Global Financial and Economic Risk, Recovery without Hiring, Loss of Ten Million Full-time Jobs, Youth and Middle Age Unemployment, United States International Trade, United States Services, World Cyclical Slow Growth and Global Recession Risk: Part I

 

Global Financial and Economic Risk, Recovery without Hiring, Loss of Ten Million Full-time Jobs, Youth and Middle Age Unemployment, United States International Trade, United States Services, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

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

I Recovery without Hiring

IA1 Hiring Collapse

IA2 Labor Underutilization

ICA3 Ten Million Fewer Full-time Jobs

IA4 Theory and Reality of Cyclical Slow Growth Not Secular Stagnation: Youth and

Middle-Age Unemployment

IIA United States International Trade

IIA1 Import and Export Prices

II United States Services

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

Contents of Executive Summary

ESI Financial “Irrational Exuberance,” Increasing Interest Rate Risk, Tapering Quantitative Easing, Duration Dumping, Competitive Devaluations, Steepening Yield Curve and Global Financial and Economic Risk

ESII Recovery without Hiring

ESIII Ten Million Fewer Full-time Jobs

ESIV Theory and Reality of Secular Stagnation: Youth and Middle-Age Unemployment

ESV United States International Trade

ESVI United States Services

ESI “Financial “Irrational Exuberance,” Increasing Interest Rate Risk, Tapering Quantitative Easing, Duration Dumping, Steepening Yield Curve and 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 for both theory and measurement. 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 for both theory and measurement. The IMF provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/ns/cs.aspx?id=29), of the world financial system with its Global Financial Stability Report (GFSR) (http://www.imf.org/external/pubs/ft/gfsr/index.htm) and of fiscal affairs with the Fiscal Monitor (http://www.imf.org/external/ns/cs.aspx?id=262). 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. Cumulative growth of China’s GDP in IIIQ2014 relative to the same period in 2013 was 7.4 percent. Secondary industry accounts for 44.2 percent of cumulative GDP in IIIQ2014. In cumulative IIIQ2014, industry alone accounts for 37.4 percent of GDP and construction with the remaining 6.8 percent. Tertiary industry accounts for 46.7 percent of cumulative GDP in IIIQ2014 and primary industry for 9.0 percent. China’s growth strategy consisted of rapid increases in productivity in industry to absorb population from agriculture where incomes are lower (Pelaez and Pelaez, The Global Recession Risk (2007), 56-80). The strategy is changing to lower growth rates while improving living standards. GDP growth decelerated from 12.1 percent in IQ2010 and 11.2 percent in IIQ2010 to 7.7 percent in IQ2013, 7.5 percent in IIQ2013 and 7.8 percent in IIIQ2013. GDP grew 7.7 percent in IVQ2013 relative to a year earlier and 1.7 percent relative to IIIQ2013, which is equivalent to 7.0 percent per year. GDP grew 7.4 percent in IQ2014 relative to a year earlier and 1.5 percent in IQ2014 that is equivalent to 6.1 percent per year. GP grew 7.5 percent in IIQ2014 relative to a year earlier and 2.0 percent relative to the prior quarter, which is equivalent 8.2 percent. In IIIQ2014, GDP grew 7.3 percent relative to a year earlier and 1.9 percent relative to the prior quarter, which is 7.8 percent in annual equivalent (Section VC and earlier http://cmpassocregulationblog.blogspot.com/2014/07/financial-irrational-exuberance.htm http://cmpassocregulationblog.blogspot.com/2014/04/imf-view-world-inflation-waves-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2014/01/capital-flows-exchange-rates-and.html and earlier http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or.html and earlier at http://cmpassocregulationblog.blogspot.com/2013/07/tapering-quantitative-easing-policy-and_7005.html 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). There is also concern about indebtedness, move to devaluation and deep policy reforms.
2. United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 26.0 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically low hiring and declining/stagnating real wages. Actual GDP is about two trillion dollars lower than trend GDP.
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/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/08/monetary-policy-world-inflation-waves.html). There is growing concern on capital outflows and currency depreciation of emerging markets.

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 with alternating episodes of revaluation.
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 mixed with reallocations of portfolios of risk financial assets

Chart VIII-1 of the Board of Governors of the Federal Reserve System provides the rate on the overnight fed funds rate and the yields of the 10-year constant maturity Treasury and the Baa seasoned corporate bond. Table VIII-3 provides the data for selected points in Chart VIII-1. There are two important economic and financial events, illustrating the ease of inducing carry trade with extremely low interest rates and the resulting financial crash and recession of abandoning extremely low interest rates.

• The Federal Open Market Committee (FOMC) lowered the target of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85). Central bank commitment to maintain the fed funds rate at 1.00 percent induced adjustable-rate mortgages (ARMS) linked to the fed funds rate. Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment. The exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at interest rates close to zero, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV). The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper with the objective of purchasing default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever-increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity by the penalty in the form of low interest rates and unsound credit decisions. 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). The FOMC implemented increments of 25 basis points of the fed funds target from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006, as shown in Chart VIII-1. The gradual exit from the first round of unconventional monetary policy from 1.00 percent in Jun 2004 (http://www.federalreserve.gov/boarddocs/press/monetary/2004/20040630/default.htm) to 5.25 percent in Jun 2006 (http://www.federalreserve.gov/newsevents/press/monetary/20060629a.htm) caused the financial crisis and global recession.
• On Dec 16, 2008, the policy determining committee of the Fed decided (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm): “The Federal Open Market Committee decided today to establish a target range for the federal funds rate of 0 to 1/4 percent.” Policymakers emphasize frequently that there are tools to exit unconventional monetary policy at the right time. At the confirmation hearing on nomination for Chair of the Board of Governors of the Federal Reserve System, Vice Chair Yellen (2013Nov14 http://www.federalreserve.gov/newsevents/testimony/yellen20131114a.htm), states that: “The Federal Reserve is using its monetary policy tools to promote a more robust recovery. A strong recovery will ultimately enable the Fed to reduce its monetary accommodation and reliance on unconventional policy tools such as asset purchases. I believe that supporting the recovery today is the surest path to returning to a more normal approach to monetary policy.” Perception of withdrawal of $2671 billion, or $2.7 trillion, of bank reserves (http://www.federalreserve.gov/releases/h41/current/h41.htm#h41tab1), would cause Himalayan increase in interest rates that would provoke another recession. There is no painless gradual or sudden exit from zero interest rates because reversal of exposures created on the commitment of zero interest rates forever.

In his classic restatement of the Keynesian demand function in terms of “liquidity preference as behavior toward risk,” James Tobin (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/1981/tobin-bio.html) identifies the risks of low interest rates in terms of portfolio allocation (Tobin 1958, 86):

“The assumption that investors expect on balance no change in the rate of interest has been adopted for the theoretical reasons explained in section 2.6 rather than for reasons of realism. Clearly investors do form expectations of changes in interest rates and differ from each other in their expectations. For the purposes of dynamic theory and of analysis of specific market situations, the theories of sections 2 and 3 are complementary rather than competitive. The formal apparatus of section 3 will serve just as well for a non-zero expected capital gain or loss as for a zero expected value of g. Stickiness of interest rate expectations would mean that the expected value of g is a function of the rate of interest r, going down when r goes down and rising when r goes up. In addition to the rotation of the opportunity locus due to a change in r itself, there would be a further rotation in the same direction due to the accompanying change in the expected capital gain or loss. At low interest rates expectation of capital loss may push the opportunity locus into the negative quadrant, so that the optimal position is clearly no consols, all cash. At the other extreme, expectation of capital gain at high interest rates would increase sharply the slope of the opportunity locus and the frequency of no cash, all consols positions, like that of Figure 3.3. The stickier the investor's expectations, the more sensitive his demand for cash will be to changes in the rate of interest (emphasis added).”

Tobin (1969) provides more elegant, complete analysis of portfolio allocation in a general equilibrium model. The major point is equally clear in a portfolio consisting of only cash balances and a perpetuity or consol. Let g be the capital gain, r the rate of interest on the consol and r^e the expected rate of interest. The rates are expressed as proportions. The price of the consol is the inverse of the interest rate, (1+r^e). Thus, g = [(r/r^e) – 1]. The critical analysis of Tobin is that at extremely low interest rates there is only expectation of interest rate increases, that is, dr^e>0, such that there is expectation of capital losses on the consol, dg<0. Investors move into positions combining only cash and no consols. Valuations of risk financial assets would collapse in reversal of long positions in carry trades with short exposures in a flight to cash. There is no exit from a central bank created liquidity trap without risks of financial crash and another global recession. 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 (Friedman 1957). According to a subsequent statement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption 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→∞. Unconventional monetary policy lowers interest rates to increase the present value of cash flows derived from projects of firms, creating the impression of long-term increase in net worth. An attempt to reverse unconventional monetary policy necessarily causes increases in interest rates, creating the opposite perception of declining net worth. As r→∞, W = Y/r →0. There is no exit from unconventional monetary policy without increasing interest rates with resulting pain of financial crisis and adverse effects on production, investment and employment.

Chart VIII-1, Fed Funds Rate and Yields of Ten-year Treasury Constant Maturity and Baa Seasoned Corporate Bond, Jan 2, 2001 to Dec 4, 2014 

Source: Board of Governors of the Federal Reserve System

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

Table VIII-3, Selected Data Points in Chart VIII-1, % per Year

	Fed Funds Overnight Rate	10-Year Treasury Constant Maturity	Seasoned Baa Corporate Bond
1/2/2001	6.67	4.92	7.91
10/1/2002	1.85	3.72	7.46
7/3/2003	0.96	3.67	6.39
6/22/2004	1.00	4.72	6.77
6/28/2006	5.06	5.25	6.94
9/17/2008	2.80	3.41	7.25
10/26/2008	0.09	2.16	8.00
10/31/2008	0.22	4.01	9.54
4/6/2009	0.14	2.95	8.63
4/5/2010	0.20	4.01	6.44
2/4/2011	0.17	3.68	6.25
7/25/2012	0.15	1.43	4.73
5/1/13	0.14	1.66	4.48
9/5/13	0.08	2.98	5.53
11/21/2013	0.09	2.79	5.44
11/26/13	0.09	2.74	5.34 (11/26/13)
12/5/13	0.09	2.88	5.47
12/11/13	0.09	2.89	5.42
12/18/13	0.09	2.94	5.36
12/26/13	0.08	3.00	5.37
1/1/2014	0.08	3.00	5.34
1/8/2014	0.07	2.97	5.28
1/15/2014	0.07	2.86	5.18
1/22/2014	0.07	2.79	5.11
1/30/2014	0.07	2.72	5.08
2/6/2014	0.07	2.73	5.13
2/13/2014	0.06	2.73	5.12
2/20/14	0.07	2.76	5.15
2/27/14	0.07	2.65	5.01
3/6/14	0.08	2.74	5.11
3/13/14	0.08	2.66	5.05
3/20/14	0.08	2.79	5.13
3/27/14	0.08	2.69	4.95
4/3/14	0.08	2.80	5.04
4/10/14	0.08	2.65	4.89
4/17/14	0.09	2.73	4.89
4/24/14	0.10	2.70	4.84
5/1/14	0.09	2.63	4.77
5/8/14	0.08	2.61	4.79
5/15/14	0.09	2.50	4.72
5/22/14	0.09	2.56	4.81
5/29/14	0.09	2.45	4.69
6/05/14	0.09	2.59	4.83
6/12/14	0.09	2.58	4.79
6/19/14	0.10	2.64	4.83
6/26/14	0.10	2.53	4.71
7/2/14	0.10	2.64	4.84
7/10/14	0.09	2.55	4.75
7/17/14	0.09	2.47	4.69
7/24/14	0.09	2.52	4.72
7/31/14	0.08	2.58	4.75
8/7/14	0.09	2.43	4.71
8/14/14	0.09	2.40	4.69
8/21/14	0.09	2.41	4.69
8/28/14	0.09	2.34	4.57
9/04/14	0.09	2.45	4.70
9/11/14	0.09	2.54	4.79
9/18/14	0.09	2.63	4.91
9/25/14	0.09	2.52	4.79
10/02/14	0.09	2.44	4.76
10/09/14	0.08	2.34	4.68
10/16/14	0.09	2.17	4.64
10/23/14	0.09	2.29	4.71
11/13/14	0.09	2.35	4.82
11/20/14	0.10	2.34	4.86
11/26/14	0.10	2.24	4.73
12/04/14	0.12	2.25	4.78
12/11/14	0.12	2.19	4.72

Source: Board of Governors of the Federal Reserve System

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

What is truly important is the fixing of the overnight fed funds at 0 to ¼ percent for which there is no end in sight as evident in the FOMC statement for Oct 29, 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20141029a.htm):

“To support continued progress toward maximum employment and price stability, the Committee today reaffirmed its view that the current 0 to 1/4 percent target range for the federal funds rate remains appropriate. In determining how long to maintain this target range, the Committee will assess progress--both realized and expected--toward its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial developments. The Committee anticipates, based on its current assessment, that it likely will be appropriate to maintain the 0 to 1/4 percent target range for the federal funds rate for a considerable time following the end of its asset purchase program this month, especially if projected inflation continues to run below the Committee's 2 percent longer-run goal, and provided that longer-term inflation expectations remain well anchored. However, if incoming information indicates faster progress toward the Committee's employment and inflation objectives than the Committee now expects, then increases in the target range for the federal funds rate are likely to occur sooner than currently anticipated. Conversely, if progress proves slower than expected, then increases in the target range are likely to occur later than currently anticipated” (emphasis added).

Perhaps one of the most critical statements on policy is the answer to a question of Peter Barnes by Chair Janet Yellen at the press conference following the meeting on Jun 18, 2014 (page 19 at http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20140618.pdf):

So I don't have a sense--the committee doesn't try to gauge what is the right level of equity prices. But we do certainly monitor a number of different metrics that give us a feeling for where valuations are relative to things like earnings or dividends, and look at where these metrics stand in comparison with previous history to get a sense of whether or not we're moving to valuation levels that are outside of historical norms, and I still don't see that. I still don't see that for equity prices broadly” (emphasis added).

Chart S provides the yield of the two-year Treasury constant maturity from Mar 17, 2014, two days before the guidance of Chair Yellen on Mar 19, 2014, to Dec 11, 2014. Chart SA provides the yields of the seven-, ten- and thirty-year Treasury constant maturity in the same dates. Yields increased right after the guidance of Chair Yellen. The two-year yield remain at a higher level than before while the ten-year yield fell and increased again. There could be more immediate impact on two-year yields of an increase in the fed funds rates but the effects would spread throughout the term structure of interest rates (Cox, Ingersoll and Ross 1981, 1985, Ingersoll 1987). Yields converged toward slightly lower earlier levels in the week of Apr 24, 2014 with reallocation of portfolios of risk financial assets away from equities and into bonds and commodities. There is ongoing reshuffling of portfolios to hedge against geopolitical events and world/regional economic performance.

Chart S, US, Yield of Two-Year Treasury Constant Maturity, Mar 17 to Dec 11, 2014 

Source: Board of Governors of the Federal Reserve System

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

Chart SA, US, Yield of Seven-Year, Ten-Year and Thirty-Year Treasury Constant Maturity, Mar 17 to Dec 11, 2014 

Source: Board of Governors of the Federal Reserve System

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

At a speech on Mar 31, 2014, Chair Yellen analyzed labor market conditions as follows (http://www.federalreserve.gov/newsevents/speech/yellen20140331a.htm):

“And based on the evidence available, it is clear to me that the U.S. economy is still considerably short of the two goals assigned to the Federal Reserve by the Congress. The first of those goals is maximum sustainable employment, the highest level of employment that can be sustained while maintaining a stable inflation rate. Most of my colleagues on the Federal Open Market Committee and I estimate that the unemployment rate consistent with maximum sustainable employment is now between 5.2 percent and 5.6 percent, well below the 6.7 percent rate in February.

Let me explain what I mean by that word "slack" and why it is so important.

Slack means that there are significantly more people willing and capable of filling a job than there are jobs for them to fill. During a period of little or no slack, there still may be vacant jobs and people who want to work, but a large share of those willing to work lack the skills or are otherwise not well suited for the jobs that are available. With 6.7 percent unemployment, it might seem that there must be a lot of slack in the U.S. economy, but there are reasons why that may not be true.”

Inflation and unemployment in the period 1966 to 1985 is analyzed by Cochrane (2011Jan, 23) by means of a Phillips circuit joining points of inflation and unemployment. Chart VI-1B for Brazil in Pelaez (1986, 94-5) was reprinted in The Economist in the issue of Jan 17-23, 1987 as updated by the author. Cochrane (2011Jan, 23) argues that the Phillips circuit shows the weakness in Phillips curve correlation. The explanation is by a shift in aggregate supply, rise in inflation expectations or loss of anchoring. The case of Brazil in Chart VI-1B cannot be explained without taking into account the increase in the fed funds rate that reached 22.36 percent on Jul 22, 1981 (http://www.federalreserve.gov/releases/h15/data.htm) in the Volcker Fed that precipitated the stress on a foreign debt bloated by financing balance of payments deficits with bank loans in the 1970s. The loans were used in projects, many of state-owned enterprises with low present value in long gestation. The combination of the insolvency of the country because of debt higher than its ability of repayment and the huge government deficit with declining revenue as the economy contracted caused adverse expectations on inflation and the economy.  This interpretation is consistent with the case of the 24 emerging market economies analyzed by Reinhart and Rogoff (2010GTD, 4), concluding that “higher debt levels are associated with significantly higher levels of inflation in emerging markets. Median inflation more than doubles (from less than seven percent to 16 percent) as debt rises from the low (0 to 30 percent) range to above 90 percent. Fiscal dominance is a plausible interpretation of this pattern.”

The reading of the Phillips circuits of the 1970s by Cochrane (2011Jan, 25) is doubtful about the output gap and inflation expectations:

“So, inflation is caused by ‘tightness’ and deflation by ‘slack’ in the economy. This is not just a cause and forecasting variable, it is the cause, because given ‘slack’ we apparently do not have to worry about inflation from other sources, notwithstanding the weak correlation of [Phillips circuits]. These statements [by the Fed] do mention ‘stable inflation expectations. How does the Fed know expectations are ‘stable’ and would not come unglued once people look at deficit numbers? As I read Fed statements, almost all confidence in ‘stable’ or ‘anchored’ expectations comes from the fact that we have experienced a long period of low inflation (adaptive expectations). All these analyses ignore the stagflation experience in the 1970s, in which inflation was high even with ‘slack’ markets and little ‘demand, and ‘expectations’ moved quickly. They ignore the experience of hyperinflations and currency collapses, which happen in economies well below potential.”

Yellen (2014Aug22) states that “Historically, slack has accounted for only a small portion of the fluctuations in inflation. Indeed, unusual aspects of the current recovery may have shifted the lead-lag relationship between a tightening labor market and rising inflation pressures in either direction.”

Chart VI-1B provides the tortuous Phillips Circuit of Brazil from 1963 to 1987. There were no reliable consumer price index and unemployment data in Brazil for that period. Chart VI-1B used the more reliable indicator of inflation, the wholesale price index, and idle capacity of manufacturing as a proxy of unemployment in large urban centers.

ChVI1-B, Brazil, Phillips Circuit, 1963-1987

Source:

©Carlos Manuel Pelaez, O Cruzado e o Austral: Análise das Reformas Monetárias do Brasil e da Argentina. São Paulo: Editora Atlas, 1986, pages 94-5. Reprinted in: Brazil. Tomorrow’s Italy, The Economist, 17-23 January 1987, page 25.

The minutes of the meeting of the Federal Open Market Committee (FOMC) on Sep 16-17, 2014, reveal concern with global economic conditions (http://www.federalreserve.gov/monetarypolicy/fomcminutes20140917.htm):

“Most viewed the risks to the outlook for economic activity and the labor market as broadly balanced. However, a number of participants noted that economic growth over the medium term might be slower than they expected if foreign economic growth came in weaker than anticipated, structural productivity continued to increase only slowly, or the recovery in residential construction continued to lag.”

It is quite difficult to measure inflationary expectations because they tend to break abruptly from past inflation. There could still be an influence of past and current inflation in the calculation of future inflation by economic agents. Table VIII-1 provides inflation of the CPI. In the three months from Aug 2014 to Oct 2014, CPI inflation for all items seasonally adjusted was minus 0.4 percent in annual equivalent, obtained by calculating accumulated inflation from Aug 2014 to Oct 2014 and compounding for a full year. In the 12 months ending in Oct 2014, CPI inflation of all items not seasonally adjusted was 1.7 percent. Inflation in Oct 2014 seasonally adjusted was 0.0 percent relative to Sep 2014, or 0.0 percent annual equivalent (http://www.bls.gov/cpi/). The second row provides the same measurements for the CPI of all items excluding food and energy: 1.8 percent in 12 months and 1.2 percent in annual equivalent Jul 2014-Sep 2014. The Wall Street Journal provides the yield curve of US Treasury securities (http://professional.wsj.com/mdc/public/page/mdc_bonds.html?mod=mdc_topnav_2_3000). The shortest term is 0.018 percent for one month, 0.028 percent for three months, 0.099 percent for six months, 0.196 percent for one year, 0.544 percent for two years, 0.974 percent for three years, 1.513 percent for five years, 1.846 percent for seven years, 2.083 percent for ten years and 2.737 percent for 30 years. The Irving Fisher (1930) definition of real interest rates is approximately the difference between nominal interest rates, which are those estimated by the Wall Street Journal, and the rate of inflation expected in the term of the security, which could behave as in Table VIII-1. Inflation in Sep 2014 is low in 12 months because of the unwinding of carry trades from zero interest rates to commodity futures prices but could ignite again with subdued risk aversion. Real interest rates in the US have been negative during substantial periods in the past decade while monetary policy pursues a policy of attaining its “dual mandate” of (http://www.federalreserve.gov/aboutthefed/mission.htm):

“Conducting the nation's monetary policy by influencing the monetary and credit conditions in the economy in pursuit of maximum employment, stable prices, and moderate long-term interest rates”

Negative real rates of interest distort calculations of risk and returns from capital budgeting by firms, through lending by financial intermediaries to decisions on savings, housing and purchases of households. Inflation on near zero interest rates misallocates resources away from their most productive uses and creates uncertainty of the future path of adjustment to higher interest rates that inhibit sound decisions.

Table VIII-1, US, Consumer Price Index Percentage Change 12 Months NSA and Annual Equivalent

	∆% 12 Months Oct 2014/Oct 2013 NSA	∆% Annual Equivalent Aug 2014 to Oct 2014 SA
CPI All Items	1.7	-0.4
CPI ex Food and Energy	1.8	1.2

Source: Bureau of Labor Statistics

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

Professionals use a variety of techniques in measuring interest rate risk (Fabozzi, Buestow and Johnson, 2006, Chapter Nine, 183-226):

• Full valuation approach in which securities and portfolios are shocked by 50, 100, 200 and 300 basis points to measure their impact on asset values
• Stress tests requiring more complex analysis and translation of possible events with high impact even if with low probability of occurrence into effects on actual positions and capital
• Value at Risk (VaR) analysis of maximum losses that are likely in a time horizon
• Duration and convexity that are short-hand convenient measurement of changes in prices resulting from changes in yield captured by duration and convexity
• Yield volatility

Analysis of these methods is in Pelaez and Pelaez (International Financial Architecture (2005), 101-162) and Pelaez and Pelaez, Globalization and the State, Vol. (I) (2008a), 78-100). Frederick R. Macaulay (1938) introduced the concept of duration in contrast with maturity for analyzing bonds. Duration is the sensitivity of bond prices to changes in yields. In economic jargon, duration is the yield elasticity of bond price to changes in yield, or the percentage change in price after a percentage change in yield, typically expressed as the change in price resulting from change of 100 basis points in yield. The mathematical formula is the negative of the yield elasticity of the bond price or –[dB/d(1+y)]((1+y)/B), where d is the derivative operator of calculus, B the bond price, y the yield and the elasticity does not have dimension (Hallerbach 2001). The duration trap of unconventional monetary policy is that duration is higher the lower the coupon and higher the lower the yield, other things being constant. Coupons and yields are historically low because of unconventional monetary policy. Duration dumping during a rate increase may trigger the same crossfire selling of high duration positions that magnified the credit crisis. Traders reduced positions because capital losses in one segment, such as mortgage-backed securities, triggered haircuts and margin increases that reduced capital available for positioning in all segments, causing fire sales in multiple segments (Brunnermeier and Pedersen 2009; see Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 217-24). Financial markets are currently experiencing fear of duration and riskier asset classes resulting from the debate within and outside the Fed on tapering quantitative easing. Table VIII-2 provides the yield curve of Treasury securities on Dec 12, 2014, Dec 31, 2013, May 1, 2013, Dec 12, 2013 and Dec 12, 2006. There is oscillating steepening of the yield curve for longer maturities, which are also the ones with highest duration. The 10-year yield increased from 1.45 percent on Jul 26, 2012 to 3.04 percent on Dec 31, 2013 and 2.10 percent on Dec 12, 2014, as measured by the United States Treasury. Assume that a bond with maturity in 10 years were issued on Dec 31, 2013, at par or price of 100 with coupon of 1.45 percent. The price of that bond would be 86.3778 with instantaneous increase of the yield to 3.04 percent for loss of 13.6 percent and far more with leverage. Assume that the yield of a bond with exactly ten years to maturity and coupon of 2.10 percent would jump instantaneously from yield of 2.10 percent on Dec 12, 2014 to 4.49 percent as occurred on Dec 12, 2006 when the economy was closer to full employment. The price of the hypothetical bond issued with coupon of 2.10 percent would drop from 100 to 80.9143 after an instantaneous increase of the yield to 4.49 percent. The price loss would be 19.1 percent. Losses absorb capital available for positioning, triggering crossfire sales in multiple asset classes (Brunnermeier and Pedersen 2009). What is the path of adjustment of zero interest rates on fed funds and artificially low bond yields? There is no painless exit from unconventional monetary policy. Chris Dieterich, writing on “Bond investors turn to cash,” on Jul 25, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323971204578625900935618178.html), uses data of the Investment Company Institute (http://www.ici.org/) in showing withdrawals of $43 billion in taxable mutual funds in Jun, which is the largest in history, with flows into cash investments such as $8.5 billion in the week of Jul 17 into money-market funds.

Table VIII-2, United States, Treasury Yields

	12/12/14	12/31/13	5/01/13	12/12/13	12/12/06
1 M	0.02	0.01	0.03	0.01	4.87
3 M	0.02	0.07	0.06	0.07	4.93
6 M	0.09	0.10	0.08	0.09	5.06
1 Y	0.19	0.13	0.11	0.14	4.91
2 Y	0.56	0.38	0.20	0.34	4.61
3 Y	0.98	0.78	0.30	0.67	4.49
5 Y	1.53	1.75	0.65	1.55	4.45
7 Y	1.86	2.45	1.07	2.26	4.45
10 Y	2.10	3.04	1.66	2.89	4.49
20 Y	2.45	3.72	2.44	3.63	4.70
30 Y	2.75	3.96	2.83	3.91	4.60

M: Months; Y: Years

Source: United States Treasury

http://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yield

Interest rate risk is increasing in the US with amplifying fluctuations. Chart VI-13 of the Board of Governors provides the conventional mortgage rate for a fixed-rate 30-year mortgage. The rate stood at 5.87 percent on Jan 8, 2004, increasing to 6.79 percent on Jul 6, 2006. The rate bottomed at 3.35 percent on May 2, 2013. Fear of duration risk in longer maturities such as mortgage-backed securities caused continuing increases in the conventional mortgage rate that rose to 4.51 percent on Jul 11, 2013, 4.58 percent on Aug 22, 2013 and 3.93 percent on Dec 11, 2014, which is the last data point in Chart VI-13. Shayndi Raice and Nick Timiraos, writing on “Banks cut as mortgage boom ends,” on Jan 9, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303754404579310940019239208), analyze the drop in mortgage applications to a 13-year low, as measured by the Mortgage Bankers Association. Nick Timiraos, writing on “Demand for home loans plunges,” on Apr 24, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304788404579522051733228402?mg=reno64-wsj), analyzes data in Inside Mortgage Finance that mortgage lending of $235 billion in IQ2014 is 58 percent lower than a year earlier and 23 percent below IVQ2013. Mortgage lending collapsed to the lowest level in 14 years. In testimony before the Committee on the Budget of the US Senate on May 8, 2004, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm): “One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.”

Chart VI-13, US, Conventional Mortgage Rate, Jan 8, 2004 to Dec 11, 2014

Source: Board of Governors of the Federal Reserve System

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

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

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

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

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

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

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

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

Source: Board of Governors of the Federal Reserve System

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

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

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

Source: Bureau of Labor Statistics

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

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

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

Source: Bureau of Labor Statistics

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

Table VI-2 extracts four rows of Table VI-1 with the Dollar/EUR (USD/EUR) exchange rate and Chinese Yuan/Dollar (CNY/USD) exchange rate that reveal pursuit of exchange rate policies resulting from monetary policy in the US and capital control/exchange rate policy in China. The ultimate intentions are the same: promoting internal economic activity at the expense of the rest of the world. The easy money policy of the US was deliberately or not but effectively to devalue the dollar from USD 1.1423/EUR on Jun 26, 2003 to USD 1.5914/EUR on Jul 14, 2008, or by 39.3 percent. The flight into dollar assets after the global recession caused revaluation to USD 1.192/EUR on Jun 7, 2010, or by 25.1 percent. After the temporary interruption of the sovereign risk issues in Europe from Apr to Jul, 2010, shown in Table VI-4 below, the dollar has devalued again to USD 1.2464 EUR on Dec 12, 2014 or by 4.6 percent {[(1.2464/1.192)-1]100 = 4.6%}. Yellen (2011AS, 6) admits that Fed monetary policy results in dollar devaluation with the objective of increasing net exports, which was the policy that Joan Robinson (1947) labeled as “beggar-my-neighbor” remedies for unemployment. Risk aversion erodes devaluation of the dollar. China fixed the CNY to the dollar for a long period at a highly undervalued level of around CNY 8.2765/USD subsequently revaluing to CNY 6.8211/USD until Jun 7, 2010, or by 17.6 percent. After fixing again the CNY to the dollar, China revalued to CNY 6.1852/USD on Fri Dec 12, 2014, or by an additional 9.3 percent, for cumulative revaluation of 25.3 percent. The final row of Table VI-2 shows: revaluation of 0.1 percent in the week of Nov 21, 2014; devaluation of 0.3 percent in the week of Nov 28, 2014; revaluation of 0.1 percent in the week of Dec 5, 2014; and devaluation of 0.6 percent in the week of Dec 12, 2014. There could be reversal of revaluation to devalue the Yuan.

Table VI-2, Dollar/Euro (USD/EUR) Exchange Rate and Chinese Yuan/Dollar (CNY/USD) Exchange Rate

USD/EUR	12/26/03	7/14/08	6/07/10	12/12/14
Rate	1.1423	1.5914	1.192	1.2464
CNY/USD	01/03 2000	07/21 2005	7/15 2008	12/12/ 2014
Rate	8.2765	8.2765	6.8211	6.1852
Weekly Rates	11/21/2014	11/28/2014	12/05/2014	12/12/ 2014
CNY/USD	6.1228	6.1431	6.1502	6.1852
∆% from Earlier Week*	0.1	-0.3	-0.1	-0.6

*Negative sign is depreciation; positive sign is appreciation

Source: http://professional.wsj.com/mdc/public/page/mdc_currencies.html?mod=mdc_topnav_2_3000

Professor Edward P Lazear (2013Jan7), writing on “Chinese ‘currency manipulation’ is not the problem,” on Jan 7, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887323320404578213203581231448.html), provides clear thought on the role of the yuan in trade between China and the United States and trade between China and Europe. There is conventional wisdom that Chinese exchange rate policy causes the loss of manufacturing jobs in the United States, which is shown by Lazear (2013Jan7) to be erroneous. The fact is that manipulation of the CNY/USD rate by China has only minor effects on US employment. Lazear (2013Jan7) shows that the movement of monthly exports of China to its major trading partners, United States and Europe, since 1995 cannot be explained by the fixing of the CNY/USD rate by China. The period is quite useful because it includes rapid growth before 2007, contraction until 2009 and weak subsequent expansion. Chart VI-1 of the Board of Governors of the Federal Reserve System provides the CNY/USD exchange rate from Jan 3, 1995 to Dec 5, 2014 together with US recession dates in shaded areas. China fixed the CNY/USD rate for a long period as shown in the horizontal segment from 1995 to 2005. There was systematic revaluation of 17.6 percent from CNY 8.2765 on Jul 21, 2005 to CNY 6.8211 on Jul 15, 2008. China fixed the CNY/USD rate until Jun 7, 2010, to avoid adverse effects on its economy from the global recession, which is shown as a horizontal segment from 2009 until mid 2010. China then continued the policy of appreciation of the CNY relative to the USD with oscillations until the beginning of 2012 when the rate began to move sideways followed by a final upward slope of devaluation that is measured in Table VI-2A but virtually disappeared in the rate of CNY 6.3589/USD on Aug 17, 2012 and was nearly unchanged at CNY 6.3558/USD on Aug 24, 2012. China then appreciated 0.2 percent in the week of Dec 21, 2012, to CNY 6.2352/USD for cumulative 1.9 percent revaluation from Oct 28, 2011 and left the rate virtually unchanged at CNY 6.2316/USD on Jan 11, 2013, appreciating to CNY 6.1497/USD on Dec 5, 2014, which is the last data point in Chart VI-1. Revaluation of the CNY relative to the USD by 25.3 percent by Dec 12, 2014 has not reduced the trade surplus of China but reversal of the policy of revaluation could result in international confrontation. The interruption with upward slope in the final segment on the right of Chart VI-I is measured as virtually stability in Table VI-2A followed with decrease or revaluation and subsequent increase or devaluation. The final segment shows decline or revaluation. Linglin Wei, writing on “China intervenes to lower yuan,” on Feb 26, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304071004579406810684766716?KEYWORDS=china+yuan&mg=reno64-wsj), finds from informed sources that the central bank of China conducted the ongoing devaluation of the yuan with the objective of driving out arbitrageurs to widen the band of fluctuation. There is concern if the policy of revaluation is changing to devaluation.

Chart VI-1, Chinese Yuan (CNY) per US Dollar (USD), Business Days, Jan 3, 1995-Dec 5, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

Chart VI-1A provides the daily CNY/USD rate from Jan 5, 1981 to Dec 5, 2014. The exchange rate was CNY 1.5418/USD on Jan 5, 1981. There is sharp cumulative depreciation of 107.8 percent to CNY 3.2031 by Jul 2, 1986, continuing to CNY 5.8145/USD on Dec 29, 1993 for cumulative 277.1 percent since Jan 5, 1981. China then devalued sharply to CNY 8.7117/USD on Jan 7, 1994 for 49.8 percent relative to Dec 29, 1993 and cumulative 465.0 percent relative to Jan 5, 1981. China then fixed the rate at CNY 8.2765/USD until Jul 21, 2005 and revalued as analyzed in Chart VI-1. The final data point in Chart VI-1A is CNY 6.1497/USD on Dec 5, 2014. To be sure, China fixed the exchange rate after substantial prior devaluation. It is unlikely that the devaluation could have been effective after many years of fixing the exchange rate with high inflation and multiple changes in the world economy. The argument of Lazear (2013Jan7) is still valid in view of the lack of association between monthly exports of China to the US and Europe since 1995 and the exchange rate of China.

Chart VI-1A, Chinese Yuan (CNY) per US Dollar (USD), Business Days, Jan 5, 1981-Dec 5, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

Chart VI-1B provides finer details with the rate of Chinese Yuan (CNY) to the US Dollar (USD) from Oct 28, 2011 to Dec 5, 2014. There have been alternations of revaluation and devaluation. The initial data point is CNY 6.5370 on Oct 28, 2011. There is an episode of devaluation from CNY 6.2790 on Apr 30, 2012 to CNY 6.3879 on Jul 25, 2012, or devaluation of 1.4 percent. Another devaluation is from CNY 6.0402/USD on Jan 14, 2014 to CNY 6.1497 on Dec 5, 2014, or devaluation of 1.8 percent. The United States Treasury estimates US government debt held by private investors at $9670 billion in Jun 2014. China’s holding of US Treasury securities represent 13.1 percent of US government marketable interest-bearing debt held by private investors (http://www.fms.treas.gov/bulletin/index.html). Min Zeng, writing on “China plays a big role as US Treasury yields fall,” on Jul 16, 2004, published in the Wall Street Journal (http://online.wsj.com/articles/china-plays-a-big-role-as-u-s-treasury-yields-fall-1405545034?tesla=y&mg=reno64-wsj), finds that acceleration in purchases of US Treasury securities by China has been an important factor in the decline of Treasury yields in 2014. Japan increased its holdings from $1149.1 billion in Aug 2013 to $1230.1 billion in Aug 2014 or 7.0 percent. The combined holdings of China and Japan in Aug 2014 add to $2500 billion, which is equivalent to 25.9 percent of US government marketable interest-bearing securities held by investors of $9670 billion in Jun 2014 (http://www.fms.treas.gov/bulletin/index.html). Total foreign holdings of Treasury securities rose from $5595.8 billion in Aug 2013 to $6066.6 billion in Aug 2014, or 8.4 percent. The US continues to finance its fiscal and balance of payments deficits with foreign savings (see Pelaez and Pelaez, The Global Recession Risk (2007)). A point of saturation of holdings of US Treasury debt may be reached as foreign holders evaluate the threat of reduction of principal by dollar devaluation and reduction of prices by increases in yield, including possibly risk premium. Shultz et al (2012) find that the Fed financed three-quarters of the US deficit in fiscal year 2011, with foreign governments financing significant part of the remainder of the US deficit while the Fed owns one in six dollars of US national debt. Concentrations of debt in few holders are perilous because of sudden exodus in fear of devaluation and yield increases and the limit of refinancing old debt and placing new debt. In their classic work on “unpleasant monetarist arithmetic,” Sargent and Wallace (1981, 2) consider a regime of domination of monetary policy by fiscal policy (emphasis added):

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

Chart VI-1B, Chinese Yuan (CNY) per US Dollar (US), Business Days, Oct 28, 2011-Dec 5, 2014

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

There are major ongoing and unresolved realignments of exchange rates in the international financial system as countries and regions seek parities that can optimize their productive structures. Seeking exchange rate parity or exchange rate optimizing internal economic activities is complex in a world of unconventional monetary policy of zero interest rates and even negative nominal interest rates of government obligations such as negative yields for the two-year government bond of Germany. Regulation, trade and devaluation conflicts should have been expected from a global recession (Pelaez and Pelaez (2007), The Global Recession Risk, Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008a)): “There are significant grounds for concern on the basis of this experience. International economic cooperation and the international financial framework can collapse during extreme events. It is unlikely that there will be a repetition of the disaster of the Great Depression. However, a milder contraction can trigger regulatory, trade and exchange wars” (Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008c), 181). Chart VI-2 of the Board of Governors of the Federal Reserve System provides the key exchange rate of US dollars (USD) per euro (EUR) from Jan 4, 1999 to Dec, 2014. US recession dates are in shaded areas. The rate on Jan 4, 1999 was USD 1.1812/EUR, declining to USD 0.8279/EUR on Oct 25, 2000, or appreciation of the USD by 29.9 percent. The rate depreciated 21.9 percent to USD 1.0098/EUR on Jul 22, 2002. There was sharp devaluation of the USD of 34.9 percent to USD 1.3625/EUR on Dec 27, 2004 largely because of the 1 percent interest rate between Jun 2003 and Jun 2004 together with a form of quantitative easing by suspension of auctions of the 30-year Treasury, which was equivalent to withdrawing supply from markets. Another depreciation of 17.5 percent took the rate to USD 1.6010/EUR on Apr 22, 2008, already inside the shaded area of the global recession. The flight to the USD and obligations of the US Treasury appreciated the dollar by 22.3 percent to USD 1.2446/EUR on Oct 27, 2008. In the return of the carry trade after stress tests showed sound US bank balance sheets, the rate depreciated 21.2 percent to USD 1.5085/EUR on Nov 25, 2009. The sovereign debt crisis of Europe in the spring of 2010 caused sharp appreciation of 20.7 percent to USD 1.1959/EUR on Jun 6, 2010. Renewed risk appetite depreciated the rate 24.4 percent to USD 1.4875/EUR on May 3, 2011. The rate depreciated 2.9 percent to USD 1.2304/EUR on Dec 5, 2014, which is the last point in Chart VI-2. The data in Table VI-6 is obtained from closing dates in New York published by the Wall Street Journal (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata).

Chart VI-2, US Dollars (USD) per Euro (EUR), Jan 4, 1999 to Dec 5, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

Chart VI-3 provides three indexes of the US Dollars (USD) from Jan 4, 1995 to Dec 5, 2014.

Chart VI-3A provides the overnight fed funds rate and yields of the three-month constant maturity Treasury bill, the ten-year constant maturity Treasury note and Moody’s Baa bond from Jan 4, 1995 to Dec 11, 2014. The first phase from 1995 to 2001 shows sharp trend of appreciation of the USD while interest rates remained at relatively high levels. The dollar revalued partly because of the emerging market crises that provoked inflows of financial investment into the US and partly because of a deliberate strong dollar policy. DeLong and Eichengreen (2001, 4-5) argue:

“That context was an economic and political strategy that emphasized private investment as the engine for U.S. economic growth. Both components of this term, "private" and "investment," had implications for the administration’s international economic strategy. From the point of view of investment, it was important that international events not pressure on the Federal Reserve to raise interest rates, since this would have curtailed capital formation and vitiated the effects of the administration’s signature achievement: deficit reduction. A strong dollar -- or rather a dollar that was not expected to weaken -- was a key component of a policy which aimed at keeping the Fed comfortable with low interest rates. In addition, it was important to create a demand for the goods and services generated by this additional productive capacity. To the extent that this demand resided abroad, administration officials saw it as important that the process of increasing international integration, of both trade and finance, move forward for the interest of economic development in emerging markets and therefore in support of U.S. economic growth.”

The process of integration consisted of restructuring “international financial architecture” (Pelaez and Pelaez, International Financial Architecture: G7, IMF, BIS, Debtors and Creditors (2005)). Policy concerns subsequently shifted to the external imbalances, or current account deficits, and internal imbalances, or government deficits (Pelaez and Pelaez, The Global Recession Risk: Dollar Devaluation and the World Economy (2007)). Fed policy consisted of lowering the policy rate or fed funds rate, which is close to the marginal cost of funding of banks, toward zero during the past decade. Near zero interest rates induce carry trades of selling dollar debt (borrowing), shorting the USD and investing in risk financial assets. Without risk aversion, near zero interest rates cause devaluation of the dollar. Chart VI-3 shows the weakening USD between the recession of 2001 and the contraction after IVQ2007. There was a flight to dollar assets and especially obligations of the US government after Sep 2008. Cochrane and Zingales (2009) show that flight was coincident with proposals of TARP (Troubled Asset Relief Program) to withdraw “toxic assets” in US banks (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a) and Regulation of Banks and Finance (2009b)). There are shocks to globalization in the form of regulation, trade and devaluation wars and breakdown of international cooperation (Pelaez and Pelaez, Globalization and the State: Vol. I (2008a), Globalization and the State: Vol. II (2008b) and Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008c)). As evident in Chart VI-3A, there is no exit from near zero interest rates without a financial crisis and economic contraction, verified by the increase of interest rates from 1 percent in Jun 2004 to 5.25 percent in Jun 2006. The Federal Open Market Committee (FOMC) lowered the target of the fed funds rate from 7.03 percent on Jul 3, 2000, to 1.00 percent on Jun 22, 2004, in pursuit of non-existing deflation (Pelaez and Pelaez, International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-85). The FOMC implemented increments of 25 basis points of the fed funds target from Jun 2004 to Jun 2006, raising the fed funds rate to 5.25 percent on Jul 3, 2006, as shown in Chart VI-3A. The gradual exit from the first round of unconventional monetary policy from 1.00 percent in Jun 2004 (http://www.federalreserve.gov/boarddocs/press/monetary/2004/20040630/default.htm) to 5.25 percent in Jun 2006 (http://www.federalreserve.gov/newsevents/press/monetary/20060629a.htm) caused the financial crisis and global recession. There are conflicts on exchange rate movements among central banks. There is concern of declining inflation in the euro area and appreciation of the euro. On Jun 5, 2014, the European Central Bank introduced cuts in interest rates and a negative rate paid on deposits of banks (http://www.ecb.europa.eu/press/pr/date/2014/html/pr140605.en.html):

“5 June 2014 - Monetary policy decisions

At today’s meeting the Governing Council of the ECB took the following monetary policy decisions:

1. The interest rate on the main refinancing operations of the Eurosystem will be decreased by 10 basis points to 0.15%, starting from the operation to be settled on 11 June 2014.
2. The interest rate on the marginal lending facility will be decreased by 35 basis points to 0.40%, with effect from 11 June 2014.
3. The interest rate on the deposit facility will be decreased by 10 basis points to -0.10%, with effect from 11 June 2014. A separate press release to be published at 3.30 p.m. CET today will provide details on the implementation of the negative deposit facility rate.”

The ECB also introduced new measures of monetary policy on Jun 5, 2014 (http://www.ecb.europa.eu/press/pr/date/2014/html/pr140605_2.en.html):

“5 June 2014 - ECB announces monetary policy measures to enhance the functioning of the monetary policy transmission mechanism

In pursuing its price stability mandate, the Governing Council of the ECB has today announced measures to enhance the functioning of the monetary policy transmission mechanism by supporting lending to the real economy. In particular, the Governing Council has decided:

1. To conduct a series of targeted longer-term refinancing operations (TLTROs) aimed at improving bank lending to the euro area non-financial private sector ^[1], excluding loans to households for house purchase, over a window of two years.
2. To intensify preparatory work related to outright purchases of asset-backed securities (ABS).”

The President of the European Central Bank (ECB) Mario Draghi analyzed the measures at a press conference (http://www.ecb.europa.eu/press/pressconf/2014/html/is140605.en.html). At the press conference following the meeting of the ECB on Jul 3, 2014, Mario Draghi stated (http://www.ecb.europa.eu/press/pressconf/2014/html/is140703.en.html): “In fact, as I said, interest rates will stay low for an extended period of time, and the Governing Council is unanimous in its commitment to use also nonstandard, unconventional measures to cope with the risk of a too-prolonged period of time of low inflation.”

The President of the ECB Mario Draghi analyzed unemployment in the euro area and the policy response policy in a speech at the Jackson Hole meeting of central bankers on Aug 22, 2014 (http://www.ecb.europa.eu/press/key/date/2014/html/sp140822.en.html):

“We have already seen exchange rate movements that should support both aggregate demand and inflation, which we expect to be sustained by the diverging expected paths of policy in the US and the euro area (Figure 7). We will launch our first Targeted Long-Term Refinancing Operation in September, which has so far garnered significant interest from banks. And our preparation for outright purchases in asset-backed security (ABS) markets is fast moving forward and we expect that it should contribute to further credit easing. Indeed, such outright purchases would meaningfully contribute to diversifying the channels for us to generate liquidity.”

On Sep 4, 2014, the European Central Bank lowered policy rates (http://www.ecb.europa.eu/press/pr/date/2014/html/pr140904.en.html):

“4 September 2014 - Monetary policy decisions

At today’s meeting the Governing Council of the ECB took the following monetary policy decisions:

1. The interest rate on the main refinancing operations of the Eurosystem will be decreased by 10 basis points to 0.05%, starting from the operation to be settled on 10 September 2014.
2. The interest rate on the marginal lending facility will be decreased by 10 basis points to 0.30%, with effect from 10 September 2014.
3. The interest rate on the deposit facility will be decreased by 10 basis points to -0.20%, with effect from 10 September 2014.”

The President of the European Central Bank announced on Sep 4, 2014, the decision to expand the balance sheet by purchases of asset-backed securities (ABS) in a new ABS Purchase Program (ABSPP) and covered bonds (http://www.ecb.europa.eu/press/pressconf/2014/html/is140904.en.html):

“Based on our regular economic and monetary analyses, the Governing Council decided today to lower the interest rate on the main refinancing operations of the Eurosystem by 10 basis points to 0.05% and the rate on the marginal lending facility by 10 basis points to 0.30%. The rate on the deposit facility was lowered by 10 basis points to -0.20%. In addition, the Governing Council decided to start purchasing non-financial private sector assets. The Eurosystem will purchase a broad portfolio of simple and transparent asset-backed securities (ABSs) with underlying assets consisting of claims against the euro area non-financial private sector under an ABS purchase programme (ABSPP). This reflects the role of the ABS market in facilitating new credit flows to the economy and follows the intensification of preparatory work on this matter, as decided by the Governing Council in June. In parallel, the Eurosystem will also purchase a broad portfolio of euro-denominated covered bonds issued by MFIs domiciled in the euro area under a new covered bond purchase programme (CBPP3). Interventions under these programmes will start in October 2014. The detailed modalities of these programmes will be announced after the Governing Council meeting of 2 October 2014. The newly decided measures, together with the targeted longer-term refinancing operations which will be conducted in two weeks, will have a sizeable impact on our balance sheet.”

At the Thirtieth Meeting of the International Monetary and Financial Committee of the IMF (IMFC), the President of the European Central Bank (ECB), Mario Draghi stated (http://www.ecb.europa.eu/press/key/date/2014/html/sp141010.en.html):

“Our monetary policy continues to aim at firmly anchoring medium to long-term inflation expectations, in line with our objective of maintaining inflation rates below, but close to, 2% over the medium term. In this context, we have taken both conventional and unconventional measures that will contribute to a return of inflation rates to levels closer to our aim. Our unconventional measures, more specifically our TLTROs (Targeted Longer-Term Refinancing Operations) and our new purchase programmes for ABSs and covered bonds, will further enhance the functioning of our monetary policy transmission mechanism and facilitate credit provision to the real economy. Should it become necessary to further address risks of too prolonged a period of low inflation, the ECB’s Governing Council is unanimous in its commitment to using additional unconventional instruments within its mandate.”

In a speech on “Monetary Policy in the Euro Area,” on Nov 21, 2014, the President of the European Central Bank, Mario Draghi, advised of the determination to bring inflation back to normal levels by aggressive holding of securities in the balance sheet (http://www.ecb.europa.eu/press/key/date/2014/html/sp141121.en.html):

“In short, there is a combination of policies that will work to bring growth and inflation back on a sound path, and we all have to meet our responsibilities in achieving that. For our part, we will continue to meet our responsibility – we will do what we must to raise inflation and inflation expectations as fast as possible, as our price stability mandate requires of us.

If on its current trajectory our policy is not effective enough to achieve this, or further risks to the inflation outlook materialise, we would step up the pressure and broaden even more the channels through which we intervene, by altering accordingly the size, pace and composition of our purchases.”

In the Introductory Statement to the press conference on Dec 4,2014, the President of the European Central Bank Mario Draghi advised that (http://www.ecb.europa.eu/press/pressconf/2014/html/is141204.en.html):

“In this context, early next year the Governing Council will reassess the monetary stimulus achieved, the expansion of the balance sheet and the outlook for price developments. We will also evaluate the broader impact of recent oil price developments on medium-term inflation trends in the euro area. Should it become necessary to further address risks of too prolonged a period of low inflation, the Governing Council remains unanimous in its commitment to using additional unconventional instruments within its mandate. This would imply altering early next year the size, pace and composition of our measures.”

Chart VI-3, US Dollar Currency Indexes, Jan 4, 1995-Dec 5, 2014

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

Chart VI-3A, US, Overnight Fed Funds Rate, Yield of Three-Month Treasury Constant Maturity, Yield of Ten-Year Treasury Constant Maturity and Yield of Moody’s Baa Bond, Jan 4, 1995 to Dec 11, 2014

Source: Board of Governors of the Federal Reserve System

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

Carry trades induced by zero interest rates increase capital flows into emerging markets that appreciate exchange rates. Portfolio reallocations away from emerging markets depreciate their exchange rates in reversals of capital flows. Chart VI-4A provides the exchange rate of the Mexican peso (MXN) per US dollar from Nov 8, 1993 to Dec 5, 2014. The first data point in Chart VI-4A is MXN 3.1520 on Nov 8, 1993. The rate devalued to 11.9760 on Nov 14, 1995 during emerging market crises in the 1990s and the increase of interest rates in the US in 1994 that stressed world financial markets (Pelaez and Pelaez, International Financial Architecture 2005, The Global Recession Risk 2007, 147-77). The MXN depreciated sharply to MXN 15.4060/USD on Mar 2, 2009, during the global recession. The rate moved to MXN 11.5050/USD on May 2, 2011, during the sovereign debt crisis in the euro area. The rate depreciated to 11.9760 on May 9, 2013. The final data point is MXN 14.3260/USD on Dec 5, 2014.

Chart VI-4A, Mexican Peso (MXN) per US Dollar (USD), Nov 8, 1993 to Dec 5, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

There are collateral effects worldwide from unconventional monetary policy. In remarkable anticipation in 2005, Professor Raghuram G. Rajan (2005) warned of low liquidity and high risks of central bank policy rates approaching the zero bound (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 218-9). Professor Rajan excelled in a distinguished career as an academic economist in finance and was chief economist of the International Monetary Fund (IMF). Shefali Anand and Jon Hilsenrath, writing on Oct 13, 2013, on “India’s central banker lobbies Fed,” published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304330904579133530766149484?KEYWORDS=Rajan), interviewed Raghuram G Rajan, who is the current Governor of the Reserve Bank of India, which is India’s central bank (http://www.rbi.org.in/scripts/AboutusDisplay.aspx). In this interview, Rajan argues that central banks should avoid unintended consequences on emerging market economies of inflows and outflows of capital triggered by monetary policy. Professor Rajan, in an interview with Kartik Goyal of Bloomberg (http://www.bloomberg.com/news/2014-01-30/rajan-warns-of-global-policy-breakdown-as-emerging-markets-slide.html), warns of breakdown of global policy coordination. Professor Willem Buiter (2014Feb4), a distinguished economist currently Global Chief Economist at Citigroup (http://www.willembuiter.com/resume.pdf), writing on “The Fed’s bad manners risk offending foreigners,” on Feb 4, 2014, published in the Financial Times (http://www.ft.com/intl/cms/s/0/fbb09572-8d8d-11e3-9dbb-00144feab7de.html#axzz2suwrwkFs), concurs with Raghuram Rajan. Buiter (2014Feb4) argues that international policy cooperation in monetary policy is both in the interest of the world and the United States. Portfolio reallocations induced by combination of zero interest rates and risk events stimulate carry trades that generate wide swings in world capital flows. In a speech at the Brookings Institution on Apr 10, 2014, Raghuram G. Rajan (2014Apr10, 1, 10) argues:

“As the world seems to be struggling back to its feet after the great financial crisis, I want to draw attention to an area we need to be concerned about: the conduct of monetary policy in this integrated world. A good way to describe the current environment is one of extreme monetary easing through unconventional policies. In a world where debt overhangs and the need for structural change constrain domestic demand, a sizeable portion of the effects of such policies spillover across borders, sometimes through a weaker exchange rate. More worryingly, it prompts a reaction. Such competitive easing occurs both simultaneously and sequentially, as I will argue, and both advanced economies and emerging economies engage in it. Aggregate world demand may be weaker and more distorted than it should be, and financial risks higher. To ensure stable and sustainable growth, the international rules of the game need to be revisited. Both advanced economies and emerging economies need to adapt, else I fear we are about to embark on the next leg of a wearisome cycle. A first step to prescribing the right medicine is to recognize the cause of the sickness. Extreme monetary easing, in my view, is more cause than medicine. The sooner we recognize that, the more sustainable world growth we will have.”

Professor Raguram G Rajan, governor of the Reserve Bank of India, which is India’s central bank, warned about risks in high valuations of asset prices in an interview with Christopher Jeffery of Central Banking Journal on Aug 6, 2014 (http://www.centralbanking.com/central-banking-journal/interview/2358995/raghuram-rajan-on-the-dangers-of-asset-prices-policy-spillovers-and-finance-in-india). Professor Rajan demystifies in the interview “competitive easing” by major central banks as equivalent to competitive devaluation.

Chart VI-4B provides the rate of the Indian rupee (INR) per US dollar (USD) from Jan 2, 1973 to Dec 5, 2014. The first data point is INR 8.0200 on Jan 2, 1973. The rate depreciated sharply to INR 51.9600 on Mar 3, 2009, during the global recession. The rate appreciated to INR 44.0300/USD on Jul 28, 2011 in the midst of the sovereign debt event in the euro area. The rate overshot to INR 68.8000 on Aug 28, 2013. The final data point is INR 61.9000/USD on Dec 5, 2014.

Chart VI-4B, Indian Rupee (INR) per US Dollar (USD), Jan 2, 1973 to Dec, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

Chart VI-5 provides the exchange rate of JPY (Japan yen) per USD (US dollars). The first data point on the extreme left is JPY 357.7300/USD for Jan 4, 1971. The JPY has appreciated over the long term relative to the USD with fluctuations along an evident long-term appreciation. Before the global recession, the JPY stood at JPY 124.0900/USD on Jun 22, 2007. The use of the JPY as safe haven is evident by sharp appreciation during the global recession to JPY 110.48/USD on Aug 15, 2008, and to JPY 87.8000/USD on Jan 21, 2009. The final data point in Chart VI-5 is JPY 121.3800/USD on Dec 5, 2014 for appreciation of 2.2 percent relative to JPY 124.0900/USD on Jun 22, 2007 before the global recession and expansion characterized by recurring bouts of risk aversion. Takashi Nakamichi and Eleanor Warnock, writing on “Japan lashes out over dollar, euro,” on Dec 29, 2012, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887323530404578207440474874604.html?mod=WSJ_markets_liveupdate&mg=reno64-wsj), analyze the “war of words” launched by Japan’s new Prime Minister Shinzo Abe and his finance minister Taro Aso, arguing of deliberate devaluations of the USD and EUR relative to the JPY, which are hurting Japan’s economic activity. Gerard Baker and Jacob M. Shlesinger, writing on “Bank of Japan’s Kuroda signals impatience with Abe government,” on May 23, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303480304579579311491068756?KEYWORDS=bank+of+japan+kuroda&mg=reno64-wsj), analyze concerns of the Governor of the Bank of Japan Haruhiko Kuroda that the JPY has strengthened relative to the USD, partly eroding earlier depreciation. The data in Table VI-6 is obtained from closing dates in New York published by the Wall Street Journal (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata).

Chart VI-5, Japanese Yen JPY per US Dollars USD, Monthly, Jan 4, 1971-Dec 5, 2014

Note: US Recessions in Shaded Areas 

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

The financial crisis and global recession were caused by interest rate and housing subsidies and affordability policies that encouraged high leverage and risks, low liquidity and unsound credit (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4). Several past comments of this blog elaborate on these arguments, among which: http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html

Zero interest rates in the United States forever tend to depreciate the dollar against every other currency if there is no risk aversion preventing portfolio rebalancing toward risk financial assets, which include the capital markets and exchange rates of emerging-market economies. The objective of unconventional monetary policy as argued by Yellen 2011AS) is to devalue the dollar to increase net exports that increase US economic growth. Increasing net exports and internal economic activity in the US is equivalent to decreasing net exports and internal economic activity in other countries.

Continental territory, rich endowment of natural resources, investment in human capital, teaching and research universities, motivated labor force and entrepreneurial initiative provide Brazil with comparative advantages in multiple economic opportunities. Exchange rate parity is critical in achieving Brazil’s potential but is difficult in a world of zero interest rates. Chart IV-6 of the Board of Governors of the Federal Reserve System provides the rate of Brazilian real (BRL) per US dollar (USD) from BRL 1.2074/USD on Jan 4, 1999 to BRL 2.6010/USD on Dec 5, 2014. The rate reached BRL 3.9450/USD on Oct 10, 2002 appreciating 60.5 percent to BRL 1.5580/USD on Aug 1, 2008. The rate depreciated 68.1 percent to BRL 2.6187/USD on Dec 5, 2008 during worldwide flight from risk. The rate appreciated again by 41.3 percent to BRL 1.5375/USD on Jul 26, 2011. The final data point in Chart VI-6 is BRL 2.6010/USD on Dec 5, 2014 for depreciation of 69.2 percent. The data in Table VI-6 is obtained from closing dates in New York published by the Wall Street Journal (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata).

Chart VI-6, Brazilian Real (BRL) per US Dollar (USD) Jan 4, 1999 to Dec 5, 2014

Note: US Recessions in Shaded Areas 

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

Chart VI-7 of the Board of Governors of the Federal Reserve System provides the history of the BRL beginning with the first data point of BRL 0.8440/USD on Jan 2, 1995. The rate jumped to BRL 2.0700/USD on Jan 29, 1999 after changes in exchange rate policy and then to BRL 2.2000/USD on Mar 3, 1999. The rate depreciated 26.7 percent to BRL 2.7880/USD on Sep 21, 2001 relative to Mar 3, 1999.

Chart VI-7, Brazilian Real (BRL) per US Dollar (USD), Jan 2, 1995 to Dec 5, 2014

Note: US Recessions in Shaded Areas 

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H10/default.htm

The major reason and channel of transmission of unconventional monetary policy is through expectations of inflation. Fisher (1930) provided theoretical and historical relation of interest rates and inflation. Let i_n be the nominal interest rate, i_r the real or inflation-adjusted interest rate and π^e the expectation of inflation in the time term of the interest rate, which are all expressed as proportions. The following expression provides the relation of real and nominal interest rates and the expectation of inflation:

(1 + i_r) = (1 + i_n)/(1 + π^e) (1)

That is, the real interest rate equals the nominal interest rate discounted by the expectation of inflation in time term of the interest rate. Fisher (1933) analyzed the devastating effect of deflation on debts. Nominal debt contracts remained at original principal interest but net worth and income of debtors contracted during deflation. Real interest rates increase during declining inflation. For example, if the interest rate is 3 percent and prices decline 0.2 percent, equation (1) calculates the real interest rate as:

(1 +0.03)/(1 – 0.02) = 1.03/(0.998) = 1.032

That is, the real rate of interest is (1.032 – 1) 100 or 3.2 percent. If inflation were 2 percent, the real rate of interest would be 0.98 percent, or about 1.0 percent {[(1.03/1.02) -1]100 = 0.98%}.

The yield of the one-year Treasury security was quoted in the Wall Street Journal at 0.114 percent on Fri May 17, 2013 (http://online.wsj.com/mdc/page/marketsdata.html?mod=WSJ_topnav_marketdata_main). The expected rate of inflation π^e in the next twelve months is not observed. Assume that it would be equal to the rate of inflation in the past twelve months estimated by the Bureau of Economic Analysis (BLS) at 1.1 percent (http://www.bls.gov/cpi/). The real rate of interest would be obtained as follows:

(1 + 0.00114)/(1 + 0.011) = (1 + r_r) = 0.9902

That is, i_r is equal to 1 – 0.9902 or minus 0.98 percent. Investing in a one-year Treasury security results in a loss of 0.98 percent relative to inflation. The objective of unconventional monetary policy of zero interest rates is to induce consumption and investment because of the loss to inflation of riskless financial assets. Policy would be truly irresponsible if it intended to increase inflationary expectations or π^e. The result could be the same rate of unemployment with higher inflation (Kydland and Prescott 1977).

Focus is shifting from tapering quantitative easing by the Federal Open Market Committee (FOMC). There is sharp distinction between the two measures of unconventional monetary policy: (1) fixing of the overnight rate of fed funds at 0 to ¼ percent; and (2) outright purchase of Treasury and agency securities and mortgage-backed securities for the balance sheet of the Federal Reserve. Markets overreacted to the so-called “paring” of outright purchases to $15 billion of securities per month for the balance sheet of the Fed. What is truly important is the fixing of the overnight fed funds at 0 to ¼ percent for which there is no end in sight as evident in the FOMC statement for Oct 29, 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20141029a.htm):

“To support continued progress toward maximum employment and price stability, the Committee today reaffirmed its view that the current 0 to 1/4 percent target range for the federal funds rate remains appropriate. In determining how long to maintain this target range, the Committee will assess progress--both realized and expected--toward its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial developments. The Committee anticipates, based on its current assessment, that it likely will be appropriate to maintain the 0 to 1/4 percent target range for the federal funds rate for a considerable time following the end of its asset purchase program this month, especially if projected inflation continues to run below the Committee's 2 percent longer-run goal, and provided that longer-term inflation expectations remain well anchored. However, if incoming information indicates faster progress toward the Committee's employment and inflation objectives than the Committee now expects, then increases in the target range for the federal funds rate are likely to occur sooner than currently anticipated. Conversely, if progress proves slower than expected, then increases in the target range are likely to occur later than currently anticipated” (emphasis added).

What is truly important is the fixing of the overnight fed funds at 0 to ¼ percent for which there is no end in sight as evident in the FOMC statement for Oct 29, 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20141029a.htm):

“To support continued progress toward maximum employment and price stability, the Committee today reaffirmed its view that the current 0 to 1/4 percent target range for the federal funds rate remains appropriate. In determining how long to maintain this target range, the Committee will assess progress--both realized and expected--toward its objectives of maximum employment and 2 percent inflation. This assessment will take into account a wide range of information, including measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial developments. The Committee anticipates, based on its current assessment, that it likely will be appropriate to maintain the 0 to 1/4 percent target range for the federal funds rate for a considerable time following the end of its asset purchase program this month, especially if projected inflation continues to run below the Committee's 2 percent longer-run goal, and provided that longer-term inflation expectations remain well anchored. However, if incoming information indicates faster progress toward the Committee's employment and inflation objectives than the Committee now expects, then increases in the target range for the federal funds rate are likely to occur sooner than currently anticipated. Conversely, if progress proves slower than expected, then increases in the target range are likely to occur later than currently anticipated” (emphasis added).

How long is “considerable time”? At the press conference following the meeting on Mar 19, 2014, Chair Yellen answered a question of Jon Hilsenrath of the Wall Street Journal explaining “In particular, the Committee has endorsed the view that it anticipates that will be a considerable period after the asset purchase program ends before it will be appropriate to begin to raise rates. And of course on our present path, well, that's not utterly preset. We would be looking at next, next fall. So, I think that's important guidance” (http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20140319.pdf). Many focused on “next fall,” ignoring that the path of increasing rates is not “utterly preset.”

At a speech on Mar 31, 2014, Chair Yellen analyzed labor market conditions as follows (http://www.federalreserve.gov/newsevents/speech/yellen20140331a.htm):

“And based on the evidence available, it is clear to me that the U.S. economy is still considerably short of the two goals assigned to the Federal Reserve by the Congress. The first of those goals is maximum sustainable employment, the highest level of employment that can be sustained while maintaining a stable inflation rate. Most of my colleagues on the Federal Open Market Committee and I estimate that the unemployment rate consistent with maximum sustainable employment is now between 5.2 percent and 5.6 percent, well below the 6.7 percent rate in February.

Let me explain what I mean by that word "slack" and why it is so important.

Slack means that there are significantly more people willing and capable of filling a job than there are jobs for them to fill. During a period of little or no slack, there still may be vacant jobs and people who want to work, but a large share of those willing to work lack the skills or are otherwise not well suited for the jobs that are available. With 6.7 percent unemployment, it might seem that there must be a lot of slack in the U.S. economy, but there are reasons why that may not be true.”

Yellen (2014Aug22) provides comprehensive review of the theory and measurement of labor markets. Monetary policy pursues a policy of attaining its “dual mandate” of (http://www.federalreserve.gov/aboutthefed/mission.htm):

“Conducting the nation's monetary policy by influencing the monetary and credit conditions in the economy in pursuit of maximum employment, stable prices, and moderate long-term interest rates”

Yellen (2014Aug22) finds that the unemployment rate is not sufficient in determining slack:

“One convenient way to summarize the information contained in a large number of indicators is through the use of so-called factor models. Following this methodology, Federal Reserve Board staff developed a labor market conditions index from 19 labor market indicators, including four I just discussed. This broadly based metric supports the conclusion that the labor market has improved significantly over the past year, but it also suggests that the decline in the unemployment rate over this period somewhat overstates the improvement in overall labor market conditions.”

Yellen (2014Aug22) restates that the FOMC determines monetary policy on newly available information and interpretation of labor markets and inflation and does not follow a preset path:

“But if progress in the labor market continues to be more rapid than anticipated by the Committee or if inflation moves up more rapidly than anticipated, resulting in faster convergence toward our dual objectives, then increases in the federal funds rate target could come sooner than the Committee currently expects and could be more rapid thereafter. Of course, if economic performance turns out to be disappointing and progress toward our goals proceeds more slowly than we expect, then the future path of interest rates likely would be more accommodative than we currently anticipate. As I have noted many times, monetary policy is not on a preset path. The Committee will be closely monitoring incoming information on the labor market and inflation in determining the appropriate stance of monetary policy.”

Yellen (2014Aug22) states that “Historically, slack has accounted for only a small portion of the fluctuations in inflation. Indeed, unusual aspects of the current recovery may have shifted the lead-lag relationship between a tightening labor market and rising inflation pressures in either direction.”

The minutes of the meeting of the Federal Open Market Committee (FOMC) on Sep 16-17, 2014, reveal concern with global economic conditions (http://www.federalreserve.gov/monetarypolicy/fomcminutes20140917.htm):

“Most viewed the risks to the outlook for economic activity and the labor market as broadly balanced. However, a number of participants noted that economic growth over the medium term might be slower than they expected if foreign economic growth came in weaker than anticipated, structural productivity continued to increase only slowly, or the recovery in residential construction continued to lag.”

Chair Yellen analyzes the view of inflation (http://www.federalreserve.gov/newsevents/speech/yellen20140416a.htm):

“Inflation, as measured by the price index for personal consumption expenditures, has slowed from an annual rate of about 2-1/2 percent in early 2012 to less than 1 percent in February of this year. This rate is well below the Committee's 2 percent longer-run objective. Many advanced economies are observing a similar softness in inflation.

To some extent, the low rate of inflation seems due to influences that are likely to be temporary, including a deceleration in consumer energy prices and outright declines in core import prices in recent quarters. Longer-run inflation expectations have remained remarkably steady, however. We anticipate that, as the effects of transitory factors subside and as labor market gains continue, inflation will gradually move back toward 2 percent.”

There is a critical phrase in the statement of Sep 19, 2013 (http://www.federalreserve.gov/newsevents/press/monetary/20130918a.htm): “but mortgage rates have risen further.” Did the increase of mortgage rates influence the decision of the FOMC not to taper? Is FOMC “communication” and “guidance” successful? Will the FOMC increase purchases of mortgage-backed securities if mortgage rates increase?

At the confirmation hearing on nomination for Chair of the Board of Governors of the Federal Reserve System, Vice Chair Yellen (2013Nov14 http://www.federalreserve.gov/newsevents/testimony/yellen20131114a.htm), states needs and intentions of policy:

“We have made good progress, but we have farther to go to regain the ground lost in the crisis and the recession. Unemployment is down from a peak of 10 percent, but at 7.3 percent in October, it is still too high, reflecting a labor market and economy performing far short of their potential. At the same time, inflation has been running below the Federal Reserve's goal of 2 percent and is expected to continue to do so for some time.

For these reasons, the Federal Reserve is using its monetary policy tools to promote a more robust recovery. A strong recovery will ultimately enable the Fed to reduce its monetary accommodation and reliance on unconventional policy tools such as asset purchases. I believe that supporting the recovery today is the surest path to returning to a more normal approach to monetary policy.”

In testimony on the Semiannual Monetary Policy Report to the Congress before the Committee on Financial Services, US House of Representatives, on Feb 11, 2014, Chair Janet Yellen states (http://www.federalreserve.gov/newsevents/testimony/yellen20140211a.htm):

“Turning to monetary policy, let me emphasize that I expect a great deal of continuity in the FOMC's approach to monetary policy. I served on the Committee as we formulated our current policy strategy and I strongly support that strategy, which is designed to fulfill the Federal Reserve's statutory mandate of maximum employment and price stability.  If incoming information broadly supports the Committee's expectation of ongoing improvement in labor market conditions and inflation moving back toward its longer-run objective, the Committee will likely reduce the pace of asset purchases in further measured steps at future meetings. That said, purchases are not on a preset course, and the Committee's decisions about their pace will remain contingent on its outlook for the labor market and inflation as well as its assessment of the likely efficacy and costs of such purchases.  In December of last year and again this January, the Committee said that its current expectation--based on its assessment of a broad range of measures of labor market conditions, indicators of inflation pressures and inflation expectations, and readings on financial developments--is that it likely will be appropriate to maintain the current target range for the federal funds rate well past the time that the unemployment rate declines below 6-1/2 percent, especially if projected inflation continues to run below the 2 percent goal. I am committed to achieving both parts of our dual mandate: helping the economy return to full employment and returning inflation to 2 percent while ensuring that it does not run persistently above or below that level (emphasis added).”

In testimony before the Committee on the Budget of the US Senate on May 8, 2004, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm):

“The economy has continued to recover from the steep recession of 2008 and 2009. Real gross domestic product (GDP) growth stepped up to an average annual rate of about 3-1/4 percent over the second half of last year, a faster pace than in the first half and during the preceding two years. Although real GDP growth is currently estimated to have paused in the first quarter of this year, I see that pause as mostly reflecting transitory factors, including the effects of the unusually cold and snowy winter weather. With the harsh winter behind us, many recent indicators suggest that a rebound in spending and production is already under way, putting the overall economy on track for solid growth in the current quarter. One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.

Conditions in the labor market have continued to improve. The unemployment rate was 6.3 percent in April, about 1-1/4 percentage points below where it was a year ago. Moreover, gains in payroll employment averaged nearly 200,000 jobs per month over the past year. During the economic recovery so far, payroll employment has increased by about 8-1/2 million jobs since its low point, and the unemployment rate has declined about 3-3/4 percentage points since its peak.

While conditions in the labor market have improved appreciably, they are still far from satisfactory. Even with recent declines in the unemployment rate, it continues to be elevated. Moreover, both the share of the labor force that has been unemployed for more than six months and the number of individuals who work part time but would prefer a full-time job are at historically high levels. In addition, most measures of labor compensation have been rising slowly--another signal that a substantial amount of slack remains in the labor market.

Inflation has been quite low even as the economy has continued to expand. Some of the factors contributing to the softness in inflation over the past year, such as the declines seen in non-oil import prices, will probably be transitory. Importantly, measures of longer-run inflation expectations have remained stable. That said, the Federal Open Market Committee (FOMC) recognizes that inflation persistently below 2 percent--the rate that the Committee judges to be most consistent with its dual mandate--could pose risks to economic performance, and we are monitoring inflation developments closely.

Looking ahead, I expect that economic activity will expand at a somewhat faster pace this year than it did last year, that the unemployment rate will continue to decline gradually, and that inflation will begin to move up toward 2 percent. A faster rate of economic growth this year should be supported by reduced restraint from changes in fiscal policy, gains in household net worth from increases in home prices and equity values, a firming in foreign economic growth, and further improvements in household and business confidence as the economy continues to strengthen. Moreover, U.S. financial conditions remain supportive of growth in economic activity and employment.”

In his classic restatement of the Keynesian demand function in terms of “liquidity preference as behavior toward risk,” James Tobin (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/1981/tobin-bio.html) identifies the risks of low interest rates in terms of portfolio allocation (Tobin 1958, 86):

“The assumption that investors expect on balance no change in the rate of interest has been adopted for the theoretical reasons explained in section 2.6 rather than for reasons of realism. Clearly investors do form expectations of changes in interest rates and differ from each other in their expectations. For the purposes of dynamic theory and of analysis of specific market situations, the theories of sections 2 and 3 are complementary rather than competitive. The formal apparatus of section 3 will serve just as well for a non-zero expected capital gain or loss as for a zero expected value of g. Stickiness of interest rate expectations would mean that the expected value of g is a function of the rate of interest r, going down when r goes down and rising when r goes up. In addition to the rotation of the opportunity locus due to a change in r itself, there would be a further rotation in the same direction due to the accompanying change in the expected capital gain or loss. At low interest rates expectation of capital loss may push the opportunity locus into the negative quadrant, so that the optimal position is clearly no consols, all cash. At the other extreme, expectation of capital gain at high interest rates would increase sharply the slope of the opportunity locus and the frequency of no cash, all consols positions, like that of Figure 3.3. The stickier the investor's expectations, the more sensitive his demand for cash will be to changes in the rate of interest (emphasis added).”

Tobin (1969) provides more elegant, complete analysis of portfolio allocation in a general equilibrium model. The major point is equally clear in a portfolio consisting of only cash balances and a perpetuity or consol. Let g be the capital gain, r the rate of interest on the consol and r^e the expected rate of interest. The rates are expressed as proportions. The price of the consol is the inverse of the interest rate, (1+r^e). Thus, g = [(r/r^e) – 1]. The critical analysis of Tobin is that at extremely low interest rates there is only expectation of interest rate increases, that is, dr^e>0, such that there is expectation of capital losses on the consol, dg<0. Investors move into positions combining only cash and no consols. Valuations of risk financial assets would collapse in reversal of long positions in carry trades with short exposures in a flight to cash. There is no exit from a central bank created liquidity trap without risks of financial crash and another global recession. 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 statement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption 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 (10

Equation (1) shows that as r goes to zero, r→0, W grows without bound, W→∞. Unconventional monetary policy lowers interest rates to increase the present value of cash flows derived from projects of firms, creating the impression of long-term increase in net worth. An attempt to reverse unconventional monetary policy necessarily causes increases in interest rates, creating the opposite perception of declining net worth. As r→∞, W = Y/r →0. There is no exit from unconventional monetary policy without increasing interest rates with resulting pain of financial crisis and adverse effects on production, investment and employment.

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (Section I and earlier (http://cmpassocregulationblog.blogspot.com/2014/11/fluctuating-financial-variables.html and earlier http://cmpassocregulationblog.blogspot.com/2014/08/weakening-world-economic-growth.html). This is merely another case of theory without reality with dubious policy proposals. The current reality is cyclical slow growth.

In delivering the biannual report on monetary policy (Board of Governors 2013Jul17), Chairman Bernanke (2013Jul17) advised Congress that:

“Instead, we are providing additional policy accommodation through two distinct yet complementary policy tools. The first tool is expanding the Federal Reserve's portfolio of longer-term Treasury securities and agency mortgage-backed securities (MBS); we are currently purchasing $40 billion per month in agency MBS and $45 billion per month in Treasuries. We are using asset purchases and the resulting expansion of the Federal Reserve's balance sheet primarily to increase the near-term momentum of the economy, with the specific goal of achieving a substantial improvement in the outlook for the labor market in a context of price stability. We have made some progress toward this goal, and, with inflation subdued, we intend to continue our purchases until a substantial improvement in the labor market outlook has been realized. We are relying on near-zero short-term interest rates, together with our forward guidance that rates will continue to be exceptionally low--our second tool--to help maintain a high degree of monetary accommodation for an extended period after asset purchases end, even as the economic recovery strengthens and unemployment declines toward more-normal levels. In appropriate combination, these two tools can provide the high level of policy accommodation needed to promote a stronger economic recovery with price stability.

The Committee's decisions regarding the asset purchase program (and the overall stance of monetary policy) depend on our assessment of the economic outlook and of the cumulative progress toward our objectives. Of course, economic forecasts must be revised when new information arrives and are thus necessarily provisional.”

Friedman (1953) argues there are three lags in effects of monetary policy: (1) between the need for action and recognition of the need; (2) the recognition of the need and taking of actions; and (3) taking of action and actual effects. Friedman (1953) finds that the combination of these lags with insufficient knowledge of the current and future behavior of the economy causes discretionary economic policy to increase instability of the economy or standard deviations of real income σ_y and prices σ_p. Policy attempts to circumvent the lags by policy impulses based on forecasts. We are all naïve about forecasting. Data are available with lags and revised to maintain high standards of estimation. Policy simulation models estimate economic relations with structures prevailing before simulations of policy impulses such that parameters change as discovered by Lucas (1977). Economic agents adjust their behavior in ways that cause opposite results from those intended by optimal control policy as discovered by Kydland and Prescott (1977). Advance guidance attempts to circumvent expectations by economic agents that could reverse policy impulses but is of dubious effectiveness. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/search?q=rules+versus+authorities http://cmpassocregulationblog.blogspot.com/2014/07/financial-irrational-exuberance.html http://cmpassocregulationblog.blogspot.com/2014/07/world-inflation-waves-united-states.html). Jon Hilsenrath, writing on “New view into Fed’s response to crisis,” on Feb 21, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303775504579396803024281322?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes 1865 pages of transcripts of eight formal and six emergency policy meetings at the Fed in 2008 (http://www.federalreserve.gov/monetarypolicy/fomchistorical2008.htm). If there were an infallible science of central banking, models and forecasts would provide accurate information to policymakers on the future course of the economy in advance. Such forewarning is essential to central bank science because of the long lag between the actual impulse of monetary policy and the actual full effects on income and prices many months and even years ahead (Romer and Romer 2004, Friedman 1961, 1953, Culbertson 1960, 1961, Batini and Nelson 2002). The transcripts of the Fed meetings in 2008 (http://www.federalreserve.gov/monetarypolicy/fomchistorical2008.htm) analyzed by Jon Hilsenrath demonstrate that Fed policymakers frequently did not understand the current state of the US economy in 2008 and much less the direction of income and prices. The conclusion of Friedman (1953) is that monetary impulses increase financial and economic instability because of lags in anticipating needs of policy, taking policy decisions and effects of decisions. This is a fortiori true when untested unconventional monetary policy in gargantuan doses shocks the economy and financial markets.

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 14,164.53 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 17,280.83 on Fri Dec 12, 2014, which is higher by 22.0 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 21.7 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs. Perhaps one of the most critical statements on policy is the answer to a question of Peter Barnes by Chair Janet Yellen at the press conference following the meeting on Jun 18, 2014 (page 19 at http://www.federalreserve.gov/mediacenter/files/FOMCpresconf20140618.pdf):

So I don't have a sense--the committee doesn't try to gauge what is the right level of equity prices. But we do certainly monitor a number of different metrics that give us a feeling for where valuations are relative to things like earnings or dividends, and look at where these metrics stand in comparison with previous history to get a sense of whether or not we're moving to valuation levels that are outside of historical norms, and I still don't see that. I still don't see that for equity prices broadly” (emphasis added).

In a speech at the IMF on Jul 2, 2014, Chair Yellen analyzed the link between monetary policy and financial risks (http://www.federalreserve.gov/newsevents/speech/yellen20140702a.htm):

“Monetary policy has powerful effects on risk taking. Indeed, the accommodative policy stance of recent years has supported the recovery, in part, by providing increased incentives for households and businesses to take on the risk of potentially productive investments. But such risk-taking can go too far, thereby contributing to fragility in the financial system. This possibility does not obviate the need for monetary policy to focus primarily on price stability and full employment--the costs to society in terms of deviations from price stability and full employment that would arise would likely be significant. In the private sector, key vulnerabilities included high levels of leverage, excessive dependence on unstable short-term funding, weak underwriting of loans, deficiencies in risk measurement and risk management, and the use of exotic financial instruments that redistributed risk in nontransparent ways.”

Yellen (2014Jul14) warned again at the Committee on Banking, Housing and Urban Affairs on Jul 15, 2014:

“The Committee recognizes that low interest rates may provide incentives for some investors to “reach for yield,” and those actions could increase vulnerabilities in the financial system to adverse events. While prices of real estate, equities, and corporate bonds have risen appreciably and valuation metrics have increased, they remain generally in line with historical norms. In some sectors, such as lower-rated corporate debt, valuations appear stretched and issuance has been brisk. Accordingly, we are closely monitoring developments in the leveraged loan market and are working to enhance the effectiveness of our supervisory guidance. More broadly, the financial sector has continued to become more resilient, as banks have continued to boost their capital and liquidity positions, and growth in wholesale short-term funding in financial markets has been modest” (emphasis added).

Greenspan (1996) made similar warnings:

“Clearly, sustained low inflation implies less uncertainty about the future, and lower risk premiums imply higher prices of stocks and other earning assets. We can see that in the inverse relationship exhibited by price/earnings ratios and the rate of inflation in the past. But how do we know when irrational exuberance has unduly escalated asset values, which then become subject to unexpected and prolonged contractions as they have in Japan over the past decade? And how do we factor that assessment into monetary policy? We as central bankers need not be concerned if a collapsing financial asset bubble does not threaten to impair the real economy, its production, jobs, and price stability. Indeed, the sharp stock market break of 1987 had few negative consequences for the economy. But we should not underestimate or become complacent about the complexity of the interactions of asset markets and the economy. Thus, evaluating shifts in balance sheets generally, and in asset prices particularly, must be an integral part of the development of monetary policy” (emphasis added).

Bernanke (2010WP) and Yellen (2011AS) reveal the emphasis of monetary policy on the impact of the rise of stock market valuations in stimulating consumption by wealth effects on household confidence. What is the success in evaluating deviations of valuations of risk financial assets from “historical norms”? What are the consequences on economic activity and employment of deviations of valuations of risk financial assets from those “historical norms”? What are the policy tools and their effectiveness in returning valuations of risk financial assets to their “historical norms”?

The key policy is maintaining fed funds rate between 0 and ¼ percent. An increase in fed funds rates could cause flight out of risk financial markets worldwide. There is no exit from this policy without major financial market repercussions. There are high costs and risks of this policy because indefinite financial repression induces carry trades with high leverage, risks and illiquidity.

Professor Raguram G Rajan, governor of the Reserve Bank of India, which is India’s central bank, warned about risks in high valuations of asset prices in an interview with Christopher Jeffery of Central Banking Journal on Aug 6, 2014 (http://www.centralbanking.com/central-banking-journal/interview/2358995/raghuram-rajan-on-the-dangers-of-asset-prices-policy-spillovers-and-finance-in-india). Professor Rajan demystifies in the interview “competitive easing” by major central banks as equivalent to competitive devaluation. Rajan (2005) anticipated the risks of the world financial crisis. Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor (1993, 1998LB, 1999, 1998LB, 1999, 2007JH, 2008Nov, 2009, 2012JMCB, 2014Jan3) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/search?q=rules+versus+authorities http://cmpassocregulationblog.blogspot.com/2014/07/financial-irrational-exuberance.html http://cmpassocregulationblog.blogspot.com/2014/07/world-inflation-waves-united-states.html).

Jon Hilsenrath, writing on “Jobs upturn isn’t enough to satisfy Fed,” on Mar 8, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324582804578348293647760204.html), finds that much stronger labor market conditions are required for the Fed to end quantitative easing. 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 78.4 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Dec 12, 2014; S&P 500 has gained 95.8 percent and DAX 69.2 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 12/12/14” 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 23.3 percent above the trough. Japan’s Nikkei Average is 96.9 percent above the trough. DJ Asia Pacific TSM is 23.9 percent above the trough. Dow Global is 44.4 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 26.6 percent above the trough. NYSE Financial Index is 54.3 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 69.2 percent above the trough. Japan’s Nikkei Average is 96.9 percent above the trough on Aug 31, 2010 and 52.5 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 17,371.58 on Fri Dec 12, 2014 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 69.4 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 4.6 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 12/12/14” in Table VI-4 shows change of 0.0 percent in the week for China’s Shanghai Composite. DJ Asia Pacific decreased 1.9 percent. NYSE Financial decreased 3.6 percent in the week. Dow Global decreased 4.2 percent in the week of Dec 5, 2014. The DJIA decreased 3.8 percent and S&P 500 decreased 3.5 percent. DAX of Germany decreased 4.9 percent. STOXX 50 decreased 6.1 percent. The USD depreciated 1.5 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 12/12/14” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Dec 12, 2014. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 12/12/14” but also relative to the peak in column “∆% Peak to 12/12/14.” There are now several equity indexes above the peak in Table VI-4: DJIA 54.2 percent, S&P 500 64.5 percent, DAX 51.5 percent, Dow Global 17.8 percent, DJ Asia Pacific 8.4 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 22.9 percent, Nikkei Average 52.5 percent, STOXX 50 7.2 percent. Shanghai Composite is 7.2 percent below the peak. The US dollar strengthened 17.6 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. Inyoung Hwang, writing on “Fed optimism spurs record bets against stock volatility,” on Aug 21, 2014, published in Bloomberg.com (http://www.bloomberg.com/news/2014-08-21/fed-optimism-spurs-record-bets-against-stock-voalitlity.html), informs that the S&P 500 is trading at 16.6 times estimated earnings, which is higher than the five-year average of 14.3 Tom Lauricella, writing on Mar 31, 2014, on “Stock investors see hints of a stronger quarter,” published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304157204579473513864900656?mod=WSJ_smq0314_LeadStory&mg=reno64-wsj), finds views of stronger earnings among many money managers with positive factors for equity markets in continuing low interest rates and US economic growth. There is important information in the Quarterly Markets review of the Wall Street Journal (http://online.wsj.com/public/page/quarterly-markets-review-03312014.html) for IQ2014. Alexandra Scaggs, writing on “Tepid profits, roaring stocks,” on May 16, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323398204578487460105747412.html), analyzes stabilization of earnings growth: 70 percent of 458 reporting companies in the S&P 500 stock index reported earnings above forecasts but sales fell 0.2 percent relative to forecasts of increase of 0.5 percent. Paul Vigna, writing on “Earnings are a margin story but for how long,” on May 17, 2013, published in the Wall Street Journal (http://blogs.wsj.com/moneybeat/2013/05/17/earnings-are-a-margin-story-but-for-how-long/), analyzes that corporate profits increase with stagnating sales while companies manage costs tightly. More than 90 percent of S&P components reported moderate increase of earnings of 3.7 percent in IQ2013 relative to IQ2012 with decline of sales of 0.2 percent. Earnings and sales have been in declining trend. In IVQ2009, growth of earnings reached 104 percent and sales jumped 13 percent. Net margins reached 8.92 percent in IQ2013, which is almost the same at 8.95 percent in IIIQ2006. Operating margins are 9.58 percent. There is concern by market participants that reversion of margins to the mean could exert pressure on earnings unless there is more accelerated growth of sales. Vigna (op. cit.) finds sales growth limited by weak economic growth. 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. Future company cash flows derive from investment projects. In IQ1980, real gross private domestic investment in the US was $951.6 billion of chained 2009 dollars, growing to $1,194.4 billion in IQ1988 or 25.5 percent. Real gross private domestic investment in the US increased 5.1 percent from $2,605.2 billion of chained 2009 dollars in IVQ2007 to $2,737.8 billion in IIQ2014, which is stagnation in comparison with growth of 47.9 percent in the comparable twenty-first quarters of expansion from $807.5 billion in IQ1983 to $1194.4 billion IQ1988. Real private fixed investment increased 1.8 percent from $2,586.3 billion of chained 2009 dollars in IVQ2007 to $2,633.8 billion in IIIQ2014. Private fixed investment fell relative to IVQ2007 in all quarters preceding IIQ2014. Growth of real private investment is mediocre for all but four quarters from IIQ2011 to IQ2012. The investment decision of United States corporations has been fractured in the current economic cycle in preference of cash.

Corporate profits with IVA and CCA rebounded with $3.1 billion in IVQ2013. Corporate profits with IVA and CCA fell $201.7 billion in IQ2014 and increased $164.1 billion in IIQ2014. Corporate profits with IVA and CCA increased $43.8 billion in IIIQ2014. In IVQ2013, profits after tax with IVA and CCA decreased $24.7 billion. In IQ2014, profits after tax with IVA and CCA decreased $268.6 billion. Profits after tax with IVA and CCA increased at $118.4 billion in IIQ2014 and at $48.6 billion in IIIQ2014. Net dividends fell at $187.0 billion in IIIQ2013 and increased at $80.6 billion in IVQ2013. Net dividends fell at $89.5 billion in IQ2014 and fell at $0.5 billion in IIQ2014. Net dividends fell at $3.9 billion in IIIQ2014. Undistributed profits with IVA and CCA fell at $105.5 billion in IVQ2013. Undistributed profits with IVA and CCA fell $178.9 percent in IQ2014 and increased at $118.8 billion in IIQ2014 and at $52.5 billion in IIIQ2014. Undistributed corporate profits swelled 304.3 percent from $107.7 billion in IQ2007 to $435.4 billion in IIIQ2014 and changed signs from minus $55.9 billion in current dollars in IVQ2007. Uncertainty originating in fiscal, regulatory and monetary policy causes wide swings in expectations and decisions by the private sector with adverse effects on investment, real economic activity and employment.

The investment decision of US business is fractured.

The basic valuation equation that is also used in capital budgeting postulates that the value of stocks or of an investment project is given by:

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

declines. Equally, decline in expected revenue from the stock or project, R_τ, 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) popularized the view of the elusive relation between stock markets and economic activity in an often-quoted phrase “the stock market has predicted nine of the last five recessions.” In the presence of zero interest rates forever, valuations of risk financial assets are likely to differ from the performance of the overall economy. The interrelations of financial and economic variables prove difficult to analyze and measure.

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

	Peak	Trough	∆% to Trough	∆% Peak to 12/12/ /14	∆% Week 12/12/14	∆% Trough to 12/12/ 14
DJIA	4/26/ 10	7/2/10	-13.6	54.2	-3.8	78.4
S&P 500	4/23/ 10	7/20/ 10	-16.0	64.5	-3.5	95.8
NYSE Finance	4/15/ 10	7/2/10	-20.3	22.9	-3.6	54.3
Dow Global	4/15/ 10	7/2/10	-18.4	17.8	-4.2	44.4
Asia Pacific	4/15/ 10	7/2/10	-12.5	8.4	-1.9	23.9
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	52.5	-3.1	96.9
China Shang.	4/15/ 10	7/02 /10	-24.7	-7.2	0.0	23.3
STOXX 50	4/15/10	7/2/10	-15.3	7.2	-6.1	26.6
DAX	4/26/ 10	5/25/ 10	-10.5	51.5	-4.9	69.2
Dollar Euro	11/25 2009	6/7 2010	21.2	17.6	-1.5	-4.6
DJ UBS Comm.	1/6/ 10	7/2/10	-14.5	NA	NA	NA
10-Year T Note	4/5/ 10	4/6/10	3.986	2.784	2.086

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

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 increased by only 4 percent from Jan 2009 to Jan 2012. 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 in early 2012 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 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2014/11/fluctuating-financial-variables.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 Theory and Reality of Cyclical Slow Growth Not Secular Stagnation: 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).

The Bureau of Labor Statistics (BLS) revised on Mar 11, 2014 “job openings, hires and separations data to incorporate the annual update to the Current Employment Statistics employment estimates and the JOLTS seasonal adjustment factors. Unadjusted data and seasonally adjusted data from December 2000 forward are subject to revisions” (http://www.bls.gov/jlt/). Hiring in the nonfarm sector (HNF) has declined from 63.3 million in 2006 to 54.2 million in 2013 or by 9.1 million while hiring in the private sector (HP) has declined from 59.1 million in 2006 to 50.7 million in 2013 or by 8.4 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.0 in 2005 to 39.7 in 2013 and in the private sector (RHP) from 52.7 in 2005 to 44.3 in 2013. Hiring has not recovered as in previous cyclical expansions because of the low rate of economic growth in the current cyclical expansion. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 21 quarters from IIIQ2009 to IIIQ2014. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IIIQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp3q14_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2014 would have accumulated to 23.0 percent. GDP in IIIQ2014 would be $18,438.0 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,273.9 billion than actual $16,164.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 26.0 million unemployed or underemployed equivalent to actual unemployment of 15.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/12/financial-risks-twenty-six-million.html

and earlier (http://cmpassocregulationblog.blogspot.com/2014/11/rules-discretionary-authorities-and.html). US GDP in IIIQ2014 is 12.3 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,164.1 billion in IIIQ2014 or 7.8 percent at the average annual equivalent rate of 1.1 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. The long-term trend is growth at average 3.3 percent per year from Jan 1919 to Oct 2014. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 123.8884 in Oct 2014. The actual index NSA in Oct 2014 is 101.5613, which is 18.0 percent below trend. Manufacturing output grew at average 2.3 percent between Dec 1986 and Dec 2013, raising the index at trend to 115.9214 in Oct 2014. The output of manufacturing at 101.5613 in Oct 2014 is 12.4 percent below trend under this alternative calculation.

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

	HNF	Rate RNF	HP	Rate HP
2001	62,633	47.4	58,501	52.7
2002	58,479	44.8	54,665	50.1
2003	56,949	43.7	53,584	49.3
2004	60,263	45.7	56,573	51.4
2005	62,951	47.0	59,179	52.7
2006	63,327	46.4	59,128	51.7
2007	62,104	45.0	57,797	49.9
2008	54,745	39.9	51,316	44.8
2009	45,931	35.0	42,703	39.3
2010	48,743	37.4	44,914	41.7
2011	50,295	38.1	47,183	43.0
2012	52,360	39.0	48,915	43.6
2013	54,191	39.7	50,718	44.3

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 recovered, remaining at a depressed level.

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2013

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 in the current environment of cyclical slow growth.

Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2015

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 6.6 percent and 2.6 percent in 2003 followed by strong rebounds of 5.8 percent in 2004 and 4.5 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 1.9 in 2007, 11.8 in 2008 and 16.1 percent in 2009. On a yearly basis, nonfarm hiring grew 6.1 percent in 2010 relative to 2009, 3.2 percent in 2011, 4.1 percent in 2012 and 3.5 percent in 2013. The relatively large length of 18 quarters of the current expansion reduces the likelihood of significant recovery of hiring levels in the United States because lower rates of growth and hiring in the final phase of expansions.

Table I-2, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2002-2013

Year	Annual ∆%
2002	-6.6
2003	-2.6
2004	5.8
2005	4.5
2006	0.6
2007	-1.9
2008	-11.8
2009	-16.1
2010	6.1
2011	3.2
2012	4.1
2013	3.5

Source: US Bureau of Labor Statistics

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

Total private hiring (HP) 12-month percentage changes of annual 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 2013.

Chart I-4, US, Total Nonfarm Hiring Level, Annual, ∆%, 2001-2013

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.

Chart I-5, US, Total Private Hiring, Annual, 2001-2013

Source: Bureau of Labor Statistics

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

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

Chart I-5A, US, Rate Total Private Hiring Level, Annual, 2001-2013

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 Oct in the years from 2001 to 2014 in Table I-3. Hiring numbers are in thousands. There is recovery in HNF from 3971 thousand (or 4.0 million) in Oct 2009 to 4285 thousand in Oct 2010, 4442 thousand in Oct 2011, 4562 thousand in Oct 2012, 4741 thousand in Oct 2013 and 5349 thousand in Oct 2014 for cumulative gain of 34.7 percent at average rate of 6.1 percent per year. HP rose from 3666 thousand in Oct 2009 to 3999 thousand in Oct 2010, 4201 thousand in Oct 2011, 4325 thousand in Oct 2012, 4475 thousand in Oct 2013 and 5068 thousand in Oct 2014 for cumulative gain of 38.2 percent at the average yearly rate of 6.7 percent. HNF has fallen from 5640 thousand in Sep 2005 to 5262 thousand in Sep 2014 or by 6.7 percent. HP has fallen from 5531 thousand in Oct 2007 to 5349 thousand in Oct 2014 or by 3.3 percent. The civilian noninstitutional population of the US, or those in condition of working, rose from 232.715 million in Oct 2006 to 248.657 million in Oct 2014, by 15.942 million or 6.9 percent. There is often ignored ugly fact that hiring fell by around 7 percent while population increased around 6.9 percent. The civilian noninstitutional population of the US, or individuals in condition to work, rose from 228.815 million in 2006 to 245.679 million in 2013 or by 16.864 million and the civilian labor force from 151.428 million in 2006 to 155.389 million in 2013 or by 3.961 million (http://www.bls.gov/data/). The number of nonfarm hires in the US fell from 63.327 million in 2006 to 54.191 million in 2013 or by 9.136 million and the number of private hires fell from 59.128 million in 2006 to 50.718 million in 2013 or by 8.410 million (http://www.bls.gov/jlt/). Private hiring of 59.128 million in 2006 was equivalent to 25.8 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 50.718 million in 2013 or 20.6 percent of the civilian noninstitutional population of 245.679 million in 2013. The percentage of hiring in civilian noninstitutional population of 25.8 percent in 2006 would correspond to 63.385 million of hiring in 2013, which would be 12.667 million higher than actual 50.718 million in 2013. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html) explains the fact that there are many million fewer hires in the US than before the global recession. 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 Oct	5399	4.1	5087	4.6
2002 Oct	5152	3.9	4845	4.4
2003 Oct	5229	4.0	4923	4.5
2004 Oct	5443	4.1	5133	4.6
2005 Oct	5378	4.0	5090	4.5
2006 Oct	5490	4.0	5205	4.5
2007 Oct	5531	4.0	5229	4.5
2008 Oct	4723	3.4	4445	3.9
2009 Oct	3971	3.0	3666	3.4
2010 Oct	4285	3.3	3999	3.7
2011 Oct	4442	3.3	4201	3.8
2012 Oct	4562	3.4	4325	3.8
2013 Oct	4741	3.4	4475	3.9
2014 Oct	5349	3.8	5068	4.3

Source: Bureau of Labor Statistics

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

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2014. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4841 in May 2010 until it surpassed it with 4975 in Jun 2011 but declined to 3084 in Dec 2012. Nonfarm hiring fell to 3012 in Dec 2011 from 3810 in Nov and to revised 3614 in Feb 2012, increasing to 4220 in Mar 2012, 3084 in Dec 2012 and 4223 in Jan 2013 and declining to 3861 in Feb 2013. Nonfarm hires not seasonally adjusted increased to 4165 in Nov 2013 and 3271 in Dec 2013. Nonfarm hires reached 5349 in Oct 2014. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Oct 2011 was 4237 thousand, increasing to revised 4446 thousand in Feb 2012, or 4.9 percent, moving to 4343 in Dec 2012 for cumulative increase of 2.0 percent from 4256 in Dec 2011 and 4578 in Dec 2013 for increase of 5.4 percent relative to 4343 in Dec 2012. The number of hires not seasonally adjusted was 4975 in Jun 2011, falling to 3012 in Dec 2011 but increasing to 4112 in Jan 2012 and declining to 3084 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 39.5 percent from 4975 in Jun 2011 to 3012 in Dec 2011 and fell 38.7 percent from 5035 in Jun 2012 to 3084 in Dec 2012 in a yearly-repeated seasonal pattern. The number of nonfarm hires not seasonally adjusted fell from 5095 in Jun 2013 to 3271 in Dec 2013, or decline of 35.8 percent, showing strong seasonality.

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2014 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 3.3 in May 2012 and falling to 3.2 in Jun 2012. The rate stabilized at 3.2 in Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.2 in Dec 2012 and 3.3 in Dec 2013. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.3 in Dec 2011, climbing to 3.7 in Jun 2012 but falling to 2.3 in Dec 2012. The rate of nonfarm hires not seasonally adjusted fell from 3.7 in Jun 2013 to 2.4 in Dec 2013. Rates of nonfarm hiring NSA were in the range of 2.7 (Dec) to 4.4 (Jun) in 2006. The rate of nonfarm hiring SA stood at 3.6 in Oct 2014 and at 3.8 NSA.

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2014

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 4057 thousand in Sep 2011 to 3962 in Dec 2011 or by 2.3 percent, decreasing to 3998 in Jan 2012 or decline by 1.5 percent relative to the level in Sep 2011. Private hiring fell to 3959 in Sep 2012 or lower by 2.4 percent relative to Sep 2011, moving to 4061 in Dec 2012 for increase of 1.6 percent relative to 3998 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4600 in Jun 2011 to 2833 in Dec 2011 or by 38.4 percent, reaching 3853 in Jan 2012 or decline of 16.2 percent relative to Jun 2011 and moving to 2911 in Dec 2012 or 37.1 percent lower relative to 4629 in Jun 2012. Hires fell from 4706 in Jun 2013 to 3098 in Dec 2013. Companies reduce hiring in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5567 in Jun 2006 to 3568 in Dec 2006 or by 35.9 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Aug 2006, private hiring NSA was 5115, declining to 4199 in Aug 2011 or by 17.9 percent and to 4401 in Aug 2012 or lower by 14.0 percent relative to Aug 2006. Private hiring NSA fell from 5501 in Jul 2006 to 5120 in Jul 2014 or 6.9 percent. Private hiring fell from 5229 in Oct 2007 to 4475 in Oct 2013 or 14.4 percent and to 5068 in Oct 2014 or decline of 3.1 percent. The conclusion is that private hiring in the US is around 3 percent below the hiring before the global recession while the noninstitutional population of the United States has grown from 228.815 million in 2006 to 245.679 million in 2013, by 16.864 million or 7.4 percent. The main problem in recovery of the US labor market has been the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-8, US, Total Private Hiring Month SA 2001-2014

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 3.7 in Sep 2011 to 3.6 in Dec 2011 and reached 3.6 in Dec 2012 and 3.7 in Dec 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 2.6 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 3.9 in Aug 2012, 2.6 in Dec 2012 and 2.7 in Dec 2013. The NSA rate increased to 4.3 in Oct 2014.

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2014

Source: Bureau of Labor Statistics

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

ESIII Ten Million Fewer Full-time Jobs. There is strong seasonality in US labor markets around the end of the year.

• Seasonally adjusted part-time for economic reasons. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.068 million in Sep 2011 to 7.780 million in Mar 2012, seasonally adjusted, or decline of 1.288 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.572 million in Sep 2012 for increase of 527,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.231 million in Oct 2012 or by 341,000 again in one month, further declining to 8.164 million in Nov 2012 for another major one-month decline of 67,000 and 7.929 million in Dec 2012 or fewer 235,000 in just one month. The number employed part-time for economic reasons increased to 7.983 million in Jan 2013 or 54,000 more than in Dec 2012 and to 7,991 million in Feb 2013, declining to 7.917 million in May 2013 but increasing to 8.194 million in Jun 2013. The number employed part-time for economic reasons fell to 7.898 million in Aug 2013 for decline of 282,000 in one month from 8.180 million in Jul 2013. The number employed part-time for economic reasons increased 16,000 from 7.898 million in Aug 2013 to 7.914 million in Sep 2013. The number part-time for economic reasons rose to 8.016 million in Oct 2013, falling by 293,000 to 7.723 million in Nov 2013. The number part-time for economic reasons increased to 7.771 million in Dec 2013, decreasing to 7.257 million in Jan 2014. The number employed part-time for economic reasons fell from 7.257 million in Jan 2014 to 7.186 million in Feb 2014. The number employed part-time for economic reasons increased to 7.411 million in Mar 2014 and 7.465 million in Apr 2014. The number employed part-time for economic reasons fell to 7.269 million in May 2014, increasing to 7.544 million in Jun 2014. The level employed part-time for economic reasons fell to 7.511 million in Jul 2014 and 7.277 million in Aug 2014. The level employed part-time for economic reasons fell to 7.103 million in Sep 2014, 7.027 million in Oct 2014 and 6.850 million in Nov 2014. There is an increase of 186,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 119,000 from Aug 2012 to Nov 2012.
• Seasonally adjusted full-time. The number employed full-time increased from 112.906 million in Oct 2011 to 115.114 million in Mar 2012 or 2.208 million but then fell to 114.279 million in May 2012 or 0.835 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.626 million in Aug 2012 to 115.531 million in Oct 2012 or increase of 0.905 million full-time jobs in two months and further to 115.821 million in Jan 2013 or increase of 1.195 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.785 million in Feb 2013, increasing to 116.288 million in May 2013 and 116.087 million in Jun 2013. Then number of full-time jobs increased to 116.156 million in Jul 2013, 116.301 million in Aug 2013 and 116.883 million in Sep 2013. The number of full-time jobs fell to 116.306 million in Oct 2013 and increased to 116.951 in Nov 2013. The level of full-time jobs fell to 117.278 million in Dec 2013, increasing to 117.656 million in Jan 2014 and 117.819 million in Feb 2014. The level of employment full-time increased to 118.003 million in Mar 2014 and 118.415 million in Apr 2014. The level of full-time employment reached 118.727 million in May 2014, decreasing to 118.204 million in Jun 2014. The level of full-time jobs increased to 118.489 in Jul 2014 and 118.616 million in Aug 2014. The level of full-time jobs increased to 119.287 million in Sep 2014, 119.632 million in Oct 2014 and 119.482 million in Nov 2014. Adjustments of benchmark and seasonality-factors at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html).
• Not seasonally adjusted part-time for economic reasons. 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 1.051 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 fewer than in Feb 2013 and fell to 7.709 million in Apr 2013. The number employed part-time for economic reasons reached 7.618 million in May 2013. The number employed part-time for economic reasons jumped from 7.618 million in May 2013 to 8.440 million in Jun 2013 or 822,000 in one month. The number employed part-time for economic reasons fell to 8.324 million in Jul 2013 and 7.690 million in Aug 2013. The number employed part-time for economic reasons NSA fell to 7.522 million in Sep 2013, increasing to 7.700 million in Oct 2013. The number employed part-time for economic reasons fell to 7.563 million in Nov 2013 and increased to 7.990 million in Dec 2013. The number employed part-time for economic reasons fell to 7.771 million in Jan 2014 and 7.397 million in Feb 2014. The level of part-time for economic reasons increased to 7.455 million in Mar 2014 and fell to 7.243 million in Apr 2014. The number of part-time for economic reasons fell to 6.960 million in May 2014, increasing to 7.805 million in Jun 2014. The level of part-time for economic reasons fell to 7.665 million in Jul 2014 and 7.083 million in Aug 2014. The level of part-time for economic reasons fell to 6.711 million in Sep 2014 and increased to 6.787 million in Oct 2014. The level of part-time for economic reasons reached 6.713 million in Nov 2014.
• Not seasonally adjusted full-time. 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. The number employed full time reached 117.400 million in Jun 2013 and increased to 117.688 in Jul 2013 or by 288,000. The number employed full-time reached 117.868 million in Aug 2013 for increase of 180,000 in one month relative to Jul 2013. The number employed full-time fell to 117.308 million in Sep 2013 or by 560,000. The number employed full-time fell to 116.798 million in Oct 2013 or decline of 510.000 in one month. The number employed full-time rose to 116.875 million in Nov 2013, falling to 116.661 million in Dec 2013. The number employed full-time fell to 115.744 million in Jan 2014 but increased to 116.323 million in Feb 2014. The level of full-time jobs increased to 116.985 in Mar 2014 and 118.073 million in Apr 2014. The number of full-time jobs increased to 119.179 million in May 2014, increasing to 119.472 million in Jun 2014. The level of full-time jobs increased to 119.900 million in Jul 2014. 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 Nov 2014 is 119.441 million, which is lower by 3.778 million relative to the peak of 123.219 million in Jul 2007.
• Loss of full-time jobs. 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 248.844 million in Nov 2014 or by 16.886 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 3.778 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 132.157 million full-time jobs with population of 248.884 million in Nov 2014 (0.531 x 248.884) or 12.716 million fewer full-time jobs relative to actual 119.441 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 17 million. Mediocre GDP growth is the main culprit of the fractured US labor market. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 21 quarters from IIIQ2009 to IIIQ2014. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IIIQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp3q14_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2014 would have accumulated to 23.0 percent. GDP in IIIQ2014 would be $18,438.0 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,273.9 billion than actual $16,164.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 26.0 million unemployed or underemployed equivalent to actual unemployment of 15.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/12/financial-risks-twenty-six-million.html and earlier (http://cmpassocregulationblog.blogspot.com/2014/11/rules-discretionary-authorities-and.html). US GDP in IIIQ2014 is 12.3 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,164.1 billion in IIIQ2014 or 7.8 percent at the average annual equivalent rate of 1.1 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. The long-term trend is growth at average 3.3 percent per year from Jan 1919 to Oct 2014. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 123.8884 in Oct 2014. The actual index NSA in Oct 2014 is 101.5613, which is 18.0 percent below trend. Manufacturing output grew at average 2.3 percent between Dec 1986 and Dec 2013, raising the index at trend to 115.9214 in Oct 2014. The output of manufacturing at 101.5613 in Oct 2014 is 12.4 percent below trend under this alternative calculation

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

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Nov 2014	6,850	119.482
Oct 2014	7,027	119.632
Sep 2014	7,103	119.287
Aug 2014	7,277	118.616
Jul 2014	7,511	118.489
Jun 2014	7,544	118.204
May 2014	7,269	118.727
Apr 2014	7,465	118.415
Mar 2014	7,411	118.003
Feb 2014	7,186	117.819
Jan 2014	7,257	117.656
Dec 2013	7,771	117.278
Nov 2013	7,723	116.951
Oct 2013	8,016	116.306
Sep 2013	7,914	116.883
Aug 2013	7,898	116.301
Jul 2013	8,180	116.156
Jun 2013	8,194	116.087
May 2013	7,917	116.288
Apr 2013	7,929	116.062
Mar 2013	7,663	115.901
Feb 2013	7,991	115.785
Jan 2013	7,983	115.821
Dec 2012	7,929	115.735
Nov 2012	8,164	115.581
Oct 2012	8,231	115.531
Sep 2012	8,572	115.229
Aug 2012	8,045	114.626
Jul 2012	8,163	114.589
Jun 2012	8,154	114.728
May 2012	8,138	114.279
Apr 2012	7,913	114.398
Mar 2012	7,780	115.114
Feb 2012	8,133	114.210
Jan 2012	8,228	113.790
Dec 2011	8,177	113.740
Nov 2011	8,457	113.158
Oct 2011	8,675	112.906
Sep 2011	9,068	112.523
Aug 2011	8,820	112.643
Jul 2011	8,342	112.209
Not Seasonally Adjusted
Nov 2014	6,713	119.441
Oct 2014	6,787	120.176
Sep 2014	6,711	119.791
Aug 2014	7,083	120.110
Jul 2014	7,665	119.900
Jun 2014	7,805	119.472
May 2014	6,960	119.179
Apr 2014	7,243	118.073
Mar 2014	7,455	116.985
Feb 2014	7,397	116.323
Jan 2014	7,771	115.744
Dec 2013	7,990	116.661
Nov 2013	7,563	116.875
Oct 2013	7,700	116.798
Sep 2013	7,522	117.308
Aug 2013	7,690	117.868
Jul 2013	8,324	117.688
Jun 2013	8,440	117.400
May 2013	7,618	116.643
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	8,166	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/

People lose their marketable job skills after prolonged unemployment and face 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.

Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2014

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.

Chart I-19, US, Marginally Attached to the Labor Force, NSA Month, Thousands, 2001-2014

Sources: US Bureau of Labor Statistics

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

The number with full-time jobs in Nov 2014 is 119.441 million, which is lower by 3.778 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 248.844 million in Nov 2014 or by 16.886 million (http://www.bls.gov/data/) while in the same period the number of full-time jobs fell 3.778 million. The ratio of full-time jobs of 123.219 million Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 132.157 million full-time jobs with population of 248.884 million in Nov 2014 (0.531 x 248.884) or 12.716 million fewer full-time jobs relative to actual 119.441 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 17 million. Mediocre GDP growth is the main culprit of the fractured US labor market.

Chart I-20 provides unadjusted full-time jobs in the US from 2001 to 2014 with sharp drop and incomplete recovery. There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

“Not until the problem of full employment of our productive resources from the long-run, secular standpoint was upon us, were we compelled to give serious consideration to those factors and forces in our economy which tend to make business recoveries weak and anaemic (sic) and which tend to prolong and deepen the course of depressions. This is the essence of secular stagnation-sick recoveries which die in their infancy and depressions which feed on them-selves and leave a hard and seemingly immovable core of unemployment. Now the rate of population growth must necessarily play an important role in determining the character of the output; in other words, the com-position of the flow of final goods. Thus a rapidly growing population will demand a much larger per capita volume of new residential building construction than will a stationary population. A stationary population with its larger proportion of old people may perhaps demand more personal services; and the composition of consumer demand will have an important influence on the quantity of capital required. The demand for housing calls for large capital outlays, while the demand for personal services can be met without making large investment expenditures. It is therefore not unlikely that a shift from a rapidly growing population to a stationary or declining one may so alter the composition of the final flow of consumption goods that the ratio of capital to output as a whole will tend to decline.”

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). This is merely another case of theory without reality with dubious policy proposals.

Inferior performance of the US economy and labor markets, during cyclical slow growth not secular stagnation, is the critical current issue of analysis and policy design.

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2014

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 2014. 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.

Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2014

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 2014. There were multiple recessions followed by expansions without contraction of full-time jobs and without recovery as during the period after 2008. The problem is specific of the current cycle and not secular.

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2014

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.

Chart I-20C, US, Noninstitutional Civilian Population, Thousands, 1968-2014

Sources: US Bureau of Labor Statistics

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

ESIV Theory and Reality of Secular Stagnation: Youth and Middle-Age Unemployment. There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

“Not until the problem of full employment of our productive resources from the long-run, secular standpoint was upon us, were we compelled to give serious consideration to those factors and forces in our economy which tend to make business recoveries weak and anaemic (sic) and which tend to prolong and deepen the course of depressions. This is the essence of secular stagnation-sick recoveries which die in their infancy and depressions which feed on them-selves and leave a hard and seemingly immovable core of unemployment. Now the rate of population growth must necessarily play an important role in determining the character of the output; in other words, the com-position of the flow of final goods. Thus a rapidly growing population will demand a much larger per capita volume of new residential building construction than will a stationary population. A stationary population with its larger proportion of old people may perhaps demand more personal services; and the composition of consumer demand will have an important influence on the quantity of capital required. The demand for housing calls for large capital outlays, while the demand for personal services can be met without making large investment expenditures. It is therefore not unlikely that a shift from a rapidly growing population to a stationary or declining one may so alter the composition of the final flow of consumption goods that the ratio of capital to output as a whole will tend to decline.”

The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). Youth workers would obtain employment at a premium in an economy with declining population. In fact, there is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages. This is merely another case of theory without reality with dubious policy proposals. Inferior performance of the US economy and labor markets is the critical current issue of analysis and policy design.

In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share s_i of a demographic group in an industry i and unemployment rate y_i of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):

Y = ∑_is_iy_i (1)

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

∆Y = ∑_i∆s_iy*_i + ∑_i∆y_is*_i (2)

The first term in (2) captures changes in the demographic and industrial composition of the economy ∆s_i multiplied by the average rate of unemployment y*_i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆y_i, multiplied by the average share of the group s*_i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:

“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. There are accentuated cyclic factors for both the entire population and the young population of ages 16 to 24 years. Table Summary Total provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment level (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would spread over long periods instead of immediately. All indicators of the labor market weakened sharply during the contraction and did not recover. Population continued to grow but all other variables collapsed and did not recover. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-16). Hansen (1938, 1939) finds secular stagnation in lower growth of an aging population. In the current US economy, Table Summary shows that population is dynamic while the labor market is fractured. There is key explanation in the behavior of the civilian labor force participation rate (CLFP) and the employment population ratio (EPOP) that collapsed during the global recession with inadequate recovery. Abandoning job searches are difficult to capture in labor statistics but likely explain the decline in the participation of the population in the labor force. Allowing for abandoning job searches, the total number of people unemployed or underemployed is 26.0 million or 15.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/12/financial-risks-twenty-six-million.html).

Table Summary Total, US, Total Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Millions and Percent

	ICP	FTE	EMP	CLF	CLFP	EPOP	UNE
2006	228.8	119.7	144.4	151.4	66.2	63.1	7.0
2009	235.8	112.6	139.9	154.1	65.4	59.3	14.3
2012	243.3	114.8	142.5	155.0	63.7	58.6	12.5
2013	245.7	116.3	143.9	155.4	63.2	58.6	11.5
12/07	233.2	121.0	146.3	153.7	65.9	62.8	7.4
9/09	236.3	111.6	139.1	153.6	65.0	58.9	14.5
10/14	248.9	119.4	147.7	156.3	62.8	59.3	8.6

ICP: Total Noninstitutional Civilian Population; FT: Full-time Employment Level, EMP: Total Employment Level; CLF: Civilian Labor Force; CLFP: Civilian Labor Force Participation Rate; EPOP: Employment Population Ratio; UNE: Unemployment

Source: Bureau of Labor Statistics

http://www.bls.gov/

The same situation is present in the labor market for young people in ages 16 to 24 years with data in Table Summary Youth. The youth noninstitutional civilian population (ICP) continued to increase during and after the global recession. There is the same disastrous labor market with decline for young people in employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP) and employment population ratio (EPOP). There are only increases for unemployment of young people (UNE) and youth unemployment rate (UNER). If aging were a factor of secular stagnation, growth of population of young people would attract a premium in remuneration in labor markets. The sad fact is that young people are also facing tough labor markets. The application of the theory of secular stagnation to the US economy and labor markets is void of reality in the form of key facts, which are best explained by accentuated cyclic factors analyzed by Lazear and Spletzer (2012JHJul22).

Table Summary Youth, US, Youth, Ages 16 to 24 Years, Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Millions and Percent

	ICP	EMP	CLF	CLFP	EPOP	UNE	UNER
2006	36.9	20.0	22.4	60.6	54.2	2.4	10.5
2009	37.6	17.6	21.4	56.9	46.9	3.8	17.6
2012	38.8	17.8	21.3	54.9	46.0	3.5	16.2
2013	38.9	18.1	21.4	55.0	46.5	3.3	15.5
12/07	37.5	19.4	21.7	57.8	51.6	2.3	10.7
9/09	37.6	17.0	20.7	55.2	45.1	3.8	18.2
10/14	38.6	18.6	21.0	54.5	48.1	2.5	11.7

ICP: Youth Noninstitutional Civilian Population; EMP: Youth Employment Level; CLF: Youth Civilian Labor Force; CLFP: Youth Civilian Labor Force Participation Rate; EPOP: Youth Employment Population Ratio; UNE: Unemployment; UNER: Youth Unemployment Rate

Source: Bureau of Labor Statistics

http://www.bls.gov/

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. Youth employment fell from 20.041 million in 2006 to 18.057 million in 2013 or 1.984 million fewer jobs. The level of youth jobs fell from 19.903 million in Nov 2006 to 18.576 million in Nov 2014 for 1.327 million fewer youth 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 21.167 million in Aug 2006 to 18.972 million in Aug 2014 for 2.195 million fewer jobs. Youth employment fell from 21.914 million in Jul 2006 to 20.085 million in Jul 2014 for 1.829 million fewer youth jobs. The number of youth jobs fell from 21.268 million in Jun 2006 million to 19.421 million in Jun 2014 or 1.847 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 21.167 million in Aug 2006 to 18.636 million in Aug 2013 or by 2.531 million. The number of youth jobs fell from 19.604 million in Sep 2006 to 18.043 million in Sep 2013 or 1.561 million fewer youth jobs. The number of youth jobs fell from 20.129 million in Dec 2006 to 18.106 million in Dec 2013 or 2.023 million fewer jobs. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The youth civilian noninstitutional population increased 1.464 million from 37.302 in Feb 2007 to 38.766 million in Feb 2014 while the number of youth jobs decreased 2.058 million. The civilian noninstitutional population increased 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 while jobs for ages 16 to 24 years decreased 1.599 million from 19.538 million in Mar 2007 to 17.939 million in Mar 2014. The civilian noninstitutional population ages 16 to 24 years increased 1.410 million from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 while the number of youth jobs fell 1.347 million. The civilian noninstitutional population increased 1.370 million from 37.379 million in May 2007 to 38.749 million in May 2014 while the number of youth jobs decreased 1.128 million. The civilian noninstitutional population increased 1.330 million from 37.410 million in Jun 2007 to 38.740 million in Jun 2014 while the number of youth jobs fell 1.847 million from 21.268 million in Jun 2006 to 19.421 million in Jun 2014. The youth civilian noninstitutional population increased by 1.292 million from 37.443 million in Jul 2007 to 38.735 million in Jul 2014 while the number of youth jobs fell 1.632 million. The youth civilian noninstitutional population increased from 37.445 million in Aug 2007 to 38.706 million in Aug 2014 or 1.251 million while the number of youth jobs fell 1.441 million. The youth civilian noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014 while the number of youth jobs fell 1.500 million. The youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million while the number of youth jobs fell 1.072 million. The youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million while the number of youth jobs fell 1.327 million. The hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. 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	May	Jun	Jul	Aug	Sep	Oct	Nov
2001	19648	21212	22042	20529	19706	19694	19675
2002	19484	20828	21501	20653	19466	19542	19397
2003	19032	20432	20950	20181	18909	19139	19163
2004	19237	20587	21447	20660	19158	19609	19615
2005	19356	20949	21749	20814	19503	19794	19750
2006	19769	21268	21914	21167	19604	19853	19903
2007	19457	21098	21717	20413	19498	19564	19660
2008	19254	20466	21021	20096	18818	18757	18454
2009	17588	18726	19304	18270	16972	16671	16689
2010	17039	17920	18564	18061	16874	16867	16946
2011	17045	18180	18632	18067	17238	17532	17402
2012	17681	18907	19461	18171	17687	17842	17877
2013	17704	19125	19684	18636	18043	17976	18104
2014	18329	19421	20085	18972	18104	18781	18576

Source: 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 2014. Employment level is sharply lower in Sep 2014 relative to the peak in 2007. The following Chart I-21A relates youth employment and youth civilian noninstitutional population.

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2014

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

Chart I-21A provides the US civilian noninstitutional population ages 16 to 24 years not seasonally adjusted from 2001 to 2014. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The youth civilian noninstitutional population increased 1.464 million from 37.302 in Feb 2007 to 38.766 million in Feb 2014 while the number of youth jobs decreased 2.058 million. The civilian noninstitutional population increased 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 while jobs for ages 16 to 24 years decreased 1.599 million from 19.538 million in Mar 2007 to 17.939 million in Mar 2014. The civilian noninstitutional population ages 16 to 24 years increased 1.410 million from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 while the number of youth jobs fell 1.347 million. The civilian noninstitutional population increased 1.370 million from 37.379 million in May 2007 to 38.749 million in May 2014 while the number of youth jobs decreased 1.128 million. The civilian noninstitutional population increased 1.330 million from 37.410 million in Jun 2007 to 38.740 million in Jun 2014 while the number of youth jobs fell 1.847 million from 21.268 million in Jun 2006 to 19.421 million in Jun 2014. The youth civilian noninstitutional population increased by 1.292 million from 37.443 million in Jul 2007 to 38.735 million in Jul 2014 while the number of youth jobs fell 1.632 million. The youth civilian noninstitutional population increased from 37.445 million in Aug 2007 to 38.706 million in Aug 2014 or 1.251 million while the number of youth jobs fell 1.441 million. The youth civilian noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014 while the number of youth jobs fell 1.500 million. The youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million while the number of youth jobs fell 1.072 million. The youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million while the number of youth jobs fell 1.327 million. The hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. 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.

Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2014

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

Chart I-21B provides the civilian labor force of the US ages 16 to 24 years NSA from 2001 to 2014. The US civilian labor force ages 16 to 24 years fell from 24.339 million in Jul 2007 to 23.506 million in Jul 2013, by 0.833 million or decline of 3.4 percent, while the civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013, by 1.418 million or 3.8 percent. The US civilian labor force ages 16 to 24 fell from 22.801 million in Aug 2007 to 22.089 million in Aug 2013, by 0.712 million or 3.1 percent, while the noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013, by 1.386 million or 3.7 percent. The US civilian labor force ages 16 to 24 years fell from 21.917 million in Sep 2007 to 21.183 million in Sep 2013, by 0.734 million or 3.3 percent while the civilian noninstitutional youth population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 by 1.355 million or 3.6 percent. The US civilian labor force fell from 21.821 million in Oct 2007 to 21.003 million in Oct 2013, by 0.818 million or 3.7 percent while the noninstitutional youth population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013, by 1.324 million or 3.5 percent. The US youth civilian labor force fell from 21.909 million in Nov 2007 to 20.825 million in Nov 2013, by 1.084 million or 4.9 percent while the civilian noninstitutional youth population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million. The US youth civilian labor force fell from 21.684 million in Dec 2007 to 20.642 million in Dec 2013, by 1.042 million or 4.8 percent, while the civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013, by 1.272 million or 3.4 percent. The youth civilian labor force of the US fell from 21.770 million in Jan 2007 to 20.423 million in Jan 2014, by 1.347 million or 6.2 percent while the youth civilian noninstitutional population increased 37.282 million in Jan 2007 to 38.770 million in Jan 2014, by 1.488 million or 4.0 percent. The youth civilian labor force of the US fell 1.255 million from 21.645 million in Feb 2007 to 20.390 million in Feb 2014 while the youth civilian noninstitutional population increased 1.464 million from 37.302 million in Feb 2007 to 38.766 million in Feb 2014. The youth civilian labor force of the US fell 0.693 million from 21.634 million in Mar 2007 to 20.941 million in Mar 2014 or 3.2 person while the youth noninstitutional civilian population 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 or 3.9 percent. The US youth civilian labor force fell 981 thousand from 21.442 million in Apr 2007 to 20.461 million in Apr 2014 while the youth civilian noninstitutional population increased from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 by 1.410 thousand or 3.8 percent. The youth civilian labor force decreased from 21.659 million in May 2007 to 21.160 million in May 2014 by 499 thousand or 2.3 percent while the youth civilian noninstitutional population increased 1.370 million from 37.739 million in May 2007 to 38.749 million in May 2007 or by 2.7 percent. The youth civilian labor force decreased from 24.128 million in Jun 2006 to 22.851 million in Jun 2014 by 1.277 million or 5.3 percent while the civilian noninstitutional population increased from 36.943 million in Jun 2006 to 38.740 million in Jun 2014 by 1.797 million or 4.9 percent. The youth civilian labor force fell from 24.664 million in Jul 2006 to 23.437 million in Jul 2014 while the civilian noninstitutional population increased from 36.989 million in Jul 2006 to 38.735 million in Jul 2014. The youth civilian labor force fell 1.818 million from 23.634 million in Aug 2006 to 21.816 million in Aug 2014 while the civilian noninstitutional population increased from 37.008 million in Aug 2006 to 38.706 million in Aug 2914 or 1.698 million. The youth civilian labor force fell 0.942 million from 21.901 million in Sep 2006 to 20.959 million in Sep 2014 while the noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014. The youth civilian labor force decreased 0.702 million from 22.105 million in Oct 2006 to 21.403 million in Oct 2014 while the youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million. The youth civilian labor force decreased 1.111 million from 22.145 million in Nov 2006 to 21.034 million in Nov 2014 while the youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.

Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2014

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

Chart I-21C provides the ratio of labor force to noninstitutional population or labor force participation of ages 16 to 24 years not seasonally adjusted. The US labor force participation rates for ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2013 because of the frustration of young people who believe there may not be jobs available for them. The US labor force participation rate of young people fell from 63.9 in Aug 2006 to 56.9 in Aug 2013. The US labor force participation rate of young people fell from 59.1 percent in Sep 2006 to 54.6 percent in Sep 2013. The US labor force participation rate of young people fell from 59.7 percent in Oct 2006 to 54.1 in Oct 2013. The US labor force participation rate of young people fell from 59.7 percent in Nov 2006 to 53.7 percent in Nov 2013. The US labor force participation rate fell from 57.8 in Dec 2007 to 53.2 in Dec 2013. The youth labor force participation rate fell from 58.4 in Jan 2007 to 52.7 in Jan 2014. The US youth labor force participation rate fell from 58.0 percent in Feb 2007 to 52.6 percent in Feb 2013. The labor force participation rate of ages 16 to 24 years fell from 58.0 in Mar 2007 to 54.0 in Mar 2014. The labor force participation rate of ages 16 to 24 years fell from 57.4 in Apr 2007 to 52.8 in Apr 2014. The labor force participation rate of ages 16 to 24 years fell from 57.9 in May 2007 to 54.6 in May 2014. The labor force participation rate of ages 16 to 24 years fell from 65.3 in Jun 2006 to 59.0 in Jun 2014. The labor force participation rate ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2014. The labor force participation rate ages 16 to 24 years fell from 63.9 in Aug 2006 to 56.4 in Aug 2014. The labor force participation rate ages 16 to 24 years fell from 59.1 in Sep 2006 to 54.2 in Sep 2014. The labor force participation rate ages 16 to 24 years fell from 59.7 in Oct 2006 to 55.4 in Oct 2014. The labor force participation rate ages 16 to 24 years fell from 59.7 in Nov 2006 to 54.5 in Nov 2014. Many young people abandoned searches for employment, dropping from the labor force.

Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2014

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

An important measure of the job market is the number of people with jobs relative to population available for work (civilian noninstitutional population) or employment/population ratio. Chart I-21D provides the employment population ratio for ages 16 to 24 years. The US employment/population ratio NSA for ages 16 to 24 years collapsed from 59.2 in Jul 2006 to 50.7 in Jul 2013. The employment population ratio for ages 16 to 24 years dropped from 57.2 in Aug 2006 to 48.0 in Aug 2013. The employment population ratio for ages to 16 to 24 years declined from 52.9 in Sep 2006 to 46.5 in Sep 2013. The employment population ratio for ages 16 to 24 years fell from 53.6 in Oct 2006 to 46.3 in Oct 2013. The employment population ratio for ages 16 to 24 years fell from 53.7 in Nov 2007 to 46.7 in Nov 2013. The US employment population ratio for ages 16 to 24 years fell from 51.6 in Dec 2007 to 46.7 in Dec 2013. The US employment population ratio fell from 52.1 in Jan 2007 to 44.8 in Jan 2014. The US employment population ratio for ages 16 to 24 fell from 52.0 in Feb 2007 to 44.8 in Feb 2014. The US employment population ratio for ages 16 to 24 years fell from 52.3 in Mar 2007 to 46.3 in Mar 2014. The US employment population ratio for ages 16 to 24 years fell from 51.9 in Apr 2007 to 46.5 in Apr 2014. The US employment population ratio for ages 16 to 24 years fell from 52.1 in May 2007 to 47.3 in May 2014. The US employment population ratio for ages 16 to 24 years fell from 57.6 in Jun 2006 to 50.1 in Jun 2014. The US employment population ratio for ages 16 to 24 years fell from 59.2 in Jul 2006 to 50.1 in Jul 2014. The employment population ratio for ages 16 to 24 years fell from 57.2 in Aug 2006 to 49.0 in Aug 2014. The employment population ratio for ages 16 to 24 fell from 52.9 in Sep 2006 to 46.8 in Sep 2014. The employment population ratio for ages 16 to 24 fell from 53.6 in Oct 2006 to 48.6 in Oct 2014. The employment population ratio for ages 16 to 24 fell from 53.7 in Nov 2006 to 48.1 in Nov 2014. Chart I-21D shows vertical drop during the global recession without recovery.

Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2014

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 23 years increased from 2342 in 2007 to 3324 thousand in 2013 or by 0.982 million. The unemployment level ages 16 to 24 years rose from 2.250 million in Nov 2007 to 2.458 million in Nov 2014 or by 0.208 million. This situation may persist for many years.

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

Year	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Annual
2001	2775	2585	2461	2301	2424	2470	2412	2371
2002	3167	3034	2688	2506	2468	2570	2374	2683
2003	3542	3200	2724	2698	2522	2522	2248	2746
2004	3191	3018	2585	2493	2572	2448	2294	2638
2005	3010	2688	2519	2339	2285	2369	2055	2521
2006	2860	2750	2467	2297	2252	2242	2007	2353
2007	2883	2622	2388	2419	2258	2250	2323	2342
2008	3450	3408	2990	2904	2842	2833	2928	2830
2009	4653	4387	4004	3774	3789	3699	3532	3760
2010	4481	4374	3903	3604	3731	3561	3352	3857
2011	4248	4110	3820	3541	3386	3287	3161	3634
2012	4180	4011	3672	3174	3285	3102	3153	3451
2013	4198	3821	3453	3139	3028	2721	2536	3324
2014	3429	3353	2844	2854	2622	2458

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

Chart I-22 provides the unemployment level for ages 16 to 24 from 2001 to 2014. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013-2014 with recent marginal improvement alternating with deterioration.

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2014

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. The rate of youth unemployment fell marginally to 15.5 percent in 2013. During the seasonal peak in Jul, the rate of youth unemployed was 18.1 percent in Jul 2011, 17.1 percent in Jul 2012 and 16.3 percent in Jul 2013 compared with 10.8 percent in Jul 2007. The rate of youth unemployment rose from 11.2 percent in Jul 2006 to 16.3 percent in Jul 2013 and likely higher if adding those who ceased searching for a job in frustration none may be available. The rate of youth unemployment rose from 10.8 in Jul 2007 to 14.3 in Jul 2014. The rate of youth unemployment increased from 9.1 percent in Dec 2006 to 12.3 percent in Dec 2013. The rate of youth unemployment increased from 10.9 percent in Jan 2007 to 14.9 percent in Jan and Feb 2014. The rate of youth unemployment increased from 9.7 percent in Mar 2007 to 14.3 percent in Mar 2014. The rate of youth unemployment increased from 9.7 percent in Apr 2007 to 11.9 percent in Apr 2014. The rate of youth unemployment increased from 10.2 percent in May 2007 to 13.4 percent in May 2014. The rate of youth unemployment increased from 12.0 percent in Jun 2007 to 15.0 percent in Jun 2014. The rate of youth unemployment increased from 10.8 in Jul 2007 to 14.3 in Jul 2014. The rate of youth unemployment increased from 10.5 in Aug 2007 to 13.0 in Aug 2014. The rate of youth unemployment increased from 11.0 in Sep 2007 to 13.6 in Sep 2014. The rate of youth unemployment increased from 10.3 in Oct 2007 to 12.2 in Oct 2014. The rate of youth unemployment increased from 10.3 in Nov 2007 to 11.7 in Nov 2014. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them.

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

Year	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Annual
2001	9.6	10.0	11.6	10.5	10.7	10.5	11.0	11.2	11.0	10.6
2002	11.6	11.6	13.2	12.4	11.5	11.4	11.2	11.7	10.9	12.0
2003	12.0	13.0	14.8	13.3	11.9	12.5	11.6	11.6	10.5	12.4
2004	11.1	12.2	13.4	12.3	11.1	11.5	11.6	11.1	10.5	11.8
2005	11.2	11.9	12.6	11.0	10.8	10.7	10.3	10.7	9.4	11.3
2006	9.7	10.2	11.9	11.2	10.4	10.5	10.2	10.1	9.1	10.5
2007	9.7	10.2	12.0	10.8	10.5	11.0	10.3	10.3	10.7	10.5
2008	10.3	13.3	14.4	14.0	13.0	13.4	13.2	13.3	13.7	12.8
2009	15.8	18.0	19.9	18.5	18.0	18.2	18.5	18.1	17.5	17.6
2010	18.5	18.4	20.0	19.1	17.8	17.6	18.1	17.4	16.7	18.4
2011	16.5	17.5	18.9	18.1	17.5	17.0	16.2	15.9	15.5	17.3
2012	15.4	16.3	18.1	17.1	16.8	15.2	15.5	14.8	15.2	16.2
2013	15.1	16.4	18.0	16.3	15.6	14.8	14.4	13.1	12.3	15.5
2014	11.9	13.4	15.0	14.3	13.0	13.6	12.2	11.7

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 2001 to 2014. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels because of low growth of GDP. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E. Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2014

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 2014. 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. In contrast, 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, 15.1 percent in Apr 2013. The rate of youth unemployment was 16.4 percent in May 2013, 18.0 percent in Jun 2013, 16.3 percent in Jul 2013 and 15.6 percent in Aug 2013. In Sep 2006, the rate of youth unemployment was 10.5 percent, increasing to 14.8 percent in Sep 2013. The rate of youth unemployment was 10.3 in Oct 2007, increasing to 14.4 percent in Oct 2013. The rate of youth unemployment was 10.3 percent in Nov 2007, increasing to 13.1 percent in Nov 2013. The rate of youth unemployment was 10.7 percent in Dec 2013, increasing to 12.3 percent in Dec 2013. The rate of youth unemployment was 10.9 percent in Jan 2007, increasing to 14.9 percent in Jan 2014. The rate of youth unemployment was 10.3 percent in Feb 2007, increasing to 14.9 percent in Feb 2014. The rate of youth unemployment was 9.7 percent in Mar 2007, increasing to 14.3 percent in Mar 2014. The rate of youth unemployment was 9.7 percent in Apr 2007, increasing to 11.9 percent in Apr 2014. The rate of youth unemployment was 10.2 percent in May 2007, increasing to 13.4 percent in May 2014. The rate of youth unemployment was 12.0 percent in Jun 2007, increasing to 15.0 percent in Jun 2014. The rate of youth unemployment was 10.8 percent in Jul 2007, increasing to 14.3 percent in Jul 2014. The rate of youth unemployment was 10.5 percent in Aug 2007, increasing to 13.0 percent in Aug 2014. The rate of youth unemployment was 11.0 percent in Sep 2007, increasing to 13.6 percent in Sep 2014. The rate of youth unemployment increased from 10.3 in Oct 2007 to 12.2 in Oct 2014. The rate of youth unemployment increased from 10.3 percent in Nov 2007 to 11.7 percent in Nov 2014. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.9 percent during the recovery from IQ1983 to IVQ1985 and 4.9 percent from IQ1983 to IQ1988 compared with 2.3 percent on average during the first 21 quarters of expansion from IIIQ2009 to IIIQ2014 (http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html). US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 21 quarters from IIIQ2009 to IIIQ2014. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the second estimate of GDP for IIIQ2014 (http://www.bea.gov/newsreleases/national/gdp/2014/pdf/gdp3q14_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIIQ2014 would have accumulated to 23.0 percent. GDP in IIIQ2014 would be $18,438.0 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2,273.9 billion than actual $16,164.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 26.0 million unemployed or underemployed equivalent to actual unemployment of 15.8 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2014/12/financial-risks-twenty-six-million.html

and earlier (http://cmpassocregulationblog.blogspot.com/2014/11/rules-discretionary-authorities-and.html). US GDP in IIIQ2014 is 12.3 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,164.1 billion in IIIQ2014 or 7.8 percent at the average annual equivalent rate of 1.1 percent. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. The long-term trend is growth at average 3.3 percent per year from Jan 1919 to Oct 2014. Growth at 3.3 percent per year would raise the NSA index of manufacturing output from 99.2392 in Dec 2007 to 123.8884 in Oct 2014. The actual index NSA in Oct 2014 is 101.5613, which is 18.0 percent below trend. Manufacturing output grew at average 2.3 percent between Dec 1986 and Dec 2013, raising the index at trend to 115.9214 in Oct 2014. The output of manufacturing at 101.5613 in Oct 2014 is 12.4 percent below trend under this alternative calculation.

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2014

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 mature 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 1.607 million in Oct 2006 to 4.576 million in Oct 2010 or by 184.8 percent. The number of unemployed ages 45 years and over declined to 3.800 million in Oct 2012 that is still higher by 136.5 percent than in Oct 2006. The number unemployed age 45 and over increased from 1.704 million in Nov 2006 to 3.861 million in Nov 2012, or 126.6 percent. The number unemployed age 45 and over is still higher by 98.5 percent at 3.383 million in Nov 2013 than 1.704 million in Nov 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. At 3.927 million in Dec 2012, mature unemployment 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 3.632 million in Oct 2013 is higher by 2.025 million than 1.607 million in Oct 2006 or higher by 126.0 percent. The number of unemployed 45 years and over increased from 1.794 million in Dec 2006 to 3.378 million in Nov 2013 or 88.3 percent. The annual number of unemployed 45 years and over increased from 1.848 million in 2006 to 3.719 million in 2013 or 101.2 percent. The number of unemployed 45 years and over increased from 2.126 million in Jan 2006 to 4.394 million in Jan 2013, by 2.618 million or 106.7 percent. The number of unemployed 45 years and over rose from 2.126 million in Jan 2006 to 3.508 million in Jan 2014, by 1.382 million or 65.0 percent. The level of unemployed 45 years or older increased 2.051 million or 99.8 percent from 2.056 million in Feb 2006 to 4.107 million in Feb 2013 and at 3.490 million in Feb 2014 is higher by 69.7 percent than in Feb 2006. The number of unemployed 45 years and over increased 2.048 million or 108.9 percent from 1.881 million in Mar 2006 to 3.929 million in Mar 2013 and at 3.394 million in Mar 2014 is higher by 80.4 percent than in Mar 2006. The number of unemployed 45 years and over increased 1.846 million or 100.2 percent from 1.843 million in Apr 2006 to 3.689 million in Apr 2013 and at 3.006 million in Apr 2014 is higher by 1.163 million or 63.1 percent. The number of unemployed ages 45 years and over increased 102.1 percent from 1.784 million in May 2006 to 3.605 million in May 2014 and at 2.913 million in May 2014 is higher by 63.3 percent than in May 2007.

The number of unemployed ages 45 years and over increased 102.1 percent from 1.805 million in Jun 2007 to 3.648 million in Jun 2013 and at 2.832 million in Jun 2014 is higher by 56.9 percent than in Jun 2007. The number of unemployed ages 45 years and over increased 81.5 percent from 2.053 million in Jul 2007 to 3.727 million in Jul 2013 and at 3.083 million in Jul 2014 is higher by 50.2 percent than in Jul 2007. The level unemployed ages 45 years and over increased 84.4 percent from 1.956 million in Aug 2007 to 3.607 million in Aug 2013 and at 3.037 million in Aug 2014 is 55.2 percent higher than in Aug 2007. The level unemployed ages 45 years and over increased 90.7 percent from 1.854 million in Sep 2007 to 3.535 million in Sep 2013 and at 2.640 million in Sep 2014 is 42.4 percent higher than in Sep 2007. The level unemployed ages 45 years and over increased 1.747 million from 1.885 million in Oct 2007 to 3.632 million in Oct 2013 and at 2.606 million in Oct 2014 is 38.2 percent higher than in Oct 2007. The level unemployed ages 45 years and over increased 1.458 million from 1.925 million in Nov 2007 to 3.383 million in Nov 2013 and at 2.829 million in Nov 2014 is 47.0 percent higher than in Nov 2007. The actual number unemployed is likely much higher because many are not accounted who abandoned job searches in frustration there may not be a job for them. Recent improvements may be illusory.

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

Year	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Annual
2000	1062	1074	1163	1253	1339	1254	1202	1242	1217	1249
2001	1421	1259	1371	1539	1640	1586	1722	1786	1901	1576
2002	2101	1999	2190	2173	2114	1966	1945	2013	2210	2114
2003	2287	2112	2212	2281	2301	2157	2032	2132	2130	2253
2004	2160	2025	2182	2116	2082	1951	1931	2053	2086	2149
2005	1939	1844	1868	2119	1895	1992	1875	1920	1963	2009
2006	1843	1784	1813	1985	1869	1710	1607	1704	1794	1848
2007	1871	1803	1805	2053	1956	1854	1885	1925	2120	1966
2008	2104	2095	2211	2492	2695	2595	2728	3078	3485	2540
2009	4172	4175	4505	4757	4683	4560	4492	4655	4960	4500
2010	4770	4565	4564	4821	5128	4640	4576	4909	4762	4879
2011	4373	4356	4559	4772	4592	4426	4375	4195	4182	4537
2012	4037	4083	4084	4405	4179	3899	3800	3861	3927	4133
2013	3689	3605	3648	3727	3607	3535	3632	3383	3378	3719
2014	3006	2913	2832	3083	3037	2640	2606	2829

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 an increase in the recessions of the 1980s, 1991 and 2001 followed by declines to earlier levels. The current expansion of the economy after IIIQ2009 has not been sufficiently vigorous to reduce significantly middle-age unemployment. Recent improvements could be illusory because many abandoned job searches in frustration that there may not be jobs for them and are not counted as unemployed.

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2014

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

ESV 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/2014/11/squeeze-of-economic-activity-by-carry.html). The Census Bureau revised data for 2014, 2013 and 2012. Exports decreased 0.2 percent from Aug to Oct 2014 while imports increased 0.9 percent. The trade deficit increased from $40.031 million in Aug 2014 to $43.432 million in Oct 2014. The US trade balance improved from deficits of $39,083 million in Oct 2013 and $42,263 million in Sep 2013 to deficit of $35,972 million in Nov 2013 but higher deficit of $37,393 million in Dec 2013. The trade deficit increased to $39,181 million in Jan 2014 and deficit of $42,230 million in Feb 2014. The trade deficit increased to $43,124 million in Mar 2014 and $45,914 million in Apr 2014. The deficit improved to $43,562 million in May 2014 and $40,695 million in Jul 2014. The trade deficit improved to $40.031 million in Aug 2014, deteriorating to $43.603 million in Sep 2014 and $43.432 million in Oct 2014. Exports increased 2.5 percent from Dec 2013 to Oct 2014 while imports increased 4.7 percent. The trade balance deteriorated from cumulative deficit of $494,658 million in Jan-Dec 2010 to deficit of $548,625 million in Jan-Dec 2011 and improved to marginally lower deficit of $537,605 million in Jan-Dec 2012. The trade deficit improved to $476,392 million in Jan-Dec 2013.

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

	Trade Balance	Exports	Month ∆%	Imports	Month ∆%
Oct 2014	-43,432	197,537	1.2	240,970	0.9
Sep	-43,603	195,232	-1.8	238,835	0.0
Aug	-40,031	198,736	0.4	238,767	0.0
Jul	-40,695	198,031	1.2	238,726	0.5
Jun	-41,745	195,698	-0.4	237,443	-1.1
May	-43,562	196,559	1.2	240,121	0.0
Apr	-45,914	194,318	0.2	240,233	1.3
Mar	-43,124	193,940	3.3	237,064	3.1
Feb	-42,230	187,773	-2.4	230,003	-0.7
Jan	-39,181	192,475	-0.2	231,655	0.6
Dec 2013	-37,393	192,799	-1.1	230,193	-0.3
Nov	-35,972	194,922	0.5	230,894	-0.9
Oct	-39,083	193,971	2.0	233,053	0.2
Sep	-42,263	190,249	-0.2	232,512	1.0
Aug	-39,515	190,606	0.4	230,121	0.3
Jul	-39,419	189,902	-0.2	229,321	1.1
Jun	-36,552	190,366	1.7	226,918	-2.2
May	-44,831	187,206	-0.3	232,037	1.7
Apr	-40,417	187,763	0.5	228,180	1.9
Mar	-36,973	186,903	-0.6	223,876	-2.6
Feb	-41,770	188,030	0.3	229,800	0.1
Jan	-42,205	187,478	-1.2	229,683	1.0
Jan-Dec 2013	-476,392	2,280,194		2,756,586
Dec 2012	-37,634	189,765	1.9	227,399	-2.4
Nov	-46,604	186,286	1.5	232,891	3.1
Oct	-42,358	183,512	-2.7	225,870	-1.3
Sep	-40,150	188,696	3.2	228,846	0.6
Aug	-44,536	182,845	-0.5	227,380	-0.1
Jul	-43,834	183,673	-0.9	227,507	-0.4
Jun	-43,078	185,330	0.6	228,408	-1.3
May	-47,184	184,306	-0.1	231,490	-0.4
Apr	-47,773	184,543	-0.9	232,317	-1.6
Mar	-49,850	186,257	2.5	236,107	4.9
Feb	-43,338	181,720	1.2	225,058	-2.5
Jan	-51,266	179,606	0.2	230,873	0.2
Jan-Dec 2012	-537,605	2,216,540		2,754,145
Jan-Dec 2011	-548,625	2,127,021		2,675,646
Jan-Dec 2010	-494,658	1,853,606		2,348,263

Note: Trade Balance of Goods = Exports of Goods less Imports of Goods. Trade balance may not add exactly because of errors of rounding and seasonality. Source: US Census Bureau, Foreign Trade Division

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

Table IIA-1B provides US exports, imports and the trade balance of goods. The US has not shown a trade surplus in trade of goods since 1976. The deficit of trade in goods deteriorated sharply during the boom years from 2000 to 2007. The deficit improved during the contraction in 2009 but deteriorated in the expansion after 2009. The deficit could deteriorate sharply with growth at full employment.

Table IIA-1B, US, International Trade Balance of Goods, Exports and Imports of Goods, Millions of Dollars, Census Basis

	Balance	∆%	Exports	∆%	Imports	∆%
1960	4,608	(X)	19,626	(X)	15,018	(X)
1961	5,476	18.8	20,190	2.9	14,714	-2.0
1962	4,583	-16.3	20,973	3.9	16,390	11.4
1963	5,289	15.4	22,427	6.9	17,138	4.6
1964	7,006	32.5	25,690	14.5	18,684	9.0
1965	5,333	-23.9	26,699	3.9	21,366	14.4
1966	3,837	-28.1	29,379	10.0	25,542	19.5
1967	4,122	7.4	30,934	5.3	26,812	5.0
1968	837	-79.7	34,063	10.1	33,226	23.9
1969	1,289	54.0	37,332	9.6	36,043	8.5
1970	3,224	150.1	43,176	15.7	39,952	10.8
1971	-1,476	-145.8	44,087	2.1	45,563	14.0
1972	-5,729	288.1	49,854	13.1	55,583	22.0
1973	2,389	-141.7	71,865	44.2	69,476	25.0
1974	-3,884	-262.6	99,437	38.4	103,321	48.7
1975	9,551	-345.9	108,856	9.5	99,305	-3.9
1976	-7,820	-181.9	116,794	7.3	124,614	25.5
1977	-28,352	262.6	123,182	5.5	151,534	21.6
1978	-30,205	6.5	145,847	18.4	176,052	16.2
1979	-23,922	-20.8	186,363	27.8	210,285	19.4
1980	-19,696	-17.7	225,566	21.0	245,262	16.6
1981	-22,267	13.1	238,715	5.8	260,982	6.4
1982	-27,510	23.5	216,442	-9.3	243,952	-6.5
1983	-52,409	90.5	205,639	-5.0	258,048	5.8
1984	-106,702	103.6	223,976	8.9	330,678	28.1
1985	-117,711	10.3	218,815	-2.3	336,526	1.8
1986	-138,279	17.5	227,159	3.8	365,438	8.6
1987	-152,119	10.0	254,122	11.9	406,241	11.2
1988	-118,526	-22.1	322,426	26.9	440,952	8.5
1989	-109,399	-7.7	363,812	12.8	473,211	7.3
1990	-101,719	-7.0	393,592	8.2	495,311	4.7
1991	-66,723	-34.4	421,730	7.1	488,453	-1.4
1992	-84,501	26.6	448,164	6.3	532,665	9.1
1993	-115,568	36.8	465,091	3.8	580,659	9.0
1994	-150,630	30.3	512,626	10.2	663,256	14.2
1995	-158,801	5.4	584,742	14.1	743,543	12.1
1996	-170,214	7.2	625,075	6.9	795,289	7.0
1997	-180,522	6.1	689,182	10.3	869,704	9.4
1998	-229,758	27.3	682,138	-1.0	911,896	4.9
1999	-328,821	43.1	695,797	2.0	1,024,618	12.4
2000	-436,104	32.6	781,918	12.4	1,218,022	18.9
2001	-411,899	-5.6	729,100	-6.8	1,140,999	-6.3
2002	-468,263	13.7	693,103	-4.9	1,161,366	1.8
2003	-532,350	13.7	724,771	4.6	1,257,121	8.2
2004	-654,830	23.0	814,875	12.4	1,469,704	16.9
2005	-772,373	18.0	901,082	10.6	1,673,455	13.9
2006	-827,971	7.2	1,025,967	13.9	1,853,938	10.8
2007	-808,763	-2.3	1,148,199	11.9	1,956,962	5.6
2008	-816,199	0.9	1,287,442	12.1	2,103,641	7.5
2009	-503,582	-38.3	1,056,043	-18.0	1,559,625	-25.9
2010	-635,362	26.2	1,278,495	21.1	1,913,857	22.7
2011	-725,447	14.2	1,482,508	16.0	2,207,954	15.4
2012	-730,599	0.7	1,545,703	4.3	2,276,302	3.1
2013	-688,728	-5.7	1,579,593	2.2	2,268,321	-0.4

Source: US Census Bureau, Foreign Trade Division

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. The low average rate of growth of GDP of 2.2 percent during the expansion beginning since IIIQ2009 does not deteriorate further the trade balance. Higher rates of growth may cause sharper deterioration.

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

Table IIA-2B provides the US international trade balance, exports and imports of goods and services on an annual basis from 1992 to 2013. 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 not seasonally adjusted increased from $81.0 billion in IQ2013 to $103.5 billion in IIQ2014 (http://www.bea.gov/international/index.htm). The current account deficit seasonally adjusted at annual rate fell from 2.6 percent of GDP in IQ2013 to 2.0 percent of GDP in IVQ2013, increasing to 2.4 percent of GDP in IQ2014 and 2.3 percent of GDP in IIQ2014 (http://www.bea.gov/international/index.htm http://www.bea.gov/iTable/index_nipa.cfm). 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-2B shows marginal improvement of the trade deficit from $548,625 million in 2011 to lower $537,605 million in 2012 with exports growing 4.2 percent and imports 2.9 percent. The trade balance improved further to deficit of $476,392 million in 2013 with growth of exports of 2.9 percent while imports stagnated. Growth and commodity shocks under alternating inflation waves (http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html) have deteriorated the trade deficit from the low of $383,774 million in 2009.

Table IIA-2B, US, International Trade Balance of Goods and Services, Exports and Imports of Goods and Services, SA, Millions of Dollars, Balance of Payments Basis

	Balance	Exports	∆%	Imports	∆%
1960	3,508	25,940	NA	22,432	NA
1961	4,195	26,403	1.8	22,208	-1.0
1962	3,370	27,722	5.0	24,352	9.7
1963	4,210	29,620	6.8	25,410	4.3
1964	6,022	33,341	12.6	27,319	7.5
1965	4,664	35,285	5.8	30,621	12.1
1966	2,939	38,926	10.3	35,987	17.5
1967	2,604	41,333	6.2	38,729	7.6
1968	250	45,543	10.2	45,293	16.9
1969	91	49,220	8.1	49,129	8.5
1970	2,254	56,640	15.1	54,386	10.7
1971	-1,302	59,677	5.4	60,979	12.1
1972	-5,443	67,222	12.6	72,665	19.2
1973	1,900	91,242	35.7	89,342	23.0
1974	-4,293	120,897	32.5	125,190	40.1
1975	12,404	132,585	9.7	120,181	-4.0
1976	-6,082	142,716	7.6	148,798	23.8
1977	-27,246	152,301	6.7	179,547	20.7
1978	-29,763	178,428	17.2	208,191	16.0
1979	-24,565	224,131	25.6	248,696	19.5
1980	-19,407	271,834	21.3	291,241	17.1
1981	-16,172	294,398	8.3	310,570	6.6
1982	-24,156	275,236	-6.5	299,391	-3.6
1983	-57,767	266,106	-3.3	323,874	8.2
1984	-109,072	291,094	9.4	400,166	23.6
1985	-121,880	289,070	-0.7	410,950	2.7
1986	-138,538	310,033	7.3	448,572	9.2
1987	-151,684	348,869	12.5	500,552	11.6
1988	-114,566	431,149	23.6	545,715	9.0
1989	-93,141	487,003	13.0	580,144	6.3
1990	-80,864	535,233	9.9	616,097	6.2
1991	-31,135	578,344	8.1	609,479	-1.1
1992	-39,212	616,882	6.7	656,094	7.6
1993	-70,311	642,863	4.2	713,174	8.7
1994	-98,493	703,254	9.4	801,747	12.4
1995	-96,384	794,387	13.0	890,771	11.1
1996	-104,065	851,602	7.2	955,667	7.3
1997	-108,273	934,453	9.7	1,042,726	9.1
1998	-166,140	933,174	-0.1	1,099,314	5.4
1999	-258,617	969,867	3.9	1,228,485	11.8
2000	-372,517	1,075,321	10.9	1,447,837	17.9
2001	-361,511	1,005,654	-6.5	1,367,165	-5.6
2002	-418,955	978,706	-2.7	1,397,660	2.2
2003	-493,890	1,020,418	4.3	1,514,308	8.3
2004	-609,883	1,161,549	13.8	1,771,433	17.0
2005	-714,245	1,286,022	10.7	2,000,267	12.9
2006	-761,716	1,457,642	13.3	2,219,358	11.0
2007	-705,375	1,653,548	13.4	2,358,922	6.3
2008	-708,726	1,841,612	11.4	2,550,339	8.1
2009	-383,774	1,583,053	-14.0	1,966,827	-22.9
2010	-494,658	1,853,606	17.1	2,348,263	19.4
2011	-548,625	2,127,021	14.8	2,675,646	13.9
2012	-537,605	2,216,540	4.2	2,754,145	2.9
2013	-476,392	2,280,194	2.9	2,756,586	0.1

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 Oct 2014. There is long-term trend of deterioration of the US trade deficit shown vividly by Chart IIA-2. The global recession from IVQ2007 to IIQ2009 reversed the trend of deterioration. 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.

Chart IIA-2, US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-Oct 2014

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 Sep 2014. 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.

Chart IIA-3, US, Exports SA, Monthly, Millions of Dollars Jan 1992-Oct 2014

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 Sep 2014. 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 and portfolio reallocations from commodity exposures to equities.

Chart IIA-4, US, Imports SA, Monthly, Millions of Dollars Jan 1992-Oct 2014

Source: US Census Bureau

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

There is deterioration of the US trade balance in goods in Table IIA-3 from deficit of $57,742 million in Oct 2013 to deficit of $62,671 million in Oct 2014. The nonpetroleum deficit increased by $8,254 million while the petroleum deficit shrank by $3,250 million. Total exports of goods increased 1.4 percent in Oct 2014 relative to a year earlier while total imports increased 3.5 percent. Nonpetroleum exports increased 3.1 percent from Oct 2013 to Oct 2014 while nonpetroleum imports increased 7.5 percent. Petroleum imports fell 16.2 percent.

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

	Oct 2014	Oct 2013	∆%
Total Balance	-62,671	-57,742
Petroleum	-15,328	-18,578
Non Petroleum	-46,159	-37,905
Total Exports	138,045	136,141	1.4
Petroleum	10,981	12,702	-13.5
Non Petroleum	126,250	122,513	3.1
Total Imports	200,716	193,884	3.5
Petroleum	26,219	31,280	-16.2
Non Petroleum	172,409	160,418	7.5

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-Oct 2014 and Jan-Oct 2013 are in Table IIA-4. The rate of growth of exports was 3.3 percent and 3.3 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that increased 6.5 percent and of mineral fuels that increased 11.0 percent both because prices of raw materials and commodities increase and fall recurrently as a result of shocks of risk aversion and portfolio reallocations. The US exports an insignificant but growing amount of crude oil, increasing 10.0 percent in cumulative Jan-Oct 2014 relative to a year earlier. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports increased 1.1 percent while manufactured imports rose 5.0 percent. Significant part of the US trade imbalance originates in imports of mineral fuels decreasing 7.6 percent and petroleum decreasing 8.9 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/2014/11/squeeze-of-economic-activity-by-carry.html). There is current reversal because of the sharp decline of commodity prices.

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

	Jan-Oct 2014 $ Millions	Jan-Oct 2014 $ Millions	∆%
Exports	1,353,708	1,311,388	3.2
Manufactured	998,381	987,079	1.1
Agricultural Commodities	121,646	114,215	6.5
Mineral Fuels	131,694	118,643	11.0
Petroleum	108,317	98,499	10.0
Imports	1,960,620	1,897,175	3.3
Manufactured	1,603,995	1,527,355	5.0
Agricultural Commodities	93,473	87,628	6.7
Mineral Fuels	298,515	323,123	-7.6
Petroleum	282,207	309,730	-8.9

Source: US Census Bureau

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

ESVI United States Services. Chart II-1 of the US Census Bureau of the Department of Commerce provides the quarterly service report SA from IIIQ2003 to IIQ2014. Services revenue contracted during the recession from IVQ2007 (December) to IIQ2009 (June) (http://wwwdev.nber.org/cycles/cyclesmain.html) but there appears to be continuing growth especially for professional, scientific and technical services with steeper slope from IVQ2010 through IIIQ2014.

Chart II-1, US, Quarterly Revenue for Selected Services, SA $ Billions

Note: _____ Information Seasonally Adjusted (SA)

_____ Professional, Scientific and Technical Services (SA)

_____ Administrative and Support and Waste Management (SA)

Source: US Census Bureau

http://www2.census.gov/services/qss/qss.gif

Total revenues of information services not seasonally adjusted in millions of current dollars are shown in Table II-1 from IVQ2003, when they become available, to IIIQ2014. The row below current values provides percentage change in the quarter from the quarter a year earlier. Growth rates were robust before the global recession in the range from 3.7 percent in IVQ2004 to 5.5 percent in IQ2005. Percentage changes were negative in all quarters in 2009 with the deepest declines in the first three quarters. Growth was milder in the expansion phase than before the global recession. As with most indicators of the US, growth was robust in the final three quarters of 2010 and initial quarters of 2011. Growth rates recovered to 5.6 percent in IVQ2012, 4.8 percent in IQ2013 and 4.4 percent in IIQ2013. Growth continued with 5.3 percent in IIIQ2013 relative to a year earlier and 5.5 percent in IVQ2013. Growth strengthened with 6.0 percent in IQ2014 relative to a year earlier and 5.7 percent in IIQ2014 relative to a year earlier. Growth softened to 4.9 percent in IIIQ2014 relative to a year earlier.

Table II-1, US, Information Services Revenue Not Seasonally Adjusted, Millions of Dollars, 2003-2014

Year	1st Quarter	2nd Quarter	3rd Quarter	4th Quarter
2003	NA	NA	NA	237,399
2004	223,675	233,241	232,983	246,201
∆%	NA	NA	NA	3.7
2005	236,033	244,136	244,711	255,856
∆%	5.5	4.7	5.0	3.9
2006	245,182	254,735	255,745	271,401
∆%	3.9	4.3	4.5	6.1
2007	257,973	265,739	267,325	281,304
∆%	5.2	4.3	4.5	3.6
2008	270,223	277,650	277,603	282,873
∆%	4.7	4.5	3.8	0.6
2009	261,921	266,862	265,511	280,665
∆%	-3.1	-3.9	-4.4	-0.8
2010	267,597	274,785	276,049	291,794
∆%	2.2	3.0	4.0	4.0
2011	277,416	289,110	288,779	305,253
∆%	3.7	5.2	4.6	4.6
2012	291,952	300,081	298,950	322,308
∆%	5.2	3.8	3.5	5.6
2013	306,040	313,234	314,646	340,055
∆%	4.8	4.4	5.3	5.5
2014	324,502	331,080	330,146	NA
∆%	6.0	5.7	4.9

Source: US Census Bureau

http://www.census.gov/services/index.html

Chart II-2 provides total revenue of information services not seasonally adjusted from IVQ2013 to IIIQ2014 in current millions of dollars not seasonally adjusted. Oscillating growth was strong before the drop of the global recession. Growth recovered in recent quarters relative to the same quarter a year earlier with strong increase in IVQ2012 followed by increases in all quarters in 2013. Growth continued in upward trend IQ2014, IIQ2014 and IIIQ2014.

Chart II-2, Quarterly Revenue for Information Services Not Seasonally Adjusted, Millions of Dollars 2003-2014

Source: US Census Bureau

http://www.census.gov/services/index.html

There is similar pattern in Chart II-3 with quarterly total revenue of information services in current millions of dollars adjusted for seasonality. There is the same hump of the global recession followed by resumption of growth.

Chart II-3, Quarterly Revenue for Information Services Seasonally Adjusted, Millions of Dollars 2003-2014

Source: US Census Bureau

http://www.census.gov/services/index.html

Table II-2 provides total revenue of financial services and insurance in current million dollars not seasonally adjusted from IIIQ2009, when data first become available, to IIIQ2014. The row below values provides percentage changes in a quarter relative to the same quarter a year earlier. Percentage changes were negative until 2012 with 3.0 percent in IQ2012, 1.3 percent in IIQ2012, 5.4 percent in IIIQ2012 and 3.8 percent in IVQ2012. Revenue increased 1.1 percent in IQ2013 relative to a year earlier and increased 3.9 percent in IIQ2013. Revenue growth moderated to 0.4 percent in IIIQ2013 and recovered to 4.9 percent in IVQ2013. Growth strengthened with 5.0 percent in IQ2014 relative to a year earlier and 4.7 percent in IIQ2014 relative to a year earlier. Growth increased to 6.6 percent in IIIQ2014 relative to a year earlier.

Table II-2, US, Financial Services and Insurance Total Revenue Not Seasonally Adjusted, Millions of Dollars, 2003-2013

2009	NA	NA	844,210	842,875
2010	831,167	831,769	831,075	832,059
∆%	NA	NA	-1.6	-1.3
2011	830,076	828,539	814,472	820,554
∆%	-0.1	-0.4	-2.0	-1.4
2012	854,954	839,140	858,619	851,997
∆%	3.0	1.3	5.4	3.8
2013	864,479	871,496	862,024	894,022
∆%	1.1	3.9	0.4	4.9
2014	907,418	912,185	919,027	NA
∆%	5.0	4.7	6.6	NA

Source: US Census Bureau

http://www.census.gov/services/index.html

Chart II-4 provides total quarterly revenue of financial services and insurance from IIIQ2009, when data first become available, to IIQ2014. Total revenue of financial services and insurance contracted 1.3 percent between IVQ2009 and IVQ2011 and grew 3.8 percent between IVQ2011 and IVQ2012. Revenue increased 1.1 percent in IQ2013 relative to a year earlier and 3.9 percent in IIQ2013. Revenue growth slowed to 0.4 percent in IIIQ2013 and jumped to 4.9 percent in IVQ2013. Growth continued with 5.0 percent in IQ2014 relative to a year earlier and 4.7 percent in IIQ2014 relative to a year earlier, strengthening to 6.6 percent in IIIQ2014 relative to a year earlier.

Chart II-4, Total Quarterly Revenue for Financial Services and Insurance Not Seasonally Adjusted, Millions of Dollars 2003-2014

Source: US Census Bureau

http://www.census.gov/services/index.html

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