Twenty Eight Million Unemployed or Underemployed, Stagnating Salaries and Wages and Real Disposable Income, Decline of Real Disposable Income per Capita, Collapse of United States Dynamism of Income Growth and Employment Creation, International Financial Turbulence and the Global Recession Risk: Part I

 

Twenty Eight Million Unemployed or Underemployed, Stagnating Salaries and Wages and Real Disposable Income, Decline of Real Disposable Income per Capita, Collapse of United States Dynamism of Income Growth and Employment Creation, International Financial Turbulence and the Global Recession Risk

Carlos M. Pelaez

© Carlos M. Pelaez, 2010, 2011, 2012

Executive Summary

IA Twenty Eight Million Unemployed or Underemployed

IA1 Summary of the Employment Situation

IA2 Number of People in Job Stress

IA3 Long-term and Cyclical Comparison of Employment

IA4 Job Creation

IB Stagnating Real Wages

II Stagnating Real Disposable Income and Consumption Expenditures, Collapse of United States Dynamism of Income Growth and Employment Creation and Financial Repression

IIA Stagnating Real Disposable Income and Consumption Expenditures

IIB Collapse of United States Dynamism of Income Growth and Employment Creation

IIC Financial Repression

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

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

Executive Summary

ESI Twenty Eight Million Unemployed or Underemployed. Table ESI-1 consists of data and additional calculations using the BLS household survey, illustrating the possibility that the actual rate of unemployment could be 10.8 percent and the number of people in job stress could be around 28.1 million, which is 17.4 percent of the labor force. The first column provides for 2006 the yearly average population (POP), labor force (LF), participation rate or labor force as percent of population (PART %), employment (EMP), employment population ratio (EMP/POP %), unemployment (UEM), the unemployment rate as percent of labor force (UEM/LF Rate %) and the number of people not in the labor force (NLF). All data are unadjusted or not-seasonally-adjusted (NSA). The numbers in column 2006 are averages in millions while the monthly numbers for Oct 2011, Sep 2012 and Oct 2012 are in thousands, not seasonally adjusted. The average yearly participation rate of the population in the labor force was in the range of 66.0 percent minimum to 67.1 percent maximum between 2000 and 2006 with the average of 66.4 percent (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). The objective of Table ESI-1 is to assess how many people could have left the labor force because they do not think they can find another job. Row “LF PART 66.2 %” applies the participation rate of 2006, almost equal to the rates for 2000 to 2006, to the noninstitutional civilian population in Sep and Oct 2012 and Oct 2011 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 64.1 percent by Oct 2011 and was 63.6 percent in Sep 2012 and 63.8 percent in Oct 2012, suggesting that many people simply gave up on finding another job. Row “∆ NLF UEM” calculates the number of people not counted in the labor force because they could have given up on finding another job by subtracting from the labor force with participation rate of 66.2 percent (row “LF PART 66.2%”) the labor force estimated in the household survey (row “LF”). Total unemployed (row “Total UEM”) is obtained by adding unemployed in row “∆NLF UEM” to the unemployed of the household survey in row “UEM.” The row “Total UEM%” is the effective total unemployed “Total UEM” as percent of the effective labor force in row “LF PART 66.2%.” The results are that: (1) there are an estimated 5.737 million unemployed in Oct 2012 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM); (2) the total number of unemployed is effectively 17.478 million (Total UEM) and not 11.741 million (UEM) of whom many have been unemployed long term; (3) the rate of unemployment is 10.8 percent (Total UEM%) and not 7.5 percent, not seasonally adjusted, or 7.9 percent seasonally adjusted; and (4) the number of people in job stress is close to 28.1 million by adding the 5.737 million leaving the labor force because they believe they could not find another job. The row “In Job Stress” in Table ESI-1 provides the number of people in job stress not seasonally adjusted at 28.1 million in Oct 2012, adding the total number of unemployed (“Total UEM”), plus those involuntarily in part-time jobs because they cannot find anything else (“Part Time Economic Reasons”) and the marginally attached to the labor force (“Marginally attached to LF”). The final row of Table ESI-1 shows that the number of people in job stress is equivalent to 17.4 percent of the labor force in Sep 2012. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 58.7 percent in Oct 2011, 58.8 percent in Sep 2012 and 59.0 percent in Oct 2012; the number employed (EMP) dropped from 144 million in 2006 to 140.039 million in Oct 2012 while population increased from 229.420 million in Sep 2006 to 243.983 million in Oct 2012 or by 14.563 million. What really matters for labor input in production and wellbeing is the number of people with jobs or the employment/population ratio, which has declined and does not show signs of increasing. There are several million fewer people working in 2012 than in 2006 and the number employed is not increasing while population increased 14.563 million. The number of hiring relative to the number unemployed measures the chances of becoming employed. The number of hiring in the US economy has declined by 17 million and does not show signs of increasing in an unusual recovery without hiring (http://cmpassocregulationblog.blogspot.com/2012/10/recovery-without-hiring-imf-view-united.html).

Table ESI-1, US, Population, Labor Force and Unemployment, NSA

	2006	Oct 2011	Sep 2012	Oct 2012
POP	229	240,269	243,772	243,983
LF	151	154,088	155,075	155,779
PART%	66.2	64.1	63.6	63.8
EMP	144	140,987	143,333	144,039
EMP/POP%	62.9	58.7	58.8	59.0
UEM	7	13,102	11,742	11,741
UEM/LF Rate%	4.6	8.5	7.6	7.5
NLF	77	86,181	88,697	88,204
LF PART 66.2%		159,058	161,377	161,516
∆NLF UEM		4,970	6,302	5,737
Total UEM		18,072	18,044	17,478
Total UEM%		11.4	11.2	10.8
Part Time Economic Reasons		8,258	8,110	7,870
Marginally Attached to LF		2,555	2,517	2,433
In Job Stress		29,477	28,671	28,085
People in Job Stress as % Labor Force		18.5	17.8	17.4

Pop: population; LF: labor force; PART: participation; EMP: employed; UEM: unemployed; NLF: not in labor force; ∆NLF UEM: additional unemployed; Total UEM is UEM + ∆NLF UEM; Total UEM% is Total UEM as percent of LF PART 66.2%; In Job Stress = Total UEM + Part Time Economic Reasons + Marginally Attached to LF

Note: the first column for 2006 is in average millions; the remaining columns are in thousands; NSA: not seasonally adjusted

The labor force participation rate of 66.2% in 2006 is applied to current population to obtain LF PART 66.2%; ∆NLF UEM is obtained by subtracting the labor force with participation of 66.2 percent from the household survey labor force LF; Total UEM is household data unemployment plus ∆NLF UEM; and total UEM% is total UEM divided by LF PART 66.2%

Sources: US Bureau of Labor Statistics http://www.bls.gov/data/

ESII Declining Real Wages. The deterioration of purchasing power of average hourly earnings of US workers is shown by Chart ESII-1 of the US Bureau of Labor Statistics. Chart IB-2 plots average hourly earnings of all US employees in constant 1982-1984 dollars with evident decline from 2010 to 2012.

Chart ESII-1, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Chart ESII-2 provides 12-month percentage changes of average hourly earnings of all employees in constant dollars of 1982-1984, that is, adjusted for inflation. There was sharp contraction of inflation-adjusted average hourly earnings of US employees during parts of 2007 and 2008. Rates of change in 12 months became positive in parts of 2009 and 2010 but then became negative again in 2011 and now into 2012 with temporary increase in Apr 2012 that was reversed in May with another gain in Jun and Jul 2012 followed by stagnation in Aug 2012 and marginal gain in Sep 2012.

Chart ESII-2, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2012

Source: US Bureau of Labor Statistics

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

ESIII Collapse of United States Dynamism of Income Growth and Employment Creation. There are four major approaches to the analysis of the depth of the financial crisis and global recession from IVQ2007 (Dec) to IIQ2009 (Jun) and the subpar recovery from IIIQ2009 (Jul) to the present IIIQ2012: (1) deeper contraction and slower recovery in recessions with financial crises; (2) counterfactual of avoiding deeper contraction by fiscal and monetary policies; (3) counterfactual that the financial crises and global recession would have been avoided had economic policies been different; and (4) evidence that growth rates are higher after deeper recessions with financial crises. A counterfactual consists of theory and measurements of what would have occurred otherwise if economic policies or institutional arrangements had been different. This task is quite difficult because economic data are observed with all effects as they actually occurred while the counterfactual attempts to evaluate how data would differ had policies and institutional arrangements been different (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008b), 125, 136). Counterfactual data are unobserved and must be calculated using theory and measurement methods. The measurement of costs and benefits of projects or applied welfare economics (Harberger 1971, 1997) specifies and attempts to measure projects such as what would be economic welfare with or without a bridge or whether markets would be more or less competitive in the absence of antitrust and regulation laws (Winston 2006). Counterfactuals were used in the “new economic history” of the United States to measure the economy with or without railroads (Fishlow 1965, Fogel 1964) and also in analyzing slavery (Fogel and Engerman 1974). A critical counterfactual in economic history is how Britain surged ahead of France (North and Weingast 1989). These four approaches are discussed below in turn followed with comparison of the two recessions of the 1980s from IQ1980 (Jan) to IIIQ1980 (Jul) and from IIIQ1981 (Jul) to IVQ1982 (Nov) as dated by the National Bureau of Economic Research (NBER http://www.nber.org/cycles.html). These comparisons are not idle exercises, defining the interpretation of history and even possibly critical policies and institutional arrangements. There is active debate on these issues (Bordo 2012Oct 21 http://www.bloomberg.com/news/2012-10-21/why-this-u-s-recovery-is-weaker.html Reinhart and Rogoff, 2012Oct14 http://www.economics.harvard.edu/faculty/rogoff/files/Is_US_Different_RR_3.pdf Taylor 2012Oct 25 http://www.johnbtaylorsblog.blogspot.co.uk/2012/10/an-unusually-weak-recovery-as-usually.html, Wolf 2012Oct23 http://www.ft.com/intl/cms/s/0/791fc13a-1c57-11e2-a63b-00144feabdc0.html#axzz2AotsUk1q).

(1) Lower Growth Rates in Recessions with Financial Crises. A monumental effort of data gathering, calculation and analysis by Professors Carmen M. Reinhart and Kenneth Rogoff at Harvard University is highly relevant to banking crises, financial crash, debt crises and economic growth (Reinhart 2010CB; Reinhart and Rogoff 2011AF, 2011Jul14, 2011EJ, 2011CEPR, 2010FCDC, 2010GTD, 2009TD, 2009AFC, 2008TDPV; see also Reinhart and Reinhart 2011Feb, 2010AF and Reinhart and Sbrancia 2011). See http://cmpassocregulationblog.blogspot.com/2011/07/debt-and-financial-risk-aversion-and.html. The dataset of Reinhart and Rogoff (2010GTD, 1) is quite unique in breadth of countries and over time periods:

“Our results incorporate data on 44 countries spanning about 200 years. Taken together, the data incorporate over 3,700 annual observations covering a wide range of political systems, institutions, exchange rate and monetary arrangements and historic circumstances. We also employ more recent data on external debt, including debt owed by government and by private entities.”

Reinhart and Rogoff (2010GTD, 2011CEPR) classify the dataset of 2317 observations into 20 advanced economies and 24 emerging market economies. In each of the advanced and emerging categories, the data for countries is divided into buckets according to the ratio of gross central government debt to GDP: below 30, 30 to 60, 60 to 90 and higher than 90 (Reinhart and Rogoff 2010GTD, Table 1, 4). Median and average yearly percentage growth rates of GDP are calculated for each of the buckets for advanced economies. There does not appear to be any relation for debt/GDP ratios below 90. The highest growth rates are for debt/GDP ratios below 30: 3.7 percent for the average and 3.9 for the median. Growth is significantly lower for debt/GDP ratios above 90: 1.7 for the average and 1.9 percent for the median. GDP growth rates for the intermediate buckets are in a range around 3 percent: the highest 3.4 percent average is for the bucket 60 to 90 and 3.1 percent median for 30 to 60. There is even sharper contrast for the United States: 4.0 percent growth for debt/GDP ratio below 30; 3.4 percent growth for debt/GDP ratio of 30 to 60; 3.3 percent growth for debt/GDP ratio of 60 to 90; and minus 1.8 percent, contraction, of GDP for debt/GDP ratio above 90.

For the five countries with systemic financial crises—Iceland, Ireland, UK, Spain and the US—real average debt levels have increased by 75 percent between 2007 and 2009 (Reinhart and Rogoff 2010GTD, Figure 1). The cumulative increase in public debt in the three years after systemic banking crisis in a group of episodes after World War II is 86 percent (Reinhart and Rogoff 2011CEPR, Figure 2, 10).

An important concept is “this time is different syndrome,” which “is rooted in the firmly-held belief that financial crises are something that happens to other people in other countries at other times; crises do not happen here and now to us” (Reinhart and Rogoff 2010FCDC, 9). There is both an arrogance and ignorance in “this time is different” syndrome, as explained by Reinhart and Rogoff (2010FCDC, 34):

“The ignorance, of course, stems from the belief that financial crises happen to other people at other time in other places. Outside a small number of experts, few people fully appreciate the universality of financial crises. The arrogance is of those who believe they have figured out how to do things better and smarter so that the boom can long continue without a crisis.”

There is sober warning by Reinhart and Rogoff (2011CEPR, 42) on the basis of the momentous effort of their scholarly data gathering, calculation and analysis:

“Despite considerable deleveraging by the private financial sector, total debt remains near its historic high in 2008. Total public sector debt during the first quarter of 2010 is 117 percent of GDP. It has only been higher during a one-year sting at 119 percent in 1945. Perhaps soaring US debt levels will not prove to be a drag on growth in the decades to come. However, if history is any guide, that is a risky proposition and over-reliance on US exceptionalism may only be one more example of the “This Time is Different” syndrome.”

As both sides of the Atlantic economy maneuver around defaults the experience on debt and growth deserves significant emphasis in research and policy. The world economy is slowing with high levels of unemployment in advanced economies. Countries do not grow themselves out of unsustainable debts but rather through de facto defaults by means of financial repression and in some cases through inflation. The conclusion is that this time is not different.

Professor Alan M. Taylor (2012) at the University of Virginia analyzes own and collaborative research on 140 years of history with data from 14 advanced economies in the effort to elucidate experience anticipating, during and after financial crises. The conclusion is (Allan M. Taylor 2012, 8):

“Recessions might be painful, but they tend to be even more painful when combined with financial crises or (worse) global crises, and we already know that post-2008 experience will not overturn this conclusion. The impact on credit is also very strong: financial crises lead to strong setbacks in the rate of growth of loans as compared to what happens in normal recessions, and this effect is strong for global crises. Finally, inflation generally falls in recessions, but the downdraft is stronger in financial crisis times.”

Alan M. Taylor (2012) also finds that advanced economies entered the global recession with the largest financial sector in history. There was doubling after 1980 of the ratio of loans to GDP and tripling of the size of bank balance sheets. In contrast, in the period from 1950 to 1970 there was high investment, savings and growth in advanced economies with firm regulation of finance and controls of foreign capital flows.

(2) Counterfactual of the Global Recession. There is a difficult decision on when to withdraw the fiscal stimulus that could have adverse consequences on current growth and employment analyzed by Krugman (2011Jun18). CBO (2011JunLTBO, Chapter 2) considers the timing of withdrawal as well as the equally tough problems that result from not taking prompt action to prevent a possible debt crisis in the future. Krugman (2011Jun18) refers to Eggertsson and Krugman (2010) on the possible contractive effects of debt. The world does not become poorer as a result of debt because an individual’s asset is another’s liability. Past levels of credit may become unacceptable by credit tightening, such as during a financial crisis. Debtors are forced into deleveraging, which results in expenditure reduction, but there may not be compensatory effects by creditors who may not be in need of increasing expenditures. The economy could be pushed toward the lower bound of zero interest rates, or liquidity trap, remaining in that threshold of deflation and high unemployment.

Analysis of debt can lead to the solution of the timing of when to cease stimulus by fiscal spending (Krugman 2011Jun18). Excessive debt caused the financial crisis and global recession and it is difficult to understand how more debt can recover the economy. Krugman (2011Jun18) argues that the level of debt is not important because one individual’s asset is another individual’s liability. The distribution of debt is important when economic agents with high debt levels are encountering different constraints than economic agents with low debt levels. The opportunity for recovery may exist in borrowing by some agents that can adjust the adverse effects of past excessive borrowing by other agents. As Krugman (2011Jun18, 20) states:

“Suppose, in particular, that the government can borrow for a while, using the borrowed money to buy useful things like infrastructure. The true social cost of these things will be very low, because the spending will be putting resources that would otherwise be unemployed to work. And government spending will also make it easier for highly indebted players to pay down their debt; if the spending is sufficiently sustained, it can bring the debtors to the point where they’re no longer so severely balance-sheet constrained, and further deficit spending is no longer required to achieve full employment. Yes, private debt will in part have been replaced by public debt – but the point is that debt will have been shifted away from severely balance-sheet-constrained players, so that the economy’s problems will have been reduced even if the overall level of debt hasn’t fallen. The bottom line, then, is that the plausible-sounding argument that debt can’t cure debt is just wrong. On the contrary, it can – and the alternative is a prolonged period of economic weakness that actually makes the debt problem harder to resolve.”

Besides operational issues, the consideration of this argument would require specifying and measuring two types of gains and losses from this policy: (1) the benefits in terms of growth and employment currently; and (2) the costs of postponing the adjustment such as in the exercise by CBO (2011JunLTO, 28-31) in Table 11. It may be easier to analyze the costs and benefits than actual measurement.

An analytical and empirical approach is followed by Blinder and Zandi (2010), using the Moody’s Analytics model of the US economy with four different scenarios: (1) baseline with all policies used; (2) counterfactual including all fiscal stimulus policies but excluding financial stimulus policies; (3) counterfactual including all financial stimulus policies but excluding fiscal stimulus; and (4) a scenario excluding all policies. The scenario excluding all policies is an important reference or the counterfactual of what would have happened if the government had been entirely inactive. A salient feature of the work by Blinder and Zandi (2010) is the consideration of both fiscal and financial policies. There was probably more activity with financial policies than with fiscal policies. Financial policies included the Fed balance sheet, 11 facilities of direct credit to illiquid segments of financial markets, interest rate policy, the Financial Stability Plan including stress tests of banks, the Troubled Asset Relief Program (TARP) and others (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 157-67; Regulation of Banks and Finance (2009a), 224-7).

Blinder and Zandi (2010, 4) find that:

“In the scenario that excludes all the extraordinary policies, the downturn con­tinues into 2011. Real GDP falls a stunning 7.4% in 2009 and another 3.7% in 2010 (see Table 3). The peak-to-trough decline in GDP is therefore close to 12%, compared to an actual decline of about 4%. By the time employment hits bottom, some 16.6 million jobs are lost in this scenario—about twice as many as actually were lost. The unemploy­ment rate peaks at 16.5%, and although not determined in this analysis, it would not be surprising if the underemployment rate approached one-fourth of the labor force. The federal budget deficit surges to over $2 trillion in fiscal year 2010, $2.6 trillion in fis­cal year 2011, and $2.25 trillion in FY 2012. Remember, this is with no policy response. With outright deflation in prices and wages in 2009-2011, this dark scenario constitutes a 1930s-like depression.”

The conclusion by Blinder and Zandi (2010) is that if the US had not taken massive fiscal and financial measures the economy could have suffered far more during a prolonged period. There are still a multitude of questions that cloud understanding of the impact of the recession and what would have happened without massive policy impulses. Some effects are quite difficult to measure. An important argument by Blinder and Zandi (2010) is that this evaluation of counterfactuals is relevant to the need of stimulus if economic conditions worsened again.

(3) Counterfactual of Policies Causing the Financial Crisis and Global Recession. The counterfactual of avoidance of deeper and more prolonged contraction by fiscal and monetary policies is not the critical issue. As Professor John B. Taylor (2012Oct25) argues the critically important counterfactual is that the financial crisis and global recessions would have not occurred in the first place if different economic policies had been followed. The counterfactual intends to verify that a combination of housing policies and discretionary monetary policies instead of rules (Taylor 1993) caused, deepened and prolonged the financial crisis (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB; see http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html) and that the experience resembles that of the Great Inflation of the 1960s and 1970s with stop-and-go growth/inflation that coined the term stagflation (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html 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 explanation of the sharp contraction of United States housing can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:

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

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

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

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

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

W = Y/r (1)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

According to Pinto (2008) in testimony to Congress:

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

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

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

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

(4) Historically Sharper Recoveries from Deeper Contractions and Financial Crises. Professor Michael D. Bordo (2012Sep27), at Rutgers University, is providing clear thought on the correct comparison of the current business cycles in the United States with those in United States history. There are two issues raised by Professor Bordo: (1) lumping together countries with different institutions, economic policies and financial systems; and (2) the conclusion that growth is mediocre after financial crises and deep recessions, which is repeated daily in the media, but that Bordo and Haubrich (2012DR) persuasively demonstrate to be inconsistent with United States experience.

Depriving economic history of institutions is perilous as is illustrated by the economic history of Brazil. Douglass C. North (1994) emphasized the key role of institutions in explaining economic history. Rondo E. Cameron (1961, 1967, 1972) applied institutional analysis to banking history. Friedman and Schwartz (1963) analyzed the relation of money, income and prices in the business cycle and related the monetary policy of an important institution, the Federal Reserve System, to the Great Depression. Bordo, Choudhri and Schwartz (1995) analyze the counterfactual of what would have been economic performance if the Fed had used during the Great Depression the Friedman (1960) monetary policy rule of constant growth of money(for analysis of the Great Depression see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 198-217). Alan Meltzer (2004, 2010a,b) analyzed the Federal Reserve System over its history. The reader would be intrigued by Figure 5 in Reinhart and Rogoff (2010FCDC, 15) in which Brazil is classified in external default for seven years between 1828 and 1834 but not again until 64 years later in 1989, above the 50 years of incidence for “serial default”. This void has been filled in scholarly research on nineteenth-century Brazil by William R. Summerhill, Jr. (2007SC, 2007IR). There are important conclusions by Summerhill on the exceptional sample of institutional change or actually lack of change, public finance and financial repression in Brazil between 1822 an 1899, combining tools of economics, political science and history. During seven continuous decades, Brazil did not miss a single interest payment with government borrowing without repudiation of debt or default. What is really surprising is that Brazil borrowed by means of long-term bonds and even more surprising interest rates fell over time. The external debt of Brazil in 1870 was ₤41,275,961 and the domestic debt in the internal market was ₤25,708,711, or 62.3 percent of the total (Summerhill 2007IR, 73).

The experience of Brazil differed from that of Latin America (Summerhill 2007IR). During the six decades when Brazil borrowed without difficulty, Latin American countries becoming independent after 1820 engaged in total defaults, suffering hardship in borrowing abroad. The countries that borrowed again fell again in default during the nineteenth century. Venezuela defaulted in four occasions. Mexico defaulted in 1827, rescheduling its debt eight different times and servicing the debt sporadically. About 44 percent of Latin America’s sovereign debt was in default in 1855 and approximately 86 percent of total government loans defaulted in London originated in Spanish American borrowing countries.

External economies of commitment to secure private rights in sovereign credit would encourage development of private financial institutions, as postulated in classic work by North and Weingast (1989), Summerhill 2007IR, 22). This is how banking institutions critical to the Industrial Revolution were developed in England (Cameron 1967). The obstacle in Brazil found by Summerhill (2007IR) is that sovereign debt credibility was combined with financial repression. There was a break in Brazil of the chain of effects from protecting public borrowing, as in North and Weingast (1989), to development of private financial institutions. According to Pelaez 1976, 283) following Cameron:

“The banking law of 1860 placed severe restrictions on two basic modern economic institutions—the corporation and the commercial bank. The growth of the volume of bank credit was one of the most significant factors of financial intermediation and economic growth in the major trading countries of the gold standard group. But Brazil placed strong restrictions on the development of banking and intermediation functions, preventing the channeling of coffee savings into domestic industry at an earlier date.”

Brazil actually abandoned the gold standard during multiple financial crises in the nineteenth century, as it should have to protect domestic economic activity. Pelaez (1975, 447) finds similar experience in the first half of nineteenth-century Brazil:

“Brazil’s experience is particularly interesting in that in the period 1808-1851 there were three types of monetary systems. Between 1808 and 1829, there was only one government-related Bank of Brazil, enjoying a perfect monopoly of banking services. No new banks were established in the 1830s after the liquidation of the Bank of Brazil in 1829. During the coffee boom in the late 1830s and 1840s, a system of banks of issue, patterned after similar institutions in the industrial countries, supplied the financial services required in the first stage of modernization of the export economy.”

Financial crises in the advanced economies were transmitted to nineteenth-century Brazil by the arrival of a ship (Pelaez and Suzigan 1981). The explanation of those crises and the economy of Brazil requires knowledge and roles of institutions, economic policies and the financial system chosen by Brazil, in agreement with Bordo (2012Sep27).

The departing theoretical framework of Bordo and Haubrich (2012DR) is the plucking model of Friedman (1964, 1988). Friedman (1988, 1) recalls “I was led to the model in the course of investigating the direction of influence between money and income. Did the common cyclical fluctuation in money and income reflect primarily the influence of money on income or of income on money?” Friedman (1964, 1988) finds useful for this purpose to analyze the relation between expansions and contractions. Analyzing the business cycle in the United States between 1870 and 1961, Friedman (1964, 15) found that “a large contraction in output tends to be followed on the average by a large business expansion; a mild contraction, by a mild expansion.” The depth of the contraction opens up more room in the movement toward full employment (Friedman 1964, 17):

“Output is viewed as bumping along the ceiling of maximum feasible output except that every now and then it is plucked down by a cyclical contraction. Given institutional rigidities and prices, the contraction takes in considerable measure the form of a decline in output. Since there is no physical limit to the decline short of zero output, the size of the decline in output can vary widely. When subsequent recovery sets in, it tends to return output to the ceiling; it cannot go beyond, so there is an upper limit to output and the amplitude of the expansion tends to be correlated with the amplitude of the contraction.”

Kim and Nelson (1999) test the asymmetric plucking model of Friedman (1964, 1988) relative to a symmetric model using reference cycles of the NBER and find evidence supporting the Friedman model. Bordo and Haubrich (2012DR) analyze 27 cycles beginning in 1872, using various measures of financial crises while considering different regulatory and monetary regimes. The revealing conclusion of Bordo and Haubrich (2012DR, 2) is that:

“Our analysis of the data shows that steep expansions tend to follow deep contractions, though this depends heavily on when the recovery is measured. In contrast to much conventional wisdom, the stylized fact that deep contractions breed strong recoveries is particularly true when there is a financial crisis. In fact, on average, it is cycles without a financial crisis that show the weakest relation between contraction depth and recovery strength. For many configurations, the evidence for a robust bounce-back is stronger for cycles with financial crises than those without.”

The average rate of growth of real GDP in expansions after recessions with financial crises was 8 percent but only 6.9 percent on average for recessions without financial crises (Bordo 2012Sep27). Real GDP declined 12 percent in the Panic of 1907 and increased 13 percent in the recovery, consistent with the plucking model of Friedman (Bordo 2012Sep27). Bordo (2012Sep27) finds two probable explanations for the weak recovery during the current economic cycles: (1) collapse of United States housing; and (2) uncertainty originating in fiscal policy, regulation and structural changes. There are serious doubts if monetary policy is adequate to recover the economy under these conditions.

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. Lucas (2011May) finds that the catch up stalled in the 1970s. The analysis of Lucas (2011May) is that the 20-40 percent gap that developed originated in differences in relative taxation and regulation that discouraged savings and work incentives in comparison with the US. A larger welfare and regulatory state, according to Lucas (2011May), could be the cause of the 20-40 percent gap. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Long-term economic growth and prosperity are measured by the key indicators of growth of real income per capita, or what is earned per person after inflation. A refined concept would include real disposable income per capita, or what is earned per person after inflation and taxes.

Table ESIII-1 provides the data required for broader comparison of the cyclical expansions of IQ1983 to IVQ1985 and the current one from 2009 to 2012. First, in the 13 quarters from IQ1983 to IVQ1985, GDP increased 19.6 percent at the annual equivalent rate of 5.7 percent; real disposable personal income (RDPI) increased 14.5 percent at the annual equivalent rate of 4.3 percent; RDPI per capita increased 11.5 percent at the annual equivalent rate of 3.4 percent; and population increased 2.7 percent at the annual equivalent rate of 0.8 percent. Second, in the 13 quarters of the current cyclical expansion from IIIQ2009 to IIIQ2012, GDP increased 7.2 percent at the annual equivalent rate of 2.2 percent. In the 12 quarters of cyclical expansion real disposable personal income (RDPI) increased 5.7 percent at the annual equivalent rate of 1.7 percent; RDPI per capita increased 3.3 percent at the annual equivalent rate of 1.0 percent; and population increased 2.3 percent at the annual equivalent rate of 0.7 percent. Third, since the beginning of the recession in IVQ2007 to IIIQ2012, GDP increased 2.2 percent, or barely above the level before the recession. Since the beginning of the recession in IVQ2007 to IIIQ2012, real disposable personal income increased 3.7 percent at the annual equivalent rate of 0.7 percent; population increased 3.9 percent at the annual equivalent rate of 0.8 percent; and real disposable personal income per capita is 0.2 percent lower than the level before the recession. Real disposable personal income is the actual take home pay after inflation and taxes and real disposable income per capita is what is left per inhabitant. The current cyclical expansion is the worst in the period after World War II in terms of growth of economic activity and income. The United States grew during its history at high rates of per capita income that made its economy the largest in the world. That dynamism is disappearing. Bordo (2012 Sep27) and Bordo and Haubrich (2012DR) provide strong evidence that recoveries have been faster after deeper recessions and recessions with financial crises, casting serious doubts on the conventional explanation of weak growth during the current expansion allegedly because of the depth of the contraction from IVQ2007 to IIQ2009 of 4.7 percent and the financial crisis.

Table ESIII-1, US, GDP, Real Disposable Personal Income, Real Disposable Income per Capita and Population in 1983-85 and 2007-2011, %

	# Quarters	∆%	∆% Annual Equivalent
IQ1983 to IVQ1985	13
GDP		19.6	5.7
RDPI		14.5	4.3
RDPI Per Capita		11.5	3.4
Population		2.7	0.8
IIIQ2009 to IIIQ2012	13
GDP		7.2	2.2
RDPI		5.7	1.7
RDPI per Capita		3.3	1.0
Population		2.3	0.7
IVQ2007 to IIIQ2012	20
GDP		2.2	0.4
RDPI		3.7	0.7
RDPI per Capita		-0.2
Population		3.9	0.8

RDPI: Real Disposable Personal Income

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

There are six basic facts illustrating the current economic disaster of the United States: (1) GDP maintained trend growth in the entire business cycle from IQ1980 to IV1985, including contractions and expansions, but is well below trend in the entire business cycle from IVQ2007 to IIQ2012, including contractions and expansions; (2) per capita real disposable income exceeded trend growth in the 1980s but is substantially below trend in IIQ2012; (3) the number of employed persons increased in the 1980s but declined into IIQ2012; (4) the number of full-time employed persons increased in the 1980s but declined into IIQ2012; (5) the number unemployed, unemployment rate and number employed part-time for economic reasons fell in the recovery from the recessions of the 1980s but not substantially in the recovery after IIQ2009; and (6) wealth of households and nonprofit organizations soared in the 1980s but declined into IIQ2012. There is a critical issue of whether the United States economy will be able in the future to attain again the level of activity and prosperity of projected trend growth. Growth at trend during the entire business cycles built the largest economy in the world but there may be an adverse, permanent weakness in United States economic performance and prosperity. Table ESIII-2 provides data for analysis of these five basic facts. The six blocks of Table ESIII-2 are separated initially after individual discussion of each one followed by the full Table ESIII-2.

1. Trend Growth.

i. As shown in Table ESIII-2, actual GDP grew cumulatively 17.7 percent from IQ1980 to IVQ1985, which is relatively close to what trend growth would have been at 18.5 percent. Rapid growth at 5.7 percent annual rate on average per quarter during the expansion from IQ1983 to IVQ1985 erased the loss of GDP of 4.8 percent during the contraction and maintained trend growth at 3 percent over the entire cycle.

ii. In contrast, cumulative growth from IVQ2007 to IIIQ2012 was 2.2 percent while trend growth would have been 15.1 percent. GDP in IIIQ2012 at seasonally adjusted annual rate is estimated at $13,616.2 percent by the Bureau of Economic Analysis (BEA) (http://www.bea.gov/iTable/index_nipa.cfm) and would have been $15,338.2 billion, or $1,722 billion higher, had the economy grown at trend over the entire business cycle as it happened during the 1980s and throughout most of US history. There is $1.7 trillion of foregone GDP that would have been created as it occurred during past cyclical expansions, which explains why employment has not rebounded to even higher than before. There would not be recovery of full employment even with growth of 3 percent per year beginning immediately because the opportunity was lost to grow faster during the expansion from IIIQ2009 to IIIQ2012 after the recession from IVQ2007 to IIQ2009. The United States has acquired a heavy social burden of unemployment and underemployment of 28.1 million people or 17.4 percent of the effective labor force (Table ESI-1) that will not be significantly diminished even with return to growth of GDP of 3 percent per year because of growth of the labor force by new entrants. The US labor force grew from 142.583 million in 2000 to 153.124 million in 2007 or by 7.4 percent at the average yearly rate of 1.0 percent per year. The civilian noninstitutional population increased from 212.577 million in 2000 to 231.867 million in 2007 or 9.1 percent at the average yearly rate of 1.3 percent per year (data from http://www.bls.gov/data/). Data for the past five years cloud accuracy because of the number of people discouraged from seeking employment. The noninstitutional population of the United States increased from 231.867 million in 2007 to 239.618 million in 2011 or by 3.3 percent while the labor force increased from 153.124 million in 2007 to 153.617 million in 2011 or by 0.3 percent (data from http://www.bls.gov/data/). People ceased to seek jobs because they do not believe that there is a job available for them (Section I and earlier at http://cmpassocregulationblog.blogspot.com/2012/10/twenty-nine-million-unemployed-or.html).

Period IQ1980 to IVQ1985
GDP SAAR USD Billions
IQ1980	5,903.4
IVQ1985	6,950.0
∆% IQ1980 to IVQ1985	17.7
∆% Trend Growth IQ1980 to IVQ1985	18.5

Period IVQ2007 to IIIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIIQ2012	13,616.2
∆% IVQ2007 to IIIQ2012 Actual	2.2
∆% IVQ2007 to IIIQ2012 Trend	15.1

2. Decline of Per Capita Real Disposable Income

i. In the entire business cycle from IQ1980 to IVQ1985, as shown in Table ESIII-2 trend growth of per capita real disposable income, or what is left per person after inflation and taxes, grew cumulatively 14.5 percent, which is close to what would have been trend growth of 12.1 percent.

ii. In contrast, in the entire business cycle from IVQ2007 to IIIQ2012, per capita real disposable income fell 0.2 percent while trend growth would have been 10.4 percent. Income available after inflation and taxes is lower than before the contraction after 13 consecutive quarters of GDP growth at mediocre rates relative to those prevailing during historical cyclical expansions.

Period IQ1980 to IVQ1985

Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD	18,938
Real Disposable Personal Income per Capita IVQ1985 Chained 2005 USD	21,687
∆% IQ1980 to IVQ1985	14.5
∆% Trend Growth	12.1

Period IVQ2007 to IIIQ2012

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIIQ2012 Chained 2005 USD	32,778
∆% IVQ2007 to IIIQ2012	-0.2
∆% Trend Growth	10.4

3. Number of Employed Persons

i. As shown in Table ESIII-2, the number of employed persons increased over the entire business cycle from 98.527 million not seasonally adjusted (NSA) in IQ1980 to 107.819 million NSA in IVQ1985 or by 9.4 percent.

ii. In contrast, during the entire business cycle the number employed fell from 146.334 million in IVQ2007 to 143.202 million in IIIQ2012 or by 2.1 percent. There are 28.1 million persons unemployed or underemployed, which is 17.4 percent of the effective labor force (Section I, Table I-4).

Period IQ1980 to IVQ1985

Employed Millions IQ1980 NSA End of Quarter	98.527
Employed Millions IV1985 NSA End of Quarter	107.819
∆% Employed IQ1980 to IV1985	9.4

Period IVQ2007 to IIIQ2012

Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIIQ2012 NSA End of Quarter	143.333
∆% Employed IVQ2007 to IIIQ2012	-2.1

4. Number of Full-Time Employed Persons

i. As shown in Table ESIII-2, during the entire business cycle in the 1980s, including contractions and expansion, the number of employed full-time rose from 81.280 million NSA in IQ1980 to 88.757 million NSA in IVQ1985 or 9.2 percent.

ii. In contrast, during the entire current business cycle, including contraction and expansion, the number of persons employed full-time fell from 121.042 million in IVQ2007 to 115.678 million in IIIQ2012 or by minus 4.4 percent.

Period IQ1980 to IVQ1985

Employed Full-time Millions IQ1980 NSA End of Quarter	81.280
Employed Full-time Millions IV1985 NSA End of Quarter	88.757
∆% Full-time Employed IQ1980 to IV1985	9.2

Period IVQ2007 to IIIQ2012

Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIIQ2012 NSA End of Quarter	115.678
∆% Full-time Employed IVQ2007 to IIIQ2012	-4.4

5. Unemployed, Unemployment Rate and Employed Part-time for Economic Reasons.

i. As shown in Table ESIII-2 and in the following block, in the cycle from IQ1980 to IVQ1985: (a) the rate of unemployment was virtually the same at 6.7 percent in IQ1985 relative to 6.6 percent in IQ1980; (b) the number unemployed increased from 6.983 million in IQ1980 to 7.717 million in IVQ1985 or 10.5 percent; and (c) the number employed part-time for economic reasons increased 49.1 percent from 3.624 million in IQ1980 to 5.402 million in IVQ1985.

ii. In contrast, in the economic cycle from IVQ2007 to IIIQ2012: (a) the rate of unemployment increased from 4.8 percent in IVQ2007 to 7.6 percent in IIIQ2012; (b) the number unemployed increased 59.3 percent from 7.371 million in IVQ2007 to 11.742 million in IIIQ2012; (c) the number employed part-time for economic reasons increased 70.7 percent from 4.750 million in IVQ2007 to 8.110 million in IIIQ2012; and (d) U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA increased from 8.7 percent in IVQ2007 to 14.2 percent in IIIQ2012.

Period IQ1980 to IVQ1985

Unemployment Rate IQ1980 NSA End of Quarter	6.6
Unemployment Rate  IV1985 NSA End of Quarter	6.7
Unemployed IQ1980 Millions End of Quarter	6.983
Unemployed IV 1985 Millions End of Quarter	7.717
Employed Part-time Economic Reasons Millions IQ1980 End of Quarter	3.624
Employed Part-time Economic Reasons Millions IVQ1985 End of Quarter	5.402
∆%	49.1

Period IVQ2007 to IIIQ2012

Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIIQ2012 NSA End of Quarter	7.6
Unemployed IVQ2007 Millions End of Quarter	7.371
Unemployed IIIQ2009 Millions End of Quarter	11.742
∆%	59.3
Employed Part-time Economic Reasons IVQ2007 Millions End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIIQ2009 End of Quarter	8.110
∆%	70.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007	8.7
IIIQ2012	14.2

6. Wealth of Households and Nonprofit Organizations.

i. The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and also from IVQ1979) to IVQ1985 and from IVQ2007 to IIQ2012 is provided in the following block and in Table ESIII-2. Net worth of households and nonprofit organizations increased from $8,326.4 billion in IVQ1979 to $14,395.2 billion in IVQ1985 or 72.9 percent or 69.3 percent from $8,502.9 billion in IQ1980. The starting quarter does not bias the results. The US consumer price index not seasonally adjusted increased from 76.7 in Dec 1979 to 109.3 in Dec 1985 or 42.5 percent or 36.5 percent from 80.1 in Mar 1980 (using consumer price index data from the US Bureau of Labor Statistics at http://www.bls.gov/cpi/data.htm). In terms of purchasing power measured by the consumer price index, real wealth of households and nonprofit organizations increased 21.3 percent in constant purchasing power from IVQ1979 to IVQ1985 or 24.0 percent from IQ1980.

ii. In contrast, as shown in the following block and in Table ESIII-2, net worth of households and nonprofit organizations fell from $66,057.1 billion in IVQ2007 to $62,668.4 billion in IIQ2012 by $3,388.7 billion or 5.1 percent. The US consumer price index was 210.036 in Dec 2007 and 229.478 in Jun 2012 for increase of 9.3 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 13.2 percent in Jun 2012 after 12 consecutive quarters of expansion from IIIQ2009 to IIQ2012 relative to IVQ2012 when the recession began. The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. The average growth rate from IIIQ2009 to IIQ2012 has been 2.2 percent, which is substantially lower than the average of 6.2 percent in cyclical expansions after World War II and 5.7 percent in the expansion from IQ1983 to IVQ1985 (see Table I-5 http://cmpassocregulationblog.blogspot.com/2012/10/mediocre-and-decelerating-united-states.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions.

Period IQ1980 to IVQ1985
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ1979	8,326.4
IVQ1985	14,395.2
∆ USD Billions	+6,068.8
Period IVQ2007 to IIQ2012
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ2007	66,057.1
IIQ2012	62,668.4
∆ USD Billions	-3,388.7

Table ESIII-2, US, GDP and Real Disposable Personal Income per Capita Actual and Trend Growth and Employment, 1980-1985 and 2007-2012, SAAR USD Billions, Millions of Persons and ∆%

Period IQ1980 to IVQ1985
GDP SAAR USD Billions
IQ1980	5,903.4
IVQ1985	6,950.0
∆% IQ1980 to IVQ1985	17.7
∆% Trend Growth IQ1980 to IVQ1985	18.5
Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD	18,938
Real Disposable Personal Income per Capita IVQ1985 Chained 2005 USD	21,687
∆% IQ1980 to IVQ1985	14.5
∆% Trend Growth	12.1
Employed Millions IQ1980 NSA End of Quarter	98.527
Employed Millions IV1985 NSA End of Quarter	107.819
∆% Employed IQ1980 to IV1985	9.4
Employed Full-time Millions IQ1980 NSA End of Quarter	81.280
Employed Full-time Millions IV1985 NSA End of Quarter	88.757
∆% Full-time Employed IQ1980 to IV1985	9.2
Unemployment Rate IQ1980 NSA End of Quarter	6.6
Unemployment Rate  IV1985 NSA End of Quarter	6.7
Unemployed IQ1980 Millions NSA End of Quarter	6.983
Unemployed IV 1985 Millions NSA End of Quarter	7.717
∆%	11.9
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 NSA End of Quarter	8.394
∆%	76.7
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ1979	8,326.4
IVQ1985	14,395.2
∆ USD Billions	+6,068.8
Period IVQ2007 to IIIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIIQ2012	13,616.2
∆% IVQ2007 to IIIQ2012	2.2
∆% IVQ2007 to IIIQ2012 Trend Growth	15.1
Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIIQ2012 Chained 2005 USD	32,778
∆% IVQ2007 to IIIQ2012	-0.2
∆% Trend Growth	10.4
Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIIQ2012 NSA End of Quarter	143.333
∆% Employed IVQ2007 to IIIQ2012	-2.1
Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIIQ2012 NSA End of Quarter	115.678
∆% Full-time Employed IVQ2007 to IIIQ2012	-4.4
Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIIQ2012 NSA End of Quarter	7.6
Unemployed IVQ2007 Millions NSA End of Quarter	7.371
Unemployed IIIQ2009 Millions NSA End of Quarter	11.742
∆%	59.3
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIIQ2009 NSA End of Quarter	8.110
∆%	70.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007	8.7
IIIQ2012	14.2
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ2007	66,057.1
IIQ2012	62,668.4
∆ USD Billions	-3,388.7

Note: GDP trend growth used is 3.0 percent per year and GDP per capita is 2.0 percent per year as estimated by Lucas (2011May) on data from 1870 to 2010.

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm US Bureau of Labor Statistics http://www.bls.gov/data/. Board of Governors of the Federal Reserve System. 2012Sep20. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System.

I Twenty Nine Million Unemployed or Underemployed. The employment situation report of the Bureau of Labor Statistics (BLS) of the US Department of Labor released in the first Fri of every month is critical in the analysis of social and economic conditions in the US. The objective of this section is to analyze the report released on Nov 2, 2012, for Oct 2012 (http://www.bls.gov/news.release/pdf/empsit.pdf). The analysis of the employment situation of the US is divided into two sections. I Twenty Nine Million Unemployed or Underemployed provides the key data on employment and job creation contained in the BLS report. These data are complemented by the BLS report on hiring, job openings and separations to be released on Tue Nov 6, 2012 (http://www.bls.gov/jlt/), which will be analyzed in this blog’s comment of Aug 11 with the latest report analyzed in the blog comment for Oct 14, 2012 (http://cmpassocregulationblog.blogspot.com/2012/10/recovery-without-hiring-imf-view-united.html). IB Stagnating Real Wages analyzes wages and hours worked. IA1 Summary of the Employment Situation provides brief analysis of the employment situation. IA2 Number of People in Job Stress provides the calculation of people unemployed or underemployed in the US using the estimates of the BLS. IA3 Long-term and Cyclical Comparison of Employment provides the comparison with long-term and relevant cyclical experience in the US. IA4 Creation of Jobs analyzes the establishment survey of the BLS that provides job creation in nonfarm payrolls. Hourly and weekly earnings and hours worked are analyzed in the following section IB Stagnating Real Wages.

IA1 Summary of the Employment Situation. The Bureau of Labor Statistics (BLS) of the US Department of Labor provides both seasonally-adjusted (SA) and not-seasonally adjusted (NSA) or unadjusted data with important uses (Bureau of Labor Statistics 2012Feb3; 2011Feb11):

“Most series published by the Current Employment Statistics program reflect a regularly recurring seasonal movement that can be measured from past experience. By eliminating that part of the change attributable to the normal seasonal variation, it is possible to observe the cyclical and other nonseasonal movements in these series. Seasonally adjusted series are published monthly for selected employment, hours, and earnings estimates.”

Table I-1 provides summary statistics of the employment situation report of the BLS. The first four rows provide the data from the establishment report of creation of nonfarm payroll jobs and remuneration of workers (for analysis of the differences in employment between the establishment report and the household survey see Abraham, Haltiwanger, Sandusky and Spletzer 2009). Total nonfarm payroll employment seasonally adjusted (SA) increased 171,000 in Oct 2012 and private payroll employment rose 184,000. The number of nonfarm jobs and private jobs created has been declining 2012 from 275,000 in Jan to 45,000 in Jun, 148,000 in Sep and 171,000 in Oct for total nonfarm jobs and from 277,000 in Jan to 63,000 in Jun, 128,000 in Sep and 184,000 in Oct for private jobs. Average new nonfarm jobs in the quarter Dec 2011 to Feb 2012 were 252,333 per month, declining to average 129,375 per month in the eight months from Mar to Oct 2012. Average new private jobs in the quarter Dec 2011 to Feb 2012 were 255,000 per month, declining to average 127,500 per month in the eight months from Mar 2012 to Oct 2012. The US labor force stood at 154.088 million in Oct 2011 and at 155.779 million in Oct 2012, not seasonally adjusted, for increase of 1.691 million, or 140,917 per month. The average increase of 129,375 new nonfarm jobs per month in the US from Mar to Oct 2012 is insufficient even to absorb 140,917 new entrants per month into the labor force. There is not sufficient job creation to merely absorb new entrants in the labor force, worsening the stock of unemployed or underemployed in involuntary part-time jobs. Subsection IA4 Job Creation analyzes the types of jobs created. Average hourly earnings in Oct 2012 were $23.58 seasonally adjusted (SA), increasing 0.9 percent not seasonally adjusted (NSA) relative to Oct 2011 and increasing 0.0 percent relative to Sep 2012 seasonally adjusted. In Sep 2012, average hourly earnings seasonally adjusted were $23.59, increasing 2.6 percent relative to Sep 2011 not seasonally adjusted and increasing 0.3 percent seasonally adjusted relative to Aug 2012. These are nominal changes in workers’ wages. The following row “average hourly earnings in constant dollars” provides hourly wages in constant dollars calculated by the BLS or what is called “real wages” adjusted for inflation. Data are not available for Oct because the prices indexes of the BLS for Oct will only be released on Nov 15 (http://www.bls.gov/cpi/), which will be covered in this blog’s comment on Sep 18. The second column provides changes in real wages for Sep 2012. Average hourly earnings adjusted for inflation or in constant dollars increased 0.6 percent in Sep 2012 relative to Sep 2011 but have been decreasing during many consecutive months. World inflation waves in bouts of risk aversion (http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united.html) mask declining trend of real wages. The fractured labor market of the US is characterized by high levels of unemployment and underemployment together with falling real wages or wages adjusted for inflation in a recovery without hiring (http://cmpassocregulationblog.blogspot.com/2012/10/recovery-without-hiring-imf-view-united.html). The following section IB Stagnating Real Wages provides more detailed analysis. Average weekly hours of US workers not seasonally adjusted remained unchanged at 34.4. Another headline number widely followed is the unemployment rate or number of people unemployed as percent of the labor force. The unemployment rate calculated in the household survey increased from 7.8 percent in Sep 2012 to 7.9 percent in Oct 2012. This blog provides with every employment situation report the number of people in the US in job stress or unemployed plus underemployed calculated without seasonal adjustment (NSA) at 28.1 million in Oct 2012 and 28.7 million in Sep 2012. The final row in Table I-1 provides the number in job stress as percent of the actual labor force calculated at 17.4 percent in Oct 2012 and 17.8 percent in Sep 2012. Almost one in every five workers in the US is unemployed or underemployed. The combination of twenty-nine million people in job stress, falling or stagnating real wages, collapse of hiring (http://cmpassocregulationblog.blogspot.com/2012/10/recovery-without-hiring-imf-view-united.html), declining household net worth by three trillion dollars, household median income adjusted for inflation back to 1996 levels and forty-eight million people in poverty and without health insurance (http://cmpassocregulationblog.blogspot.com/2012/09/collapse-of-united-states-creation-of.html) constitutes a socio-economic disaster.

Table I-1, US, Summary of the Employment Situation Report SA

	Oct 2012	Sep 2012
New Nonfarm Payroll Jobs	171,000	148,000
New Private Payroll Jobs	184,000	128,000
Average Hourly Earnings	$23.58 SA ∆% Oct 12/Oct 11 NSA: 0.9 ∆% Oct 12/Sep 12 SA: 0.0	$23.59 SA ∆% Sep 12/Sep 11 NSA: 2.6 ∆% Sep 12/Aug 12 SA: 0.3
Average Hourly Earnings in Constant Dollars	NA	∆% Sep 2012/Sep 2011: 0.6
Average Weekly Hours	34.4	34.4
Unemployment Rate Household Survey % of Labor Force SA	7.9	7.8
Number in Job Stress Unemployed and Underemployed Blog Calculation	28.1 million NSA	28.7 million NSA
In Job Stress as % Labor Force	17.4	17.8

Source: US Bureau of Labor Statistics http://www.bls.gov/news.release/empsit.nr0.htm http://www.bls.gov/data/ See Tables I-2, I-3, I-4, I-8, IB-1, IB-3 and IB-4.

IA2 Number of People in Job Stress. There are two approaches to calculating the number of people in job stress. The first approach consists of calculating the number of people in job stress unemployed or underemployed with the raw data of the employment situation report as in Table I-2. The data are seasonally adjusted (SA). The first three rows provide the labor force and unemployed in millions and the unemployment rate of unemployed as percent of the labor force. There is decrease in the number unemployed from 12.544 million in Aug 2012 to 12.088 million in Sep 2012 or decrease of 456,000 and decrease to 12.258 million in Oct 2012 for decrease of 286,000 from Aug to Oct 2012. Thus, the rate of unemployment decreases from 8.1 percent in Aug 2012 to 7.8 percent in Sep, increasing to 7.9 percent in Oct 2012. The labor force SA increased from 154.645 million in Aug 2012 to 155.063 million in Sep 2012 or by 418,000 and increased to 155.641 in Oct 2012 for increase of 996,000 relative to Aug 2012. People have been dropping out of the labor force because they believe there are no jobs for them are actually unemployed but not counted as they stopped their job searches. An important aspect of unemployment is its persistence with 5.033 million in Aug who had been unemployed for 27 weeks or more, constituting 40.5 percent of the unemployed, 5.033 million in Aug or 40.1 percent of total unemployed, 4.844 million in Sep or 40.1 percent of total unemployed and 5.002 million in Oct or 40.8 percent of total unemployed. The longer the period of unemployment the lower are the chances of finding another job. Another key characteristic of the current labor market is the high number of people trying to subsist with part-time jobs because they cannot find full-time employment or part-time for economic reasons. The BLS explains as follows: “these individuals were working part time because their hours had been cut back or because they were unable to find a full-time job” (http://www.bls.gov/news.release/pdf/empsit.pdf 2). The number of part-time for economic reasons increased from 8.031 million in Aug 2012 to 8.613 million in Sep 2012 or by 582,000 but decreased to 8.344 million in Oct 2012 or 313,000 more people employed part-time in Oct relative to Aug because they cannot find full-time employment. Another category consists of people marginally attached to the labor force who have sought employment at some point but believe there may not be another job for them. The BLS explains as follows: “these individuals were not in the labor force, wanted and were available for work, and had looked for a job sometime in the prior 12 months. They were not counted as unemployed because they had not searched for work in the 4 weeks preceding the survey” (http://www.bls.gov/news.release/pdf/empsit.pdf 2). The number in job stress unemployed or underemployed of 23.035 million in Oct is composed of 12.258 million unemployed (of whom 5.002 million, or 40.8 percent, unemployed for 27 weeks or more) compared with 12.088 million unemployed in Sep (of whom 4.844 million, or 40.1 percent, unemployed for 27 weeks or more), 8.344 million employed part-time for economic reasons in Oct (who suffered reductions in their work hours or could not find full-time employment) compared with 8.613 million in Sep and 2.433 million who were marginally attached to the labor force in Oct (who were not in the labor force but wanted and were available for work) compared with 2.517 million in Sep. The final row in Table I-2 provides the number in job stress as percent of the labor force: 14.8 percent in Oct, which is equal to 14.9 percent in Sep and equal to 14.9 percent in Aug.

Table I-2, US, People in Job Stress, Millions and % SA

2012	Oct 2012	Sep 2012	Aug 2012
Labor Force Millions	155.641	155.063	154.645
Unemployed Millions	12.258	12.088	12.544
Unemployment Rate (unemployed as % labor force)	7.9	7.8	8.1
Unemployed ≥27 weeks Millions	5.002	4.844	5.033
Unemployed ≥27 weeks %	40.8	40.1	40.1
Part Time for Economic Reasons Millions ∆ Aug 2012/Dec 2011: -7 thousand ∆ Aug 2012/Sep 2011: -0.759 million	8.344	8.613	8.031
Marginally Attached to Labor Force Millions ∆Aug 2012/Sep 2011: +50 thousand   ∆Aug 2012/Dec 2011:    21 thousand	2.433	2.517	2.561
Job Stress Millions ∆Mar 12/Dec 11:          -948 thousand ∆Feb 12/Sep 11:           -2.145 million	23.035	23.218	23.136
In Job Stress as % Labor Force	14.8	14.9	14.9

Job Stress = Unemployed + Part Time Economic Reasons + Marginally Attached Labor Force

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

Table I-3 repeats the data in Table I-2 but including Jul and additional data. What really matters is the number of people with jobs or the total employed. The final row of Table I-3 provides people employed as percent of the population or employment to population ratio. The number has remained relatively constant around 58.6 percent, decreasing to 58.3 percent in Aug 2012 but increasing to 58.7 percent in Sep 2012 and 58.8 percent in Oct 2012.

Table I-3, US, Unemployment and Underemployment, SA, Millions and Percent

	Oct 2012	Sep 2012	Aug 2012	Jul 2012
Labor Force	155.641	155.063	154.645	155.013
Unemployed	12.258	12.088	12.544	12.794
UNE Rate %	7.9	7.8	8.1	8.3
Part Time Economic Reasons	8.344	8.613	8.031	8.246
Marginally Attached to Labor Force	2.433	2.517	2.561	2.529
In Job Stress	23.035	23.218	23.136	23.569
In Job Stress % Labor Force	14.8	14.9	14.9	15.2
Employed	143.384	142.974	142.101	142.220
Employment % Population	58.8	58.7	58.3	58.4

Source: US Bureau of Labor Statistics

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

The second approach is considered in the balance of this subsection. Charts I-1 to I-12 explain the reasons for considering another approach to calculating job stress in the US. Chart I-1 of the Bureau of Labor Statistics provides the level of employment in the US from 2001 to 2012. There was a big drop of the number of people employed from 147.315 million at the peak in Jul 2007 (NSA) to 136.809 million at the trough in Jan 2010 (NSA) with 10.506 million fewer people employed. Recovery has been anemic compared with the shallow recession of 2001 that was followed by nearly vertical growth in jobs. The number employed in Oct 2012 was 144.039 million (NSA) or 3.276 million fewer people with jobs relative to the peak of 147.315 million in Jul 2007 while the civilian noninstitutional population increased from 231.958 million in Jul 2007 to 243.983 million in Oct 2012 or by 11.025 million.

Chart I-1, US, Employed, Thousands, SA, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-2 of the Bureau of Labor Statistics provides 12-month percentage changes of the number of people employed in the US from 2001 to 2012. There was recovery in 2010 and 2011 but not sufficient to recover lost jobs. There are many people in the US who had jobs before the global recession who are not working now.

Chart I-2, US, Employed, 12-Month Percentage Change NSA, 2001-2012

Source: Bureau of Labor Statistics

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

The foundation of the second approach derives from Chart I-3 of the Bureau of Labor Statistics providing the level of the civilian labor force in the US. The civilian labor force consists of people who are available and willing to work and who have searched for employment recently. The labor force of the US grew from 142.828 million in Jan 2001 to 156.255 million in Jul 2009 but has declined to 153.905 million in Apr 2012, 154.998 million in May 2012, 156.385 million in Jun 2012, 156.526 million in Jul, 155.255 million in Aug 2012, 155.075 million Sep 2012 and 155.779 million in Oct 2012, all numbers not seasonally adjusted. Chart 1-3 shows the flattening of the curve of expansion of the labor force and its decline in 2010 and 2011. The ratio of the labor force of 154.871 million in Jul 2007 to the noninstitutional population of 231.958 million in Jul 2007 was 66.8 percent while the ratio of the labor force of 155.779 million in Oct 2012 to the noninstitutional population of 243.983 million in Oct 2012 was 63.8 percent. The labor force of the US in Oct 2012 corresponding to 66.8 percent of participation in the population would be 162.981 million (0.668 x 243.983). The difference between the measured labor force in Oct 2012 of 155.779 million and the labor force with participation rate of 66.8 percent as in Jul 2007 of 162.981 million is 7.702 million. The level of the labor force in the US has stagnated and is 7.7702 million lower than what it would have been had the same participation rate been maintained. There are millions of people who have abandoned their search for employment because they believe there are no jobs available for them. The key issue is whether the decline in participation of the population in the labor force is the result of people giving up on finding another job.

Chart I-3, US, Civilian Labor Force, Thousands, SA, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-4 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of the labor force in the US. The rate of growth fell almost instantaneously with the global recession and became negative from 2009 to 2011. The labor force of the US collapsed and did not recover.

Chart I-4, US, Civilian Labor Force, Thousands, NSA, 12-month Percentage Change, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-5 of the Bureau of Labor Statistics provides the labor force participation rate in the US or labor force as percent of the population. The labor force participation rate of the US fell from 66.8 percent in Jan 2001 to 63.6 percent NSA in Sep 2012, all numbers not seasonally adjusted. The annual labor force participation rate for 1979 was 63.7 percent and also 63.7 percent in Nov 1980 during sharp economic contraction. This comparison is further elaborated below. Chart I-5 shows an evident downward trend beginning with the global recession that has continued throughout the recovery beginning in IIIQ2009. The critical issue is whether people left the workforce of the US because they believe there is no longer a job for them.

Chart I-5, Civilian Labor Force Participation Rate, Percent of Population in Labor Force SA, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-6 of the Bureau of Labor Statistics provides the level of unemployed in the US. The number unemployed rose from the trough of 6.272 million in Oct 2006 to the peak of 16.147 million in Jan 2010, declining to 13.400 million in Jul 2012, 12.696 million in Aug 2012, 11.742 million in Sep 2012 and 11.741 million in Oct 2012, all numbers not seasonally adjusted.

Chart I-6, US, Unemployed, Thousands, SA, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-7 of the Bureau of Labor Statistics provides the rate of unemployment in the US or unemployed as percent of the labor force. The rate of unemployment of the US rose from 4.7 percent in Jan 2001 to 6.5 percent in Jun 2003, declining to 4.1 percent in Oct 2006. The rate of unemployment jumped to 10.6 percent in Jan 2010 and declined to 8.2 percent in Aug 2012, 7.6 percent in Sep 2012 and 7.5 percent in Oct 2012, all numbers not seasonally adjusted.

Chart I-7, US, Unemployment Rate, SA, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-8 of the Bureau of Labor Statistics provides 12-month percentage changes of the level of unemployed. There was a jump of 81.8 percent in Apr 2009 with subsequent decline and negative rates since 2010. On an annual basis, the level of unemployed rose 59.8 percent in 2009 and 26.1 percent in 2008 with increase of 3.9 percent in 2010 and decline of 7.3 percent in 2011.

Chart I-8, US, Unemployed, 12-month Percentage Change, NSA, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-9 of the Bureau of Labor Statistics provides the number of people in part-time occupations because of economic reasons, that is, because they cannot find full-time employment. The number underemployed in part-time occupations not seasonally adjusted rose from 3.732 million in Jan 2001 to 5.270 million in Jan 2004, falling to 3.787 million in Apr 2006. The number underemployed seasonally adjusted jumped to 9.130 million in Nov 2009, falling to 8.098 million in Dec 2011 but increasing to 8.230 million in Jan 2012 and 8.119 million in Feb 2012 but then falling to 7.853 million in Apr 2012 and increasing to 8.246 million in Jul 2012, 8.031 million in Aug 2012, 8.613 million in Sep 2012 and 8.344 million in Oct 2012. Without seasonal adjustment the number employed part-time for economic reasons reached 9.354 million in Dec 2009, declining to 8.918 million in Jan 2012 and 7.870 million in Oct 2012. The longer the period in part-time jobs the worst are the chances of finding another full-time job.

Chart I-9, US, Part-Time for Economic Reasons, Thousands, SA, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-10 of the Bureau of Labor Statistics repeats the behavior of unemployment. The 12-month rate of the level of people at work part-time for economic reasons jumped 84.7 percent in Mar 2009 and declined subsequently. The declines have been insufficient to reduce significantly the number of people who cannot shift from part-time to full-time employment. On an annual basis, the number of part-time for economic reasons increased 33.5 percent in 2008 and 51.7 percent in 2009, declining 0.4 percent in 2010 and 3.5 percent in 2011.

Chart I-10, US, Part-Time for Economic Reasons NSA 12-Month Percentage Change, 2001-2011

Source: Bureau of Labor Statistics

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

Chart I-11 of the Bureau of Labor Statistics provides the same pattern of the number marginally attached to the labor force jumping to significantly higher levels during the global recession and remaining at historically high levels. The number marginally attached to the labor force not seasonally adjusted increased from 1.295 million in Jan 2001 to 1.691 million in Feb 2004. The number of marginally attached to the labor force fell to 1.299 million in Sep 2006 and increased to 2.609 million in Dec 2009 and 2.800 million in Jan 2011. The number marginally attached to the labor force was 2.540 million in Dec 2011, increasing to 2.809 million in Jan 2012, falling to 2.608 million in Feb 2012, 2.352 million in Mar 2012, 2.363 million in Apr 2012, 2.483 million in May 2012, 2.529 million in Jun 2012, 2.529 million in Jul 2012, 2.561 million in Aug 2012, 2.517 million in Sep 2012 and 2.433 million in Oct 2012.

Chart I-11, US, Marginally-Attached to the Labor Force, Thousands, NSA, 2001-2012

Source: Bureau of Labor Statistics

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

Chart I-12 provides 12-month percentage changes of the marginally attached to the labor force from 2001 to 2012. There was a jump of 56.1 percent in May 2009 during the global recession followed by declines in percentage changes but insufficient negative changes. On an annual basis, the number of marginally attached to the labor force increased in four consecutive years: 15.7 percent in 2008, 37.9 percent in 2009, 11.7 percent in 2010 and 3.5 percent in 2011. The number marginally attached to the labor force fell 4.8 percent in the 12 months ending in Oct 2012.

Chart I-12, US, Marginally-Attached to the Labor Force 12-Month Percentage Change, NSA, 2001-2012

Source: Bureau of Labor Statistics

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

Table I-4 consists of data and additional calculations using the BLS household survey, illustrating the possibility that the actual rate of unemployment could be 10.8 percent and the number of people in job stress could be around 28.1 million, which is 17.4 percent of the labor force. The first column provides for 2006 the yearly average population (POP), labor force (LF), participation rate or labor force as percent of population (PART %), employment (EMP), employment population ratio (EMP/POP %), unemployment (UEM), the unemployment rate as percent of labor force (UEM/LF Rate %) and the number of people not in the labor force (NLF). All data are unadjusted or not-seasonally-adjusted (NSA). The numbers in column 2006 are averages in millions while the monthly numbers for Oct 2011, Sep 2012 and Oct 2012 are in thousands, not seasonally adjusted. The average yearly participation rate of the population in the labor force was in the range of 66.0 percent minimum to 67.1 percent maximum between 2000 and 2006 with the average of 66.4 percent (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). Table I-4b provides the yearly labor force participation rate from 1979 to 2012. The objective of Table I-4 is to assess how many people could have left the labor force because they do not think they can find another job. Row “LF PART 66.2 %” applies the participation rate of 2006, almost equal to the rates for 2000 to 2006, to the noninstitutional civilian population in Sep and Oct 2012 and Oct 2011 to obtain what would be the labor force of the US if the participation rate had not changed. In fact, the participation rate fell to 64.1 percent by Oct 2011 and was 63.6 percent in Sep 2012 and 63.8 percent in Oct 2012, suggesting that many people simply gave up on finding another job. Row “∆ NLF UEM” calculates the number of people not counted in the labor force because they could have given up on finding another job by subtracting from the labor force with participation rate of 66.2 percent (row “LF PART 66.2%”) the labor force estimated in the household survey (row “LF”). Total unemployed (row “Total UEM”) is obtained by adding unemployed in row “∆NLF UEM” to the unemployed of the household survey in row “UEM.” The row “Total UEM%” is the effective total unemployed “Total UEM” as percent of the effective labor force in row “LF PART 66.2%.” The results are that: (1) there are an estimated 5.737 million unemployed in Oct 2012 who are not counted because they left the labor force on their belief they could not find another job (∆NLF UEM); (2) the total number of unemployed is effectively 17.478 million (Total UEM) and not 11.741 million (UEM) of whom many have been unemployed long term; (3) the rate of unemployment is 10.8 percent (Total UEM%) and not 7.5 percent, not seasonally adjusted, or 7.9 percent seasonally adjusted; and (4) the number of people in job stress is close to 28.1 million by adding the 5.737 million leaving the labor force because they believe they could not find another job. The row “In Job Stress” in Table I-4 provides the number of people in job stress not seasonally adjusted at 28.1 million in Oct 2012, adding the total number of unemployed (“Total UEM”), plus those involuntarily in part-time jobs because they cannot find anything else (“Part Time Economic Reasons”) and the marginally attached to the labor force (“Marginally attached to LF”). The final row of Table I-4 shows that the number of people in job stress is equivalent to 17.4 percent of the labor force in Sep 2012. The employment population ratio “EMP/POP %” dropped from 62.9 percent on average in 2006 to 58.7 percent in Oct 2011, 58.8 percent in Sep 2012 and 59.0 percent in Oct 2012; the number employed (EMP) dropped from 144 million in 2006 to 140.039 million in Oct 2012 while population increased from 229.420 million in Sep 2006 to 243.983 million in Oct 2012 or by 14.563 million. What really matters for labor input in production and wellbeing is the number of people with jobs or the employment/population ratio, which has declined and does not show signs of increasing. There are several million fewer people working in 2012 than in 2006 and the number employed is not increasing while population increased 14.563 million. The number of hiring relative to the number unemployed measures the chances of becoming employed. The number of hiring in the US economy has declined by 17 million and does not show signs of increasing in an unusual recovery without hiring (http://cmpassocregulationblog.blogspot.com/2012/10/recovery-without-hiring-imf-view-united.html).

Table I-4, US, Population, Labor Force and Unemployment, NSA

	2006	Oct 2011	Sep 2012	Oct 2012
POP	229	240,269	243,772	243,983
LF	151	154,088	155,075	155,779
PART%	66.2	64.1	63.6	63.8
EMP	144	140,987	143,333	144,039
EMP/POP%	62.9	58.7	58.8	59.0
UEM	7	13,102	11,742	11,741
UEM/LF Rate%	4.6	8.5	7.6	7.5
NLF	77	86,181	88,697	88,204
LF PART 66.2%		159,058	161,377	161,516
∆NLF UEM		4,970	6,302	5,737
Total UEM		18,072	18,044	17,478
Total UEM%		11.4	11.2	10.8
Part Time Economic Reasons		8,258	8,110	7,870
Marginally Attached to LF		2,555	2,517	2,433
In Job Stress		29,477	28,671	28,085
People in Job Stress as % Labor Force		18.5	17.8	17.4

Pop: population; LF: labor force; PART: participation; EMP: employed; UEM: unemployed; NLF: not in labor force; ∆NLF UEM: additional unemployed; Total UEM is UEM + ∆NLF UEM; Total UEM% is Total UEM as percent of LF PART 66.2%; In Job Stress = Total UEM + Part Time Economic Reasons + Marginally Attached to LF

Note: the first column for 2006 is in average millions; the remaining columns are in thousands; NSA: not seasonally adjusted

The labor force participation rate of 66.2% in 2006 is applied to current population to obtain LF PART 66.2%; ∆NLF UEM is obtained by subtracting the labor force with participation of 66.2 percent from the household survey labor force LF; Total UEM is household data unemployment plus ∆NLF UEM; and total UEM% is total UEM divided by LF PART 66.2%

Sources: US Bureau of Labor Statistics http://www.bls.gov/data/

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 s_i of a demographic group in an industry i and unemployment rate y_i of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):

Y = ∑_is_iy_i (1)

This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):

∆Y = ∑_i∆s_iy*_i + ∑_i∆y_is*_i (2)

The first term in (2) captures changes in the demographic and industrial composition of the economy ∆s_i 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 ∆y_i, 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 provides 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.”

Table I-4b and Chart 12-b provide the US labor force participation rate or percentage of the labor force in population. It is not likely that simple demographic trends caused the sharp decline during the global recession and failure to recover earlier levels. The civilian labor force participation rate dropped from the peak of 66.9 percent in Jul 2006 to 63.8 percent in Oct 2012 and even 63.4 percent in Jan and Apr 2012 and 63.6 percent in Sep 2012. The civilian labor force participation rate was 63.7 percent on an annual basis in 1979 and 63.7 percent in Nov 1980, reaching even 62.9 percent in both Apr and May 1979. The civilian labor force participation rate jumped with the recovery to 64.8 percent on an annual basis in 1985 and 65.9 percent in Jul 1985. Structural factors cannot explain these sudden changes vividly shown visually in the final segment of Chart 12b. Seniors would like to delay their retiring especially because of the adversities of financial repression on their savings. Labor force statistics are capturing the disillusion of potential workers of their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors.

Table I-4b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2012

Year	Jul	Aug	Sep	Oct	Nov	Dec	Annual
1979	64.9	64.5	63.8	64.0	63.8	63.8	63.7
1980	65.1	64.5	63.6	63.9	63.7	63.4	63.8
1981	65.0	64.6	63.5	64.0	63.8	63.4	63.9
1982	65.3	64.9	64.0	64.1	64.1	63.8	64.0
1983	65.4	65.1	64.3	64.1	64.1	63.8	64.0
1984	65.9	65.2	64.4	64.6	64.4	64.3	64.4
1985	65.9	65.4	64.9	65.1	64.9	64.6	64.8
1986	66.6	66.1	65.3	65.5	65.4	65.0	65.3
1987	66.8	66.5	65.5	65.9	65.7	65.5	65.6
1988	67.1	66.8	65.9	66.1	66.2	65.9	65.9
1989	67.7	67.2	66.3	66.6	66.7	66.3	66.5
1990	67.7	67.1	66.4	66.5	66.3	66.1	66.5
1991	67.3	66.6	66.1	66.1	66.0	65.8	66.2
1992	67.9	67.2	66.3	66.2	66.2	66.1	66.4
1993	67.5	67.0	66.1	66.4	66.3	66.2	66.3
1994	67.5	67.2	66.5	66.8	66.7	66.5	66.6
1995	67.7	67.1	66.5	66.7	66.5	66.2	66.6
1996	67.9	67.2	66.8	67.1	67.0	66.7	66.8
1997	68.1	67.6	67.0	67.1	67.1	67.0	67.1
1998	67.9	67.3	67.0	67.1	67.1	67.0	67.1
1999	67.9	67.3	66.8	67.0	67.0	67.0	67.1
2000	67.6	67.2	66.7	66.9	66.9	67.0	67.1
2001	67.4	66.8	66.6	66.7	66.6	66.6	66.8
2002	67.2	66.8	66.6	66.6	66.3	66.2	66.6
2003	66.8	66.3	65.9	66.1	66.1	65.8	66.2
2004	66.8	66.2	65.7	66.0	66.1	65.8	66.0
2005	66.8	66.5	66.1	66.2	66.1	65.9	66.0
2006	66.9	66.5	66.1	66.4	66.4	66.3	66.2
2007	66.8	66.1	66.0	66.0	66.1	65.9	66.0
2008	66.8	66.4	65.9	66.1	65.8	65.7	66.0
2009	66.2	65.6	65.0	64.9	64.9	64.4	65.4
2010	65.3	65.0	64.6	64.4	64.4	64.1	64.7
2011	64.6	64.3	64.2	64.1	63.9	63.8	64.1
2012	64.3	63.7	63.6	63.8

Sources: US Bureau of Labor Statistics http://www.bls.gov/data/

Chart 12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2012

Source: Bureau of Labor Statistics

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

IA3 Long-term and Cyclical Comparison of Employment. There is initial discussion here of long-term employment trends followed by cyclical comparison. Growth and employment creation have been mediocre in the expansion beginning in Jul IIIQ2009 from the contraction between Dec IVQ2007 and Jun IIQ2009 (http://www.nber.org/cycles.html). A series of charts from the database of the Bureau of Labor Statistics (BLS) provides significant insight. Chart I-13 provides the monthly employment level of the US from 1948 to 2012. The number of people employed has trebled. There are multiple contractions throughout the more than six decades but followed by resumption of the strong upward trend. The contraction after 2007 is deeper and followed by a flatter curve of job creation. Economic growth is much lower in the current expansion at 2.2 percent relative to average 6.2 percent in expansions following earlier contractions.

Chart I-13, US, Employment Level, Thousands, 1948-2012

Source: US Bureau of Labor Statistics

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

The steep and consistent curve of growth of the US labor force is shown in Chart I-14. The contraction beginning in Dec 2007 flattened the path of the US civilian labor force and is now followed by a flatter curve during the current expansion.

Chart I-14, US, Civilian Labor Force, 1948-2012, Thousands

Source: US Bureau of Labor Statistics

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

Chart I-15 for the period from 1948 to 2012. The labor force participation rate is influenced by numerous factors such as the age of the population. There is no comparable episode in the postwar economy to the sharp collapse of the labor force participation rate in Chart I-15 during the contraction and subsequent expansion after 2007. Aging can reduce the labor force participation rate as many people retire but many may have decided to work longer as their wealth and savings have been significantly reduced. There is an important effect of many people just exiting the labor force because they believe there is no job available for them.

Chart I-15, US, Civilian Labor Force Participation Rate, 1948-2012, %

Source: US Bureau of Labor Statistics

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

The number of unemployed in the US jumped from 5.8 million in May 1979 to 12.1 million in Dec 1982, by 6.3 million, or 108.6 percent. The number of unemployed jumped from 6.7 million in Mar 2007 to 15.6 million in Oct 2009, by 8.9 million, or 132.8 percent. These are the two episodes with steepest increase in the level of unemployment in Chart I-16.

Chart I-16, US, Unemployed, 1948-2012, Thousands

Source: US Bureau of Labor Statistics

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

Chart I-17 provides the rate of unemployment of the US from 1948 to 2012. The peak of the series is 10.8 percent in both Nov and Dec 1982. The second highest rates are 10.1 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009.

Chart I-17, US, Unemployment Rate, 1948-2012

Source: US Bureau of Labor Statistics

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

Chart I-18 provides the number unemployed for 27 weeks and over from 1948 to 2012. The number unemployed for 27 weeks and over jumped from 510,000 in Dec 1978 to 2.9 million in Jun 1983, by 2.4 million, or 480 percent. The number of unemployed 27 weeks or over jumped from 1.1 million in May 2007 to 6.7 million in Jun 2010, by 5.6 million, or 509 percent.

Chart I-18, US, Unemployed for 27 Weeks or More, 1948-2012, Thousands

Source: US Bureau of Labor Statistics

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

The employment-population ratio in Chart I-19 is an important indicator of wellbeing in labor markets, measuring the number of people with jobs. The US employment-population ratio fell from 63.4 in Dec 2006 to 58.6 in Jul 2011 and stands at 59.0 NSA in Oct 2012. There is no comparable decline during an expansion in Chart I-19.

Chart I-19, US, Employment-Population Ratio, 1948-2012

Source: US Bureau of Labor Statistics

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

The number of people at work part-time for economic reasons because they cannot find full-time employment is provided in Chart I-20. The number of people at work part-time for economic reasons jumped from 3.7 million in Sep 2006 to a high of 9.4 million in Dec 2009 and 9.2 million in Jan 2011, or by 5.2 million, or 148.6 percent, all numbers not seasonally adjusted. Earlier increases in the 1980s and after the tough recession of 1991 were followed by rapid decrease that is still absent in the current expansion. The drop by 1,172,000 of seasonally-adjusted data from Sep to Dec 2011 while actual data without seasonal adjustment show decrease by 113,000 is not very credible.

Chart I-20, US, Part-Time for Economic Reasons, 1955-2012, Thousands

Source: US Bureau of Labor Statistics

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

Table I-5 provides the change in real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.7 percent cumulatively and fell 45.6 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7). Data are available for the 1930s only on a yearly basis. US GDP fell 4.8 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1981 to IVQ1982 and 4.7 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first two years of the expansions in the 1980s and the current expansion. GDP grew at 4.5 percent in 1983 and 7.2 percent in 1984 while GDP grew at 2.4 percent in 2010, 1.8 percent in 2011 and at 2.0 percent in IQ2012 relative to IQ2011 and 1.5 percent in IIQ2012 relative to IQ2012. Growth in the first two quarters of 2012 accumulates to 0.87 percent, which is equivalent to 1.75 percent per year, decelerating from 2.4 percent annual growth in 2011. GDP grew at 4.1 percent in 1985 and 3.5 percent in 1986 while the forecasts of participants of the Federal Open Market Committee (FOMC) are in the range of 1.7 to 2.0 percent in 2012 and 2.5 to 3.0 percent in 2013 (http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20120913.pdf).

Table I-5, GDP in the 1930s, 1980s and 2000s, ∆%

Year	GDP ∆%	Year	GDP ∆%	Year	GDP ∆%
1930	-8.6	1980	-0.3	2000	4.1
1931	-6.5	1981	2.5	2001	1.1
1932	-13.1	1982	-1.9	2002	1.8
1933	-1.3	1983	4.5	2003	2.5
1934	10.9	1984	7.2	2004	3.5
1935	8.9	1985	4.1	2005	3.1
1936	13.1	1986	3.5	2006	2.7
1937	5.1	1987	3.2	2007	1.9
1938	-3.4	1988	4.1	2008	-0.3
1930	8.1	1989	3.6	2009	-3.1
1940	8.8	1990	1.9	2010	2.4
1941	17.1	1991	-0.2	2011	1.8

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

Characteristics of the four cyclical contractions are provided in Table I-6 with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.8 percent, which is almost equal to the decline of 4.7 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.7 percent cumulatively and fell 45.6 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

Table I-6, US, Number of Quarters, Cumulative Percentage Contraction and Average Percentage Annual Equivalent Rate in Cyclical Contractions   

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	4	-2.5	-0.63
IIIQ1957 to IIQ1958	3	-3.1	-9.0
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.7	-0.67
IVQ2007 to IIQ2009	6	-4.7	-0.80

Sources: Business Cycle Reference Dates: http://www.nber.org/cycles.html US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

Table I-7 shows the extraordinary contrast between the mediocre average annual equivalent growth rate of 2.2 percent of the US economy in the twelve quarters of the current cyclical expansion from IIIQ2009 to IIQ2012 and the average of 6.2 percent in the four earlier cyclical expansions. BEA data show the US economy in standstill with annual growth of 2.4 percent in 2010 percent decelerating to 1.8 percent annual growth in 2011 (http://www.bea.gov/iTable/index_nipa.cfm) and cumulative 0.82 percent in the first three quarters of 2012 {[(1.02)^1/4(1.013)^1/4(1.02)^1/4 – 1]100 = 1.3%}, which is equivalent to 1.77 percent per year {([(1.02)^1/4(1.013)^1/4(1.02)^1/4 ]^4/3 – 1)100 = 1.77%}. The expansion of IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent.

Table I-7, US, Number of Quarters, Cumulative Growth and Average Annual Equivalent Growth Rate in Cyclical Expansions

	Number of Quarters	Cumulative Growth ∆%	Average Annual Equivalent Growth Rate
IIIQ 1954 to IQ1957	11	12.6	4.4
IIQ1958 to IIQ1959	5	10.2	8.1
IIQ1975 to IVQ1976	8	9.5	4.6
IQ1983 to IV1985	13	19.6	5.7
Average Four Above Expansions			6.2
IIIQ2009 to IIIQ2012	13	7.2	2.2

Sources: Business Cycle Reference Dates: http://www.nber.org/cycles.html US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm

A group of charts from the database of the Bureau of Labor Statistics facilitate the comparison of employment in the 1980s and 2000s. The long-term charts and tables from I-5 to I-7 in the discussion above confirm the view that the comparison of the current expansion should be with that in the 1980s because of similar dimensions. Chart I-21 provides the level of employment in the US between 1979 and 1989. Employment surged after the contraction and grew rapidly during the decade.

Chart I-21, US, Employed, Thousands, 1979-1989

Source: US Bureau of Labor Statistics

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

The number employed in the US fell from 146.743 million in Oct 2007 to 144.039 million in Oct 2012, by 2.704 million, or 1.8 percent, while the noninstitutional population increased from 232.715 million in Oct 2007 to 243.983 million in Oct 2012, by 11.268 million or increase of 4.8 percent, using not seasonally adjusted data. Chart I-22 shows tepid recovery early in 2010 followed by near stagnation and marginal expansion.

Chart I-22, US, Employed, Thousands, 2001-2012

Source: US Bureau of Labor Statistics

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

There was a steady upward trend in growth of the civilian labor force between 1979 and 1989 as shown in Chart I-23. There were fluctuations but strong long-term dynamism over an entire decade.

Chart I-23, US, Civilian Labor Force, Thousands, 1979-1989

Source: US Bureau of Labor Statistics

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

The civilian labor force in Chart I-24 grew steadily on an upward trend in the 2000s until it contracted together with the economy after 2007. There has not been recovery during the expansion but rather decline and marginal turn of the year into 2012 expansion.

Chart I-24, US, Civilian Labor Force, Thousands, 2001-2012

Source: US Bureau of Labor Statistics

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

The rate of participation of the labor force in population stagnated during the stagflation and conquest of inflation in the late 1970s and early 1980s, as shown in Chart I-25. Recovery was vigorous during the expansion and lasted through the remainder of the decade.

Chart I-25, US, Civilian Labor Force Participation Rate, 1979-1989, %

Source: US Bureau of Labor Statistics

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

The rate of participation in the labor force declined after the recession of 2001 and stagnated until 2007, as shown in Chart I-26. The rate of participation in the labor force continued to decline both during the contraction after 2007 and the expansion after 2009 with marginal expansion at the turn of the year into 2012 followed by trend of decline.

Chart I-26, US, Civilian Labor Force Participation Rate, 2001-2012, %

Source: US Bureau of Labor Statistics

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

Chart I-27 provides the number unemployed during the 1980s. The number unemployed peaked at 12.051 million in Dec 1982 seasonally adjusted and 12.517 in Jan 1983 million not seasonally adjusted, declining to 8.358 million in Dec 1984 seasonally adjusted and 7.978 million not seasonally adjusted during the first two years of expansion from the contraction. The number unemployed then fell to 6.667 million in Dec 1989 seasonally adjusted and 6.300 million not seasonally adjusted.

Chart I-27, US, Unemployed Thousands 1979-1989

Source: US Bureau of Labor Statistics

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

Chart I-28 provides the number unemployed from 2001 to 2012. Using seasonally adjusted data, the number unemployed rose from 6.727 million in Oct 2006 to 15.421 million in Oct 2009, declining to 13.097 million in Dec 2011 and to 12.258 million in Oct 2012. Using data not seasonally adjusted, the number unemployed rose from 6.272 million in Oct 2006 to 16.147 million in Jan 2010, declining to 11.741 million in Oct 2012.

Chart I-28, US, Unemployed Thousands 2001-2012

Source: US Bureau of Labor Statistics

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

The rate of unemployment peaked at 10.8 percent in both Nov and Dec 1982 seasonally adjusted, as shown in Chart I-29. The rate of unemployment dropped sharply during the expansion after 1984 and continued to decline during the rest of the decade to 5.4 percent in Dec 1989. Using not seasonally adjusted data, the rate of unemployment peaked at 11.4 percent in Jan 1983, declining to 7.0 percent in Dec 1984 and 5.1 percent in Dec 1989.

Chart I-29, US, Unemployment Rate, 1979-1989, %

Source: US Bureau of Labor Statistics

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

The rate of unemployment in the US seasonally adjusted jumped from 4.4 percent in May 2007 to 10.0 percent in Oct 2009 and 9.9 percent in both Nov and Dec 2009, as shown in Chart I-30. The rate of unemployment fluctuated at around 9.0 percent in 2011 with the somewhat less credible 8.7 percent in Nov 2011 because of the decrease of the labor force by 120,000 from 154.057 million Oct to 153.937 million in Nov and then declined to 8.5 percent in Dec 2011 with decline of 50,000 of the labor force from 153.937 million in Nov to 153.887 million Dec 2011. The rate of unemployment then fell to 8.3 percent in Jan and Feb 2012 and fell to 8.2 percent in Mar 2012 and 8.1 percent in Apr 2012 with another decline of the labor force. The rate fell to 7.8 percent in Sep 2012 and increased to 7.9 percent in Oct 2012. Using not seasonally adjusted data, the rate of unemployment rose from 4.3 percent in Apr and May 2007 to 10.6 percent in Jan 2010, declining to 7.5 percent in Oct 2012.

Chart I-30, US, Unemployment Rate, 2001-2012, %

Source: US Bureau of Labor Statistics

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

The employment population ratio seasonally adjusted fell from around 60.1 in Dec 1979 to 57.1 in both Feb and Mar 1983, as shown in Chart I-31. The employment population ratio seasonally adjusted rose back to 59.9 in Dec 1984 and reached 63.0 later in the decade in Dec 1989. Using not seasonally adjusted data, the employment population ratio dropped from 60.4 percent in Oct 1979 to 56.1 percent in Jan 1983, increasing to 59.8 in Dec 1984 and to 62.9 percent in Dec 1989.

Chart I-31, US, Employment Population Ratio, 1979-1989, %

Source: US Bureau of Labor Statistics

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

The US employment-population ratio seasonally adjusted has fallen from 63.4 in Dec 2006 to 58.5 in Dec 2011 and Jan 2012, increasing to 58.6 percent in Feb 2012 and falling back to 58.5 percent in Mar 2012 and 58.4 percent in Apr 2012 but rising to 58.6 percent in May and Jun 2012, falling back to 58.4 percent in Jul 2012 and 58.3 percent in Aug 2012 with latest increase to 58.7 percent in Sep 2012 and 58.8 percent in Oct 2012, as shown in Chart I-32. The employment population-ratio has stagnated during the expansion. Using not seasonally adjusted data, the employment population ratio fell from 63.6 percent in Jul 2006 to 57.6 percent in Jan 2011 and 59.0 percent in Oct 2012.

Chart I-32, US, Employment Population Ratio, 2001-2012, %

Source: US Bureau of Labor Statistics

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

The number unemployed for 27 weeks or over peaked at 2.885 million in Jun 1983 as shown in Chart I-33. The number unemployed for 27 weeks or over fell sharply during the expansion to 1.393 million in Dec 1984 and continued to decline throughout the 1980s to 0.635 million in Dec 1989.

Chart I-33, US, Number Unemployed for 27 Weeks or More 1979-1989, Thousands

Source: US Bureau of Labor Statistics

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

The number unemployed for 27 weeks or over, seasonally adjusted, increased sharply during the contraction as shown in Chart I-34 from 1.131 million in Nov 2006 to 6.730 in Apr 2010. The number of unemployed for 27 weeks remained at around 6 million during the expansion compared with somewhat above 1 million before the contraction, falling to 5.002 million in Oct 2012 seasonally adjusted and 4.915 million not seasonally adjusted.

Chart I-34, US, Number Unemployed for 27 Weeks or More, 2001-2012, Thousands

Source: US Bureau of Labor Statistics

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

The number of persons working part-time for economic reasons because they cannot find full-time work peaked during the contraction at 6.857 million in Oct 1982, as shown in Chart I-35. The number of persons at work part-time for economic reasons fell sharply during the expansion to 5.797 million in Dec 1984 and continued to fall throughout the decade to 4.817 million in Dec 1989.

Chart I-35, US, Part-Time for Economic Reasons, 1979-1989, Thousands

Source: US Bureau of Labor Statistics

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

The number of people working part-time because they cannot find full-time employment, not seasonally adjusted, increased sharply during the contraction from 3.787 million in Apr 2006, not seasonally adjusted, to 9.354 million in Dec 2009, as shown in Chart I-36. The number of people working part-time because of failure to find an alternative occupation stagnated at a very high level during the expansion, declining to 7.870 million not seasonally adjusted in Oct 2012.

Chart I-36, US, Part-Time for Economic Reasons, 2001-2012, Thousands

Source: US Bureau of Labor Statistics

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

The number marginally attached to the labor force in Chart I-37 jumped from 1.252 million in Dec 2006 to 2.730 million in Feb 2011, remaining at a high level of 2.540 million in Dec 2011, 2.809 million in Jan 2012, 2.608 million in Feb 2012, 2.352 million in Mar 2012, 2.363 million in Apr 2012 and increase to 2.423 million in May 2012, 2.483 million in Jun 2012, 2.529 million in Jul 2012, 2.561 million in Aug 2012, 2.517 million in Sep 2012 and 2.433 million in Nov 2012.

Chart I-37, US, Marginally Attached to the Labor Force, 2001-2012

Source: US Bureau of Labor Statistics

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

Total nonfarm payroll employment seasonally adjusted (SA) increased 171,000 in Oct 2012 and private payroll employment rose 184,000. The number of nonfarm jobs and private jobs created has been declining 2012 from 275,000 in Jan to 45,000 in Jun, 148,000 in Sep and 171,000 in Oct for total nonfarm jobs and from 277,000 in Jan to 63,000 in Jun, 128,000 in Sep and 184,000 in Oct for private jobs. Average new nonfarm jobs in the quarter Dec 2011 to Feb 2012 were 252,333 per month, declining to average 129,375 per month in the eight months from Mar to Oct 2012. Average new private jobs in the quarter Dec 2011 to Feb 2012 were 255,000 per month, declining to average 127,500 per month in the eight months from Mar 2012 to Oct 2012. The US labor force stood at 154.088 million in Oct 2011 and at 155.779 million in Oct 2012, not seasonally adjusted, for increase of 1.691 million, or 140,917 per month. The average increase of 129,375 new nonfarm jobs per month in the US from Mar to Oct 2012 is insufficient even to absorb 140,917 new entrants per month into the labor force. There is not sufficient job creation to merely absorb new entrants in the labor force, worsening the stock of unemployed or underemployed in involuntary part-time jobs. Table I-8 provides the monthly change in jobs seasonally adjusted in the prior strong contraction of 1981-1982 and the recovery in 1983 into 1984 and in the contraction of 2008-2009 and in the recovery in 2009 to 2012. All revisions have been incorporated in Table I-8. The data in the recovery periods are in relief to facilitate comparison. There is significant bias in the comparison. The average yearly civilian noninstitutional population was 174.2 million in 1983 and the civilian labor force 111.6 million, growing by 2009 to an average yearly civilian noninstitutional population of 235.8 million and civilian labor force of 154.1 million, that is, increasing by 35.4 percent and 38.1 percent, respectively (http://www.bls.gov/data/). Total nonfarm payroll jobs in 1983 were 90.280 million, jumping to 94.530 million in 1984 while total nonfarm jobs in 2010 were 129.874 million declining from 130.807 million in 2009 (http://www.bls.gov/data/). What is striking about the data in Table I-8 is that the numbers of monthly increases in jobs in 1983 and 1984 are several times higher than in 2010 to 2011 even with population higher by 35.4 percent and labor force higher by 38.1 percent in 2009 relative to 1983 nearly three decades ago and total number of jobs in payrolls rose by 39.5 million in 2010 relative to 1983 or by 43.8 percent. Growth at 2.2 percent has been mediocre in the twelve quarters of expansion beginning in IIIQ2009 in comparison with 6.2 percent in earlier expansions (http://cmpassocregulationblog.blogspot.com/2012/10/mediocre-and-decelerating-united-states.html) and also in terms of what is required to reduce the job stress of at around 24 million persons but likely close to 30 million. Some of the job growth and contraction in 2010 in Table I-8 is caused by the hiring and subsequent layoff of temporary workers for the 2010 census.

Table I-8, US, Monthly Change in Jobs, Number SA

Month	1981	1982	1983	2008	2009	2010	Private
Jan	95	-327	225	41	-818	-40	-40
Feb	67	-6	-78	-84	-724	-35	-27
Mar	104	-129	173	-95	-799	189	141
Apr	74	-281	276	-208	-692	239	193
May	10	-45	277	-190	-361	516	84
Jun	196	-243	378	-198	-482	-167	92
Jul	112	-343	418	-210	-339	-58	92
Aug	-36	-158	-308	-274	-231	-51	128
Sep	-87	-181	1114	-432	-199	-27	115
Oct	-100	-277	271	-489	-202	220	196
Nov	-209	-124	352	-803	-42	121	134
Dec	-278	-14	356	-661	-171	120	140
			1984			2011	Private
Jan			447			110	119
Feb			479			220	257
Mar			275			246	261
Apr			363			251	264
May			308			54	108
Jun			379			84	102
Jul			312			96	175
Aug			241			85	52
Sep			311			202	216
Oct			286			112	139
Nov			349			157	178
Dec			127			223	234
			1985			2012	Private
Jan			266			275	277
Feb			124			259	254
Mar			346			143	147
Apr			195			68	85
May			274			87	116
Jun			145			45	63
Jul			189			181	163
Aug			193			192	134
Sep			204			148	128
Oct			187			171	184
Nov			209
Dec			168

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

Charts numbered from I-38 to I-41 from the database of the Bureau of Labor Statistics provide a comparison of payroll survey data for the contractions and expansions in the 1980s and after 2007. Chart I-38 provides total nonfarm payroll jobs from 2001 to 2012. The sharp decline in total nonfarm jobs during the contraction after 2007 has been followed by initial stagnation and then inadequate growth in the first eight months of 2012.

Chart I-38, US, Total Nonfarm Payroll Jobs SA 2001-2012

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

Total nonfarm payroll jobs grew rapidly during the expansion in 1983 and 1984 as shown in Chart I-39. Nonfarm payroll jobs continued to grow at high rates during the remainder of the 1980s.

Chart I-39, US, Total Nonfarm Payroll Jobs SA 1979-1989

Source: US Bureau of Labor Statistics

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

Most job creation in the US is by the private sector. Chart I-40 shows the sharp destruction of private payroll jobs during the contraction after 2007. There has been growth after 2010 but insufficient to recover higher levels of employment prevailing before the contraction. At current rates, recovery of employment may spread over several years in contrast with past expansions of the business cycle in the US.

Chart I-40, US, Total Private Payroll Jobs SA 2001-2012

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

In contrast, growth of private payroll jobs in the US recovered vigorously during the expansion in 1983 through 1985, as shown in Chart I-41. Rapid growth of creation of private jobs continued throughout the 1980s.

Chart I-41, US, Total Private Payroll Jobs SA 1979-1989

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

IA4 Creation of Jobs. Types of jobs created, and not only the pace of job creation, may be important. Aspects of growth of payroll jobs from Sep 2011 to Sep 2012, not seasonally adjusted (NSA), are provided in Table I-9. Total nonfarm employment increased by 1,922,000 (row A, column Change), consisting of growth of total private employment by 1,920,000 (row B, column Change) and increase by 2,000 of government employment (row C, column Change). Monthly average growth of private payroll employment has been 160,000, which is mediocre relative to 24 to 30 million in job stress, while total nonfarm employment has grown on average by only 160,166 per month, which barely keeps with 140,917 new entrants per month in the labor force. These monthly rates of job creation are insufficient to meet the demands of new entrants in the labor force and thus perpetuate unemployment and underemployment. Manufacturing employment increased by 180,000, at the monthly rate of 15,000, while private service providing employment grew by 1,709,000, at the monthly rate of 142,417. An important feature in Table I-9 is that jobs in professional and business services increased by 513,000 with temporary help services increasing by 177,000. This episode of jobless recovery is characterized by part-time jobs and creation of jobs that are inferior to those that have been lost. Monetary and fiscal stimuli fail to increase consumption in a fractured job market. The segment leisure and hospitality added 335,000 jobs in 12 months. An important characteristic is that the losses of government jobs has stabilized in local government after heavy losses, 14,000 jobs gained in the past twelve months (row C3 Local), while there is a higher number of employees in local government, 14.3 million relative to 5.2 million in state jobs and 2.8 million in federal jobs.

Table I-9, US, Employees in Nonfarm Payrolls Not Seasonally Adjusted, in Thousands

	Oct 2011	Oct 2012	Change
A Total Nonfarm	132,870	134,792	1,922
B Total Private	110,479	112,399	1,920
B1 Goods Producing	18,414	18,625	211
B1a Manufacturing	11,839	12,019	180
B2 Private service providing	92,065	93,774	1,709
B2a Wholesale Trade	5,565	5,665	100
B2b Retail Trade	14,700	14,840	140
B2c Transportation & Warehousing	4,352	4,443	91
B2d Financial Activities	7,686	7,766	80
B2e Professional and Business Services	17,658	18,171	513
B2e1 Temporary help services	2,477	2,654	177
B2f Health Care & Social Assistance	16,792	17,134	342
B2g Leisure & Hospitality	13,357	13,692	335
C Government	22,391	22,393	2
C1 Federal	2,846	2,807	-39
C2 State	5,215	5,242	27
C3 Local	14,330	14,344	14

Note: A = B+C, B = B1 + B2, C=C1 + C2 + C3

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

Greater detail on the types of jobs created is provided in Table I-10 with data for Sep and Oct 2012. Strong seasonal effects are shown by the significant difference between seasonally-adjusted (SA) and not-seasonally-adjusted (NSA) data. The purpose of adjusting for seasonality is to isolate nonseasonal effects. The 171,000 SA total nonfarm jobs created in Oct relative to Sep actually correspond to job decrease of 89,000 jobs NSA, as shown in row A. The 184,000 total private payroll jobs SA created in Oct relative to Sep actually correspond to increase of 361,000 jobs NSA. Adjustment for seasonality isolates nonseasonal effects that suggest improvement from Oct 2011 to Oct 2012. The analysis of NSA job creation in the prior Table I-9 does show improvement over the 12 months ending in Oct 2012 that is not clouded by seasonal variations but significant reduction in number of jobs created. In fact, the 12-month rate of job creation without seasonal adjustment is stronger indication of marginal improvement in the US job market but that is insufficient to even make a dent in about 30 million people unemployed or underemployed.

Table I-10, US, Employees on Nonfarm Payrolls and Selected Industry Detail, Thousands, SA

	Sep      2012 SA	Oct       2012 SA	∆	Sep 2012 NSA	Oct 2012 NSA	∆
A Total Nonfarm	133,584	133,755	171	133,881	133,792	-89
B Total Private	111,560	111,744	184	112,038	112,399	361
B1 Goods Producing	18,309	18,330	21	18,653	18,625	-28
B1a Constr.	5,522	5,539	17	5,770	5,770	0
B Mfg	11,953	11,966	13	12,035	12,019	-16
B2 Private Service Providing	93,251	93,414	163	93,385	93,774	389
B2a Wholesale Trade	5,643	5,650	7	5,641	5,665	24
B2b Retail Trade	14,796	14,832	36	14,710	14,840	130
B2c Couriers     & Mess.	526	521	-5	521	516	-5
B2d Health-care & Social Assistance	17,070	17,102	32	17,050	17,134	84
B2De Profess. & Business Services	17,956	18,007	51	18,035	18,171	136
B2De1 Temp Help Services	2,527	2,540	13	2,597	2,654	57
B2f Leisure & Hospit.	13,706	13,734	28	13,906	13,692	-214

Notes: ∆: Absolute Change; Constr.: Construction; Mess.: Messengers; Temp: Temporary; Hospit.: Hospitality. SA aggregates do not add because of seasonality.

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

Manufacturing jobs increased 13,000 in Oct 2012 relative to Sep 2012, seasonally adjusted but fell 16,000 in Oct 2012 relative to Sep 2012, not seasonally adjusted, as shown in Table I-10, because of the weaker economy and international trade. In the six months ending in Aug, United States national industrial production accumulated decline of 0.4 percent at the annual equivalent rate of decline of 0.8 percent, which is substantially lower than 2.8 percent growth in 12 months. Capacity utilization for total industry in the United States fell 1.0 percentage point in Aug to 78.2 percent, which is 2.1 percentage points lower than the long-run average from 1972 to 2011. Manufacturing increased 0.2 percent in Sep seasonally adjusted, increasing 3.2 percent not seasonally adjusted in 12 months, and increased 0.1 percent in the six months ending in Sep or at the annual equivalent rate of 0.2 percent (http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html). Table I-11 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 86.5 percent in US national income in IQ2012 and 86.3 percent in IIQ2012. Most of US national income is in the form of services. In Oct 2012, there were 134.792 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 112.399 million NSA in Oct 2012 accounted for 83.4 percent of total nonfarm jobs of 134.792 million, of which 11.777 million, or 10.5 percent of total private jobs and 8.7 percent of total nonfarm jobs, were in manufacturing. Private service-producing jobs were 93.774 million NSA in Oct 2012, or 69.6 percent of total nonfarm jobs and 83.4 percent of total private-sector jobs. Manufacturing has share of 11.0 percent in US national income in IIQ2011, as shown in Table I-11. Most income in the US originates in services. Subsidies and similar measures designed to increase manufacturing jobs will not increase economic growth and employment and may actually reduce growth by diverting resources away from currently employment-creating activities because of the drain of taxation.

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

	SAAR IQ2012	% Total	SAAR IIQ2012	% Total
National Income WCCA	13,788.3	100.0	13,867.8	100.0
Domestic Industries	13,573.4	98.4	13,620.5	98.2
Private Industries	11,922.7	86.5	11,967.5	86.3
Agriculture	134.0	1.0	132.8	0.9
Mining	211.0	1.5	208.7	1.5
Utilities	211.9	1.5	214.7	1.6
Construction	585.6	4.3	585.8	4.2
Manufacturing	1521.9	11.0	1530.4	11.0
Durable Goods	865.2	6.3	877.3	6.3
Nondurable Goods	656.6	4.8	653.1	4.7
Wholesale Trade	831.6	6.0	852.8	6.2
Retail Trade	947.5	6.9	947.2	6.8
Transportation & WH	416.5	3.0	417.7	3.0
Information	486.7	3.5	497.0	3.6
Finance, insurance, RE	2301.3	16.7	2271.1	16.4
Professional, BS	1955.0	14.2	1983.5	14.3
Education, Health Care	1380.8	10.0	1382.7	10.0
Arts, Entertainment	541.1	3.9	542.7	3.9
Other Services	397.9	2.9	400.3	2.9
Government	1650.7	12.0	1653.0	11.9
Rest of the World	214.9	1.6	247.3	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://www.bea.gov/iTable/index_nipa.cfm

The NBER dates recessions in the US from peaks to troughs as: IQ80 to IIIQ80, IIIQ81 to IV82 and IVQ07 to IIQ09 (http://www.nber.org/cycles/cyclesmain.html). Table I-12 provides total annual level nonfarm employment in the US for the 1980s and the 2000s, which is different from 12 months comparisons. Nonfarm jobs rose by 4.853 million in 1982 to 1984, or 5.4 percent, and continued rapid growth in the rest of the decade. In contrast, nonfarm jobs are down by 7.724 million in 2010 relative to 2007 and fell by 933,000 in 2010 relative to 2009 even after six quarters of GDP growth. Monetary and fiscal stimuli have failed in increasing growth to rates required for mitigating job stress. The initial growth impulse reflects a flatter growth curve in the current expansion.

Table I-12, US, Total Nonfarm Employment in Thousands

Year	Total Nonfarm	Year	Total Nonfarm
1980	90,528	2000	131,785
1981	91,289	2001	131,826
1982	89,677	2002	130,341
1983	90,280	2003	129,999
1984	94,530	2004	131,435
1985	97,511	2005	133,703
1986	99,474	2006	136,086
1987	102,088	2007	137,598
1988	105,345	2008	136,790
1989	108,014	2009	130,807
1990	109,487	2010	129,874
1991	108,374	2011	131,359

Source: http://www.bls.gov/data/

The highest average yearly percentage of unemployed to the labor force since 1940 was 14.6 percent in 1940 followed by 9.9 percent in 1941, 8.5 percent in 1975, 9.7 percent in 1982 and 9.6 percent in 1983 (ftp://ftp.bls.gov/pub/special.requests/lf/aa2006/pdf/cpsaat1.pdf). The rate of unemployment remained at high levels in the 1930s, rising from 3.2 percent in 1929 to 22.9 percent in 1932 in one estimate and 23.6 percent in another with real wages increasing by 16.4 percent (Margo 1993, 43; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 214-5). There are alternative estimates of 17.2 percent or 9.5 percent for 1940 with real wages increasing by 44 percent. Employment declined sharply during the 1930s. The number of hours worked remained in 1939 at 29 percent below the level of 1929 (Cole and Ohanian 1999). Private hours worked fell in 1939 to 25 percent of the level in 1929. The policy of encouraging collusion through the National Industrial Recovery Act (NIRA), to maintain high prices, together with the National Labor Relations Act (NLRA), to maintain high wages, prevented the US economy from recovering employment levels until Roosevelt abandoned these policies toward the end of the 1930s (for review of the literature analyzing the Great Depression see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 198-217).

The Bureau of Labor Statistics (BLS) makes yearly revisions of its establishment survey (Harris 2011BA):

“With the release of data for January 2011, the Bureau of Labor Statistics (BLS) introduced its annual revision of national estimates of employment, hours, and earnings from the Current Employment Statistics (CES) monthly survey of nonfarm establishments.  Each year, the CES survey realigns its sample-based estimates to incorporate universe counts of employment—a process known as benchmarking.  Comprehensive counts of employment, or benchmarks, are derived primarily from unemployment insurance (UI) tax reports that nearly all employers are required to file with State Workforce Agencies.”

The number of not seasonally adjusted total private jobs in the US in Dec 2010 is 108.464 million, declining to 106.079 million in Jan 2011, or by 2.385 million, because of the adjustment of a different benchmark and not actual job losses. The not seasonally adjusted number of total private jobs in Dec 1984 is 80.250 million, declining to 78.704 million in Jan 1985, or by 1.546 million for the similar adjustment. Table I-13 attempts to measure job losses and gains in the recessions and expansions of 1981-1985 and 2007-2011. The final ten rows provide job creation from May 1983 to May 1984 and from May 2010 to May 2011, that is, at equivalent stages of the recovery from two comparable strong recessions. The row “Change ∆%” for May 1983 to May 1984 shows an increase of total nonfarm jobs by 4.9 percent and of 5.9 percent for total private jobs. The row “Change ∆%” for May 2010 to May 2011 shows an increase of total nonfarm jobs by 0.7 percent and of 1.7 percent for total private jobs. The last two rows of Table 7 provide a calculation of the number of jobs that would have been created from May 2010 to May 2011 if the rate of job creation had been the same as from May 1983 to May 1984. If total nonfarm jobs had grown between May 2010 and May 2011 by 4.9 percent, as between May 1983 and May 1984, 6.409 million jobs would have been created in the past 12 months for a difference of 5.457 million more total nonfarm jobs relative to 0.952 million jobs actually created. If total private jobs had grown between May 2010 and May 2011 by 5.9 percent as between May 1983 and May 1984, 6.337 million private jobs would have been created for a difference of 4.539 million more total private jobs relative to 1.798 million jobs actually created.

Table I-13, US, Total Nonfarm and Total Private Jobs Destroyed and Subsequently Created in

Two Recessions IIIQ1981-IVQ1982 and IVQ2007-IIQ2009, Thousands and Percent

	Total Nonfarm Jobs	Total Private Jobs
06/1981 #	92,288	75,969
11/1982 #	89,482	73,260
Change #	-2,806	-2,709
Change ∆%	-3.0	-3.6
12/1982 #	89,383	73,185
05/1984 #	94,471	78,049
Change #	5,088	4,864
Change ∆%	5.7	6.6
11/2007 #	139,090	116,291
05/2009 #	131,626	108,601
Change %	-7,464	-7,690
Change ∆%	-5.4	-6.6
12/2009 #	130,178	107,338
05/2011 #	131,753	108,494
Change #	1,575	1,156
Change ∆%	1.2	1.1
05/1983 #	90,005	73,667
05/1984 #	94,471	78,049
Change #	4,466	4,382
Change ∆%	4.9	5.9
05/2010 #	130,801	107,405
05/2011 #	131,753	109,203
Change #	952	1,798
Change ∆%	0.7	1.7
Change # by ∆% as in 05/1984 to 05/1985	6,409*	6,337**
Difference in Jobs that Would Have Been Created	5,457 = 6,409-952	4,539 = 6,337-1,798

*[(130,801x1.049)-130,801] = 6,409 thousand

**[(107,405)x1.059 – 107,405] = 6,337 thousand

Source: http://www.bls.gov/data/

IB Stagnating Real Wages. The wage bill is the product of average weekly hours times the earnings per hour. Table IB-1 provides the estimates by the Bureau of Labor Statistics (BLS) of earnings per hour seasonally adjusted, increasing from $23.22/hour in Oct 2011 to $23.58/hour in Oct 2012, or by 1.6 percent. There has been disappointment about the pace of wage increases because of rising food and energy costs that inhibit consumption and thus sales and similar concern about growth of consumption that accounts for about 70 percent of GDP. Growth of consumption by decreasing savings by means of controlling interest rates in what is called financial repression may not be lasting and sound for personal finances (See Pelaez and Pelaez, Globalization and the State, Vol. II (2008c), 81-6 and http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/09/collapse-of-united-states-dynamism-of.html http://cmpassocregulationblog.blogspot.com/2012/07/recovery-without-jobs-stagnating-real.html http://cmpassocregulationblog.blogspot.com/2012/06/mediocre-recovery-without-jobs.html http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-growth-with-high-unemployment.html http://cmpassocregulationblog.blogspot.com/2012/04/mediocre-economic-growth-falling-real.html http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html http://cmpassocregulationblog.blogspot.com/2012/01/mediocre-economic-growth-financial.html http://cmpassocregulationblog.blogspot.com/2011/12/slow-growth-falling-real-disposable.html http://cmpassocregulationblog.blogspot.com/2011/11/us-growth-standstill-falling-real.html http://cmpassocregulationblog.blogspot.com/2011/10/slow-growth-driven-by-reducing-savings.html). Average hourly earnings seasonally adjusted decreased 0.04 percent from $23.59 in Sep 2012 to $23.58 in Oct 2012. Average private weekly earnings increased $12.38 from $798.77 in Oct 2011 to $811.15 in Oct 2012 or 1.5 percent and decreased from $811.50 in Sep 2012 to $811.15 in Oct 2012 or 0.4 percent. The inflation-adjusted wage bill can only be calculated for Sep, which is the most recent month for which there are estimates of the consumer price index. Earnings per hour (not-seasonally-adjusted (NSA)) rose from $23.09 in Sep 2011 to $23.70 in Sep 2012 or by 2.6 percent (http://www.bls.gov/data/; see Table II-3 below). Data NSA are more suitable for comparison over a year. Average weekly hours NSA were 34.4 in Sep 2011 and 34.9 in Sep 2012 (http://www.bls.gov/data/; see Table II-2 below). The wage bill rose 2.3 percent in the 12 months ending in Sep 2012:

{[(wage bill in Sep 2012)/(wage bill in Sep 2011)]-1}100 =

{[($23.70x34.9)/($23.09x34.4)]-1]}100

= {[($827.13/$794.29)]-1}100 = 4.1%

CPI inflation was 2.0 percent in the 12 months ending in Sep 2012 (http://www.bls.gov/cpi/) for an inflation-adjusted wage-bill change of 2.1 percent :{[(1.041/1.02)-1]100}. The wage bill for Oct 2012 before inflation adjustment decreased 0.6 percent relative to the wage bill for Oct 2011:

{[(wage bill in Oct 2012)/(wage bill in Oct 2011)]-1}100 =

{[($23.54x34.4)/($23.34x34.9)]-1]}100

= {[($809.78/$814.57)]-1}100 = -0.6%

Average hourly earnings increased 2.6 percent from Sep 2011 to Sep 2012 {[($23.70/23.09) – 1]100 = 2.6%] while hours worked increased 1.5 percent {[(34.9/34.4) – 1]100 = 1.5%}. The increase of the wage bill is the product of the increase of hourly earnings of 2.6 percent and of hours worked of 1.5 percent {[(1.026x1.015) -1]100 = 4.1%}.

Energy and food price increases are similar to a “silent tax” that is highly regressive, harming the most those with lowest incomes. There are concerns that the wage bill would deteriorate in purchasing power because of renewed raw materials shocks in the form of increases in prices of commodities such as the 31.1 percent steady increase in the DJ-UBS Commodity Index from Jul 2, 2010 to Sep 2, 2011. The charts of four commodity price indexes by Bloomberg show steady increase since Jul 2, 2010 that was interrupted briefly only in Nov 2010 with the sovereign issues in Europe triggered by Ireland, in Mar 2011 by the earthquake and tsunami in Japan and in the beginning of May 2011 by the decline in oil prices and sovereign risk difficulties in Europe (http://www.bloomberg.com/markets/commodities/futures/). Renewed risk aversion because of the sovereign risks in Europe has reduced the rate of increase of the DJ UBS commodity index to 13.2 percent on Nov 2, 2012, relative to Jul 2, 2010 (see Table VI-4). Inflation has been rising in waves with carry trades driven by zero interest rates to commodity futures during periods of risk appetite with interruptions during risk aversion (http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united.html). Inflation-adjusted wages fall sharply during carry trades from zero interest rates to long positions in commodity futures during periods of risk appetite.

Table IB-1, US, Earnings per Hour and Average Weekly Hours SA

Earnings per Hour	Oct 2011	Aug 2012	Sep 2012	Oct 2012
Total Private	$23.22	$23.52	$23.59	$23.58
Goods Producing	$24.56	$24.73	$24.83	$24.76
Service Providing	$22.91	$23.23	$23.30	$23.30
Average Weekly Earnings
Total Private	$798.77	$809.09	$811.50	$811.15
Goods Producing	$984.86	$991.67	$998.17	$992.88
Service Providing	$762.90	$773.56	$775.89	$773.56
Average Weekly Hours
Total Private	34.4	34.4	34.4	34.4
Goods Producing	40.1	40.1	40.2	40.1
Service Providing	33.3	33.3	33.3	33.2

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

Table IB-2 provides average weekly hours of all employees in the US from 2006 to 2012. Average weekly hours fell from 35.0 in Dec 2007 at the beginning of the contraction to 33.8 in Jun 2009, which was the last month of the contraction. Average weekly hours rose to 34.4 in Dec 2011 and oscillated to 34.4 in Oct 2012.

Table IB-2, US, Average Weekly Hours of All Employees, NSA 2006-2012

Year	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
2006			34.2	34.6	34.3	34.6	34.9	34.6	34.5	34.9	34.4	34.6
2007	34.1	34.2	34.3	34.7	34.4	34.7	34.9	34.7	35.0	34.5	34.5	35.0
2008	34.2	34.2	34.8	34.4	34.4	34.9	34.5	34.6	34.4	34.4	34.6	34.1
2009	33.8	34.2	34.0	33.6	33.7	33.8	33.8	34.3	33.7	33.8	34.3	33.9
2010	33.7	33.6	33.8	34.0	34.4	34.1	34.2	34.7	34.1	34.3	34.2	34.2
2011	34.2	34.0	34.1	34.3	34.6	34.4	34.4	34.4	34.4	34.9	34.4	34.4
2012	34.5	34.2	34.3	34.7	34.3	34.4	34.8	34.5	34.9	34.4

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

Chart IB-1 provides average weekly hours monthly from Mar 2006 to Oct 2012. Average weekly hours remained relatively stable in the period before the contraction and fell sharply during the contraction as business could not support lower production with the same labor input. Average weekly hours rose rapidly during the expansion but have stabilized at a level below that prevailing before the contraction.

Chart IB-1, US, Average Weekly Hours of All Employees, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Calculations using BLS data of inflation-adjusted average hourly earnings are shown in Table II-3. The final column of Table II-3 (“12 Month Real ∆%”) provides inflation-adjusted average hourly earnings of all employees in the US. Average hourly earnings rose above inflation throughout the first nine months of 2007 just before the global recession that began in the final quarter of 2007 when average hourly earnings lost to inflation. In contrast, average hourly earnings of all US workers have risen less than inflation in four months in 2010 and in all but the first month in 2011 and the loss accelerated at 1.8 percent in Sep 2011, declining to a real loss of 1.1 percent in Feb 2012 and 0.6 percent in Mar 2012. There was a gain of 0.5 percent in Apr 2012 in inflation-adjusted average hourly earnings but another fall of 0.6 percent in May 2012 followed by increases of 0.3 percent in Jun and 0.9 percent in Jul 2012. Real hourly earnings stagnated in the 12 months ending in Aug 2012 with increase of only 0.1 percent and increased 0.6 percent in the 12 months ending in Oct 2012. Real hourly earnings are oscillating in part because of world inflation waves caused by carry trades from zero interest rates to commodity futures (http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united.html) and in part because of the collapse of hiring (http://cmpassocregulationblog.blogspot.com/2012/10/recovery-without-hiring-imf-view-united.html).

Table IB-3, US, Average Hourly Earnings Nominal and Inflation Adjusted, Dollars and % NSA

	AHE ALL	12 Month Nominal ∆%	∆% 12 Month CPI	12 Month Real ∆%
2007
Jan*	$20.70*	4.2*	2.1	2.1*
Feb*	$20.79*	4.1*	2.4	1.7*
Mar	$20.82	3.7	2.8	0.9
Apr	$21.05	3.3	2.6	0.7
May	$20.83	3.7	2.7	1.0
Jun	$20.82	3.8	2.7	1.1
Jul	$20.99	3.4	2.4	1.0
Aug	$20.85	3.5	2.0	1.5
Sep	$21.18	4.0	2.8	1.2
Oct	$21.07	2.7	3.5	-0.8
Nov	$21.13	3.3	4.3	-0.9
Dec	$21.37	3.7	4.1	-0.4
2010
Jan	$22.55	2.0	2.6	-0.6
Feb	$22.61	1.4	2.1	-0.7
Mar	$22.51	1.2	2.3	-1.1
Apr	$22.56	1.8	2.2	-0.4
May	$22.63	2.5	2.0	0.5
Jun	$22.37	1.7	1.1	0.6
Jul	$22.44	1.8	1.2	0.6
Aug	$22.58	1.7	1.1	0.6
Sep	$22.63	1.8	1.1	0.7
Oct	$22.73	1.9	1.2	0.7
Nov	$22.72	1.1	1.1	0.0
Dec	$22.79	1.7	1.5	0.2
2011
Jan	$23.20	2.9	1.6	1.3
Feb	$23.03	1.9	2.1	-0.2
Mar	$22.93	1.9	2.7	-0.8
Apr	$23.00	2.0	3.2	-1.2
May	$23.09	2.0	3.6	-1.5
Jun	$22.85	2.1	3.6	-1.4
Jul	$22.98	2.4	3.6	-1.2
Aug	$22.88	1.3	3.8	-2.4
Sep	$23.09	2.0	3.9	-1.8
Oct	$23.34	2.7	3.5	-0.8
Nov	$23.19	2.1	3.4	-1.3
Dec	$23.26	2.1	3.0	-0.9
2012
Jan	$23.61	1.8	2.9	-1.1
Feb	$23.45	1.8	2.9	-1.1
Mar	$23.41	2.1	2.7	-0.6
Apr	$23.64	2.8	2.3	0.5
May	$23.35	1.1	1.7	-0.6
Jun	$23.30	2.0	1.7	0.3
Jul	$23.52	2.3	1.4	0.9
Aug	$23.30	1.8	1.7	0.1
Sep	$23.70	2.6	2.0	0.6
Oct	$23.54	0.9

Note: AHE ALL: average hourly earnings of all employees; CPI: consumer price index; Real: adjusted by CPI inflation; NA: not available

*AHE of production and nonsupervisory employees because of unavailability of data for all employees

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

Average hourly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are provided in Table IB-4. Average hourly earnings fell 0.5 percent after adjusting for inflation in the 12 months ending in Mar 2012 and gained 0.4 percent in the 12 months ending in Apr 2011 but then lost 0.6 percent in the 12 months ending in May 2012 with a gain of 0.3 percent in the 12 months ending in Jun 2012 and 1.0 percent in Jul 2012 followed by 0.1 percent in Aug 2012 and 0.6 percent in Sep 2012. Table IB-4 confirms the trend of deterioration of purchasing power of average hourly earnings in 2011 and into 2012 with 12-month percentage declines in three of the first four months of 2012, increase in four and stagnation in one. Those who still work bring back home a paycheck that buys fewer goods than a year earlier and savings in bank deposits do not pay anything because of financial repression (Section IBC and earlier http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html).

Table IB-4, US, Average Hourly Earnings of All Employees NSA in Constant Dollars of 1982-1984

Year	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep
2006		10.05	10.11	9.92	9.88	9.97	9.88	10.03
2007	10.22	10.14	10.18	10.02	9.99	10.08	10.03	10.16
2008	10.12	10.11	10.00	9.91	9.84	9.77	9.83	9.94
2009	10.50	10.46	10.39	10.32	10.20	10.23	10.29	10.30
2010	10.43	10.34	10.35	10.37	10.26	10.29	10.34	10.36
2011	10.41	10.26	10.23	10.22	10.12	10.17	10.10	10.18
2012	10.30	10.21	10.27	10.16	10.15	10.27	10.11	10.24
∆% 12 Months	-1.1	-0.5	0.4	-0.6	0.3	1.0	0.1	0.6

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

The deterioration of purchasing power of average hourly earnings of US workers is shown by Chart IB-2 of the US Bureau of Labor Statistics. Chart IB-2 plots average hourly earnings of all US employees in constant 1982-1984 dollars with evident decline from 2010 to 2012.

Chart IB-2, US, Average Hourly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Chart IB-3 provides 12-month percentage changes of average hourly earnings of all employees in constant dollars of 1982-1984, that is, adjusted for inflation. There was sharp contraction of inflation-adjusted average hourly earnings of US employees during parts of 2007 and 2008. Rates of change in 12 months became positive in parts of 2009 and 2010 but then became negative again in 2011 and now into 2012 with temporary increase in Apr 2012 that was reversed in May with another gain in Jun and Jul 2012 followed by stagnation in Aug 2012 and marginal gain in Sep 2012.

Chart IB-3, Average Hourly Earnings of All Employees NSA 12-Month Percent Change, 1982-1984 Dollars, NSA 2007-2012

Source: US Bureau of Labor Statistics

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

Average weekly earnings of all US employees in the US in constant dollars of 1982-1984 from the dataset of the US Bureau of Labor Statistics (BLS) are provided in Table IB-5. Average weekly earnings fell 0.9 percent after adjusting for inflation in the 12 months ending in Sep 2011, increased 0.9 percent in the 12 months ending in Oct, fell 0.7 percent in the 12 months ending in Nov and 0.3 in the 12 months ending in Dec, declining 0.3 percent in the 12 months ending in Jan 2012 and 0.4 percent in the 12 months ending in Feb 2012. Average weekly earnings in constant dollars were flat in Mar 2012 relative to Mar 2011, increasing 0.04 percent. Average weekly earnings in constant dollars increased 1.6 percent in Apr 2012 relative to Apr 2011 but fell 1.4 percent in May 2012 relative to May 2011, increasing 0.3 percent in the 12 months ending in Jun and 2.1 percent in Jul 2012. Real weekly earnings increased 0.4 percent in the 12 months ending in Aug 2012 and 2.1 percent in the 12 months ending in Sep 2012. Table IB-5 confirms the trend of deterioration of purchasing power of average weekly earnings in 2011 and into 2012 with oscillations according to carry trades causing world inflation waves (http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html). Those who still work bring back home a paycheck that buys fewer goods than a year earlier. The fractured US job market does not provide an opportunity for advancement as in past booms following recessions.

Table IB-5, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, NSA 2007-2012

Year	Mar	Apr	May	Jun	Jul	Aug	Sep
2006	343.71	349.78	340.12	341.91	347.97	341.76	346.19
2007	347.76	353.41	344.58	346.74	351.68	347.98	355.56
2008	351.70	344.13	340.77	343.40	337.06	340.18	341.83
2009	355.65	349.17	347.79	344.59	345.92	352.80	347.04
2010	349.60	351.84	356.80	349.97	352.02	358.90	353.27
2011	349.90	350.77	353.56	348.23	349.90	347.42	350.08
2012	350.04	356.52	348.50	349.28	357.26	348.93	357.44
∆% 12 M	0.0	1.6	-1.4	0.3	2.1	0.4	2.1

Source: US Bureau of Labor Statistics

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

Chart IB-4 provides average weekly earnings of all employees in constant dollars of 1982-1984. The same pattern emerges of sharp decline during the contraction, followed by recovery in the expansion and continuing fall from 2010 to 2011 and into 2012.

Chart IB-4, US, Average Weekly Earnings of All Employees in Constant Dollars of 1982-1984, SA 2006-2012

Source: US Bureau of Labor Statistics

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

Chart II-5 provides 12-month percentage changes of average weekly earnings of all employees in the US in constant dollars of 1982-1984. There is the same pattern of contraction during the global recession in 2008 and then again trend of deterioration in the recovery without hiring and inflation waves in 2011 and 2012 (Chart II-5 provides 12-month percentage changes of average weekly earnings of all employees in the US in constant dollars of 1982-1984. There is the same pattern of contraction during the global recession in 2008 and then again trend of deterioration in the recovery without hiring and inflation waves in 2011 and 2012 (http://cmpassocregulationblog.blogspot.com/2012/09/recovery-without-hiring-world-inflation.html http://cmpassocregulationblog.blogspot.com/2012_09_01_archive.html http://cmpassocregulationblog.blogspot.com/2012/07/world-inflation-waves-financial.html http://cmpassocregulationblog.blogspot.com/2012/06/destruction-of-three-trillion-dollars.html http://cmpassocregulationblog.blogspot.com/2012/05/world-inflation-waves-monetary-policy.html http://cmpassocregulationblog.blogspot.com/2012/06/recovery-without-hiring-continuance-of.html http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html http://cmpassocregulationblog.blogspot.com/2012/03/global-financial-and-economic-risk.html http://cmpassocregulationblog.blogspot.com/2012/02/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/01/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/01/recovery-without-hiring-united-states.html).

http://cmpassocregulationblog.blogspot.com/2012/09/recovery-without-hiring-world-inflation.html http://cmpassocregulationblog.blogspot.com/2012_09_01_archive.html http://cmpassocregulationblog.blogspot.com/2012/07/world-inflation-waves-financial.html http://cmpassocregulationblog.blogspot.com/2012/06/destruction-of-three-trillion-dollars.html http://cmpassocregulationblog.blogspot.com/2012/05/world-inflation-waves-monetary-policy.html http://cmpassocregulationblog.blogspot.com/2012/06/recovery-without-hiring-continuance-of.html http://cmpassocregulationblog.blogspot.com/2012/04/fractured-labor-market-with-hiring.html http://cmpassocregulationblog.blogspot.com/2012/03/global-financial-and-economic-risk.html http://cmpassocregulationblog.blogspot.com/2012/02/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/01/world-inflation-waves-united-states.html http://cmpassocregulationblog.blogspot.com/2012/01/recovery-without-hiring-united-states.html).

Chart IB-5, US, Average Weekly Earnings of All Employees NSA in Constant Dollars of 1982-1984 12-Month Percent Change, NSA 2007-2011

Source: US Bureau of Labor Statistics

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

II Stagnating Real Disposable Income and Consumption Expenditures and Financial Repression. Subsection IIA Stagnating Real Disposable Income and Consumption Expenditures provides analysis of the personal income and consumption outlays of the Bureau of Economic Analysis (BEA) for Jul 2012. Subsection IIB Collapse of United States Dynamism of Income Growth and Employment Creation provides analysis of the frustration of US growth and creation of income, employment and wealth. Subsection IIC Repression of Savings analyzes financial repression and how it is affecting savings and wealth allocation in the US.

Subsection IIA Stagnating Real Disposable Income and Consumption Expenditures. The data on personal income and consumption have been revised back to 2003 as it the case of the national accounts (GDP revisions, which are covered in http://cmpassocregulationblog.blogspot.com/2012/07/decelerating-united-states-recovery.html with the latest estimates at http://cmpassocregulationblog.blogspot.com/2012/10/mediocre-and-decelerating-united-states.html. The release of the Bureau of Economic Analysis (BEA) for personal income and outlays for Jun 2012 available on Jul 31, 2012 provides “the results of the annual revision of national and product accounts (NIPAs), beginning with estimates for Jan 2009” (http://www.bea.gov/newsreleases/national/pi/2012/pdf/pi0612.pdf). All revisions are incorporated in this subsection as provided in the latest Personal Income and Outlays: September 2012 released on Oct 29, 2012 (http://www.bea.gov/newsreleases/national/pi/2012/pdf/pi0912.pdf) and in the interactive dataset of the Bureau of Economic Analysis (BEA) (http://www.bea.gov/iTable/index_nipa.cfm). Table IIA-1 provides monthly and annual equivalent percentage changes, seasonally adjusted, of current dollars or nominal personal income (NPI), current dollars or nominal disposable personal income (NDPI), real or constant chained (2005) dollars DPI (RDPI), current dollars nominal personal consumption expenditures (NPCE) and constant or chained (2005) dollars PCE. There are waves of changes in personal income and expenditures in Table IIA-1 that correspond somewhat to inflation waves observed worldwide (http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united.html) because of the influence through price indexes. In the first wave in Jan-Apr 2011 with relaxed risk aversion, nominal personal income (NPI) increased at the annual equivalent rate of 8.4 percent, nominal disposable personal income (NDPI) at 5.8 percent and nominal personal consumption expenditures (NPCE) at 6.5 percent. Real disposable income (RDPI) increased at the annual equivalent rate of 1.5 percent and real personal consumption expenditures (RPCE) rose at annual equivalent 2.4 percent. In the second wave in May-Aug 2011 under risk aversion, NPI rose at annual equivalent 0.9 percent, NPDI at 1.2 percent and NPCE at 2.7 percent. RDPI contracted at 1.5 percent annual equivalent and RPCE crawled at 0.3 percent annual equivalent. With mixed shocks of risk aversion in the third wave from Sep to Dec 2011, NPI rose at 1.5 percent annual equivalent, NDPI at 0.9 percent and NPCE at 2.7 percent. RDPI increased at 0.3 percent annual equivalent and RPCE at 1.8 percent annual equivalent. In the fourth wave from Jan to Mar 2012, NPI increased at 8.7 percent annual equivalent and NDPI at 8.3 percent. Real disposable income (RDPI) is more dynamic in the revisions, growing at 4.5 percent annual equivalent and RPCE at 2.8 percent. The policy of repressing savings with zero interest rates stimulated growth of nominal consumption (NPCE) at the annual equivalent rate of 6.6 percent and real consumption (RPCE) at 2.8 percent. In the fifth wave in Apr-Jul 2012, NPI increased at annual equivalent 3.0 percent, NDPI at 2.7 percent and RDPI at 2.7 percent. Financial repression failed to stimulate consumption with NPCE growing at 1.2 percent annual equivalent and RPCE at 1.2 percent. The revisions of GDP lowered growth during the expansion from average annual equivalent of 2.4 per quarter from IIQ2009 to IQ2011 to average 2. In the sixth wave in Aug-Sep 2012, in another wave of carry trades into commodity futures, NPI and NDPI increased at 3.0 percent annual equivalent while real disposable income (RDPI) declined at 1.8 percent annual equivalent. The US economy began to decelerate in mid 2010 and has not recovered the pace of growth in the early expansion phase. Growth in the first three quarters of 2012 accumulates to 1.3 percent {[(1.02)^1/4(1.013)^1/4(1.02)^1/4 -1]100 = 1.3%}, which is equivalent to 1.77 percent per year {([(1.02)^1/4(1.013)^1/4(1.02)^1/4]² – 1]100 = 1.77%}. Surprisingly, the revised data for personal income and personal consumption are much stronger than earlier until the bump in Aug 2012. RDPI stagnated in Jan-Dec 2011 with the latest revised data compared with growth of 3.3 percent in Jan-Dec 2010 but grew at annual equivalent 4.5 percent in Jan-Mar 2012 and 2.7 percent in Apr-Jul. The salient deceleration is the decline of the annual equivalent rate of NPCE to 1.2 percent annual equivalent in Apr-Jul 2012 and of RPCE to 1.2 percent. A bump occurred in Aug with increases of commodity prices by the carry trade from zero interest rates to exposures in commodity futures and other risk financial assets. Real disposable income fell 0.3 percent in Aug 2012 or at annual equivalent minus 3.5 percent. Nominal personal consumption expenditures increased 0.5 percent in Aug 2012 or at annual equivalent 6.2 percent but only 0.1 percent for real personal consumption expenditures or at annual equivalent 1.2 percent. Both nominal personal income and nominal disposable income increased 0.1 percent in Aug 2012 or at 1.2 percent in annual equivalent.

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

	NPI	NDPI	RDPI	NPCE	RPCE
2012
Sep	0.4	0.4	0.0	0.8	0.4
Aug	0.1	0.1	-0.3	0.5	0.1
AE ∆% Aug-Sep	3.0	3.0	-1.8	8.1	3.0
Jul	0.2	0.2	0.1	0.4	0.3
Jun	0.3	0.3	0.2	0.0	-0.1
May	0.3	0.3	0.5	-0.2	0.0
Apr	0.2	0.1	0.1	0.2	0.2
AE ∆% Apr-Jul	3.0	2.7	2.7	1.2	1.2
Mar	0.5	0.5	0.2	0.3	0.0
Feb	0.7	0.6	0.3	0.8	0.4
Jan	0.9	0.9	0.6	0.5	0.3
AE ∆% Jan-Mar	8.7	8.3	4.5	6.6	2.8
2011
∆% Jan-Dec 2011*	3.6	2.5	0.0	4.2	1.7
Dec	0.3	0.3	0.2	0.1	0.0
Nov	-0.2	-0.3	-0.3	0.1	0.0
Oct	0.3	0.3	0.3	0.2	0.2
Sep	0.1	0.0	-0.1	0.5	0.4
AE ∆% Sep-Dec	1.5	0.9	0.3	2.7	1.8
Aug	0.0	0.0	-0.3	0.2	-0.1
Jul	0.1	0.2	-0.1	0.7	0.5
Jun	0.2	0.2	0.1	-0.1	-0.2
May	0.0	0.0	-0.2	0.1	-0.1
AE ∆% May-Aug	0.9	1.2	-1.5	2.7	0.3
Apr	0.3	0.3	0.0	0.4	0.0
Mar	0.1	0.1	-0.3	0.7	0.3
Feb	0.4	0.4	0.0	0.6	0.3
Jan	1.9	1.1	0.8	0.4	0.2
AE ∆% Jan-Apr	8.4	5.8	1.5	6.5	2.4
2010
∆% Jan-Dec 2010**	5.3	4.9	3.3	4.4	2.8
Dec	0.7	0.7	0.4	0.4	0.2
Nov	0.2	0.2	0.1	0.5	0.4
Oct	0.4	0.3	0.1	0.6	0.4
IVQ2010∆%	1.3	1.2	0.6	1.5	1.0
IVQ2010 AE ∆%	5.3	4.9	2.4	6.6	4.1

Notes: NPI: current dollars personal income; NDPI: current dollars disposable personal income; RDPI: chained (2005) dollars DPI; NPCE: current dollars personal consumption expenditures; RPCE: chained (2005) dollars PCE; AE: annual equivalent; IVQ2010: fourth quarter 2010; A: annual equivalent

Percentage change month to month seasonally adjusted

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

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

Further information on income and consumption is provided by Table IIA-2. The 12-month rates of increase of RDPI and RPCE in 2011 show sharp trend of deterioration of RDPI from over 3 percent in the final four months of 2010 to less than 3 percent at the end of IQ2011 and then collapsing to a range of 0.9 to 0.0 percent in Jun-Dec 2011. Revisions shows decline of RDPI of 0.2 percent in the 12 months ending in Jan 2012 and marginal increase of 0.1 percent in the 12 months ending in Feb 2012. The significant difference is continuing growth of 12-month percentage changes of RDPI with 1.6 percent in Jun 2012, 1.8 percent in both Jul and Aug 2012 and 1.9 percent in Sep 2012. RPCE growth decelerated less sharply from close to 3 percent in IVQ 2010 to 1.6 percent in Mar 2012 and 2.1 percent in Sep 2012. Subdued growth of RPCE could affect revenues of business. Growth rates of personal consumption have weakened. Goods and especially durable goods have been driving growth of PCE as shown by the much higher 12-month rates of growth of real goods PCE (RPCEG) and durable goods real PCE (RPCEGD) than services real PCE (RPCES). The faster expansion of industry in the economy is derived from growth of consumption of goods and in particular of consumer durable goods while growth of consumption of services is much more moderate. The 12-month rates of growth of RPCEGD have fallen from around 10 percent and even higher in several months from Sep 2010 to Feb 2011 to the range of 6.5 to 9.3 percent in Jan-Sep 2012. RPCEG growth rates have fallen from around 5 percent late in 2010 and early Jan-Feb 2011 to the range of 2.4 to 4.1 percent in Jan-Sep 2012. There are limits to sustained growth on the basis of financial repression in an environment of weak labor markets and real labor remuneration.

Table IIA-2, Real Disposable Personal Income and Real Personal Consumption Expenditures Percentage Change from the Same Month a Year Earlier %

	RDPI	RPCE	RPCEG	RPCEGD	RPCES
2012
Sep	1.9	2.1	3.8	8.2	1.2
Aug	1.8	2.0	4.1	9.3	1.0
Jul	1.8	1.9	3.1	7.3	1.2
Jun	1.6	2.0	3.5	8.6	1.3
May	1.5	1.9	3.0	7.4	1.4
Apr	0.8	1.8	2.4	6.5	1.5
Mar	0.7	1.6	2.6	6.6	1.1
Feb	0.1	1.9	2.7	7.4	1.5
Jan	-0.2	1.8	2.6	6.8	1.4
2011
Dec	0.0	1.7	2.5	6.0	1.3
Nov	0.3	1.9	2.6	5.8	1.5
Oct	0.7	2.3	3.2	5.9	1.8
Sep	0.5	2.4	3.4	7.0	2.0
Aug	0.4	2.1	2.6	5.3	1.9
Jul	0.9	2.8	4.1	6.4	2.1
Jun	0.9	2.4	3.4	5.3	1.9
May	1.0	2.6	3.9	6.5	2.0
Apr	1.8	3.0	4.7	8.2	2.1
Mar	2.6	3.0	4.2	7.8	2.4
Feb	3.4	3.1	5.5	11.3	1.9
Jan	3.5	3.1	5.5	11.0	1.9
2010
Dec	3.3	2.8	4.7	9.0	1.9
Nov	3.5	3.2	5.1	8.8	2.2
Oct	3.7	2.7	5.3	10.8	1.5
Sep	3.2	2.5	4.7	9.1	1.5

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

Numbers are percentage changes from the same month a year earlier

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

Chart IIA-1 shows US real personal consumption expenditures (RPCE) between 1995 and 2012. There is an evident drop in RPCE during the global recession in 2007 to 2009 but the slope is flatter during the current recovery than in the period before 2007.

Chart IIA-1, US, Real Personal Consumption Expenditures, Quarterly Seasonally Adjusted at Annual Rates 1995-2012

Source: US Bureau of Economic Analysis

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

Percent changes from the prior period in seasonally-adjusted annual equivalent quarterly rates (SAAR) of real personal consumption expenditures (RPCE) are provided in Chart IIA-2 from 1995 to 2012. The average rate could be visualized as a horizontal line. Although there are not yet sufficient observations, it appears from Chart IB-2 that the average rate of growth of RPCE was higher before the recession than during the past twelve quarters of expansion that began in IIIQ2009.

Chart IIA-2, Percent Change from Prior Period in Real Personal Consumption Expenditure, Quarterly Seasonally Adjusted at Annual Rates 1995-2012

Source: US Bureau of Economic Analysis

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

Personal income and its disposition are shown in Table IIA-3. The latest revisions have changed movements in two forms: (1) more dynamism in personal and disposable income; (2) stronger trend of increase of the savings rate with decline into Aug and Sep. Disposable personal income in current dollars or without adjusting for inflation increased from the annual rate of $11,609.1 billion in Dec 2011 to $11,996.2 billion in Sep 2012, by 3.3 percent or at annual equivalent 4.5 percent. Nominal wage and salary disbursements increased from the annual rate of $6687.6 billion in Dec 2011 to $$6940.6 billion in Sep 2012, by 3.8 percent or at annual equivalent rate of 5.1 percent. From Dec 2010 to Dec 2011, wage and salary disbursements increased 3.2 percent and disposable personal income 2.5 percent. Personal savings as percent of disposable personal income, or savings rate, fell from 4.9 percent in Dec 2010 to 3.5 percent in Dec 2011 but climbed back to 4.1 percent in Jul 2012 but declined to 3.7 percent in Aug 2012 and 3.3 percent in Sep 2012. Revised data suggest that economic weakness originates in increasing savings but fractured labor markets (http://cmpassocregulationblog.blogspot.com/2012/10/twenty-nine-million-unemployed-or.html) and weak hiring (http://cmpassocregulationblog.blogspot.com/2012/10/recovery-without-hiring-imf-view-united.html) are ignored in such interpretation.

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

	Personal Income	Wages & Salaries	Personal Taxes	DPI	Savings Rate %
Sep 2012	13,484.7	6,940.6	1,488.5	11.996.2	3.3
Aug 2012	13,436.6	6,919.8	1,483.3	11,953.2	3.7
Change Sep/Aug	48.1 ∆% 0.4	20.8 ∆% 0.3	5.2 ∆% 0.4	43.0 ∆% 0.4
Jul 2012	13,418.8	6,912.8	1,480.8	11,938.1	4.1
Change Aug/Jul	17.8 ∆% 0.1	7.0 ∆% 0.1	2.5 ∆% 0.2	15.1 ∆% 0.1
Jun 2012	13,396.9	6,901.4	1,477.8	11,919.1	4.4
Change Jul/Jun	21.9 ∆% 0.2	11.4 ∆% 0.2	3.0 ∆% 0.2	19.0 ∆% 0.2
May 2012	13,355.3	6,874.9	1,470.4	11,884.9	4.1
Change Jun/ May	41.6 ∆% 0.3	26.5 ∆% 0.4	7.4 ∆% 0.5	34.2 ∆% 0.3
Apr 2012	13,320.1	6,867.0	1,464.8	11,855.2	3.6
Change May/  Apr	35.2 ∆% 0.3	7.9 ∆% 0.1	5.6 ∆% 0.4	29.7 ∆% 0.3
Mar	13,298.3	6,869.4	1,460.6	11,837.7	3.7
Change  Apr/ Mar	21.8 ∆% 0.2	-2.4 ∆% 0.0	4.2 ∆% 0.3	17.5 ∆% 0.1
Feb 2012	13,234.7	6,831.5	1,452.0	11,782.7	3.5
Change Mar/ Feb	63.6 ∆% 0.5	37.9 ∆% 0.6	8.6 ∆% 0.6	55.0 ∆% 0.5
Jan	13,148.4	6,776.7	1,439.6	11,708.8	3.7
Change Feb/Jan	86.3 ∆% 0.7	54.8 ∆% 0.8	12.4 ∆% 0.9	73.9 ∆% 0.6
Dec 2011	13,032.2	6,687.6	1,423.1	11,609.1	3.5
Change Jan/Dec	116.2   ∆% 0.9	89.1        ∆% 1.3	16.5       ∆% 1.2	99.7 ∆% 0.9
Dec 2010	12,574.1	6,482.8	1,243.5	11,330.6	4.9
Change Dec 2011/ Dec 2010	458.1 ∆% 3.6	204.8   ∆% 3.2	179.6     ∆% 14.4	278.5    ∆% 2.5

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

Chart IIA-3 provides personal income in the US between 1980 and 1989. These data are not adjusted for inflation that was still high in the 1980s in the exit from the Great Inflation of the 1960s and 1970s. Personal income grew steadily during the 1980s after recovery from two recessions from Jan IQ1980 to Jul IIIQ1980 and from Jul IIIQ1981 to Nov IVQ1982 (http://www.nber.org/cycles.html) with combined drop of GDP by 4.8 percent.

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

Source: US Bureau of Economic Analysis

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

A different evolution of personal income is shown in Chart IIA-4. Personal income also fell during the recession from Dec IVQ2007 to Jun IIQ2009 (http://www.nber.org/cycles.html). Growth of personal income during the expansion has been tepid even with the new revisions.

Chart IIA-4, US, Personal Income, Current Billions of Dollars, Quarterly Seasonally Adjusted at Annual Rates, 2007-2012

Source:

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

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

Chart IIA-5, US, Real Disposable Income, Billions of Chained 2005 Dollars, Quarterly Seasonally Adjusted at Annual Rates 1980-1989

Source: US Bureau of Economic Analysis

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

Much weaker performance of real disposable income is evident in Chart IIA-6. There was initial recovery in 2010 and then income after inflation and taxes stagnated into 2011. There is more dynamism with the new revisions for the first half of 2012.

Chart IIA-6, US, Real Disposable Income, Billions of Chained 2005 Dollars, Seasonally Adjusted at Annual Rates, 2007-2012

Source: US Bureau of Economic Analysis

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

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

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

Source: US Bureau of Economic Analysis

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

Chart IIA-8 provides percentage quarterly changes in real disposable income from the preceding period at seasonally-adjusted annual rates from 2007 to 2012. There has been a period of positive rates followed by decline of rates and then negative and low rates in 2011. Recovery in 2012 has not recovered the dynamism of the brief early phase of expansion.

Chart, IIA-8, US, Real Disposable Income, Percentage Change from Preceding Period at Seasonally-Adjusted Annual Rates, 2007-2012

Source: US Bureau of Economic Analysis

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

In the latest available report, the Bureau of Economic Analysis (BEA) estimates US personal income in 2012 at the seasonally adjusted annual rate of $13,484.7 billion, as shown in Table IIA-3 above (see Table 1 at http://www.bea.gov/newsreleases/national/pi/2012/pdf/pi0912.pdf). The major portion of personal income is compensation of employees of $8,636.7 billion, or 64.1 percent of the total. Wage and salary disbursements are $6,940.6 billion, of which $5,735.7 billion by private industries and supplements to wages and salaries of $1,696.1 billion (employer contributions to pension and insurance funds are $1,179.4 billion and contributions to social insurance are $516.7 billion). In Aug 1985, US personal income was $3,503.2 billion at SAAR (http://www.bea.gov/iTable/index_nipa.cfm). Compensation of employees was $2,427.2 billion, or 70.1 percent of the total. Wage and salary disbursement were $1,995.4 billion of which $1618.6 billion by private industries. Supplements to wages and salaries were $431.8 billion with employer contributions to pension and insurance funds of $283.4 billion and $148.4 billion to government social insurance. Chart IIA-9 provides US wage and salary disbursement by private industries in the 1980s. Growth was robust after the interruption of the recessions.

Chart IIA-9, US, Wage and Salary Disbursement, Private Industries, Quarterly, Seasonally Adjusted at Annual Rates Billions of Dollars, 1980-1989

Source: US Bureau of Economic Analysis

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

Chart IIA-10 shows US wage and salary disbursement of private industries from 2007 to 2012. There is a drop during the contraction followed by initial recovery in 2010 and then the current much weaker relative performance in 2011 and 2012.

Chart IIA-10, US, Wage and Salary Disbursement, Private Industries, Quarterly, Seasonally Adjusted at Annual Rates, Billions of Dollars 2007-2012

Source: US Bureau of Economic Analysis

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

Chart IIA-11 provides finer detail with monthly wage and salary disbursement of private industries from 2007 to 2012. There is decline during the contraction and a period of mild recovery followed by stagnation and recent recovery that is weaker than in earlier expansion periods of the business cycle.

Chart IIA-11, US, Wage and Salary Disbursement, Private Industries, Monthly, Seasonally Adjusted at Annual Rates, Billions of Dollars 2007-2012

Source: US Bureau of Economic Analysis

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

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

Chart IIA-12, US, Real Disposable Per Capita Income, Monthly, Seasonally Adjusted at Annual Rates, Billions of Dollars 1980-1989

Source: US Bureau of Economic Analysis

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

Chart IIA-13 provides monthly real disposable personal per capita income from 2007 to 2012. There was initial recovery from the drop during the global recession followed by stagnation.

Chart IIA-13, US, Real Disposable Per Capita Income, Monthly, Seasonally Adjusted at Annual Rates, Billions of Dollars 2007-2012

Source: US Bureau of Economic Analysis

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

IIB Collapse of United States Dynamism of Income Growth and Employment Creation. There are four major approaches to the analysis of the depth of the financial crisis and global recession from IVQ2007 (Dec) to IIQ2009 (Jun) and the subpar recovery from IIIQ2009 (Jul) to the present IIIQ2012: (1) deeper contraction and slower recovery in recessions with financial crises; (2) counterfactual of avoiding deeper contraction by fiscal and monetary policies; (3) counterfactual that the financial crises and global recession would have been avoided had economic policies been different; and (4) evidence that growth rates are higher after deeper recessions with financial crises. A counterfactual consists of theory and measurements of what would have occurred otherwise if economic policies or institutional arrangements had been different. This task is quite difficult because economic data are observed with all effects as they actually occurred while the counterfactual attempts to evaluate how data would differ had policies and institutional arrangements been different (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008b), 125, 136). Counterfactual data are unobserved and must be calculated using theory and measurement methods. The measurement of costs and benefits of projects or applied welfare economics (Harberger 1971, 1997) specifies and attempts to measure projects such as what would be economic welfare with or without a bridge or whether markets would be more or less competitive in the absence of antitrust and regulation laws (Winston 2006). Counterfactuals were used in the “new economic history” of the United States to measure the economy with or without railroads (Fishlow 1965, Fogel 1964) and also in analyzing slavery (Fogel and Engerman 1974). A critical counterfactual in economic history is how Britain surged ahead of France (North and Weingast 1989). These four approaches are discussed below in turn followed with comparison of the two recessions of the 1980s from IQ1980 (Jan) to IIIQ1980 (Jul) and from IIIQ1981 (Jul) to IVQ1982 (Nov) as dated by the National Bureau of Economic Research (NBER http://www.nber.org/cycles.html). These comparisons are not idle exercises, defining the interpretation of history and even possibly critical policies and institutional arrangements. There is active debate on these issues (Bordo 2012Oct 21 http://www.bloomberg.com/news/2012-10-21/why-this-u-s-recovery-is-weaker.html Reinhart and Rogoff, 2012Oct14 http://www.economics.harvard.edu/faculty/rogoff/files/Is_US_Different_RR_3.pdf Taylor 2012Oct 25 http://www.johnbtaylorsblog.blogspot.co.uk/2012/10/an-unusually-weak-recovery-as-usually.html, Wolf 2012Oct23 http://www.ft.com/intl/cms/s/0/791fc13a-1c57-11e2-a63b-00144feabdc0.html#axzz2AotsUk1q).

(1) Lower Growth Rates in Recessions with Financial Crises. A monumental effort of data gathering, calculation and analysis by Professors Carmen M. Reinhart and Kenneth Rogoff at Harvard University is highly relevant to banking crises, financial crash, debt crises and economic growth (Reinhart 2010CB; Reinhart and Rogoff 2011AF, 2011Jul14, 2011EJ, 2011CEPR, 2010FCDC, 2010GTD, 2009TD, 2009AFC, 2008TDPV; see also Reinhart and Reinhart 2011Feb, 2010AF and Reinhart and Sbrancia 2011). See http://cmpassocregulationblog.blogspot.com/2011/07/debt-and-financial-risk-aversion-and.html. The dataset of Reinhart and Rogoff (2010GTD, 1) is quite unique in breadth of countries and over time periods:

“Our results incorporate data on 44 countries spanning about 200 years. Taken together, the data incorporate over 3,700 annual observations covering a wide range of political systems, institutions, exchange rate and monetary arrangements and historic circumstances. We also employ more recent data on external debt, including debt owed by government and by private entities.”

Reinhart and Rogoff (2010GTD, 2011CEPR) classify the dataset of 2317 observations into 20 advanced economies and 24 emerging market economies. In each of the advanced and emerging categories, the data for countries is divided into buckets according to the ratio of gross central government debt to GDP: below 30, 30 to 60, 60 to 90 and higher than 90 (Reinhart and Rogoff 2010GTD, Table 1, 4). Median and average yearly percentage growth rates of GDP are calculated for each of the buckets for advanced economies. There does not appear to be any relation for debt/GDP ratios below 90. The highest growth rates are for debt/GDP ratios below 30: 3.7 percent for the average and 3.9 for the median. Growth is significantly lower for debt/GDP ratios above 90: 1.7 for the average and 1.9 percent for the median. GDP growth rates for the intermediate buckets are in a range around 3 percent: the highest 3.4 percent average is for the bucket 60 to 90 and 3.1 percent median for 30 to 60. There is even sharper contrast for the United States: 4.0 percent growth for debt/GDP ratio below 30; 3.4 percent growth for debt/GDP ratio of 30 to 60; 3.3 percent growth for debt/GDP ratio of 60 to 90; and minus 1.8 percent, contraction, of GDP for debt/GDP ratio above 90.

For the five countries with systemic financial crises—Iceland, Ireland, UK, Spain and the US—real average debt levels have increased by 75 percent between 2007 and 2009 (Reinhart and Rogoff 2010GTD, Figure 1). The cumulative increase in public debt in the three years after systemic banking crisis in a group of episodes after World War II is 86 percent (Reinhart and Rogoff 2011CEPR, Figure 2, 10).

An important concept is “this time is different syndrome,” which “is rooted in the firmly-held belief that financial crises are something that happens to other people in other countries at other times; crises do not happen here and now to us” (Reinhart and Rogoff 2010FCDC, 9). There is both an arrogance and ignorance in “this time is different” syndrome, as explained by Reinhart and Rogoff (2010FCDC, 34):

“The ignorance, of course, stems from the belief that financial crises happen to other people at other time in other places. Outside a small number of experts, few people fully appreciate the universality of financial crises. The arrogance is of those who believe they have figured out how to do things better and smarter so that the boom can long continue without a crisis.”

There is sober warning by Reinhart and Rogoff (2011CEPR, 42) on the basis of the momentous effort of their scholarly data gathering, calculation and analysis:

“Despite considerable deleveraging by the private financial sector, total debt remains near its historic high in 2008. Total public sector debt during the first quarter of 2010 is 117 percent of GDP. It has only been higher during a one-year sting at 119 percent in 1945. Perhaps soaring US debt levels will not prove to be a drag on growth in the decades to come. However, if history is any guide, that is a risky proposition and over-reliance on US exceptionalism may only be one more example of the “This Time is Different” syndrome.”

As both sides of the Atlantic economy maneuver around defaults the experience on debt and growth deserves significant emphasis in research and policy. The world economy is slowing with high levels of unemployment in advanced economies. Countries do not grow themselves out of unsustainable debts but rather through de facto defaults by means of financial repression and in some cases through inflation. The conclusion is that this time is not different.

Professor Alan M. Taylor (2012) at the University of Virginia analyzes own and collaborative research on 140 years of history with data from 14 advanced economies in the effort to elucidate experience anticipating, during and after financial crises. The conclusion is (Allan M. Taylor 2012, 8):

“Recessions might be painful, but they tend to be even more painful when combined with financial crises or (worse) global crises, and we already know that post-2008 experience will not overturn this conclusion. The impact on credit is also very strong: financial crises lead to strong setbacks in the rate of growth of loans as compared to what happens in normal recessions, and this effect is strong for global crises. Finally, inflation generally falls in recessions, but the downdraft is stronger in financial crisis times.”

Alan M. Taylor (2012) also finds that advanced economies entered the global recession with the largest financial sector in history. There was doubling after 1980 of the ratio of loans to GDP and tripling of the size of bank balance sheets. In contrast, in the period from 1950 to 1970 there was high investment, savings and growth in advanced economies with firm regulation of finance and controls of foreign capital flows.

(2) Counterfactual of the Global Recession. There is a difficult decision on when to withdraw the fiscal stimulus that could have adverse consequences on current growth and employment analyzed by Krugman (2011Jun18). CBO (2011JunLTBO, Chapter 2) considers the timing of withdrawal as well as the equally tough problems that result from not taking prompt action to prevent a possible debt crisis in the future. Krugman (2011Jun18) refers to Eggertsson and Krugman (2010) on the possible contractive effects of debt. The world does not become poorer as a result of debt because an individual’s asset is another’s liability. Past levels of credit may become unacceptable by credit tightening, such as during a financial crisis. Debtors are forced into deleveraging, which results in expenditure reduction, but there may not be compensatory effects by creditors who may not be in need of increasing expenditures. The economy could be pushed toward the lower bound of zero interest rates, or liquidity trap, remaining in that threshold of deflation and high unemployment.

Analysis of debt can lead to the solution of the timing of when to cease stimulus by fiscal spending (Krugman 2011Jun18). Excessive debt caused the financial crisis and global recession and it is difficult to understand how more debt can recover the economy. Krugman (2011Jun18) argues that the level of debt is not important because one individual’s asset is another individual’s liability. The distribution of debt is important when economic agents with high debt levels are encountering different constraints than economic agents with low debt levels. The opportunity for recovery may exist in borrowing by some agents that can adjust the adverse effects of past excessive borrowing by other agents. As Krugman (2011Jun18, 20) states:

“Suppose, in particular, that the government can borrow for a while, using the borrowed money to buy useful things like infrastructure. The true social cost of these things will be very low, because the spending will be putting resources that would otherwise be unemployed to work. And government spending will also make it easier for highly indebted players to pay down their debt; if the spending is sufficiently sustained, it can bring the debtors to the point where they’re no longer so severely balance-sheet constrained, and further deficit spending is no longer required to achieve full employment. Yes, private debt will in part have been replaced by public debt – but the point is that debt will have been shifted away from severely balance-sheet-constrained players, so that the economy’s problems will have been reduced even if the overall level of debt hasn’t fallen. The bottom line, then, is that the plausible-sounding argument that debt can’t cure debt is just wrong. On the contrary, it can – and the alternative is a prolonged period of economic weakness that actually makes the debt problem harder to resolve.”

Besides operational issues, the consideration of this argument would require specifying and measuring two types of gains and losses from this policy: (1) the benefits in terms of growth and employment currently; and (2) the costs of postponing the adjustment such as in the exercise by CBO (2011JunLTO, 28-31) in Table 11. It may be easier to analyze the costs and benefits than actual measurement.

An analytical and empirical approach is followed by Blinder and Zandi (2010), using the Moody’s Analytics model of the US economy with four different scenarios: (1) baseline with all policies used; (2) counterfactual including all fiscal stimulus policies but excluding financial stimulus policies; (3) counterfactual including all financial stimulus policies but excluding fiscal stimulus; and (4) a scenario excluding all policies. The scenario excluding all policies is an important reference or the counterfactual of what would have happened if the government had been entirely inactive. A salient feature of the work by Blinder and Zandi (2010) is the consideration of both fiscal and financial policies. There was probably more activity with financial policies than with fiscal policies. Financial policies included the Fed balance sheet, 11 facilities of direct credit to illiquid segments of financial markets, interest rate policy, the Financial Stability Plan including stress tests of banks, the Troubled Asset Relief Program (TARP) and others (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 157-67; Regulation of Banks and Finance (2009a), 224-7).

Blinder and Zandi (2010, 4) find that:

“In the scenario that excludes all the extraordinary policies, the downturn con­tinues into 2011. Real GDP falls a stunning 7.4% in 2009 and another 3.7% in 2010 (see Table 3). The peak-to-trough decline in GDP is therefore close to 12%, compared to an actual decline of about 4%. By the time employment hits bottom, some 16.6 million jobs are lost in this scenario—about twice as many as actually were lost. The unemploy­ment rate peaks at 16.5%, and although not determined in this analysis, it would not be surprising if the underemployment rate approached one-fourth of the labor force. The federal budget deficit surges to over $2 trillion in fiscal year 2010, $2.6 trillion in fis­cal year 2011, and $2.25 trillion in FY 2012. Remember, this is with no policy response. With outright deflation in prices and wages in 2009-2011, this dark scenario constitutes a 1930s-like depression.”

The conclusion by Blinder and Zandi (2010) is that if the US had not taken massive fiscal and financial measures the economy could have suffered far more during a prolonged period. There are still a multitude of questions that cloud understanding of the impact of the recession and what would have happened without massive policy impulses. Some effects are quite difficult to measure. An important argument by Blinder and Zandi (2010) is that this evaluation of counterfactuals is relevant to the need of stimulus if economic conditions worsened again.

(3) Counterfactual of Policies Causing the Financial Crisis and Global Recession. The counterfactual of avoidance of deeper and more prolonged contraction by fiscal and monetary policies is not the critical issue. As Professor John B. Taylor (2012Oct25) argues the critically important counterfactual is that the financial crisis and global recessions would have not occurred in the first place if different economic policies had been followed. The counterfactual intends to verify that a combination of housing policies and discretionary monetary policies instead of rules (Taylor 1993) caused, deepened and prolonged the financial crisis (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB; see http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html) and that the experience resembles that of the Great Inflation of the 1960s and 1970s with stop-and-go growth/inflation that coined the term stagflation (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html 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 explanation of the sharp contraction of United States housing can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:

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

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

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

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

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

W = Y/r (1)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

According to Pinto (2008) in testimony to Congress:

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

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

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

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

(4) Historically Sharper Recoveries from Deeper Contractions and Financial Crises. Professor Michael D. Bordo (2012Sep27), at Rutgers University, is providing clear thought on the correct comparison of the current business cycles in the United States with those in United States history. There are two issues raised by Professor Bordo: (1) lumping together countries with different institutions, economic policies and financial systems; and (2) the conclusion that growth is mediocre after financial crises and deep recessions, which is repeated daily in the media, but that Bordo and Haubrich (2012DR) persuasively demonstrate to be inconsistent with United States experience.

Depriving economic history of institutions is perilous as is illustrated by the economic history of Brazil. Douglass C. North (1994) emphasized the key role of institutions in explaining economic history. Rondo E. Cameron (1961, 1967, 1972) applied institutional analysis to banking history. Friedman and Schwartz (1963) analyzed the relation of money, income and prices in the business cycle and related the monetary policy of an important institution, the Federal Reserve System, to the Great Depression. Bordo, Choudhri and Schwartz (1995) analyze the counterfactual of what would have been economic performance if the Fed had used during the Great Depression the Friedman (1960) monetary policy rule of constant growth of money(for analysis of the Great Depression see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 198-217). Alan Meltzer (2004, 2010a,b) analyzed the Federal Reserve System over its history. The reader would be intrigued by Figure 5 in Reinhart and Rogoff (2010FCDC, 15) in which Brazil is classified in external default for seven years between 1828 and 1834 but not again until 64 years later in 1989, above the 50 years of incidence for “serial default”. This void has been filled in scholarly research on nineteenth-century Brazil by William R. Summerhill, Jr. (2007SC, 2007IR). There are important conclusions by Summerhill on the exceptional sample of institutional change or actually lack of change, public finance and financial repression in Brazil between 1822 an 1899, combining tools of economics, political science and history. During seven continuous decades, Brazil did not miss a single interest payment with government borrowing without repudiation of debt or default. What is really surprising is that Brazil borrowed by means of long-term bonds and even more surprising interest rates fell over time. The external debt of Brazil in 1870 was ₤41,275,961 and the domestic debt in the internal market was ₤25,708,711, or 62.3 percent of the total (Summerhill 2007IR, 73).

The experience of Brazil differed from that of Latin America (Summerhill 2007IR). During the six decades when Brazil borrowed without difficulty, Latin American countries becoming independent after 1820 engaged in total defaults, suffering hardship in borrowing abroad. The countries that borrowed again fell again in default during the nineteenth century. Venezuela defaulted in four occasions. Mexico defaulted in 1827, rescheduling its debt eight different times and servicing the debt sporadically. About 44 percent of Latin America’s sovereign debt was in default in 1855 and approximately 86 percent of total government loans defaulted in London originated in Spanish American borrowing countries.

External economies of commitment to secure private rights in sovereign credit would encourage development of private financial institutions, as postulated in classic work by North and Weingast (1989), Summerhill 2007IR, 22). This is how banking institutions critical to the Industrial Revolution were developed in England (Cameron 1967). The obstacle in Brazil found by Summerhill (2007IR) is that sovereign debt credibility was combined with financial repression. There was a break in Brazil of the chain of effects from protecting public borrowing, as in North and Weingast (1989), to development of private financial institutions. According to Pelaez 1976, 283) following Cameron:

“The banking law of 1860 placed severe restrictions on two basic modern economic institutions—the corporation and the commercial bank. The growth of the volume of bank credit was one of the most significant factors of financial intermediation and economic growth in the major trading countries of the gold standard group. But Brazil placed strong restrictions on the development of banking and intermediation functions, preventing the channeling of coffee savings into domestic industry at an earlier date.”

Brazil actually abandoned the gold standard during multiple financial crises in the nineteenth century, as it should have to protect domestic economic activity. Pelaez (1975, 447) finds similar experience in the first half of nineteenth-century Brazil:

“Brazil’s experience is particularly interesting in that in the period 1808-1851 there were three types of monetary systems. Between 1808 and 1829, there was only one government-related Bank of Brazil, enjoying a perfect monopoly of banking services. No new banks were established in the 1830s after the liquidation of the Bank of Brazil in 1829. During the coffee boom in the late 1830s and 1840s, a system of banks of issue, patterned after similar institutions in the industrial countries, supplied the financial services required in the first stage of modernization of the export economy.”

Financial crises in the advanced economies were transmitted to nineteenth-century Brazil by the arrival of a ship (Pelaez and Suzigan 1981). The explanation of those crises and the economy of Brazil requires knowledge and roles of institutions, economic policies and the financial system chosen by Brazil, in agreement with Bordo (2012Sep27).

The departing theoretical framework of Bordo and Haubrich (2012DR) is the plucking model of Friedman (1964, 1988). Friedman (1988, 1) recalls “I was led to the model in the course of investigating the direction of influence between money and income. Did the common cyclical fluctuation in money and income reflect primarily the influence of money on income or of income on money?” Friedman (1964, 1988) finds useful for this purpose to analyze the relation between expansions and contractions. Analyzing the business cycle in the United States between 1870 and 1961, Friedman (1964, 15) found that “a large contraction in output tends to be followed on the average by a large business expansion; a mild contraction, by a mild expansion.” The depth of the contraction opens up more room in the movement toward full employment (Friedman 1964, 17):

“Output is viewed as bumping along the ceiling of maximum feasible output except that every now and then it is plucked down by a cyclical contraction. Given institutional rigidities and prices, the contraction takes in considerable measure the form of a decline in output. Since there is no physical limit to the decline short of zero output, the size of the decline in output can vary widely. When subsequent recovery sets in, it tends to return output to the ceiling; it cannot go beyond, so there is an upper limit to output and the amplitude of the expansion tends to be correlated with the amplitude of the contraction.”

Kim and Nelson (1999) test the asymmetric plucking model of Friedman (1964, 1988) relative to a symmetric model using reference cycles of the NBER and find evidence supporting the Friedman model. Bordo and Haubrich (2012DR) analyze 27 cycles beginning in 1872, using various measures of financial crises while considering different regulatory and monetary regimes. The revealing conclusion of Bordo and Haubrich (2012DR, 2) is that:

“Our analysis of the data shows that steep expansions tend to follow deep contractions, though this depends heavily on when the recovery is measured. In contrast to much conventional wisdom, the stylized fact that deep contractions breed strong recoveries is particularly true when there is a financial crisis. In fact, on average, it is cycles without a financial crisis that show the weakest relation between contraction depth and recovery strength. For many configurations, the evidence for a robust bounce-back is stronger for cycles with financial crises than those without.”

The average rate of growth of real GDP in expansions after recessions with financial crises was 8 percent but only 6.9 percent on average for recessions without financial crises (Bordo 2012Sep27). Real GDP declined 12 percent in the Panic of 1907 and increased 13 percent in the recovery, consistent with the plucking model of Friedman (Bordo 2012Sep27). Bordo (2012Sep27) finds two probable explanations for the weak recovery during the current economic cycles: (1) collapse of United States housing; and (2) uncertainty originating in fiscal policy, regulation and structural changes. There are serious doubts if monetary policy is adequate to recover the economy under these conditions.

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. Lucas (2011May) finds that the catch up stalled in the 1970s. The analysis of Lucas (2011May) is that the 20-40 percent gap that developed originated in differences in relative taxation and regulation that discouraged savings and work incentives in comparison with the US. A larger welfare and regulatory state, according to Lucas (2011May), could be the cause of the 20-40 percent gap. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Long-term economic growth and prosperity are measured by the key indicators of growth of real income per capita, or what is earned per person after inflation. A refined concept would include real disposable income per capita, or what is earned per person after inflation and taxes.

Table IIB-1 provides the data required for broader comparison of the cyclical expansions of IQ1983 to IVQ1985 and the current one from 2009 to 2012. First, in the 13 quarters from IQ1983 to IVQ1985, GDP increased 19.6 percent at the annual equivalent rate of 5.7 percent; real disposable personal income (RDPI) increased 14.5 percent at the annual equivalent rate of 4.3 percent; RDPI per capita increased 11.5 percent at the annual equivalent rate of 3.4 percent; and population increased 2.7 percent at the annual equivalent rate of 0.8 percent. Second, in the 13 quarters of the current cyclical expansion from IIIQ2009 to IIIQ2012, GDP increased 7.2 percent at the annual equivalent rate of 2.2 percent. In the 12 quarters of cyclical expansion real disposable personal income (RDPI) increased 5.7 percent at the annual equivalent rate of 1.7 percent; RDPI per capita increased 3.3 percent at the annual equivalent rate of 1.0 percent; and population increased 2.3 percent at the annual equivalent rate of 0.7 percent. Third, since the beginning of the recession in IVQ2007 to IIIQ2012, GDP increased 2.2 percent, or barely above the level before the recession. Since the beginning of the recession in IVQ2007 to IIIQ2012, real disposable personal income increased 3.7 percent at the annual equivalent rate of 0.7 percent; population increased 3.9 percent at the annual equivalent rate of 0.8 percent; and real disposable personal income per capita is 0.2 percent lower than the level before the recession. Real disposable personal income is the actual take home pay after inflation and taxes and real disposable income per capita is what is left per inhabitant. The current cyclical expansion is the worst in the period after World War II in terms of growth of economic activity and income. The United States grew during its history at high rates of per capita income that made its economy the largest in the world. That dynamism is disappearing. Bordo (2012 Sep27) and Bordo and Haubrich (2012DR) provide strong evidence that recoveries have been faster after deeper recessions and recessions with financial crises, casting serious doubts on the conventional explanation of weak growth during the current expansion allegedly because of the depth of the contraction from IVQ2007 to IIQ2009 of 4.7 percent and the financial crisis.

Table IIB-1, US, GDP, Real Disposable Personal Income, Real Disposable Income per Capita and Population in 1983-85 and 2007-2011, %

	# Quarters	∆%	∆% Annual Equivalent
IQ1983 to IVQ1985	13
GDP		19.6	5.7
RDPI		14.5	4.3
RDPI Per Capita		11.5	3.4
Population		2.7	0.8
IIIQ2009 to IIIQ2012	13
GDP		7.2	2.2
RDPI		5.7	1.7
RDPI per Capita		3.3	1.0
Population		2.3	0.7
IVQ2007 to IIIQ2012	20
GDP		2.2	0.4
RDPI		3.7	0.7
RDPI per Capita		-0.2
Population		3.9	0.8

RDPI: Real Disposable Personal Income

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

There are six basic facts illustrating the current economic disaster of the United States: (1) GDP maintained trend growth in the entire business cycle from IQ1980 to IV1985, including contractions and expansions, but is well below trend in the entire business cycle from IVQ2007 to IIQ2012, including contractions and expansions; (2) per capita real disposable income exceeded trend growth in the 1980s but is substantially below trend in IIQ2012; (3) the number of employed persons increased in the 1980s but declined into IIQ2012; (4) the number of full-time employed persons increased in the 1980s but declined into IIQ2012; (5) the number unemployed, unemployment rate and number employed part-time for economic reasons fell in the recovery from the recessions of the 1980s but not substantially in the recovery after IIQ2009; and (6) wealth of households and nonprofit organizations soared in the 1980s but declined into IIQ2012. There is a critical issue of whether the United States economy will be able in the future to attain again the level of activity and prosperity of projected trend growth. Growth at trend during the entire business cycles built the largest economy in the world but there may be an adverse, permanent weakness in United States economic performance and prosperity. Table IA-2 provides data for analysis of these five basic facts. The six blocks of Table IA-2 are separated initially after individual discussion of each one followed by the full Table IA-2.

1. Trend Growth.

i. As shown in Table IIB-2, actual GDP grew cumulatively 17.7 percent from IQ1980 to IVQ1985, which is relatively close to what trend growth would have been at 18.5 percent. Rapid growth at 5.7 percent annual rate on average per quarter during the expansion from IQ1983 to IVQ1985 erased the loss of GDP of 4.8 percent during the contraction and maintained trend growth at 3 percent over the entire cycle.

ii. In contrast, cumulative growth from IVQ2007 to IIIQ2012 was 2.2 percent while trend growth would have been 15.1 percent. GDP in IIIQ2012 at seasonally adjusted annual rate is estimated at $13,616.2 percent by the Bureau of Economic Analysis (BEA) (http://www.bea.gov/iTable/index_nipa.cfm) and would have been $15,338.2 billion, or $1,722 billion higher, had the economy grown at trend over the entire business cycle as it happened during the 1980s and throughout most of US history. There is $1.7 trillion of foregone GDP that would have been created as it occurred during past cyclical expansions, which explains why employment has not rebounded to even higher than before. There would not be recovery of full employment even with growth of 3 percent per year beginning immediately because the opportunity was lost to grow faster during the expansion from IIIQ2009 to IIIQ2012 after the recession from IVQ2007 to IIQ2009. The United States has acquired a heavy social burden of unemployment and underemployment of 28.1 million people or 17.4 percent of the effective labor force (Section I, Table I-4) that will not be significantly diminished even with return to growth of GDP of 3 percent per year because of growth of the labor force by new entrants. The US labor force grew from 142.583 million in 2000 to 153.124 million in 2007 or by 7.4 percent at the average yearly rate of 1.0 percent per year. The civilian noninstitutional population increased from 212.577 million in 2000 to 231.867 million in 2007 or 9.1 percent at the average yearly rate of 1.3 percent per year (data from http://www.bls.gov/data/). Data for the past five years cloud accuracy because of the number of people discouraged from seeking employment. The noninstitutional population of the United States increased from 231.867 million in 2007 to 239.618 million in 2011 or by 3.3 percent while the labor force increased from 153.124 million in 2007 to 153.617 million in 2011 or by 0.3 percent (data from http://www.bls.gov/data/). People ceased to seek jobs because they do not believe that there is a job available for them (Section I and earlier at http://cmpassocregulationblog.blogspot.com/2012/10/twenty-nine-million-unemployed-or.html).

Period IQ1980 to IVQ1985
GDP SAAR USD Billions
IQ1980	5,903.4
IVQ1985	6,950.0
∆% IQ1980 to IVQ1985	17.7
∆% Trend Growth IQ1980 to IVQ1985	18.5

Period IVQ2007 to IIIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIIQ2012	13,616.2
∆% IVQ2007 to IIIQ2012 Actual	2.2
∆% IVQ2007 to IIIQ2012 Trend	15.1

2. Decline of Per Capita Real Disposable Income

i. In the entire business cycle from IQ1980 to IVQ1985, as shown in Table IIB-2 trend growth of per capita real disposable income, or what is left per person after inflation and taxes, grew cumulatively 14.5 percent, which is close to what would have been trend growth of 12.1 percent.

ii. In contrast, in the entire business cycle from IVQ2007 to IIIQ2012, per capita real disposable income fell 0.2 percent while trend growth would have been 10.4 percent. Income available after inflation and taxes is lower than before the contraction after 13 consecutive quarters of GDP growth at mediocre rates relative to those prevailing during historical cyclical expansions.

Period IQ1980 to IVQ1985

Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD	18,938
Real Disposable Personal Income per Capita IVQ1985 Chained 2005 USD	21,687
∆% IQ1980 to IVQ1985	14.5
∆% Trend Growth	12.1

Period IVQ2007 to IIIQ2012

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIIQ2012 Chained 2005 USD	32,778
∆% IVQ2007 to IIIQ2012	-0.2
∆% Trend Growth	10.4

3. Number of Employed Persons

i. As shown in Table IIB-2, the number of employed persons increased over the entire business cycle from 98.527 million not seasonally adjusted (NSA) in IQ1980 to 107.819 million NSA in IVQ1985 or by 9.4 percent.

ii. In contrast, during the entire business cycle the number employed fell from 146.334 million in IVQ2007 to 143.202 million in IIIQ2012 or by 2.1 percent. There are 28.1 million persons unemployed or underemployed, which is 17.4 percent of the effective labor force (Section I, Table I-4).

Period IQ1980 to IVQ1985

Employed Millions IQ1980 NSA End of Quarter	98.527
Employed Millions IV1985 NSA End of Quarter	107.819
∆% Employed IQ1980 to IV1985	9.4

Period IVQ2007 to IIIQ2012

Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIIQ2012 NSA End of Quarter	143.333
∆% Employed IVQ2007 to IIIQ2012	-2.1

4. Number of Full-Time Employed Persons

i. As shown in Table IIB-2, during the entire business cycle in the 1980s, including contractions and expansion, the number of employed full-time rose from 81.280 million NSA in IQ1980 to 88.757 million NSA in IVQ1985 or 9.2 percent.

ii. In contrast, during the entire current business cycle, including contraction and expansion, the number of persons employed full-time fell from 121.042 million in IVQ2007 to 115.678 million in IIIQ2012 or by minus 4.4 percent.

Period IQ1980 to IVQ1985

Employed Full-time Millions IQ1980 NSA End of Quarter	81.280
Employed Full-time Millions IV1985 NSA End of Quarter	88.757
∆% Full-time Employed IQ1980 to IV1985	9.2

Period IVQ2007 to IIIQ2012

Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIIQ2012 NSA End of Quarter	115.678
∆% Full-time Employed IVQ2007 to IIIQ2012	-4.4

5. Unemployed, Unemployment Rate and Employed Part-time for Economic Reasons.

i. As shown in Table IIB-2 and in the following block, in the cycle from IQ1980 to IVQ1985: (a) the rate of unemployment was virtually the same at 6.7 percent in IQ1985 relative to 6.6 percent in IQ1980; (b) the number unemployed increased from 6.983 million in IQ1980 to 7.717 million in IVQ1985 or 10.5 percent; and (c) the number employed part-time for economic reasons increased 49.1 percent from 3.624 million in IQ1980 to 5.402 million in IVQ1985.

ii. In contrast, in the economic cycle from IVQ2007 to IIIQ2012: (a) the rate of unemployment increased from 4.8 percent in IVQ2007 to 7.6 percent in IIIQ2012; (b) the number unemployed increased 59.3 percent from 7.371 million in IVQ2007 to 11.742 million in IIIQ2012; (c) the number employed part-time for economic reasons increased 70.7 percent from 4.750 million in IVQ2007 to 8.110 million in IIIQ2012; and (d) U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA increased from 8.7 percent in IVQ2007 to 14.2 percent in IIIQ2012.

Period IQ1980 to IVQ1985

Unemployment Rate IQ1980 NSA End of Quarter	6.6
Unemployment Rate  IV1985 NSA End of Quarter	6.7
Unemployed IQ1980 Millions End of Quarter	6.983
Unemployed IV 1985 Millions End of Quarter	7.717
Employed Part-time Economic Reasons Millions IQ1980 End of Quarter	3.624
Employed Part-time Economic Reasons Millions IVQ1985 End of Quarter	5.402
∆%	49.1

Period IVQ2007 to IIIQ2012

Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIIQ2012 NSA End of Quarter	7.6
Unemployed IVQ2007 Millions End of Quarter	7.371
Unemployed IIIQ2009 Millions End of Quarter	11.742
∆%	59.3
Employed Part-time Economic Reasons IVQ2007 Millions End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIIQ2009 End of Quarter	8.110
∆%	70.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007	8.7
IIIQ2012	14.2

6. Wealth of Households and Nonprofit Organizations.

i. The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and also from IVQ1979) to IVQ1985 and from IVQ2007 to IIQ2012 is provided in the following block and in Table IIB-2. Net worth of households and nonprofit organizations increased from $8,326.4 billion in IVQ1979 to $14,395.2 billion in IVQ1985 or 72.9 percent or 69.3 percent from $8,502.9 billion in IQ1980. The starting quarter does not bias the results. The US consumer price index not seasonally adjusted increased from 76.7 in Dec 1979 to 109.3 in Dec 1985 or 42.5 percent or 36.5 percent from 80.1 in Mar 1980 (using consumer price index data from the US Bureau of Labor Statistics at http://www.bls.gov/cpi/data.htm). In terms of purchasing power measured by the consumer price index, real wealth of households and nonprofit organizations increased 21.3 percent in constant purchasing power from IVQ1979 to IVQ1985 or 24.0 percent from IQ1980.

ii. In contrast, as shown in the following block and in Table IIB-2, net worth of households and nonprofit organizations fell from $66,057.1 billion in IVQ2007 to $62,668.4 billion in IIQ2012 by $3,388.7 billion or 5.1 percent. The US consumer price index was 210.036 in Dec 2007 and 229.478 in Jun 2012 for increase of 9.3 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 13.2 percent in Jun 2012 after 12 consecutive quarters of expansion from IIIQ2009 to IIQ2012 relative to IVQ2012 when the recession began. The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. The average growth rate from IIIQ2009 to IIQ2012 has been 2.2 percent, which is substantially lower than the average of 6.2 percent in cyclical expansions after World War II and 5.7 percent in the expansion from IQ1983 to IVQ1985 (see Table I-5 http://cmpassocregulationblog.blogspot.com/2012/10/mediocre-and-decelerating-united-states.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions.

Period IQ1980 to IVQ1985
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ1979	8,326.4
IVQ1985	14,395.2
∆ USD Billions	+6,068.8
Period IVQ2007 to IIQ2012
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ2007	66,057.1
IIQ2012	62,668.4
∆ USD Billions	-3,388.7

Table IIB-2, US, GDP and Real Disposable Personal Income per Capita Actual and Trend Growth and Employment, 1980-1985 and 2007-2012, SAAR USD Billions, Millions of Persons and ∆%

Period IQ1980 to IVQ1985
GDP SAAR USD Billions
IQ1980	5,903.4
IVQ1985	6,950.0
∆% IQ1980 to IVQ1985	17.7
∆% Trend Growth IQ1980 to IVQ1985	18.5
Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD	18,938
Real Disposable Personal Income per Capita IVQ1985 Chained 2005 USD	21,687
∆% IQ1980 to IVQ1985	14.5
∆% Trend Growth	12.1
Employed Millions IQ1980 NSA End of Quarter	98.527
Employed Millions IV1985 NSA End of Quarter	107.819
∆% Employed IQ1980 to IV1985	9.4
Employed Full-time Millions IQ1980 NSA End of Quarter	81.280
Employed Full-time Millions IV1985 NSA End of Quarter	88.757
∆% Full-time Employed IQ1980 to IV1985	9.2
Unemployment Rate IQ1980 NSA End of Quarter	6.6
Unemployment Rate  IV1985 NSA End of Quarter	6.7
Unemployed IQ1980 Millions NSA End of Quarter	6.983
Unemployed IV 1985 Millions NSA End of Quarter	7.717
∆%	11.9
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 NSA End of Quarter	8.394
∆%	76.7
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ1979	8,326.4
IVQ1985	14,395.2
∆ USD Billions	+6,068.8
Period IVQ2007 to IIIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIIQ2012	13,616.2
∆% IVQ2007 to IIIQ2012	2.2
∆% IVQ2007 to IIIQ2012 Trend Growth	15.1
Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIIQ2012 Chained 2005 USD	32,778
∆% IVQ2007 to IIIQ2012	-0.2
∆% Trend Growth	10.4
Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIIQ2012 NSA End of Quarter	143.333
∆% Employed IVQ2007 to IIIQ2012	-2.1
Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIIQ2012 NSA End of Quarter	115.678
∆% Full-time Employed IVQ2007 to IIIQ2012	-4.4
Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIIQ2012 NSA End of Quarter	7.6
Unemployed IVQ2007 Millions NSA End of Quarter	7.371
Unemployed IIIQ2009 Millions NSA End of Quarter	11.742
∆%	59.3
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIIQ2009 NSA End of Quarter	8.110
∆%	70.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007	8.7
IIIQ2012	14.2
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ2007	66,057.1
IIQ2012	62,668.4
∆ USD Billions	-3,388.7

Note: GDP trend growth used is 3.0 percent per year and GDP per capita is 2.0 percent per year as estimated by Lucas (2011May) on data from 1870 to 2010.

Source: US Bureau of Economic Analysis http://www.bea.gov/iTable/index_nipa.cfm US Bureau of Labor Statistics http://www.bls.gov/data/. Board of Governors of the Federal Reserve System. 2012Sep20. Flow of funds accounts of the United States. Washington, DC, Federal Reserve System.

IIC Financial Repression. McKinnon (1973) and Shaw (1974) argue that legal restrictions on financial institutions can be detrimental to economic development. “Financial repression” is the term used in the economic literature for these restrictions (see Pelaez and Pelaez, Globalization and the State, Vol. II (2008b), 81-6). Interest rate ceilings on deposits and loans have been commonly used. Prohibition of payment of interest on demand deposits and ceilings on interest rates on time deposits were imposed by the Banking Act of 1933. These measures were justified by arguments that the banking panic of the 1930s was caused by competitive rates on bank deposits that led banks to engage in high-risk loans (Friedman, 1970, 18; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 74-5). The objective of policy was to prevent unsound loans in banks. Savings and loan institutions complained of unfair competition from commercial banks that led to continuing controls with the objective of directing savings toward residential construction. Friedman (1970, 15) argues that controls were passive during periods when rates implied on demand deposit were zero or lower and when Regulation Q ceilings on time deposits were above market rates on time deposits. The Great Inflation or stagflation of the 1960s and 1970s changed the relevance of Regulation Q.

Most regulatory actions trigger compensatory measures by the private sector that result in outcomes that are different from those intended by regulation (Kydland and Prescott 1977). Banks offered services to their customers and loans at rates lower than market rates to compensate for the prohibition to pay interest on demand deposits (Friedman 1970, 24). The prohibition of interest on demand deposits was eventually lifted in recent times. In the second half of the 1960s, already in the beginning of the Great Inflation (DeLong 1997), market rates rose above the ceilings of Regulation Q because of higher inflation. Nobody desires savings allocated to time or savings deposits that pay less than expected inflation. This is a fact currently with zero interest rates and consumer price inflation of 1.4 percent in the 12 months ending in Jul (http://www.bls.gov/cpi/) but rising during waves of carry trades from zero interest rates to commodity futures exposures (http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united.html). Funding problems motivated compensatory measures by banks. Money-center banks developed the large certificate of deposit (CD) to accommodate increasing volumes of loan demand by customers. As Friedman (1970, 25) finds:

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

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

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

Friedman (1970, 26-7) predicted the future:

“The banks have been forced into costly structural readjustments, the European banking system has been given an unnecessary competitive advantage, and London has been artificially strengthened as a financial center at the expense of New York.”

In short, Depression regulation exported the US financial system to London and offshore centers. What is vividly relevant currently from this experience is the argument by Friedman (1970, 27) that the controls affected the most people with lower incomes and wealth who were forced into accepting controlled-rates on their savings that were lower than those that would be obtained under freer markets. As Friedman (1970, 27) argues:

“These are the people who have the fewest alternative ways to invest their limited assets and are least sophisticated about the alternatives.”

Chart IIC-1 of the Bureau of Economic Analysis (BEA) provides quarterly savings as percent of disposable income or the US savings rate from 1980 to 2012. There was a long-term downward sloping trend from 12 percent in the early 1980s to less than 2 percent in 2005-2006. The savings rate then rose during the contraction and also in the expansion. In 2011 and into 2012 the savings rate declined as consumption is financed with savings in part because of the disincentive or frustration of receiving a few pennies for every $10,000 of deposits in a bank. The savings rate increased in the final segment of Chart IIC-1 in 2012 followed by another decline because of the pain of the opportunity cost of zero remuneration for hard-earned savings. The objective of monetary policy is to reduce borrowing rates to induce consumption but it has collateral disincentive of reducing savings and misallocating resources away from their best uses. The zero interest rate of monetary policy is a tax on saving. This tax is highly regressive, meaning that it affects the most people with lower income or wealth and retirees. The long-term decline of savings rates in the US has created a dependence on foreign savings to finance the deficits in the federal budget and the balance of payments.

Chart IIC-1, US, Personal Savings as a Percentage of Disposable Personal Income, Quarterly, 1980-2012

Source: US Bureau of Economic Analysis

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

Chart IIC-2 of the US Bureau of Economic Analysis provides personal savings as percent of personal disposable income, or savings ratio, from Jan 2007 to Aug 2012. The uncertainties caused by the global recession resulted in sharp increase in the savings ratio that peaked at 8.3 percent in May 2008 (http://www.bea.gov/iTable/index_nipa.cfm). The second highest ratio occurred at 6.7 percent in May 2009. There was another rising trend until 5.8 percent in Jun 2010 and then steady downward trend until trough of 3.2 percent in Jan 2012, which was followed by an upward trend with 4.1 percent in Jul 2012, marginally lower than 4.4 percent in Jun 2012 but decline to 3.7 percent in Aug 2012 and 3.3 percent in Sep 2012. Permanent manipulation of the entire spectrum of interest rates with monetary policy measures distorts the compass of resource allocation with inferior outcomes of future growth, employment and prosperity and dubious redistribution of income and wealth worsening the most the personal welfare of people without vast capital and financial relations to manage their savings.

Chart IIC-2, US, Personal Savings as a Percentage of Disposable Income, Monthly 2007-2012

Source: US Bureau of Economic Analysis

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

III World Financial Turbulence. Financial markets are being shocked by multiple factors including (1) world economic slowdown; (2) slowing growth in China with political development and slowing growth in Japan and world trade; (3) slow growth propelled by savings reduction in the US with high unemployment/underemployment, falling wages and hiring collapse; and (3) the outcome of the sovereign debt crisis in Europe. This section provides current data and analysis. Subsection IIIA Financial Risks provides analysis of the evolution of valuations of risk financial assets during the week. There are various appendixes for convenience of reference of material related to the euro area debt crisis. Some of this material is updated in Subsection IIIA when new data are available and then maintained in the appendixes for future reference until updated again in Subsection IIIA. Subsection IIIB Appendix on Safe Haven Currencies discusses arguments and measures of currency intervention and is available in the Appendixes section at the end of the blog comment. Subsection IIIC Appendix on Fiscal Compact provides analysis of the restructuring of the fiscal affairs of the European Union in the agreement of European leaders reached on Dec 9, 2011 and is available in the Appendixes section at the end of the blog comment. Subsection IIID Appendix on European Central Bank Large Scale Lender of Last Resort considers the policies of the European Central Bank and is available in the Appendixes section at the end of the blog comment. Appendix IIIE Euro Zone Survival Risk analyzes the threats to survival of the European Monetary Union and is available following Subsection IIIA. Subsection IIIF Appendix on Sovereign Bond Valuation provides more technical analysis and is available following Subsection IIIA. Subsection IIIG Appendix on Deficit Financing of Growth and the Debt Crisis provides analysis of proposals to finance growth with budget deficits together with experience of the economic history of Brazil and is available in the Appendixes section at the end of the blog comment.

IIIA Financial Risks. The past half year has been characterized by financial turbulence, attaining unusual magnitude in recent months. Table III-1, updated with every comment in this blog, provides beginning values on Fr Oct 26 and daily values throughout the week ending on Nov 2 of various financial assets. Section VI Valuation of Risk Financial Assets provides a set of more complete values. All data are for New York time at 5 PM. The first column provides the value on Fri Oct 26 and the percentage change in that prior week below the label of the financial risk asset. For example, the first column “Fri Oct 26, 2012”, first row “USD/EUR 1.2942 0.6 %,” provides the information that the US dollar (USD) appreciated 0.6 percent to USD 1.2942/EUR in the week ending on Fri Oct 26 relative to the exchange rate on Fri Oct 19. The first five asset rows provide five key exchange rates versus the dollar and the percentage cumulative appreciation (positive change or no sign) or depreciation (negative change or negative sign). Positive changes constitute appreciation of the relevant exchange rate and negative changes depreciation. Financial turbulence has been dominated by reactions to the new program for Greece (see section IB in http://cmpassocregulationblog.blogspot.com/2011/07/debt-and-financial-risk-aversion-and.html), modifications and new approach adopted in the Euro Summit of Oct 26 (European Commission 2011Oct26SS, 2011Oct26MRES), doubts on the larger countries in the euro zone with sovereign risks such as Spain and Italy but expanding into possibly France and Germany, the growth standstill recession and long-term unsustainable government debt in the US, worldwide deceleration of economic growth and continuing waves of inflation. The most important current shock is that resulting from the agreement by European leaders at their meeting on Dec 9 (European Council 2911Dec9), which is analyzed in IIIC Appendix on Fiscal Compact. European leaders reached a new agreement on Jan 30 (http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/127631.pdf) and another agreement on Jun 29, 2012 (http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/131388.pdf).

The dollar/euro rate is quoted as number of US dollars USD per one euro EUR, USD 1.2942/EUR in the first row, first column in the block for currencies in Table III-1 for Fri Oct 26, appreciating to USD 1.2904/EUR on Mon Oct 29, or by 0.3 percent. The dollar appreciated because fewer dollars, $1.2904, were required on Mon Oct 29 to buy one euro than $1.2942 on Oct 26. Table III-1 defines a country’s exchange rate as number of units of domestic currency per unit of foreign currency. USD/EUR would be the definition of the exchange rate of the US and the inverse [1/(USD/EUR)] is the definition in this convention of the rate of exchange of the euro zone, EUR/USD. A convention used throughout this blog is required to maintain consistency in characterizing movements of the exchange rate such as in Table III-1 as appreciation and depreciation. The first row for each of the currencies shows the exchange rate at 5 PM New York time, such as USD 1.2942/EUR on Oct 26; the second row provides the cumulative percentage appreciation or depreciation of the exchange rate from the rate on the last business day of the prior week, in this case Fri Oct 26, to the last business day of the current week, in this case Fri Nov 2, such as appreciation by 0.8 percent to USD 1.2838/EUR by Nov 2; and the third row provides the percentage change from the prior business day to the current business day. For example, the USD appreciated (denoted by positive sign) by 0.8 percent from the rate of USD 1.2904/EUR on Fri Oct 26 to the rate of USD 1.2838/EUR on Fri Nov {[(1.2838/1.2942) – 1]100 = -0.8%} and appreciated (denoted by positive sign) by 0.8 percent from the rate of USD 1.2942 on Thu Nov 1 to USD 1.2838/EUR on Fri Nov 2 {[(1.2838/1.2942) -1]100 = -0.8%}. Other factors constant, appreciation of the dollar relative to the euro is caused by increasing risk aversion, with rising uncertainty on European sovereign risks increasing dollar-denominated assets with sales of risk financial investments. Funds move away from higher yielding risk financial assets to the safety of dollar investments. When risk aversion declines, funds have been moving away from safe assets in dollars to risk financial assets, depreciating the dollar.

Table III-I, Weekly Financial Risk Assets Oct 29 to Nov 2, 2012

Fri Oct 26, 2012	M 29	Tue 30	W 31	Thu 1	Fr 2
USD/EUR 1.2942 0.6%	1.2904 0.3% 0.3%	1.2960 -0.1% -0.4%	1.2957 -0.1% 0.0%	1.2942 0.0% 0.1%	1.2838 0.8% 0.8%
JPY/  USD 79.65 -0.4%	79.81 -0.2% -0.2%	79.61 0.1% 0.3%	79.79 -0.2% -0.2%	80.15 -0.6% -0.5%	80.43 -1.0% -0.3%
CHF/  USD 0.9347 -0.7%	0.9365 -0.2% -0.2%	0.9326 0.2% 0.4%	0.9316 0.3% 0.1%	0.9320 0.3% 0.0%	0.9405 -0.6 -0.9%
CHF/ EUR 1.2096 -0.1%	1.2086 0.1% 0.1%	1.2085 0.1% 0.0%	1.2072 0.2% 0.1%	1.2062 0.3% 0.1%	1.2071 0.2% -0.1%
USD/  AUD 1.0373 0.9640 0.4%	1.0332 0.9679 -0.4% -0.4%	1.0366 0.9647 -0.1% 0.3%	1.0374 0.9639 0.0% 0.1%	1.0403 0.9613 0.3% 0.3%	1.0337 0.9674 -0.4% -0.6%
10 Year  T Note 1.748	1.72	1.72	1.69	1.72	1.715
2 Year     T Note 0.299	0.29	0.29	0.28	0.28	0.274
German Bond 2Y 0.05 10Y 1.54	2Y 0.03 10Y 1.46	2Y 0.04 10Y 1.48	2Y 0.04 10Y 1.46	2Y 0.02 10Y 1.46	2Y 0.01 10Y 1.45
DJIA 13107.21 -1.8%	13107.21 0.0% 0.0%	13107.21 0.0% 0.0%	13096.46 -0.1% -0.1%	13232.62 0.9% 1.0%	13093.16 -0.1% -1.1%
DJ Global 1915.30 -2.2%	1909.68 -0.3% -0.3%	1919.28 0.2% 0.5%	1920.16 0.3% 0.0%	1936.50 1.1% 0.9%	1932.44 0.9% -0.2%
DJ Asia Pacific 1240.25 -1.5%	1236.24 -0.3% -0.3%	1235.58 -0.4% -0.1%	1244.04 0.3% 0.7%	1242.55 0.2% -0.1%	1249.69 0.8% 0.6%
Nikkei 8993.06 -0.1%	8929.34 -0.7% -0.7%	8841.98 -1.7% -1.0%	8928.29 -0.7% 1.0%	8946.87 -0.5% 0.2%	9051.22 0.6% 1.2%
Shanghai 2066.21 -2.9%	2058.94 -0.4% -0.4%	2062.35 -0.2% 0.2%	2068.88 0.1% 0.3%	2104.43 1.8% 1.7%	2117.05 2.5% 0.6%
DAX 7231.85 -2.0%	7203.16 -0.4% -0.4%	7284.40 0.7% 1.1%	7260.63 0.4% -0.3%	7335.67 1.4% 1.0%	7363.85 1.8% 0.4%
DJ UBS Comm. 143.00 -2.3%	142.97 0.0% 0.0%	142.22 -0.5% -0.5%	142.74 -0.2% 0.4%	143.08 0.1% 0.2%	140.37 -1.8% -1.9%
WTI $ B 86.28 -4.1%	85.28 -1.2% -1.2%	85.68 -0.7% 0.5%	86.02 -0.3% 0.4%	86.92 0.7% 1.0%	84.86 -1.6% -2.4%
Brent    $/B 109.55 -0.5%	109.18 -0.3% -0.3%	109.07 -0.4% -0.1%	108.36 -1.1% -0.7%	108.17 -1.3% -0.2%	105.68 -3.5% -2.3%
Gold  $/OZ 1711.9 -0.7%	1709.9 -0.1% -0.1%	1709.5 -0.1% 0.0%	1720.5 0.5% 0.6%	1714.7 0.2% -0.3%	1675.20 -2.1% -2.3%

Note: USD: US dollar; JPY: Japanese Yen; CHF: Swiss

Franc; AUD: Australian dollar; Comm.: commodities; OZ: ounce

Sources: http://www.bloomberg.com/markets/

http://professional.wsj.com/mdc/page/marketsdata.html?mod=WSJ_hps_marketdata

Discussion of current and recent risk-determining events is followed below by analysis of risk-measuring yields of the US and Germany and the USD/EUR rate.

First, Risk-Determining Events. The European Council (2012Oct19 http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/133004.pdf ) reached conclusions on strengthening the euro area and providing unified financial supervision:

“The European Council called for work to proceed on the proposals on the Single Supervisory Mechanism as a matter of priority with the objective of agreeing on the legislative framework by 1st January 2013 and agreed on a number of orientations to that end. It also took note of issues relating to the integrated budgetary and economic policy frameworks and democratic legitimacy and accountability which should be further explored. It agreed that the process towards deeper economic and monetary union should build on the EU's institutional and legal framework and be characterised by openness and transparency towards non-euro area Member States and respect for the integrity of the Single Market. It looked forward to a specific and time-bound roadmap to be presented at its December 2012 meeting, so that it can move ahead on all essential building blocks on which a genuine EMU should be based.”

Buiter (2012Oct15) finds that resolution of the euro crisis requires full banking union together with restructuring the sovereign debt of at least four and possibly total seven European countries. The Bank of Spain released new data on doubtful debtors in Spain’s credit institutions (http://www.bde.es/bde/en/secciones/prensa/Agenda/Datos_de_credit_a6cd708c59cf931.html). In 2006, the value of doubtful credits reached €10,859 million or 0.7 percent of total credit of €1,508,626 million. In Aug 2012, doubtful credit reached €178,579 million or 10.5 percent of total credit of €1,698,714 million.

There are three critical factors influencing world financial markets. (1) Spain could request formal bailout from the European Stability Mechanism (ESM) that may also affect Italy’s international borrowing. David Roman and Jonathan House, writing on “Spain risks backlash with budget plan,” on Sep 27, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390443916104578021692765950384.html?mod=WSJ_hp_LEFTWhatsNewsCollection) analyze Spain’s proposal of reducing government expenditures by €13 billion, or around $16.7 billion, increasing taxes in 2013, establishing limits on early retirement and cutting the deficit by €65 billion through 2014. Banco de España, Bank of Spain, contracted consulting company Oliver Wyman to conduct rigorous stress tests of the resilience of its banking system. (Stress tests and their use are analyzed by Pelaez and Pelaez Globalization and the State Vol. I (2008b), 95-100, International Financial Architecture (2005) 112-6, 123-4, 130-3).) The results are available from Banco de España (http://www.bde.es/bde/en/secciones/prensa/infointeres/reestructuracion/ http://www.bde.es/f/webbde/SSICOM/20120928/informe_ow280912e.pdf). The assumptions of the adverse scenario used by Oliver Wyman are quite tough for the three-year period from 2012 to 2014: “6.5 percent cumulative decline of GDP, unemployment rising to 27.2 percent and further declines of 25 percent of house prices and 60 percent of land prices (http://www.bde.es/f/webbde/SSICOM/20120928/informe_ow280912e.pdf). Fourteen banks were stress tested with capital needs estimates of seven banks totaling €59.3 billion. The three largest banks of Spain, Banco Santander (http://www.santander.com/csgs/Satellite/CFWCSancomQP01/es_ES/Corporativo.html), BBVA (http://www.bbva.com/TLBB/tlbb/jsp/ing/home/index.jsp) and Caixabank (http://www.caixabank.com/index_en.html), with 43 percent of exposure under analysis, have excess capital of €37 billion in the adverse scenario in contradiction with theories that large, international banks are necessarily riskier. Jonathan House, writing on “Spain expects wider deficit on bank aid,” on Sep 30, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444138104578028484168511130.html?mod=WSJPRO_hpp_LEFTTopStories), analyzes the 2013 budget plan of Spain that will increase the deficit of 7.4 percent of GDP in 2012, which is above the target of 6.3 percent under commitment with the European Union. The ratio of debt to GDP will increase to 85.3 percent in 2012 and 90.5 percent in 2013 while the 27 members of the European Union have an average debt/GDP ratio of 83 percent at the end of IIQ2012. (2) Symmetric inflation targets appear to have been abandoned in favor of a self-imposed single jobs mandate of easing monetary policy even after the economy grows again at or close to potential output. Monetary easing by unconventional measures is now apparently open ended in perpetuity as provided in the statement of the meeting of the Federal Open Market Committee (FOMC) on Sep 13, 2012 (http://www.federalreserve.gov/newsevents/press/monetary/20120913a.htm):

“To support a stronger economic recovery and to help ensure that inflation, over time, is at the rate most consistent with its dual mandate, the Committee agreed today to increase policy accommodation by purchasing additional agency mortgage-backed securities at a pace of $40 billion per month. The Committee also will continue through the end of the year its program to extend the average maturity of its holdings of securities as announced in June, and it is maintaining its existing policy of reinvesting principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities. These actions, which together will increase the Committee’s holdings of longer-term securities by about $85 billion each month through the end of the year, should put downward pressure on longer-term interest rates, support mortgage markets, and help to make broader financial conditions more accommodative.

To support continued progress toward maximum employment and price stability, the Committee expects that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the economic recovery strengthens.”

In fact, it is evident to the public that this policy will be abandoned if inflation costs rise. There is the concern of the production and employment costs of controlling future inflation.

(2) The European Central Bank (ECB) approved a new program of bond purchases under the name “Outright Monetary Transactions” (OMT). The ECB will purchase sovereign bonds of euro zone member countries that have a program of conditionality under the European Financial Stability Facility (EFSF) that is converting into the European Stability Mechanism (ESM). These programs provide enhancing the solvency of member countries in a transition period of structural reforms and fiscal adjustment. The purchase of bonds by the ECB would maintain debt costs of sovereigns at sufficiently low levels to permit adjustment under the EFSF/ESM programs. Purchases of bonds are not limited quantitatively with discretion by the ECB as to how much is necessary to support countries with adjustment programs. Another feature of the OMT of the ECB is sterilization of bond purchases: funds injected to pay for the bonds would be withdrawn or sterilized by ECB transactions. The statement by the European Central Bank on the program of OTM is as follows (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html):

“6 September 2012 - Technical features of Outright Monetary Transactions

As announced on 2 August 2012, the Governing Council of the European Central Bank (ECB) has today taken decisions on a number of technical features regarding the Eurosystem’s outright transactions in secondary sovereign bond markets that aim at safeguarding an appropriate monetary policy transmission and the singleness of the monetary policy. These will be known as Outright Monetary Transactions (OMTs) and will be conducted within the following framework:

Conditionality

A necessary condition for Outright Monetary Transactions is strict and effective conditionality attached to an appropriate European Financial Stability Facility/European Stability Mechanism (EFSF/ESM) programme. Such programmes can take the form of a full EFSF/ESM macroeconomic adjustment programme or a precautionary programme (Enhanced Conditions Credit Line), provided that they include the possibility of EFSF/ESM primary market purchases. The involvement of the IMF shall also be sought for the design of the country-specific conditionality and the monitoring of such a programme.

The Governing Council will consider Outright Monetary Transactions to the extent that they are warranted from a monetary policy perspective as long as programme conditionality is fully respected, and terminate them once their objectives are achieved or when there is non-compliance with the macroeconomic adjustment or precautionary programme.

Following a thorough assessment, the Governing Council will decide on the start, continuation and suspension of Outright Monetary Transactions in full discretion and acting in accordance with its monetary policy mandate.

Coverage

Outright Monetary Transactions will be considered for future cases of EFSF/ESM macroeconomic adjustment programmes or precautionary programmes as specified above. They may also be considered for Member States currently under a macroeconomic adjustment programme when they will be regaining bond market access.

Transactions will be focused on the shorter part of the yield curve, and in particular on sovereign bonds with a maturity of between one and three years.

No ex ante quantitative limits are set on the size of Outright Monetary Transactions.

Creditor treatment

The Eurosystem intends to clarify in the legal act concerning Outright Monetary Transactions that it accepts the same (pari passu) treatment as private or other creditors with respect to bonds issued by euro area countries and purchased by the Eurosystem through Outright Monetary Transactions, in accordance with the terms of such bonds.

Sterilisation

The liquidity created through Outright Monetary Transactions will be fully sterilised.

Transparency

Aggregate Outright Monetary Transaction holdings and their market values will be published on a weekly basis. Publication of the average duration of Outright Monetary Transaction holdings and the breakdown by country will take place on a monthly basis.

Securities Markets Programme

Following today’s decision on Outright Monetary Transactions, the Securities Markets Programme (SMP) is herewith terminated. The liquidity injected through the SMP will continue to be absorbed as in the past, and the existing securities in the SMP portfolio will be held to maturity.”

Jon Hilsenrath, writing on “Fed sets stage for stimulus,” on Aug 31, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390443864204577623220212805132.html?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes the essay presented by Chairman Bernanke at the Jackson Hole meeting of central bankers, as defending past stimulus with unconventional measures of monetary policy that could be used to reduce extremely high unemployment. Chairman Bernanke (2012JHAug31, 18-9) does support further unconventional monetary policy impulses if required by economic conditions (http://www.federalreserve.gov/newsevents/speech/bernanke20120831a.htm):

“Over the past five years, the Federal Reserve has acted to support economic growth and foster job creation, and it is important to achieve further progress, particularly in the labor market. Taking due account of the uncertainties and limits of its policy tools, the Federal Reserve will provide additional policy accommodation as needed to promote a stronger economic recovery and sustained improvement in labor market conditions in a context of price stability.”

Professor John H Cochrane (2012Aug31), at the University of Chicago Booth School of Business, writing on “The Federal Reserve: from central bank to central planner,” on Aug 31, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444812704577609384030304936.html?mod=WSJ_hps_sections_opinion), analyzes that the departure of central banks from open market operations into purchase of assets with risks to taxpayers and direct allocation of credit subject to political influence has caused them to abandon their political independence and accountability. Cochrane (2012Aug31) finds a return to the proposition of Milton Friedman in the 1960s that central banks can cause inflation and macroeconomic instability.

Mario Draghi (2012Aug29), President of the European Central Bank, also reiterated the need of exceptional and unconventional central bank policies (http://www.ecb.int/press/key/date/2012/html/sp120829.en.html):

“Yet it should be understood that fulfilling our mandate sometimes requires us to go beyond standard monetary policy tools. When markets are fragmented or influenced by irrational fears, our monetary policy signals do not reach citizens evenly across the euro area. We have to fix such blockages to ensure a single monetary policy and therefore price stability for all euro area citizens. This may at times require exceptional measures. But this is our responsibility as the central bank of the euro area as a whole.

The ECB is not a political institution. But it is committed to its responsibilities as an institution of the European Union. As such, we never lose sight of our mission to guarantee a strong and stable currency. The banknotes that we issue bear the European flag and are a powerful symbol of European identity.”

Buiter (2011Oct31) analyzes that the European Financial Stability Fund (EFSF) would need a “bigger bazooka” to bail out euro members in difficulties that could possibly be provided by the ECB. Buiter (2012Oct15) finds that resolution of the euro crisis requires full banking union together with restructuring the sovereign debt of at least four and possibly total seven European countries. Table III-7 in IIIE Appendix Euro Zone Survival Risk below provides the combined GDP in 2012 of the highly indebted euro zone members estimated in the latest World Economic Outlook of the IMF at $4167 billion or 33.1 percent of total euro zone GDP of $12,586 billion. Using the WEO of the IMF, Table III-8 in IIIE Appendix Euro Zone Survival Risk below provides debt of the highly indebted euro zone members at $3927.8 billion in 2012 that increases to $5809.9 billion when adding Germany’s debt, corresponding to 167.0 percent of Germany’s GDP. There are additional sources of debt in bailing out banks. The dimensions of the problem may require more firepower than a bazooka perhaps that of the largest conventional bomb of all times of 44,000 pounds experimentally detonated only once by the US in 1948 (http://www.airpower.au.af.mil/airchronicles/aureview/1967/mar-apr/coker.html).

Second, Risk-Measuring Yields and Exchange Rate. The ten-year government bond of Spain was quoted at 6.868 percent on Aug 10, declining to 6.447 percent on Aug 17 and 6.403 percent on Aug 24, and the ten-year government bond of Italy fell from 5.894 percent on Aug 10 to 5.709 percent on Aug 17 and 5.618 percent on Aug 24. On Aug 31, the yield of the 10-year sovereign bond of Italy rose to 5.787 percent and that of Spain to 6.832 percent. The announcement of the OMT of bond-buying by the ECB together with weak employment creation in the US created risk appetite with the yield of the ten-year government bond of Spain collapsing to 5.708 percent on Sep 7 and the yield of the ten-year government bond of Italy to 5.008 percent (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata). The yield of the ten-year government bond of Spain traded at 5.770 percent on Sep 14 and at 5.739 percent on Sep 21 and ten-year government of Italy traded at 4.953 percent on Sep 14 and 4.982 on Sep 21. The imminence of a bailout of Spain drove the yield of the ten-year sovereign bond of Spain to 5.979 percent on Fri Sep 28 and that of Italy to 5.031 percent but both traded higher during the day. Sovereign yields continued to decline by Oct 5 with the yield of the ten-year sovereign bond of Spain trading at 5.663 percent and that of Italy at 4.922 percent. On Oct 12, 2012, the yield of the ten-year sovereign bond of Spain traded at 5.612 percent and that of Italy at 4.856 percent. Sovereign bonds continued to decline in the week of Oct 19 with the ten-year government bond Spain trading at 5.289 percent and that of Italy at 4.655 percent. On Oct 26, the yield of the ten-year government bond of Spain traded at 5.574 percent and that of Italy at 4.838 percent. On Nov 2, the ten-year government bond of Spain traded at 5.649 percent and that of Italy at 4.879 percent. Risk aversion is captured by flight of investors from risk financial assets to the government securities of the US and Germany. Diminishing aversion is captured by increase of the yield of the two- and ten-year Treasury notes and the two- and ten-year government bonds of Germany. Table III-1A provides yields of US and German governments bonds and the rate of USD/EUR. Yields of US and German government bonds decline during shocks of risk aversion and the dollar strengthens in the form of fewer dollars required to buy one euro. The yield of the US ten-year Treasury note fell from 2.202 percent on Aug 26, 2011 to 1.459 percent on Jul 20, 2012, reminiscent of experience during the Treasury-Fed accord of the 1940s that placed a ceiling on long-term Treasury debt (Hetzel and Leach 2001), while the yield of the ten-year government bond of Germany fell from 2.16 percent to 1.17 percent. Under increasing risk appetite, the yield of the ten-year Treasury rose to 1.544 on Jul 27, 2012 and 1.569 percent on Aug 3, 2012, while the yield of the ten-year Government bond of Germany rose to 1.40 percent on Jul 27 and 1.42 percent on Aug 3. Yields moved on an increasing trend with the US ten-year note at 1.814 percent on Aug 17 and the German ten-year bond at 1.50 percent with sharp decline on Aug 24 to 1.684 percent for the yield of the US ten-year note and 1.35 for the yield of the German ten-year bond. The trend was interrupted with decline of the yield of the ten-year Treasury note to 1.543 percent on Aug 31, 2012, and of the ten-year German bond to 1.33 percent. The US dollar strengthened significantly from USD 1.450/EUR on Aug 26, 2011, to USD 1.2158 on Jul 20, 2012, or by 16.2 percent, but depreciated to USD 1.2320/EUR on Jul 27, 2012 and 1.2387 on Aug 3, 2012 in expectation of massive support of highly indebted euro zone members. Doubts returned at the end of the week of Aug 10, 2012 with appreciation to USD 1.2290/EUR and decline of the yields of the two-year government bond of Germany to -0.07 percent and of the ten-year to 1.38 percent. On Aug 17, the US dollar depreciated by 0.4 percent to USD 1.2335/EUR and the ten-year bond of Germany yielded -0.04 percent. Risk appetite returned in the week of Aug 24 with depreciation by 1.4 percent to USD 1.2512/EUR and lower yield of the German two-year bond to -0.01 percent and of the US two-year note to 0.266 percent. Further risk aversion is captured by decline of yield of the two-year Treasury note to 0.225 percent on Aug 31, 2012, and to -0.03 percent for the two-year sovereign bond of Germany while the USD moved in opposite direction, depreciating to USD 1.2575/EUR. The almost simultaneous announcement of the bond-buying OMT of the ECB on Sep 6 and the weak employment report on Sep 7 suggesting further easing by the FOMC caused risk appetite shown by the increase in yields of government bonds of the US on Sep 7 to 1.668 percent for the ten-year note and 0.252 percent for the two-year while the two-year yield of Germany rose from -0.03 percent to 0.03 percent and the ten-year yield from 1.33 percent to 1.52 percent. Risk aversion retreated again on Sep 14, 2012 because of the open-ended monetary policy of the FOMC with the dollar devaluing to USD 1.3130 and the ten-year yield of the US Treasury note increasing to 1.863 percent (also in part because of bond buying by the Fed at shorter maturities) and the yield of the ten-year German bond increasing to 1.71 percent. Risk aversions returned because of weak flash purchasing managers indices with appreciation to USD1.2981 in the week of Sep 21 and declines of the yield of the ten-year Treasury note to 1.753 percent and of the yield of the ten-year government bond to 1.60 percent. Risk aversion because of the potential bailout of Spain drove down the US ten-year yield to 1.631 and the ten-year yield of Germany to 1.44 percent while the dollar appreciated to USD 1.2859/EUR. Increasing risk appetite drove the yield of the ten-year Treasury to 1.737 percent on Oct 5, 2012 and depreciated the dollar to USD 1.3036 with more muted response in the yield of the ten-year bond of Germany rising to 1.52 percent and the two-year yield to 0.06 percent. There is indication of some risk aversion in the week of Oct 12, 2012, with decline of the yield of the ten-year Treasury to 1.663 percent and that of Germany to 1.45 percent, stability of the two-year Treasury yield at 0.264 percent and marginal decline of the yield of the two-year German bond to 0.04 percent while the dollar appreciated to USD 1.2953/EUR. Risk aversion fluctuated in the week of Oct 19 but the week ended with the increase of the yield of the two-year note of the US to 0.296 percent and of the ten-year note to 1.766 percent; there was similar increase of the yield of the two-year government bond of Germany to 0.11 percent and of the ten-year yield to 1.59 percent; and the dollar depreciated 0.5 percent to USD 1.3023 percent. Mild risk aversion returned in the week of Oct 26, with the 10-year Treasury yield declining marginally to 1.748 percent and that of Germany to 1.54 percent while the dollar appreciated to USD 1.2942/EUR. Mild risk aversion continued in the week of Nov 2 with declines in the yield of the ten-year Treasury note to 1.715 percent and of the ten-year government bond of Germany to 1.45 percent while the dollar appreciated to USD 1.2838/EUR. Under zero interest rates for the monetary policy rate of the US, or fed funds rate, carry trades ensure devaluation of the dollar if there is no risk aversion but the dollar appreciates in flight to safe haven during episodes of risk aversion. Unconventional monetary policy induces significant global financial instability, excessive risks and low liquidity. The ten-year Treasury yield is below consumer price inflation of 2.0 percent in the 12 months ending in Sep (see http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html) and the expectation of higher inflation if risk aversion diminishes. Treasury securities continue to be safe haven for investors fearing risk but with concentration in shorter maturities such as the two-year Treasury. The lower part of Table III-1A provides the same flight to government securities of the US and Germany and the USD during the financial crisis and global recession and the beginning of the European debt crisis in the spring of 2010 with the USD trading at USD 1.192/EUR on Jun 7, 2010.

Table III-1A, Two- and Ten-Year Yields of Government Bonds of the US and Germany and US Dollar/EUR Exchange rate

	US 2Y	US 10Y	DE 2Y	DE 10Y	USD/ EUR
11/02/12	0.274	1.715	0.01	1.45	1.2838
10/26/12	0.299	1.748	0.05	1.54	1.2942
10/19/12	0.296	1.766	0.11	1.59	1.3023
10/12/12	0.264	1.663	0.04	1.45	1.2953
10/5/12	0.26	1.737	0.06	1.52	1.3036
9/28/12	0.236	1.631	0.02	1.44	1.2859
9/21/12	0.26	1.753	0.04	1.60	1.2981
9/14/12	0.252	1.863	0.10	1.71	1.3130
9/7/12	0.252	1.668	0.03	1.52	1.2816
8/31/12	0.225	1.543	-0.03	1.33	1.2575
8/24/12	0.266	1.684	-0.01	1.35	1.2512
8/17/12	0.288	1.814	-0.04	1.50	1.2335
8/10/12	0.267	1.658	-0.07	1.38	1.2290
8/3/12	0.242	1.569	-0.02	1.42	1.2387
7/27/12	0.244	1.544	-0.03	1.40	1.2320
7/20/12	0.207	1.459	-0.07	1.17	1.2158
7/13/12	0.24	1.49	-0.04	1.26	1.2248
7/6/12	0.272	1.548	-0.01	1.33	1.2288
6/29/12	0.305	1.648	0.12	1.58	1.2661
6/22/12	0.309	1.676	0.14	1.58	1.2570
6/15/12	0.272	1.584	0.07	1.44	1.2640
6/8/12	0.268	1.635	0.04	1.33	1.2517
6/1/12	0.248	1.454	0.01	1.17	1.2435
5/25/12	0.291	1.738	0.05	1.37	1.2518
5/18/12	0.292	1.714	0.05	1.43	1.2780
5/11/12	0.248	1.845	0.09	1.52	1.2917
5/4/12	0.256	1.876	0.08	1.58	1.3084
4/6/12	0.31	2.058	0.14	1.74	1.3096
3/30/12	0.335	2.214	0.21	1.79	1.3340
3/2/12	0.29	1.977	0.16	1.80	1.3190
2/24/12	0.307	1.977	0.24	1.88	1.3449
1/6/12	0.256	1.957	0.17	1.85	1.2720
12/30/11	0.239	1.871	0.14	1.83	1.2944
8/26/11	0.20	2.202	0.65	2.16	1.450
8/19/11	0.192	2.066	0.65	2.11	1.4390
6/7/10	0.74	3.17	0.49	2.56	1.192
3/5/09	0.89	2.83	1.19	3.01	1.254
12/17/08	0.73	2.20	1.94	3.00	1.442
10/27/08	1.57	3.79	2.61	3.76	1.246
7/14/08	2.47	3.88	4.38	4.40	1.5914
6/26/03	1.41	3.55	NA	3.62	1.1423

Note: DE: Germany

Source:

http://www.bloomberg.com/markets/

http://professional.wsj.com/mdc/page/marketsdata.html?mod=WSJ_hps_marketdata

http://www.federalreserve.gov/releases/h15/data.htm

http://www.bundesbank.de/Navigation/EN/Statistics/Time_series_databases/Macro_economic_time_series/macro_economic_time_series_node.html?anker=GELDZINS

http://www.ecb.int/stats/money/long/html/index.en.html

Chart III-1A of the Board of Governors of the Federal Reserve System provides the ten-year and two-year Treasury constant maturity yields. The combination of zero fed funds rate and quantitative easing caused sharp decline of the yields from 2008 and 2009. Yield declines have also occurred during periods of financial risk aversion, including the current one of stress of financial markets in Europe.

Chart III-1A, US, Ten-Year and Two-Year Treasury Constant Maturity Yields Jul 31, 2001-Nov 1, 2012

Note: US Recessions in shaded areas

Source: Board of Governors of the Federal Reserve System

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

http://www.ecb.int/press/pr/wfs/2012/html/fs121030.en.html

Kate Linebaugh, writing on “Falling revenue dings stocks,” on Oct 20, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10000872396390444592704578066933466076070.html?mod=WSJPRO_hpp_LEFTTopStories), identifies a key financial vulnerability: falling revenues across markets for United States reporting companies. Global economic slowdown is reducing corporate sales and squeezing corporate strategies. Linebaugh quotes data from Thomson Reuters that 100 companies of the S&P 500 index have reported declining revenue only 1 percent higher in Jun-Sep 2012 relative to Jun-Sep 2011 but about 60 percent of the companies are reporting lower sales than expected by analysts with expectation that revenue for the S&P 500 will be lower in Jun-Sep 2012 for the entities represented in the index. Results of US companies are likely repeated worldwide. The basic valuation equation that is also used in capital budgeting postulates that the value of stocks or of an investment project is given by:

Where is expected revenue in the time horizon from τ =1 to T; denotes costs; and ρ is an appropriate rate of discount. In words, the value today of a stock or investment project is the net revenue, or revenue less costs, in the investment period from τ =1 to T discounted to the present by an appropriate rate of discount. In the current weak economy, revenues have been increasing more slowly than anticipated in investment plans. An increase in interest rates would affect discount rates used in calculations of present value, resulting in frustration of investment decisions. If V represents value of the stock or investment project, as ρ → ∞, meaning that interest rates increase without bound, then V → 0, or

declines.

Equity indexes in Table III-1 were mixed in the week ending on Nov 2, 2012. Stagnating revenues are causing reevaluation of discounted net earnings. DJIA dropped 1.1 percent on Nov 2, declining 0.1 percent in the week with trading interrupted on Mon and Tue by hurricane Sandy. Germany’s Dax increased 0.4 percent on Fri Nov 2 and increased 1.8 percent in the week. Dow Global decreased 0.2 percent on Nov 2 and lost 0.9 percent in the week. Japan’s Nikkei Average increased 1.2 percent on Fri Nov 2 and increased 0.6 percent in the week. Dow Asia Pacific TSM decreased 0.9 percent on Oct 26 and decreased 1.5 percent in the week while Shanghai Composite increased 0.6 percent on Nov 2 and increased 0.8 percent in the week. There is evident trend of deceleration of the world economy that could affect corporate revenue and equity valuations.

Commodities were mostly weak in the week of Nov 2, 2012. The DJ UBS Commodities Index decreased 1.9 percent on Fri Nov 2 and decreased 1.8 percent in the week, as shown in Table III-1. WTI decreased 1.6 percent in the week of Nov 2 while Brent decreased 3.5 percent in the week. Gold decreased 2.3 percent on Fri Nov 2 and decreased 2.1 percent in the week.

Table III-2 provides an update of the consolidated financial statement of the Eurosystem. The balance sheet has swollen with the long-term refinancing operations (LTROs). Line 5 “Lending to Euro Area Credit Institutions Related to Monetary Policy” increased from €546,747 million on Dec 31, 2010, to €879,130 million on Dec 28, 2011 and €1,135.148 million on Oct 26, 2012. The sum of line 5 and line 7 (“Securities of Euro Area Residents Denominated in Euro”) has increased to €1,726,881 million in the statement of Oct 26. There is high credit risk in these transactions with capital of only €85,551 million as analyzed by Cochrane (2012Aug31).

Table III-2, Consolidated Financial Statement of the Eurosystem, Million EUR

	Dec 31, 2010	Dec 28, 2011	Oct 26, 2012
1 Gold and other Receivables	367,402	419,822	479,107
2 Claims on Non Euro Area Residents Denominated in Foreign Currency	223,995	236,826	260,111
3 Claims on Euro Area Residents Denominated in Foreign Currency	26,941	95,355	38,289
4 Claims on Non-Euro Area Residents Denominated in Euro	22,592	25,982	17,268
5 Lending to Euro Area Credit Institutions Related to Monetary Policy Operations Denominated in Euro	546,747	879,130	1,135,148
6 Other Claims on Euro Area Credit Institutions Denominated in Euro	45,654	94,989	230,744
7 Securities of Euro Area Residents Denominated in Euro	457,427	610,629	591,733
8 General Government Debt Denominated in Euro	34,954	33,928	30,010
9 Other Assets	278,719	336,574	264,132
TOTAL ASSETS	2,004, 432	2,733,235	3,046,543
Memo Items
Sum of 5 and  7	1,004,174	1,489,759	1,726,881
Capital and Reserves	78,143	85,748	85,551

Source: European Central Bank

http://www.ecb.int/press/pr/wfs/2011/html/fs110105.en.html

http://www.ecb.int/press/pr/wfs/2011/html/fs111228.en.html

http://www.ecb.int/press/pr/wfs/2012/html/fs121030.en.html

© Carlos M. Pelaez, 2010, 2011, 2012