CMP Associates Regulation Blog: Capital Flows, Exchange Rates and Unconventional Monetary Policy, Interest Rate Risks, Recovery without Hiring, Cyclical Slow Growth not Secular Stagnation, Collapse of United States Dynamism of Income Growth and Employment Creation, World Financial Turbulence, World Economic Slowdown and Global Recession Risk: Part I

Capital Flows, Exchange Rates and Unconventional Monetary Policy, Interest Rate Risks, Recovery without Hiring, Cyclical Slow Growth not Secular Stagnation, Collapse of United States Dynamism of Income Growth and Employment Creation, World Financial Turbulence, World Economic Slowdown and Global Recession Risk

Carlos M. Pelaez

Executive Summary

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

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

IIB United States Commercial Banks Assets and Liabilities

IIA1 Transmission of Monetary Policy

IIB1 Functions of Banks

IIC United States Commercial Banks Assets and Liabilities

IID Theory and Reality of Economic History, Cyclical Slow Growth Not Secular Stagnation and Monetary Policy Based on Fear of Deflation

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 Increasing Interest Rate Risk, Tapering Quantitative Easing, Duration Dumping, 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 Commercial Banks Assets and Liabilities

ESI 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 (2013WEOOct) provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/pubs/ft/weo/2013/02/), of the world financial system with its Global Financial Stability Report (GFSR) (IMF 2013GFSROct) (http://www.imf.org/External/Pubs/FT/GFSR/2013/02/index.htm) and of fiscal affairs with the Fiscal Monitor (IMF 2013FMOct) (http://www.imf.org/external/pubs/ft/fm/2013/02/fmindex.htm). There appears to be a moment of transition in global economic and financial variables that may prove of difficult analysis and measurement. It is useful to consider a summary of global economic and financial risks, which are analyzed in detail in the comments of this blog in Section VI Valuation of Risk Financial Assets, Table VI-4.

Economic risks include the following:

China’s Economic Growth. China is lowering its growth target to 7.5 percent per year. China’s 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 1.8 percent relative to IIIQ2013, which is equivalent to 7.4 percent per year (Section VC 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.
United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 29.3 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically low hiring and declining/stagnating real wages.
Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.
World Inflation Waves. Inflation continues in repetitive waves globally (http://cmpassocregulationblog.blogspot.com/2014/01/world-inflation-waves-interest-rate.htmland earlier http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html). There is growing concern on capital outflows and currency depreciation of emerging markets.

A list of financial uncertainties includes:

Euro Area Survival Risk. The resilience of the euro to fiscal and financial doubts on larger member countries is still an unknown risk.
Foreign Exchange Wars. Exchange rate struggles continue as zero interest rates in advanced economies induce devaluation of their currencies with alternating episodes of revaluation.
Valuation of Risk Financial Assets. Valuations of risk financial assets have reached extremely high levels in markets with lower volumes.
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.
Credibility and Commitment of Central Bank Policy. There is a credibility issue of the commitment of monetary policy (Sargent and Silber 2012Mar20).
Carry Trades. Commodity prices driven by zero interest rates have resumed their increasing path with fluctuations caused by intermittent risk aversion

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 $2495 billion, or $2.5 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 Jan 23, 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
11/27/13	0.09	2.74	5.34 (11/26/13)
12/6/13	0.09	2.88	5.47
12/12/13	0.09	2.89	5.42
12/19/13	0.09	2.94	5.36
12/26/13	0.08	3.00	5.37
1/2/2014	0.08	3.00	5.34
1/9/2014	0.07	2.97	5.28
1/16/2014	0.07	2.86	5.18
1/23/2014	0.07	2.79	5.11

Source: Board of Governors of the Federal Reserve System

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

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 resulting from the debate within and outside the Fed on tapering quantitative easing. Table VIII-2 provides the yield curve of Treasury securities on Jan 24, 2014, Dec 31, 2013, May 1, 2013, Jan 24, 2013 and Jan 24, 2006. There is ongoing 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 2.75 percent on Jan 24, 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 2.75 percent as occurred on Jan 24, 2013 would jump instantaneously from yield of 2.75 percent on Jan 24, 2014 to 4.40 percent as occurred on Jan 24, 2006 when the economy was closer to full employment. The price of the hypothetical bond issued with coupon of 2.75 percent would drop from 100 to 87.7669 after an instantaneous increase of the yield to 4.40 percent. The price loss would be 12.2 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

	1/24/14	12/31/13	5/01/13	1/24/13	1/24/06
1 M	0.04	0.01	0.03	0.06	4.24
3 M	0.04	0.07	0.06	0.08	4.40
6 M	0.06	0.10	0.08	0.10	4.51
1 Y	0.11	0.13	0.11	0.15	4.46
2 Y	0.37	0.38	0.20	0.23	4.37
3 Y	0.75	0.78	0.30	0.37	4.33
5 Y	1.58	1.75	0.65	0.78	4.32
7 Y	2.20	2.45	1.07	1.26	4.34
10 Y	2.75	3.04	1.66	1.88	4.40
20 Y	3.40	3.72	2.44	2.64	4.63
30 Y	3.64	3.96	2.83	3.04	NA

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 4.39 percent on Jan 23, 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.

Chart VI-13, US, Conventional Mortgage Rate, Jan 8, 2004 to Jan 23, 2014

Source: Board of Governors of the Federal Reserve System

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

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 Jan 17, 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 in the current flight from emerging markets is MXN 13.2680/USD on Jan 17, 2014.

Chart VI-4A, Mexican Peso (MXN) per US Dollar (USD), Nov 8, 1993 to Jan 17, 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. Portfolio reallocations induced by combination of zero interest rates and risk events stimulate carry trades that generate wide swings in world capital flows. Chart VI-4B provides the rate of the Indian rupee (INR) per US dollar (USD) from Jan 2, 1973 to Jan 17, 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 61.5400/USD on Jan 17, 2014.

Chart VI-4B, Indian Rupee (INR) per US Dollar (USD), Jan 2, 1973 to Jan 17, 2014

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

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

ChVI-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 104.3200/USD on Jan 17, 2013 for appreciation of 15.9 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. 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-Jan 17, 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 2.3550/USD on Jan 17, 2013. 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 2.3550/USD on Jan 17, 2014 for depreciation of 53.2 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 Jan 17, 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 Jan 17, 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).

Current focus is on 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. Market are overreacting to the so-called “paring” of outright purchases of $85 billion of securities per month for the balance sheet of the Fed (http://www.federalreserve.gov/newsevents/press/monetary/20131218a.htm):

“In light of the cumulative progress toward maximum employment and the improvement in the outlook for labor market conditions, the Committee decided to modestly reduce the pace of its asset purchases. Beginning in January, the Committee will add to its holdings of agency mortgage-backed securities at a pace of $35 billion per month rather than $40 billion per month, and will add to its holdings of longer-term Treasury securities at a pace of $40 billion per month rather than $45 billion per month. The Committee is maintaining its existing policy of reinvesting principal payments from its holdings of agency debt and agency mortgage-backed securities in agency mortgage-backed securities and of rolling over maturing Treasury securities at auction. The Committee's sizable and still-increasing holdings of longer-term securities should maintain downward pressure on longer-term interest rates, support mortgage markets, and help to make broader financial conditions more accommodative, which in turn should promote a stronger economic recovery and help to ensure that inflation, over time, is at the rate most consistent with the Committee's dual mandate.”

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 Dec 18, 2013 (http://www.federalreserve.gov/newsevents/press/monetary/20131218a.htm):

“To support continued progress toward maximum employment and price stability, the Committee today reaffirmed its view that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the asset purchase program ends and the economic recovery strengthens. The Committee also reaffirmed its expectation that the current exceptionally low target range for the federal funds rate of 0 to 1/4 percent will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee's 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored (emphasis added).

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.”

“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 differfrom 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

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/2013/12/theory-and-reality-of-secular.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).

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. Indefinite financial repression induces carry trades with high leverage, risks and illiquidity. 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 15,879.11 on Fri Jan 24, 2014, which is higher by 12.1 percent than the value of 14,164.53 reached on Oct 9, 2007 and higher by 11.8 percent than the value of 14,198.10 reached on Oct 11, 2007. Values of risk financial are approaching or exceeding historical highs.

Jon Hilsenrath, writing on “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 63.9 percent since the trough of the sovereign debt crisis in Europe on Jul 2, 2010 to Jan 24, 2014; S&P 500 has gained 75.1 percent and DAX 65.6 percent. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 1/24/14” 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 13.8 percent below the trough. Japan’s Nikkei Average is 74.4 percent above the trough. DJ Asia Pacific TSM is 23.9 percent above the trough. Dow Global is 42.3 percent above the trough. STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 25.3 percent above the trough. NYSE Financial Index is 44.4 percent above the trough. DJ UBS Commodities is 2.4 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 65.6 percent above the trough. Japan’s Nikkei Average is 74.4 percent above the trough on Aug 31, 2010 and 35.1 percent above the peak on Apr 5, 2010. The Nikkei Average closed at 15,391.56 on Fri Jan 17, 2014 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 50.1 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 14.7 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 1/24/14” in Table VI-4 shows increase of 2.5 percent in the week for China’s Shanghai Composite. DJ Asia Pacific decreased 1.4 percent. NYSE Financial decreased 3.7 percent in the week. DJ UBS Commodities increased 1.5 percent. Dow Global decreased 2.6 percent in the week of Jan 24, 2014. The DJIA decreased 3.5 percent and S&P 500 decreased 2.6 percent. DAX of Germany decreased 3.6 percent. STOXX 50 decreased 3.4 percent. The USD depreciated 1.0 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 1/24/14” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Jan 24, 2014. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 1/24/14” but also relative to the peak in column “∆% Peak to 1/24/14.” There are now several equity indexes above the peak in Table VI-4: DJIA 41.7 percent, S&P 500 47.1 percent, DAX 48.3 percent, Dow Global 16.1 percent, DJ Asia Pacific 8.4 percent, NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) 15.0 percent, Nikkei Average 35.1 percent and STOXX 50 6.1 percent. There is only one equity index below the peak: Shanghai Composite by 35.1 percent. DJ UBS Commodities Index is now 12.4 percent below the peak. The US dollar strengthened 9.6 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. 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, gross private domestic investment in the US was $951.6 billion of 2009 dollars, growing to $1,143.0 billion in IVQ1986 or 20.1 percent. Real gross private domestic investment in the US increased 0.8 percent from $2,605.2 billion of 2009 dollars in IVQ2007 to $2,627.2 billion in IIIQ2013. As shown in Table IAI-2, real private fixed investment fell 3.6 percent from $2,586.3 billion of 2009 dollars in IVQ2007 to $2,494.0 billion in IIIQ2013. Growth of real private investment is mediocre for all but four quarters from IIQ2011 to IQ2012 (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/11/global-financial-risk-mediocre-united.html). 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 fell $26.6 billion in IQ2013 after increasing $34.9 billion in IVQ2012 and $13.9 billion in IIIQ2012. Corporate profits with IVA and CCA rebounded with $66.8 billion in IIQ2013 and $39.2 billion in IIIQ2013. Profits after tax with IVA and CCA fell $1.7 billion in IQ2013 after increasing $40.8 billion in IVQ2012 and $4.5 billion in IIIQ2012. In IIQ2013, profits after tax with IVA and CCA increased $56.9 billion and $39.5 billion in IIIQ2013. Anticipation of higher taxes in the “fiscal cliff” episode caused increase of $120.9 billion in net dividends in IVQ2012 followed with adjustment in the form of decrease of net dividends by $103.8 billion in IQ2013, rebounding with $273.5 billion in IIQ2013. Net dividends fell at $179.0 billion in IIIQ2013. There is similar decrease of $80.1 billion in undistributed profits with IVA and CCA in IVQ2012 followed by increase of $102.1 billion in IQ2013 and decline of $216.6 billion in IIQ2013. Undistributed profits with IVA and CCA rose at $218.6 billion in IIIQ2013. Undistributed profits of US corporations swelled 382.4 percent from $107.7 billion IQ2007 to $519.5 billion in IIIQ2013 and changed signs from minus $55.9 billion in billion in IVQ2007 (Section IA2). In IQ2013, corporate profits with inventory valuation and capital consumption adjustment fell $26.6 billion relative to IVQ2012, from $2047.2 billion to $2020.6 billion at the quarterly rate of minus 1.3 percent. In IIQ2013, corporate profits with IVA and CCA increased $66.8 billion from $2020.6 billion in IQ2013 to $2087.4 billion at the quarterly rate of 3.3 percent. Corporate profits with IVA and CCA increased $39.2 billion from $2087.4 billion in IIQ2013 to $2126.6 billion in IIIQ2013 at the annual rate of 1.9 percent (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_3rd.pdf). 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. 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 1/24/ /14	∆% Week 1/24/14	∆% Trough to 1/24/ 14
DJIA	4/26/ 10	7/2/10	-13.6	41.7	-3.5	63.9
S&P 500	4/23/ 10	7/20/ 10	-16.0	47.1	-2.6	75.1
NYSE Finance	4/15/ 10	7/2/10	-20.3	15.0	-3.7	44.4
Dow Global	4/15/ 10	7/2/10	-18.4	16.1	-2.6	42.3
Asia Pacific	4/15/ 10	7/2/10	-12.5	8.4	-1.4	23.9
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	35.1	-2.2	74.4
China Shang.	4/15/ 10	7/02 /10	-24.7	-35.1	2.5	-13.8
STOXX 50	4/15/10	7/2/10	-15.3	6.1	-3.4	25.3
DAX	4/26/ 10	5/25/ 10	-10.5	48.3	-3.6	65.6
Dollar Euro	11/25 2009	6/7 2010	21.2	9.6	-1.0	-14.7
DJ UBS Comm.	1/6/ 10	7/2/10	-14.5	-12.4	1.5	2.4
10-Year T Note	4/5/ 10	4/6/10	3.986	2.784	2.720

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 have increased by only 4 percent since Jan 2009. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job currently is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn, there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (Section I and earlier http://cmpassocregulationblog.blogspot.com/2013/12/theory-and-reality-of-secular.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).

Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 52.0 million in 2012 or by 11.8 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 48.5 million in 2012 or by 11.0 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.2 in 2005 to 38.9 in 2012 and in the private sector (RHP) from 53.1 in 2005 to 43.4 in 2012. 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. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 17 quarters from IIIQ2009 to IIIQ2013. 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 third estimate of GDP for IIIQ2013 (http://www.bea.gov/newsreleases/national/gdp/2013/pdf/gdp3q13_3rd.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 $14,738.0 billion in IIQ2010 by GDP of $14,356.9 billion in IIQ2009 {[$14,738.0/$14,356.9 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.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, 5.4 percent from IQ1983 to IVQ1986 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.html).As a result, there are 29.3 million unemployed or underemployed in the United States for an effective unemployment rate of 18.0 percent (http://cmpassocregulationblog.blogspot.com/2014/01/twenty-nine-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/risks-of-zero-interest-rates-mediocre.html). 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.

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	62,948	47.8	58,825	53.1
2002	58,583	44.9	54,759	50.3
2003	56,451	43.4	53,056	48.9
2004	60,367	45.9	56,617	51.6
2005	63,150	47.2	59,372	53.1
2006	63,773	46.9	59,494	52.1
2007	62,421	45.4	58,035	50.3
2008	55,128	40.3	51,591	45.1
2009	46,357	35.4	43,031	39.8
2010	48,607	37.4	44,788	41.7
2011	49,675	37.8	46,552	42.5
2012	51,991	38.9	48,493	43.4

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

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

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

Source: US Bureau of Labor Statistics

Year	Annual ∆%
2002	-6.9
2003	-3.6
2004	6.9
2005	4.6
2006	1.0
2007	-2.1
2008	-11.7
2009	-15.9
2010	4.9
2011	2.2
2012	4.7

	HNF	Rate RNF	HP	Rate HP
2001 Nov	4283	3.2	4020	3.6
2002 Nov	4247	3.2	3969	3.6
2003 Nov	4067	3.1	3853	3.5
2004 Nov	4591	3.4	4329	3.9
2005 Nov	4597	3.4	4344	3.8
2006 Nov	4901	3.6	4642	4.0
2007 Nov	4595	3.3	4345	3.7
2008 Nov	3490	2.6	3292	2.9
2009 Nov	3508	2.7	3305	3.1
2010 Nov	3662	2.8	3445	3.2
2011 Oct	3827	2.9	3611	3.3
2012 Nov	3988	2.9	3772	3.3
2013 Nov	4097	3.0	3864	3.3

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
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
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

Year	GDP ∆%	Year	GDP ∆%	Year	GDP ∆%
1930	-8.5	1980	-0.2	2000	4.1
1931	-6.4	1981	2.6	2001	1.0
1932	-12.9	1982	-1.9	2002	1.8
1933	-1.3	1983	4.6	2003	2.8
1934	10.8	1984	7.3	2004	3.8
1935	8.9	1985	4.2	2005	3.4
1936	12.9	1986	3.5	2006	2.7
1937	5.1	1987	3.5	2007	1.8
1938	-3.3	1988	4.2	2008	-0.3
1930	8.0	1989	3.7	2009	-2.8
1940	8.8	1990	1.9	2010	2.5
1941	17.7	1991	-0.1	2011	1.8
1942	18.9	1992	3.6	2012	2.8

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	3	-2.4	-0.8
IIIQ1957 to IIQ1958	3	-3.0	-1.0
IVQ1973 to IQ1975	5	-3.1	-0.6
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.5	-0.64
IVQ2007 to IIQ2009	6	-4.3	-0.72

	Number of Quarters	Cumulative Growth ∆%	Average Annual Equivalent Growth Rate
IIIQ 1954 to IQ1957	11	12.8	4.5
First Four Quarters IIIQ1954 to IIQ1955	4	7.8
IIQ1958 to IIQ1959	5	10.0	7.9
First Four Quarters IIIQ1958 to IIQ1959	4	9.2
IIQ1975 to IVQ1976	8	8.3	4.1
First Four Quarters IIIQ1975 to IIQ1976	4	6.1
IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987	13 15 16 17	19.9 21.6 22.3 23.1	5.7 5.4 5.2 5.0
First Four Quarters IQ1983 to IVQ1983	4	7.8
Average First Four Quarters in Four Expansions*		7.7
IIIQ2009 to IIIQ2013	17	10.3	2.3
First Four Quarters IIIQ2009 to IIQ2010		2.7

	Employed	Full-Time Employed	Part Time Economic Reasons	Noninstitutional Civilian Population
2000s
2000	136.891	113.846	3.227	212.577
2001	136.933	113.573	3.715	215.092
2002	136.485	112.700	4.213	217.570
2003	137.736	113.324	4.701	221.168
2004	139.252	114.518	4.567	223.357
2005	141.730	117.016	4.350	226.082
2006	144.427	119.688	4.162	228.815
2007	146.047	121.091	4.401	231.867
2008	145.362	120.030	5.875	233.788
2009	139.877	112.634	8.913	235.801
2010	139.064	111.714	8.874	237.830
2011	139.869	112.556	8.560	239.618
2012	142.469	114.809	8.122	243.284
2013	143.929	116.314	7.935	245.679
∆2007-2013	-2.118	-4.777	3.534	13.812
∆% 2007-2013	-1.5	-3.9	80.3	6.0
1980s
1979	98.824	82.654	3.577	164.863
1980	99.303	82.562	4.321	167.745
1981	100.397	83.243	4.768	170.130
1982	99.526	81.421	6.170	172.271
1983	100.834	82.322	6.266	174.215
1984	105.005	86.544	5.744	176.383
1985	107.150	88.534	5.590	178.206
1986	109.597	90.529	5.588	180.587
1987	112.440	92.957	5.401	182.753
1988	114.968	95.214	5.206	184.613
1989	117.342	97.369	4.894	186.393
∆1979-1986	10.773	7.875	2.011	15.724
∆% 1979-86	10.9	9.5	56.2	9.5

	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	112.0	139.1	153.6	65.0	58.9	14.5
12/13	246.7	116.7	144.4	154.4	62.6	58.5	10.0

	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	38.7	17.8	21.3	54.9	46.0	3.5	16.2
2013	38.8	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
12/13	38.8	18.1	20.6	53.2	46.7	2.5	12.3

Year	Sep	Oct	Nov	Dec	Annual
2001	19706	19694	19675	19547	20088
2002	19466	19542	19397	19394	19683
2003	18909	19139	19163	19136	19351
2004	19158	19609	19615	19619	19630
2005	19503	19794	19750	19733	19770
2006	19604	19853	19903	20129	20041
2007	19498	19564	19660	19361	19875
2008	18818	18757	18454	18378	19202
2009	16972	16671	16689	16615	17601
2010	16874	16867	16946	16727	17077
2011	17238	17532	17402	17234	17362
2012	17687	17842	17877	17604	17834
2013	18043	17976	18104	18106	18057

Year	Aug	Sep	Oct	Nov	Dec	Annual
2001	2461	2301	2424	2470	2412	2371
2002	2688	2506	2468	2570	2374	2683
2003	2724	2698	2522	2522	2248	2746
2004	2585	2493	2572	2448	2294	2638
2005	2519	2339	2285	2369	2055	2521
2006	2467	2297	2252	2242	2007	2353
2007	2388	2419	2258	2250	2323	2342
2008	2990	2904	2842	2833	2928	2830
2009	4004	3774	3789	3699	3532	3760
2010	3903	3604	3731	3561	3352	3857
2011	3820	3541	3386	3287	3161	3634
2012	3672	3174	3285	3102	3153	3451
2013	3453	3139	3028	2721	2536	3324

Year	Jul	Aug	Sep	Oct	Nov	Dec	Annual
2000	1253	1339	1254	1202	1242	1217	1249
2001	1539	1640	1586	1722	1786	1901	1576
2002	2173	2114	1966	1945	2013	2210	2114
2003	2281	2301	2157	2032	2132	2130	2253
2004	2116	2082	1951	1931	2053	2086	2149
2005	2119	1895	1992	1875	1920	1963	2009
2006	1985	1869	1710	1607	1704	1794	1848
2007	2053	1956	1854	1885	1925	2120	1966
2008	2492	2695	2595	2728	3078	3485	2540
2009	4757	4683	4560	4492	4655	4960	4500
2010	4821	5128	4640	4576	4909	4762	4879
2011	4772	4592	4426	4375	4195	4182	4537
2012	4405	4179	3899	3800	3861	3927	4133
2013	3727	3607	3535	3632	3383	3378	3719

	Dec 2012	Dec 2013	∆%
Total Assets	13,143.4	14,020.3	6.7
Bank Credit	10,018.7	10,136.9	1.2
Securities in Bank Credit	2741.5	2717.2	-0.9
Treasury & Agency Securities	1878.2	1805.4	-3.9
Mortgage-Backed Securities	1346.4	1320.0	-2.0
Loans & Leases	7277.1	7419.7	2.0
Real Estate Loans	3558.1	3528.4	-0.8
Commercial Real Estate Loans	1429.6	1495.1	4.6
Consumer Loans	1132.3	1158.3	2.3
Commercial & Industrial Loans	1496.8	1607.7	7.4
Other Loans & Leases	1089.9	1125.3	3.2
Cash Assets*	1694.5	2572.9	51.8
Total Liabilities	11,627.6	12,501.8	7.5
Deposits	9328.7	9868.2	5.8
Residual (Assets less Liabilities)	1515.7	1518.3	NA

	2009	2010	2011	2012	2013	Nov 2013	Dec 2013
Total Assets	-5.9	-2.7	5.4	2.5	7.1	5.4	4.9
Bank Credit	-6.7	-2.6	1.7	4.0	1.0	2.0	5.9
Securities in Bank Credit	6.3	6.9	1.8	7.5	-1.9	4.5	11.7
Treasury & Agency Securities	13.5	15.2	3.0	8.6	-5.6	6.1	9.0
Other Securities	-4.1	-7.1	-0.7	5.3	6.5	1.3	17.1
Loans & Leases	-10.2	-5.7	1.7	2.7	2.1	1.0	3.7
Real Estate Loans	-5.7	-5.6	-3.7	-1.1	-1.2	-1.2	0.5
Commercial Real Estate Loans	-4.8	-8.9	-6.3	-1.3	4.2	5.0	4.8
Consumer Loans	-3.2	-6.8	-1.2	1.2	3.5	4.1	6.4
Commercial & Industrial Loans	-18.5	-9.0	8.6	11.4	7.8	1.1	14.2
Other Loans & Leases	-23.1	0.4	20.1	6.8	4.1	5.0	-3.8
Cash Assets	49.8	-7.8	48.0	-2.3	55.1	30.5	-9.0
Total Liabilities	-7.1	-3.3	5.5	2.3	8.1	6.3	1.0
Deposits	5.2	2.4	6.7	7.1	6.4	3.7	9.4

	TNF JOB	TNF JOB Rate	TNF LD	TNF LD Annual
Nov 2001	3124	2.3	2132	24499
Nov 2002	3103	2.3	1881	22922
Nov 2003	2894	2.2	1813	23294
Nov 2004	2973	2.2	1864	22802
Nov 2005	3903	2.8	1621	22185
Nov 2006	4162	2.9	1864	21157
Nov 2007	3879	2.7	1940	22142
Nov 2008	2822	2.0	2237	24181
Nov 2009	2134	1.6	1903	26784
Nov 2010	2723	2.0	1781	21773
Nov 2011	2780	2.0	1780	20401
Nov 2012	3371	2.4	1739	20546
Nov 2013	3574	2.5	1460

	U1	U2	U3	U4	U5	U6
2013
Dec	3.5	3.5	6.5	7.0	7.9	13.0
Nov	3.7	3.5	6.6	7.1	7.9	12.7
Oct	3.7	3.6	7.0	7.4	8.3	13.2
Sep	3.7	3.5	7.0	7.5	8.4	13.1
Aug	3.7	3.8	7.3	7.9	8.7	13.6
Jul	3.7	3.8	7.7	8.3	9.1	14.3
Jun	3.9	3.8	7.8	8.4	9.3	14.6
May	4.1	3.7	7.3	7.7	8.5	13.4
Apr	4.3	3.9	7.1	7.6	8.5	13.4
Mar	4.3	4.3	7.6	8.1	9.0	13.9
Feb	4.3	4.6	8.1	8.6	9.6	14.9
Jan	4.3	4.9	8.5	9.0	9.9	15.4
2012
Dec	4.2	4.3	7.6	8.3	9.2	14.4
Nov	4.2	3.9	7.4	7.9	8.8	13.9
Oct	4.3	3.9	7.5	8.0	9.0	13.9
Sep	4.2	4.0	7.6	8.0	9.0	14.2
Aug	4.3	4.4	8.2	8.7	9.7	14.6
Jul	4.3	4.6	8.6	9.1	10.0	15.2
Jun	4.5	4.4	8.4	8.9	9.9	15.1
May	4.7	4.3	7.9	8.4	9.3	14.3
Apr	4.8	4.3	7.7	8.3	9.1	14.1
Mar	4.9	4.8	8.4	8.9	9.7	14.8
Feb	4.9	5.1	8.7	9.3	10.2	15.6
Jan	4.9	5.4	8.8	9.4	10.5	16.2
2011
Dec	4.8	5.0	8.3	8.8	9.8	15.2
Nov	4.9	4.7	8.2	8.9	9.7	15.0
Oct	5.0	4.8	8.5	9.1	10.0	15.3
Sep	5.2	5.0	8.8	9.4	10.2	15.7
Aug	5.2	5.1	9.1	9.6	10.6	16.1
Jul	5.2	5.2	9.3	10.0	10.9	16.3
Jun	5.1	5.1	9.3	9.9	10.9	16.4
May	5.5	5.1	8.7	9.2	10.0	15.4
Apr	5.5	5.2	8.7	9.2	10.1	15.5
Mar	5.7	5.8	9.2	9.7	10.6	16.2
Feb	5.6	6.0	9.5	10.1	11.1	16.7
Jan	5.6	6.2	9.8	10.4	11.4	17.3
Dec 2010	5.4	5.9	9.1	9.9	10.7	16.6
Annual
2013	3.9	3.9	7.4	7.9	8.8	13.8
2012	4.5	4.4	8.1	8.6	9.5	14.7
2011	5.3	5.3	8.9	9.5	10.4	15.9
2010	5.7	6.0	9.6	10.3	11.1	16.7
2009	4.7	5.9	9.3	9.7	10.5	16.2
2008	2.1	3.1	5.8	6.1	6.8	10.5
2007	1.5	2.3	4.6	4.9	5.5	8.3
2006	1.5	2.2	4.6	4.9	5.5	8.2
2005	1.8	2.5	5.1	5.4	6.1	8.9
2004	2.1	2.8	5.5	5.8	6.5	9.6
2003	2.3	3.3	6.0	6.3	7.0	10.1
2002	2.0	3.2	5.8	6.0	6.7	9.6
2001	1.2	2.4	4.7	4.9	5.6	8.1
2000	0.9	1.8	4.0	4.2	4.8	7.0

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