CMP Associates Regulation Blog

Total private hiring (HP) yearly data are provided in ESIV-2. There has been sharp contraction of total private hiring in the US and only milder recovery in 2011 than in 2010.

Chart ESIV-2, US, Total Private Hiring, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

Chart ESIV-3 provides total nonfarm hiring on a monthly basis from 2001 to 2012. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak in 2010 of 4418 in May. Nonfarm hiring fell again in Dec to 4188 from 4268 in Nov and to 4158 in Jan 2012, as shown in ESIV-3 with SA monthly data. The number of seasonally-adjusted hires in Sep was 4276 thousand, falling to 4158 in Jan 2012 or by 2.8 percent. The number of hires not seasonally adjusted was 4507 in Sep, falling to 3038 in Dec but increasing to 3993 in Jan 2012. The number of nonfarm hiring not seasonally adjusted fell by 34.7 percent from Aug to Dec.

Chart ESIV-3, US, Total Nonfarm Hiring (HNF), 2001-2012 Month SA

Source: US Bureau of Labor Statistics

There is only milder improvement in total private hiring shown in Chart ESIV-4. Hiring private (HP) rose in 2010 followed by stability and renewed increase in 2011. The number of private hiring seasonally adjusted fell from 4002 thousand in Sep 2011 to 3889 in Dec or by 2.8 percent, falling to 3835 in Jan 2012 or decline by 4.2 relative to the level in Sep 2011. The number of private hiring not seasonally adjusted fell from 4130 in Sep 2011 to 2856 in Dec or by 30.8 percent, reaching 3668 in Jan 2012 or decline of 11.2 percent relative to Sep 2011. Companies do not hire in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 4934 in Sep 2006 to 3635 in Dec 2006 or by 26.3 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Jul 2006 private hiring NSA was 5555, declining to 4293 in Jul 2011 or by 22.7 percent. The conclusion is that private hiring in the US is more than 20 percent below the hiring before the global recession. The main problem in recovery of the US labor market has been the low rate of growth of 2.4 percent in the ten quarters of expansion of the economy since IIIQ2009 compared with average 6.2 percent in prior expansions from contractions (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html ). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

Chart ESIV-4, US, Total Private Hiring Month SA 2011-2012

Source: US Bureau of Labor Statistics

ESV Ten Million Fewer Full-time Jobs. There is strong seasonality in US labor markets around the end of the year. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.270 million in Sep 2011 to 8.119 million in Feb 2012, seasonally adjusted, or decline of 1.151 million in just three months, as shown in Table ESV-1. The number employed full-time increased from 112.479 million in Sep 2011 to 114.408 million in Feb 2012 or 1.929 million. 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 8.455 million in Feb 2012 or by 463.000. 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. 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 108.770 million in Jan 2010 or by 14.449 million. The number with full-time jobs in Feb 2012 is 112.587 million, which is lower by 10.6 million relative to the peak of 123.219 million in Jul 2007. There appear to be around 10 million less full-time jobs in the US than before the global recession. Growth at 2.4 percent on average in the ten quarters of expansion since IIIQ2009 compared with 6.2 percent on average in expansions from postwar cyclical contractions is the main culprit of the fractured US labor market (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html ).

Table ESV-1, US, Employed Part-time for Economic Reasons, Thousands, and Full-time, Millions

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Feb 2012	8,119	114.408
Jan 2012	8,230	113.845
Dec 2011	8,098	113.765
Nov 2011	8,469	113.212
Oct 2011	8,790	112.841
Sep 2011	9,270	112.479
Aug 2011	8,787	112.406
Not Seasonally Adjusted
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
Feb 2011	8,749	110.731
Jan 2011	9,187	110.373
Dec 2010	9,205	111.207
Nov 2010	8,670	113.138
Oct 2010	8,408	112.342
Feb 2010	9,282	109.100
Jan 2010	9,290	108.770 (low)
Mar 2009	9,305 (high)	112.215
Feb 2009	9,170	112.947
Jan 2009	8,829	113.815
Feb 2008	5,114	119.452
Jan 2008	5,340	119.322
Jul 2007	4,516	123.219 (high)
Feb 2007	4,417	119.041
Jan 2007	4,726	119.094
Sep 2006	3,735 (low)	120.780
Feb 2006	4,403	119.041
Jan 2006	4,597	116.395

Source: US Bureau of Labor Statistics

Chart ESV-1 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 2012 with fluctuations around the typical behavior of a stationary series: there is no improvement in the United States in creating full-time jobs.

Chart ESV-1, US, Full-time Employed, Thousands, NSA, 2001-2012

Sources: US Bureau of Labor Statistics

ESVI Youth Unemployment. The United States is experiencing high youth unemployment as in European economies. Table ESVI-1 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. 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. 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 ESVI-1, US, Employment Level 16-24 Years, Thousands, NSA


Year	Jan	Feb	Dec	Annual
2001	19678	19745	19547	20088
2002	18653	19074	19394	19683
2003	18811	18880	19136	19351
2004	18852	18841	19619	19630
2005	18858	18670	19733	19770
2006	19003	19182	20129	20041
2007	19407	19415	19361	19875
2008	18724	18546	18378	19202
2009	17467	17606	16615	17601
2010	16166	16412	16727	17077
2011	16512	16638	17234	17362
2012	16944	17150

Sources: US Bureau of Labor Statistics

Chart ESVI-1 provides US employment level ages 16 to 24 years from 2001 to 2012. Employment level is sharply lower in Feb 2012 relative to the peak in 2007.

Chart ESVI-1, US, Employment Level 16-24 Years, Thousands SA, 2002-2012

Sources: US Bureau of Labor Statistics

Chart ESVI-2 provides the unemployment level ages 16 to 24 from 2001 to 2012. The level rose sharply from 2007 to 2010 with tepid improvement into 2012.

Chart ESVI-2, US, Unemployment Level 16-24 Years, Thousands SA, 2002-2012

Sources: US Bureau of Labor Statistics

Chart ESVI-3 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 23 years from 2002 to 2012. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels during the ten quarters of expansion of the economy since IIIQ2009.

Chart ESVI-3, US, Unemployment Rate 16-24 Years, Thousands, NSA, 2002-2012

Sources: US Bureau of Labor Statistics

Chart ESVI-4 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2012. 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 claim 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 fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984 while the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 19.9 percent in Jun 2009, 20.0 percent in Jun 2010 and 18.9 percent in Jun 2011. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.4 percent on average during the first ten quarters of expansion from IIIQ2009 to IVQ2011 (see Table I-5 at http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html). The fractured US labor market denies an early start for young people.

Chart ESVI-4, US, Unemployment Rate 16-24 Years, Percent NSA, 1979-2012

Sources: US Bureau of Labor Statistics

Sources: http://www.bls.gov/ppi/data.htm http://www.boj.or.jp/en/statistics/pi/cgpi_release/cgpi1202.pdf http://www.stats.gov.cn/english/pressrelease/t20120312_402791465.htm

I World Inflation Waves. This section provides analysis and data on world inflation waves. The general framework is provided in Subsection IA World Inflation Waves. Subsection IIB United States Inflation analyzes inflation in the United States in three subsections: IB1 Long-term US Inflation, IB2 Current US Inflation and IB3 Import Export Prices.

IA World Inflation Waves. The critical fact of current world financial markets is the combination of “unconventional” monetary policy with intermittent shocks of financial risk aversion. There are two interrelated unconventional monetary policies. First, unconventional monetary policy consists of (1) reducing short-term policy interest rates toward the “zero bound” such as fixing the fed funds rate at 0 to ¼ percent by decision of the Federal Open Market Committee (FOMC) since Dec 16, 2008 (http://www.federalreserve.gov/newsevents/press/monetary/20081216b.htm). Second, unconventional monetary policy also includes a battery of measures to also reduce long-term interest rates of government securities and asset-backed securities such as mortgage-backed securities.

When inflation is low, the central bank lowers interest rates to stimulate aggregate demand in the economy, which consists of consumption and investment. When inflation is subdued and unemployment high, monetary policy would lower interest rates to stimulate aggregate demand, reducing unemployment. When interest rates decline to zero, unconventional monetary policy would consist of policies such as large-scale purchases of long-term securities to lower their yields. A major portion of credit in the economy is financed with long-term asset-backed securities. Loans for purchasing houses, automobiles and other consumer products are bundled in securities that in turn are sold to investors. Corporations borrow funds for investment by issuing corporate bonds. Loans to small businesses are also financed by bundling them in long-term bonds. Securities markets bridge the needs of higher returns by savers obtaining funds from investors that are channeled to consumers and business for consumption and investment. Lowering the yields of these long-term bonds could lower costs of financing purchases of consumer durables and investment by business. The essential mechanism of transmission from lower interest rates to increases in aggregate demand is portfolio rebalancing. Withdrawal of bonds in a specific maturity segment or directly in a bond category such as currently mortgage-backed securities causes reductions in yield that are equivalent to increases in the prices of the bonds. There can be secondary increases in purchases of those bonds in private portfolios in pursuit of their increasing prices. Lower yields translate into lower costs of buying homes and consumer durables such as automobiles and also lower costs of investment for business. There are two additional intended routes of transmission.

1. Unconventional monetary policy or its expectation can increase stock market valuations (Bernanke 2010WP). Increases in equities traded in stock markets can increase the wealth of consumers inducing increases in consumption.

2. Unconventional monetary policy causes devaluation of the dollar relative to other currencies than can cause increases in net exports of the US that increase aggregate economic activity (Yellen 2011AS).

Monetary policy can lower short-term interest rates quite effectively. Lowering long-term yields is somewhat more difficult. The critical issue is that monetary policy cannot ensure that increasing credit at low interest cost increases consumption and investment. There is a large variety of possible allocation of funds at low interest rates from consumption and investment to multiple risk financial assets. Monetary policy does not control how investors will allocate asset categories. A critical financial practice is to borrow at low short-term interest rates to invest in high-risk, leveraged financial assets. Investors may increase in their portfolios asset categories such as equities, emerging market equities, high-yield bonds, currencies, commodity futures and options and multiple other risk financial assets including structured products. If there is risk appetite, the carry trade from zero interest rates to risk financial assets will consist of short positions at short-term interest rates (or borrowing) and short dollar assets with simultaneous long positions in high-risk, leveraged financial assets such as equities, commodities and high-yield bonds. Low interest rates may induce increases in valuations of risk financial assets that may fluctuate in accordance with perceptions of risk aversion by investors and the public. During periods of muted risk aversion, carry trades from zero interest rates to exposures in risk financial assets cause temporary waves of inflation that may foster instead of preventing financial stability. During periods of risk aversion such as fears of disruption of world financial markets and the global economy resulting from collapse of the European Monetary Union, carry trades are unwound with sharp deterioration of valuations of risk financial assets. More technical discussion is in IF Appendix: Transmission of Unconventional Monetary Policy at http://cmpassocregulationblog.blogspot.com/2012/01/financial-risk-aversion-and-collapse-of.html.

Table IA-1 provides annual equivalent rates of inflation for producer price indexes followed in this blog. The behavior of the US producer price index in 2011 shows neatly five waves. (1) In Jan-Apr, without risk aversion, US producer prices rose at the annual equivalent rate of 9.7 percent. (2) After risk aversion, producer prices increased in the US at the annual equivalent rate of 1.2 percent in May-Jul. (3) From Jul to Sep, under alternating episodes of risk aversion, producer prices increased at the annual equivalent rate of 6.6 percent. (4) Under the pressure of risk aversion because of the European debt crisis US producer prices were flat at the annual equivalent rate of 0.0 percent in Oct-Nov. (5) From Dec 2011 to Feb 2012, US producer prices rose at the annual equivalent rate of 1.6 percent with relaxed risk aversion and commodity-price increases at the margin. Resolution of the European debt crisis if there is not an unfavorable growth event in China would result in jumps of valuations of risk financial assets. Increases in commodity prices would cause the same high producer price inflation experienced in Jan-Apr. There are seven producer-price indexes in Table IA-1 for six countries (two for the UK) showing very similar behavior. Zero interest rates without risk aversion cause increases in commodity prices that in turn increase input and output prices. Producer price inflation rose at very high rates during the first part of the year for the US, China, Germany, France, Italy and the UK when risk aversion was contained. With the increase in risk aversion in May and Jun, inflation moderated because carry trades were unwound. Producer price inflation returned since July, with alternating bouts of risk aversion. In the final months of the year producer price inflation collapsed because of the disincentive to exposures in commodity futures resulting from fears of resolution of the European debt crisis. There is renewed worldwide inflation in the early part of 2012.

Table IA-1, Annual Equivalent Rates of Producer Price Indexes

INDEX 2011-2012	AE ∆%
US Producer Price Index
AE ∆% Dec-Feb	1.6
AE ∆% Oct-Nov	0.0
AE ∆% Jul-Sep	6.6
AE ∆% May-Jul	1.2
AE ∆% Jan-Apr	9.7
Japan Corporate Goods Price Index
AE ∆% Dec-Feb	0.4
AE ∆% Jul-Nov	2.1
AE ∆% May-Jun	-1.2
AE ∆% Jan-Apr	7.1
China Producer Price Index
AE ∆% Jan-Feb	0.0
AE ∆% Dec-Jan	-2.4
AE ∆% Jul-Nov	-3.1
AE ∆% Jan-Jun	6.4
Germany Producer Price Index
AE ∆% Dec-Jan	1.2
AE ∆% Oct-Dec	-0.4
AE ∆% Jul-Sep	2.8
AE ∆% Jun-May	0.6
AE ∆% Jan-Apr	10.3
France Producer Price Index for the French Market
AE ∆% Dec-Jan	3.0
AE ∆% Oct-Dec	2.8
AE ∆% Jul-Sep	2.4
AE ∆% May-Jun	-3.5
AE ∆% Jan-Apr	11.4
Italy Producer Price Index
AE ∆% Nov-Jan	4.1
AE ∆% Oct-Dec	0.4
AE ∆% Jul-Sep	2.4
AE ∆% Jun-May	-1.2
AE ∆% Jan-April	10.7
UK Output Prices
AE ∆% Nov-Feb	3.0
AE ∆% Oct-Dec	0.0
AE ∆% May-Dec	1.5
AE ∆% Jan-Apr	12.0
UK Input Prices
AE ∆% Nov-Feb	6.1
AE ∆% May-Dec	-3.1
AE ∆% May-Jun	-8.7
AE ∆% Jan-Apr	35.6

http://www.destatis.de/jetspeed/portal/cms/Sites/destatis/Internet/EN/Content/Statistics/TimeSeries/EconomicIndicators/KeyIndicators/ProducerPrices/liste__erzpr,templateId=renderPrint.psml

http://www.insee.fr/en/themes/info-rapide.asp?id=25&date=20120227

http://www.istat.it/it/archivio/55640

http://www.ons.gov.uk/ons/rel/ppi2/producer-price-index/february-2012/index.html

Similar world inflation waves are in the behavior of consumer price indexes of six countries and the euro zone in Table IA-2. US consumer price inflation shows five waves. (1) Under risk appetite in Jan-Apr consumer prices increased at the annual equivalent rate of 4.9 percent. (2) Risk aversion caused the collapse of inflation to annual equivalent 2.8 percent in May-Jul. (3) Risk appetite drove the rate of consumer price inflation in the US to 3.7 percent in Jul-Sep. (4) Gloomier views of carry trades caused the collapse of inflation in Oct-Dec to annual equivalent 0.4 percent. (5) Consumer price inflation resuscitated with increased risk appetite at annual equivalent of 2.4 percent in Dec 2011 to Feb 2012. There is similar behavior in all the other consumer price indexes in Table IA-2. China’s CPI increased at annual equivalent 8.3 percent in Jan-Mar, 2.0 percent in Apr-Jun, 3.0 percent in Jul-Dec and resuscitated at 11.3 percent annual equivalent in Dec 2011 to Jan 2012. The euro zone harmonized index of consumer prices (HICP) increased at annual equivalent 5.2 percent in Jan-Apr, minus 2.4 percent in May-Jul and 3.9 percent in Aug-Dec. The price indexes of the largest members of the euro zone, Germany, France and Italy, exhibit the same inflation waves. The United Kingdom CPI increased at annual equivalent 6.5 percent in Jan-Apr, falling to only 0.4 percent in May-Jul and then increasing at 4.7 percent in Aug-Dec. UK consumer prices increased at 0.6 percent annual equivalent from Dec 2011 to Jan 2012.

Table IA-2, Annual Equivalent Rates of Consumer Price Indexes

Index 2011-2012	AE ∆%
US Consumer Price Index
AE ∆% Dec-Feb	2.4
AE ∆% Oct-Dec	0.4
AE ∆% Jul-Sep	3.7
AE ∆% May-Jul	2.8
AE ∆% Jan-Apr	4.9
China Consumer Price Index
AE ∆% Feb	-1.2
AE ∆% Dec-Jan	11.3
AE ∆% Jul-Dec	2.9
AE ∆% Apr-Jun	2.0
AE ∆% Jan-Mar	8.3
Euro Zone Harmonized Index of Consumer Prices
AE ∆% Dec-Feb	0.0
AE ∆% Aug-Dec	3.9
AE ∆% May-Jul	-2.4
AE ∆% Jan-Apr	5.2
Germany Consumer Price Index
AE ∆% Dec-Feb	4.1
AE ∆% Jul-Dec	2.4
AE ∆% May-Jun	0.6
AE ∆% Feb-Apr	4.9
France Consumer Price Index
AE ∆% Dec-Feb	1.6
AE ∆% Aug-Dec	3.0
AE ∆% May-Jul	-1.2
AE ∆% Jan-Apr	4.3
Italy Consumer Price Index
AE ∆% Dec-Feb	4.5
AE ∆% Oct-Jan	3.7
AE ∆% May-Jun	1.2
AE ∆% Jan-Apr	4.9
UK Consumer Price Index
AE ∆% Dec-Jan	0.6
AE ∆% Aug-Dec	4.7
AE ∆% May-Jul	0.4
AE ∆% Jan-Apr	6.5

Sources: http://www.bls.gov/cpi/data.htm http://www.stats.gov.cn/english/pressrelease/t20120309_402791303.htm http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-14032012-BP/EN/2-14032012-BP-EN.PDF

http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home

http://www.destatis.de/jetspeed/portal/cms/Sites/destatis/Internet/EN/press/pr/2012/03/PE12__085__611,templateId=renderPrint.psml

http://www.insee.fr/en/themes/info-rapide.asp?id=29&date=20120313

http://www.istat.it/it/archivio/56476

http://www.ons.gov.uk/ons/rel/cpi/consumer-price-indices/january-2012/index.html

IIB United States Inflation. Monetary policy pursues symmetric inflation targets of maintaining core inflation of the index of personal consumption expenditures (core PCE) in an open interval of 2.00 percent. If inflation increases above 2.00 percent, the central bank could use restrictive monetary policy such as increases in interest rates to contain inflation in a tight range or interval around 2.00 percent. If inflation falls below 2 percent, the central bank could use restrictive monetary policy such as lowering interest rates to prevent inflation from falling too much below 2.00 percent. Currently, with about thirty million unemployed and underemployed, there may even be a policy bias to raise or at least ignore inflation, maintaining accommodation as a form of promoting full employment. There are two arguments in favor of symmetric inflation targets preventing inflation from falling to very low levels.

3. Room for interest rate policy. Nominal interest rates hardly ever fall below zero. In economic jargon, the floor of zero nominal interest rates is referred to as “the zero bound.” Symmetric targets are proposed to maintain a sufficiently high inflation rate such that interest rates can be lowered to promote economic activity when recession threatens. With inflation close to zero there is no room for lowering interest rates with policy tools.

4. Fear of Deflation. Inflation is a process of sustained increases in prices. Deflation is a process of sustained decreases in prices. The probability of deflation increases as inflation approximates zero. The influence of fear of deflation in monetary policy is discussed in Pelaez and Pelaez (International Financial Architecture (2005), 18-28, The Global Recession Risk (2007), 83-95).

Subsection IIB1 Long-term US Inflation evaluates long-term inflation in the US, concluding that there has not been deflation risk since World War II. Subsection IIB2 Current US Inflation finds no evidence in current inflation justifying fear of deflation. Subsection IIB3 Import Export Prices analyzes inflation in US international trade.

IIB1 Long-term US Inflation. Key percentage average yearly rates of the US economy on growth and inflation are provided in Table IB-1 updated with release of new data. The choice of dates prevents the measurement of long-term potential economic growth because of two recessions from IQ2001 (Mar) to IVQ2001 (Nov) with decline of GDP of 0.4 percent and the drop in GDP of 5.1 percent in IVQ2007 (Dec) to IIQ2009 (June) (http://www.nber.org/cycles.html) followed with unusually low economic growth for an expansion phase after recession with the economy growing at 1.6 percent IVQ2011 relative to IVQ2010 (http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html). Between 2000 and 2011, real GDP grew at the average rate of 1.6 percent per year, nominal GDP at 3.9 percent and the implicit deflator at 2.3 percent. Between 2000 and 2012, the average rate of CPI inflation was 2.5 percent per year and 2.0 percent excluding food and energy. PPI inflation increased at 2.8 percent per year on average and at 1.6 percent excluding food and energy. There is also inflation in international trade. Import prices grew at 2.8 percent per year between 2000 and 2011 and at 3.0 percent between 2000 and 2012. The commodity price shock is revealed by inflation of import prices of petroleum increasing at 11.8 percent per year between 2000 and 2011 and at 12.4 percent between 2000 and 2012. The average growth rates of import prices excluding fuels are much lower at 1.3 percent for 2002 to 2011 and also 1.3 percent for 2000 to 2012. Export prices rose at the average rate of 2.5 percent between 2000 and 2011 and at 2.4 percent from 2000 to 2012. What spared the US of sharper decade-long deterioration of the terms of trade, (export prices)/(import prices), was its diversification and competitiveness in agriculture. Agricultural export prices grew at the average yearly rate of 7.2 percent from 2000 to 2011 and at 6.0 percent from 2000 to 2012. US nonagricultural export prices rose at 2.1 percent per year from 2000 to 2011 and also at 2.1 percent from 2000 to 2012. These dynamic growth rates are not similar to those for the economy of Japan where inflation was negative in seven of the 10 years in the 2000s.

Table IB-1, US, Average Growth Rates of Real and Nominal GDP, Consumer Price Index, Producer Price Index and Import and Export Prices, Percent per Year

Real GDP	2000-2011: 1.6%
Nominal GDP	2000-2011: 3.9%
Implicit Price Deflator	2000-2011: 2.3%
CPI	2000-2011: 2.4% 2000-2012: 2.5%
CPI ex Food and Energy	2000-2011: 2.0% 2000-2012: 2.0%
PPI	2000-2011: 2.8% 2000-2012: 2.8%
PPI ex Food and Energy	2000-2011: 1.4% 2000-2012: 1.6%
Import Prices	2000-2011: 2.8% 2000-2012: 3.0%
Import Prices of Petroleum and Petroleum Products	2000-2011: 11.8% 2000-2012: 12.4%
Import Prices Excluding Petroleum	2000-2011: 1.3% 2000-2012: 1.3%
Import Prices Excluding Fuels	2002-2011: 1.9% 2002-2012: 1.9%
Export Prices	2000-2011: 2.5% 2000-2012: 2.4%
Agricultural Export Prices	2000-2011: 7.2% 2000-2012: 6.0%
Nonagricultural Export Prices	2000-2011: 2.1% 2000-2012: 2.1%

Sources: http://www.bea.gov/iTable/index_nipa.cfm http://www.bls.gov/ppi/data.htm

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

-0.3 percent in 1963,

-1.4 percent in 1986,

-0.8 percent in 1986,

-0.8 percent in 1998,

-1.3 percent in 2001

-2.6 percent in 2009.

Chart IB-1 provides US nominal GDP from 1980 to 2010. The only major bump in the chart occurred in the recession of IVQ2007 to IIQ2009. Tendency for deflation would be reflected in persistent bumps. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.5 percent cumulatively and fell 45.6 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

Chart IB-1, US, Nominal GDP 1980-2011

Source: US Bureau of Economic Analysis

Chart IB-2 provides US real GDP from 1980 to 2011. Persistent deflation threatening real economic activity would also be reflected in the series of long-term growth of GDP. There is no such behavior in Chart II-2 except for periodic recessions in the US economy that have occurred throughout history.

Chart IB-2, US, Real GDP 1980-2011

Source: US Bureau of Economic Analysis

Deflation would also be in evidence in long-term series of prices in the form of bumps. The GDP implicit deflator series in Chart IB-3 from 1980 to 2011 shows rather dynamic behavior over time. The US economy is not plagued by deflation but by long-run inflation.

Chart IB-3, US, GDP Implicit Price Deflator 1980-2011

Source: US Bureau of Economic Analysis

Chart IB-4 provides percent change from preceding quarter in prices of GDP at seasonally-adjusted annual rates (SAAR) from 1980 to 2011. There is one case of negative change in IIQ2009. There has not been actual deflation or risk of deflation in the US that would justify unconventional monetary policy.

Chart IB-4, Percent Change from Preceding Period in Prices for GDP Seasonally Adjusted at Annual Rates 1980-2011

Source: US Bureau of Economic Analysis

Chart IB-5 provides percent change from preceding year in prices of GDP from 1980 to 2011. There was not one single year of deflation or risk of deflation in the past three decades.

Chart IB-5, Percent Change from Preceding Year in Prices for Gross Domestic Product 1980-2011

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

The producer price index of the US from 1960 to 2012 in Chart IB-6 shows various periods of more rapid or less rapid inflation but no bumps. The major event is the decline in 2008 when risk aversion because of the global recession caused the collapse of oil prices from $148/barrel to less than $80/barrel with most other commodity prices also collapsing. The event had nothing in common with explanations of deflation but rather with the concentration of risk exposures in commodities after the decline of stock market indexes. Eventually, there was a flight to government securities because of the fears of insolvency of banks caused by statements supporting proposals for withdrawal of toxic assets from bank balance sheets in the Troubled Asset Relief Program (TARP), as explained by Cochrane and Zingales (2009). The bump in 2008 with decline in 2009 is consistent with the view that zero interest rates with subdued risk aversion induce carry trades into commodity futures.

Chart IB-6, US, Producer Price Index, Finished Goods, NSA, 1960-2012

Source: US Bureau of Labor Statistics

Chart IB-7 provides 12-month percentage changes of the producer price index from 1960 to 2012. The distinguishing event in Chart II-7 is the Great Inflation of the 1970s. The shape of the two-hump Bactrian camel of the 1970s resembles the double hump from 2007 to 2012.

Chart IB-7, US, Producer Price Index, Finished Goods, 12-Month Percentage Change, NSA, 1960-2012

Source: US Bureau of Labor Statistics

The producer price index excluding food and energy from 1974 to 2012, the first historical date of availability in the dataset of the Bureau of Labor Statistics (BLS), shows similarly dynamic behavior as the overall index, as shown in Chart IB-8. There is no evidence of persistent deflation in the US PPI.

Chart IB-8, US Producer Price Index, Finished Goods Excluding Food and Energy, NSA, 1973-2012

Source: US Bureau of Labor Statistics

Chart IB-9 provides 12-month percentage rates of change of the finished goods index excluding food and energy. The dominating characteristic is the Great Inflation of the 1970s. The double hump illustrates how inflation may appear to be subdued and then returns with strength.

Chart IB-9, US Producer Price Index, Finished Goods Excluding Food and Energy, 12-Month Percentage Change, NSA, 1974-2012

Source: US Bureau of Labor Statistics

The producer price index of energy goods from 1974 to 2012 is provided in Chart IB-10. The first jump occurred during the Great Inflation of the 1970s analyzed in various comments of this blog (http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html) and in Appendix I. There is relative stability of producer prices after 1986 with another jump and decline in the late 1990s into the early 2000s. The episode of commodity price increases during a global recession in 2008 could only have occurred with interest rates dropping toward zero, which stimulated the carry trade from zero interest rates to leveraged positions in commodity futures. Commodity futures exposures were dropped in the flight to government securities after Sep 2008. Commodity future exposures were created again when risk aversion diminished around Mar 2011 after the finding that US bank balance sheets did not have the toxic assets that were mentioned in proposing TARP in Congress (see Cochrane and Zingales 2009). Fluctuations in commodity prices and other risk financial assets originate in carry trade when risk aversion ameliorates.

Chart IB-10, US, Producer Price Index, Finished Energy Goods, NSA, 1974-2012

Source: US Bureau of Labor Statistics

Chart 1B-11 shows 12-month percentage change of the producer price index of finished energy goods from 1975 to 2012. This index is only available after 1974 and captures only one of the humps of energy prices during the Great Inflation. Fluctuations in energy prices have occurred throughout history in the US but without provoking deflation. Two cases are the decline of oil prices in 2001 to 2002 that has been analyzed by Barsky and Kilian (2004) and the collapse of oil prices from over $140/barrel with shock of risk aversion to the carry trade in Sep 2008.

Chart IB-11, US, Producer Price Index, Finished Energy Goods, 12-Month Percentage Change, NSA, 1974-2012

Source: US Bureau of Labor Statistics

Chart IB-12 provides the consumer price index NSA from 1960 to 2012. The dominating characteristic is the increase in slope during the Great Inflation from the middle of the 1960s through the 1970s. There is long-term inflation in the US and no evidence of deflation risks.

Chart IB-12, US, Consumer Price Index, NSA, 1960-2012

Source: US Bureau of Labor Statistics

Chart IB-13 provides 12-month percentage changes of the consumer price index from 1960 to 2012. There are actually three waves of inflation in the second half of the 1960s, in the mid 1970s and again in the late 1970s. Inflation rates then stabilized in a range with only two episodes above 5 percent.

Chart IB-13, US, Consumer Price Index, All Items, 12- Month Percentage Change 1960-2012

Source: US Bureau of Labor Statistics

Chart IB-14 provides the consumer price index excluding food and energy from 1960 to 2012. There is long-term inflation in the US without episodes of deflation.

Chart IB-14, US, Consumer Price Index Excluding Food and Energy, NSA, 1960-2012

Source: US Bureau of Labor Statistics

Chart IB-15 provides 12-month percentage changes of the consumer price index excluding food and energy from 1960 to 2012. There are three waves of inflation in the 1970s during the Great Inflation. There is no episode of deflation.

Chart IB-15, US, Consumer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 1960-2012

Source: US Bureau of Labor Statistics

The consumer price index of housing is provided in Chart IB-16. There was also acceleration during the Great Inflation of the 1970s. The index flattens after the global recession in IVQ2007 to IIQ2009. Housing prices collapsed under the weight of construction of several times more housing than needed. Surplus housing originated in subsidies and artificially low interest rates in the shock of unconventional monetary policy in 2003 to 2004 in fear of deflation.

Chart IB-16, US, Consumer Price Index Housing, NSA, 1967-2012

Source: US Bureau of Labor Statistics

Chart IB-17 provides 12-month percentage changes of the housing CPI. The Great Inflation also had extremely high rates of housing inflation. Housing is considered as potential hedge of inflation.

Chart IB-17, US, Consumer Price Index, Housing, 12- Month Percentage Change, NSA, 1968-2012

Source: US Bureau of Labor Statistics

http://www.bls.gov/news.release/pdf/cpi.pdf

IB2 Current US Inflation. Consumer price inflation has decelerated in recent months. Table IB-2 provides 12-month and annual equivalent percentage changes for the months of Dec 2011 to Feb 2012 of the CPI and major segments. The final column provides inflation from Jan to Feb 2012. CPI inflation in the 12 months ending in Feb reached 2.9 percent, the annual equivalent rate Dec to Feb was 2.4 percent and the monthly inflation rate of 0.4 percent annualizes at 4.9 percent {[(1.004)¹² – 1]100}. These inflation rates fluctuate in accordance with inducement of risk appetite or frustration by risk aversion of carry trades from zero interest rates to commodity futures. Excluding food and energy, CPI inflation was 2.2 percent in the 12 months ending in Jan and 1.6 percent in annual equivalent in Dec-Feb. There is no deflation in the US economy that could justify further quantitative easing. Consumer food prices in the US have risen 3.9 percent in 12 months and at 1.6 percent in annual equivalent in Dec-Feb. Monetary policies stimulating carry trades of commodities that increase prices of food constitute a highly regressive tax on lower income families for whom food is a major portion of the consumption basket. Energy consumer prices increased 7.0 percent in 12 months, 8.5 percent in annual equivalent in Dec-Feb 3.2 percent in Feb (annualizing at 45.9 percent) as the carry trade from zero interest rates to commodity futures was unwound and repositioned during alternating risk aversion and risk appetite originating in the European debt crisis. For lower income families, food and energy are a major part of the family budget. Inflation is not low or threatening deflation in annual equivalent in Dec-Feb in any of the categories in Table IB-2 but simply reflecting waves of inflation originating in carry trades. An upward trend is determined by carry trades from zero interest rates to commodity futures positions with episodes of risk aversion causing fluctuations.

Table IB-2, US, Consumer Price Index Percentage Changes 12 months NSA and Annual Equivalent ∆%

	∆% 12 Months Feb 2012/Feb 2011 NSA	∆% Annual Equivalent Dec 2011 to Feb 2012 SA	∆% Feb/Jan SA
CPI All Items	2.9	2.4	0.4
CPI ex Food and Energy	2.2	1.6	0.1
Food	3.9	1.6	0.0
Food at Home	4.5	0.8	0.0
Food Away from Home	3.1	2.8	0.1
Energy	7.0	8.5	3.2
Gasoline	12.6	20.2	6.0
Fuel Oil	8.9	13.4	2.8
New Vehicles	3.0	1.6	0.6
Used Cars and Trucks	2.9	-7.3	-0.2
Medical Care Commodities	3.3	6.6	0.8
Apparel	4.2	-0.4	-0.9
Services Less Energy Services	2.2	2.0	0.1
Shelter	2.0	2.4	0.2
Transportation Services	1.6	-0.4	-0.2
Medical Care Services	3.4	2.4	0.0

Source: US Bureau of Labor Statistics

The weights of the CPI, US city average, are shown in Table IB-3. Housing has a weight of 41.460 percent. The combined weight of housing and transportation is 58.768 percent or more than one half. The combined weight of housing, transportation and food and beverages is 73.56 percent of the US CPI.

Table IB-3, US, Relative Importance, 2007-2008 Weights, of Components in the Consumer Price Index, US City Average, Dec 2010

All Items	100.000
Food and Beverages	14.792
Food	13.742
Food at home	7.816
Food away from home	5.926
Housing	41.460
Shelter	31.955
Rent of primary residence	5.925
Owners’ equivalent rent	24.905
Apparel	3.601
Transportation	17.308
Private Transportation	16.082
New vehicles	3.513
Used cars and trucks	2.055
Motor fuel	5.079
Gasoline	4.865
Medical Care	6.627
Medical care commodities	1.633
Medical care services	4.994
Recreation	6.293
Education and Communication	6.421
Other Goods and Services	3.497

Source:

US Bureau of Labor Statistics

Chart IB-18 provides the US consumer price index for housing from 2001 to 2012. Housing prices rose sharply during the decade until the bump of the global recession and increased again in 2011 with some stabilization currently. The CPI excluding housing would likely show much higher inflation. Income remaining after paying for indispensable shelter has been compressed by the commodity carry trades resulting from unconventional monetary policy.

Chart IB-18, US, Consumer Price Index, Housing, NSA, 2001-2012

Source: US Bureau of Labor Statistics

Chart IB-19 provides 12-month percentage changes of the housing CPI. Percentage changes collapsed during the global recession but have been rising into positive territory in 2011.

Chart IB-19, US, Consumer Price Index, Housing, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

There have been five waves of consumer price inflation in the US in 2011 that are illustrated in Table IB-4. The first wave occurred in Jan-Apr and was caused by the carry trade of commodity prices induced by unconventional monetary policy of zero interest rates. Cheap money at zero opportunity cost was channeled into financial risk assets, causing increases in commodity prices. The annual equivalent rate of increase of the all-items CPI in Jan-Apr was 4.9 percent and the CPI excluding food and energy increased at annual equivalent rate of 2.4 percent. The second wave occurred during the collapse of the carry trade from zero interest rates to exposures in commodity futures as a result of risk aversion in financial markets created by the sovereign debt crisis in Europe. The annual equivalent rate of increase of the all-items CPI dropped to 2.8 percent in May-Jul but the annual equivalent rate of the CPI excluding food and energy increased to 2.8 percent. In the third wave in Jul-Sep, the annual equivalent CPI rose to 3.7 percent while the core CPI fell to 2.0 percent. The fourth wave occurred in the form of decrease of the CPI all-items annual equivalent rate to 0.4 percent in Oct-Dec with the annual equivalent rate of the CPI excluding food and energy remaining at 2.0 percent. The fifth wave occurred in Dec-Feb with annual equivalent headline inflation of 2.4 percent and core inflation of 1.6 percent. The conclusion is that inflation accelerates and decelerates in unpredictable fashion that turns symmetric inflation targets in a source of destabilizing shocks to the financial system and eventually the overall economy.

Table IB-4, US, Headline and Core CPI Inflation Monthly SA and 12 Months NSA ∆%

	All Items SA Month	All Items NSA 12 month	Core SA Month	Core NSA 12 months
Feb 2012	0.4	2.9	0.1	2.2
Jan	0.2	2.9	0.2	2.3
Dec 2011	0.0	3.0	0.1	2.2
AE ∆% Dec-Feb	2.4		1.6
Nov	0.1	3.4	0.2	2.2
Oct	0.0	3.5	0.2	2.1
AE ∆% Oct-Dec	0.4		2.0
Sep	0.3	3.9	0.1	2.0
Aug	0.3	3.8	0.2	2.0
Jul	0.3	3.6	0.2	1.8
AE ∆% Jul-Sep	3.7		2.0
Jun	0.1	3.6	0.2	1.6
May	0.3	3.6	0.3	1.5
AE ∆% May-Jul	2.8		2.8
Apr	0.4	3.2	0.2	1.3
Mar	0.5	2.7	0.2	1.2
Feb	0.4	2.1	0.2	1.1
Jan	0.3	1.6	0.2	1.0
AE ∆% Jan-Apr	4.9		2.4
Dec 2010	0.4	1.5	0.1	0.8
Nov	0.2	1.1	0.1	0.8
Oct	0.3	1.2	0.0	0.6
Sep	0.1	1.1	0.0	0.8
Aug	0.2	1.1	0.1	0.9
Jul	0.2	1.2	0.1	0.9
Jun	0.0	1.1	0.1	0.9
May	-0.1	2.0	0.1	0.9
Apr	0.0	2.2	0.0	0.9
Mar	0.0	2.3	0.1	1.1
Feb	0.0	2.1	0.1	1.3
Jan	0.1	1.6	-0.1	1.6

Note: Core: excluding food and energy; AE: annual equivalent

Source: US Bureau of Labor Statistics

The behavior of the US consumer price index NSA from 2001 to 2011 is provided in Chart IB-20. Inflation in the US is very dynamic without deflation risks that would justify symmetric inflation targets. The hump in 2008 originated in the carry trade from interest rates dropping to zero into commodity futures. There is no other explanation for the increase of oil prices toward $140/barrel during the global recession. The unwinding of the carry trade with the TARP announcement of toxic assets in banks channeled cheap money into government obligations (see Cochrane and Zingales 2009).

Chart IB-20, US, Consumer Price Index, NSA, 2001-2012

Source: US Bureau of Labor Statistics

Chart IB-21 provides 12-month percentage changes of the consumer price index from 2001 to 2012. There was no deflation or threat of deflation from 2008 into 2009. Commodity prices collapsed during the panic of toxic assets in banks. When stress tests revealed US bank balance sheets in much stronger position, cheap money at zero opportunity cost exited government obligations and flowed into carry trades of risk financial assets. Increases in commodity prices drove again the all items CPI with interruptions during risk aversion originating in the sovereign debt crisis of Europe.

Chart IB-21, US, Consumer Price Index, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

The trend of increase of the consumer price index excluding food and industry in Chart IB-22 does not reveal any threat of deflation that would justify symmetric inflation targets. There are mild oscillations in a neat upward trend.

Chart IB-22, US, Consumer Price Index Excluding Food and Energy, NSA, 2001-2012

Source: US Bureau of Labor Statistics

Chart II-23 provides 12-month percentage change of the consumer price index excluding food and energy. Past-year rates of inflation fell toward 1 percent from 2001 into 2003 as a result of the recession and the decline of commodity prices beginning before the recession with declines of real oil prices. Near zero interest rates with fed funds at 1 percent between Jun 2003 and Jun 2004 stimulated carry trades of all types, including in buying homes with subprime mortgages in expectation that low interest rates forever would increase home prices permanently, creating the equity that would permit the conversion of subprime mortgages into creditworthy mortgages (Gorton 2009EFM; see http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Inflation rose and then collapsed during the unwinding of carry trades and the housing debacle of the global recession. Carry trade into 2011 gave a new impulse to CPI inflation, all items and core. Symmetric inflation targets destabilize the economy by encouraging hunts for yields that inflate and deflate financial assets.

Chart IB-23, US, Consumer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

Headline and core producer price index are in Table IB-5. The headline PPI increased 0.4 percent SA in Feb but the 12-month rate NSA fell from 4.8 in Dec to 4.1 percent in Jan and 3.3 percent in Feb. The core PPI SA increased 0.2 in Feb and rose 3.0 percent in 12 months. Analysis of annual equivalent rates of change shows five different waves. In the first wave, the absence of risk aversion from the sovereign risk crisis in Europe motivated the carry trade from zero interest rates into commodity futures that caused the average equivalent rate of 9.7 percent in the headline PPI in Jan-Apr and 4.0 percent in the core PPI. In the second wave, commodity futures prices collapsed in May with the return of risk aversion originating in the sovereign risk crisis of Europe. The annual equivalent rate of headline PPI inflation collapsed to 1.2 percent in May-Jul but the core annual equivalent inflation rate was much higher at 3.0 percent. In the third wave, headline PPI inflation resuscitated with annual equivalent at 6.6 percent in Jul-Sep and core PPI inflation at 4.1 percent. Core PPI inflation was persistent throughout 2011, jumping from annual equivalent at 2.4 percent in the first four months of 2010 to 3.0 percent in 12 months in Feb 2012 and 3.7 percent in annual equivalent rate in Dec 2011 to Feb 2012. In the fourth wave, risk aversion originating in the lack of resolution of the European debt crisis caused unwinding of carry trades with annual equivalent headline PPI inflation of 0.0 percent in Oct-Nov and minus 0.6 percent in the core annual equivalent. In the fifth wave from Dec 2011 to Feb 2012, annual equivalent inflation was 1.6 percent for the headline index but 3.7 percent for the core index excluding food and energy. It is impossible to forecast PPI inflation and its relation to CPI inflation. “Inflation surprise” by monetary policy could be proposed to climb along a downward sloping Phillips curve, resulting in higher inflation but lower unemployment (see Kydland and Prescott 1977, Barro and Gordon 1983 and past comments of this blog http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html). The architects of monetary policy would require superior inflation forecasting ability compared to forecasting naivety by everybody else. In practice, we are all naïve in forecasting inflation and other economic variables and events.

Table IB-5, US, Headline and Core PPI Inflation Monthly SA and 12 Months NSA ∆%

	Finished Goods SA Month	Finished Goods NSA 12 months	Finished Core SA Month	Finished Core NSA 12 months
Feb 2012	0.4	3.3	0.2	3.0
Jan	0.1	4.1	0.4	3.0
Dec 2011	-0.1	4.8	0.3	3.0
AE ∆% Dec-Feb	1.6		3.7
Nov	0.3	5.7	-0.1	2.9
Oct	-0.3	5.9	0.0	2.9
AE ∆% Oct-Nov	0.0		-0.6
Sep	0.9	7.0	0.3	2.8
Aug	0.2	6.6	0.2	2.7
Jul	0.5	7.1	0.5	2.7
AE ∆% Jul-Sep	6.6		4.1
Jun	0.1	6.9	0.3	2.3
May	0.1	7.1	0.2	2.1
AE ∆% May-Jul	1.2		3.0
Apr	0.7	6.6	0.3	2.3
Mar	0.5	5.6	0.3	2.0
Feb	1.1	5.4	0.2	1.8
Jan	0.8	3.6	0.5	1.6
AE ∆% Jan-Apr	9.7		4.0
Dec 2010	0.9	3.8	0.2	1.4
Nov	0.4	3.4	-0.1	1.2
Oct	0.8	4.3	-0.2	1.6
Sep	0.4	3.9	0.2	1.6
Aug	0.7	3.3	0.2	1.3
Jul	0.2	4.1	0.2	1.5
Jun	-0.2	2.7	0.1	1.1
May	-0.2	5.1	0.3	1.3
Apr	-0.1	5.4	0.1	0.9
Mar	0.5	5.9	0.2	0.9
Feb	-0.6	4.2	0.0	1.0
Jan	1.0	4.5	0.3	1.0

Note: Core: excluding food and energy; AE: annual equivalent

Source: US Bureau of Labor Statistics

The US producer price index NSA from 2001 to 2012 is shown in Chart IB-24. There are two episodes of decline of the PPI during recessions in 2001 and in 2008. Barsky and Kilian (2004) consider the 2001 episode as one in which real oil prices were declining when recession began. Recession and the fall of commodity prices instead of generalized deflation explain the behavior of US inflation in 2008.

Chart IB-24, US, Producer Price Index, NSA, 2001-2012

Source: US Bureau of Labor Statistics

Twelve-month percentage changes of the PPI NSA from 2001 to 2012 are shown in Chart IB-25. It may be possible to forecast trends a few months in the future under adaptive expectations but turning points are almost impossible to anticipate especially when related to fluctuations of commodity prices in response to risk aversion. In a sense, monetary policy has been tied to behavior of the PPI in the negative 12-month rates in 2001 to 2003 and then again in 2009 to 2010. Monetary policy following deflation fears caused by commodity price fluctuations would introduce significant volatility and risks in financial markets and eventually in consumption and investment.

Chart IB-25, US, Producer Price Index, 12-Month Percentage Change NSA, 2001-2012

Source: US Bureau of Labor Statistics

The US PPI excluding food and energy from 2001 to 2012 is shown in Chart IB-26. There is here again a smooth trend of inflation instead of prolonged deflation as in Japan.

Chart IB-26, US, Producer Price Index Excluding Food and Energy, NSA, 2001-2012

Source: US Bureau of Labor Statistics

Twelve-month percentage changes of the producer price index excluding food and energy are shown in Chart IB-27. Fluctuations replicate those in the headline PPI. There is an evident trend of increase of 12 months rates of core PPI inflation in 2011 and in the firth month of 2012.

Chart IB-27, US, Producer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

The US producer price index of energy goods from 2001 to 2012 is in Chart IB-28. There is a clear upward trend with fluctuations that would not occur under persistent deflation.

Chart IB-28, US, Producer Price Index Finished Energy Goods, NSA, 2001-2012

Source: US Bureau of Labor Statistics

Chart IB-29 provides 12-month percentage changes of the producer price index of energy goods from 2001 to 2012. The episode of declining prices of energy goods in 2001 to 2002 is related to the analysis of decline of real oil prices by Barsky and Kilian (2004). Interest rates dropping to zero during the global recession explain the rise of the PPI of energy goods toward 30 percent. Bouts of risk aversion with policy interest rates held close to zero explain the fluctuations in the 12-month rates of the PPI of energy goods in the expansion phase of the economy. Symmetric inflation targets induce significant instability in inflation and interest rates with adverse effects on financial markets and the overall economy.

Chart IB-29, US, Producer Price Index Energy Goods, 12-Month Percentage Change, NSA, 2001-2012

Source: US Bureau of Labor Statistics

Table IB-6 provides 12-month percentage changes of the CPI all items, CPI core and CPI housing from 2001 to 2011. There is no evidence in these data supporting symmetric inflation targets that would only induce greater instability in inflation, interest rates and financial markets. Unconventional monetary policy drives wide swings in allocations of positions into risk financial assets that generate instability instead of intended pursuit of prosperity without inflation. There is insufficient knowledge and imperfect tools to maintain the gap of actual relative to potential output constantly at zero while restraining inflation in an open interval of (1.99, 2.0). The impact on the overall economy and the financial system of errors of policy are magnified by large-scale policy doses of trillions of dollars of quantitative easing and zero interest rates. The US economy has been experiencing financial repression as a result of negative real rates of interest in the past few years and programmed in monetary policy statements until 2014 or, for practical purposes, forever. The essential calculus of risk/return in capital budgeting and financial allocations has been distorted.

Table IB-6, CPI All Items, CPI Core and CPI Housing, 12-Month Percentage Change, NSA 2001-2012

Feb	CPI All Items	CPI Core ex Food and Energy	CPI Housing
2012	2.9	2.2	1.8
2011	2.1	1.1	0.7
2010	2.1	1.3	-0.6
2009	0.2	1.8	1.9
2008	4.0	2.3	2.8
2007	2.4	2.7	3.3
2006	3.6	2.1	4.0
2005	3.0	2.4	3.0
2004	1.7	1.2	2.1
2003	3.0	1.7	2.6
2002	1.1	2.6	2.2
2001	3.5	2.7	4.5

Source: US Bureau of Labor Statistics

IB3 Import Export Prices. Chart IB3-1 provides prices of total US imports 2001-2012. Prices fell during the contraction of 2001. Import price inflation accelerated after unconventional monetary policy of near zero interest rates in 2003-2004 and quantitative easing by withdrawing supply with the suspension of 30-year Treasury bond auctions. Slow pace of adjusting fed funds rates from 1 percent by increments of 25 basis points in 17 consecutive meetings of the Federal Open Market Committee (FOMC) between Jun 2004 and Jun 2006 continued to give impetus to carry trades. The reduction of fed funds rates toward zero in 2008 fueled a spectacular hunt for yields that caused commodity price inflation in the middle of a global recession. After risk aversion in 2009 because of the announcement of TARP (Troubled Asset Relief Program) creating anxiety on “toxic assets” in bank balance sheets (see Cochrane and Zingales 2009), prices collapsed after unwinding carry trades. Renewed price increases returned with zero interest rates and quantitative easing. Monetary policy impulses in massive doses have driven inflation and valuation of risk financial assets in wide fluctuations over a decade.

Chart IB3-1, US, Prices of Total US Imports 2001=100, 2001-2012

Chart IB3-2 provides 12-month percentage changes of prices of total US imports from 2001 to 2012. The only plausible explanation for the wide oscillations is by the carry trade from unconventional monetary policy. Import prices jumped in 2008 during deep and protracted global recession driven by carry trades from zero interest rates to long, leveraged positions in commodity futures. Carry trades were unwound during the financial panic in the final quarter of 2008 that resulted in flight to government obligations. Import prices jumped again in 2009 with subdued risk aversion because US banks did not have unsustainable toxic assets. Import prices then fluctuated as carry trades were resumed during periods of risk appetite and unwound during risk aversion resulting from the European debt crisis

Chart IB3-2, US, Prices of Total US Imports, 12-Month Percentage Changes, 2001-2012

Chart IB3-3 provides prices of US imports from 1982 to 2012. There is no similar episode to that of the increase of commodity prices in 2008 during a protracted and deep global recession with subsequent collapse during a flight into government obligations. Trade prices have been driven by carry trades created by unconventional monetary policy in the past decade.

Chart IB3-3, US, Prices of Total US Imports, 2001=100, 1982-2012

Chart IB3-4 provides 12-month percentage changes of US total imports from 1982 to 2012. There have not been wide consecutive oscillations as the ones during the global recession of IVQ2007 to IIQ2009.

Chart IB3-4, US, Prices of Total US Imports, 12-Month Percentage Changes, 1982-2012

Chart IB3-5 provides the index of US export prices from 2001 to 2012. Import and export prices have been driven by impulses of unconventional monetary policy in massive doses. The most recent segment in Chart IIC-5 shows declining trend resulting from a combination of the world economic slowdown and the decline of commodity prices as carry trade exposures are unwound because of risk aversion to the sovereign debt crisis in Europe.

Chart IB3-5, US, Prices of Total US Exports, 2001=100, 2001-2012

Chart IB3-6 provides prices of US total exports from 1982 to 2012. The rise before the global recession from 2003 to 2008, driven by carry trades, is also unique in the series

Chart IB3-6, US, Prices of Total US Exports, 2001=100, 1982-2012

Chart IB3-7 provides 12-month percentage changes of total US exports from 1982 to 2012. The uniqueness of the oscillations around the global recession of IVQ2007 to IIQ2009 is clearly revealed.

Chart IB3-7, US, Prices of Total US Exports, 12-Month Percentage Changes, 1982-2012

Twelve-month percentage changes of US prices of exports and imports are provided in Table IB3-1. Import prices have been driven since 2003 by unconventional monetary policy of near zero interest rates influencing commodity prices according to moods of risk aversion. In a global recession without risk aversion until the panic of Sep 2008 with flight to government obligations, import prices rose 13.5 percent in the twelve months ending in Feb 2008 and fell 12.7 percent in the 12 months ending in Feb 2009 when risk aversion developed in 2008 until mid 2009. Import prices rose again sharply in 2010 by 11.3 percent and in 2011 until May in the presence of zero interest rates with relaxed mood of risk aversion. There is similar behavior of prices of imports ex fuels, exports and exports ex agricultural goods but less pronounced than for commodity-rich prices dominated by carry trades from zero interest rates.

Table IB3-1, US, Twelve-Month Percentage Rates of Change of Prices of Exports and Imports

	Imports	Imports Ex Fuels	Exports	Exports Non-Ag
Feb 2012	5.5	2.3	1.5	2.6
Feb 2011	7.6	3.8	8.7	6.3
Feb 2010	11.3	1.9	3.4	3.6
Feb 2009	-12.7	-1.2	-4.5	-3.4
Feb 2008	13.5	4.3	6.9	4.8
Feb 2007	1.2	2.5	4.9	3.8
Feb 2006	6.9	0.8	2.7	2.7
Feb 2005	6.1	2.7	3.4	4.6
Feb 2004	0.9	1.8	2.7	1.6
Feb 2003	7.5	0.5	2.3	1.6
Feb 2002	-8.3	NA	-2.9	-2.9
Feb 2001	0.2	NA	0.6	0.5

Source: http://www.bls.gov/mxp/data.htm#

Chart IB3-8 shows the US monthly import price index of all commodities excluding fuels from 2001 to 2011. All curves of nominal values follow the same behavior under the influence of unconventional monetary policy. Zero interest rates without risk aversion result in jumps of nominal values and zero interest rates while under strong risk aversion there are declines of nominal values.

Chart IB3-8, US, Import Price Index All Commodities Excluding Fuels, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IB3-9 provides 12-month percentage changes of the US import price index excluding fuels between 2001 and 2012. There is the same behavior of carry trades driving up without risk aversion and down with risk aversion prices of raw materials, commodities and food in international trade during the global recession of IVQ2007 to IIQ2009 and in previous and subsequent periods.

Chart IB3-9, US, Import Price Index All Commodities Excluding Fuels, 12-Month Percentage Changes, 2002-2012

Source: US Bureau of Labor Statistics

Chart IB3-10 provides the monthly US import price index ex petroleum from 2001 to 2012. Prices including or excluding commodities follow the same fluctuations and trends originating in impulses of unconventional monetary policy of zero interest rates.

Chart IB3-10, US, Import Price Index ex Petroleum, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IB3-11 provides the US import price index ex petroleum from 1982 to 2012. There is the same unique hump in 2008 caused by carry trades from zero interest rates to prices of commodities and raw materials.

Chart IB3-11, US, Import Price Index ex Petroleum, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

Chart IB3-12 provides 12-month percentage changes of the import price index ex petroleum from 1986 to 2012. The oscillations caused by the carry trade in increasing prices of commodities and raw materials without risk aversion and subsequently decreasing them during risk aversion are quite unique.

Chart IB3-12, US, Import Price Index ex Petroleum, 12-Month Percentage Changes, 1986-2012

Source: US Bureau of Labor Statistics

http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RCLC1&f=D

Chart IB3-13 of the US Energy Information Administration provides the price of the crude oil futures contract from 1985 to 2012. There is the same hump in 2008 as in all charts caused by the common factor of carry trades from zero interest rates to commodity futures positions with risk appetite and subsequent decline when carry trades were unwound during shocks of risk aversion.

Chart IIC-13, US, Crude Oil Futures Contract

Source: US Energy Information Administration

The price index of US imports of petroleum and petroleum products in shown in Chart IB3-14. There is similar behavior of the curves all driven by the same impulses of monetary policy.

Chart IB3-14, US, Import Price Index of Petroleum and Petroleum Products, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IB3-15 provides the price index of petroleum and petroleum products from 1982 to 2012. The rise in prices during the global recession in 2008 and the decline after the flight to government obligations is unique in the history of the series. Increases in prices of trade in petroleum and petroleum products were induced by carry trades and declines by unwinding carry trades in flight to government obligations.

Chart IB3-15, US, Import Price Index of Petroleum and Petroleum Products, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

Chart IB3-16 provides 12-month percentage changes of the price index of US imports of petroleum and petroleum products from 1982 to 2012. There were wider oscillations in this index from 1999 to 2001 (see Barsky and Killian 2004 for an explanation).

Chart IB3-16, US, Import Price Index of Petroleum and Petroleum Products, 12-Month Percentage Changes, 1982-2012

Source: US Bureau of Labor Statistics

The price index of US exports of agricultural commodities is in Chart IB3-17 from 2001 to 2012. There are similar fluctuations and trends as in all other price index originating in unconventional monetary policy repeated over a decade. The most recent segment in 2011 has declining trend in a new flight from risk resulting from the sovereign debt crisis in Europe.

Chart IB3-17, US, Exports Price Index of Agricultural Commodities, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IB3-18 provides the price index of US exports of agricultural commodities from 1982 to 2012. The increase in 2008 in the middle of deep, protracted contraction was induced by unconventional monetary policy. The decline from 2008 into 2009 was caused by unwinding carry trades in a flight to government obligations. The increase into 2011 and current pause were also induced by unconventional monetary policy in waves of increases during relaxed risk aversion and declines during unwinding of positions because of aversion to financial risk.

Chart IB3-18, US, Exports Price Index of Agricultural Commodities, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

Chart IB3-19 provides 12-month percentage changes of the index of US exports of agricultural commodities from 1986 to 2012. The wide swings in 2008, 2009 and 2011 are only explained by unconventional monetary policy inducing carry trades from zero interest rates to commodity futures and reversals during risk aversion.

Chart IB3-19, US, Exports Price Index of Agricultural Commodities, 12-Month Percentage Changes, 1986-2012

Source: US Bureau of Labor Statistics

Chart IB3-20 shows the export price index of nonagricultural commodities from 2001 to 2012. Unconventional monetary policy of zero interest rates drove price behavior during the past decade. Policy has been based on the myth of stimulating the economy by climbing the negative slope of an imaginary short-term Phillips curve.

Chart IB3-20, US, Exports Price Index of Nonagricultural Commodities, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IB3-21 provides a longer perspective of the price index of US nonagricultural commodities from 1982 to 2012. Increases and decreases around the global contraction after 2007 were caused by carry trade induced by unconventional monetary policy.

Chart IB3-21, US, Exports Price Index of Nonagricultural Commodities, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

Finally, Chart IB3-22 provides 12-month percentage changes of the price index of US exports of nonagricultural commodities from 1986 to 2012. The wide swings before, during and after the global recession beginning in 2007 were caused by carry trades induced by unconventional monetary policy.

Chart IB3-22, US, Exports Price Index of Nonagricultural Commodities, 12-Month Percentage Changes, 1986-2012

Source: US Bureau of Labor Statistics

II 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 forthcoming in the American Economic Review 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 (http://cmpassocregulationblog.blogspot.com/2012/03/thirty-million-unemployed-or.html) 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. 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. There are four subsections. IIA Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IIB 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 IIC Ten Million Fewer Full-time Jobs. IID Youth Unemployment provides the data on high unemployment of ages 16 to 24 years.

IIA 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.

An appropriate measure of job stress is considered by Blanchard and Katz (1997, 53):

“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 69.4 million in 2004 to 50.1 million in 2011 or by 17.7 million while hiring in the private sector (HP) has declined from 59.5 million in 2006 to 46.9 million in 2011 or by 12.6 million, as shown in Table II-1. The ratio of nonfarm hiring to unemployment (RNF) has fallen from 47.2 in 2005 to 38.1 in 2011 and in the private sector (RHP) from 52.1 in 2006 to 42.9 in 2011. (http://cmpassocregulationblog.blogspot.com/2011/03/slow-growth-inflation-unemployment-and.html).

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

	HNF	Rate RNF	HP	Rate HP
2001	62,948	47.8	58,825	53.1
2002	58,583	44.9	54,759	50.3
2003	56,451	43.4	53,056	48.9
2004	69,367	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	55,166	40.3	51,606	45.2
2009	46,398	35.5	43,052	39.8
2010	48,647	37.5	44,826	41.7
2011	50,083	38.1	46,869	42.9

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

Chart II-1 provides the yearly levels of total nonfarm hiring (NFH) in Table II-1. The fall of hiring during the contraction of 2007 to 2009 was much stronger than in the shallow contraction of 2001 with GDP contraction of only 0.4 percent from Mar 2001 (IQ2001) to Dec 2001 (IVQ 2001) compared with 5.1 percent contraction in the much longer recession from Dec 2007 (IVQ2007) to Jun 2009 (IIQ2009) (http://www.nber.org/cycles/cyclesmain.html). Recovery is tepid.

Chart II-1, US, Total Nonfarm Hiring (HNF), Yearly, 2001-2011

Source: US Bureau of Labor Statistics

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

Chart II-2, US, Rate Total Nonfarm Hiring (HNF), Yearly, 2001-2011

Source: US Bureau of Labor Statistics

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table II-2. There were much milder declines in 2002 of 6.2 percent and 3.4 percent in 2003 followed by strong rebounds of 6.6 percent in 2004 and 4.7 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.4 in 2007, 14.7 in 2008 and 16 percent in 2009. On a yearly basis, nonfarm hiring grew 4.1 percent in 2010 relative to 2009.

Table II-2, US, Annual Total Nonfarm Hiring (HNF), Yearly Percentage Change, 2001-2011

Year	Annual
2002	-6.9
2003	-3.6
2004	6.9
2005	4.6
2006	1.0
2007	-2.1
2008	-11.6
2009	-15.9
2010	4.8
2011	3.0

Source: US Bureau of Labor Statistics

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

Chart II-3, US, Annual Total Nonfarm Hiring (HNF), Yearly Percentage Change, 2001-2011

Source: US Bureau of Labor Statistics

Total private hiring (HP) yearly data are provided in Chart II-4. There has been sharp contraction of total private hiring in the US and only milder recovery in 2011 than in 2010.

Chart II-4, US, Total Private Hiring, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

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

Chart II-5, US, Rate Total Private Hiring, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Jan in the years from 2001 to 2012 in Table II-3. Hiring numbers are in thousands. There is some recovery in HNF from 3716 thousand (or 3.7 million) in Jan 2010 to 3801 thousand in Jan 2011 and 3993 thousand in Jan 2012 for cumulative gain of 7.5 percent. HP rose from 3448 thousand in Jan 2010 to 3542 thousand in Jan 2011 and 3668 thousand in Jan 2012 for cumulative gain of 6.4 percent. HNF has fallen from 5160 in Jan 2005 to 3993 in Jan 2012 or by 22.6 percent. HP has fallen from 4825 in Jan 2006 to 3668 in Jan 2012 or by 23.9 percent. 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 II-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 Jan	5953	4.6	5632	5.1
2002 Jan	4978	3.9	4695	4.4
2003 Jan	5076	4.0	4775	4.5
2004 Jan	4829	3.8	4563	4.3
2005 Jan	5160	4.0	4856	4.5
2006 Jan	5098	3.8	4825	4.3
2007 Jan	5142	3.8	4820	4.3
2008 Jan	4797	3.5	4505	4.0
2009 Jan	4055	3.1	3743	3.4
2010 Jan	3716	2.9	3448	3.3
2011 Jan	3801	3.0	3542	3.3
2012 Jan	3993	3.1	3668	3.4

Source: US Bureau of Labor Statistics

Chart II-6 provides total nonfarm hiring on a monthly basis from 2001 to 2012. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak in 2010 of 4418 in May. Nonfarm hiring fell again in Dec to 4188 from 4268 in Nov and to 4158 in Jan 2012, as shown in Chart II-6 with SA monthly data. The number of seasonally-adjusted hires in Sep was 4276 thousand, falling to 4158 in Jan 2012 or by 2.8 percent. The number of hires not seasonally adjusted was 4507 in Sep, falling to 3038 in Dec but increasing to 3993 in Jan 2012. The number of nonfarm hiring not seasonally adjusted fell by 34.7 percent from Aug to Dec.

Chart II-6, US, Total Nonfarm Hiring (HNF), 2001-2012 Month SA

Source: US Bureau of Labor Statistics

Similar behavior occurs in the rate of nonfarm hiring plot in Chart II-7. Recovery in early 2010 was followed by decline and stabilization at a lower level but with decrease in monthly SA estimates from 3.2 in Sep to 2.1 in Jan 2012. The rate not seasonally adjusted fell from 3.7 in Jun 2011 to 2.3 in Dec, climbing to 3.1 in Jan 2012. Rates of nonfarm hiring NSA were in the range of 2.8 (Dec) to 4.5 (Jun) in 2006.

Chart II-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2012

Source: US Bureau of Labor Statistics

There is only milder improvement in total private hiring shown in Chart II-8. Hiring private (HP) rose in 2010 followed by stability and renewed increase in 2011. The number of private hiring seasonally adjusted fell from 4002 thousand in Sep 2011 to 3889 in Dec or by 2.8 percent, falling to 3835 in Jan 2012 or decline by 4.2 relative to the level in Sep 2011. The number of private hiring not seasonally adjusted fell from 4130 in Sep 2011 to 2856 in Dec or by 30.8 percent, reaching 3668 in Jan 2012 or decline of 11.2 percent relative to Sep 2011. Companies do not hire in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 4934 in Sep 2006 to 3635 in Dec 2006 or by 26.3 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. In Jul 2006 private hiring NSA was 5555, declining to 4293 in Jul 2011 or by 22.7 percent. The conclusion is that private hiring in the US is more than 20 percent below the hiring before the global recession. The main problem in recovery of the US labor market has been the low rate of growth of 2.4 percent in the ten quarters of expansion of the economy since IIIQ2009 compared with average 6.2 percent in prior expansions from contractions (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html ). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

Chart II-8, US, Total Private Hiring Month SA 2011-2012

Source: US Bureau of Labor Statistics

Chart II-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data has not risen significantly above the peak in 2010. The rate seasonally adjusted fell from 3.6 in Sep 2011 to 3.5 in both Dec 2011 and Jan 2012. The rate not seasonally adjusted fell from 3.8 in Sep to 2.6 in Dec, increasing to 3.4 in Jan 2012. The NSA rate of private hiring fell from 4.9 in Jun 2006 to 3.6 in Jun 2009 but recovery was insufficient to only 4.1 in Jun 2011.

Chart II-9, US, Rate Total Private Hiring Month SA 2011-2011

Source: US Bureau of Labor Statistics

The JOLTS report of the Bureau of Labor Statistics also provides total nonfarm job openings (TNF JOB), TNF JOB rate and TNF LD (layoffs and discharges) shown in Table II-4 for the month of Jan from 2001 to 2012. The final column provides TNF LD for the years from 2001 to 2010. Nonfarm job openings fell from a peak of 4794 in Jan 2006 to 3638 in Jan 2012 or by 24.1 percent while the rate dropped from 3.2 to 2.5. Nonfarm layoffs and discharges (TNF LD) rose from 2476 in Jan 2005 to 3335 in Jan 2009 or by 34.7 percent. The yearly data show layoffs and discharges rising from 21.2 million in 2006 to 26.8 million in 2009 or by 26.4 percent.

Table II-4, US, Job Openings and Total Separations, Thousands NSA

	TNF JOB	TNF JOB Rate	TNF LD SA	TNF LD Year
Jan 2001	5771	3.8	3037	24499
Jan 2002	3920	2.7	2495	22922
Jan 2003	3938	2.7	2602	23294
Jan 2004	3567	2.5	2462	22802
Jan 2005	3845	2.7	2476	22185
Jan 2006	4524	3.1	2167	21157
Jan 2007	4794	3.2	2197	22142
Jan 2008	4425	3.0	2334	24166
Jan 2009	2949	2.1	3335	26783
Jan 2010	2864	2.1	2382	21784
Jan 2011	3020	2.1	2155	20718
Jan 2012	3638	2.5	2077

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

Source: US Bureau of Labor Statistics

Chart II-10 shows monthly job openings rising from the trough in 2009 to a high in the beginning of 2010. Job openings then stabilized into 2011 but have surpassed the peak of 2010 with 3107 seasonally adjusted in Jan 2012 relative to 2536 in Jan 2011 but fell from 3100 in Sep 2011 to 2925 in Nov or 5.6 percent. Job openings recovered in Dec at 3188 and 3107 in Jan 2012. The high of job openings not seasonally adjusted in 2010 was 2880 in OCT 2010 that was surpassed by 3310 in Oct 2011. The level of job openings not seasonally adjusted fell to 2582 in Nov 2011 or by 18.2 percent relative to 3156 in Sep 2011. There is here again the strong seasonality of year-end labor data. Job openings NSA fell from 4276 in Oct 2006 to 2158 in Oct 2009 or by 49.5 percent, recovering to 3310 in Oct 2011 or by 53.4 percent, which is still 22.6 percent lower in Oct 2011 relative to Oct 2006. Again, the main problem in recovery of the US labor market has been the low rate of growth of 2.4 percent in the ten quarters of expansion of the economy since IIIQ2009 compared with average 6.2 percent in prior expansions from contractions (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

Chart II-10, US Job Openings, Thousands NSA, 2001-2012

Source: US Bureau of Labor Statistics

The rate of job openings in Chart II-11 shows similar behavior. The rate seasonally adjusted rose from 2.3 percent in Jan 2011 to 2.8 percent in Dec 2011. The rate not seasonally adjusted rose from the high of 2.6 in Oct 2010 to 2.9 in Jul 2011 and 3.0 in Jan 2012. The rate of job openings NSA fell from 3.8 in Apr 2006 to 2.6 in Apr 2009, recovering insufficiently to 3.0 in Jan 2012.

Chart II-11, US, Rate of Job Openings, Thousands NSA, 2001-2012

Source: US Bureau of Labor Statistics

Total separations are shown in Chart II-12. Separations are much lower in 2012 than before the global recession.

Chart II-12, US, Total Separations, Month SA, 2001-2012

Source: US Bureau of Labor Statistics

Yearly total separations are shown in Chart II-13. Separations are much lower in 2011 than before the global recession.

Chart II-13, US, Total Separations, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

Table II-5 provides total nonfarm total separations from 2001 to 2010. Separations fell from 62.7 million in 2006 to 46.3 million in 2010 or by 16.4 million.

Table II-5, US, Total Nonfarm Total Separations, Thousands, 2001-2011

Year	Annual
2001	64765
2002	59190
2003	56487
2004	58340
2005	60733
2006	61565
2007	61162
2008	58601
2009	51527
2010	47641
2011	48242

Source: US Bureau of Labor Statistics

Monthly data of layoffs and discharges reach a peak in early 2009, as shown in Chart II-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business.

Chart II-14, US, Total Nonfarm Layoffs and Discharges, Monthly SA, 2011-2012

Source: US Bureau of Labor Statistics

Layoffs and discharges in Chart II-15 rose sharply to a peak in 2009. There was pronounced drop into 2010 and 2011.

Chart II-15, US, Total Nonfarm Layoffs and Discharges, Yearly, 2001-2011

Source: US Bureau of Labor Statistics

Table II-6 provides annual nonfarm layoffs and discharges from 2001 to 2011. Layoffs and discharges peaked at 26.8 million in 2009 and then fell to 20.7 million in 2010, by 6.1 million, or 22.8 percent.

Table II-6, US, Total Nonfarm Layoffs and Discharges, 2001-2011

Year    Annual
2001    24499
2002    22922
2003    23294
2004    22802
2005    22185
2006    21157
2007    22142
2008    24166
2009    26783
2010    21784
2011    20718

Source: US Bureau of Labor Statistics

IIB Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table II-7. The most comprehensive measure is U6 that consists of total unemployed plus total employed part time for economic reasons plus all marginally attached workers as percent of the labor force. U6 not seasonally annualized has risen from 8.2 percent in 2006 to 15.6 in Feb 2012.

Table II-7, US, Alternative Measures of Labor Underutilization %

	U1	U2	U3	U4	U5	U6
Feb 2012 NSA	4.9	5.1	8.7	9.3	10.2	15.6
Jan 2012 NSA	4.9	5.4	8.8	9.4	10.5	16.2
Dec 2011 NSA	4.8	5.0	8.3	8.8	9.8	15.2
Nov 2011 NSA	4.9	4.7	8.2	8.9	9.7	15.0
Oct 2011 NSA	5.0	4.8	8.5	9.1	10.0	15.3
Sep 2011 NSA	5.2	5.0	8.8	9.4	10.2	15.7
Jan 2011 NSA	5.6	6.2	9.8	10.4	11.4	17.3
Feb 2011	5.6	6.0	9.5	10.1	11.1	16.7
Dec 2010 NSA	5.4	5.9	9.1	9.9	10.7	16.6
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

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

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

Monthly seasonally adjusted measures of labor underutilization are provided in Table II-8. U6 climbed from 16.1 percent in Jul 2011 to 16.4 percent in Sep 2011 and then fell to 14.9 percent in Feb 2012. Unemployment is an incomplete measure of the stress in US job markets. A different calculation in this blog is provided by using the participation rate in the labor force before the global recession. This calculation shows 30.5 million in job stress of unemployment/underemployment in Feb 2012, not seasonally adjusted, corresponding to 18.9 percent of the labor force (http://cmpassocregulationblog.blogspot.com/2012/03/thirty-million-unemployed-or.html Table I-4).

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

	Feb 2012	Jan 2012	Dec 2011	Nov 2011	Oct 2011	Sep 2011	Aug 2011	Jul 2011
U1	4.8	4.9	5.0	5.0	5.1	5.3	5.3	5.3
U2	4.7	4.7	4.9	4.9	5.1	5.2	5.3	5.3
U3	8.3	8.3	8.5	8.7	8.9	9.0	9.1	9.1
U4	8.9	8.9	9.1	9.3	9.5	9.6	9.6	9.7
U5	9.8	9.9	10.0	10.2	10.4	10.5	10.6	10.7
U6	14.9	15.1	15.2	15.6	16.0	16.4	16.2	16.1

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

Chart II-16 provides U6 on a monthly basis from 2001 to 2011. There was a steep climb from 2007 into 2009 and then this measure of unemployment and underemployment stabilized at that high level but declined into Jan and Feb 2012.

Chart II-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons % LF plus all marginally attached workers as % of Labor Force, Month, SA, 2001-2011

Source: US Bureau of Labor Statistics

Chart II-17 provides the number employed part-time for economic reasons or who cannot find full-time employment. There are sharp declines at the end of 2009, 2010 and 2011.

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

Thousands, Month SA 2001-2012

Sources: US Bureau of Labor Statistics

There is strong seasonality in US labor markets around the end of the year. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.270 million in Sep 2011 to 8.119 million in Feb 2012, seasonally adjusted, or decline of 1.151 million in just three months, as shown in Table II-9. The number employed full-time increased from 112.479 million in Sep 2011 to 114.408 million in Feb 2012 or 1.929 million. 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 8.455 million in Feb 2012 or by 463.000. 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. 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 108.770 million in Jan 2010 or by 14.449 million. The number with full-time jobs in Feb 2012 is 112.587 million, which is lower by 10.6 million relative to the peak of 123.219 million in Jul 2007. There appear to be around 10 million less full-time jobs in the US than before the global recession. Growth at 2.4 percent on average in the ten quarters of expansion since IIIQ2009 compared with 6.2 percent on average in expansions from postwar cyclical contractions is the main culprit of the fractured US labor market (Table I-5 in http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html ).

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

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Feb 2012	8,119	114.408
Jan 2012	8,230	113.845
Dec 2011	8,098	113.765
Nov 2011	8,469	113.212
Oct 2011	8,790	112.841
Sep 2011	9,270	112.479
Aug 2011	8,787	112.406
Not Seasonally Adjusted
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
Feb 2011	8,749	110.731
Jan 2011	9,187	110.373
Dec 2010	9,205	111.207
Nov 2010	8,670	113.138
Oct 2010	8,408	112.342
Feb 2010	9,282	109.100
Jan 2010	9,290	108.770 (low)
Mar 2009	9,305 (high)	112.215
Feb 2009	9,170	112.947
Jan 2009	8,829	113.815
Feb 2008	5,114	119.452
Jan 2008	5,340	119.322
Jul 2007	4,516	123.219 (high)
Feb 2007	4,417	119.041
Jan 2007	4,726	119.094
Sep 2006	3,735 (low)	120.780
Feb 2006	4,403	119.041
Jan 2006	4,597	116.395

Source: US Bureau of Labor Statistics

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

Chart II-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2011

Sources: http://www.bls.gov/cps/data.htm

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 II-19 shows the sharp rise in people marginally attached to the labor force after 2007 and subsequent stabilization.

Chart II-19, US, Marginally Attached to the Labor Force, SA Month 2001-2012

Sources: US Bureau of Labor Statistics

IIC Ten Million Fewer Full-time Jobs. Chart II-20 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 2012 with fluctuations around the typical behavior of a stationary series: there is no improvement in the United States in creating full-time jobs.

Chart II-20, US, Full-time Employed, Thousands, NSA, 2001-2012

Sources: US Bureau of Labor Statistics

IID Youth Unemployment. The United States is experiencing high youth unemployment as in European economies. Table II-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. 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. 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 II-10, US, Employment Level 16-24 Years, Thousands, NSA


Year	Jan	Feb	Dec	Annual
2001	19678	19745	19547	20088
2002	18653	19074	19394	19683
2003	18811	18880	19136	19351
2004	18852	18841	19619	19630
2005	18858	18670	19733	19770
2006	19003	19182	20129	20041
2007	19407	19415	19361	19875
2008	18724	18546	18378	19202
2009	17467	17606	16615	17601
2010	16166	16412	16727	17077
2011	16512	16638	17234	17362
2012	16944	17150

Sources: US Bureau of Labor Statistics

Chart II-21 provides US employment level ages 16 to 24 years from 2002 to 2012. Employment level is sharply lower in Feb 2012 relative to the peak in 2007.

Chart II-21, US, Employment Level 16-24 Years, Thousands SA, 2002-2012

Sources: US Bureau of Labor Statistics

Table II-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. This situation may persist for many years.

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

Year	Jan	Feb	Dec	Annual
2001	2250	2258	2412	2371
2002	2754	2731	2374	2683
2003	2748	2740	2248	2746
2004	2767	2631	2294	2638
2005	2661	2787	2055	2521
2006	2366	2433	2007	2353
2007	2363	2230	2323	2342
2008	2633	2480	2928	2830
2009	3278	3457	3532	3760
2010	3983	3888	3352	3857
2011	3851	3696	3161	3634
2012	3416	3507

Sources: US Bureau of Labor Statistics

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

Chart II-22, US, Unemployment Level 16-24 Years, Thousands SA, 2002-2012

Sources: US Bureau of Labor Statistics

Table II-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 and 17.3 percent in 2011. During the seasonal peak in Jun 2011 the rate of youth unemployed was 18.1 percent compared with 10.8 percent in Jun 2007.

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

Year	Jan	Feb	Dec	Annual
2001	10.3	10.3	11.0	10.6
2002	12.9	12.5	10.9	12.0
2003	12.7	12.7	10.5	12.4
2004	12.8	12.3	10.5	11.8
2005	12.4	13.0	9.4	11.3
2006	11.1	11.3	9.1	10.5
2007	10.9	10.3	10.7	10.5
2008	12.3	11.8	13.7	12.8
2009	15.8	16.4	17.5	17.6
2010	19.8	19.2	16.7	18.4
2011	18.9	18.2	15.5	17.3
2012	16.8	17.0

Sources: US Bureau of Labor Statistics

Chart II-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 23 years from 2002 to 2012. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels during the ten quarters of expansion of the economy since IIIQ2009.

Chart II-23, US, Unemployment Rate 16-24 Years, Thousands, NSA, 2002-2012

Sources: US Bureau of Labor Statistics

Chart II-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2012. 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 claim 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 fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984 while the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 19.9 percent in Jun 2009, 20.0 percent in Jun 2010 and 18.9 percent in Jun 2011. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.4 percent on average during the first ten quarters of expansion from IIIQ2009 to IVQ2011 (see Table I-5 at http://cmpassocregulationblog.blogspot.com/2012/03/mediocre-economic-growth-flattening.html). The fractured US labor market denies an early start for young people.

Chart II-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1979-2012

Sources: US Bureau of Labor Statistics

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

IIIA Financial Risks. The past half year has been characterized by financial turbulence, attaining unusual magnitude in recent months. Table III-1, updated with every comment in this blog, provides beginning values on Fr Mar 9 and daily values throughout the week ending on Fri Mar16 of several financial assets. Section VI Valuation of Risk Financial Assets provides a set of more complete values. All data are for New York time at 5 PM. The first column provides the value on Fri Mar 2 and the percentage change in that prior week below the label of the financial risk asset. For example, the US dollar (USD) appreciated 0.5 percent to USD 1.3123/EUR in the week ending on Mar 2. The first five asset rows provide five key exchange rates versus the dollar and the percentage cumulative appreciation (positive change or no sign) or depreciation (negative change or negative sign). Positive changes constitute appreciation of the relevant exchange rate and negative changes depreciation. Financial turbulence has been dominated by reactions to the new program for Greece (see section IB in http://cmpassocregulationblog.blogspot.com/2011/07/debt-and-financial-risk-aversion-and.html), modifications and new approach adopted in the Euro Summit of Oct 26 (European Commission 2011Oct26SS, 2011Oct26MRES), doubts on the larger countries in the euro zone with sovereign risks such as Spain and Italy but expanding into possibly France and Germany, the growth standstill recession and long-term unsustainable government debt in the US, worldwide deceleration of economic growth and continuing waves of inflation. The most important current shock is that resulting from the agreement by European leaders at their meeting on Dec 9 (European Council 2911Dec9), which is analyzed in IIIC Appendix on Fiscal Compact. European leaders reached a new agreement on Jan 30 (http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/127631.pdf).

The dollar/euro rate is quoted as number of US dollars USD per one euro EUR, USD 1.3123/EUR in the first row, first column in the block for currencies in Table III-1 for Fri Mar 9, depreciating to USD 1.3158/EUR on Mon Mar 12, or by 0.3 percent. The dollar depreciated because more dollars, $1.3158, were required on Mar 12 to buy one euro than $1.3123 on Mar 9. Table III-1 defines a country’s exchange rate as number of units of domestic currency per unit of foreign currency. USD/EUR would be the definition of the exchange rate of the US and the inverse [1/(USD/EUR)] is the definition in this convention of the rate of exchange of the euro zone, EUR/USD. A convention used throughout this blog is required to maintain consistency in characterizing movements of the exchange rate in Table III-1 as appreciation and depreciation. The first row for each of the currencies shows the exchange rate at 5 PM New York time, such as USD 1.3158/EUR on Mar 12; the second row provides the cumulative percentage appreciation or depreciation of the exchange rate from the rate on the last business day of the prior week, in this case Fri Mar 9, to the last business day of the current week, in this case Fri Mar 16, such as depreciation by 0.4 percent to USD 1.3175/EUR by Mar 16; and the third row provides the percentage change from the prior business day to the current business day. For example, the USD depreciated (denoted by negative sign) by 0.4 percent from the rate of USD 1.3123/EUR on Fri Mar 9 to the rate of USD 1.3175/EUR on Fri Mar 16 {[(1.3175/1.3123) – 1]100 = 0.4%} and depreciated (denoted by negative sign) by 0.7 percent from the rate of USD 1.3084 on Thus Mar 15 to USD 1.3175/EUR on Fri Mar 16 {[(1.3175/1.3084) -1]100 = 0.7%}. Other factors constant, appreciation of the dollar relative to the euro is caused by increasing risk aversion, with rising uncertainty on European sovereign risks increasing dollar-denominated assets with sales of risk financial investments. Funds move away from higher yielding risk financial assets to the safety of dollar investments. When risk aversion declines, funds have been moving away from safe assets in dollars to risk financial assets, depreciating the dollar

Table III-I, Weekly Financial Risk Assets Mar 12 to Mar 16, 2012

Fri Mar 9, 2012

M 12

Tue 13

W 14

Thu 15

Fr 16

USD/EUR

1.3123

0.5%

1.3158

-0.3%

1.3074

0.4%

0.6%

1.3024

0.8%

0.4%

1.3084

0.3%

-0.5%

1.3175

-0.4%

-0.7%

JPY/ USD

82.47

-0.8%

82.2438

0.3%

82.9875

-0.6%

-0.9%

83.7310

-1.5%

-0.9%

83.4888

-1.2%

0.3%

83.43

-1.2%

0.1%

CHF/ USD

0.9192

-0.7%

0.9163

0.3%

0.9239

-0.5%

-0.8%

0.9308

-1.3%

-0.7%

0.9228

-0.4%

0.9%

0.9157

0.4%

0.8%

CHF/ EUR

1.2059

0.1%

1.2057

0.0%

1.2079

-0.2%

1.2123

-0.5%

-0.4%

1.2074

-0.1%

0.4%

1.2064

0.0%

0.1%

USD/ AUD

1.0575

0.9456

-1.7%

1.0518

0.9508

-0.5%

1.0535

0.9492

-0.4%

0.2%

1.0452

0.9568

-1.2%

-0.8%

1.0534

0.9493

-0.4%

0.8%

1.0591

0.9442

0.1%

0.5%

10 Year T Note

2.031

2.03

2.12

2.27

2.28

2.294

2 Year T Note

0.316

0.32

0.34

0.39

0.37

0.36

German Bond

2Y 0.16 10Y 1.79

2Y 0.15 10Y 1.76

2Y 0.18 10Y 1.82

2Y 0.25 10Y 1.95

2Y 0.28 10Y 1.97

2Y 0.33 10Y 2.05

DJIA

12922.02

-0.4%

12959.71

0.3%

13177.68

2.0

1.7%

13194.10

2.1%

0.1%

13252.76

2.6%

0.4%

13232.62

2.4%

-0.2%

DJ Global

1979.18

-1.0%

1974.20

-0.3%

2007.09

1.4%

1.7%

2007.35

1.4%

0.0%

2022.20

2.2%

0.7%

2033.09

2.7%

0.5%

DJ Asia Pacific

1299.61

-0.9%

1292.44

-0.6%

1299.10

0.0%

0.5%

1301.48

0.1%

0.2%

1306.81

0.5%

0.4%

1307.74

0.6%

0.1%

Nikkei

9929.74

1.6%

9889.86

-0.4%

9899.08

-0.3%

0.1%

10050.52

1.2%

1.5%

10123.28

1.9%

0.7%

10129.83

2.0%

0.1%

Shanghai

2439.46

-0.9%

2434.86

-0.2%

2455.79

0.7%

0.9%

2391.23

-2.0%

-2.6%

2373.77

-2.7%

-0.7%

2404.74

-1.4%

1.3%

DAX

6880.21

-0.6%

6901.35

0.3%

6995.91

1.7%

1.4%

7079.42

2.9%

1.2%

7144.45

3.8%

0.9%

7157.82

4.0%

0.2%

DJ UBS

Comm.

145.40

-1.6%

144.88

-0.4%

145.98

0.4%

0.8%

144.63

-0.5%

-0.9%

145.58

0.1%

0.7%

146.23

0.6%

0.4%

WTI $ B

107.53

0.8%

106.44

-1.0%

106.70

-0.8%

0.2%

105.65

-1.7%

-1.0%

105.42

-2.0%

-0.2%

107.26

-0.3%

1.7%

Brent $/B

126.00

1.8%

125.39

-0.5%

126.16

0.1%

0.6%

124.99

-0.8%

-0.9%

122.72

-2.6%

-1.8%

126.15

0.1%

2.8%

Gold $/OZ

1712.9

0.0%

1700.6

-0.7%

1671.9

-2.4%

-1.7%

1642.9

-4.1%

-1.7%

1658.9

-3.2%

1.0%

1651.1

-3.6%

-0.5%

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

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

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

A key development in the bailout of Greece is the approval by the Executive Board of the International Monetary Fund (IMF) on Mar 15, 2012, of a new four-year financing in the value of €28 billion to be disbursed in equal quarterly disbursements (http://www.imf.org/external/np/tr/2012/tr031512.htm). The sovereign debt crisis of Europe has moderated significantly with the elimination of immediate default of Greece.

The JPY depreciated an additional 1.2 percent during the week of Mar 16 largely because of strong new measures by the Bank of Japan. The Policy Board of the Bank of Japan decided three important measures of enhancing monetary easing at the meeting held on Feb 14, 2012 (Bank of Japan 2012EME, 2012PSG and 2012APP). First, the Bank of Japan (2012Feb14EME, 2012Feb14PSG) adopted a “price stability goal” for the “medium term” of 2 percent of the “year-on-year rate of change of the CPI” with the immediate goal of inflation of 1 percent. Japan’s CPI inflation in the 12 months ending in Dec was minus 0.2 percent. Second, the Bank of Japan (2012Feb14EME, 1-2) will conduct “virtually zero interest rate policy” by maintaining “the uncollateralized overnight call rate at around 0 to 0.1 percent.” Third, the Bank of Japan (20012Feb13EME, 2014Feb14APP) is increasing the size of its quantitative easing:

“The Bank increases the total size of the Asset Purchase Program by about 10 trillion yen, from about 55 trillion yen to about 65 trillion yen. The increase in the Program is earmarked for the purchase of Japanese government bonds. By fully implementing the Program including the additional expansion decided today, by the end of 2012, the amount outstanding of the Program will be increased by about 22 trillion yen from the current level of around 43 trillion yen.”

IIIB Appendix on Safe Haven Currencies analyzes the burden on the Japanese economy of yen appreciation. Policy rates close to zero by major central banks in the world together with quantitative easing tend to depreciate currencies. Monetary policy is an indirect form of currency intervention.

The Swiss franc appreciated 0.4 percent to USD 0.9157/USD relative to the dollar and was flat relative to the euro at CHF 1.2064/EUR. The Australian dollar appreciated to USD 1.0591/AUD by Mar 16. The AUD is considered a carry trade commodity currency.

Risk aversion is captured by flight of investors from risk financial assets to the government securities of the US and Germany. Increasing aversion is captured by decrease of the yield of the ten-year Treasury note from 2.326 percent on Oct 28 to 1.964 percent on Fri Nov 25, 2.065 on Dec 9 and collapse to 1.847 percent by Fr Dec 16. The yield of the ten-year Treasury rose from 1.81 percent on Mon Dec 19 to 2.027 percent on Fri Dec 23, falling to 1.871 percent on Fri Dec 30 and increasing to 1.957 percent on Jan 6 but falling again to 1.869 on Jan 13. More relaxed risk aversion is shown in the increase of the yield of the ten-year Treasury to 2.026 percent on Fri Jan 20 but renewed aversion with decline to 1.893 percent on Jan 27 and 1.923 on Feb 3 but increase to 1.974 on Fri Feb 10 and 2.0 percent on Fri Feb 17. As shown in Table III-1, the ten-year Treasury yield fell marginally to 1.977 on Fri Feb 24 and remained at 1.977 percent on Mar 2, increasing to 2.031 percent on Mar 9 and jumping to 2.294 percent by Mar 16. The ten-year Treasury yield is still at a level well below consumer price inflation of 2.9 percent in the 12 months ending in Jan (see section II United States Inflation). Treasury securities continue to be safe haven for investors fearing risk but with concentration in shorter maturities such as the two-year Treasury with stable low yield of 0.226 percent on Dec 16 but rising to 0.28 percent on Dec 23 and then falling to 0.239 percent on Fri Dec 30, increasing to 0.256 on Fri Jan 6 but falling to 0.225 on Jan 13. The yield of the two-year Treasury rose to 0.242 percent on Fri Jan 20 in an environment of more relaxed risk aversion but fell to 0.215 on Fri Jan 27 in another shock of aversion, standing at 0.234 on Feb 3, 0.274 on Feb 10 and rising to 0.292 on Fri Feb 17. As shown in Table III-1, the two-year Treasury yield rose to 0.307 percent on Fri Feb 24, falling to 0.274 percent on Mar 2 but increasing to 0.316 percent on Mar 9 and 0.36 percent on Mar 16. Investors are willing to sacrifice yield relative to inflation in defensive actions to avoid turbulence in valuations of risk financial assets but may be managing duration more carefully. During the financial panic of Sep 2008, funds moved away from risk exposures to government securities. The latest statement of the Federal Open Market Committee (FOMC) on March 13, 2012 does not have sufficient changes suggesting that it contributed to the rise in Treasury yields. The statement continues to consider inflation low, unemployment high and growth at a moderate pace. Because of the “slack” in the economy, the FOMC maintained the zero interest rate policy until 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20120313a.htm):

“In particular, the Committee decided today to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that economic conditions--including low rates of resource utilization and a subdued outlook for inflation over the medium run--are likely to warrant exceptionally low levels for the federal funds rate at least through late 2014.”

A similar risk aversion phenomenon occurred in Germany. Eurostat confirmed euro zone CPI inflation is at 2.7 percent for the 12 months ending in Feb 2012 (http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/2-14032012-BP/EN/2-14032012-BP-EN.PDF) but the yield of the two-year German government bond fell from 0.32 percent on Dec 9 to 0.22 percent on Dec 16, virtually equal to the yield of the two-year Treasury note of the US and settled at 0.23 percent on Fri Dec 23, collapsing to 0.14 percent on Fri Dec 30 and rising to 0.17 percent on Jan 6 and 0.15 percent on Jan 13. The yield of the two-year government bond of Germany increased to 0.21 percent in an environment of marginally more relaxed risk aversion on Jan 20 but fell to 0.19 percent on Jan 27 and 0.20 percent on Feb 3, increasing to 0.24 on Feb 10 and 0.24 percent on Fri Feb 17. As shown in Table III-1, the yield of the two-year German government bond stabilized at 0.24 percent on Fri Feb 24 and fell marginally to 0.16 percent on Fri Mar 2, remaining at 0.16 percent on Mar 9. The yield of the ten-year German government bond has also collapsed from 2.15 percent on Dec 9 to 1.85 percent on Dec 16, rising to 1.96 percent on Dec 23, falling to 1.83 percent on Dec 30, which was virtually equal to the yield of 1.871 percent of the US ten-year Treasury note. The ten-year government bond of Germany traded at 1.85 percent on Jan 6 and at 1.77 percent on Jan 13, increasing to 1.93 percent on Jan 20 but falling to 1.86 percent on Jan 27 and rising to 1.93 percent on Feb 10. As shown in Table III-1, the yield of the ten-year government bond of Germany settled at 1.92 percent on Fri Feb 17 and remained almost unchanged at 1.88 percent on Fri Feb 24, falling to 1.80 on Fri Mar 2, remaining almost unchanged at 1.79 percent on Fri Mar 9, rising to 2.05 percent on Mar 16. Safety overrides inflation-adjusted yield but there could be duration aversion. Turbulence has also affected the market for German sovereign bonds.

Equity indexes in Table III-1 increased during the week of Mar 16 with relief on the completion of the bailout of Greece but remaining perceptions of counterparty risk in euro area banks and the execution of the austerity program of Greece. Germany’s Dax jumped 4.0 percent. DJIA gained 2.4 percent in the week of Mar 16 and Dow Global increased 2.7 percent. Japan’s Nikkei Average jumped 4.9 percent in the week of Feb 17 and an additional 2.8 percent in the week of Feb 24 because of measures of enhancing monetary easing by the Bank of Japan and expectations of further intervention to weaken the JPY. The Nikkei Average gained 1.3 percent in the week of Mar 2, another 1.6 percent in the week of Mar 9 and 2.0 percent in the week of Mar 16. Dow Asia Pacific increased 0.6 percent in the week of Mar 16.

Commodities were soft during the week of Mar 9. The DJ UBS Commodities Index gained 0.6 percent. WTI lost 0.3 percent and Brent increased 0.1 percent. Gold fell 3.6 percent.

Table III-1 shows changes in valuations of risk financial assets in the week of Mar 5 to Mar 9. Valuations have been affected by the continuing impasse on the feasibility of the bailout for Greece, decisions by rating agencies and the International Swaps and Derivatives Association (ISAD). Risk aversion returned in earlier weeks because of the uncertainties on rapidly moving political development in Greece, Italy, Spain and perhaps even in France and Germany. Most currency movements in Table III-1 reflect alternating bouts of risk aversion because of continuing doubts on the success of the new agreement on Europe reached in the week of Dec 9, 2011 and the new agreement reached on Jan 30, 2012. Risk aversion is observed in foreign exchange markets with daily trading of around $4 trillion. The dollar had fluctuated in a tight range with hardly any changes but depreciated after advanced guidance by the Federal Open Market Committee (FOMC) that fed funds rates may remain at 0 to ¼ percent until the latter part of 2014 (http://www.federalreserve.gov/newsevents/press/monetary/20120125a.htm http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20120125.pdf).

Risk aversion during the week of Mar 2, 2012, was dominated by the long-term refinancing operations (LTRO) of the European Central Bank. LTROs and related principles are analyzed in subsection IIID Appendix on European Central Bank Large Scale Lender of Last Resort. First, as analyzed by David Enrich, writing on “ECB allots €529.5 billion in long-term refinancing operations,” published on Feb 29, 2012 by the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970203986604577252803223310964.html?mod=WSJ_hp_LEFTWhatsNewsCollection), the ECB provided a second round of three-year loans at 1.0 percent to about 800 banks. The earlier round provided €489 billion to more than 500 banks. Second, the ECB sets the fixed-rate for main refinancing operations at 1.00 percent and the overnight deposit facility at 0.25 percent (http://www.ecb.int/home/html/index.en.html) for negative spread of 75 basis points. That is, if a bank borrows at 1.0 percent for three years through the LTRO and deposits overnight at the ECB, it incurs negative spread of 75 basis points. An alternative allocation could be to lend for a positive spread to other banks. Richard Milne, writing on “Banks deposit record cash with ECB,” on Mar 2, 2012, published in the Financial Times (http://www.ft.com/intl/cms/s/0/9798fd36-644a-11e1-b30e-00144feabdc0.html#axzz1nxeicB6H), provides important information and analysis that banks deposited a record €776.9 billion at the ECB on Fri Mar 2 at interest receipt of 0.25 percent, just two days after receiving €529.5 billion of LTRO loans at interest cost of 1.0 percent. The main issue here is whether there is ongoing perceptions of high risks in counterparties in financial transactions that froze credit markets in 2008 (see Pelaez and Pelaez, Regulation of Banks and Finance (2009a), 57-60, 217-27, Financial Regulation after the Global Recession (2009b), 155-67).

Table III-1A provides an update of the consolidated financial statement of the Eurosystem. The balance sheet has swollen with the LTROs. Line 5 “Lending to Euro Area Credit Institutions Related to Monetary Policy” increased from €546,747 million on Dec 31, 2010, to €870,130 million on Dec 28, 2011 and €1,118,273 million on Mar 9, 2012. The sum of line 5 and line 7 (“Securities of Euro Area Residents Denominated in Euro”) has increased to €1,749,395 million in the statement of Mar 9.

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

	Dec 31, 2010	Dec 28, 2011	Mar 9, 2012
1 Gold and other Receivables	367,402	419,822	423,449
2 Claims on Non Euro Area Residents Denominated in Foreign Currency	223,995	236,826	246,978
3 Claims on Euro Area Residents Denominated in Foreign Currency	26,941	95,355	70,367
4 Claims on Non-Euro Area Residents Denominated in Euro	22,592	25,982	20,363
5 Lending to Euro Area Credit Institutions Related to Monetary Policy Operations Denominated in Euro	546,747	879,130	1,118,273
6 Other Claims on Euro Area Credit Institutions Denominated in Euro	45,654	94,989	57,880
7 Securities of Euro Area Residents Denominated in Euro	457,427	610,629	631,122
8 General Government Debt Denominated in Euro	34,954	33,928	31,176
9 Other Assets	278,719	336,574	406,174
TOTAL ASSETS	2,004, 432	2,733,235	3,023,159
Memo Items
Sum of 5 and 7	1,004,174	1,489,759	1,749,395
Capital and Reserves	78,143	81,481	83,000

Source: European Central Bank

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

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

http://www.ecb.int/press/pr/wfs/2012/html/fs120313.en.html

Professors Ricardo Caballero and Francesco Giavazzi (2012Jan15) find that the resolution of the European sovereign crisis with survival of the euro area would require success in the restructuring of Italy. That success would be assured with growth of the Italian economy. A critical problem is that the common currency prevents Italy from devaluation to parity or the exchange rate that would permit export growth to promote internal economic activity that generates fiscal revenues for primary fiscal surplus that ensure creditworthiness. Fiscal consolidation and restructuring are important but of long-term gestation. Immediate growth of the Italian economy would consolidate the resolution of the sovereign debt crisis. Caballero and Giavazzi (2012Jan15) argue that 55 percent of the exports of Italy are to countries outside the euro area such that devaluation of 15 percent would be effective in increasing export revenue. Newly available data in Table III-1B providing Italy’s trade with regions and countries supports the argument of Caballero and Giavazzi (2012Jan15). Italy’s exports to the European Monetary Union (EMU) are only 42.6 percent of the total. Exports to the non-European Union area are growing at 4.8 percent in Jan 2012 relative to Jan 2011 while those to EMU are growing at 2.9 percent.

Table III-1B, Italy, Exports and Imports by Regions and Countries, % Share and 12-Month ∆%

	Exports % Share	∆% Jan 2012/ Jan 2011	Imports % Share	Imports ∆% Jan 2012/ Jan 2011
EU	56.0	3.9	53.3	-5.4
EMU 17	42.6	2.9	43.2	-5.2
France	11.6	4.2	8.3	-3.7
Germany	13.1	7.6	15.6	-4.9
Spain	5.3	-3.6	4.5	-6.2
UK	4.7	9.1	2.7	-12.5
Non EU	44.0	4.8	46.7	0.2
Europe non EU	13.3	21.9	11.1	-2.8
USA	6.1	-19.1	3.3	15.2
China	2.7	-11.8	7.3	-15.8
OPEC	4.7	15.4	8.6	13.6
Total	100.0	4.3	100.0	-2.6

Notes: EU: European Union; EMU: European Monetary Union (euro zone)

Table III-1C provides Italy’s trade balance by regions and countries. Italy has a trade deficit of €44 million with the 17 countries of the euro zone (EMU 17). Depreciation to parity could permit greater competitiveness in improving the trade surpluses of €98 million with Europe non European Union and of €256 million with the US. There is significant rigidity in the trade deficits of €1732 million with China and €2581 million with oil exporting countries (OPEC).

Table III-1C, Italy, Trade Balance by Regions and Countries, Millions of Euro

Regions and Countries	Trade Balance Jan 2012 Millions of Euro	Trade Balance Cumulative Jan 2012 Millions of Euro
EU	756	756
EMU 17	-44	-44
France	831	831
Germany	-399	-399
Spain	326	326
UK	636	636
Non EU	-5,106	-5,106
Europe non EU	98	98
USA	256	256
China	-1,732	-1,732
OPEC	-2,581	-2,581
Total	-4,350	-4,350

Notes: EU: European Union; EMU: European Monetary Union (euro zone)

Growth rates of Italy’s trade and major products are provided in Table III-1D for the period Jan-2012 relative to Jan 2011. Growth rates are high for the total and all segments with the exception of decline of durable goods imports of 4.5 percent and decline of exports of 0.2 percent. Capital goods exports decreased 0.3 percent relative to a year earlier but imports of capital goods fell 6.6 percent and exports of intermediate products rose 4.2 percent.

Table III-1D, Italy, Exports and Imports % Share of Products in Total and ∆%

	Exports Share %	Exports ∆% Jan 2012/ Jan 2011	Imports Share %	Imports ∆% Jan 2012/ Jan 2011
Consumer Goods	28.9	5.6	25.0	0.8
Durable	5.9	-0.2	3.0	-4.5
Non Durable	23.0	6.9	22.0	1.6
Capital Goods	32.2	-0.3	20.8	-6.6
Inter- mediate Goods	34.3	4.2	34.5	-11.9
Energy	4.7	23.2	19.7	11.8
Total ex Energy	95.3	3.2	80.3	-6.6
Total	100.0	4.3	100.0	-2.6

Table III-1E provides Italy’s trade balance by product categories in Jan 2012. Italy’s trade balance excluding energy is a surplus of €1781 million in Jan 2012 but the energy trade balance is a deficit of €6132 million. Italy has significant competitiveness in contrast with some other countries with debt difficulties.

Table III-1E, Italy, Trade Balance by Product Categories, € Millions

	Jan 2012	Cumulative Jan 2012
Consumer Goods	161	161
Durable	471	471
Nondurable	-310	-310
Capital Goods	1,997	1,997
Intermediate Goods	-376	-376
Energy	-6,132	-6,132
Total ex Energy	1,781	1,781
Total	-4,350	-4,350

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

IIIB Appendix on Safe Haven Currencies. Safe-haven currencies, such as the Swiss franc (CHF) and the Japanese yen (JPY) have been under threat of appreciation but also remained relatively unchanged. A characteristic of the global recession would be struggle for maintaining competitiveness by policies of regulation, trade and devaluation (Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation War (2008c)). Appreciation of the exchange rate causes two major effects on Japan.

1. Trade. Consider an example with actual data (Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008c), 70-72). The yen traded at JPY 117.69/USD on Apr 2, 2007 and at JPY 102.77/USD on Apr 2, 2008, or appreciation of 12.7 percent. This meant that an export of JPY 10,000 to the US sold at USD 84.97 on Apr 2, 2007 [(JPY 10,000)/(USD 117.69/USD)], rising to USD 97.30 on Apr 2, 2008 [(JPY 10,000)/(JPY 102.77)]. If the goods sold by Japan were invoiced worldwide in dollars, Japanese’s companies would suffer a reduction in profit margins of 12.7 percent required to maintain the same dollar price. An export at cost of JPY 10,000 would only bring JPY 8,732 when converted at JPY 102.77 to maintain the price of USD 84.97 (USD 84.97 x JPY 102.77/USD). If profit margins were already tight, Japan would be uncompetitive and lose revenue and market share. The pain of Japan from dollar devaluation is illustrated by Table 58 in the Nov 6 comment of this blog (http://cmpassocregulationblog.blogspot.com/2011/10/slow-growth-driven-by-reducing-savings.html): The yen traded at JPY 110.19/USD on Aug 18, 2008 and at JPY 75.812/USD on Oct 28, 2011, for cumulative appreciation of 31.2 percent. Cumulative appreciation from Sep 15, 2010 (JPY 83.07/USD) to Oct 28, 2011 (JPY 75.812) was 8.7 percent. The pain of Japan from dollar devaluation continues as illustrated by Table VI-6 in Section VII Valuation of Risk Financial Assets: The yen traded at JPY 110.19/USD on Aug 18, 2008 and at JPY 78.08/USD on Dec 23, 2011, for cumulative appreciation of 29.1 percent. Cumulative appreciation from Sep 15, 2010 (JPY 83.07/USD) to Dec 23, 2011 (JPY 78.08) was 6.0 percent.

2. Foreign Earnings and Investment. Consider the case of a Japanese company receiving earnings from investment overseas. Accounting the earnings and investment in the books in Japan would also result in a loss of 12.7 percent. Accounting would show fewer yen for investment and earnings overseas.

There is a point of explosion of patience with dollar devaluation and domestic currency appreciation. Andrew Monahan, writing on “Japan intervenes on yen to cap sharp rise,” on Oct 31, 2011, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204528204577009152325076454.html?mod=WSJPRO_hpp_MIDDLETopStories), analyzes the intervention of the Bank of Japan, at request of the Ministry of Finance, on Oct 31, 2011. Traders consulted by Monahan estimate that the Bank of Japan sold JPY 7 trillion, about $92.31 billion, against the dollar, exceeding the JPY 4.5 trillion on Aug 4, 2011. The intervention caused an increase of the yen rate to JPY 79.55/USD relative to earlier trading at a low of JPY 75.31/USD. The JPY appreciated to JPY76.88/USD by Fri Nov 18 for cumulative appreciation of 3.4 percent from JPY 79.55 just after the intervention. The JPY appreciated another 0.3 percent in the week of Nov 18 but depreciated 1.1 percent in the week of Nov 25. There was mild depreciation of 0.3 percent in the week of Dec 2 that was followed by appreciation of 0.4 percent in the week of Dec 9. The JPY was virtually unchanged in the week of Dec 16 with depreciation of 0.1 percent but depreciated by 0.5 percent in the week of Dec 23, appreciating by 1.5 percent in the week of Dec 30. Historically, interventions in yen currency markets have been unsuccessful (Pelaez and Pelaez, The Global Recession Risk (2007), 107-109). Interventions are even more difficult currently with daily trading of some $4 trillion in world currency markets. Risk aversion with zero interest rates in the US diverts hot capital movements toward safe-haven currencies such as Japan, causing appreciation of the yen. Mitsuru Obe, writing on Nov 25, on “Japanese government bonds tumble,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204452104577060231493070676.html?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes the increase in yields of the Japanese government bond with 10 year maturity to a high for one month of 1.025 percent at the close of market on Nov 25. Thin markets in after-hours trading may have played an important role in this increase in yield but there may have been an effect of a dreaded reduction in positions of bonds by banks under pressure of reducing assets. The report on Japan sustainability by the IMF (2011JSRNov23, 2), analyzes how rising yields could threaten Japan:

· “As evident from recent developments, market sentiment toward sovereigns with unsustainably large fiscal imbalances can shift abruptly, with adverse effects on debt dynamics. Should JGB yields increase, they could initiate an adverse feedback loop from rising yields to deteriorating confidence, diminishing policy space, and a contracting real economy.

· Higher yields could result in a withdrawal of liquidity from global capital markets, disrupt external positions and, through contagion, put upward pressure on sovereign bond yields elsewhere.”

Exchange rate controls by the Swiss National Bank (SNB) fixing the rate at a minimum of CHF 1.20/EUR (http://www.snb.ch/en/mmr/reference/pre_20110906/source/pre_20110906.en.pdf) has prevented flight of capital into the Swiss franc. The Swiss franc remained unchanged relative to the USD in the week of Dec 23 and appreciated 0.2 percent in the week of Dec 30 relative to the USD and 0.5 percent relative to the euro, as shown in Table II-1. Risk aversion is evident in the depreciation of the Australian dollar by cumulative 2.5 percent in the week of Fr Dec 16 after no change in the week of Dec 9. In the week of Dec 23, the Australian dollar appreciated 1.9 percent, appreciating another 0.5 percent in the week of Dec 30 as shown in Table II-1. Risk appetite would be revealed by carry trades from zero interest rates in the US and Japan into high yielding currencies such as in Australia with appreciation of the Australian dollar (see Pelaez and Pelaez, Globalization and the State, Vol. II (2008b), 202-4, Pelaez and Pelaez, Government Intervention in Globalization (2008c), 70-4).

IIIC Appendix on Fiscal Compact. There are three types of actions in Europe to steer the euro zone away from the threats of fiscal and banking crises: (1) fiscal compact; (2) enhancement of stabilization tools and resources; and (3) bank capital requirements. The first two consist of agreements by the Euro Area Heads of State and government while the third one consists of measurements and recommendations by the European Banking Authority.

1. Fiscal Compact. The “fiscal compact” consists of (1) conciliation of fiscal policies and budgets within a “fiscal rule”; and (2) establishment of mechanisms of governance, monitoring and enforcement of the fiscal rule.

i. Fiscal Rule. The essence of the fiscal rule is that “general government budgets shall be balanced or in surplus” by compliance of members countries that “the annual structural deficit does not exceed 0.5% of nominal GDP” (European Council 2011Dec9, 3). Individual member states will create “an automatic correction mechanism that shall be triggered in the event of deviation” (European Council 2011Dec9, 3). Member states will define their automatic correction mechanisms following principles proposed by the European Commission. Those member states falling into an “excessive deficit procedure” will provide a detailed plan of structural reforms to correct excessive deficits. The European Council and European Commission will monitor yearly budget plans for consistency with adjustment of excessive deficits. Member states will report in anticipation their debt issuance plans. Deficits in excess of 3 percent of GDP and/or debt in excess of 60 percent of GDP will trigger automatic consequences.

ii. Policy Coordination and Governance. The euro area is committed to following common economic policy. In accordance, “a procedure will be established to ensure that all major economic policy reforms planned by euro area member states will be discussed and coordinated at the level of the euro area, with a view to benchmarking best practices” (European Council 2011Dec9, 5). Governance of the euro area will be strengthened with regular euro summits at least twice yearly.

2. Stabilization Tools and Resources. There are several enhancements to the bailouts of member states.

i. Facilities. The European Financial Stability Facility (EFSF) will use leverage and the European Central Bank as agent of its market operations. The European Stability Mechanism (ESM) or permanent bailout facility will be operational as soon as 90 percent of the capital commitments are ratified by member states. The ESM is planned to begin in Jul 2012.

ii. Financial Resources. The overall ceiling of the EFSF/ESM of €500 billion (USD 670 billion) will be reassessed in Mar 2012. Measures will be taken to maintain “the combined effective lending capacity of EUR 500 billion” (European Council 2011Dec9, 6). Member states will “consider, and confirm within 10 days, the provision of additional resources for the IMF of up to EUR 200 billion (USD 270 billion), in the form of bilateral loans, to ensure that the IMF has adequate resources to deal with the crisis. We are looking forward to parallel contributions from the international community” (European Council 2011Dec9, 6). Matthew Dalton and Matina Stevis, writing on Dec 20, 2011, on “Euro Zone Agrees to New IMF Loans,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204791104577107974167166272.html?mod=WSJPRO_hps_MIDDLESecondNews), inform that at a meeting on Dec 20, finance ministers of the euro-zone developed plans to contribute €150 billion in bilateral loans to the IMF as provided in the agreement of Dec 9. Bailouts “will strictly adhere to the well established IMF principles and practices.” There is a specific statement on private sector involvement and its relation to recent experience: “We clearly reaffirm that the decisions taken on 21 July and 26/27 October concerning Greek debt are unique and exceptional; standardized and identical Collective Action clauses will be included, in such a way as to preserve market liquidity, in the terms and conditions of all new euro government bonds” (European Council 2011Dec9, 6). Will there be again “unique and exceptional” conditions? The ESM is authorized to take emergency decisions with “a qualified majority of 85% in case the Commission and the ECB conclude that an urgent decision related to financial assistance is needed when the financial and economic sustainability of the euro area is threatened” (European Council 2011Dec9, 6).

3. Bank Capital. The European Banking Authority (EBA) finds that European banks have a capital shortfall of €114.7 billion (http://stress-test.eba.europa.eu/capitalexercise/Press%20release%20FINAL.pdf). To avoid credit difficulties, the EBA recommends “that the credit institutions build a temporary capital buffer to reach a 9% Core Tier 1 ratio by 30 June 2012” (http://stress-test.eba.europa.eu/capitalexercise/EBA%20BS%202011%20173%20Recommendation%20FINAL.pdf 6). Patrick Jenkins, Martin Stabe and Stanley Pignal, writing on Dec 9, 2011, on “EU banks slash sovereign holdings,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/a6d2fd4e-228f-11e1-acdc-00144feabdc0.html#axzz1gAlaswcW), analyze the balance sheets of European banks released by the European Banking Authority. They conclude that European banks have reduced their holdings of riskier sovereign debt of countries in Europe by €65 billion from the end of 2010 to Sep 2011. Bankers informed that the European Central Bank and hedge funds acquired those exposures that represent 13 percent of their holdings of debt to Greece, Ireland, Italy, Portugal and Spain, which are down to €513 billion by the end of IIIQ2011.

IIID Appendix on European Central Bank Large Scale Lender of Last Resort. European Central Bank. The European Central Bank (ECB) has been pressured to assist in the bailouts by acquiring sovereign debts. The ECB has been providing liquidity lines to banks under pressure and has acquired sovereign debts but not in the scale desired by authorities. In an important statement to the European Parliament, the President of the ECB Mario Draghi (2011Dec1) opened the possibility of further ECB actions but after a decisive “fiscal compact:”

“What I believe our economic and monetary union needs is a new fiscal compact – a fundamental restatement of the fiscal rules together with the mutual fiscal commitments that euro area governments have made.

Just as we effectively have a compact that describes the essence of monetary policy – an independent central bank with a single objective of maintaining price stability – so a fiscal compact would enshrine the essence of fiscal rules and the government commitments taken so far, and ensure that the latter become fully credible, individually and collectively.

We might be asked whether a new fiscal compact would be enough to stabilise markets and how a credible longer-term vision can be helpful in the short term. Our answer is that it is definitely the most important element to start restoring credibility.

Other elements might follow, but the sequencing matters. And it is first and foremost important to get a commonly shared fiscal compact right. Confidence works backwards: if there is an anchor in the long term, it is easier to maintain trust in the short term. After all, investors are themselves often taking decisions with a long time horizon, especially with regard to government bonds.

A new fiscal compact would be the most important signal from euro area governments for embarking on a path of comprehensive deepening of economic integration. It would also present a clear trajectory for the future evolution of the euro area, thus framing expectations.”

An important statement of Draghi (2011Dec15) focuses on the role of central banking: “You all know that the statutes of the ECB inherited this important principle and that central bank independence and the credible pursuit of price stability go hand in hand.”

Draghi (2011Dec19) explains measures to ensure “access to funding markets” by euro zone banks:

§ “We have decided on three-year refinancing operations to support the supply of credit to the euro area economy. These measures address the risk that persistent financial markets tensions could affect the capacity of euro area banks to obtain refinancing over longer horizons.

§ Earlier, in October, the Governing Council had already decided to have two more refinancing operations with a maturity of around one year.

§ Also, it was announced then that in all refinancing operations until at least the first half of 2012 all liquidity demand by banks would be fully allotted at fixed rate.

§ Funding via the covered bonds market was also facilitated by the ECB deciding in October to introduce a new Covered Bond Purchase Programme of €40 billion.

§ Funding in US dollar is facilitated by lowering the pricing on the temporary US dollar liquidity swap arrangements.”

Lionel Barber and Ralph Atkins interviewed Mario Draghi on Dec 14 with the transcript published in the Financial Times on Dec 18 (http://www.ft.com/intl/cms/s/0/25d553ec-2972-11e1-a066-00144feabdc0.html#axzz1gzoHXOj6) as “FT interview transcript: Mario Draghi.” A critical question in the interview is if the new measures are a European version of quantitative easing. Draghi analyzes the difference between the measures of the European Central Bank (ECB) and quantitative easing such as in Japan, US and UK:

1. The measures are termed “non-standard” instead of “unconventional.” While quantitative easing attempts to lower the yield of targeted maturities, the three-year facility operates through the “bank channel.” Quantitative easing would not be feasible because the ECB is statutorily prohibited of funding central governments. The ECB would comply with its mandate of medium-term price stability.

2. There is a critical difference in the two programs. Quantitative easing has been used as a form of financial repression known as “directed lending.” For example, the purchase of mortgage-backed securities more recently or the suspension of the auctions of 30-year bonds in response to the contraction early in the 2000s has the clear objective of directing spending to housing. The ECB gives the banks entire discretion on how to use the funding within their risk/return decisions, which could include purchase of government bonds.

The question on the similarity of the ECB three-year lending facility and quantitative easing is quite valid. Tracy Alloway, writing on Oct 10, 2011, on “Investors worry over cheap ECB money side effects,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/d2f87d16-f339-11e0-8383-00144feab49a.html#axzz1hAqMH1vn), analyzes the use of earlier long-term refinancing operations (LTRO) of the ECB. LTROs by the ECB in Jun, Sep and Dec 2009 lent €614 billion at 1 percent. Alloway quotes estimates of Deutsche Bank that banks used €442billion to acquire assets with higher yields. Carry trades developed from LTRO funds at 1 percent into liquid investments at a higher yield to earn highly profitable spreads. Alloway quotes estimates of Morgan Stanley that European debt of GIIPS (Greece, Ireland, Italy, Portugal and Spain) in European bank balance sheets is €700 billion. Tracy Alloway, writing on Dec 21, 2011, on “Demand for ECB loans rises to €489bn,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/d6ddd0ae-2bbd-11e1-98bc-00144feabdc0.html#axzz1hAqMH1vn), informs that European banks borrowed the largest value of €489 billion in all LTROs of the ECB. Tom Fairless and David Cottle, writing on Dec 21, 2011, on “ECB sees record refinancing demand,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204464404577111983838592746.html?mod=WSJPRO_hpp_LEFTTopStories), inform that the first of three operations of the ECB lent €489.19 billion, or $639.96 billion, to 523 banks. Three such LTROs could add to $1.9 trillion, which is not far from the value of quantitative easing in the US of $2.5 trillion. Fairless and Cottle find that there could be renewed hopes that banks could use the LTROs to support euro zone bond markets. It is possible that there could be official moral suasion by governments on banks to increase their holdings of government bonds or at least not to sell existing holdings. Banks are not free to choose assets in evaluation of risk and returns. Floods of cheap money at 1 percent per year induce carry trades to high-risk assets and not necessarily financing of growth with borrowing and lending decisions constrained by shocks of confidence.

The LTROs of the ECB are not very different from the liquidity facilities of the Fed during the financial crisis. Kohn (2009Sep10) finds that the trillions of dollars in facilities provided by the Fed (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-64, Regulation of Banks and Finance (2009b), 224-7) could fall under normal principles of “lender of last resort” of central banks:

“The liquidity measures we took during the financial crisis, although unprecedented in their details, were generally consistent with Bagehot's principles and aimed at short-circuiting these feedback loops. The Federal Reserve lends only against collateral that meets specific quality requirements, and it applies haircuts where appropriate. Beyond the collateral, in many cases we also have recourse to the borrowing institution for repayment. In the case of the TALF, we are backstopped by the Treasury. In addition, the terms and conditions of most of our facilities are designed to be unattractive under normal market conditions, thus preserving borrowers' incentives to obtain funds in the market when markets are operating normally. Apart from a very small number of exceptions involving systemically important institutions, such features have limited the extent to which the Federal Reserve has taken on credit risk, and the overall credit risk involved in our lending during the crisis has been small.

In Ricardo's view, if the collateral had really been good, private institutions would have lent against it. However, as has been recognized since Bagehot, private lenders, acting to protect themselves, typically severely curtail lending during a financial crisis, irrespective of the quality of the available collateral.The central bank--because it is not liquidity constrained and has the infrastructure in place to make loans against a variety of collateral--is well positioned to make those loans in the interest of financial stability, and can make them without taking on significant credit risk, as long as its lending is secured by sound collateral. A key function of the central bank is to lend in such circumstances to contain the crisis and mitigate its effects on the economy.”

The Bagehot (1873) principle is that central banks should provide a safety net, lending to temporarily illiquid but solvent banks and not to insolvent banks (see Cline 2001, 2002; Pelaez and Pelaez, International Financial Architecture (2005), 175-8). Kohn (2009Apr18) characterizes “quantitative easing” as “large scale purchases of assets:”

“Another aspect of our efforts to affect financial conditions has been the extension of our open market operations to large-scale purchases of agency mortgage-backed securities (MBS), agency debt, and longer-term Treasury debt. We initially announced our intention to undertake large-scale asset purchases last November, when the federal funds rate began to approach its zero lower bound and we needed to begin applying stimulus through other channels as the economic contraction deepened. These purchases are intended to reduce intermediate- and longer-term interest rates on mortgages and other credit to households and businesses; those rates influence decisions about investments in long-lived assets like houses, consumer durable goods, and business capital. In ordinary circumstances, the typically quite modest volume of central bank purchases and sales of such assets has only small and temporary effects on their yields. However, the extremely large volume of purchases now underway does appear to have substantially lowered yields. The decline in yields reflects "preferred habitat" behavior, meaning that there is not perfect arbitrage between the yields on longer-term assets and current and expected short-term interest rates. These preferences are likely to be especially strong in current circumstances, so that long-term asset prices rise and yields fall as the Federal Reserve acquires a significant portion of the outstanding stock of securities held by the public.”

Non-standard ECB policy and unconventional Fed policy have a common link in the scale of implementation or policy doses. Direct lending by the central bank to banks is the function “large scale lender of last resort.” If there is moral suasion by governments to coerce banks into increasing their holdings of government bonds, the correct term would be financial repression.

An important additional measure discussed by Draghi (2011Nov19) is relaxation on the collateral pledged by banks in LTROs:

“Some banks’ access to refinancing operations may be restricted by lack of eligible collateral. To overcome this, a temporary expansion of the list of collateral has been decided. Furthermore, the ECB intends to enhance the use of bank loans as collateral in Eurosystem operations. These measures should support bank lending, by increasing the amount of assets on euro area banks’ balance sheets that can be used to obtain central bank refinancing.”

There are collateral concerns about European banks. David Enrich and Sara Schaefer Muñoz, writing on Dec 28, on “European bank worry: collateral,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970203899504577126430202451796.html?mod=WSJPRO_hpp_LEFTTopStories), analyze the strain on bank funding from a squeeze in the availability of high-quality collateral as guarantee in funding. High-quality collateral includes government bonds and investment-grade non-government debt. There could be difficulties in funding for a bank without sufficient available high-quality collateral to offer in guarantee of loans. It is difficult to assess from bank balance sheets the availability of sufficient collateral to support bank funding requirements. There has been erosion in the quality of collateral as a result of the debt crisis and further erosion could occur. Perceptions of counterparty risk among financial institutions worsened the credit/dollar crisis of 2007 to 2009. The banking theory of Diamond and Rajan (2000, 2001a, 2001b) and the model of Diamond Dybvig (1983, 1986) provide the analysis of bank functions that explains the credit crisis of 2007 to 2008 (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 155-7, 48-52, Regulation of Banks and Finance (2009b), 52-66, 217-24). In fact, Rajan (2005, 339-41) anticipated the role of low interest rates in causing a hunt for yields in multiple financial markets from hedge funds to emerging markets and that low interest rates foster illiquidity. Rajan (2005, 341) argued:

“The point, therefore, is that common factors such as low interest rates—potentially caused by accommodative monetary policy—can engender excessive tolerance for risk on both sides of financial transactions.”

A critical function of banks consists of providing transformation services that convert illiquid risky loans and investment that the bank monitors into immediate liquidity such as unmonitored demand deposits. Credit in financial markets consists of the transformation of asset-backed securities (SRP) constructed with monitoring by financial institutions into unmonitored immediate liquidity by sale and repurchase agreements (SRP). In the financial crisis financial institutions distrusted the quality of their own balance sheets and those of their counterparties in SRPs. The financing counterparty distrusted that the financed counterparty would not repurchase the assets pledged in the SRP that could collapse in value below the financing provided. A critical problem was the unwillingness of banks to lend to each other in unsecured short-term loans. Emse Bartha, writing on Dec 28, on “Deposits at ECB hit high,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204720204577125913779446088.html?mod=WSJ_hp_LEFTWhatsNewsCollection), informs that banks deposited €453.034 billion, or $589.72 billion, at the ECB on Dec 28, which is a record high in two consecutive days. The deposit facility is typically used by banks when they do prefer not to extend unsecured loans to other banks. In addition, banks borrowed €6.225 billion from the overnight facility on Dec 28, when in normal times only a few hundred million euro are borrowed. The collateral issues and the possible increase in counterparty risk occurred a week after large-scale lender of last resort by the ECB in the value of €489 billion in the prior week. The ECB may need to extend its lender of last resort operations.

The financial reform of the United States around the proposal of a national bank by Alexander Hamilton (1780) to develop the money economy with specialization away from the barter economy is credited with creating the financial system that brought prosperity over a long period (see Pelaez 2008). Continuing growth and prosperity together with sound financial management earned the US dollar the role as reserve currency and the AAA rating of its Treasury securities. McKinnon (2011Dec18) analyzes the resolution of the European debt crisis by comparison with the reform of Alexander Hamilton. Northern states of the US had financed the revolutionary war with the issue of paper notes that were at risk of default by 1890. Alexander Hamilton proposed the purchase of the states’ paper notes by the Federal government without haircuts. McKinnon (2011Dec18) describes the conflicts before passing the assumption bill in 1790 for federal absorption of the debts of states. Other elements in the Hamilton reform consisted of creation of a market for US Treasury bonds by their use as paid-in capital in the First Bank of the United States. McKinnon (2011Dec18) finds growth of intermediation in the US by the branching of the First Bank of the United States throughout several states, accepting deposits to provide commercial short-term credit. The reform consolidated the union of states, fiscal credibility for the union and financial intermediation required for growth. The reform also introduced low tariffs and an excise tax on whisky to service the interest on the federal debt. Trade relations among members of the euro zone are highly important to economic activity. There are two lessons drawn by McKinnon (2011Dec18) from the experience of Hamilton for the euro zone currently. (1) The reform of Hamilton included new taxes for the assumption of debts of states with concrete provisions for their credibility. (2) Commercial lending was consolidated with a trusted bank both for accepting private deposits and for commercial lending, creating the structure of financial intermediation required for growth.

IIIE Appendix Euro Zone Survival Risk. Markets have been dominated by rating actions of Standard & Poor’s Ratings Services (S&PRS) (2012Jan13) on 16 members of the European Monetary Union (EMU) or eurozone. The actions by S&PRS (2012Jan13) are of several types:

1. Downgrades by two notches of long-term credit ratings of Cyprus (from BBB/Watch/NegA-3+ to BB+/Neg/B), Italy (from A/Watch Neg/A-1 to BBB+/Neg/A-2), Portugal (from BBB-/Watch Neg/A-3 to BB/Neg/B) and Spain (from AA-/Watch Neg/A-1+ to A/Neg/A-1).

2. Downgrades by one notch of long-term credit ratings of Austria (from AAA/Watch Neg/A-1+ to AA+/Neg/A-1+), France (from AAA/Watch Neg/A-1+ to AA+/Neg A-1+), Malta (from A/Watch, Neg/A-1 to A-/Neg/A-2), Slovakia (from A+/Watch Neg/A-1 to A/Stable/A-1) and Slovenia (AA-/Watch Neg/A-1+ to A+/Neg/A-1).

3. Affirmation of long-term ratings of Belgium (AA/Neg/A-1+), Estonia (AA-/Neg/A-1+), Finland (AAA/Neg/A-1+), Germany (AAA/Stable/A-1+), Ireland (BBB+/Neg/A-2), Luxembourg (AAA/Neg/A-1+) and the Netherlands (AAA/Neg/A-1+) with removal from CreditWatch.

4. Negative outlook on the long-term credit ratings of Austria, Belgium, Cyprus, Estonia, Finland, France, Ireland, Italy, Luxembourg, Malta, the Netherlands, Portugal, Slovenia and Spain, meaning that S&PRS (2012Jan13) finds that the ratings of these sovereigns have a chance of at least 1-to-3 of downgrades in 2012 or 2013.

S&PRS (2012Jan13) finds that measures by European policymakers may not be sufficient to contain sovereign risks in the eurozone. The sources of stress according to S&PRS (2012Jan13) are:

1. Worsening credit environment

2. Increases in risk premiums for many eurozone borrowers

3. Simultaneous attempts at reducing debts by both eurozone governments and households

4. More limited perspectives of economic growth

5. Deepening and protracted division among Europe’s policymakers in agreeing to approaches to resolve the European debt crisis

There is now only one major country in the eurozone with AAA rating of its long-term debt by S&PRS (2012Jan13): Germany. IIIE Appendix Euro Zone Survival Risk analyzes the hurdle of financial bailouts of euro area members by the strength of the credit of Germany alone. The sum of the debt of Italy, Spain, Portugal, Greece and Ireland is abouy $3531.6 billion. There is some simple “unpleasant bond arithmetic.” Suppose the entire debt burdens of the five countries with probability of default were to be guaranteed by France and Germany, which de facto would be required by continuing the euro zone. The sum of the total debt of these five countries and the debt of France and Germany is about $7385.1 billion, which would be equivalent to 126.3 percent of their combined GDP in 2010. Under this arrangement the entire debt of the euro zone including debt of France and Germany would not have nil probability of default. Debt as percent of Germany’s GDP would exceed 224 percent if including debt of France and 165 percent of German GDP if excluding French debt. The unpleasant bond arithmetic illustrates that there is a limit as to how far Germany and France can go in bailing out the countries with unsustainable sovereign debt without incurring severe pains of their own such as downgrades of their sovereign credit ratings. A central bank is not typically engaged in direct credit because of remembrance of inflation and abuse in the past. There is also a limit to operations of the European Central Bank in doubtful credit obligations. Charles Forelle, writing on Jan 14, 2012, on “Downgrade hurts euro rescue fund,” published by the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204409004577159210191567778.html), analyzes the impact of the downgrades on the European Financial Stability Facility (EFSF). The EFSF is a special purpose vehicle that has not capital but can raise funds to be used in bailouts by issuing AAA-rated debt. S&P may cut the rating of the EFSF to the new lowest rating of the six countries with AAA rating, which are now down to four with the downgrades of France and Austria. The other rating agencies Moody’s and Fitch have not taken similar action. On Jan, S&PRS (2012Jan16) did cut the long-term credit rating of the EFSF to AA+ and affirmed the short-term credit rating at A-+. The decision is derived from the reduction in credit rating of the countries guaranteeing the EFSF. In the view of S&PRS (2012Jan16), there are not sufficient credit enhancements after the reduction in the creditworthiness of the countries guaranteeing the EFSF. The decision could be reversed if credit enhancements were provided.

The flow of cash from safe havens to risk financial assets is processed by carry trades from zero interest rates that are frustrated by episodes of risk aversion or encouraged with return of risk appetite. European sovereign risk crises are closely linked to the exposures of regional banks to government debt. An important form of financial repression consists of changing the proportions of debt held by financial institutions toward higher shares in government debt. The financial history of Latin America, for example, is rich in such policies. Bailouts in the euro zone have sanctioned “bailing in” the private sector, which means that creditors such as banks will participate by “voluntary” reduction of the principal in government debt (see Pelaez and Pelaez, International Financial Architecture (2005), 163-202). David Enrich, Sara Schaeffer Muñoz and Patricia Knowsmann, writing on “European nations pressure own banks for loans,” on Nov 29, 2011, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204753404577066431341281676.html?mod=WSJPRO_hpp_MIDDLETopStories), provide important data and analysis on the role of banks in the European sovereign risk crisis. They assemble data from various sources showing that domestic banks hold 16.2 percent of Italy’s total government securities outstanding of €1,617.4 billion, 22.9 percent of Portugal’s total government securities of €103.9 billion and 12.3 percent of Spain’s total government securities of €535.3 billion. Capital requirements force banks to hold government securities to reduce overall risk exposure in balance sheets. Enrich, Schaeffer Muñoz and Knowsmann find information that governments are setting pressures on banks to acquire more government debt or at least to stop selling their holdings of government debt.

Bond auctions are also critical in episodes of risk aversion. David Oakley, writing on Jan 3, 2012, on “Sovereign issues draw euro to crunch point,” published by the Financial Times (http://www.ft.com/intl/cms/s/0/63b9d7ca-2bfa-11e1-98bc-00144feabdc0.html#axzz1iLNRyEbs), estimates total euro area sovereign issues in 2012 at €794 billion, much higher than the long-term average of €670 billion. Oakley finds that the sovereign issues are: Italy €220 billion, France €197 billion, Germany €178 billion and Spain €81 billion. Bond auctions will test the resilience of the euro. Victor Mallet and Robin Wigglesworth, writing on Jan 12, 2012, on “Spain and Italy raise €22bn in debt sales,” published in the Financial Times (http://www.ft.com/intl/cms/s/0/e22c4e28-3d05-11e1-ae07-00144feabdc0.html#axzz1j4euflAi), analyze debt auctions during the week. Spain placed €10 billion of new bonds with maturities in 2015 and 2016, which was twice the maximum planned for the auction. Italy placed €8.5 billion of one-year bills at average yield of 2.735 percent, which was less than one-half of the yield of 5.95 percent a month before. Italy also placed €3.5 billion of 136-day bills at 1.64 percent. There may be some hope in the sovereign debt market. The yield of Italy’s 10-year bond dropped from around 7.20 percent on Jan 9 to about 6.70 percent on Jan 13 and then to around 6.30 percent on Jan 20. The yield of Spain’s 10-year bond fell from about 6.60 percent on Jan 9 to around 5.20 percent on Jan 13 and then to 5.50 percent on Jan 20.

A combination of strong economic data in China analyzed in subsection VC and the realization of the widely expected downgrade could explain the strength of the European sovereign debt market. Emese Bartha, Art Patnaude and Nick Cawley, writing on January 17, 2012, on “European T-bills see solid demand,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204555904577166363369792848.html?mod=WSJPRO_hpp_LEFTTopStories), analyze successful auctions treasury bills by Spain and Greece. A day after the downgrade, the EFSF found strong demand on Jan 17 for its six-month debt auction at the yield of 0.2664 percent, which is about the same as sovereign bills of France with the same maturity.

There may be some hope in the sovereign debt market. The yield of Italy’s 10-year bond dropped from around 7.20 percent on Jan 9 to about 6.70 percent on Jan 13 and then to around 6.30 percent on Jan 20. The yield of Spain’s 10-year bond fell from about 6.60 percent on Jan 9 to around 5.20 percent on Jan 13 and then to 5.50 percent on Jan 20. Paul Dobson, Emma Charlton and Lucy Meakin, writing on Jan 20, 2012, on “Bonds show return of crisis once ECB loans expire,” published in Bloomberg (http://www.bloomberg.com/news/2012-01-20/bonds-show-return-of-crisis-once-ecb-loans-expire-euro-credit.html), analyze sovereign debt and analysis of market participants. Large-scale lending of last resort by the European Central Bank, considered in VD Appendix on European Central Bank Large Scale Lender of Last Resort, provided ample liquidity in the euro zone for banks to borrow at 1 percent and lend at higher rates, including to government. Dobson, Charlton and Meakin trace the faster decline of yields of short-term sovereign debt relative to decline of yields of long-term sovereign debt. The significant fall of the spread of short relative to long yields could signal concern about the resolution of the sovereign debt while expanding lender of last resort operations have moderated relative short-term sovereign yields. Normal conditions would be attained if there is definitive resolution of long-term sovereign debt that would require fiscal consolidation in an environment of economic growth.

Charles Forelle and Stephen Fidler, writing on Dec 10, 2011, on “Questions place EU pact,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970203413304577087562993283958.html?mod=WSJPRO_hpp_LEFTTopStories#project%3DEUSUMMIT121011%26articleTabs%3Darticle), provide data, information and analysis of the agreement of Dec 9. There are multiple issues centering on whether investors will be reassured that the measures have reduced the risks of European sovereign obligations. While the European Central Bank has welcomed the measures, it is not yet clear of its future role in preventing erosion of sovereign debt values.

Another complicating factor is whether there will be further actions on sovereign debt ratings. On Dec 5, 2011, four days before the conclusion of the meeting of European leaders, Standard & Poor’s (2011Dec5) placed the sovereign ratings of 15 members of the euro zone on “CreditWatch with negative implications.” S&P finds five conditions that trigger the action: (1) worsening credit conditions in the euro area; (2) differences among member states on how to manage the debt crisis in the short run and on measures to move toward enhanced fiscal convergence; (3) household and government debt at high levels throughout large parts of the euro area; (4) increasing risk spreads on euro area sovereigns, including those with AAA ratings; and (5) increasing risks of recession in the euro zone. S&P also placed the European Financial Stability Facility (EFSF) in CreditWatch with negative implications (http://www.standardandpoors.com/ratings/articles/en/us/?articleType=HTML&assetID=1245325307963). On Dec 9, 2011, Moody’s Investors Service downgraded the ratings of the three largest French banks (http://www.moodys.com/research/Moodys-downgrades-BNP-Paribass-long-term-ratings-to-Aa3-concluding--PR_232989 http://www.moodys.com/research/Moodys-downgrades-Credit-Agricole-SAs-long-term-ratings-to-Aa3--PR_233004 http://www.moodys.com/research/Moodys-downgrades-Socit-Gnrales-long-term-ratings-to-A1--PR_232986 ).

Improving equity markets and strength of the euro appear related to developments in sovereign debt negotiations and markets. Alkman Granitsas and Costas Paris, writing on Jan 29, 2012, on “Greek debt deal, new loan agreement to finish next week,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204573704577189021923288392.html?mod=WSJPRO_hpp_LEFTTopStories), inform that Greece and its private creditors were near finishing a deal of writing off €100 billion, about $132 billion, of Greece’s debt depending on the conversations between Greece, the euro area and the IMF on the new bailout. An agreement had been reached in Oct 2011 for a new package of fresh money in the amount of €130 billion to fill needs through 2015 but was contingent on haircuts reducing Greece’s debt from 160 percent of GDP to 120 percent of GDP. The new bailout would be required to prevent default by Greece of €14.4 billion maturing on Mar 20, 2012. There has been increasing improvement of sovereign bond yields. Italy’s ten-year bond yield fell from over 6.30 percent on Jan 20, 2012 to slightly above 5.90 percent on Jan 27. Spain’s ten-year bond yield fell from slightly above 5.50 percent on Jan 20 to just below 5 percent on Jan 27.

An important difference, according to Beim (2011Oct9), between large-scale buying of bonds by the central bank between the Federal Reserve of the US and the European Central Bank (ECB) is that the Fed and most banks do not buy local and state government obligations with lower creditworthiness. The European Monetary Union (EMU) that created the euro and the ECB did not include common fiscal policy and affairs. Thus, EMU cannot issue its own treasury obligations. The line “Reserve bank credit” in the Fed balance sheet for Jan 25, 2012, is $2902 billion of which $2570 billion consisting of $1565 billion US Treasury notes and bonds, $68 billion inflation-indexed bonds and notes, $101 billion Federal agency debt securities and $836 billion mortgage-backed securities (http://www.federalreserve.gov/releases/h41/current/h41.htm#h41tab1). The Fed has been careful in avoiding credit risk in its portfolio of securities. The 11 exceptional liquidity facilities of several trillion dollars created during the financial crisis (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-62) have not resulted in any losses. The Fed has used unconventional monetary policy without credit risk as in classical central banking.

Beim (2011Oct9, 6) argues:

“In short, the ECB system holds more than €1 trillion of debt of the banks and governments of the 17 member states. The state-by-state composition of this debt is not disclosed, but the events of the past year suggest that a disproportionate fraction of these assets are likely obligations of stressed countries. If a significant fraction of the €1 trillion were to be restructured at 40-60% discounts, the ECB would have a massive problem: who would bail out the ECB?

This is surely why the ECB has been so shrill in its antagonism to the slightest mention of default and restructuring. They need to maintain the illusion of risk-free sovereign debt because confidence in the euro itself is built upon it.”

Table III-2 provides an update of the consolidated financial statement of the Eurosystem. The balance sheet has swollen with the LTROs. Line 5 “Lending to Euro Area Credit Institutions Related to Monetary Policy” increased from €546,747 million on Dec 31, 2010, to €870,130 million on Dec 28, 2011 and €1,118,273 million on Mar 9, 2012. The sum of line 5 and line 7 (“Securities of Euro Area Residents Denominated in Euro”) has increased to €1,749,395 million in the statement of Mar 9.

This sum is roughly what concerns Beim (2012Oct9) because of the probable exposure relative to capital to institutions and sovereigns with higher default risk. To be sure, there is no precise knowledge of the composition of the ECB portfolio of loans and securities with weights and analysis of the risks of components. Javier E. David, writing on Jan 16, 2012, on “The risks in ECB’s crisis moves,” published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052970204542404577158753459542024.html?mod=WSJ_hp_LEFTWhatsNewsCollection), informs that the estimated debt of weakest euro zone sovereigns held by the ECB is €211 billion, with Greek debt in highest immediate default risk being only 17 percent of the total. Another unknown is whether there is high risk collateral in the €489 billion three-year loans to credit institutions at 1 percent interest rates. The potential risk is the need for recapitalization of the ECB that could find similar political hurdles as the bailout fund EFSF. There is a recurring issue of whether the ECB should accept a haircut on its portfolio of Greek bonds of €40 billion acquired at discounts from face value. An article on “Haircut for the ECB? Not so fast,” published by the Wall Street Journal on Jan 28, 2012 (http://blogs.wsj.com/davos/2012/01/28/haircut-for-the-ecb-not-so-fast/), informs of the remarks by Mark Carney, Governor of the Bank of Canada and President of the Financial Stability Board (FSB) (http://www.financialstabilityboard.org/about/overview.htm), expressing what appears to be correct doctrine that there could conceivably be haircuts for official debt but that such a decision should be taken by governments and not by central banks.

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

	Dec 31, 2010	Dec 28, 2011	Mar 2, 2012
1 Gold and other Receivables	367,402	419,822	423,445
2 Claims on Non Euro Area Residents Denominated in Foreign Currency	223,995	236,826	246,981
3 Claims on Euro Area Residents Denominated in Foreign Currency	26,941	95,355	72,110
4 Claims on Non-Euro Area Residents Denominated in Euro	22,592	25,982	23,269
5 Lending to Euro Area Credit Institutions Related to Monetary Policy Operations Denominated in Euro	546,747	879,130	1,130,352
6 Other Claims on Euro Area Credit Institutions Denominated in Euro	45,654	94,989	59,261
7 Securities of Euro Area Residents Denominated in Euro	457,427	610,629	631,714
8 General Government Debt Denominated in Euro	34,954	33,928	31,176
9 Other Assets	278,719	336,574	404,851
TOTAL ASSETS	2,004, 432	2,733,235	3,023,159
Memo Items
Sum of 5 and 7	1,004,174	1,489,759	1,762,066
Capital and Reserves	78,143	81,481	82,990

Source: European Central Bank

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

http://www.ecb.int/press/pr/wfs/2012/html/fs120306.en.html

Professors Ricardo Caballero and Francesco Giavazzi (2012Jan15) find that the resolution of the European sovereign crisis with survival of the euro area would require success in the restructuring of Italy. That success would be assured with growth of the Italian economy. A critical problem is that the common currency prevents Italy from devaluation to parity or the exchange rate that would permit export growth to promote internal economic activity that generates fiscal revenues for primary fiscal surplus that ensure creditworthiness. Fiscal consolidation and restructuring are important but of long-term gestation. Immediate growth of the Italian economy would consolidate the resolution of the sovereign debt crisis. Caballero and Giavazzi (2012Jan15) argue that 55 percent of the exports of Italy are to countries outside the euro area such that devaluation of 15 percent would be effective in increasing export revenue. Newly available data in Table III-3 providing Italy’s trade with regions and countries supports the argument of Caballero and Giavazzi (2012Jan15). Italy’s exports to the European Monetary Union (EMU) are only 42.6 percent of the total. Exports to the non-European Union area are growing at 4.8 percent in Jan 2012 relative to Jan 2011 while those to EMU are growing at 2.9 percent.

Table III-3, Italy, Exports and Imports by Regions and Countries, % Share and 12-Month ∆%

	Exports % Share	∆% Jan 2012/ Jan 2011	Imports % Share	Imports ∆% Jan 2012/ Jan 2011
EU	56.0	3.9	53.3	-5.4
EMU 17	42.6	2.9	43.2	-5.2
France	11.6	4.2	8.3	-3.7
Germany	13.1	7.6	15.6	-4.9
Spain	5.3	-3.6	4.5	-6.2
UK	4.7	9.1	2.7	-12.5
Non EU	44.0	4.8	46.7	0.2
Europe non EU	13.3	21.9	11.1	-2.8
USA	6.1	-19.1	3.3	15.2
China	2.7	-11.8	7.3	-15.8
OPEC	4.7	15.4	8.6	13.6
Total	100.0	4.3	100.0	-2.6

Notes: EU: European Union; EMU: European Monetary Union (euro zone)

Table III-4 provides Italy’s trade balance by regions and countries. Italy has a trade deficit of €44 million with the 17 countries of the euro zone (EMU 17). Depreciation to parity could permit greater competitiveness in improving the trade surpluses of €98 million with Europe non European Union and of €256 million with the US. There is significant rigidity in the trade deficits of €1732 million with China and €2581 million with oil exporting countries (OPEC).

Table III-4, Italy, Trade Balance by Regions and Countries, Millions of Euro

Regions and Countries	Trade Balance Jan 2012 Millions of Euro	Trade Balance Cumulative Jan 2012 Millions of Euro
EU	756	756
EMU 17	-44	-44
France	831	831
Germany	-399	-399
Spain	326	326
UK	636	636
Non EU	-5,106	-5,106
Europe non EU	98	98
USA	256	256
China	-1,732	-1,732
OPEC	-2,581	-2,581
Total	-4,350	-4,350

Notes: EU: European Union; EMU: European Monetary Union (euro zone)

Growth rates of Italy’s trade and major products are provided in Table III-5 for the period Jan 2012 relative to Jan 2011. Growth rates are high for the total and all segments with the exception of decline of durable goods imports of 4.5 percent and decline of exports of 0.2 percent. Capital goods exports decreased 0.3 percent relative to a year earlier but imports of capital goods fell 6.6 percent and exports of intermediate products rose 4.2 percent.

Table III-5, Italy, Exports and Imports % Share of Products in Total and ∆%

	Exports Share %	Exports ∆% Jan 2012/ Jan 2011	Imports Share %	Imports ∆% Jan 2012/ Jan 2011
Consumer Goods	28.9	5.6	25.0	0.8
Durable	5.9	-0.2	3.0	-4.5
Non Durable	23.0	6.9	22.0	1.6
Capital Goods	32.2	-0.3	20.8	-6.6
Inter- mediate Goods	34.3	4.2	34.5	-11.9
Energy	4.7	23.2	19.7	11.8
Total ex Energy	95.3	3.2	80.3	-6.6
Total	100.0	4.3	100.0	-2.6

Table III-6 provides Italy’s trade balance by product categories in Jan 2012. Italy’s trade balance excluding energy is a surplus of €1781 million in Jan 2012 but the energy trade balance is a deficit of €6132 million. Italy has significant competitiveness in contrast with some other countries with debt difficulties.

Table III-6, Italy, Trade Balance by Product Categories, € Millions

	Jan 2012	Cumulative Jan 2012
Consumer Goods	161	161
Durable	471	471
Nondurable	-310	-310
Capital Goods	1,997	1,997
Intermediate Goods	-376	-376
Energy	-6,132	-6,132
Total ex Energy	1,781	1,781
Total	-4,350	-4,350