusted. The report of the Board of Governors of the Federal Reserve System states (http://www.federalreserve.gov/releases/g17/Current/default.htm):
“Industrial production increased 1.1 percent in November after having edged up 0.1 percent in October; output was previously reported to have declined 0.1 percent in October. The gain in November was the largest since November 2012, when production rose 1.3 percent. Manufacturing output increased 0.6 percent in November for its fourth consecutive monthly gain. Production at mines advanced 1.7 percent to more than reverse a decline of 1.5 percent in October. The index for utilities was up 3.9 percent in November, as colder-than-average temperatures boosted demand for heating. At 101.3 percent of its 2007 average, total industrial production was 3.2 percent above its year-earlier level. In November, industrial production surpassed for the first time its pre-recession peak of December 2007 and was 21 percent above its trough of June 2009. Capacity utilization for the industrial sector increased 0.8 percentage point in November to 79.0 percent, a rate 1.2 percentage points below its long-run (1972-2012) average.”
In the six months ending in Nov 2013, United States national industrial production accumulated increase of 2.2 percent at the annual equivalent rate of 4.5 percent, which is higher than growth of 3.2 percent in the 12 months ending in Nov 2013. Excluding growth of 1.1 percent in Nov 2013, growth in the remaining five months from Jun 2012 to Oct 2013 accumulated to 1.1 percent or 2.2 percent annual equivalent. Industrial production fell in one of the past six months. Business equipment accumulated growth of 1.4 percent in the six months from Jun to Nov 2013 at the annual equivalent rate of 2.8 percent, which is higher than growth of 2.2 percent in the 12 months ending in Nov 2013. The Fed analyzes capacity utilization of total industry in its report (http://www.federalreserve.gov/releases/g17/Current/default.htm): “Capacity utilization for the industrial sector increased 0.8 percentage point in November to 79.0 percent, a rate 1.2 percentage points below its long-run (1972-2012) average.” United States industry apparently decelerated to a lower growth rate with possible acceleration in Nov 2013.
Manufacturing increased 0.3 percent in Oct 2013 after increasing 0.1 percent in Sep 2013 and increasing 0.7 percent in Aug 2013 seasonally adjusted, increasing 3.4 percent not seasonally adjusted in 12 months ending in Oct 2013, as shown in Table I-2 (http://cmpassocregulationblog.blogspot.com/2013/11/risks-of-unwinding-monetary-policy.html). Manufacturing increased 0.6 percent in No 2013 after increasing 0.5 percent in Oct 2013 and increasing 0.1 percent in Sep 2013 seasonally adjusted, increasing 3.0 percent not seasonally adjusted in 12 months ending in Nov 2013, as shown in Table I-2. Manufacturing grew cumulatively 1.7 percent in the six months ending in Nov 2013 or at the annual equivalent rate of 3.4 percent. Excluding the increase of 0.6 percent in Nov 2013, manufacturing accumulated growth of 1.1 percent from Jun 2013 to Oct 2013 or at the annual equivalent rate of 2.2 percent. Table I-2 provides a longer perspective of manufacturing in the US. There has been evident deceleration of manufacturing growth in the US from 2010 and the first three months of 2011 into more recent months as shown by 12 months rates of growth. Growth rates appeared to be increasing again closer to 5 percent in Apr-Jun 2012 but deteriorated. The rates of decline of manufacturing in 2009 are quite high with a drop of 18.2 percent in the 12 months ending in Apr 2009. Manufacturing recovered from this decline and led the recovery from the recession. Rates of growth appeared to be returning to the levels at 3 percent or higher in the annual rates before the recession but the pace of manufacturing fell steadily in the past six months with some weakness at the margin. Manufacturing fell by 21.9 from the peak in Jun 2007 to the trough in Apr 2009 and increase by 16.8 percent from the trough in Apr 2009 to Dec 2012. Manufacturing grew 20.5 percent from the trough in Apr 2009 to Nov 2013. Manufacturing output in Nov 2013 is 5.9 percent below the peak in Jun 2007.
Table I-13 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 86.8 percent in IIIQ2013. Most of US national income is in the form of services. In Nov 2013, there were 137.942 million nonfarm jobs NSA in the US, according to estimates of the establishment survey of the Bureau of Labor Statistics (BLS) (http://www.bls.gov/news.release/empsit.nr0.htm Table B-1). Total private jobs of 115.622 million NSA in Nov 2013 accounted for 83.8 percent of total nonfarm jobs of 137.942 million, of which 12.022 million, or 10.4 percent of total private jobs and 8.7 percent of total nonfarm jobs, were in manufacturing. Private service-producing jobs were 96.761 million NSA in Nov 2013, or 70.1 percent of total nonfarm jobs and 83.7 percent of total private-sector jobs. Manufacturing has share of 10.8 percent in US national income in IIQ2013, as shown in Table I-3. Most income in the US originates in services. Subsidies and similar measures designed to increase manufacturing jobs will not increase economic growth and employment and may actually reduce growth by diverting resources away from currently employment-creating activities because of the drain of taxation.
Table I-3, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total
| SAAR | % Total | SAAR IIIQ2013 | % Total | |
| National Income WCCA | 14,495.5 | 100.0 | 14,643.3 | 100.0 |
| Domestic Industries | 14,248.7 | 98.3 | 14,380.3 | 98.2 |
| Private Industries | 12,568.6 | 86.7 | 12,705.2 | 86.8 |
| Agriculture | 220.3 | 1.5 | 225.2 | 1.5 |
| Mining | 254.3 | 1.8 | 256.4 | 1.8 |
| Utilities | 216.5 | 1.5 | 221.2 | 1.5 |
| Construction | 629.0 | 4.3 | 639.1 | 4.4 |
| Manufacturing | 1558.9 | 10.8 | 1577.7 | 10.8 |
| Durable Goods | 888.1 | 6.1 | 910.1 | 6.2 |
| Nondurable Goods | 670.1 | 4.6 | 667.6 | 4.6 |
| Wholesale Trade | 874.4 | 6.0 | 884.0 | 6.0 |
| Retail Trade | 995.8 | 6.9 | 1000.2 | 6.8 |
| Transportation & WH | 436.3 | 3.0 | 443.6 | 3.0 |
| Information | 507.2 | 3.5 | 497.5 | 3.4 |
| Finance, Insurance, RE | 2448.1 | 16.9 | 2521.0 | 17.2 |
| Professional, BS | 2004.7 | 13.8 | 2004.0 | 13.7 |
| Education, Health Care | 1438.9 | 9.9 | 1439.2 | 9.8 |
| Arts, Entertainment | 577.1 | 4.0 | 585.2 | 4.0 |
| Other Services | 409.7 | 2.8 | 410.8 | 2.8 |
| Government | 1680.1 | 11.6 | 1675.1 | 11.4 |
| Rest of the World | 246.8 | 1.7 | 262.9 | 1.8 |
Notes: SSAR: Seasonally-Adjusted Annual Rate; WCCA: Without Capital Consumption Adjustment by Industry; WH: Warehousing; RE, includes rental and leasing: Real Estate; Art, Entertainment includes recreation, accommodation and food services; BS: business services
Source: US Bureau of Economic Analysis http://bea.gov/iTable/index_nipa.cfm
Motor vehicle sales and production in the US have been in long-term structural change. Table I-4 provides the data on new motor vehicle sales and domestic car production in the US from 1990 to 2010. New motor vehicle sales grew from 14,137 thousand in 1990 to the peak of 17,806 thousand in 2000 or 29.5 percent. In that same period, domestic car production fell from 6,231 thousand in 1990 to 5,542 thousand in 2000 or -11.1 percent. New motor vehicle sales fell from 17,445 thousand in 2005 to 11,772 in 2010 or 32.5 percent while domestic car production fell from 4,321 thousand in 2005 to 2,840 thousand in 2010 or 34.3 percent. In Jan-Nov 2013, light vehicle sales accumulated to 14,239,897, which is higher by 8.4 percent relative to 13,135,875 a year earlier (http://motorintelligence.com/m_frameset.html). The seasonally adjusted annual rate of light vehicle sales in the US reached 16.41 million in Nov 2013, higher than 15.23 million in Oct 2013 and higher than 15.32 million in Nov 2012 (http://motorintelligence.com/m_frameset.html).
Table I-4, US, New Motor Vehicle Sales and Car Production, Thousand Units
| New Motor Vehicle Sales | New Car Sales and Leases | New Truck Sales and Leases | Domestic Car Production | |
| 1990 | 14,137 | 9,300 | 4,837 | 6,231 |
| 1991 | 12,725 | 8,589 | 4,136 | 5,454 |
| 1992 | 13,093 | 8,215 | 4,878 | 5,979 |
| 1993 | 14,172 | 8,518 | 5,654 | 5,979 |
| 1994 | 15,397 | 8,990 | 6,407 | 6,614 |
| 1995 | 15,106 | 8,536 | 6,470 | 6,340 |
| 1996 | 15,449 | 8,527 | 6,922 | 6,081 |
| 1997 | 15,490 | 8,273 | 7,218 | 5,934 |
| 1998 | 15,958 | 8,142 | 7,816 | 5,554 |
| 1999 | 17,401 | 8,697 | 8,704 | 5,638 |
| 2000 | 17,806 | 8,852 | 8,954 | 5,542 |
| 2001 | 17,468 | 8,422 | 9,046 | 4,878 |
| 2002 | 17,144 | 8,109 | 9,036 | 5,019 |
| 2003 | 16,968 | 7,611 | 9,357 | 4,510 |
| 2004 | 17,298 | 7,545 | 9,753 | 4,230 |
| 2005 | 17,445 | 7,720 | 9,725 | 4,321 |
| 2006 | 17,049 | 7,821 | 9,228 | 4,367 |
| 2007 | 16,460 | 7,618 | 8,683 | 3,924 |
| 2008 | 13,494 | 6,814 | 6.680 | 3,777 |
| 2009 | 10,601 | 5,456 | 5,154 | 2,247 |
| 2010 | 11,772 | 5,729 | 6,044 | 2,840 |
Source: US Census Bureau http://www.census.gov/compendia/statab/cats/wholesale_retail_trade/motor_vehicle_sales.html
Chart I-5 of the Board of Governors of the Federal Reserve provides output of motor vehicles and parts in the United States from 1972 to 2013. Output has stagnated since the late 1990s.
Chart I-5, US, Motor Vehicles and Parts Output, 1972-2013
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/default.htm
Chart I-6 of the Board of Governors of the Federal Reserve System provides output of computers and electronic products in the United States from 1972 to 2013. Output accelerated sharply in the 1990s and 2000s and has surpassed the level before the global recession beginning in IVQ2007.
Chart I-6, US, Output of Computers and Electronic Products, 1972-2013
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/default.htm
Chart I-7 of the Board of Governors of the Federal Reserve System shows that output of durable manufacturing accelerated in the 1980s and 1990s with slower growth in the 2000s perhaps because processes matured. Growth was robust after the major drop during the global recession but appears to vacillate in the final segment.
Chart I-7, US, Output of Durable Manufacturing, 1972-2013
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/default.htm
Chart I-8 of the Board of Governors of the Federal Reserve System provides output of aerospace and miscellaneous transportation equipment from 1972 to 2013. There is long-term upward trend with oscillations around the trend and cycles of large amplitude.
Chart I-8, US, Output of Aerospace and Miscellaneous Transportation Equipment, 1972-2013
Source: Board of Governors of the Federal Reserve System
http://www.federalreserve.gov/releases/g17/Current/default.htm
The Empire State Manufacturing Survey Index in Table I-5 provides continuing deterioration that started in Jun 2012 well before Hurricane Sandy in Oct 2012. The current general index has been in negative contraction territory from minus 3.78 in Aug 2012 to minus 7.78 in Jan 2012 and minus 1.43 in May 2013. The current general index deteriorated to 2.21 in Nov 2013, which is again in contraction territory, and 0.98 in Dec 2013 The index of current orders has also been in negative contraction territory from minus 4.63 in Aug 2012 to minus 7.18 in Jan 2013 and minus 6.69 in Jun 2013. The index of current new orders decreased to minus 3.54 in Dec 2012, again in contraction territory. Number of workers and hours worked have registered negative or declining readings since Sep 2012 with neutral reading at 0.00 for number of workers in Dec 2013 and contraction in the average workweek to 10.84 in Dec 2013. There is improvement in the general index for the next six months at 3.61 in Dec 2013 and weakening new orders at 26.36 in Dec 2013.
Table I-5, US, New York Federal Reserve Bank Empire State Manufacturing Survey Index SA
| General | New Orders | Shipments | # Workers | Average Work-week | |
| Current | |||||
| Dec 2013 | 0.98 | -3.54 | 7.66 | 0.00 | -10.84 |
| Nov | -2.21 | -5.53 | -0.53 | 0.00 | -5.26 |
| Oct | 1.52 | 7.75 | 13.12 | 3.61 | 3.61 |
| Sep | 6.29 | 2.35 | 16.43 | 7.53 | 1.08 |
| Aug | 8.24 | 0.27 | 1.47 | 10.84 | 4.82 |
| Jul | 9.46 | 3.77 | 8.96 | 3.26 | -7.61 |
| Jun | 7.84 | -6.69 | -11.77 | 0.00 | -11.29 |
| May | -1.43 | -1.17 | -0.02 | 5.68 | -1.14 |
| Apr | 3.05 | 2.20 | 0.75 | 6.82 | 5.68 |
| Mar | 9.24 | 8.18 | 7.76 | 3.23 | 0.00 |
| Feb | 10.04 | 13.31 | 13.08 | 8.08 | -4.04 |
| Jan | -7.78 | -7.18 | -3.08 | -4.30 | -5.38 |
| Dec 2012 | -7.30 | -3.44 | 11.93 | -9.68 | -10.75 |
| Nov | -4.31 | 2.93 | 14.18 | -14.61 | -7.87 |
| Oct | -6.75 | -7.21 | -6.48 | -1.08 | -4.30 |
| Sep | -7.54 | -10.60 | 7.30 | 4.26 | -1.06 |
| Aug | -3.78 | -4.63 | 6.37 | 16.47 | 3.53 |
| Jul | 7.08 | -2.27 | 11.52 | 18.52 | 0.00 |
| Jun | 4.15 | 2.28 | 6.34 | 12.37 | 3.09 |
| May | 14.52 | 8.99 | 23.11 | 20.48 | 12.05 |
| Apr | 6.40 | 4.81 | 4.51 | 19.28 | 6.02 |
| Mar | 18.00 | 6.55 | 15.97 | 13.58 | 18.52 |
| Feb | 18.31 | 7.93 | 19.90 | 11.76 | 7.06 |
| Jan | 12.12 | 11.21 | 18.94 | 12.09 | 6.59 |
| Dec 2011 | 9.60 | 6.35 | 23.77 | 2.33 | -2.33 |
| Nov | 1.82 | -0.97 | 11.34 | -3.66 | 2.44 |
| Oct | -7.39 | 1.51 | 2.46 | 3.37 | -4.49 |
| Sep | -4.75 | -4.31 | -4.48 | -5.43 | -2.17 |
| Six Months | |||||
| Dec 2013 | 3.61 | 26.36 | 31.97 | 9.64 | 1.20 |
| Nov | -3.95 | 40.27 | 37.80 | 22.37 | -3.95 |
| Oct | 2.41 | 37.04 | 32.18 | 7.23 | 2.41 |
| Sep | 8.60 | 38.17 | 37.84 | 4.30 | -2.15 |
| Aug | 3.61 | 30.01 | 30.02 | 8.43 | -6.02 |
| Jul | 1.09 | 31.12 | 34.44 | 1.09 | -1.09 |
| Jun | 11.29 | 19.77 | 20.21 | 1.61 | -9.68 |
| May | 4.55 | 28.84 | 25.18 | 11.36 | 1.14 |
| Apr 2013 | 5.68 | 36.23 | 39.28 | 25.00 | 7.95 |
| Mar | 2.15 | 34.94 | 41.60 | 19.35 | 2.15 |
| Feb | 8.08 | 29.11 | 26.82 | 15.15 | 11.11 |
| Jan | 10.75 | 25.11 | 23.86 | 7.53 | 3.23 |
| Dec 2012 | 1.08 | 17.19 | 22.46 | 10.75 | 5.38 |
| Nov | 5.62 | 15.96 | 25.67 | -1.12 | 0.00 |
| Oct | 4.30 | 22.79 | 17.39 | 0.00 | -11.83 |
| Sep | 5.32 | 27.85 | 23.35 | 8.51 | 2.13 |
| Aug | 2.35 | 14.34 | 21.16 | 3.53 | -8.24 |
| Jul | 3.70 | 19.85 | 21.60 | 6.17 | -4.94 |
| Jun | 1.03 | 26.02 | 22.18 | 16.49 | 2.06 |
| May | 12.05 | 31.26 | 26.00 | 12.05 | 8.43 |
| Apr | 19.28 | 38.95 | 40.75 | 27.71 | 10.84 |
| Mar | 13.58 | 39.18 | 41.64 | 32.10 | 20.99 |
| Feb | 15.29 | 39.25 | 40.92 | 29.41 | 18.82 |
| Jan | 23.08 | 45.70 | 44.12 | 28.57 | 17.58 |
| Dec 2011 | 3.49 | 42.20 | 40.36 | 24.42 | 22.09 |
| Nov | 6.10 | 30.89 | 33.01 | 14.63 | 8.54 |
| Oct | 4.49 | 19.71 | 22.65 | 6.74 | -2.25 |
| Sep | 8.70 | 23.52 | 22.89 | 0.00 | -6.52 |
Source: http://www.newyorkfed.org/survey/empire/empiresurvey_overview.html
The Business Outlook Survey Diffusion Index of the Federal Reserve Bank of Philadelphia in Table VA-3 also shows improvement after prior deterioration. The general index moved out contraction of 5.2 in May 2013 to 7.0 in Dec 2013 together with renewed expansion at 15.4 for new orders. Employment segments show weakness in Dec 2013 with 2.2 for number of workers and 6.8 for hours worked. Expectations for the next six months are brighter with the general index at 45.0 in Dec 2013 and the index of new orders at 41.7.
Table VA-3, FRB of Philadelphia Business Outlook Survey Diffusion Index
| Current | General Index | New Orders | Shipments | # Workers | Hours Worked |
| 11-Jan | 15 | 19.1 | 11.1 | 13.9 | 8 |
| 11-Feb | 25.6 | 15.7 | 24 | 19.6 | 6.9 |
| 11-Mar | 36.1 | 33.2 | 28.1 | 16.1 | 7.3 |
| 11-Apr | 13.7 | 12.6 | 23 | 9.9 | 15.1 |
| 11-May | 4 | 6.8 | 5.4 | 22.2 | 2.8 |
| 11-Jun | -1.1 | -1.2 | 5.7 | 3.4 | 3.7 |
| 11-Jul | 9.4 | 4.7 | 9 | 12.6 | -0.8 |
| 11-Aug | -19 | -18.6 | -4.7 | -0.5 | -7.6 |
| 11-Sep | -10 | -4.5 | -7.4 | 9.4 | -2.8 |
| 11-Oct | 9.7 | 8.8 | 11.2 | 7.8 | 5.2 |
| 11-Nov | 5 | 3.6 | 6.9 | 10.9 | 6.8 |
| 11-Dec | 4.2 | 5.9 | 6.2 | 8 | -0.3 |
| 12-Jan | 4.7 | 9 | 4.4 | 9.6 | 3.9 |
| 12-Feb | 5 | 5.3 | 8.6 | 0.9 | 5.7 |
| 12-Mar | 8.6 | -0.7 | 0.2 | 5.9 | -0.6 |
| 12-Apr | 6.5 | -0.8 | 0.5 | 13.4 | -3.4 |
| 12-May | -4.9 | -0.6 | 2.7 | -0.2 | -6.4 |
| 12-Jun | -12.8 | -13.1 | -13.8 | 2.3 | -16.9 |
| 12-Jul | -9.1 | -2.1 | -7.5 | -4.7 | -13.9 |
| 12-Aug | -1.7 | -0.8 | -5.9 | -7.6 | -9.9 |
| 12-Sep | 1.4 | 2.5 | -10.4 | -4.9 | -2.9 |
| 12-Oct | 4.2 | -0.5 | -3.5 | -7.6 | -6.5 |
| 12-Nov | -8.9 | -4.7 | -6.3 | -6.9 | -7.4 |
| 12-Dec | 4.6 | 4.9 | 14.7 | -0.2 | 0.4 |
| 13-Jan | -5.8 | -4.3 | 0.4 | -5.2 | -8.3 |
| 13-Feb | -12.5 | -7.8 | 2.4 | 0.9 | -1.6 |
| 13-Mar | 2 | 0.5 | 3.5 | 2.7 | -12.9 |
| 13-Apr | 1.3 | -1 | 9.1 | -6.8 | -2.1 |
| 13-May | -5.2 | -7.9 | -8.5 | -8.7 | -12.4 |
| 13-Jun | 12.5 | 16.6 | 4.1 | -5.4 | 0.8 |
| 13-Jul | 19.8 | 10.2 | 14.3 | 7.7 | 6.6 |
| 13-Aug | 9.3 | 5.3 | -0.9 | 3.5 | -2.6 |
| 13-Sep | 22.3 | 21.2 | 21.2 | 10.3 | 12.2 |
| 13-Oct | 19.8 | 27.5 | 20.4 | 15.4 | 8.5 |
| 13-Nov | 6.5 | 11.8 | 5.6 | 1.1 | -8.6 |
| 13-Dec | 7 | 15.4 | 13.3 | 2.2 | 6.8 |
| Future | General Index | New Orders | Shipments | # Workers | Hours Worked |
| 10-Dec | 42.1 | 41.9 | 14.5 | 28 | 22 |
| 11-Jan | 35.9 | 39.8 | 10.3 | 29.1 | 19.6 |
| 11-Feb | 38.6 | 42.7 | 14.2 | 22.6 | 11.8 |
| 11-Mar | 53.6 | 52.3 | 12.6 | 25.2 | 13 |
| 11-Apr | 26.6 | 33.5 | 8.8 | 32.3 | 15.9 |
| 11-May | 22.4 | 26.1 | 3.8 | 20.9 | 12.5 |
| 11-Jun | 9.6 | 7.7 | -4.7 | 7.2 | 4.2 |
| 11-Jul | 35 | 31 | 8 | 16.2 | 6.6 |
| 11-Aug | 26.4 | 22.8 | 3.5 | 13.9 | 2.4 |
| 11-Sep | 26.6 | 27 | 6 | 13.4 | 5.7 |
| 11-Oct | 29.8 | 31 | 5.3 | 17.5 | 8.2 |
| 11-Nov | 36.2 | 34 | 8.9 | 27.9 | 4.5 |
| 11-Dec | 37.7 | 31.6 | 4.4 | 7.9 | 2 |
| 12-Jan | 43.9 | 46.1 | 13 | 17.8 | 6.8 |
| 12-Feb | 32.2 | 26.3 | 5.7 | 20.2 | 8.7 |
| 12-Mar | 34.4 | 28.6 | 6 | 19.2 | 8 |
| 12-Apr | 34.8 | 29.6 | 5.6 | 23.6 | 6.9 |
| 12-May | 30.2 | 26 | 10.1 | 11.8 | 1.2 |
| 12-Jun | 35.5 | 35.6 | 6 | 19.1 | 5 |
| 12-Jul | 30.8 | 24.7 | 6.5 | 15.3 | 14.6 |
| 12-Aug | 25.3 | 17.3 | 4.8 | 14.5 | 8.8 |
| 12-Sep | 52 | 42.8 | 12.6 | 21.2 | 13.8 |
| 12-Oct | 22.6 | 22.7 | 8.6 | 9.8 | 10.5 |
| 12-Nov | 23.2 | 24.9 | 2.7 | 7 | 8.2 |
| 12-Dec | 28.3 | 28 | 2.7 | 11.2 | 14.4 |
| 13-Jan | 32.5 | 38.9 | 2.9 | 10.7 | 8.9 |
| 13-Feb | 38 | 30.3 | 4.3 | 14.9 | 6.5 |
| 13-Mar | 34.5 | 31.2 | 6.6 | 8.1 | 3.4 |
| 13-Apr | 24.3 | 26.5 | -2.1 | 8.2 | 6.6 |
| 13-May | 34.5 | 31.7 | 16.9 | 10 | 14.1 |
| 13-Jun | 41.5 | 37.6 | 17.8 | 27.3 | 7.5 |
| 13-Jul | 58.8 | 51.2 | 25.8 | 36.2 | 14.6 |
| 13-Aug | 39.5 | 40.1 | 12.3 | 22.3 | 15 |
| 13-Sep | 62.2 | 58.3 | 18.5 | 31 | 16.2 |
| 13-Oct | 63.7 | 53.8 | 17.8 | 27.2 | 9.3 |
| 13-Nov | 47.5 | 42.7 | 14.3 | 26.9 | 17.2 |
| 13-Dec | 45 | 41.7 | 11.3 | 16 | 9.6 |
Source: Federal Reserve Bank of Philadelphia
http://www.phil.frb.org/index.cfm
Chart VA-14 of the Federal Reserve Bank of Philadelphia is very useful, providing current and future general activity indexes from Jan 1995 to Dec 2013. The shaded areas are the recession cycle dates of the National Bureau of Economic Research (NBER) (http://www.nber.org/cycles.html). The Philadelphia Fed index dropped during the initial period of recession and then led the recovery, as industry overall. There was a second decline of the index into 2011 followed now by what hopefully appeared as renewed strength from late 2011 into Jan 2012 with decline to negative territory of the current activity index in Nov 2012 and return to positive territory in Dec 2012 with decline of current conditions into contraction in Jan-Feb 2013 and rebound to mild expansion in Mar-Apr 2013. The index of current activity moved into expansion in Jun-Oct 2013 with weakness in Nov-Dec 2013.
Chart VA-14, Federal Reserve Bank of Philadelphia Business Outlook Survey, Current and Future Activity Indexes
Source: Federal Reserve Bank of Philadelphia
http://www.philadelphiafed.org/index.cfm
The index of current new orders of the Business Outlook Survey of the Federal Reserve Bank of Philadelphia in Chart VA-15 illustrates the weakness of the cyclical expansion. The index weakened in 2006 and 2007 and then fell sharply into contraction during the global recession. There have been twelve readings into contraction from Jan 2012 to May 2013 and generally weak readings with some exceptions. The index of new orders moved into expansion in Jun-Oct 2013 with moderation in Nov-Dec 2013.
Chart VA-15, Federal Reserve Bank of Philadelphia Current New Orders Diffusion Index
Source: Federal Reserve Bank of Philadelphia
http://www.philadelphiafed.org/index.cfm
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013
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