Sunday, May 12, 2013

Recovery without Hiring, Collapse of United States Dynamism of Income Growth and Employment Creation, Peaking Valuations of Risk Financial Assets, World Economic Slowdown and Global Recession Risk: Part I

 

Recovery without Hiring, Collapse of United States Dynamism of Income Growth and Employment Creation, Peaking Valuations of Risk Financial Assets, World Economic Slowdown and Global Recession Risk

Carlos M. Pelaez

© Carlos M. Pelaez, 2010, 2011, 2012, 2013

Executive Summary

I Recovery without Hiring

IA1 Hiring Collapse

IA2 Labor Underutilization

IA3 Ten Million Fewer Full-time Job

IA4 Youth and Middle-Aged Unemployment

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

II United States International Trade

IIA1 United States International Trade

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

IIID Appendix on European Central Bank Large Scale Lender of Last Resort

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during the Debt Crisis of the 1980s

Executive Summary

ESI 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 IVQ2012: (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; Pelaez 1979, 26-8). 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 preceding, 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 of skills of the relationship banker converts 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 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. Congress established the Federal Home Loan Bank (FHLB) system 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 Germany. 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”. William R. Summerhill, Jr. (2007SC, 2007IR) has filled this void in scholarly research on nineteenth-century Brazil. 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 and 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 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 [Cameron 1967], 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 cycle: (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 IB-1 provides the data required for broader comparison of the cyclical expansions of IQ1983 to IIIQ1986 and the current one from 2009 to 2012. First, in the 13 quarters from IQ1983 to IQ1986: GDP increased 19.6 percent at the annual equivalent rate of 5.7 percent; real disposable personal income (RDPI) increased 14.9 percent at the annual equivalent rate of 4.4 percent; RDPI per capita increased 11.9 percent at the annual equivalent rate of 3.5 percent; and population increased 2.7 percent at the annual equivalent rate of 0.8 percent. In the 15 quarters from IQ1983 to IQ1II986: GDP increased 21.3 percent at the annual equivalent rate of 5.3 percent; real disposable personal income (RDPI) increased 16.9 percent at the annual equivalent rate of 4.2 percent; RDPI per capita increased 13.3 percent at the annual equivalent rate of 3.4 percent; and population increased 3.2 percent at the annual equivalent rate of 0.8 percent Second, in the 15 quarters of the current cyclical expansion from IIIQ2009 to IQ2013, GDP increased 8.3 percent at the annual equivalent rate of 2.1 percent. In the 15 quarters of cyclical expansion: real disposable personal income (RDPI) increased 5.6 percent at the annual equivalent rate of 1.5 percent; RDPI per capita increased 2.9 percent at the annual equivalent rate of 0.8 percent; and population increased 2.6 percent at the annual equivalent rate of 0.7 percent. Third, since the beginning of the recession in IVQ2007 to IQ2013, GDP increased 3.2 percent, or barely above the level before the recession. Since the beginning of the recession in IVQ2007 to IQ2013, real disposable personal income increased 5.0 percent at the annual equivalent rate of 0.9 percent; population increased 4.2 percent at the annual equivalent rate of 0.8 percent; and real disposable personal income per capita is 0.6 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 IB-1, US, GDP, Real Disposable Personal Income, Real Disposable Income per Capita and Population in 1983-85 and 2007-2012, %

 

# Quarters

∆%

∆% Annual Equivalent

IQ1983 to IQ1986

IQ1983 to IIIQ1986

13

15

   

GDP

IQ1983 to IVQ1985

IQ1983 to IIIQ1986

13

15

19.6

21.3

5.7

5.3

RDPI

IQ1983 to IQ1986

IQ1983 to IIIQ1986

13

15

14.9

16.9

4.4

4.2

RDPI Per Capita

IQ1983 to IVQ1986

IQ1983 to IIIQ1986

13

15

11.9

13.3

3.5

3.4

Population

IQ1983 to IQ1986

IQ1983 to IIIQ1986

13

15

2.7

3.2

0.8

0.8

IIIQ2009 to IQ2013

15

   

GDP

 

8.3

2.1

RDPI

 

5.6

1.5

RDPI per Capita

 

2.9

0.8

Population

 

2.6

0.7

IVQ2007 to IQ2013

22

   

GDP

 

3.2

0.6

RDPI

 

5.0

0.9

RDPI per Capita

 

-0.6

NA

Population

 

4.2

0.8

RDPI: Real Disposable Personal Income

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

There are seven 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 and IIIQ1986, including contractions and expansions, but is well below trend in the entire business cycle from IVQ2007 to IQ2013, including contractions and expansions; (2) per capita real disposable income exceeded trend growth in the 1980s but is substantially below trend in IQ2013; (3) the number of employed persons increased in the 1980s but declined into IQ2013; (4) the number of full-time employed persons increased in the 1980s but declined into IQ2013; (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; (6) wealth of households and nonprofit organizations soared in the 1980s but declined in real terms into IVQ2012; and (7) gross private domestic investment increased sharply from IQ1980 to IVQ1985 and IIIQ1986 but gross private domestic investment and private fixed investment have fallen sharply from IVQ2007 to IQ2013. 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 IB-2 provides data for analysis of these seven basic facts. The seven blocks of Table IB-2 are separated initially after individual discussion of each one followed by the full Table IB-2.

1. Trend Growth.

i. As shown in Table IB-2, actual GDP grew cumulatively 20.5 percent from IQ1980 to IIIQ1986, which is relatively close to what trend growth would have been at 22.9 percent. Rapid growth at 5.7 percent annual rate on average per quarter during the expansion from IQ1983 to IQ1986 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 IQ2013 was 3.2 percent while trend growth would have been 17.7 percent. GDP in IQ2013 at seasonally adjusted annual rate is estimated at $13,750.1 billion by the Bureau of Economic Analysis (BEA) (http://www.bea.gov/iTable/index_nipa.cfm) and would have been $15,684.7 billion, or $1,935 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 $1.9 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 IQ2013 after the recession from IVQ2007 to IIQ2009. The United States has acquired a heavy social burden of unemployment and underemployment of 28.6 million people or 17.6 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html) 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 243.284 million in 2012 or by 4.9 percent while the labor force increased from 153.124 million in 2007 to 154.975 million in 2012 or by 1.2 percent and only by 0.3 percent to 153.617 million in 2011 while population increased 3.3 percent from 231.867 million in 2007 to 239.618 million in 2011 (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 (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html). Structural change in demography occurs over relatively long periods and not suddenly as shown by Edward P. Lazear and James R. Spletzer (2012JHJul22).

Period IQ1980 to IIIQ1986

 

GDP SAAR USD Billions

 

    IQ1980

5,903.4

    IIIQ1986

7,112.9

∆% IQ1980 to IIIQ1986 (21.3 percent from IVQ1982 $5866.0 billion)

20.5

∆% Trend Growth IQ1980 to IIIQ1986

22.9

Period IVQ2007 to IQ2013

 

GDP SAAR USD Billions

 

    IVQ2007

13,326.0

    IVQ2012

13,750.1

∆% IVQ2007 to IVQ2012 Actual

3.2

∆% IVQ2007 to IQ2013 Trend

17.7

2. Decline of Per Capita Real Disposable Income

i. In the entire business cycle from IQ1980 to IIIQ1986, as shown in Table IB-2 trend growth of per capita real disposable income, or what is left per person after inflation and taxes, grew cumulatively 17.0 percent, which is close to what would have been trend growth of 14.9 percent.

ii. In contrast, in the entire business cycle from IVQ2007 to IQ2013, per capita real disposable income fell 0.6 percent while trend growth would have been 11.5 percent. Income available after inflation and taxes is about the same or lower as before the contraction after 15 consecutive quarters of GDP growth at mediocre rates relative to those prevailing during historical cyclical expansions. In IQ2013, personal income fell at the SAAR of minus 3.2 percent; real personal income excluding current transfer receipts at minus 5.8 percent; and real disposable personal income at minus 5.3 percent (Table 5 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf). The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

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

Period IQ1980 to IIIQ1986

 

Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD

18,938

Real Disposable Personal Income per Capita IQ1II986 Chained 2005 USD

22,165

∆% IQ1980 to IIIQ1986

17.0

∆% Trend Growth

14.9

Period IVQ2007 to IQ2013

 

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD

32,837

Real Disposable Personal Income per Capita IQ2013 Chained 2005 USD

32,640

∆% IVQ2007 to IQ2013

-0.6

∆% Trend Growth

11.5

3. Number of Employed Persons

i. As shown in Table IB-2, the number of employed persons increased over the entire business cycle from 98.527 million not seasonally adjusted (NSA) in IQ1980 to 110.229 million NSA in IIIQ1986 or by 11.9 percent.

ii. In contrast, during the entire business cycle the number employed fell from 146.334 million in IVQ2007 to 142.698 million in IQ2013 or by 2.5 percent. There are 28.6 million persons unemployed or underemployed, which is 17.6 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html).

Period IQ1980 to IIIQ1986

 

Employed Millions IQ1980 NSA End of Quarter

98.527

Employed Millions IIIQ1986 NSA End of Quarter

110.229

∆% Employed IQ1980 to IIIQ1986

11.9

Period IVQ2007 to IQ2013

 

Employed Millions IVQ2007 NSA End of Quarter

146.334

Employed Millions IQ2013 NSA End of Quarter

142.698

∆% Employed IVQ2007 to IQ2013

-2.5

4. Number of Full-Time Employed Persons

i. As shown in Table IB-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 91.579 million NSA in IIIQ1986 or 12.7 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 114.796 million in IQ2013 or by minus 5.2 percent.

Period IQ1980 to IIIQ1986

 

Employed Full-time Millions IQ1980 NSA End of Quarter

81.280

Employed Full-time Millions IIIQ1986 NSA End of Quarter

91.579

∆% Full-time Employed IQ1980 to IIIQ1986

12.7

Period IVQ2007 to IQ2013

 

Employed Full-time Millions IVQ2007 NSA End of Quarter

121.042

Employed Full-time Millions IQ2013 NSA End of Quarter

114.796

∆% Full-time Employed IVQ2007 to IQ2013

-5.2

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

i. As shown in Table IB-2 and in the following block, in the cycle from IQ1980 to IIIQ1986: (a) the rate of unemployment was virtually the same at 6.8 percent in IIIQ1986 relative to 6.6 percent in IQ1980; (b) the number unemployed increased from 6.983 million in IQ1980 to 8.015 million in IIIQ1986 or 14.8 percent; and (c) the number employed part-time for economic reasons increased 44.7 percent from 3.624 million in IQ1980 to 5.245 million in IIIQ1986.

ii. In contrast, in the economic cycle from IVQ2007 to IVQ2012: (a) the rate of unemployment increased from 4.8 percent in IVQ2007 to 7.6 percent in IQ2013; (b) the number unemployed increased 60.3 percent from 7.371 million in IVQ2007 to 11.815 million in IQ2013; (c) the number employed part-time for economic reasons increased 62.8 percent from 4.750 million in IVQ2007 to 7.734 million in IQ2013; 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 13.9 percent in IQ2013.

Period IQ1980 to IIIQ1986

 

Unemployment Rate IQ1980 NSA End of Quarter

6.6

Unemployment Rate  IIIQ1986 NSA End of Quarter

6.8

Unemployed IQ1980 Millions End of Quarter

6.983

Unemployed IIIQ1986 Millions End of Quarter

8.015

Employed Part-time Economic Reasons Millions IQ1980 End of Quarter

3.624

Employed Part-time Economic Reasons Millions IIIQ1986 End of Quarter

5.245

∆%

44.7

Period IVQ2007 to IQ2013

 

Unemployment Rate IVQ2007 NSA End of Quarter

4.8

Unemployment Rate IQ2013 NSA End of Quarter

7.6

Unemployed IVQ2007 Millions End of Quarter

7.371

Unemployed IQ2013 Millions End of Quarter

11.815

∆%

60.3

Employed Part-time Economic Reasons IVQ2007 Millions End of Quarter

4.750

Employed Part-time Economic Reasons Millions IQ2013 End of Quarter

7.734

∆%

62.8

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

IQ2013

13.9

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 IIIQ2012 is provided in the following block and in Table IB-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 Table IB-2, net worth of households and nonprofit organizations fell from $66,118.3 billion in IVQ2007 to $66,071.7 billion in IVQ2012 by $46.6 billion or 0.1 percent. The US consumer price index was 210.036 in Dec 2007 and 229.601 in Dec 2012 for increase of 9.1 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 8.4 percent in Dec 2012 after 14 consecutive quarters of expansion from IIIQ2009 to IVQ2012 relative to IVQ2007 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 IVQ2012 has been 2.1 percent, which is substantially lower than the average of 5.7 percent in the expansion from IQ1983 to IQ1986 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions. US wealth of households and nonprofit organizations grew from IVQ1945 at $710,125.9 million to IIIQ2009 at $64,768,835.3 million or increase of 9,020.8 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 231.407 in Sep 2012 or 1,171.5 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 67 years with inflation adjusted increase of 617.3 percent. The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIQ2009 caused sharp contraction of US household and nonprofit net worth. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 67 years when US GDP grew at 2.1 percent on average in 14 quarters between IIIQ2009 and IVQ2012 in contrast with average 5.7 percent from IQ1983 to IQ1986. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html).

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 IIIQ2012

 

Net Worth of Households and Nonprofit Organizations USD Billions

 

IVQ2007

66,118.3

IVQ2012

66,071.7

∆ USD Billions

-46.6

7. Gross Private Domestic Investment.

i. The comparison of gross private domestic investment in the entire economic cycles from IQ1980 to IIIIQ1986 and from IVQ2007 to IQ2013 is provided in the following block and in Table IB-2. Gross private domestic investment increased from $778.3 billion in IQ1980 to $913.0 billion in IIIQ1986 or by 17.3 percent.

ii In the current cycle, gross private domestic investment decreased from $2,123.6 billion in IVQ2007 to $1,991.8 billion in IQ2013, or decline by 6.2 percent. Private fixed investment fell from $2,111.5 billion in IVQ2007 to $1,925.5 billion in IQ2013, or decline by 8.8 percent.

Period IQ1980 to IIIQ1986

 

Gross Private Domestic Investment USD 2005 Billions

 

IQ1980

778.3

IIIQ1986

913.0

∆%

17.3

Period IVQ2007 to IQ2013

 

Gross Private Domestic Investment USD Billions

 

IVQ2007

2,123.6

IQ2013

1,991.8

∆%

-6.2

Private Fixed Investment USD 2005 Billions

 

IVQ2007

2,111.5

IQ2013

1,925.5

∆%

-8.8

Table IB-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 IIIQ1986

 

GDP SAAR USD Billions

 

    IQ1980

5,903.4

    IIIQ1986

7,112.9

∆% IQ1980 to IIIQ1986 (21.3 percent from IVQ1982 $5866.0 billion)

20.5

∆% Trend Growth IQ1980 to IIIQ1986

22.9

Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD

18,938

Real Disposable Personal Income per Capita IIIQ1986 Chained 2005 USD

22,165

∆% IQ1980 to IIIQ1986

17.0

∆% Trend Growth

14.9

Employed Millions IQ1980 NSA End of Quarter

98.527

Employed Millions III1986 NSA End of Quarter

110.229

∆% Employed IQ1980 to IIIQ1986

11.9

Employed Full-time Millions IQ1980 NSA End of Quarter

81.280

Employed Full-time Millions IIIIQ1986 NSA End of Quarter

91.579

∆% Full-time Employed IQ1980 to IIIQ1986

12.7

Unemployment Rate IQ1980 NSA End of Quarter

6.6

Unemployment Rate  IIIQ1986 NSA End of Quarter

6.8

Unemployed IQ1980 Millions NSA End of Quarter

6.983

Unemployed IIIQ1986 Millions NSA End of Quarter

8.015

∆%

16.3

Employed Part-time Economic Reasons IQ1980 Millions NSA End of Quarter

3.624

Employed Part-time Economic Reasons Millions IIIQ1986 NSA End of Quarter

5.245

∆%

44.7

Net Worth of Households and Nonprofit Organizations USD Billions

 

IVQ1979

8,326.4

IVQ1985

14,395.2

∆ USD Billions

+6,068.8

Gross Private Domestic Investment USD 2005 Billions

 

IQ1980

778.3

IQ1986

913.0

∆%

17.3

Period IVQ2007 to IQ2013

 

GDP SAAR USD Billions

 

    IVQ2007

13,326.0

    IQ2013

13,750.1

∆% IVQ2007 to IVQ2012

3.2

∆% IVQ2007 to IQ2013 Trend Growth

17.7

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD

32,837

Real Disposable Personal Income per Capita IQ2013 Chained 2005 USD

32,640

∆% IVQ2007 to IQ2013

-0.6

∆% Trend Growth

11.5

Employed Millions IVQ2007 NSA End of Quarter

146.334

Employed Millions IQ2013 NSA End of Quarter

142.698

∆% Employed IVQ2007 to IQ2013

-2.5

Employed Full-time Millions IVQ2007 NSA End of Quarter

121.042

Employed Full-time Millions IQ2013 NSA End of Quarter

114.796

∆% Full-time Employed IVQ2007 to IQ2013

-5.2

Unemployment Rate IVQ2007 NSA End of Quarter

4.8

Unemployment Rate IQ2013 NSA End of Quarter

7.6

Unemployed IVQ2007 Millions NSA End of Quarter

7.371

Unemployed IQ2013 Millions NSA End of Quarter

11.815

∆%

60.3

Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter

4.750

Employed Part-time Economic Reasons Millions IQ2013 NSA End of Quarter

7.734

∆%

62.8

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

IQ2013

13.9

Net Worth of Households and Nonprofit Organizations USD Billions

 

IVQ2007

66,118.3

IVQ2012

66,071.7

∆ USD Billions

-46.6

Gross Private Domestic Investment USD Billions

 

IVQ2007

2,123.6

IQ2013

1,991.8

∆%

-6.2

Private Fixed Investment USD 2005 Billions

 

IVQ2007

2,111.5

IQ2013

1,925.5

∆%

-8.8

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.

The Congressional Budget Office (CBO 2013BEOFeb5) estimates potential GDP, potential labor force and potential labor productivity provided in Table IB-3. The average rate of growth of potential GDP from 1950 to 2012 is estimated at 3.3 percent per year. The projected path is significantly lower at 2.2 percent per year from 2012 to 2023. The legacy of the economic cycle with expansion from IIIQ2009 to IQ2013 at 2.1 percent on average in contrast with 5.7 percent on average in the expansion (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html) may perpetuate unemployment and underemployment estimated at 28.6 million or 17.6 percent of the effective labor force in Apr 2013 (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html) with much lower hiring than in the period before the current cycle (Section I).

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

 

Potential GDP

Potential Labor Force

Potential Labor Productivity*

Average Annual ∆%

     

1950-1973

3.9

1.6

2.3

1974-1981

3.3

2.5

0.8

1982-1990

3.1

1.6

1.5

1991-2001

3.1

1.3

1.8

2002-2012

2.2

0.8

1.4

Total 1950-2012

3.3

1.5

1.7

Projected Average Annual ∆%

     

2013-2018

2.2

0.6

1.6

2019-2023

2.3

0.5

1.8

2012-2023

2.2

0.5

1.7

*Ratio of potential GDP to potential labor force

Source: CBO (2013BEOFeb5).

Chart IB-1 of the Congressional Budget Office (CBO 2013BEOFeb5) provides actual and potential GDP of the United States from 2000 to 2011 and projected to 2024. Lucas (2011May) estimates trend of United States real GDP of 3.0 percent from 1870 to 2010 and 2.2 percent for per capita GDP. The United States successfully returned to trend growth of GDP by higher rates of growth during cyclical expansion as analyzed by Bordo (2012Sep27, 2012Oct21) and Bordo and Haubrich (2012DR). Growth in expansions following deeper contractions and financial crises was much higher in agreement with the plucking model of Friedman (1964, 1988). The unusual weakness of growth at 2.1 percent on average from IIIQ2009 to IVQ2012 during the current economic expansion in contrast with 5.7 percent on average in the cyclical expansion from IQ1983 to IQ1986 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html) cannot be explained by the contraction of 4.7 of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 28.6 million or 17.6 percent of the labor as estimated for Apr 2013 (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html) and the collapse of hiring (Section I).

clip_image002

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

Source: Congressional Budget Office, CBO (2013BEOFeb5).

ESII Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels have increased by only 4 percent since Jan 2009. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job currently is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html). Lazear and Spletzer (2012Mar, 1) argue that reductions of churn reduce the operational effectiveness of labor markets. Churn is part of the allocation of resources or in this case labor to occupations of higher marginal returns. The decline in churn can harm static and dynamic economic efficiency. Losses from decline of churn during recessions can affect an economy over the long-term by preventing optimal growth trajectories because resources are not used in the occupations where they provide highest marginal returns. Lazear and Spletzer (2012Mar 7-8) conclude that: “under a number of assumptions, we estimate that the loss in output during the recession [of 2007 to 2009] and its aftermath resulting from reduced churn equaled $208 billion. On an annual basis, this amounts to about .4% of GDP for a period of 3½ years.”

There are two additional facts discussed below: (1) there are about ten million fewer full-time jobs currently than before the recession of 2008 and 2009; and (2) the extremely high and rigid rate of youth unemployment is denying an early start to young people ages 16 to 24 years while unemployment of ages 45 years or over has swelled. Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 52.0 million in 2012 or by 11.8 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 48.5 million in 2012 or by 11.0 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.2 in 2005 to 38.9 in 2012 and in the private sector (RHP) from 52.1 in 2006 to 43.4 in 2012. The collapse of hiring in the US has not been followed by dynamic labor markets because of the low rate of economic growth of 2.1 percent in the first fourteen quarters of expansion from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).

Table I-1, US, Annual Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US and Percentage of Total Employment

 

HNF

Rate RNF

HP

Rate HP

2001

62,948

47.8

58,825

53.1

2002

58,583

44.9

54,759

50.3

2003

56,451

43.4

53,056

48.9

2004

60,367

45.9

56,617

51.6

2005

63,150

47.2

59,372

53.1

2006

63,773

46.9

59,494

52.1

2007

62,421

45.4

58,035

50.3

2008

55,128

40.3

51,591

45.1

2009

46,357

35.4

43,031

39.8

2010

48,607

37.4

44,788

41.7

2011

49,675

37.8

46,552

42.5

2012

51,991

38.9

48,493

43.4

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

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Mar in the years from 2001 to 2013 in Table I-3. Hiring numbers are in thousands. There is virtually no recovery in HNF from 3530 thousand (or 3.5 million) in Mar 2009 to 3922 thousand in Mar 2010, 3980 thousand in Mar 2011, 4210 thousand in Mar 2012 and 4049 thousand in Mar 2013 for cumulative gain of 14.7 percent. HP rose from 3359 thousand in Mar 2009 to 3806 thousand in Mar 2011, 3997 thousand in Mar 2012 and 3838 in Mar 2013 for cumulative gain of 14.3 percent. HNF has fallen from 5036 in Mar 2006 to 4049 in Mar 2012 or by 19.6 percent. HP has fallen from 4773 in Mar 2006 to 3838 in Mar 2013 or by 19.6 percent. The civilian noninstitutional population of the US rose from 228.815 million in 2006 to 243.284 million in 2012 or by 14.469 million and the civilian labor force from 151.428 million in 2006 to 154.975 million in 2012 or by 3.547 million (http://www.bls.gov/data/). The number of nonfarm hires in the US fell from 63.773 million in 2006 to 51.991 million in 2012 or by 11.782 million and the number of private hires fell from 59.494 million in 2006 to 48.493 million in 2012 or by 11 million (http://www.bls.gov/jlt/). The labor market continues to be fractured, failing to provide an opportunity to exit from unemployment/underemployment or to find an opportunity for advancement away from declining inflation-adjusted earnings.

Table I-3, US, Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US in Thousands and in Percentage of Total Employment Not Seasonally Adjusted

 

HNF

Rate RNF

HP

Rate HP

2001 Mar

5235

4.0

4993

4.5

2002 Mar

4312

3.3

4097

3.8

2003 Mar

4099

3.2

3900

3.6

2004 Mar

4826

3.7

4592

4.3

2005 Mar

4894

3.7

4677

4.3

2006 Mar

5036

3.7

4773

4.2

2007 Mar

5013

3.7

4749

4.2

2008 Mar

4482

3.3

4256

3.7

2009 Mar

3530

2.7

3359

3.1

2010 Mar

3922

3.0

3663

3.5

2011 Mar

3980

3.1

3806

3.5

2012 Mar

4210

3.2

3997

3.6

2013 Mar

4049

3.0

3838

3.4

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

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2013. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4774 in May 2010 until it surpassed it with 4883 in Jun 2011 but declined to 3013 in Dec 2012. Nonfarm hiring fell again in Dec 2011 to 2990 from 3827 in Nov and to revised 3683 in Feb 2012, increasing to 4210 in Mar 2012, 3013 in Dec 2012 and 4128 in Jan 2013 and declining to 3632 in Feb 2013. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Aug 2011 was 4187 thousand, increasing to revised 4489 thousand in Feb 2012, or 7.2 percent, moving to 4195 in Dec 2012 for cumulative increase of 0.5 percent from 4174 in Dec 2011 and 4259 in Mar 2013 for increase of 1.5 percent relative to 4195 in Dec 2012. The number of hires not seasonally adjusted was 4883 in Jun 2011, falling to 2990 in Dec 2011 but increasing to 4013 in Jan 2012 and declining to 3013 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 38.8 percent from 4883 in Jun 2011 to 2990 in Dec 2011 and fell 41.3 percent from 5130 in Jun 2012 to 3013 in Dec 2012 in a yearly-repeated seasonal pattern.

clip_image003

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2013 Month SA

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

ESII Ten Million Fewer Full-time Jobs. The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in Apr 2013 is 115.674 million, which is lower by 7.545 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 245.175 million in Apr 2013 or by 13.217 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 7.545 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 13 million. Chart I-20 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 2013 with fluctuations around the typical behavior of a stationary series: there is no improvement in the United States in creating full-time jobs.

clip_image004

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2013

Sources: US Bureau of Labor Statistics

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

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2013. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

clip_image005

Chart I-20A, US, Noninstitutional Civilian Population, 2001-2013

Sources: US Bureau of Labor Statistics

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

Chart I-20B provides number of full-time jobs in the US from 1968 to 2013. There were multiple recessions followed by expansions without contraction of full-time jobs without recovery as during the period after 2008.

clip_image006

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2013

Sources: US Bureau of Labor Statistics

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

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

clip_image007

Chart I-20C, US, Noninstitutional Civilian Population, 1968-2013

Sources: US Bureau of Labor Statistics

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

ESIII Youth Unemployment and Middle-Aged Unemployment. The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs and to 17.834 million in 2012 or 2.207 million fewer jobs. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.914 million in Jul 2006 with 19.461 million in Jul 2012 for 2.453 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 19.406 million in Apr 2006 to 17.593 million in Apr 2013 or by 1.813 million. There are two hardships behind these data. First, young people cannot find employment after finishing high-school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

Table I-10, US, Employment Level 16-24 Years, Thousands, NSA

Year

Jan

Feb

Mar

Apr

Dec

Annual

2001

19678

19745

19800

19778

19547

20088

2002

18653

19074

19091

19108

19394

19683

2003

18811

18880

18709

18873

19136

19351

2004

18852

18841

18752

19184

19619

19630

2005

18858

18670

18989

19071

19733

19770

2006

19003

19182

19291

19406

20129

20041

2007

19407

19415

19538

19368

19361

19875

2008

18724

18546

18745

19161

18378

19202

2009

17467

17606

17564

17739

16615

17601

2010

16166

16412

16587

16764

16727

17077

2011

16512

16638

16898

16970

17234

17362

2012

16944

17150

17301

17387

17604

17834

2013

17183

17257

17271

17593

   

Sources: US Bureau of Labor Statistics

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

Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2013. Employment level is sharply lower in Apr 2013 relative to the peak in 2007.

clip_image008

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2013

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

Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million and 3451 thousand in 2012 or by 1.109 million. The unemployment level ages 16 to 24 years rose from 2.074 million in Apr 2007 to 3.129 million in Apr 2013 or by 1.055 million. This situation may persist for many years.

Table I-11, US, Unemployment Level 16-24 Years, Thousands NSA

Year

Jan

Feb

Mar

Apr

Dec

Annual

2001

2250

2258

2253

2095

2412

2371

2002

2754

2731

2822

2515

2374

2683

2003

2748

2740

2601

2572

2248

2746

2004

2767

2631

2588

2387

2294

2638

2005

2661

2787

2520

2398

2055

2521

2006

2366

2433

2216

2092

2007

2353

2007

2363

2230

2096

2074

2323

2342

2008

2633

2480

2347

2196

2928

2830

2009

3278

3457

3371

3321

3532

3760

2010

3983

3888

3748

3803

3352

3857

2011

3851

3696

3520

3365

3161

3634

2012

3416

3507

3294

3175

3153

3451

2013

3674

3449

3261

3129

   

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

Chart I-22 provides the unemployment level ages 16 to 24 from 2002 to 2012. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013.

clip_image009

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2013

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

Table I-12 provides the rate of unemployment of young peoples in ages 16 to 24 years. The annual rate jumped from 10.5 percent in 2007 to 18.4 percent in 2010, 17.3 percent in 2011 and 16.2 percent in 2012. During the seasonal peak in Jul the rate of youth unemployed was 18.1 percent in Jul 2011 and 17.1 percent in Jul 2012 compared with 10.8 percent in Jul 2007.

Table I-12, US, Unemployment Rate 16-24 Years, Thousands, NSA

Year

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Annual

2001

10.3

10.3

10.2

9.6

10.0

11.6

10.5

10.7

10.6

2002

12.9

12.5

12.9

11.6

11.6

13.2

12.4

11.5

12.0

2003

12.7

12.7

12.2

12.0

13.0

14.8

13.3

11.9

12.4

2004

12.8

12.3

12.1

11.1

12.2

13.4

12.3

11.1

11.8

2005

12.4

13.0

11.7

11.2

11.9

12.6

11.0

10.8

11.3

2006

11.1

11.3

10.3

9.7

10.2

11.9

11.2

10.4

10.5

2007

10.9

10.3

9.7

9.7

10.2

12.0

10.8

10.5

10.5

2008

12.3

11.8

11.1

10.3

13.3

14.4

14.0

13.0

12.8

2009

15.8

16.4

16.1

15.8

18.0

19.9

18.5

18.0

17.6

2010

19.8

19.2

18.4

18.5

18.4

20.0

19.1

17.8

18.4

2011

18.9

18.2

17.2

16.5

17.5

18.9

18.1

17.5

17.3

2012

16.8

17.0

16.0

15.4

16.3

18.1

17.1

16.8

16.2

2013

17.6

16.7

15.9

15.1

         

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

Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2002 to 2013. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels during the fourteen consecutive quarters of expansion of the economy since IIIQ2009 because of much lower growth at 2.1 percent annual equivalent on (Table I -5 http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).

clip_image010

Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2013

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

Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2013. The rate of youth unemployment rose to 20 percent during the contractions of the early 1980s and also during the contraction of the global recession in 2008 and 2009. The data illustrate again the argument in this blog that the contractions of the early 1980s are the valid framework for comparison with the global recession of 2008 and 2009 instead of misleading comparisons with the 1930s. During the initial phase of recovery, the rate of youth unemployment 16 to 24 years NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984 while the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 17.5 percent in Dec 2009, 16.7 percent in Dec 2010, 15.5 percent in Dec 2011, 15.2 percent in Dec 2012, 17.6 percent in Jan 2013, 16.7 percent in Feb 2013, 15.9 percent in Mar 2013 and 15.1 percent in Apr 2013. In Jul 2007, the rate of youth unemployment was 10.8 percent, increasing to 17.1 percent in Jul 2012. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.1 percent on average during the first fourteen quarters of expansion from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The fractured US labor market denies an early start for young people.

clip_image011

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2013

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

It is more difficult to move to other jobs after a certain age because of fewer available opportunities for matured individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.985 million in Jul 2006 to 4.821 million in July 2010 or by 142.9 percent. The number of unemployed ages 45 years and over declined to 4.405 million in Jul 2012 that is still higher by 121.9 percent than in Jul 2006. The number unemployed age 45 and over jumped from 1.794 million in Dec 2006 to 4.762 million in Dec 2010 or 165.4 percent and at 3.927 million in Dec 2012 is higher by 2.133 million or 118.9 percent higher than 1.794 million in Dec 2006. The level of unemployment of those aged 45 year or more of 3.689 million in Apr 2013 is higher by 1.846 million than 1.843 million in Apr 2006 or higher by 100.2 percent.

Table I-13, US, Unemployment Level 45 Years and Over, Thousands NSA

Year

Jan

Feb

Mar

Apr

Nov

Dec

2000

1498

1392

1291

1062

1242

1217

2001

1572

1587

1533

1421

1786

1901

2002

2235

2280

2138

2101

2013

2210

2003

2495

2415

2485

2287

2132

2130

2004

2453

2397

2354

2160

2053

2086

2005

2286

2286

2126

1939

1920

1963

2006

2126

2056

1881

1843

1704

1794

2007

2155

2138

2031

1871

1925

2120

2008

2336

2336

2326

2104

3078

3485

2009

4138

4380

4518

4172

4655

4960

2010

5314

5307

5194

4770

4909

4762

2011

5027

4837

4748

4373

4195

4182

2012

4458

4472

4390

4037

3861

3927

2013

4394

4107

3929

3689

   

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

Chart I-25 provides the level unemployed ages 45 years and over. There was sharp increase during the global recession and inadequate decline. There was an increase during the 2001 recession and then stability. The US is facing a major challenge of reemploying middle-aged workers.

clip_image012

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2013

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

ESVIII Global Financial and Economic Risk. The International Monetary Fund (IMF) provides an international safety net for prevention and resolution of international financial crises. The IMF’s Financial Sector Assessment Program (FSAP) provides analysis of the economic and financial sectors of countries (see Pelaez and Pelaez, International Financial Architecture (2005), 101-62, Globalization and the State, Vol. II (2008), 114-23). Relating economic and financial sectors is a challenging task both for theory and measurement. The IMF (2012WEOOct) provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/pubs/ft/weo/2012/02/index.htm), of the world financial system with its Global Financial Stability Report (GFSR) (IMF 2012GFSROct) (http://www.imf.org/external/pubs/ft/gfsr/2012/02/index.htm) and of fiscal affairs with the Fiscal Monitor (IMF 2012FMOct) (http://www.imf.org/external/pubs/ft/fm/2012/02/fmindex.htm). There appears to be a moment of transition in global economic and financial variables that may prove of difficult analysis and measurement. It is useful to consider a summary of global economic and financial risks, which are analyzed in detail in the comments of this blog in Section VI Valuation of Risk Financial Assets, Table VI-4.

Economic risks include the following:

  1. China’s Economic Growth. China is lowering its growth target to 7.5 percent per year. China’s GDP growth decelerated significantly from annual equivalent 9.9 percent in IIQ2011 to 7.4 percent in IVQ2011 and 6.6 percent in IQ2012, rebounding to 7.8 percent in IIQ2012, 8.7 percent in IIIQ2012 and 8.2 percent in IVQ2012. Annual equivalent growth in IQ2013 fell to 6.6 percent. (See Subsection VC and earlier at http://cmpassocregulationblog.blogspot.com/2013/01/recovery-without-hiring-world-inflation.html and earlier at http://cmpassocregulationblog.blogspot.com/2012/10/world-inflation-waves-stagnating-united_21.html).
  2. United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 28.6 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically low hiring and declining real wages.
  3. Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
  4. World Inflation Waves. Inflation continues in repetitive waves globally (http://cmpassocregulationblog.blogspot.com/2013/04/world-inflation-waves-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2013/03/recovery-without-hiring-ten-million.html ).

A list of financial uncertainties includes:

  1. Euro Area Survival Risk. The resilience of the euro to fiscal and financial doubts on larger member countries is still an unknown risk.
  2. Foreign Exchange Wars. Exchange rate struggles continue as zero interest rates in advanced economies induce devaluation of their currencies.
  3. Valuation of Risk Financial Assets. Valuations of risk financial assets have reached extremely high levels in markets with lower volumes.
  4. Duration Trap of the Zero Bound. The yield of the US 10-year Treasury rose from 2.031 percent on Mar 9, 2012, to 2.294 percent on Mar 16, 2012. Considering a 10-year Treasury with coupon of 2.625 percent and maturity in exactly 10 years, the price would fall from 105.3512 corresponding to yield of 2.031 percent to 102.9428 corresponding to yield of 2.294 percent, for loss in a week of 2.3 percent but far more in a position with leverage of 10:1. Min Zeng, writing on “Treasurys fall, ending brutal quarter,” published on Mar 30, 2012, in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702303816504577313400029412564.html?mod=WSJ_hps_sections_markets), informs that Treasury bonds maturing in more than 20 years lost 5.52 percent in the first quarter of 2012.
  5. Credibility and Commitment of Central Bank Policy. There is a credibility issue of the commitment of monetary policy (Sargent and Silber 2012Mar20).
  6. Carry Trades. Commodity prices driven by zero interest rates have resumed their increasing path with fluctuations caused by intermittent risk aversion

A competing event is the high level of valuations of risk financial assets (http://cmpassocregulationblog.blogspot.com/2013/01/peaking-valuation-of-risk-financial.html). Matt Jarzemsky, writing on Dow industrials set record,” on Mar 5, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324156204578275560657416332.html), analyzes that the DJIA broke the closing high of 14164.53 set on Oct 9, 2007, and subsequently also broke the intraday high of 14,198.10 reached on Oct 11, 2007. The DJIA closed at 15118.49

on Fri May 10, 2013, which is higher by 6.7 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 6.5 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs.

The DJIA closed at 14973.96

on Fri May 3, 2013, which is higher by 5.7 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 5.5 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs.

Jon Hilsenrath, writing on “Fed maps exit from stimulus,” on May 11, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887324744104578475273101471896.html?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes the development of strategy for unwinding quantitative easing and how it can create uncertainty in financial markets. Unconventional monetary policy with zero interest rates and quantitative easing is quite difficult to unwind because of the adverse effects of raising interest rates on valuations of risk financial assets and home prices, including the very own valuation of the securities held outright in the Fed balance sheet. Gradual unwinding of 1 percent fed funds rates from Jun 2003 to Jun 2004 by seventeen consecutive increases of 25 percentage points from Jun 2004 to Jun 2006 to reach 5.25 percent caused default of subprime mortgages and adjustable-rate mortgages linked to the overnight fed funds rate. The zero interest rate has penalized liquidity and increased risks by inducing carry trades from zero interest rates to speculative positions in risk financial assets. There is no exit from zero interest rates without provoking another financial crash.

The carry trade from zero interest rates to leveraged positions in risk financial assets had proved strongest for commodity exposures but US equities have regained leadership. The DJIA has increased 56.1 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to May 10, 2013, S&P 500 has gained 59.8 percent and DAX 46.0 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 5/10/13” had double digit gains relative to the trough around Jul 2, 2010 followed by negative performance but now some valuations of equity indexes show varying behavior: China’s Shanghai Composite is 5.7 percent below the trough; Japan’s Nikkei Average is 65.5 percent above the trough; DJ Asia Pacific TSM is 26.6 percent above the trough; Dow Global is 29.7 percent above the trough; STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 21.7 percent above the trough; and NYSE Financial Index is 37.0 percent above the trough. DJ UBS Commodities is 6.4 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 46.0 percent above the trough. Japan’s Nikkei Average is 65.5 percent above the trough on Aug 31, 2010 and 28.2 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 14607.54

on Fri May 10, 2013 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 42.5 percent higher than 10,254.43 on Mar 11, 2011, on the date of the Tōhoku or Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar depreciated by 10.0 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 5/10/13” in Table VI-4 shows increase of 1.9 percent for China’s Shanghai Composite in the week. DJ Asia Pacific increased 1.3 percent. NYSE Financial increased 1.3 percent in the week. DJ UBS Commodities decreased 0.9 percent. Dow Global increased 0.9 percent in the week of May 10, 2013. The DJIA increased 1.0 percent and S&P 500 increased 1.2 percent. DAX of Germany increased 1.9 percent. STOXX 50 increased 1.0 percent. The USD appreciated 0.9 percent. There are still high uncertainties on European sovereign risks and banking soundness, US and world growth slowdown and China’s growth tradeoffs. Sovereign problems in the “periphery” of Europe and fears of slower growth in Asia and the US cause risk aversion with trading caution instead of more aggressive risk exposures. There is a fundamental change in Table VI-4 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 5/10/13” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to May 10, 2013. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 5/10/13” but also relative to the peak in column “∆% Peak to 5/10/13.” There are now several equity indexes above the peak in Table VI-4: DJIA 34.9 percent, S&P 500 34.2 percent, DAX 30.7 percent, Dow Global 5.8 percent, DJ Asia Pacific 10.8 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 9.1 percent, Nikkei Average 28.2 percent and STOXX 50 3.0 percent. There is only one equity index below the peak: Shanghai Composite by 29.0 percent. DJ UBS Commodities Index is now 9.0 percent below the peak. The US dollar strengthened 14.1 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010. 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. It may be quite painful to exit QE→∞ or use of the balance sheet of the central together with zero interest rates forever. 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:

clip_image013

Where Rτ is expected revenue in the time horizon from τ =1 to T; Cτ 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

clip_image013[1]

declines. Equally, decline in expected revenue from the stock or project, Rτ, causes decline in valuation. An intriguing issue is the difference in performance of valuations of risk financial assets and economic growth and employment. Paul A. Samuelson (http://www.nobelprize.org/nobel_prizes/economics/laureates/1970/samuelson-bio.html).

Table VI-4, Stock Indexes, Commodities, Dollar and 10-Year Treasury  

 

Peak

Trough

∆% to Trough

∆% Peak to 5/10/

/13

∆% Week 5/10/13

∆% Trough to 5/10/

13

DJIA

4/26/
10

7/2/10

-13.6

34.9

1.0

56.1

S&P 500

4/23/
10

7/20/
10

-16.0

34.2

1.2

59.8

NYSE Finance

4/15/
10

7/2/10

-20.3

9.1

1.3

37.0

Dow Global

4/15/
10

7/2/10

-18.4

5.8

0.9

29.7

Asia Pacific

4/15/
10

7/2/10

-12.5

10.8

1.3

26.6

Japan Nikkei Aver.

4/05/
10

8/31/
10

-22.5

28.2

6.7

65.5

China Shang.

4/15/
10

7/02
/10

-24.7

-29.0

1.9

-5.7

STOXX 50

4/15/10

7/2/10

-15.3

3.0

1.0

21.7

DAX

4/26/
10

5/25/
10

-10.5

30.7

1.9

46.0

Dollar
Euro

11/25 2009

6/7
2010

21.2

14.1

0.9

-9.0

DJ UBS Comm.

1/6/
10

7/2/10

-14.5

-9.0

-0.9

6.4

10-Year T Note

4/5/
10

4/6/10

3.986

1.896

   

T: trough; Dollar: positive sign appreciation relative to euro (less dollars paid per euro), negative sign depreciation relative to euro (more dollars paid per euro)

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

I Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels have increased by only 4 percent since Jan 2009. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job currently is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html). Lazear and Spletzer (2012Mar, 1) argue that reductions of churn reduce the operational effectiveness of labor markets. Churn is part of the allocation of resources or in this case labor to occupations of higher marginal returns. The decline in churn can harm static and dynamic economic efficiency. Losses from decline of churn during recessions can affect an economy over the long-term by preventing optimal growth trajectories because resources are not used in the occupations where they provide highest marginal returns. Lazear and Spletzer (2012Mar 7-8) conclude that: “under a number of assumptions, we estimate that the loss in output during the recession [of 2007 to 2009] and its aftermath resulting from reduced churn equaled $208 billion. On an annual basis, this amounts to about .4% of GDP for a period of 3½ years.”

There are two additional facts discussed below: (1) there are about ten million fewer full-time jobs currently than before the recession of 2008 and 2009; and (2) the extremely high and rigid rate of youth unemployment is denying an early start to young people ages 16 to 24 years while unemployment of ages 45 years or over has swelled. There are four subsections. IA1 Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IA2 Labor Underutilization provides the measures of labor underutilization of the Bureau of Labor Statistics (BLS). Statistics on the decline of full-time employment are in IA3 Ten Million Fewer Full-time Jobs. IA4 Youth and Middle-Age Unemployment provides the data on high unemployment of ages 16 to 24 years and of ages 45 years or over.

IA1 Hiring Collapse. An important characteristic of the current fractured labor market of the US is the closing of the avenue for exiting unemployment and underemployment normally available through dynamic hiring. Another avenue that is closed is the opportunity for advancement in moving to new jobs that pay better salaries and benefits again because of the collapse of hiring in the United States. Those who are unemployed or underemployed cannot find a new job even accepting lower wages and no benefits. The employed cannot escape declining inflation-adjusted earnings because there is no hiring. The objective of this section is to analyze hiring and labor underutilization in the United States.

Blanchard and Katz (1997, 53 consider an appropriate measure of job stress:

“The right measure of the state of the labor market is the exit rate from unemployment, defined as the number of hires divided by the number unemployed, rather than the unemployment rate itself. What matters to the unemployed is not how many of them there are, but how many of them there are in relation to the number of hires by firms.”

The natural rate of unemployment and the similar NAIRU are quite difficult to estimate in practice (Ibid; see Ball and Mankiw 2002).

The Bureau of Labor Statistics (BLS) created the Job Openings and Labor Turnover Survey (JOLTS) with the purpose that (http://www.bls.gov/jlt/jltover.htm#purpose):

“These data serve as demand-side indicators of labor shortages at the national level. Prior to JOLTS, there was no economic indicator of the unmet demand for labor with which to assess the presence or extent of labor shortages in the United States. The availability of unfilled jobs—the jobs opening rate—is an important measure of tightness of job markets, parallel to existing measures of unemployment.”

The BLS collects data from about 16,000 US business establishments in nonagricultural industries through the 50 states and DC. The data are released monthly and constitute an important complement to other data provided by the BLS (see also Lazear and Spletzer 2012Mar, 6-7).

Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 52.0 million in 2012 or by 11.8 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 48.5 million in 2012 or by 11.0 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.2 in 2005 to 38.9 in 2012 and in the private sector (RHP) from 52.1 in 2006 to 43.4 in 2012. The collapse of hiring in the US has not been followed by dynamic labor markets because of the low rate of economic growth of 2.1 percent in the first fourteen quarters of expansion from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).

Table I-1, US, Annual Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US and Percentage of Total Employment

 

HNF

Rate RNF

HP

Rate HP

2001

62,948

47.8

58,825

53.1

2002

58,583

44.9

54,759

50.3

2003

56,451

43.4

53,056

48.9

2004

60,367

45.9

56,617

51.6

2005

63,150

47.2

59,372

53.1

2006

63,773

46.9

59,494

52.1

2007

62,421

45.4

58,035

50.3

2008

55,128

40.3

51,591

45.1

2009

46,357

35.4

43,031

39.8

2010

48,607

37.4

44,788

41.7

2011

49,675

37.8

46,552

42.5

2012

51,991

38.9

48,493

43.4

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

Chart I-1 shows the annual level of total nonfarm hiring (HNF) that collapsed during the global recession after 2007 in contrast with milder decline in the shallow recession of 2001. Nonfarm hiring has not been recovered, remaining at a depressed level.

clip_image014

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2012

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-2 shows the ratio or rate of nonfarm hiring to employment (RNF) that also fell much more in the recession of 2007 to 2009 than in the shallow recession of 2001. Recovery is weak.

http://www.bls.gov/jlt/

clip_image015

Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2012

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table I-2. There were much milder declines in 2002 of 6.9 percent and 3.6 percent in 2003 followed by strong rebounds of 6.9 percent in 2004 and 4.6 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.1 in 2007, 11.7 in 2008 and 15.9 percent in 2009. On a yearly basis, nonfarm hiring grew 4.9 percent in 2010 relative to 2009, 2.2 percent in 2011 and 4.7 percent in 2012.

Table I-2, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2002-2012

Year

Annual

2002

-6.9

2003

-3.6

2004

6.9

2005

4.6

2006

1.0

2007

-2.1

2008

-11.7

2009

-15.9

2010

4.9

2011

2.2

2012

4.7

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-3 plots yearly percentage changes of nonfarm hiring. Percentage declines after 2007 were quite sharp.

clip_image016

Chart I-3, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2001-2012

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Total private hiring (HP) yearly data are provided in Chart I-4. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2012.

clip_image017

Chart I-4, US, Total Private Hiring Level, Annual, 2001-2012

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-5 plots the rate of total private hiring relative to employment (RHP). The rate collapsed during the global recession after 2007 with insufficient recovery.

clip_image018

Chart I-5, US, Rate Total Private Hiring, Annual, 2001-2012

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Mar in the years from 2001 to 2013 in Table I-3. Hiring numbers are in thousands. There is virtually no recovery in HNF from 3530 thousand (or 3.5 million) in Mar 2009 to 3922 thousand in Mar 2010, 3980 thousand in Mar 2011, 4210 thousand in Mar 2012 and 4049 thousand in Mar 2013 for cumulative gain of 14.7 percent. HP rose from 3359 thousand in Mar 2009 to 3806 thousand in Mar 2011, 3997 thousand in Mar 2012 and 3838 in Mar 2013 for cumulative gain of 14.3 percent. HNF has fallen from 5036 in Mar 2006 to 4049 in Mar 2012 or by 19.6 percent. HP has fallen from 4773 in Mar 2006 to 3838 in Mar 2013 or by 19.6 percent. The civilian noninstitutional population of the US rose from 228.815 million in 2006 to 243.284 million in 2012 or by 14.469 million and the civilian labor force from 151.428 million in 2006 to 154.975 million in 2012 or by 3.547 million (http://www.bls.gov/data/). The number of nonfarm hires in the US fell from 63.773 million in 2006 to 51.991 million in 2012 or by 11.782 million and the number of private hires fell from 59.494 million in 2006 to 48.493 million in 2012 or by 11 million (http://www.bls.gov/jlt/). The labor market continues to be fractured, failing to provide an opportunity to exit from unemployment/underemployment or to find an opportunity for advancement away from declining inflation-adjusted earnings.

Table I-3, US, Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US in Thousands and in Percentage of Total Employment Not Seasonally Adjusted

 

HNF

Rate RNF

HP

Rate HP

2001 Mar

5235

4.0

4993

4.5

2002 Mar

4312

3.3

4097

3.8

2003 Mar

4099

3.2

3900

3.6

2004 Mar

4826

3.7

4592

4.3

2005 Mar

4894

3.7

4677

4.3

2006 Mar

5036

3.7

4773

4.2

2007 Mar

5013

3.7

4749

4.2

2008 Mar

4482

3.3

4256

3.7

2009 Mar

3530

2.7

3359

3.1

2010 Mar

3922

3.0

3663

3.5

2011 Mar

3980

3.1

3806

3.5

2012 Mar

4210

3.2

3997

3.6

2013 Mar

4049

3.0

3838

3.4

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

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2013. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4774 in May 2010 until it surpassed it with 4883 in Jun 2011 but declined to 3013 in Dec 2012. Nonfarm hiring fell again in Dec 2011 to 2990 from 3827 in Nov and to revised 3683 in Feb 2012, increasing to 4210 in Mar 2012, 3013 in Dec 2012 and 4128 in Jan 2013 and declining to 3632 in Feb 2013. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Aug 2011 was 4187 thousand, increasing to revised 4489 thousand in Feb 2012, or 7.2 percent, moving to 4195 in Dec 2012 for cumulative increase of 0.5 percent from 4174 in Dec 2011 and 4259 in Mar 2013 for increase of 1.5 percent relative to 4195 in Dec 2012. The number of hires not seasonally adjusted was 4883 in Jun 2011, falling to 2990 in Dec 2011 but increasing to 4013 in Jan 2012 and declining to 3013 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 38.8 percent from 4883 in Jun 2011 to 2990 in Dec 2011 and fell 41.3 percent from 5130 in Jun 2012 to 3013 in Dec 2012 in a yearly-repeated seasonal pattern.

clip_image003[1]

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2013 Month SA

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Similar behavior occurs in the rate of nonfarm hiring in Chart I-7. Recovery in early 2010 was followed by decline and stabilization at a lower level but with stability in monthly SA estimates of 3.2 in Aug 2011 to 3.2 in Jan 2012, increasing to 3.4 in May 2012 and falling to 3.3 in Jun and 3.1 in Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.1 in Dec 2012 and 3.2 in Mar 2013. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.2 in Dec 2012, climbing to 3.8 in Jun 2012 but falling to 2.2 in Dec 2012 and 3.0 in Mar 2013. Rates of nonfarm hiring NSA were in the range of 2.8 (Dec) to 4.5 (Jun) in 2006.

clip_image019

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2013

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

There is only milder improvement in total private hiring shown in Chart I-8. Hiring private (HP) rose in 2010 with stability and renewed increase in 2011 followed by almost stationary series in 2012. The number of private hiring seasonally adjusted fell from 4026 thousand in Sep 2011 to 3876 in Dec 2011 or by 3.7 percent, increasing to 3915 in Jan 2012 or decline by 2.8 percent relative to the level in Sep 2011 but decreasing to 3934 in Sep 2012 or lower by 2.3 percent relative to Sep 2011 and decreasing to 3915 in Dec 2012 for change of 0.0 percent relative to 3915 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4504 in Jun 2011 to 2809 in Dec 2011 or by 37.6 percent, reaching 3749 in Jan 2012 or decline of 16.8 percent relative to Jun 2011 and moving to 2842 in Dec 2012 or 39.8 percent lower relative to 4724 in Jun 2012. Companies do not hire in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5661 in Jun 2006 to 3635 in Dec 2006 or by 35.8 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Jul 2006 private hiring NSA was 5555, declining to 4245 in Jul 2011 or by 23.6 percent and to 4277 in Jul 2012 or lower by 23.0 percent relative to Jul 2006. Private hiring NSA fell from 5215 in Sep 2005 to 4005 in Sep 2012 or 23.2 percent and fell from 3635 in Dec 2006 to 2842 in Dec 2012 or 21.8 percent. The conclusion is that private hiring in the US is around 20 percent below the hiring before the global recession. The main problem in recovery of the US labor market has been the low rate of growth of 2.1 percent in the fourteen quarters of expansion of the economy from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

clip_image020

Chart I-8, US, Total Private Hiring Month SA 2001-2013

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data did not rise significantly above the peak in 2010. The rate seasonally adjusted fell from 3.6 in Sep 2011 to 3.5 in Dec 2011 and reached 3.5 in Dec 2012 and 3.5 in Mar 2013. The rate not seasonally adjusted (NSA) fell from 3.7 in Sep 2011 to 2.5 in Dec 2011, increasing to 3.8 in Oct 2012 but falling to 2.5 in Dec 2012 and 3.4 in Mar 2013. The NSA rate of private hiring fell from 4.8 in Jul 2006 to 3.4 in Aug 2009 but recovery was insufficient to only 3.8 in Aug 2012, 2.5 in Dec 2012 and 3.4 in Mar 2013.

clip_image021

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2013

Source: Bureau of Labor Statistics

http://www.bls.gov/jlt/

The JOLTS report of the Bureau of Labor Statistics also provides total nonfarm job openings (TNF JOB), TNF JOB rate and TNF LD (layoffs and discharges) shown in Table I-4 for the month of Mar from 2001 to 2013. The final column provides annual TNF LD for the years from 2001 to 2012. Nonfarm job openings (TNF JOB) fell from a peak of 4615 in Mar 2007 to 3869 in Mar 2013 or by 16.2 percent while the rate dropped from 3.3 to 2.8. Nonfarm layoffs and discharges (TNF LD) rose from 1353 in Mar 2006 to 2003 in Mar 2009 or by 48.0 percent. The annual data show layoffs and discharges rising from 21.2 million in 2006 to 26.8 million in 2009 or by 26.4 percent. Business pruned payroll jobs to survive the global recession but there has not been hiring because of the weak recovery in the form of growth of 2.1 percent on average in the fourteen quarters of expansion from IIIQ2009 to IQ2013 (see Table I-5 at http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).

Table I-4, US, Total Nonfarm Job Openings and Total Nonfarm Layoffs and Discharges, Thousands NSA

 

TNF JOB

TNF JOB
Rate

TNF LD

TNF LD
Annual

Mar 2001

4569

3.4

1800

24499

Mar 2002

3414

2.6

1432

22922

Mar 2003

2955

2.2

1488

23294

Mar 2004

3300

2.5

1538

22802

Mar 2005

3832

2.8

1595

22185

Mar 2006

4384

3.1

1353

21157

Mar 2007

4615

3.3

1446

22142

Mar 2008

3929

2.8

1492

24181

Mar 2009

2499

1.9

2003

26784

Mar 2010

2566

2.0

1480

21773

Mar 2011

3062

2.3

1338

20401

Mar 2012

3802

2.8

1345

20546

Mar 2013

3869

2.8

1343

 

Notes: TNF JOB: Total Nonfarm Job Openings; LD: Layoffs and Discharges

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

Chart I-10 shows monthly job openings rising from the trough in 2009 to a high in the beginning of 2010. Job openings then stabilized into 2011 but have surpassed the peak of 3142 seasonally adjusted in Apr 2010 with 3612 seasonally adjusted in Dec 2012, which is higher by 15.0 percent relative to Apr 2010 but lower by 4.7 percent than 3789 in Nov 2012 and lower than 3848 in Mar 2012 by 6.1 percent. Nonfarm job openings increased from 3612 in Dec 2012 to 3844 in Mar 2012 or by 6.4 percent. The high of job openings not seasonally adjusted in 2010 was 3396 in Apr 2010 that was surpassed by 3554 in Jul 2011, increasing to 3896 in Oct 2012 but declining to 3103 in Dec 2012 and increasing to 3869 in Mar 2013. The level of job openings not seasonally adjusted fell to 3103 in Dec 2012 or by 19.0 percent relative to 3831 in Apr 2012. There is here again the strong seasonality of year-end labor data. The level of job openings of 3869 in Mar 2013 NSA is lower by 16.2 percent relative to 4615 in Mar 2007. The main problem in recovery of the US labor market has been the low rate of growth of 2.1 percent in the fourteen quarters of expansion of the economy since IIIQ2009 (see table I-5 at http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

clip_image022

Chart I-10, US Job Openings, Thousands NSA, 2001-2013

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted rose from 2.2 percent in Jan 2011 to 2.5 percent in Dec 2011, 2.6 in Dec 2012 and 2.8 in Mar 2013. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 2.8 in Mar 2013. The rate of job openings NSA fell from 3.4 in Jul 2007 to 1.6 in Nov-Dec 2009, recovering insufficiently to 2.8 in Mar 2013.

clip_image023

Chart I-11, US, Rate of Job Openings, NSA, 2001-2013

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Total separations are shown in Chart I-12. Separations are much lower in 2012-2-13 than before the global recession but hiring has not recovered.

clip_image024

Chart I-12, US, Total Nonfarm Separations, Month SA, 2001-2013

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Annual total separations are shown in Chart I-13. Separations are much lower in 2011-2012 than before the global recession but without recovery in hiring.

clip_image025

Chart I-13, US, Total Separations, Annual, 2001-2012

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Table I-5 provides total nonfarm total separations from 2001 to 2012. Separations fell from 61.6 million in 2006 to 47.6 million in 2010 or by 14.0 million and 47.6 million in 2011 or by 14.0 million. Total separations increased from 47.6 million in 2011 to 49.7 million in 2012 or by 2.1 million.

Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2012

Year

Annual

2001

64765

2002

59190

2003

56487

2004

58340

2005

60733

2006

61565

2007

61162

2008

58627

2009

51532

2010

47646

2011

47626

2012

49676

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt

Monthly data of layoffs and discharges reach a peak in early 2009, as shown in Chart I-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business. Weak rates of growth of 2.1 percent of GDP on average from IIIQ2009 to IQ2013 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html) frustrated employment recovery. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).

clip_image026

Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly SA, 2011-2013

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Layoffs and discharges in Chart I-15 rose sharply to a peak in 2009. There was pronounced drop into 2010 and 2011 with mild increase into 2012.

clip_image027

Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2012

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

Table I-6 provides annual nonfarm layoffs and discharges from 2001 to 2012. Layoffs and discharges peaked at 26.8 million in 2009 and then fell to 20.4 million in 2011, by 6.4 million, or 23.9 percent. Total nonfarm layoffs and discharges increased mildly to 20.5 million in 2012.

Table I-6, US, Total Nonfarm Layoffs and Discharges, 2001-2012

Year

Annual

2001

24499

2002

22922

2003

23294

2004

22802

2005

22185

2006

21157

2007

22142

2008

24181

2009

26784

2010

21773

2011

20401

2012

20546

Source: US Bureau of Labor Statistics

http://www.bls.gov/jlt/

IA2 Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table I-7. The most comprehensive measure is U6 that consists of total unemployed plus total employed part time for economic reasons plus all marginally attached workers as percent of the labor force. U6 not seasonally annualized has risen from 8.2 percent in 2006 to 13.4 percent in Apr 2013.

Table I-7, US, Alternative Measures of Labor Underutilization NSA %

 

U1

U2

U3

U4

U5

U6

2013

           

Apr

4.3

3.9

7.1

7.6

8.5

13.4

Mar

4.3

4.3

7.6

8.1

9.0

13.9

Feb

4.3

4.6

8.1

8.6

9.6

14.9

Jan

4.3

4.9

8.5

9.0

9.9

15.4

2012

           

Dec

4.2

4.3

7.6

8.3

9.2

14.4

Nov

4.2

3.9

7.4

7.9

8.8

13.9

Oct

4.3

3.9

7.5

8.0

9.0

13.9

Sep

4.2

4.0

7.6

8.0

9.0

14.2

Aug

4.3

4.4

8.2

8.7

9.7

14.6

Jul

4.3

4.6

8.6

9.1

10.0

15.2

Jun

4.5

4.4

8.4

8.9

9.9

15.1

May

4.7

4.3

7.9

8.4

9.3

14.3

Apr

4.8

4.3

7.7

8.3

9.1

14.1

Mar

4.9

4.8

8.4

8.9

9.7

14.8

Feb

4.9

5.1

8.7

9.3

10.2

15.6

Jan

4.9

5.4

8.8

9.4

10.5

16.2

2011

           

Dec

4.8

5.0

8.3

8.8

9.8

15.2

Nov

4.9

4.7

8.2

8.9

9.7

15.0

Oct 

5.0

4.8

8.5

9.1

10.0

15.3

Sep

5.2

5.0

8.8

9.4

10.2

15.7

Aug

5.2

5.1

9.1

9.6

10.6

16.1

Jul

5.2

5.2

9.3

10.0

10.9

16.3

Jun

5.1

5.1

9.3

9.9

10.9

16.4

May

5.5

5.1

8.7

9.2

10.0

15.4

Apr

5.5

5.2

8.7

9.2

10.1

15.5

Mar

5.7

5.8

9.2

9.7

10.6

16.2

Feb

5.6

6.0

9.5

10.1

11.1

16.7

Jan

5.6

6.2

9.8

10.4

11.4

17.3

Dec  2010

5.4

5.9

9.1

9.9

10.7

16.6

Annual

           

2012

4.5

4.4

8.1

8.6

9.5

14.7

2011

5.3

5.3

8.9

9.5

10.4

15.9

2010

5.7

6.0

9.6

10.3

11.1

16.7

2009

4.7

5.9

9.3

9.7

10.5

16.2

2008

2.1

3.1

5.8

6.1

6.8

10.5

2007

1.5

2.3

4.6

4.9

5.5

8.3

2006

1.5

2.2

4.6

4.9

5.5

8.2

2005

1.8

2.5

5.1

5.4

6.1

8.9

2004

2.1

2.8

5.5

5.8

6.5

9.6

2003

2.3

3.3

6.0

6.3

7.0

10.1

2002

2.0

3.2

5.8

6.0

6.7

9.6

2001

1.2

2.4

4.7

4.9

5.6

8.1

2000

0.9

1.8

4.0

4.2

4.8

7.0

Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers

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

Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.1 percent in Aug 2011 to 16.3 percent in Sep 2011 and then fell to 14.5 percent in Apr 2012 and 13.9 percent in Apr 2013. Unemployment is an incomplete measure of the stress in US job markets. A different calculation in this blog is provided by using the participation rate in the labor force before the global recession. This calculation shows 28.6 million in job stress of unemployment/underemployment in Mar 2013, not seasonally adjusted, corresponding to 17.6 percent of the labor force (Table I-4 http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).

Table I-8, US, Alternative Measures of Labor Underutilization SA %

 

U1

U2

U3

U4

U5

U6

Apr 2013

4.1

4.1

7.5

8.0

8.9

13.9

Mar

4.1

4.1

7.6

8.1

8.9

13.8

Feb

4.2

4.2

7.7

8.3

9.2

14.3

Jan

4.2

4.3

7.9

8.4

9.3

14.4

Dec 2012

4.3

4.1

7.8

8.5

9.4

14.4

Nov

4.3

4.1

7.8

8.3

9.2

14.4

Oct

4.4

4.2

7.9

8.4

9.3

14.5

Sep

4.3

4.2

7.8

8.3

9.3

14.7

Aug

4.4

4.5

8.1

8.6

9.6

14.7

Jul

4.5

4.6

8.2

8.7

9.7

14.9

Jun

4.6

4.6

8.2

8.7

9.6

14.8

May

4.6

4.5

8.2

8.7

9.6

14.8

Apr

4.5

4.5

8.1

8.7

9.5

14.5

Mar

4.6

4.5

8.2

8.7

9.6

14.5

Feb

4.8

4.6

8.3

8.9

9.8

15.0

Jan

4.8

4.7

8.3

8.9

9.9

15.1

Dec 2011

4.9

4.9

8.5

9.0

10.0

15.2

Nov

5.0

4.9

8.6

9.3

10.2

15.5

Oct

5.1

5.1

8.9

9.5

10.4

16.0

Sep

5.4

5.2

9.0

9.6

10.5

16.3

Aug

5.3

5.2

9.0

9.6

10.5

16.1

Jul

5.3

5.3

9.0

9.7

10.6

16.0

Jun

5.3

5.3

9.1

9.7

10.7

16.1

May

5.3

5.4

9.0

9.5

10.3

15.8

Apr

5.2

5.4

9.0

9.6

10.5

16.0

Mar

5.3

5.4

8.9

9.5

10.4

15.8

Feb

5.4

5.5

9.0

9.6

10.6

16.0

Jan

5.5

5.5

9.1

9.7

10.8

16.2

Note: LF: labor force; U1, persons unemployed 15 weeks % LF; U2, job losers and persons who completed temporary jobs %LF; U3, total unemployed % LF; U4, total unemployed plus discouraged workers, plus all other marginally attached workers; % LF plus discouraged workers; U5, total unemployed, plus discouraged workers, plus all other marginally attached workers % LF plus all marginally attached workers; U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers

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

Chart I-16 provides U1 on a monthly basis from 2001 to 2013. There was a steep climb from 2007 into 2009 and then this measure of unemployment and underemployment stabilized at that high level but declined into 2012. The low of U6 SA was 7.9 percent in Dec 2006 and the peak was 17.1 percent in Oct-Dec 2009. The low NSA was 7.6 percent in Oct 2006 and the peak was 18.0 percent in Jan 2010.

clip_image028

Chart I-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed Part-Time for Economic Reasons, Month, SA, 2001-2013

Source: US Bureau of Labor Statistics

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

Chart I-17 provides the number employed part-time for economic reasons or who cannot find full-time employment. There are sharp declines at the end of 2009, 2010 and 2011 but an increase in 2012 followed by stability in 2013.

clip_image029

Chart I-17, US, Working Part-time for Economic Reasons

Thousands, Month SA 2001-2013

Sources: US Bureau of Labor Statistics

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

There is strong seasonality in US labor markets around the end of the year. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.101 million in Sep 2011 to 8.043 million in Aug 2012, seasonally adjusted, or decline of 1.058 million in nine months, as shown in Table I-9, but then rebounded to 8.607 million in Sep 2012 for increase of 564,000 in one month from Aug to Sep 2012, declining to 8.286 million in Oct 2012 or by 321,000 again in one month, further declining to 8.138 million in Nov 2012 for another major one-month decline of 148,000 and 7.918 million in Dec 2012 or fewer 220,000 in just one month. The number employed part-time for economic reasons increased to 7.973 million in Jan 2013 or 15,000 more than in Dec 2012 and to 7,988 million in Feb 2013, declining to 7.616 million in Apr 2013. There is an increase of 243,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 95,000 from Aug 2012 to Nov 2012. The number employed full-time increased from 112.871 million in Oct 2011 to 115.145 million in Mar 2012 or 2.274 million but then fell to 114.300 million in May 2012 or 0.845 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.492 million in Aug 2012 to 115.469 million in Oct 2012 or increase of 0.977 million full-time jobs in two months and further to 115.918 million in Jan 2013 or increase of 1.426 million more full-time jobs in four months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.841 in Feb 2013, increasing to 116.053 million in Apr 2013. Benchmark and seasonality-factors adjustments at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html http://cmpassocregulationblog.blogspot.com/2013/03/thirty-one-million-unemployed-or.html). The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.0151 million and to 7.694 million in Apr 2012 or 1.224 million fewer relative to Jan 2012. In Aug 2012, the number employed part-time for economic reasons reached 7.842 million NSA or 148,000 more than in Apr 2012. The number employed part-time for economic reasons increased from 7.842 million in Aug 2012 to 8.110 million in Sep 2012 or by 3.4 percent. The number part-time for economic reasons fell from 8.110 million in Sep 2012 to 7.870 million in Oct 2012 or by 240.000 in one month. The number employed part-time for economic reasons NSA increased to 8.628 million in Jan 2013 or 758,000 more than in Oct 2012. The number employed part-time for economic reasons fell to 8.298 million in Feb 2013, which is lower by 330,000 relative to 8.628 million in Jan 2013 but higher by 428,000 relative to 7.870 million in Oct 2012. The number employed part time for economic reasons fell to 7.734 million in Mar 2013 or 564,000 less than in Feb 2013 and fell to 7.709 million in Apr 2013. The number employed full time without seasonal adjustment fell from 113.138 million in Nov 2011 to 113.050 million in Dec 2011 or by 88,000 and fell further to 111.879 in Jan 2012 for cumulative decrease of 1.259 million. The number employed full-time not seasonally adjusted fell from 113.138 million in Nov 2011 to 112.587 million in Feb 2012 or by 551.000 but increased to 116.214 million in Aug 2012 or 3.076 million more full-time jobs than in Nov 2011. The number employed full-time not seasonally adjusted decreased from 116.214 million in Aug 2012 to 115.678 million in Sep 2012 for loss of 536,000 full-time jobs and rose to 116.045 million in Oct 2012 or by 367,000 full-time jobs in one month relative to Sep 2012. The number employed full-time NSA fell from 116.045 million in Oct 2012 to 115.515 million in Nov 2012 or decline of 530.000 in one month. The number employed full-time fell from 115.515 in Nov 2012 to 115.079 million in Dec 2012 or decline by 436,000 in one month. The number employed full time fell from 115.079 million in Dec 2012 to 113.868 million in Jan 2013 or decline of 1.211 million in one month. The number of full time jobs increased to 114.191 in Feb 2012 or by 323,000 in one month and increased to 114.796 million in Mar 2013 for cumulative increase from Jan by 928,000 full-time jobs but decrease of 283,000 from Dec 2012. Comparisons over long periods require use of NSA data. The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in Apr 2013 is 115.674 million, which is lower by 7.545 million relative to the peak of 123.219 million in Jul 2007. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 245.175 million in Apr 2013 or by 13.217 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 7.545 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 13 million. Growth at 2.1 percent on average in the fourteen quarters of expansion from IIIQ2009 to IQ2013 is the main culprit of the fractured US labor market (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).

Table I-9, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions

 

Part-time Thousands

Full-time Millions

Seasonally Adjusted

   

Apr 2013

7,616

116.053

Mar

7,638

115.903

Feb 2013

7,988

115.841

Jan 2013

7,973

115.918

Dec 2012

7,918

115.868

Nov 2012

8,138

115.665

Oct 2012

8,286

115.469

Sep 2012

8,607

115.259

Aug 2012

8,043

114.492

Jul 2012

8,245

114.478

Jun 2012

8,210

114.606

May 2012

8,116

114.300

Apr 2012

7,896

114.441

Mar 2012

7,664

115.145

Feb 2012

8,127

114.263

Jan 2012

8,220

113.833

Dec 2011

8,168

113.820

Nov 2011

8,436

113.217

Oct 2011

8,726

112.871

Sep 2011

9,101

112.541

Aug 2011

8,816

112.555

Jul 2011

8,416

112.141

Not Seasonally Adjusted

   

Apr 2013

7,709

115.674

Mar 2013

7,734

114.796

Feb 2013

8,298

114.191

Jan 2013

8,628

113.868

Dec 2012

8,116

115.079

Nov 2012

7,994

115.515

Oct 2012

7,870

116.045

Sep 2012

8,110

115.678

Aug 2012

7,842

116.214

Jul 2012

8,316

116.131

Jun 2012

8,394

116.024

May 2012

7,837

114.634

Apr 2012

7,694

113.999

Mar 2012

7,867

113.916

Feb 2012

8,455

112.587

Jan 2012

8,918

111.879

Dec 2011

8,428

113.050

Nov 2011

8,271

113.138

Oct 2011

8,258

113.456

Sep 2011

8,541

112.980

Aug 2011

8,604

114.286

Jul 2011

8,514

113.759

Jun 2011

8,738

113.255

May 2011

8,270

112.618

Apr 2011

8,425

111.844

Mar 2011

8,737

111.186

Feb 2011

8,749

110.731

Jan 2011

9,187

110.373

Dec 2010

9,205

111.207

Nov 2010

8,670

111.348

Oct 2010

8,408

112.342

Sep 2010

8,628

112.385

Aug 2010

8,628

113.508

Jul 2010

8,737

113.974

Jun 2010

8,867

113.856

May 2010

8,513

112.809

Apr 2010

8,921

111.391

Mar 2010

9,343

109.877

Feb 2010

9,282

109.100

Jan 2010

9,290

108.777 (low)

Dec 2009

9,354 (high)

109.875

Nov 2009

8,894

111.274

Oct 2009

8,474

111.599

Sep 2009

8,255

111.991

Aug 2009

8,835

113.863

Jul 2009

9,103

114.184

Jun 2009

9,301

114.014

May 2009

8,785

113.083

Apr 2009

8,648

112.746

Mar 2009

9,305

112.215

Feb 2009

9,170

112.947

Jan 2009

8,829

113.815

Dec 2008

8,250

116.422

Nov 2008

7,135

118.432

Oct 2008

6,267

120.020

Sep 2008

5,701

120.213

Aug 2008

5,736

121.556

Jul 2008

6,054

122.378

Jun 2008

5,697

121.845

May 2008

5,096

120.809

Apr 2008

5,071

120.027

Mar 2008

5,038

119.875

Feb 2008

5,114

119.452

Jan 2008

5,340

119.332

Dec 2007

4,750

121.042

Nov 2007

4,374

121.846

Oct 2007

4,028

122.006

Sep 2007

4,137

121.728

Aug 2007

4,494

122.870

Jul 2007

4,516

123.219 (high)

Jun 2007

4,469

122.150

May 2007

4,315

120.846

Apr 2007

4,205

119.609

Mar 2007

4,384

119.640

Feb 2007

4,417

119.041

Jan 2007

4,726

119.094

Dec 2006

4,281

120.371

Nov 2006

4,054

120.507

Oct 2006

4,010

121.199

Sep 2006

3,735 (low)

120.780

Aug 2006

4,104

121.979

Jul 2006

4,450

121.951

Jun 2006

4,456

121.070

May 2006

3,968

118.925

Apr 2006

3,787

118.559

Mar 2006

4,097

117.693

Feb 2006

4,403

116.823

Jan 2006

4,597

116.395

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

People lose their marketable job skills after prolonged unemployment and find increasing difficulty in finding another job. Chart I-18 shows the sharp rise in unemployed over 27 weeks and stabilization at an extremely high level.

clip_image030

Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2013

Sources: US Bureau of Labor Statistics

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

Another segment of U6 consists of people marginally attached to the labor force who continue to seek employment but less frequently on the frustration there may not be a job for them. Chart I-19 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.

clip_image031

Chart I-19, US, Marginally Attached to the Labor Force, NSA Month 2001-2013

Sources: US Bureau of Labor Statistics

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

IA3 Ten Million Fewer Full-time Jobs. Chart I-20 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 2013 with fluctuations around the typical behavior of a stationary series: there is no improvement in the United States in creating full-time jobs.

clip_image004[1]

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2013

Sources: US Bureau of Labor Statistics

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

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2013. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

clip_image005[1]

Chart I-20A, US, Noninstitutional Civilian Population, 2001-2013

Sources: US Bureau of Labor Statistics

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

Chart I-20B provides number of full-time jobs in the US from 1968 to 2013. There were multiple recessions followed by expansions without contraction of full-time jobs without recovery as during the period after 2008.

clip_image006[1]

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2013

Sources: US Bureau of Labor Statistics

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

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2013. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

clip_image007[1]

Chart I-20C, US, Noninstitutional Civilian Population, 1968-2013

Sources: US Bureau of Labor Statistics

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

IA4 Youth Unemployment and Middle-Aged Unemployment. The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs and to 17.834 million in 2012 or 2.207 million fewer jobs. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.914 million in Jul 2006 with 19.461 million in Jul 2012 for 2.453 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 19.406 million in Apr 2006 to 17.593 million in Apr 2013 or by 1.813 million. There are two hardships behind these data. First, young people cannot find employment after finishing high-school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

Table I-10, US, Employment Level 16-24 Years, Thousands, NSA

Year

Jan

Feb

Mar

Apr

Dec

Annual

2001

19678

19745

19800

19778

19547

20088

2002

18653

19074

19091

19108

19394

19683

2003

18811

18880

18709

18873

19136

19351

2004

18852

18841

18752

19184

19619

19630

2005

18858

18670

18989

19071

19733

19770

2006

19003

19182

19291

19406

20129

20041

2007

19407

19415

19538

19368

19361

19875

2008

18724

18546

18745

19161

18378

19202

2009

17467

17606

17564

17739

16615

17601

2010

16166

16412

16587

16764

16727

17077

2011

16512

16638

16898

16970

17234

17362

2012

16944

17150

17301

17387

17604

17834

2013

17183

17257

17271

17593

   

Sources: US Bureau of Labor Statistics

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

Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2013. Employment level is sharply lower in Apr 2013 relative to the peak in 2007.

clip_image008[1]

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2013

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

Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million and 3451 thousand in 2012 or by 1.109 million. The unemployment level ages 16 to 24 years rose from 2.074 million in Apr 2007 to 3.129 million in Apr 2013 or by 1.055 million. This situation may persist for many years.

Table I-11, US, Unemployment Level 16-24 Years, Thousands NSA

Year

Jan

Feb

Mar

Apr

Dec

Annual

2001

2250

2258

2253

2095

2412

2371

2002

2754

2731

2822

2515

2374

2683

2003

2748

2740

2601

2572

2248

2746

2004

2767

2631

2588

2387

2294

2638

2005

2661

2787

2520

2398

2055

2521

2006

2366

2433

2216

2092

2007

2353

2007

2363

2230

2096

2074

2323

2342

2008

2633

2480

2347

2196

2928

2830

2009

3278

3457

3371

3321

3532

3760

2010

3983

3888

3748

3803

3352

3857

2011

3851

3696

3520

3365

3161

3634

2012

3416

3507

3294

3175

3153

3451

2013

3674

3449

3261

3129

   

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

Chart I-22 provides the unemployment level ages 16 to 24 from 2002 to 2012. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013.

clip_image009[1]

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2013

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

Table I-12 provides the rate of unemployment of young peoples in ages 16 to 24 years. The annual rate jumped from 10.5 percent in 2007 to 18.4 percent in 2010, 17.3 percent in 2011 and 16.2 percent in 2012. During the seasonal peak in Jul the rate of youth unemployed was 18.1 percent in Jul 2011 and 17.1 percent in Jul 2012 compared with 10.8 percent in Jul 2007.

Table I-12, US, Unemployment Rate 16-24 Years, Thousands, NSA

Year

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Annual

2001

10.3

10.3

10.2

9.6

10.0

11.6

10.5

10.7

10.6

2002

12.9

12.5

12.9

11.6

11.6

13.2

12.4

11.5

12.0

2003

12.7

12.7

12.2

12.0

13.0

14.8

13.3

11.9

12.4

2004

12.8

12.3

12.1

11.1

12.2

13.4

12.3

11.1

11.8

2005

12.4

13.0

11.7

11.2

11.9

12.6

11.0

10.8

11.3

2006

11.1

11.3

10.3

9.7

10.2

11.9

11.2

10.4

10.5

2007

10.9

10.3

9.7

9.7

10.2

12.0

10.8

10.5

10.5

2008

12.3

11.8

11.1

10.3

13.3

14.4

14.0

13.0

12.8

2009

15.8

16.4

16.1

15.8

18.0

19.9

18.5

18.0

17.6

2010

19.8

19.2

18.4

18.5

18.4

20.0

19.1

17.8

18.4

2011

18.9

18.2

17.2

16.5

17.5

18.9

18.1

17.5

17.3

2012

16.8

17.0

16.0

15.4

16.3

18.1

17.1

16.8

16.2

2013

17.6

16.7

15.9

15.1

         

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

Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2002 to 2013. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels during the fourteen consecutive quarters of expansion of the economy since IIIQ2009 because of much lower growth at 2.1 percent annual equivalent on (Table I -5 http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The average of 7.8 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 3.2 percent obtained by diving GDP of $13,103.5 billion in IIIQ2010 by GDP of $12,701.0 billion in IIQ2009 {[$13.103.5/$12,701.0 -1]100 = 3.2%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.7 percent and at 7.7 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html).

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Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2013

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

Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2013. The rate of youth unemployment rose to 20 percent during the contractions of the early 1980s and also during the contraction of the global recession in 2008 and 2009. The data illustrate again the argument in this blog that the contractions of the early 1980s are the valid framework for comparison with the global recession of 2008 and 2009 instead of misleading comparisons with the 1930s. During the initial phase of recovery, the rate of youth unemployment 16 to 24 years NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984 while the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 17.5 percent in Dec 2009, 16.7 percent in Dec 2010, 15.5 percent in Dec 2011, 15.2 percent in Dec 2012, 17.6 percent in Jan 2013, 16.7 percent in Feb 2013, 15.9 percent in Mar 2013 and 15.1 percent in Apr 2013. In Jul 2007, the rate of youth unemployment was 10.8 percent, increasing to 17.1 percent in Jul 2012. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.1 percent on average during the first fourteen quarters of expansion from IIIQ2009 to IQ2013 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html). The fractured US labor market denies an early start for young people.

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Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2013

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

It is more difficult to move to other jobs after a certain age because of fewer available opportunities for matured individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.985 million in Jul 2006 to 4.821 million in July 2010 or by 142.9 percent. The number of unemployed ages 45 years and over declined to 4.405 million in Jul 2012 that is still higher by 121.9 percent than in Jul 2006. The number unemployed age 45 and over jumped from 1.794 million in Dec 2006 to 4.762 million in Dec 2010 or 165.4 percent and at 3.927 million in Dec 2012 is higher by 2.133 million or 118.9 percent higher than 1.794 million in Dec 2006. The level of unemployment of those aged 45 year or more of 3.689 million in Apr 2013 is higher by 1.846 million than 1.843 million in Apr 2006 or higher by 100.2 percent.

Table I-13, US, Unemployment Level 45 Years and Over, Thousands NSA

Year

Jan

Feb

Mar

Apr

Nov

Dec

2000

1498

1392

1291

1062

1242

1217

2001

1572

1587

1533

1421

1786

1901

2002

2235

2280

2138

2101

2013

2210

2003

2495

2415

2485

2287

2132

2130

2004

2453

2397

2354

2160

2053

2086

2005

2286

2286

2126

1939

1920

1963

2006

2126

2056

1881

1843

1704

1794

2007

2155

2138

2031

1871

1925

2120

2008

2336

2336

2326

2104

3078

3485

2009

4138

4380

4518

4172

4655

4960

2010

5314

5307

5194

4770

4909

4762

2011

5027

4837

4748

4373

4195

4182

2012

4458

4472

4390

4037

3861

3927

2013

4394

4107

3929

3689

   

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

Chart I-25 provides the level unemployed ages 45 years and over. There was sharp increase during the global recession and inadequate decline. There was an increase during the 2001 recession and then stability. The US is facing a major challenge of reemploying middle-aged workers.

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Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2013

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

IB 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 IVQ2012: (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; Pelaez 1979, 26-8). 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 preceding, 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 of skills of the relationship banker converts 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 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. Congress established the Federal Home Loan Bank (FHLB) system 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 Germany. 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”. William R. Summerhill, Jr. (2007SC, 2007IR) has filled this void in scholarly research on nineteenth-century Brazil. 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 and 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 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 [Cameron 1967], 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 cycle: (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 IB-1 provides the data required for broader comparison of the cyclical expansions of IQ1983 to IIIQ1986 and the current one from 2009 to 2012. First, in the 13 quarters from IQ1983 to IQ1986: GDP increased 19.6 percent at the annual equivalent rate of 5.7 percent; real disposable personal income (RDPI) increased 14.9 percent at the annual equivalent rate of 4.4 percent; RDPI per capita increased 11.9 percent at the annual equivalent rate of 3.5 percent; and population increased 2.7 percent at the annual equivalent rate of 0.8 percent. In the 15 quarters from IQ1983 to IQ1II986: GDP increased 21.3 percent at the annual equivalent rate of 5.3 percent; real disposable personal income (RDPI) increased 16.9 percent at the annual equivalent rate of 4.2 percent; RDPI per capita increased 13.3 percent at the annual equivalent rate of 3.4 percent; and population increased 3.2 percent at the annual equivalent rate of 0.8 percent Second, in the 15 quarters of the current cyclical expansion from IIIQ2009 to IQ2013, GDP increased 8.3 percent at the annual equivalent rate of 2.1 percent. In the 15 quarters of cyclical expansion: real disposable personal income (RDPI) increased 5.6 percent at the annual equivalent rate of 1.5 percent; RDPI per capita increased 2.9 percent at the annual equivalent rate of 0.8 percent; and population increased 2.6 percent at the annual equivalent rate of 0.7 percent. Third, since the beginning of the recession in IVQ2007 to IQ2013, GDP increased 3.2 percent, or barely above the level before the recession. Since the beginning of the recession in IVQ2007 to IQ2013, real disposable personal income increased 5.0 percent at the annual equivalent rate of 0.9 percent; population increased 4.2 percent at the annual equivalent rate of 0.8 percent; and real disposable personal income per capita is 0.6 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 IB-1, US, GDP, Real Disposable Personal Income, Real Disposable Income per Capita and Population in 1983-85 and 2007-2012, %

 

# Quarters

∆%

∆% Annual Equivalent

IQ1983 to IQ1986

IQ1983 to IIIQ1986

13

15

   

GDP

IQ1983 to IVQ1985

IQ1983 to IIIQ1986

13

15

19.6

21.3

5.7

5.3

RDPI

IQ1983 to IQ1986

IQ1983 to IIIQ1986

13

15

14.9

16.9

4.4

4.2

RDPI Per Capita

IQ1983 to IVQ1986

IQ1983 to IIIQ1986

13

15

11.9

13.3

3.5

3.4

Population

IQ1983 to IQ1986

IQ1983 to IIIQ1986

13

15

2.7

3.2

0.8

0.8

IIIQ2009 to IQ2013

15

   

GDP

 

8.3

2.1

RDPI

 

5.6

1.5

RDPI per Capita

 

2.9

0.8

Population

 

2.6

0.7

IVQ2007 to IQ2013

22

   

GDP

 

3.2

0.6

RDPI

 

5.0

0.9

RDPI per Capita

 

-0.6

NA

Population

 

4.2

0.8

RDPI: Real Disposable Personal Income

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

There are seven 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 and IIIQ1986, including contractions and expansions, but is well below trend in the entire business cycle from IVQ2007 to IQ2013, including contractions and expansions; (2) per capita real disposable income exceeded trend growth in the 1980s but is substantially below trend in IQ2013; (3) the number of employed persons increased in the 1980s but declined into IQ2013; (4) the number of full-time employed persons increased in the 1980s but declined into IQ2013; (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; (6) wealth of households and nonprofit organizations soared in the 1980s but declined in real terms into IVQ2012; and (7) gross private domestic investment increased sharply from IQ1980 to IVQ1985 and IIIQ1986 but gross private domestic investment and private fixed investment have fallen sharply from IVQ2007 to IQ2013. 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 IB-2 provides data for analysis of these seven basic facts. The seven blocks of Table IB-2 are separated initially after individual discussion of each one followed by the full Table IB-2.

1. Trend Growth.

i. As shown in Table IB-2, actual GDP grew cumulatively 20.5 percent from IQ1980 to IIIQ1986, which is relatively close to what trend growth would have been at 22.9 percent. Rapid growth at 5.7 percent annual rate on average per quarter during the expansion from IQ1983 to IQ1986 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 IQ2013 was 3.2 percent while trend growth would have been 17.7 percent. GDP in IQ2013 at seasonally adjusted annual rate is estimated at $13,750.1 billion by the Bureau of Economic Analysis (BEA) (http://www.bea.gov/iTable/index_nipa.cfm) and would have been $15,684.7 billion, or $1,935 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 $1.9 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 IQ2013 after the recession from IVQ2007 to IIQ2009. The United States has acquired a heavy social burden of unemployment and underemployment of 28.6 million people or 17.6 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html) 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 243.284 million in 2012 or by 4.9 percent while the labor force increased from 153.124 million in 2007 to 154.975 million in 2012 or by 1.2 percent and only by 0.3 percent to 153.617 million in 2011 while population increased 3.3 percent from 231.867 million in 2007 to 239.618 million in 2011 (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 (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html). Structural change in demography occurs over relatively long periods and not suddenly as shown by Edward P. Lazear and James R. Spletzer (2012JHJul22).

Period IQ1980 to IIIQ1986

 

GDP SAAR USD Billions

 

    IQ1980

5,903.4

    IIIQ1986

7,112.9

∆% IQ1980 to IIIQ1986 (21.3 percent from IVQ1982 $5866.0 billion)

20.5

∆% Trend Growth IQ1980 to IIIQ1986

22.9

Period IVQ2007 to IQ2013

 

GDP SAAR USD Billions

 

    IVQ2007

13,326.0

    IVQ2012

13,750.1

∆% IVQ2007 to IVQ2012 Actual

3.2

∆% IVQ2007 to IQ2013 Trend

17.7

2. Decline of Per Capita Real Disposable Income

i. In the entire business cycle from IQ1980 to IIIQ1986, as shown in Table IB-2 trend growth of per capita real disposable income, or what is left per person after inflation and taxes, grew cumulatively 17.0 percent, which is close to what would have been trend growth of 14.9 percent.

ii. In contrast, in the entire business cycle from IVQ2007 to IQ2013, per capita real disposable income fell 0.6 percent while trend growth would have been 11.5 percent. Income available after inflation and taxes is about the same or lower as before the contraction after 15 consecutive quarters of GDP growth at mediocre rates relative to those prevailing during historical cyclical expansions. In IQ2013, personal income fell at the SAAR of minus 3.2 percent; real personal income excluding current transfer receipts at minus 5.8 percent; and real disposable personal income at minus 5.3 percent (Table 5 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf). The BEA explains as follows (page 3 at http://www.bea.gov/newsreleases/national/pi/2013/pdf/pi0313.pdf):

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

Period IQ1980 to IIIQ1986

 

Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD

18,938

Real Disposable Personal Income per Capita IQ1II986 Chained 2005 USD

22,165

∆% IQ1980 to IIIQ1986

17.0

∆% Trend Growth

14.9

Period IVQ2007 to IQ2013

 

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD

32,837

Real Disposable Personal Income per Capita IQ2013 Chained 2005 USD

32,640

∆% IVQ2007 to IQ2013

-0.6

∆% Trend Growth

11.5

3. Number of Employed Persons

i. As shown in Table IB-2, the number of employed persons increased over the entire business cycle from 98.527 million not seasonally adjusted (NSA) in IQ1980 to 110.229 million NSA in IIIQ1986 or by 11.9 percent.

ii. In contrast, during the entire business cycle the number employed fell from 146.334 million in IVQ2007 to 142.698 million in IQ2013 or by 2.5 percent. There are 28.6 million persons unemployed or underemployed, which is 17.6 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html).

Period IQ1980 to IIIQ1986

 

Employed Millions IQ1980 NSA End of Quarter

98.527

Employed Millions IIIQ1986 NSA End of Quarter

110.229

∆% Employed IQ1980 to IIIQ1986

11.9

Period IVQ2007 to IQ2013

 

Employed Millions IVQ2007 NSA End of Quarter

146.334

Employed Millions IQ2013 NSA End of Quarter

142.698

∆% Employed IVQ2007 to IQ2013

-2.5

4. Number of Full-Time Employed Persons

i. As shown in Table IB-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 91.579 million NSA in IIIQ1986 or 12.7 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 114.796 million in IQ2013 or by minus 5.2 percent.

Period IQ1980 to IIIQ1986

 

Employed Full-time Millions IQ1980 NSA End of Quarter

81.280

Employed Full-time Millions IIIQ1986 NSA End of Quarter

91.579

∆% Full-time Employed IQ1980 to IIIQ1986

12.7

Period IVQ2007 to IQ2013

 

Employed Full-time Millions IVQ2007 NSA End of Quarter

121.042

Employed Full-time Millions IQ2013 NSA End of Quarter

114.796

∆% Full-time Employed IVQ2007 to IQ2013

-5.2

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

i. As shown in Table IB-2 and in the following block, in the cycle from IQ1980 to IIIQ1986: (a) the rate of unemployment was virtually the same at 6.8 percent in IIIQ1986 relative to 6.6 percent in IQ1980; (b) the number unemployed increased from 6.983 million in IQ1980 to 8.015 million in IIIQ1986 or 14.8 percent; and (c) the number employed part-time for economic reasons increased 44.7 percent from 3.624 million in IQ1980 to 5.245 million in IIIQ1986.

ii. In contrast, in the economic cycle from IVQ2007 to IVQ2012: (a) the rate of unemployment increased from 4.8 percent in IVQ2007 to 7.6 percent in IQ2013; (b) the number unemployed increased 60.3 percent from 7.371 million in IVQ2007 to 11.815 million in IQ2013; (c) the number employed part-time for economic reasons increased 62.8 percent from 4.750 million in IVQ2007 to 7.734 million in IQ2013; 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 13.9 percent in IQ2013.

Period IQ1980 to IIIQ1986

 

Unemployment Rate IQ1980 NSA End of Quarter

6.6

Unemployment Rate  IIIQ1986 NSA End of Quarter

6.8

Unemployed IQ1980 Millions End of Quarter

6.983

Unemployed IIIQ1986 Millions End of Quarter

8.015

Employed Part-time Economic Reasons Millions IQ1980 End of Quarter

3.624

Employed Part-time Economic Reasons Millions IIIQ1986 End of Quarter

5.245

∆%

44.7

Period IVQ2007 to IQ2013

 

Unemployment Rate IVQ2007 NSA End of Quarter

4.8

Unemployment Rate IQ2013 NSA End of Quarter

7.6

Unemployed IVQ2007 Millions End of Quarter

7.371

Unemployed IQ2013 Millions End of Quarter

11.815

∆%

60.3

Employed Part-time Economic Reasons IVQ2007 Millions End of Quarter

4.750

Employed Part-time Economic Reasons Millions IQ2013 End of Quarter

7.734

∆%

62.8

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

IQ2013

13.9

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 IIIQ2012 is provided in the following block and in Table IB-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 Table IB-2, net worth of households and nonprofit organizations fell from $66,118.3 billion in IVQ2007 to $66,071.7 billion in IVQ2012 by $46.6 billion or 0.1 percent. The US consumer price index was 210.036 in Dec 2007 and 229.601 in Dec 2012 for increase of 9.1 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 8.4 percent in Dec 2012 after 14 consecutive quarters of expansion from IIIQ2009 to IVQ2012 relative to IVQ2007 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 IVQ2012 has been 2.1 percent, which is substantially lower than the average of 5.7 percent in the expansion from IQ1983 to IQ1986 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html). Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions. US wealth of households and nonprofit organizations grew from IVQ1945 at $710,125.9 million to IIIQ2009 at $64,768,835.3 million or increase of 9,020.8 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 231.407 in Sep 2012 or 1,171.5 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 67 years with inflation adjusted increase of 617.3 percent. The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIQ2009 caused sharp contraction of US household and nonprofit net worth. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 67 years when US GDP grew at 2.1 percent on average in 14 quarters between IIIQ2009 and IVQ2012 in contrast with average 5.7 percent from IQ1983 to IQ1986. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html).

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 IIIQ2012

 

Net Worth of Households and Nonprofit Organizations USD Billions

 

IVQ2007

66,118.3

IVQ2012

66,071.7

∆ USD Billions

-46.6

7. Gross Private Domestic Investment.

i. The comparison of gross private domestic investment in the entire economic cycles from IQ1980 to IIIIQ1986 and from IVQ2007 to IQ2013 is provided in the following block and in Table IB-2. Gross private domestic investment increased from $778.3 billion in IQ1980 to $913.0 billion in IIIQ1986 or by 17.3 percent.

ii In the current cycle, gross private domestic investment decreased from $2,123.6 billion in IVQ2007 to $1,991.8 billion in IQ2013, or decline by 6.2 percent. Private fixed investment fell from $2,111.5 billion in IVQ2007 to $1,925.5 billion in IQ2013, or decline by 8.8 percent.

Period IQ1980 to IIIQ1986

 

Gross Private Domestic Investment USD 2005 Billions

 

IQ1980

778.3

IIIQ1986

913.0

∆%

17.3

Period IVQ2007 to IQ2013

 

Gross Private Domestic Investment USD Billions

 

IVQ2007

2,123.6

IQ2013

1,991.8

∆%

-6.2

Private Fixed Investment USD 2005 Billions

 

IVQ2007

2,111.5

IQ2013

1,925.5

∆%

-8.8

Table IB-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 IIIQ1986

 

GDP SAAR USD Billions

 

    IQ1980

5,903.4

    IIIQ1986

7,112.9

∆% IQ1980 to IIIQ1986 (21.3 percent from IVQ1982 $5866.0 billion)

20.5

∆% Trend Growth IQ1980 to IIIQ1986

22.9

Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD

18,938

Real Disposable Personal Income per Capita IIIQ1986 Chained 2005 USD

22,165

∆% IQ1980 to IIIQ1986

17.0

∆% Trend Growth

14.9

Employed Millions IQ1980 NSA End of Quarter

98.527

Employed Millions III1986 NSA End of Quarter

110.229

∆% Employed IQ1980 to IIIQ1986

11.9

Employed Full-time Millions IQ1980 NSA End of Quarter

81.280

Employed Full-time Millions IIIIQ1986 NSA End of Quarter

91.579

∆% Full-time Employed IQ1980 to IIIQ1986

12.7

Unemployment Rate IQ1980 NSA End of Quarter

6.6

Unemployment Rate  IIIQ1986 NSA End of Quarter

6.8

Unemployed IQ1980 Millions NSA End of Quarter

6.983

Unemployed IIIQ1986 Millions NSA End of Quarter

8.015

∆%

16.3

Employed Part-time Economic Reasons IQ1980 Millions NSA End of Quarter

3.624

Employed Part-time Economic Reasons Millions IIIQ1986 NSA End of Quarter

5.245

∆%

44.7

Net Worth of Households and Nonprofit Organizations USD Billions

 

IVQ1979

8,326.4

IVQ1985

14,395.2

∆ USD Billions

+6,068.8

Gross Private Domestic Investment USD 2005 Billions

 

IQ1980

778.3

IQ1986

913.0

∆%

17.3

Period IVQ2007 to IQ2013

 

GDP SAAR USD Billions

 

    IVQ2007

13,326.0

    IQ2013

13,750.1

∆% IVQ2007 to IVQ2012

3.2

∆% IVQ2007 to IQ2013 Trend Growth

17.7

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD

32,837

Real Disposable Personal Income per Capita IQ2013 Chained 2005 USD

32,640

∆% IVQ2007 to IQ2013

-0.6

∆% Trend Growth

11.5

Employed Millions IVQ2007 NSA End of Quarter

146.334

Employed Millions IQ2013 NSA End of Quarter

142.698

∆% Employed IVQ2007 to IQ2013

-2.5

Employed Full-time Millions IVQ2007 NSA End of Quarter

121.042

Employed Full-time Millions IQ2013 NSA End of Quarter

114.796

∆% Full-time Employed IVQ2007 to IQ2013

-5.2

Unemployment Rate IVQ2007 NSA End of Quarter

4.8

Unemployment Rate IQ2013 NSA End of Quarter

7.6

Unemployed IVQ2007 Millions NSA End of Quarter

7.371

Unemployed IQ2013 Millions NSA End of Quarter

11.815

∆%

60.3

Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter

4.750

Employed Part-time Economic Reasons Millions IQ2013 NSA End of Quarter

7.734

∆%

62.8

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

IQ2013

13.9

Net Worth of Households and Nonprofit Organizations USD Billions

 

IVQ2007

66,118.3

IVQ2012

66,071.7

∆ USD Billions

-46.6

Gross Private Domestic Investment USD Billions

 

IVQ2007

2,123.6

IQ2013

1,991.8

∆%

-6.2

Private Fixed Investment USD 2005 Billions

 

IVQ2007

2,111.5

IQ2013

1,925.5

∆%

-8.8

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.

The Congressional Budget Office (CBO 2013BEOFeb5) estimates potential GDP, potential labor force and potential labor productivity provided in Table IB-3. The average rate of growth of potential GDP from 1950 to 2012 is estimated at 3.3 percent per year. The projected path is significantly lower at 2.2 percent per year from 2012 to 2023. The legacy of the economic cycle with expansion from IIIQ2009 to IQ2013 at 2.1 percent on average in contrast with 5.7 percent on average in the expansion (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states_28.html) may perpetuate unemployment and underemployment estimated at 28.6 million or 17.6 percent of the effective labor force in Apr 2013 (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html) with much lower hiring than in the period before the current cycle (Section I).

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

 

Potential GDP

Potential Labor Force

Potential Labor Productivity*

Average Annual ∆%

     

1950-1973

3.9

1.6

2.3

1974-1981

3.3

2.5

0.8

1982-1990

3.1

1.6

1.5

1991-2001

3.1

1.3

1.8

2002-2012

2.2

0.8

1.4

Total 1950-2012

3.3

1.5

1.7

Projected Average Annual ∆%

     

2013-2018

2.2

0.6

1.6

2019-2023

2.3

0.5

1.8

2012-2023

2.2

0.5

1.7

*Ratio of potential GDP to potential labor force

Source: CBO (2013BEOFeb5).

Chart IB-1 of the Congressional Budget Office (CBO 2013BEOFeb5) provides actual and potential GDP of the United States from 2000 to 2011 and projected to 2024. Lucas (2011May) estimates trend of United States real GDP of 3.0 percent from 1870 to 2010 and 2.2 percent for per capita GDP. The United States successfully returned to trend growth of GDP by higher rates of growth during cyclical expansion as analyzed by Bordo (2012Sep27, 2012Oct21) and Bordo and Haubrich (2012DR). Growth in expansions following deeper contractions and financial crises was much higher in agreement with the plucking model of Friedman (1964, 1988). The unusual weakness of growth at 2.1 percent on average from IIIQ2009 to IVQ2012 during the current economic expansion in contrast with 5.7 percent on average in the cyclical expansion from IQ1983 to IQ1986 (http://cmpassocregulationblog.blogspot.com/2013/04/mediocre-and-decelerating-united-states.html) cannot be explained by the contraction of 4.7 of GDP from IVQ2007 to IIQ2009 and the financial crisis. Weakness of growth in the expansion is perpetuating unemployment and underemployment of 28.6 million or 17.6 percent of the labor as estimated for Apr 2013 (http://cmpassocregulationblog.blogspot.com/2013/05/twenty-nine-million-unemployed-or.html) and the collapse of hiring (Section I).

clip_image032

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

Source: Congressional Budget Office, CBO (2013BEOFeb5).

II United States International Trade. Table IIA-1 provides the trade balance of the US and monthly growth of exports and imports seasonally adjusted with the latest release and revisions (http://www.census.gov/foreign-trade/). Because of heavy dependence on imported oil, fluctuations in the US trade account originate largely in fluctuations of commodity futures prices caused by carry trades from zero interest rates into commodity futures exposures in a process similar to world inflation waves (http://cmpassocregulationblog.blogspot.com/2013/04/world-inflation-waves-squeeze-of.html). Data for 2012 have been revised. The US trade balance improved from deficit of $51,726 million in Mar 2012 to deficit of $49,726 million in Apr 2012 and lower deficits of $47,009 million in May, $40,921 million in Jun and $41,944 million in Jul 2012 but with increase to 42,552 million in Aug 2012. The trade deficits of Mar and Apr 2012 both end in 726 in actual data. The increase of exports in Sep 2012 of 3.1 percent was higher than increase of imports of 1.5 percent, resulting in decrease of the trade deficit in Sep to $40,345 million. Exports decreased 3.4 percent in Oct 2012 and imports decreased 2.1 percent for increase in the trade deficit to $42,046 million in Oct 2012. The increase of exports by 1.2 percent in Nov 2012 was much lower than the increase in imports of 3.8 percent, resulting in sharply increasing deficit of $48,228 million. Export growth of 2.2 with decline of imports by 2.6 resulted in lower trade deficit of $38,144 million in Dec 2012. The trade deficit increased to $44,460 million in Jan 2013 with decrease of exports of 1.2 percent while imports increased 1.8 percent. Growth of exports of 0.8 percent in Feb 2013 with zero growth of imports reduced the trade deficit to $42,960 million. The trade deficit fell to $38,829 million in Mar 2013 with decline of exports of 0.9 percent while imports fell 2.5 percent. The deterioration of the trade deficit from $44,586 million in Feb 2012 to $51,726 million in Mar 2012 resulted from growth of exports of 2.5 percent while imports jumped 5.2 percent. The US trade balance had improved from deficit of $52,288 million in Jan 2012 to lower deficit of $44,586 million in Feb 2012 mostly because of decline of imports by 2.7 percent while exports increased 0.9 percent. The US trade balance deteriorated sharply from Nov 2011 to Jan 2012 with growth of imports by cumulative 2.9 percent and cumulative change of exports of 0.0 percent, resulting in deficits of $48,835 million in Nov 2011, $51,748 million in Dec 2011 and $52,288 million in Jan 2012, which are the highest since $50,234 million in Jun 2011. In the months of Jun to Oct 2011, exports increased 1.8 percent while imports increased 0.5 percent, resulting in improvement of the trade deficit from $50,234 million in Jun 2011 to $45,703 million in Oct 2011. The trade balance deteriorated from cumulative deficit of $494,737 million in Jan-Dec 2010 to deficit of $559,880 million in Jan-Dec 2011 and virtually no change to $539,514 million in Jan-Dec 2012.

Table IIA-1, US, Trade Balance of Goods and Services Seasonally Adjusted Millions of Dollars and ∆%  

 

Trade Balance

Exports

Month ∆%

Imports

Month ∆%

Mar 2013

-38,829

184,276

-0.9

223,105

-2.5

Feb

-42,960

185,963

0.8

228,923

0.0

Jan

-44,460

184,401

-1.2

228,862

1.8

Dec 2012

-38,144

186,630

2.2

224,774

-2.6

Nov

-48,228

182,526

1.2

230,753

3.8

Oct

-42,046

180,279

-3.4

222,325

-2.1

Sep

-40,345

186,653

3.1

226,998

1.5

Aug

-42,552

181,117

-0.9

223,668

-0.4

Jul

-41,944

182,689

-1.5

224,634

-0.8

Jun

-40,921

185,550

1.3

226,471

-1.6

May

-47,009

183,109

0.4

230,118

-0.9

Apr

-49,726

182,468

-1.2

232,194

-1.8

Mar

-51,726

184,685

2.5

236,412

5.2

Feb

-44,586

180,166

0.9

224,751

-2.7

Jan

-52,288

178,619

0.5

230,907

0.6

Dec 2011

-51,748

177,751

0.6

229,499

1.8

Nov

-48,835

176,710

-1.1

225,545

0.5

Oct

-45,703

178,742

-1.0

224,445

-0.3

Sep

-44,467

180,629

1.3

225,096

0.9

Aug

-44,775

178,382

0.0

223,157

-0.3

Jul

-45,580

178,339

3.3

223,919

0.4

Jun

-50,234

172,664

-1.7

222,988

-0.2

May

-47,669

175,673

0.0

223,343

1.9

Apr

-43,556

175,662

0.9

219,218

0.1

Mar

-44,902

174,169

4.6

219,071

3.7

Feb

-44,801

166,545

-0.9

211,346

-2.0

Jan

-47,523

168,098

1.6

215,621

4.6

Dec 2010

-40,677

165,499

2.0

206,176

2.5

Jan-Dec 2012

-539,514

2,194,491

 

2,734,005

 

Jan-Dec
2011

-559,880

2,103,367

 

2,663,247

 

Jan-Dec
2010

-494,737

1,842,485

 

2,337,222

 

Note: Trade Balance of Goods and Services = Exports of Goods and Services less Imports of Goods and Services. Trade balance may not add exactly because of errors of rounding and seasonality. Source: US Census Bureau http://www.census.gov/foreign-trade/

Table IIA-2 provides the US international trade balance, exports and imports on an annual basis from 1992 to 2012. The trade balance deteriorated sharply over the long term. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US decreased from $117.9 billion in IVQ2011, or 3.1 percent of GDP to $111.9 billion in IVQ2012, or 2.8 percent of GDP (http://cmpassocregulationblog.blogspot.com/2013/03/recovery-without-hiring-ten-million.html). The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71). The last row of Table IIA-2 shows marginal improvement of the trade deficit from $559,880 million in 2011 to lower $539,514 million in 2012 with exports growing 4.4 percent and imports 2.7 percent. Growth and commodity shocks under alternating inflation waves (http://cmpassocregulationblog.blogspot.com/2013/04/world-inflation-waves-squeeze-of.html) have deteriorated the trade deficit from the low of $379,154 million in 2009.

Table IIA-2, US, International Trade Balance, Exports and Imports SA, Millions of Dollars and ∆%

 

Balance

Exports

Imports

1960

3,508

25,940

22,432

1961

4,195

26,403

22,208

1962

3,370

27,722

24,352

1963

4,210

29,620

25,410

1964

6,022

33,341

27,319

1965

4,664

35,285

30,621

1966

2,939

38,926

35,987

1967

2,604

41,333

38,729

1968

250

45,543

45,293

1969

91

49,220

49,129

1970

2,254

56,640

54,386

1971

-1,302

59,677

60,979

1972

-5,443

67,222

72,665

1973

1,900

91,242

89,342

1974

-4,293

120,897

125,190

1975

12,404

132,585

120,181

1976

-6,082

142,716

148,798

1977

-27,246

152,301

179,547

1978

-29,763

178,428

208,191

1979

-24,565

224,131

248,696

1980

-19,407

271,834

291,241

1981

-16,172

294,398

310,570

1982

-24,156

275,236

299,391

1983

-57,767

266,106

323,874

1984

-109,072

291,094

400,166

1985

-121,880

289,070

410,950

1986

-138,538

310,033

448,572

1987

-151,684

348,869

500,552

1988

-114,566

431,149

545,715

1989

-93,141

487,003

580,144

1990

-80,864

535,233

616,097

1991

-31,135

578,344

609,479

1992

-39,212

616,882

656,094

1993

-70,311

642,863

713,174

1994

-98,493

703,254

801,747

1995

-96,384

794,387

890,771

1996

-104,065

851,602

955,667

1997

-108,273

934,453

1,042,726

1998

-166,140

933,174

1,099,314

1999

-263,160

967,008

1,230,168

2000

-376,749

1,072,783

1,449,532

2001

-361,771

1,007,726

1,369,496

2002

-417,432

980,879

1,398,311

2003

-490,984

1,023,519

1,514,503

2004

-605,357

1,163,146

1,768,502

2005

-708,624

1,287,441

1,996,065

2006

-753,288

1,459,823

2,213,111

2007

-696,728

1,654,561

2,351,289

2008

-698,338

1,842,682

2,541,020

2009

-379,154

1,578,945

1,958,099

2010

-494,737

1,842,485

2,337,222

2011

-559,880

2,103,367

2,663,247

2012

-539,514

2,194,491

2,734,005

Source: US Census Bureau http://www.census.gov/foreign-trade/

Chart IIA-1 of the US Census Bureau of the Department of Commerce shows that the trade deficit (gap between exports and imports) fell during the economic contraction after 2007 but has grown again during the expansion. There was slight improvement at the margin from Jul to Oct 2011 but new increase in the gap from Nov 2011 to Jan 2012 and again in Mar 2012 as exports grow less rapidly than imports. There is improvement in Apr 2012 with imports declining at a faster rate of 1.8 percent than decline of exports by 1.2 percent and growth of exports of 0.4 percent in May 2012 with imports declining 0.9 percent. Further improvement occurred in Jun 2012 with imports increasing 1.3 percent and exports declining 1.6 percent. There was deterioration in Jul with exports declining 1.5 percent and imports only 0.8 percent but deterioration in Aug with exports decreasing 0.9 percent while imports declined only 0.4 percent. In Sep 2012, exports increased 3.1 percent while imports increased only 1.5 percent. Further deterioration occurred in Oct with exports declining 3.4 percent but imports falling 2.1 percent. The trade deficit widened sharply to $48,228 million in Nov 2012 with growth of imports by 3.8 percent while exports increased 1.2 percent. In Dec 2012, the trade deficit narrowed to $38,144 million with growth of exports of 2.2 percent while imports fell 2.6 percent. There was further deterioration in Jan 2013 with exports falling 1.2 percent while exports grew 1.8 percent. The trade balance improved in Feb with growth of exports of 0.8 percent while imports were unchanged. The deficit fell further to $38,829 in Mar 2013 with decline of exports by 0.9 percent while imports fell 2.5 percent. Weaker world and internal demand and fluctuating commodity price increases explain the declining or less dynamic changes in exports and imports in Chart IIA-1.

clip_image034

Chart IIA-1, US, International Trade Balance, Exports and Imports of Goods and Services USD Billions

Source: US Census Bureau

http://www.census.gov/briefrm/esbr/www/esbr042.html

Chart IIA-2 of the US Census Bureau provides the US trade account in goods and services SA from Jan 1992 to Mar 2013. There is a long-term trend of deterioration of the US trade deficit shown vividly by Chart IIA-2. The trend of deterioration was reversed by the global recession from IVQ2007 to IIQ2009. Deterioration resumed together with incomplete recovery and was influenced significantly by the carry trade from zero interest rates to commodity futures exposures (these arguments are elaborated in Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4 http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html). Earlier research focused on the long-term external imbalance of the US in the form of trade and current account deficits (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). US external imbalances have not been fully resolved and tend to widen together with improving world economic activity and commodity price shocks.

clip_image035

Chart IIA-2, US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-Mar 2013

Source: US Census Bureau

http://www.census.gov/foreign-trade/

Chart IIA-3 of the US Census Bureau provides US exports SA from Jan 1992 to Mar 2013. There was sharp acceleration from 2003 to 2007 during worldwide economic boom and increasing inflation. Exports fell sharply during the financial crisis and global recession from IVQ2007 to IIQ2009. Growth picked up again together with world trade and inflation but stalled in the final segment with less rapid global growth and inflation.

clip_image036

Chart IIA-3, US, Exports SA, Monthly, Millions of Dollars Jan 1992-Mar 2013

Source: US Census Bureau

http://www.census.gov/foreign-trade/

Chart IIA-4 of the US Census Bureau provides US imports SA from Jan 1992 to Mar 2013. Growth was stronger between 2003 and 2007 with worldwide economic boom and inflation. There was sharp drop during the financial crisis and global recession. There is stalling import levels in the final segment resulting from weaker world economic growth and diminishing inflation because of risk aversion.

clip_image037

Chart IIA-4, US, Imports SA, Monthly, Millions of Dollars Jan 1992-Mar 2013

Source: US Census Bureau

http://www.census.gov/foreign-trade/

The balance of international trade in goods of the US seasonally adjusted is shown in Table IIA-3. The US has a dynamic surplus in services that reduces the large deficit in goods for a still very sizeable deficit in international trade of goods and services. The balance in international trade of goods fell from $67.6 billion in Mar 2012 to $56.1 billion in Mar 2013. The improvement of the goods balance in Mar 2013 relative to Mar 2012 occurred mostly in the petroleum balance, exports less imports of petroleum, in the magnitude of decreasing the deficit by $7344 million, while there was improvement in the nonpetroleum balance, exports less imports of nonpetroleum goods, in the magnitude of decreasing the deficit by $3519 million. US terms of trade, export prices relative to import prices, and the US trade account fluctuate in accordance with the carry trade from zero interest rates to commodity futures exposures, especially oil futures. Exports decreased 1.2 percent with nonpetroleum exports decreasing 1.1 percent. Total imports decreased 6.5 percent with petroleum imports declining 20.7 percent and nonpetroleum imports decreasing 3.0 percent.

Table IIA-3, US, International Trade in Goods Balance, Exports and Imports $ Millions and ∆% SA

 

Mar 2013

Mar 2012

∆%

Total Balance

-56,143

-67,551

 

Petroleum

-21,133

-28,477

 

Non Petroleum

-34,759

-38,278

 

Total Exports

130,345

131,964

-1.2

Petroleum

9,664

10,367

-7.0

Non Petroleum

118,953

120,229

-1.1

Total Imports

186,489

199,515

-6.5

Petroleum

30,797

38,844

-20.7

Non Petroleum

153,712

158,508

-3.0

Details may not add because of rounding and seasonal adjustment

Source: US Census Bureau http://www.census.gov/foreign-trade/

US exports and imports of goods not seasonally adjusted in Jan-Mar 2013 and Jan-Mar 2012 are shown in Table IIA-4. The rate of growth of exports was 0.5 percent and minus 2.8 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that increased 6.3 percent and of mineral fuels that increased 1.2 percent both because higher prices of raw materials and commodities increase and fall recurrently as a result of shocks of risk aversion. The US exports an insignificant amount of crude oil. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports rose 1.0 percent while manufactured imports fell 0.1 percent. Significant part of the US trade imbalance originates in imports of mineral fuels decreasing 15.1 percent and petroleum decreasing 16.0 percent with wide oscillations in oil prices. The limited hedge in exports of agricultural commodities and mineral fuels compared with substantial imports of mineral fuels and crude oil results in waves of deterioration of the terms of trade of the US, or export prices relative to import prices, originating in commodity price increases caused by carry trades from zero interest rates. These waves are similar to those in worldwide inflation (http://cmpassocregulationblog.blogspot.com/2013/04/world-inflation-waves-squeeze-of.html).

Table IIA-4, US, Exports and Imports of Goods, Not Seasonally Adjusted Millions of Dollars and %

 

Jan-Mar 2013 $ Millions

Jan-Mar 2012 $ Millions

∆%

Exports

383,409

381,602

0.5

Manufactured

287,312

284,540

1.0

Agricultural
Commodities

37,194

35,005

6.3

Mineral Fuels

32,684

32,282

1.2

Petroleum

26,694

26,018

2.6

Imports

536,763

552,471

-2.8

Manufactured

430,101

430,666

-0.1

Agricultural
Commodities

26,722

26,787

-0.2

Mineral Fuels

92,917

109,477

-15.1

Petroleum

88,291

105,055

-16.0

Source: US Census Bureau http://www.census.gov/foreign-trade/

The G7 meeting in Washington on Apr 21 2006 of finance ministers and heads of central bank governors of the G7 established the “doctrine of shared responsibility” (G7 2006Apr):

“We, Ministers and Governors, reviewed a strategy for addressing global imbalances. We recognized that global imbalances are the product of a wide array of macroeconomic and microeconomic forces throughout the world economy that affect public and private sector saving and investment decisions. We reaffirmed our view that the adjustment of global imbalances:

  • Is shared responsibility and requires participation by all regions in this global process;
  • Will importantly entail the medium-term evolution of private saving and investment across countries as well as counterpart shifts in global capital flows; and
  • Is best accomplished in a way that maximizes sustained growth, which requires strengthening policies and removing distortions to the adjustment process.

In this light, we reaffirmed our commitment to take vigorous action to address imbalances. We agreed that progress has been, and is being, made. The policies listed below not only would be helpful in addressing imbalances, but are more generally important to foster economic growth.

  • In the United States, further action is needed to boost national saving by continuing fiscal consolidation, addressing entitlement spending, and raising private saving.
  • In Europe, further action is needed to implement structural reforms for labor market, product, and services market flexibility, and to encourage domestic demand led growth.
  • In Japan, further action is needed to ensure the recovery with fiscal soundness and long-term growth through structural reforms.

Others will play a critical role as part of the multilateral adjustment process.

  • In emerging Asia, particularly China, greater flexibility in exchange rates is critical to allow necessary appreciations, as is strengthening domestic demand, lessening reliance on export-led growth strategies, and actions to strengthen financial sectors.
  • In oil-producing countries, accelerated investment in capacity, increased economic diversification, enhanced exchange rate flexibility in some cases.
  • Other current account surplus countries should encourage domestic consumption and investment, increase micro-economic flexibility and improve investment climates.

We recognized the important contribution that the IMF can make to multilateral surveillance.”

The concern at that time was that fiscal and current account global imbalances could result in disorderly correction with sharp devaluation of the dollar after an increase in premiums on yields of US Treasury debt (see Pelaez and Pelaez, The Global Recession Risk (2007)). The IMF was entrusted with monitoring and coordinating action to resolve global imbalances. The G7 was eventually broadened to the formal G20 in the effort to coordinate policies of countries with external surpluses and deficits.

The database of the WEO (http://www.imf.org/external/pubs/ft/weo/2013/01/weodata/index.aspx) is used to contract Table IIA-5 with fiscal and current account imbalances projected for 2013 and 2015. The WEO finds the need to rebalance external and domestic demand (IMF 2011WEOSep xvii):

“Progress on this front has become even more important to sustain global growth. Some emerging market economies are contributing more domestic demand than is desirable (for example, several economies in Latin America); others are not contributing enough (for example, key economies in emerging Asia). The first set needs to restrain strong domestic demand by considerably reducing structural fiscal deficits and, in some cases, by further removing monetary accommodation. The second set of economies needs significant currency appreciation alongside structural reforms to reduce high surpluses of savings over investment. Such policies would help improve their resilience to shocks originating in the advanced economies as well as their medium-term growth potential.”

The IMF (2012WEOApr, XVII) explains decreasing importance of the issue of global imbalances as follows:

“The latest developments suggest that global current account imbalances are no longer expected to widen again, following their sharp reduction during the Great Recession. This is largely because the excessive consumption growth that characterized economies that ran large external deficits prior to the crisis has been wrung out and has not been offset by stronger consumption in surplus economies. Accordingly, the global economy has experienced a loss of demand and growth in all regions relative to the boom years just before the crisis. Rebalancing activity in key surplus economies toward higher consumption, supported by more market-determined exchange rates, would help strengthen their prospects as well as those of the rest of the world.”

Table IIA-5, Fiscal Deficit, Current Account Deficit and Government Debt as % of GDP and 2011 Dollar GDP

 

GDP
$B

2012

FD
%GDP
2013

CAD
%GDP
2013

Debt
%GDP
2013

FD%GDP
2015

CAD%GDP
2015

Debt
%GDP
2015

US

15685

-7.3

-3.1

80.3

-2.3

-3.2

88.3

Japan

5964

-9.1

2.0

126.6

-5.8

2.4

155.0

UK

2441

-5.8

-1.9

78.3

-0.8

-0.4

88.1

Euro

12198

-1.6

0.3

68.4

1.1

1.2

71.3

Ger

3401

0.7

5.7

56.1

1.4

4.3

52.4

France

2609

-2.9

-2.2

80.4

0.3

-0.8

83.8

Italy

2014

0.8

-3.2

99.6

4.4

-1.6

101.5

Can

1819

-4.1

-2.8

33.3

-1.1

-2.5

37.4

China

8227

-1.2

2.7

25.8

-0.1

3.4

14.8

Brazil

2396

3.3

-2.4

33.6

3.1

-3.3

30.8

Note: GER = Germany; Can = Canada; FD = fiscal deficit; CAD = current account deficit

FD is primary except total for China; Debt is net except gross for China

Source: IMF World Economic Outlook databank http://www.imf.org/external/pubs/ft/weo/2013/01/weodata/index.aspx

The current account of the US balance of payments is provided in Table IIA-6 for IVQ2011 and IVQ2012. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US decreased from $117.9 billion in IVQ2011, or 3.1 percent of GDP, to $111.2 billion in IIIQ2012, or 2.8 percent of GDP. The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession but is combined now with much higher imbalance in the Treasury budget (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71).

Table IIA-6, US Balance of Payments, Millions of Dollars NSA

 

IVQ2011

IVQ2012

Difference

Goods Balance

-186,332

-176,774

9,558

X Goods

387,237

399,304

3.1 ∆%

M Goods

-573,569

-576,078

0.4 ∆%

Services Balance

44,252

52,148

3,647

X Services

151,164

158,749

5.0 ∆%

M Services

-106,912

-106,601

-0.3 ∆%

Balance Goods and Services

-142,080

-124,626

17,454

Balance Income

56,263

48,293

-7,970

Unilateral Transfers

-32,135

-34,827

-2,692

Current Account Balance

-117,952

-111,159

6,793

% GDP

IVQ2011

IVQ2012

IIIQ2012

 

3.1

2.8

2.8

X: exports; M: imports

Balance on Current Account = Balance on Goods and Services + Balance on Income + Unilateral Transfers

Source: Bureau of Economic Analysis http://www.bea.gov/international/index.htm#bop http://www.bea.gov/iTable/index_nipa.cfm

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

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

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

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

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

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

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

The United States could be moving toward a situation typical of heavily indebted countries, requiring fiscal adjustment and increases in productivity to become more competitive internationally. The CAD and NIIP of the United States are not observed in full deterioration because the economy is well below potential. There are two complications in the current environment relative to the concern with disorderly correction in the first half of the past decade. Table IIA-7 provides data on the US fiscal and balance of payments imbalances. In 2007, the federal deficit of the US was $161 billion corresponding to 1.2 percent of GDP while the Congressional Budget Office (CBO 2012NovCDR) estimates the federal deficit in 2012 at $1089 billion or 7.0 percent of GDP (http://cmpassocregulationblog.blogspot.com/2013/02/united-states-unsustainable-fiscal.html). The combined record federal deficits of the US from 2009 to 2012 are $5092 billion or 33 percent of the estimate of GDP of $15,549 billion for fiscal year 2012 by the CBO (http://www.cbo.gov/publication/43905 CBO (2013BEOFeb5)). The deficits from 2009 to 2012 exceed one trillion dollars per year, adding to $5092 trillion in four years, using the fiscal year deficit of $1089.4 billion for fiscal year 2012 (http://www.fms.treas.gov/mts/mts0912.txt), which is the worst fiscal performance since World War II. Federal debt in 2007 was $5035 billion, less than the combined deficits from 2009 to 2012 of $5092 billion. Federal debt in 2011 was 67.8 percent of GDP and is estimated to reach 72.5 percent of GDP in 2012 (CBO2012AugBEO, CBO2012NovCDR, CBO2013BEOFeb5). This situation may worsen in the future (CBO 2012LTBO):

“The budget outlook is much bleaker under the extended alternative fiscal scenario, which maintains what some analysts might consider “current policies,” as opposed to current laws. Federal debt would grow rapidly from its already high level, exceeding 90 percent of GDP in 2022. After that, the growing imbalance between revenues and spending, combined with spiraling interest payments, would swiftly push debt to higher and higher levels. Debt as a share of GDP would exceed its historical peak of 109 percent by 2026, and it would approach 200 percent in 2037.

The changes under this scenario would result in much lower revenues than would occur under the extended baseline scenario because almost all expiring tax provisions are assumed to be extended through 2022 (with the exception of the current reduction in the payroll tax rate for Social Security). After 2022, revenues under this scenario are assumed to remain at their 2022 level of 18.5 percent of GDP, just above the average of the past 40 years.

Outlays would be much higher than under the other scenario. This scenario incorporates assumptions that through 2022, lawmakers will act to prevent Medicare’s payment rates for physicians from declining; that after 2022, lawmakers will not allow various restraints on the growth of Medicare costs and health insurance subsidies to exert their full effect; and that the automatic reductions in spending required by the Budget Control Act of 2011 will not occur (although the original caps on discretionary appropriations in that law are assumed to remain in place). Finally, under this scenario, federal spending as a percentage of GDP for activities other than Social Security, the major health care programs, and interest payments is assumed to return to its average level during the past two decades, rather than fall significantly below that level, as it does under the extended baseline scenario.”

Table IIA-7, US, Current Account, NIIP, Fiscal Balance, Nominal GDP, Federal Debt and Direct Investment, Dollar Billions and %

 

2007

2008

2009

2010

2011

2012

Goods &
Services

-696

-698

-379

-495

-560

-539

Income

101

147

119

184

227

198

UT

-115

-126

-122

-131

-133

-134

Current Account

-710

-677

-382

-442

-466

-475

NGDP

14028

14291

13974

14499

15076

15681

Current Account % GDP

-5.1

-4.7

-2.7

-3.1

-3.1

-3.0

NIIP

-1796

-3260

-2321

-2474

-4030

NA

US Owned Assets Abroad

18399

19464

18512

20298

21132

NA

Foreign Owned Assets in US

20195

22724

20833

22772

25162

NA

NIIP % GDP

-12.8

-22.8

-16.6

-17.1

-26.7

NA

Exports
Goods
Services
Income

2488

2657

2181

2519

2848

2937

NIIP %
Exports
Goods
Services
Income

-72

-123

-106

-98

-142

NA

DIA MV

5274

3102

4287

4767

4499

NA

DIUS MV

3551

2486

2995

3397

3509

NA

Fiscal Balance

-161

-459

-1413

-1294

-1296

-1089

Fiscal Balance % GDP

-1.2

-3.2

-10.1

-9.0

-8.7

-7.0

Federal   Debt

5035

5803

7545

9019

10128

11280

Federal Debt % GDP

36.3

40.5

54.1

62.9

67.8

72.5

Federal Outlays

2729

2983

3518

3456

3598

3538

∆%

2.8

9.3

17.9

-1.8

4.1

-1.7

% GDP

19.7

20.8

25.2

24.1

24.1

22.8

Federal Revenue

2568

2524

2105

2162

2302

2449

∆%

6.7

-1.7

-16.6

2.7

6.5

6.4

% GDP

18.5

17.6

15.1

15.1

15.4

15.8

Sources: 

Notes: UT: unilateral transfers; NGDP: nominal GDP or in current dollars; NIIP: Net International Investment Position; DIA MV: US Direct Investment Abroad at Market Value; DIUS MV: Direct Investment in the US at Market Value. There are minor discrepancies in the decimal point of percentages of GDP between the balance of payments data and federal debt, outlays, revenue and deficits in which the original number of the CBO source is maintained. These discrepancies do not alter conclusions.

Sources: http://www.bea.gov/international/index.htm#bop Balance of Payments and NIIP, Bureau of Economic Analysis (BEA)

Gross Domestic Product, Bureau of Economic Analysis (BEA) http://www.bea.gov/iTable/index_nipa.cfm

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

clip_image038

Chart IIA-5, US, Balance on Current Account, 1960-2012, Millions of Dollars

Source: Bureau of Economic Analysis

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

Chart IIA-6 provides the quarterly balance of current account of the United States in millions of dollars from 1995 to IVQ2012. The global recession appeared to be adjusting the current account deficit that rises to lower dollar values. Recovery of the economy worsened again the current account deficit. Growth at trend worsens the external imbalance of the US that combines now with unsustainable Treasury deficits/debt.

clip_image039

Chart IIA-6, US, Balance on Current Account, Quarterly 1979-2012, Millions of Dollars, SA

Source: Bureau of Economic Analysis

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

© Carlos M. Pelaez, 2010, 2011, 2012, 2013

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