CMP Associates Regulation Blog

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are provided for the month of Aug in the years from 2001 to 2012 in Table ESI-2. Hiring numbers are in thousands. There is some recovery in HNF from 4655 thousand (or 4.7 million) in Aug 2009 to 4655 thousand in Aug 2011 and 4843 thousand in Aug 2012 for cumulative gain of 12.9 percent. HP rose from 3736 thousand in Aug 2009 to 4154 thousand in Aug 2011 and 4345 thousand in Aug 2012 for cumulative gain of 16.3 percent. HNF has fallen from 5881 in Aug 2006 to 4843 in Aug 2012 or by 17.7 percent. HP has fallen from 5387 in Aug 2005 to 4345 in Aug 2012 or by 19.3 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 ESI-2, 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 Aug	5450	4.1	4894	4.4
2002 Aug	5198	4.0	4677	4.3
2003 Aug	4948	3.8	4589	4.2
2004 Aug	5501	4.2	5019	4.5
2005 Aug	5881	4.4	5387	4.8
2006 Aug	5735	4.2	5119	4.8
2007 Aug	5662	4.1	5020	4.4
2008 Aug	5025	3.7	4540	4.3
2009 Aug	4184	3.2	3736	3.9
2010 Aug	4287	3.3	3897	3.4
2011 Aug	4655	3.5	4154	3.6
2012 Aug	4843	3.6	4345	3.8

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

Chart ESI-2 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 not-seasonally adjusted (NSA) of 4786 in May 2010 until it surpassed it in with 4869 in Jun 2011 and after 4926 in May 2012. Nonfarm hiring fell again in Dec 2011 to 3038 from 3844 in Nov and to revised 3633 in Feb 2012, increasing to 4127 in Mar 2012, 4490 in Apr 2012, 4926 in May 2012, 4988 in Jun 2012, 4752 in Jul 2012 and 4843 in Aug 2012. Chart ESI-2 provides seasonally-adjusted (SA) monthly data. The number of seasonally-adjusted hires in Aug 2011 was 4221 thousand, increasing to revised 4444 thousand in Feb 2012, or 5.3 percent, but falling to revised 4335 thousand in Mar 2012 and 4213 in Apr 2012, or cumulative decline of 0.2 percent relative to Aug 2011, increasing to 4390 in Aug 2012 for cumulative increase of 2.7 percent from 4276 in Sep 2011. The number of hires not seasonally adjusted was 4655 in Aug 2011, falling to 3038 in Dec but increasing to 4072 in Jan 2012 and 4843 in Aug 2012. The number of nonfarm hiring not seasonally adjusted fell by 34.7 percent from 4655 in Aug 2011 to 3038 in Dec 2011 in a yearly-repeated seasonal pattern.

Chart ESI-2, US, Total Nonfarm Hiring (HNF), 2001-2012 Month SA

Source: US Bureau of Labor Statistics

ESII 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 8.031 million in Aug 2012, seasonally adjusted, or decline of 1.024 million in nine months, as shown in Table ESII-1, but then rebounded to 8.164 million in Sep 2012 for increase of 582,000 in one month from Aug to Sep 2012. The number employed full-time increased from 112.479 million in Sep 2011 to 115.290 million in Mar 2012 or 2.811 million but then fell to 114.212 million in May 2012 or 1.078 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.388 million in Aug 2012 to 115.226 in Sep 2012 or increase of 838,000 full-time jobs in one month. There is a jump in the level of full-time SA to 114.573 million in Jun 2012 or 361,000 relative to May 2012 but then decline to 114.345 million in Jul 2012 or decline of 228,000 full time jobs from Jun 2012 into Jul 2012 and further decline to 114.388 million in Aug 2012 or decline of 185,000 full-time jobs relative to Jun 2012. The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.0151 million and to 7.694 million in Apr 2012 or 1.224 million fewer relative to Jan 2012. In Aug 2012, the number employed part-time for economic reasons reached 7.842 million NSA or 148,000 more than in Apr 2012. The number employed part-time for economic reasons increased from 7.842 million in Aug 2012 to 8.110 million in Sep 2012 or by 3.4 percent. The number employed full time without seasonal adjustment fell from 113.138 million in Nov 2011 to 113.050 million in Dec 2011 or by 88,000 and fell further to 111.879 in Jan 2012 for cumulative decrease of 1.259 million. The number employed full-time not seasonally adjusted fell from 113.138 million in Nov 2011 to 112.587 million in Feb 2012 or by 551.000 but increased to 116.214 million in Aug 2012 or 3.076 million more full-time jobs than in Nov 2011. The number employed full-time not seasonally adjusted decreased from 116.214 million in Aug 2012 to loss of 536,000 full-time jobs. Comparisons over long periods require use of NSA data. The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in Sep 2012 is 115.678 million, which is lower by 7.541 million relative to the peak of 123.219 million in Jul 2007. There appear to be around 10 million fewer full-time jobs in the US than before the global recession. Growth at 2.2 percent on average in the eleven quarters of expansion from IIIQ2009 to IIQ2012 compared with 6.2 percent on average in expansions from postwar cyclical contractions is the main culprit of the fractured US labor market (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html).

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

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Sep 2012	8,613	115.226
Aug 2012	8,031	114.388
Jul 2012	8,246	114.345
Jun 2012	8,210	114.573
May 2012	8,098	114.212
Apr 2012	7,853	114.478
Mar 2012	7,672	115.290
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
Jul 2011	8,437	112.006
Not Seasonally Adjusted
Sep 2012	8,110	115.678
Aug 2012	7,842	116.214
Jul 2012	8,316	116.131
Jun 2012	8,394	116.024
May 2012	7,837	114.634
Apr 2012	7,694	113.999
Mar 2012	7,867	113.916
Feb 2012	8,455	112.587
Jan 2012	8,918	111.879
Dec 2011	8,428	113.050
Nov 2011	8,271	113.138
Oct 2011	8,258	113.456
Sep 2011	8,541	112.980
Aug 2011	8,604	114.286
Jul 2011	8,514	113.759
Jun 2011	8,738	113.255
May 2011	8,270	112.618
Apr 2011	8,425	111.844
Mar 2011	8,737	111.186
Feb 2011	8,749	110.731
Jan 2011	9,187	110.373
Dec 2010	9,205	111.207
Nov 2010	8,670	111.348
Oct 2010	8,408	112.342
Sep 2010	8,628	112.385
Aug 2010	8,628	113.508
Jul 2010	8,737	113.974
Jun 2010	8,867	113.856
May 2010	8,513	112.809
Apr 2010	8,921	111.391
Mar 2010	9,343	109.877
Feb 2010	9,282	109.100
Jan 2010	9,290	108.777 (low)
Dec 2009	9,354 (high)	109.875
Sep 2009	8,255	111.991
Aug 2009	8,835	113.863
Jul 2009	9,103	114.184
Jun 2009	9,301	114.014
May 2009	8,785	113.083
Apr 2009	8,648	112.746
Mar 2009	9,305	112.215
Feb 2009	9,170	112.947
Jan 2009	8,829	113.815
Sep 2008	5,701	120.213
Aug 2008	5,736	121.556
Jul 2008	6,054	122.378
Jun 2008	5,697	121.845
May 2008	5,096	120.809
Apr 2008	5,071	120.027
Mar 2008	5,038	119.875
Feb 2008	5,114	119.452
Jan 2008	5,340	119.322
Sep 2007	4,137	121.278
Aug 2007	4,494	122.870
Jul 2007	4,516	123.219 (high)
Jun 2007	4,469	122.150
May 2007	4,315	120.846
Apr 2007	4,205	119.609
Mar 2007	4,384	119.640
Feb 2007	4,417	119.041
Jan 2007	4,726	119.094
Sep 2006	3,735 (low)	120.780
Aug 2006	4,104	121.979
Jul 2006	4,450	121.951
Jun 2006	4,456	121.070
May 2006	3,968	118.925
Apr 2006	3,787	118.559
Mar 2006	4,097	117.693
Feb 2006	4,403	116.823
Jan 2006	4,597	116.395

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

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

Sources: US Bureau of Labor Statistics

ESIII Youth and Middle Age Unemployment. Table ESIII-1 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 Jul 2011 the rate of youth unemployed was 18.1 percent and 17.1 percent in Jul 2012 compared with 10.8 percent in Jun 2007.

Table ESIII-1, US, Unemployment Rate 16-24 Years, Thousands, NSA

Year	Apr	May	Jun	Jul	Aug	Sep	Annual
2002	11.6	11.6	13.2	12.4	11.5	11.4	12.0
2003	12.0	13.0	14.8	13.3	11.9	12.5	12.4
2004	11.1	12.2	13.4	12.3	11.1	11.5	11.8
2005	11.2	11.9	12.6	11.0	10.8	10.7	11.3
2006	9.7	10.2	11.9	11.2	10.4	10.5	10.5
2007	9.7	10.2	12.0	10.8	10.5	11.0	10.5
2008	10.3	13.3	14.4	14.0	13.0	13.4	12.8
2009	15.8	18.0	19.9	18.5	18.0	18.2	17.6
2010	18.5	18.4	20.0	19.1	17.8	17.6	18.4
2011	16.5	17.5	18.9	18.1	17.5	17.0	17.3
2012	15.4	16.3	18.1	17.1	16.8	15.2

Sources: US Bureau of Labor Statistics

Chart ESIII-1 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 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 twelve consecutive quarters of expansion of the economy since IIIQ2009 because of much lower growth at 2.2 percent annual equivalent on average compared with 6.2 percent on average in cyclical expansions since World War II Table I -5 (http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html).

Chart ESIII-11, US, Unemployment Rate 16-24 Years, Thousands, NSA, 2001-2012

Sources: US Bureau of Labor Statistics

Chart ESIII-2 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 NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984 while the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 18.2 percent in Sep 2009, 17.6 percent in Sep 2010, 17.0 percent in Sep 2011 and 15.2 percent in Sep 2012. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.2 percent on average during the first eleven quarters of expansion from IIIQ2009 to IIQ2012 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html). The fractured US labor market denies an early start for young people.

Chart ESIII-2, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2012

Sources: US Bureau of Labor Statistics

It is more difficult to move to other jobs after a certain age because of fewer available opportunities for matured individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table ESIII-2 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.985 million in Jul 2006 to 4.821 million in July 2010 or by 142.9 percent. The number of unemployed ages 45 years and over declined to 4.405 million in Jul 2012 that is still higher by 121.9 percent than in Jul 2006. The number unemployed age 45 and over jumped from 1.869 million in Aug 2006 to 5.128 million in Aug 2010 or 174.4 percent and at 4.179 million in Aug 2012 is higher by 2.310 million or 123.6 percent than 1.869 million in Aug 2006. The number unemployed ages 45 and over increased from 1.710 million in Sep 2006 to 4.640 million in Sep 2010, which is higher by 2.930 million or 161.1 percent, declining to 3.899 million in Sep 2012, which is higher by 2.189 million or 128.0 percent than in Sep 2006.

Table ESIII-2, US, Unemployment Level 45 Years and Over, Thousands NSA

Year	Apr	May	Jun	Jul	Aug	Sep	Annual
2001	1421	1259	1371	1539	1640	1586	1576
2002	2101	1999	2190	2173	2114	1966	2114
2003	2287	2112	2212	2281	2301	2157	2253
2004	2160	2025	2182	2116	2082	1951	2149
2005	1939	1844	1868	2119	1895	1992	2009
2006	1843	1784	1813	1985	1869	1710	1848
2007	1871	1803	1805	2053	1956	1854	1966
2008	2104	2095	2211	2492	2695	2595	2540
2009	4172	4175	4505	4757	4683	4560	4500
2010	4770	4565	4564	4821	5128	4640	4879
2011	4373	4356	4559	4772	4592	4426	4537
2012	4037	4083	4084	4405	4179	3899

Sources: US Bureau of Labor Statistics

Chart ESIII-3 provides the level unemployed ages 45 years and over. There was sharp increase during the global recession and inadequate decline. There was an increase during the 2001 recession and then stability. The US is facing a major challenge of reemploying middle-aged workers.

Chart ESIII-3, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2012

Sources: US Bureau of Labor Statistics

http://www.federalreserve.gov/datadownload/Choose.aspx?rel=H10

ESIV World Currency Wars. Exchange rate struggles continue as zero interest rates in advanced economies induce devaluation of their currencies. After deep global recession, regulation, trade and devaluation wars were to be expected (Pelaez and Pelaez, Government Intervention in Globalization: Regulation, Trade and Devaluation Wars (2008c), 181): “There are significant grounds for concern on the basis of this experience. International economic cooperation and the international financial framework can collapse during extreme events. It is unlikely that there will be a repetition of the disaster of the Great Depression. However, a milder contraction can trigger regulatory, trade and exchange wars.”

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 augment perceptions of the wealth of consumers inducing increases in consumption.

2. Unconventional monetary policy causes devaluation of the dollar relative to other currencies, which 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 instability. 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 IA Appendix: Transmission of Unconventional Monetary Policy http://cmpassocregulationblog.blogspot.com/2012/09/recovery-without-hiring-world-inflation.html).

Symmetric inflation targets appear to have been abandoned in favor of a self-imposed single jobs mandate of easing monetary policy even with the economy growing at or close to potential output. Monetary easing by unconventional measures is now open ended in perpetuity, or QE_∞, as provided in the statement of the meeting of the Federal Open Market Committee (FOMC) on Sep 13, 2012 (http://www.federalreserve.gov/newsevents/press/monetary/20120913a.htm):

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

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

Chairman Bernanke (2012Oct14IMF) dismisses arguments that unconventional monetary policy causes undesirable capital flows into emerging-market economies and offers the following alternative policy:

“Of course, an alternative strategy--one consistent with classical principles of international adjustment--is to refrain from intervening in foreign exchange markets, thereby allowing the currency to rise and helping insulate the financial system from external pressures. Under a flexible exchange-rate regime, a fully independent monetary policy, together with fiscal policy as needed, would be available to help counteract any adverse effects of currency appreciation on growth. The resultant rebalancing from external to domestic demand would not only preserve near-term growth in the emerging market economies while supporting recovery in the advanced economies, it would redound to everyone's benefit in the long run by putting the global economy on a more stable and sustainable path.”

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

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

Continental territory, rich endowment of natural resources, investment in human capital, teaching and research universities, motivated labor force and entrepreneurial initiative provide Brazil with comparative advantages in multiple economic opportunities. Exchange rate parity is critical in achieving Brazil’s potential but is difficult in a world of zero interest rates. Chart ESIV-1 of the Board of Governors of the Federal Reserve System provides the rate of Brazilian real (BRL) per US dollar (USD) from BRL 1.2074/USD on Jan 4, 1999 to BRL 2.0273/USD on Oct 5, 2012. The rate reached BRL 3.9450/USD on Oct 10, 2002 appreciating 60.5 percent to BRL 1.5580/USD on Aug 1, 2008. The rate depreciated 68.1 percent to BRL 2.6187/USD on Dec 5, 2008 during worldwide flight from risk. The rate appreciated again by 41.3 percent to BRL 1.5375/USD on Jul 26, 2011. The final data point in Chart ESIV-1 is BRL 2.0273/USD on Oct 5, 2012 for depreciation of 31.9 percent. The data in Table VI-6 in the text is obtained from closing dates in New York published by the Wall Street Journal (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata).

Chart ESIV-1, Brazilian Real (BRL) per US Dollar (USD) Jan 4, 1999 to Oct 5, 2012

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

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

Chart ESIV-2, Brazilian Real (BRL) per US Dollar (USD), Jan 2, 1995 to Oct 5, 2012

Note: US Recessions in Shaded Areas

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/datadownload/Choose.aspx?rel=H10

ESV Collapse of United States Dynamism of Income Growth and Employment Creation. This blog has analyzed systematically the weakness of the United States recovery in the current business cycle from IIIQ2009 to the present in comparison with the recovery from the recessions in the 1980s from IQ1983 to IVQ1985. The United States has grown on average at 2.2 percent annual equivalent in the 12 quarters of expansion since IIIQ2009 while growth was 6.2 percent on average in recoveries after World War II and 5.7 percent from IQ1983 to IVQ1985. The conventional explanation is that the recession from IVQ2007 (Dec) to IIQ2009 (Jun) was so profound that it caused subsequent weak recovery and that historically growth after recessions with financial crises has been weaker. Michael D. Bordo (2012Sep27) and Bordo and Haubrich (2012DR) provide evidence contradicting the conventional explanation: recovery is much stronger on average after profound contractions and also much stronger after recessions with financial crises than after recessions without financial crises. Insistence on the conventional explanation prevents finding policies that can accelerate growth, employment and prosperity.

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

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

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

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

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

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

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

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

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

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

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

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

External economies of commitment to secure private rights in sovereign credit would encourage development of private financial institutions, as postulated in classic work by North and Weingast (1989), Summerhill 2007IR, 22). This is how banking institutions critical to the Industrial Revolution were developed in England (Cameron 1967). The obstacle in Brazil found by Summerhill (2007IR) is that sovereign debt credibility was combined with financial repression. There was a break in Brazil of the chain of effects from protecting public borrowing, as in North and Weingast (1989), to development of private financial institutions. According to Pelaez 1976, 283) following Rondo E. Cameron (1961, 1967, 1972):

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

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

“Brazil’s experience is particularly interesting in that in the period 1808-1851 there were three types of monetary systems. Between 1808 and 1829, there was only one government-related Bank of Brazil, enjoying a perfect monopoly of banking services. No new banks were established in the 1830s after the liquidation of the Bank of Brazil in 1829. During the coffee boom in the late 1830s and 1840s, a system of banks of issue, patterned after similar institutions in the industrial countries [Cameron 1967], supplied the financial services required in the first stage of modernization of the export economy.”

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

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

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

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

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

The average rate of growth of real GDP in expansions after recessions with financial crises was 8 percent but only 6.9 percent on average for recessions without financial crises (Bordo 2012Sep27). Real GDP declined 12 percent in the Panic of 1907 and increased 13 percent in the recovery, consistent with the plucking model of Friedman (Bordo 2012Sep27). The comparison of recovery from IQ1983 to IVQ1985 is appropriate even when considering financial crises. Bordo and Haubrich (2012DR, 11) identify a recession with financial crisis beginning in IIIQ1981 (Jul) (http://www.nber.org/cycles.html). There was significant financial turmoil during the 1980s. Benston and Kaufman (1997, 139) find that there was failure of 1150 US commercial and savings banks between 1983 and 1990, or about 8 percent of the industry in 1980, which is nearly twice more than between the establishment of the Federal Deposit Insurance Corporation in 1934 through 1983. More than 900 savings and loans associations, representing 25 percent of the industry, were closed, merged or placed in conservatorships (see Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 74-7). The Financial Institutions Reform, Recovery and Enforcement Act of 1989 (FIRREA) created the Resolution Trust Corporation (RTC) and the Savings Association Insurance Fund (SAIF) that received $150 billion of taxpayer funds to resolve insolvent savings and loans. The GDP of the US in 1989 was $5482.1 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.74 percent of GDP in a year. US GDP in 2011 is estimated at $15,075.7 billion, such that the bailout would be equivalent to cost to taxpayers of about $412.5 billion in current GDP terms. A major difference with the Troubled Asset Relief Program (TARP) for private-sector banks is that most of the costs were recovered with interest gains whereas in the case of savings and loans there was no recovery. Money center banks were under extraordinary pressure from the default of sovereign debt by various emerging nations that represented a large share of their net worth (see Pelaez 1986).

Bordo (2012Sep27) finds two probable explanations for the weak recovery during the current economic cycle: (1) collapse of United States housing; and (2) uncertainty originating in fiscal policy, regulation and structural changes. There are serious doubts if monetary policy is adequate to recover the economy under these conditions.

Lucas (2011May) estimates US economic growth in the long-term at 3 percent per year and about 2 percent per year in per capita terms. There are displacements from this trend caused by events such as wars and recessions but the economy then returns to trend. Historical US GDP data exhibit remarkable growth: Lucas (2011May) estimates an increase of US real income per person by a factor of 12 in the period from 1870 to 2010. The explanation by Lucas (2011May) of this remarkable growth experience is that government provided stability and education while elements of “free-market capitalism” were an important driver of long-term growth and prosperity. The analysis is sharpened by comparison with the long-term growth experience of G7 countries (US, UK, France, Germany, Canada, Italy and Japan) and Spain from 1870 to 2010. Countries benefitted from “common civilization” and “technology” to “catch up” with the early growth leaders of the US and UK, eventually growing at a faster rate. Significant part of this catch up occurred after World War II. Lucas (2011May) finds that the catch up stalled in the 1970s. The analysis of Lucas (2011May) is that the 20-40 percent gap that developed originated in differences in relative taxation and regulation that discouraged savings and work incentives in comparison with the US. A larger welfare and regulatory state, according to Lucas (2011May), could be the cause of the 20-40 percent gap. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Long-term economic growth and prosperity are measured by the key indicators of growth of real income per capita, or what is earned per person after inflation. A refined concept would include real disposable income per capita, or what is earned per person after inflation and taxes.

Table ESV-1 provides the data required for broader comparison of the cyclical expansions of IQ1983 to IVQ1985 and the current one from 2009 to 2012. First, in the 13 quarters from IQ1983 to IVQ1985, GDP increased 19.6 percent at the annual equivalent rate of 5.7 percent; real disposable personal income (RDPI) increased 14.5 percent at the annual equivalent rate of 4.3 percent; RDPI per capita increased 11.5 percent at the annual equivalent rate of 3.4 percent; and population increased 2.7 percent at the annual equivalent rate of 0.8 percent. Second, in the 12 quarters of the current cyclical expansion from IIIQ2009 to IIQ2012, GDP increased 6.7 percent at the annual equivalent rate of 2.2 percent; real disposable personal income (RDPI) increased 3.8 percent at the annual equivalent rate of 1.3 percent; RDPI per capita increased 1.4 percent at the annual equivalent rate of 0.5 percent; and population increased 2.3 percent at the annual equivalent rate of 0.8 percent. Third, since the beginning of the recession in IVQ2007 to IIQ2012, GDP increased 1.7 percent, or barely above the level before the recession; real disposable personal income increased 3.5 percent; population increased 3.7 percent; and real disposable personal income per capita is 0.2 percent lower than the level before the recession. Real disposable personal income is the actual take home pay after inflation and taxes and real disposable income per capita is what is left per inhabitant. The current cyclical expansion is the worst in the period after World War II in terms of growth of economic activity and income. The United States grew during its history at high rates of per capita income that made its economy the largest in the world. That dynamism is disappearing. Bordo (2012 Sep27) and Bordo and Haubrich (2012DR) provide strong evidence that recoveries have been faster after deeper recessions and recessions with financial crises, casting serious doubts on the conventional explanation of weak growth during the current expansion allegedly because of the depth of the contraction from IVQ2007 to IIQ2009 of 4.7 percent and the financial crisis.

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

	# Quarters	∆%	∆% Annual Equivalent
IQ1983 to IVQ1985	13
GDP		19.6	5.7
RDPI		14.5	4.3
RDPI Per Capita		11.5	3.4
Population		2.7	0.8
IIIQ2009 to IIQ2012	12
GDP		6.7	2.2
RDPI		3.8	1.3
RDPI per Capita		1.4	0.5
Population		2.3	0.8
IVQ2007 to IIQ2012	19
GDP		1.7	0.4
RDPI		3.5	0.7
RDPI per Capita		-0.2
Population		3.7	0.8

RDPI: Real Disposable Personal Income

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

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

1. Trend Growth.

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

ii. In contrast, cumulative growth from IVQ2007 to IIQ2012 was 1.7 percent while trend growth would have been 14.2 percent. GDP in IIQ2012 at seasonally adjusted annual rate is estimated at $13,548.5 percent by the Bureau of Economic Analysis (BEA) (http://www.bea.gov/iTable/index_nipa.cfm) and would have been $15,218.3 billion, or $1,669 billion higher, had the economy grown at trend over the entire business cycle as it happened during the 1980s and throughout most of US history. There is $1.7 trillion of foregone GDP that would have been created as it occurred during past cyclical expansions, which explains why employment has not rebounded to even higher than before. There would not be recovery of full employment even with growth of 3 percent per year beginning immediately because the opportunity was lost to grow faster during the expansion from IIIQ2009 to IIQ2012 after the recession from IVQ2007 to IIQ2009. The United States has acquired a heavy social burden of unemployment and underemployment of 28.7 million people or 17.8 percent of the effective labor force (Section I, Table I-4 http://cmpassocregulationblog.blogspot.com/2012/10/twenty-nine-million-unemployed-or.html) that will not be significantly diminished even with return to growth of GDP of 3 percent per year because of growth of the labor force by new entrants. The US labor force grew from 142.583 million in 2000 to 153.124 million in 2007 or by 7.4 percent at the average yearly rate of 1.0 percent per year. The civilian noninstitutional population increased from 212.577 million in 2000 to 231.867 million in 2007 or 9.1 percent at the average yearly rate of 1.3 percent per year (data from http://www.bls.gov/data/). Data for the past five years cloud accuracy because of the number of people discouraged from seeking employment. The noninstitutional population of the United States increased from 231.867 million in 2007 to 239.618 million in 2011 or by 3.3 percent while the labor force increased from 153.124 million in 2007 to 153.617 million in 2011 or by 0.3 percent (data from http://www.bls.gov/data/). People ceased to seek jobs because they do not believe that there is a job available for them (Section I http://cmpassocregulationblog.blogspot.com/2012/10/twenty-nine-million-unemployed-or.html).

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

Period IVQ2007 to IIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIQ2012	13,548.5
∆% IVQ2007 to IIQ2012 Actual	1.7
∆% IVQ2007 to IIQ2012 Trend	14.2

2. Decline of Per Capita Real Disposable Income

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

ii. In contrast, in the entire business cycle from IVQ2007 to IIQ2012, per capita real disposable income fell 0.2 percent while trend growth would have been 9.3 percent. Income available after inflation and taxes is lower than before the contraction after 12 consecutive quarters of GDP growth at mediocre rates relative to those prevailing during historical cyclical expansions.

Period IQ1980 to IVQ1985

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

Period IVQ2007 to IIQ2012

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIQ2012 Chained 2005 USD	32,779
∆% IVQ2007 to IIQ2012	-0.2
∆% Trend Growth	9.3

3. Number of Employed Persons

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

ii. In contrast, during the entire business cycle the number employed fell from 146.334 million in IVQ2007 to 143.202 million in IIQ2012 or by 2.1 percent. There are 28.7 million persons unemployed or underemployed, which is 17.8 percent of the effective labor force (Section I, Table I-4 http://cmpassocregulationblog.blogspot.com/2012/10/twenty-nine-million-unemployed-or.html).

Period IQ1980 to IVQ1985

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

Period IVQ2007 to IIQ2012

Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIQ2012 NSA End of Quarter	143.202
∆% Employed IVQ2007 to IIQ2012	-2.1

4. Number of Full-Time Employed Persons

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

ii. In contrast, during the entire current business cycle, including contraction and expansion, the number of persons employed full-time fell from 121.042 million in IVQ2007 to 116.024 million in IIQ2012 or by minus 4.1 percent.

Period IQ1980 to IVQ1985

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

Period IVQ2007 to IIQ2012

Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIQ2012 NSA End of Quarter	116.024
∆% Full-time Employed IVQ2007 to IIQ2012	-4.1

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

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

ii. In contrast, in the economic cycle from IVQ2007 to IIQ2012: (a) the rate of unemployment increased from 4.8 percent in IVQ2007 to 8.4 percent in IIQ2012; (b) the number unemployed increased 78.9 percent from 7.371 million in IVQ2007 to 13.184 million in IIQ2012; (c) the number employed part-time for economic reasons increased 76.7 percent from 4.750 in IVQ2007 to 8.394 million in IIQ2012; and (d) U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA increased from 8.7 percent in IVQ2007 to 14.2 in IIQ2012 .

Period IQ1980 to IVQ1985

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

Period IVQ2007 to IIQ2012

Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIQ2012 NSA End of Quarter	8.4
Unemployed IVQ2007 Millions End of Quarter	7.371
Unemployed IIQ2009 Millions End of Quarter	13.184
∆%	78.9
Employed Part-time Economic Reasons IVQ2007 Millions End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 End of Quarter	8.394
∆%	76.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007 Dec	8.7
IIQ2012	14.2

6. Wealth of Households and Nonprofit Organizations.

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

ii. In contrast, as shown in the following block and in Table ESV-2, net worth of households and nonprofit organizations fell from $66,057.1 billion in IVQ2007 to $62,668.4 billion in IIQ2012 by $3,388.7 billion or 5.1 percent. The US consumer price index was 210.036 in Dec 2007 and 229.478 in Jun 2012 for increase of 9.3 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 13.2 percent in Jun 2012 after 12 consecutive quarters of expansion from IIIQ2009 to IIQ2012 relative to IVQ2012 when the recession began. The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. The average growth rate from IIIQ2009 to IIQ2012 has been 2.2 percent, which is substantially lower than the average of 6.2 percent in cyclical expansions after World War II and 5.7 percent in the expansion from IQ1983 to IVQ1985 (see Table I-5 http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions.

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

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


Period IQ1980 to IVQ1985
GDP SAAR USD Billions
IQ1980	5,903.4
IVQ1985	6,950.0
∆% IQ1980 to IVQ1985	17.7
∆% Trend Growth IQ1980 to IVQ1985	18.5
Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD	18,938
Real Disposable Personal Income per Capita IVQ1985 Chained 2005 USD	21,687
∆% IQ1980 to IVQ1985	14.5
∆% Trend Growth	12.1
Employed Millions IQ1980 NSA End of Quarter	98.527
Employed Millions IV1985 NSA End of Quarter	107.819
∆% Employed IQ1980 to IV1985	9.4
Employed Full-time Millions IQ1980 NSA End of Quarter	81.280
Employed Full-time Millions IV1985 NSA End of Quarter	88.757
∆% Full-time Employed IQ1980 to IV1985	9.2
Unemployment Rate IQ1980 NSA End of Quarter	6.6
Unemployment Rate IV1985 NSA End of Quarter	6.7
Unemployed IQ1980 Millions NSA End of Quarter	6.983
Unemployed IV 1985 Millions NSA End of Quarter	7.717
∆%	11.9
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 NSA End of Quarter	8.394
∆%	76.7
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ1979	8,326.4
IVQ1985	14,395.2
∆ USD Billions	+6,068.8
Period IVQ2007 to IIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIQ2012	13,548.5
∆% IVQ2007 to IIQ2012	1.7
∆% IVQ2007 to IIQ2012 Trend Growth	14.2
Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIQ2012 Chained 2005 USD	32,779
∆% IVQ2007 to IIQ2012	-0.2
∆% Trend Growth	9.3
Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIQ2012 NSA End of Quarter	143.202
∆% Employed IVQ2007 to IIQ2012	-2.1
Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIQ2012 NSA End of Quarter	116.024
∆% Full-time Employed IVQ2007 to IIQ2012	-4.1
Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIQ2012 NSA End of Quarter	8.4
Unemployed IVQ2007 Millions NSA End of Quarter	7.371
Unemployed IIQ2009 Millions NSA End of Quarter	13.184
∆%	78.9
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 NSA End of Quarter	8.394
∆%	76.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007	8.7
IIQ2012	14.2
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ2007	66,057.1
IIQ2012	62,668.4
∆ USD Billions	-3,388.7

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

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

ESVI Global Financial and Economic Risk. The International Monetary Fund (IMF) provides an international safety net for prevention and resolution of international financial crises. The IMF’s Financial Sector Assessment Program (FSAP) provides analysis of the economic and financial sectors of countries (see Pelaez and Pelaez, International Financial Architecture (2005), 101-62, Globalization and the State, Vol. II (2008), 114-23). Relating economic and financial sectors is a challenging task both for theory and measurement. The IMF provides surveillance of the world economy with its Global Economic Outlook (WEO) (http://www.imf.org/external/pubs/ft/weo/2012/update/01/index.htm), of the world financial system with its Global Financial Stability Report (GFSR) (http://www.imf.org/external/pubs/ft/fmu/eng/2012/01/index.htm) and of fiscal affairs with the Fiscal Monitor (http://www.imf.org/external/pubs/ft/fm/2012/update/01/fmindex.htm). There appears to be a moment of transition in global economic and financial variables that may prove of difficult analysis and measurement. It is useful to consider a summary of global economic and financial risks, which are analyzed in detail in the comments of this blog in Section VI Valuation of Risk Financial Assets, Table VI-4.

Economic risks include the following:

1. China’s Economic Growth. China is lowering its growth target to 7.5 percent per year. The growth rate of GDP of China in the second quarter of 2012 of 1.8 percent is equivalent to 7.4 percent per year.

2. United States Economic Growth, Labor Markets and Budget/Debt Quagmire. The US is growing slowly with 28.1 million in job stress, fewer 10 million full-time jobs, high youth unemployment, historically-low hiring and declining real wages.

3. Economic Growth and Labor Markets in Advanced Economies. Advanced economies are growing slowly. There is still high unemployment in advanced economies.

4. World Inflation Waves. Inflation continues in repetitive waves globally (see http://cmpassocregulationblog.blogspot.com/2012/08/world-inflation-waves-loss-of-dynamism.html).

A list of financial uncertainties includes:

1. Euro Area Survival Risk. The resilience of the euro to fiscal and financial doubts on larger member countries is still an unknown risk.

2. Foreign Exchange Wars. Exchange rate struggles continue as zero interest rates in advanced economies induce devaluation of their currencies.

3. Valuation of Risk Financial Assets. Valuations of risk financial assets have reached extremely high levels in markets with lower volumes.

4. Duration Trap of the Zero Bound. The yield of the US 10-year Treasury rose from 2.031 percent on Mar 9, 2012, to 2.294 percent on Mar 16, 2012. Considering a 10-year Treasury with coupon of 2.625 percent and maturity in exactly 10 years, the price would fall from 105.3512 corresponding to yield of 2.031 percent to 102.9428 corresponding to yield of 2.294 percent, for loss in a week of 2.3 percent but far more in a position with leverage of 10:1. Min Zeng, writing on “Treasurys fall, ending brutal quarter,” published on Mar 30, 2012, in the Wall Street Journal (http://professional.wsj.com/article/SB10001424052702303816504577313400029412564.html?mod=WSJ_hps_sections_markets), informs that Treasury bonds maturing in more than 20 years lost 5.52 percent in the first quarter of 2012.

5. Credibility and Commitment of Central Bank Policy. There is a credibility issue of the commitment of monetary policy (Sargent and Silber 2012Mar20).

6. Carry Trades. Commodity prices driven by zero interest rates have resumed their increasing path with fluctuations caused by intermittent risk aversion.

It is in this context of economic and financial uncertainties that decisions on portfolio choices of risk financial assets must be made. There is a new carry trade that learned from the losses after the crisis of 2007 or learned from the crisis how to avoid losses. The sharp rise in valuations of risk financial assets shown in Table VI-1 in the text after the first policy round of near zero fed funds and quantitative easing by the equivalent of withdrawing supply with the suspension of the 30-year Treasury auction was on a smooth trend with relatively subdued fluctuations. The credit crisis and global recession have been followed by significant fluctuations originating in sovereign risk issues in Europe, doubts of continuing high growth and accelerating inflation in China now complicated by political developments, events such as in the Middle East and Japan and legislative restructuring, regulation, insufficient growth, falling real wages, depressed hiring and high job stress of unemployment and underemployment in the US now with realization of growth standstill. The “trend is your friend” motto of traders has been replaced with a “hit and realize profit” approach of managing positions to realize profits without sitting on positions. There is a trend of valuation of risk financial assets driven by the carry trade from zero interest rates with fluctuations provoked by events of risk aversion or the “sharp shifts in risk appetite” of Blanchard (2012WEOApr, XIII). Table ESVI-1, which is updated for every comment of this blog, shows the deep contraction of valuations of risk financial assets after the Apr 2010 sovereign risk issues in the fourth column “∆% to Trough.” There was sharp recovery after around Jul 2010 in the last column “∆% Trough to 10/12/12,” which has been recently stalling or reversing amidst bouts of risk aversion. “Let’s twist again” monetary policy during the week of Sep 23 caused deep worldwide risk aversion and selloff of risk financial assets (http://cmpassocregulationblog.blogspot.com/2011/09/imf-view-of-world-economy-and-finance.html http://cmpassocregulationblog.blogspot.com/2011/09/collapse-of-household-income-and-wealth.html). Monetary policy was designed to increase risk appetite but instead suffocated risk exposures. There has been rollercoaster fluctuation in risk aversion and financial risk asset valuations: surge in the week of Dec 2, 2011, mixed performance of markets in the week of Dec 9, renewed risk aversion in the week of Dec 16, end-of-the-year relaxed risk aversion in thin markets in the weeks of Dec 23 and Dec 30, mixed sentiment in the weeks of Jan 6 and Jan 13 2012 and strength in the weeks of Jan 20, Jan 27 and Feb 3 followed by weakness in the week of Feb 10 but strength in the weeks of Feb 17 and 24 followed by uncertainty on financial counterparty risk in the weeks of Mar 2 and Mar 9. All financial values have fluctuated with events such as the surge in the week of Mar 16 on favorable news of Greece’s bailout even with new risk issues arising in the week of Mar 23 but renewed risk appetite in the week of Mar 30 because of the end of the quarter and the increase in the firewall of support of sovereign debts in the euro area. New risks developed in the week of Apr 6 with increase of yields of sovereign bonds of Spain and Italy, doubts on Fed policy and weak employment report. Asia and financial entities are experiencing their own risk environments. Financial markets were under stress in the week of Apr 13 because of the large exposure of Spanish banks to lending by the European Central Bank and the annual equivalent growth rate of China’s GDP of 7.4 percent in IQ2012 [(1.018)⁴], which was repeated in IIQ2012. There was strength again in the week of Apr 20 because of the enhanced IMF firewall and Spain placement of debt, continuing into the week of Apr 27. Risk aversion returned in the week of May 4 because of the expectation of elections in Europe and the new trend of deterioration of job creation in the US. Europe’s sovereign debt crisis and the fractured US job market continued to influence risk aversion in the week of May 11. Politics in Greece and banking issues in Spain were important factors of sharper risk aversion in the week of May 18. Risk aversion continued during the week of May 25 and exploded in the week of Jun 1. Expectations of stimulus by central banks caused valuation of risk financial assets in the week of Jun 8 and in the week of Jun 15. Expectations of major stimulus were frustrated by minor continuance of maturity extension policy in the week of Jun 22 together with doubts on the silent bank run in highly indebted euro area member countries. There was a major rally of valuations of risk financial assets in the week of Jun 29 with the announcement of new measures on bank resolutions by the European Council. New doubts surfaced in the week of Jul 6, 2012 on the implementation of the bank resolution mechanism and on the outlook for the world economy because of interest rate reductions by the European Central, Bank of England and People’s Bank of China. Risk appetite returned in the week of July 13 in relief that economic data suggests continuing high growth in China but fiscal and banking uncertainties in Spain spread to Italy in the selloff of July 20, 2012. Mario Draghi (2012Jul26), president of the European Central Bank, stated: “But there is another message I want to tell you.

Within our mandate, the ECB is ready to do whatever it takes to preserve the euro. And believe me, it will be enough.” This statement caused return of risk appetite, driving upward valuations of risk financial assets worldwide. Buiter (2011Oct31) analyzes that the European Financial Stability Fund (EFSF) would need a “bigger bazooka” to bail out euro members in difficulties that could possibly be provided by the ECB. The dimensions of the problem may require more firepower than a bazooka perhaps that of the largest conventional bomb of all times of 44,000 pounds experimentally detonated only once by the US in 1948 (http://www.airpower.au.af.mil/airchronicles/aureview/1967/mar-apr/coker.html). Risk appetite continued in the week of Aug 3, 2012, in expectation of purchases of sovereign bonds by the ECB. Growth of China’s exports by 1.0 percent in the 12 months ending in Jul 2012 released in the week of Aug 10, 2012, together with doubts on the purchases of bonds by the ECB injected a mild dose of risk aversion. There was optimism on the resolution of the European debt crisis on Aug 17, 2012. The week of Aug 24, 2012 had alternating shocks of risk aversion and risk appetite from the uncertainties of success of the Greek adjustment program, the coming decision of the Federal Constitutional Court of Germany on the European Stability Mechanism, disagreements between the Deutsche Bundesbank and the European Central Bank on purchase of sovereign bonds of highly indebted euro area member countries and the exchange of letters between Darrell E. Issa (2012Aug1), Chairman of the House Committee on Oversight and Government Reform, and Chairman Bernanke (2012Aug22) on monetary policy. Bernanke (2012JHAug31) and Draghi (2012Aug29) generated risk enthusiasm in the week of Aug 31, 2012. Risk appetite returned in the week of Sep 7, 2012, with the announcement of the bond-buying program of OMT (Outright Monetary Transactions) on Sep 6, 2012, by the European Central Bank (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html). Valuations of risk financial assets increased sharply after the statement of the FOMC on Sep 13, 2012 with open-ended quantitative easing and self-imposed single-mandate of jobs that would maintain easing monetary policy well after the economy returns to full potential. Risk aversion returned in the week of Sep 21, 2012 on doubts about the success of quantitative easing and weakness in flash purchasing managers’ indices. Risk aversion returned in the week of Sep 28, 2012, because of uncertainty on the consequences of a bailout of Spain and weakness of central banks in controlling financial turbulence but was followed by risk appetite in the week of Oct 5 and risk aversion in the week of Oct 12. The highest valuations in column “∆% Trough to 10/12/12” are by US equities indexes: DJIA 37.6 percent and S&P 500 39.7 percent, driven by stronger earnings and economy in the US than in other advanced economies but with doubts on the relation of business revenue to the weakening economy and fractured job market. The DJIA reached 13,703.53 on Oct 5, 2012, which is the highest level in 52 weeks (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata). The carry trade from zero interest rates to leveraged positions in risk financial assets had proved strongest for commodity exposures but US equities have regained leadership. Before the current round of risk aversion, almost all assets in the column “∆% Trough to 10/12/12” had double digit gains relative to the trough around Jul 2, 2010 but now some valuations of equity indexes show varying increases: China’s Shanghai Composite is 11.7 percent below the trough; Japan’s Nikkei Average is 3.3 percent below the trough; DJ Asia Pacific TSM is 7.7 percent above the trough; Dow Global is 12.6 percent above the trough; STOXX 50 of 50 blue-chip European equities (http://www.stoxx.com/indices/index_information.html?symbol=sx5E) is 10.0 percent above the trough; and NYSE Financial is 13.1 percent above the trough. DJ UBS Commodities is 18.5 percent above the trough. DAX index of German equities (http://www.bloomberg.com/quote/DAX:IND) is 27.5 percent above the trough. Japan’s Nikkei Average is 3.3 percent below the trough on Aug 31, 2010 and 25.1 percent below the peak on Apr 5, 2010. The Nikkei Average closed at 8534.12 on Fri Oct 12, 2012 (http://professional.wsj.com/mdc/public/page/marketsdata.html?mod=WSJ_PRO_hps_marketdata), which is 16.8 percent lower than 10,254.43 on Mar 11, 2011, on the date of the Tōhoku or Great East Japan Earthquake/tsunami. Global risk aversion erased the earlier gains of the Nikkei. The dollar depreciated by 8.7 percent relative to the euro and even higher before the new bout of sovereign risk issues in Europe. The column “∆% week to 10/12/12” in Table ESVI-1 shows that there were decreases of valuations of risk financial assets in the week of Oct 12, 2012 such as 2.0 percent for Dow Global, 1.6 percent for NYSE Financial, 1.5 percent for STOXX 50, 2.2 percent for DAX, 1.5 percent for DJ Asia Pacific TSM. Nikkei Average fell 3.7 percent in the week. DJ UBS Commodities decreased 0.6 percent. China’s Shanghai Composite increased 0.9 percent in the week of Oct 12, 2012. The DJIA decreased 2.1 percent and S&P 500 decreased 2.2 percent. The USD appreciated 0.6 percent. There are still high uncertainties on European sovereign risks and banking soundness, US and world growth slowdown and China’s growth tradeoffs. Sovereign problems in the “periphery” of Europe and fears of slower growth in Asia and the US cause risk aversion with trading caution instead of more aggressive risk exposures. There is a fundamental change in Table ESVI-1 from the relatively upward trend with oscillations since the sovereign risk event of Apr-Jul 2010. Performance is best assessed in the column “∆% Peak to 10/12/12” that provides the percentage change from the peak in Apr 2010 before the sovereign risk event to Oct 12, 2012. Most risk financial assets had gained not only relative to the trough as shown in column “∆% Trough to 10/12/12” but also relative to the peak in column “∆% Peak to 10/12/12.” There are now only three equity indexes above the peak in Table ESVI-1: DJIA 18.9 percent, S&P 500 17.4 percent and DAX 14.2 percent. There are several indexes below the peak: NYSE Financial Index (http://www.nyse.com/about/listed/nykid.shtml) by 9.9 percent, Nikkei Average by 25.1 percent, Shanghai Composite by 33.5 percent, DJ Asia Pacific by 5.7 percent, STOXX 50 by 6.9 percent and Dow Global by 8.1 percent. DJ UBS Commodities Index is now 1.3 percent above the peak. The US dollar strengthened 14.4 percent relative to the peak. The factors of risk aversion have adversely affected the performance of risk financial assets. The performance relative to the peak in Apr 2010 is more important than the performance relative to the trough around early Jul 2010 because improvement could signal that conditions have returned to normal levels before European sovereign doubts in Apr 2010. An intriguing issue is the difference in performance of valuations of risk financial assets and economic growth and employment. Paul A. Samuelson (http://www.nobelprize.org/nobel_prizes/economics/laureates/1970/samuelson-bio.html) popularized the view of the elusive relation between stock markets and economic activity in an often-quoted phrase “the stock market has predicted nine of the last five recessions.” In the presence of zero interest rates forever, valuations of risk financial assets are likely to differ from the performance of the overall economy. The interrelations of financial and economic variables prove difficult to analyze and measure.

Table ESVI-1, Stock Indexes, Commodities, Dollar and 10-Year Treasury

	Peak	Trough	∆% to Trough	∆% Peak to 10/12/ /12	∆% Week 10/12/12	∆% Trough to 10/12/ 12
DJIA	4/26/ 10	7/2/10	-13.6	18.9	-2.1	37.6
S&P 500	4/23/ 10	7/20/ 10	-16.0	17.4	-2.2	39.7
NYSE Finance	4/15/ 10	7/2/10	-20.3	-9.9	-1.6	13.1
Dow Global	4/15/ 10	7/2/10	-18.4	-8.1	-2.0	12.6
Asia Pacific	4/15/ 10	7/2/10	-12.5	-5.7	-1.5	7.7
Japan Nikkei Aver.	4/05/ 10	8/31/ 10	-22.5	-25.1	-3.7	-3.3
China Shang.	4/15/ 10	7/02 /10	-24.7	-33.5	0.9	-11.7
STOXX 50	4/15/10	7/2/10	-15.3	-6.9	-1.5	10.0
DAX	4/26/ 10	5/25/ 10	-10.5	14.2	-2.2	27.5
Dollar Euro	11/25 2009	6/7 2010	21.2	14.4	0.6	-8.7
DJ UBS Comm.	1/6/ 10	7/2/10	-14.5	1.3	-0.6	18.5
10-Year T Note	4/5/ 10	4/6/10	3.986	1.663

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

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

IA 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 by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (http://cmpassocregulationblog.blogspot.com/2012/10/twenty-nine-million-unemployed-or.html). Lazear and Spletzer (2012Mar, 1) argue that reductions of churn reduce the operational effectiveness of labor markets. Churn is part of the allocation of resources or in this case labor to occupations of higher marginal returns. The decline in churn can harm static and dynamic economic efficiency. Losses from decline of churn during recessions can affect an economy over the long-term by preventing optimal growth trajectories because resources are not used in the occupations where they provide highest marginal returns. Lazear and Spletzer (2012Mar 7-8) conclude that: “under a number of assumptions, we estimate that the loss in output during the recession [of 2007 to 2009] and its aftermath resulting from reduced churn equaled $208 billion. On an annual basis, this amounts to about .4% of GDP for a period of 3½ years.”

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

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

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

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):

Hiring in the nonfarm sector (HNF) has declined from 63.8 million in 2006 to 50.1 million in 2011 or by 13.7 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 I-1. The ratio of nonfarm hiring to employment (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. The collapse of hiring in the US has not been followed by dynamic labor markets because of the low rate of economic growth of 2.2 percent in the first twelve quarters of expansion from IIIQ2009 to IIQ2012 compared with 6.2 percent in prior cyclical expansions (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html).

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

	HNF	Rate RNF	HP	Rate HP
2001	62,948	47.8	58,825	53.1
2002	58,583	44.9	54,759	50.3
2003	56,451	43.4	53,056	48.9
2004	60,367	45.9	56,617	51.6
2005	63,150	47.2	59,372	53.1
2006	63,773	46.9	59,494	52.1
2007	62,421	45.4	58,035	50.3
2008	55,166	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: Bureau of Labor Statistics http://www.bls.gov/jlt/data.htm

Chart I-1 provides the yearly levels of total nonfarm hiring (NFH) in Table I-1. The fall of hiring during the contraction of 2007 to 2009 was much stronger than in the shallow recession of 2001 with GDP contraction of only 0.4 percent from Mar 2001 (IQ2001) to Dec 2001 (IVQ 2001) compared with 4.7 percent contraction in the much longer recession from Dec 2007 (IVQ2007) to Jun 2009 (IIQ2009) (http://www.nber.org/cycles/cyclesmain.html http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html). Recovery is tepid.

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2011

Source: US Bureau of Labor Statistics

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

Chart I-2, US, Rate Total Nonfarm Hiring (HNF), Annual, 2001-2011

Source: US Bureau of Labor Statistics

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table I-2. There were much milder declines in 2002 of 6.9 percent and 3.6 percent in 2003 followed by strong rebounds of 6.9 percent in 2004 and 4.6 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.1 in 2007, 11.6 in 2008 and 15.9 percent in 2009. On a yearly basis, nonfarm hiring grew 4.8 percent in 2010 relative to 2009 and 3.0 percent in 2011.

Table I-2, US, Annual Total Nonfarm Hiring (HNF), Annual 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 I-3 plots yearly percentage changes of nonfarm hiring. Percentage declines after 2007 were quite sharp.

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

Source: US Bureau of Labor Statistics

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

Chart I-4, US, Total Private Hiring Level, Annual, 2001-2011

Source: US Bureau of Labor Statistics

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

Chart I-5, US, Rate Total Private Hiring, Annual, 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 Aug in the years from 2001 to 2012 in Table I-3. Hiring numbers are in thousands. There is some recovery in HNF from 4655 thousand (or 4.7 million) in Aug 2009 to 4655 thousand in Aug 2011 and 4843 thousand in Aug 2012 for cumulative gain of 12.9 percent. HP rose from 3736 thousand in Aug 2009 to 4154 thousand in Aug 2011 and 4345 thousand in Aug 2012 for cumulative gain of 16.3 percent. HNF has fallen from 5881 in Aug 2006 to 4843 in Aug 2012 or by 17.7 percent. HP has fallen from 5387 in Aug 2005 to 4345 in Aug 2012 or by 19.3 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 I-3, US, Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US in Thousands and in Percentage of Total Employment Not Seasonally Adjusted

	HNF	Rate RNF	HP	Rate HP
2001 Aug	5450	4.1	4894	4.4
2002 Aug	5198	4.0	4677	4.3
2003 Aug	4948	3.8	4589	4.2
2004 Aug	5501	4.2	5019	4.5
2005 Aug	5881	4.4	5387	4.8
2006 Aug	5735	4.2	5119	4.8
2007 Aug	5662	4.1	5020	4.4
2008 Aug	5025	3.7	4540	4.3
2009 Aug	4184	3.2	3736	3.9
2010 Aug	4287	3.3	3897	3.4
2011 Aug	4655	3.5	4154	3.6
2012 Aug	4843	3.6	4345	3.8

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

Chart I-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 not-seasonally adjusted (NSA) of 4786 in May 2010 until it surpassed it in with 4869 in Jun 2011 and after 4926 in May 2012. Nonfarm hiring fell again in Dec 2011 to 3038 from 3844 in Nov and to revised 3633 in Feb 2012, increasing to 4127 in Mar 2012, 4490 in Apr 2012, 4926 in May 2012, 4988 in Jun 2012, 4752 in Jul 2012 and 4843 in Aug 2012. Chart I-6 provides seasonally-adjusted (SA) monthly data. The number of seasonally-adjusted hires in Aug 2011 was 4221 thousand, increasing to revised 4444 thousand in Feb 2012, or 5.3 percent, but falling to revised 4335 thousand in Mar 2012 and 4213 in Apr 2012, or cumulative decline of 0.2 percent relative to Aug 2011, increasing to 4390 in Aug 2012 for cumulative increase of 2.7 percent from 4276 in Sep 2011. The number of hires not seasonally adjusted was 4655 in Aug 2011, falling to 3038 in Dec but increasing to 4072 in Jan 2012 and 4843 in Aug 2012. The number of nonfarm hiring not seasonally adjusted fell by 34.7 percent from 4655 in Aug 2011 to 3038 in Dec 2011 in a yearly-repeated seasonal pattern.

Chart I-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 I-7. Recovery in early 2010 was followed by decline and stabilization at a lower level but with stability in monthly SA estimates of 3.2 in Sep 2011 to 3.2 in Jan 2012, increasing to 3.4 in May 2012 and falling to 3.2 in both Jun and Jul 2012, increasing to 3.3 in Aug 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, 3.7 in both May and Jun 2012 and falling to 36 in both Jul and Aug 2012. Rates of nonfarm hiring NSA were in the range of 2.8 (Dec) to 4.5 (Jun) in 2006.

Chart I-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 I-8. Hiring private (HP) rose in 2010 followed by stability and renewed increase in 2011 followed by stationary series in 2012. The number of private hiring seasonally adjusted fell from 4002 thousand in Sep 2011 to 3889 in Dec 2011 or by 2.8 percent, increasing to 3945 in Jan 2012 or decline by 1.4 relative to the level in Sep 2011 but increasing to 4087 in Aug 2012 or higher by 2.1 percent relative to 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 3782 in Jan 2012 or decline of 8.4 percent relative to Sep 2011 but increasing to 4345 in Aug 2012 or 5.2 percent higher 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 Aug 2006 private hiring NSA was 5555, declining to 4293 in Jul 2011 or by 22.7 percent and to 4403 in Jul 2012 or lower by 20.7 percent relative to Jul 2006. Private hiring NSA fell from 5387 in Aug 2005 to 4345 in Aug 2012 or 19.3 percent. The conclusion is that private hiring in the US is around 20 percent below the hiring before the global recession. The main problem in recovery of the US labor market has been the low rate of growth of 2.2 percent in the eleven quarters of expansion of the economy from IIIQ2009 to IIQ2012 compared with average 6.2 percent in prior expansions from contractions (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

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

Source: US Bureau of Labor Statistics

Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data did not rise significantly above the peak in 2010. The rate seasonally adjusted fell from 3.6 in Sep 2011 to 3.5 in Dec 2011, increasing to 3.7 in Aug 2012. The rate not seasonally adjusted (NSA) fell from 3.8 in Sep 2011 to 2.6 in Dec 2011, increasing to 3.9 in Aug 2012. The NSA rate of private hiring fell from 4.8 in Jul 2006 to 3.4 in Jul 2009 but recovery was insufficient to only 3.9 in both Jul and Aug 2012.

Chart I-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 I-4 for the month of Aug from 2001 to 2012. The final column provides annual TNF LD for the years from 2001 to 2011. Nonfarm job openings fell from a peak of 4591 in Aug 2007 to 3624 in Aug 2012 or by 21.1 percent while the rate dropped from 3.2 to 2.7. Nonfarm layoffs and discharges (TNF LD) rose from 1741 in Aug 2006 to 2235 in Aug 2009 or by 28.4 percent. The annual data show layoffs and discharges rising from 21.2 million in 2006 to 26.8 million in 2009 or by 26.4 percent.

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

	TNF JOB	TNF JOB Rate	TNF LD	TNF LD Annual
Aug 2001	4154	3.1	1971	24499
Aug 2002	3416	2.6	1930	22922
Aug 2003	3178	2.4	2159	23294
Aug 2004	3649	2.7	2139	22802
Aug 2005	4144	3.0	2016	22185
Aug 2006	4584	3.3	1741	21157
Aug 2007	4591	3.2	1990	22142
Aug 2008	3746	2.7	2246	24166
Aug 2009	2330	1.8	2235	26783
Aug 2010	2975	2.2	1955	21784
Aug 2011	3216	2.4	1866	20718
Aug 2012	3624	2.7	1940

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

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

Chart I-10 shows monthly job openings rising from the trough in 2009 to a high in the beginning of 2010. Job openings then stabilized into 2011 but have surpassed the peak of 3057 seasonally adjusted in Nov 2010 with 3561 seasonally adjusted in Aug 2012, which is higher by 1.7 percent than 3501 in Sep 2011 and lower by 4.3 percent relative to 3722 in Jun 2012 and lower by 0.9 percent relative to 3593 in Jul 2012. The high of job openings not seasonally adjusted in 2010 was 3221 in Oct 2010 that was surpassed by 3659 in Oct 2011, decreasing to 3624 in Aug 2012. The level of job openings not seasonally adjusted fell to 2912 in Nov 2011 or by 17.9 percent relative to 3546 in Sep 2011. There is here again the strong seasonality of year-end labor data. Job openings NSA fell from 4678 in Oct 2006 to 2547 in Oct 2009 or by 45.6 percent, recovering to 3221 in Oct 2010 or by 26.5 percent, which is still 21.8 percent lower at 3659 in Oct 2011 relative to Oct 2006. The level of job openings of 3624 in Aug 2012 NSA is lower by 21.1 percent relative to 4591 in Aug 2007. Again, the main problem in recovery of the US labor market has been the low rate of growth of 2.2 percent in the eleven quarters of expansion of the economy since IIIQ2009 compared with average 6.2 percent in prior expansions from contractions (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html). The US missed the opportunity to recover employment as in past cyclical expansions from contractions.

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

Source: US Bureau of Labor Statistics

The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted rose from 2.1 percent in Jan 2011 to 2.6 percent in Dec 2011 and 2.6 in Aug 2012. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 2.7 in Jul 2011 and 2.7 in all months from Jan to Jun 2012 with exception of 2.5 in Feb 2012 and then to 2.9 in Jul 2012 but back to 2.7 in Aug 2012. The rate of job openings NSA fell from 3.3 in Aug 2005 to 1.8 in Aug 2009, recovering insufficiently to 2.7 in Aug 2012.

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

Source: US Bureau of Labor Statistics

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

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

Source: US Bureau of Labor Statistics

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

Chart I-13, US, Total Separations, Annual, 2001-2011

Source: US Bureau of Labor Statistics

Table I-5 provides total nonfarm total separations from 2001 to 2011. Separations fell from 61.6 million in 2006 to 47.6 million in 2010 or by 14.0 million and 48.2 million in 2011 or by 13.4 million.

Table I-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 I-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business.

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

Source: US Bureau of Labor Statistics

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

Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2011

Source: US Bureau of Labor Statistics

Table I-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 2011, by 6.1 million, or 22.8 percent.

Table I-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

IA2 Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table I-7. The most comprehensive measure is U6 that consists of total unemployed plus total employed part time for economic reasons plus all marginally attached workers as percent of the labor force. U6 not seasonally annualized has risen from 8.2 percent in 2006 to 14.7 percent in Sep 2012.

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

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

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

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

Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.2 percent in Aug 2011 to 16.4 percent in Sep 2011 and then fell to 14.5 percent in Apr 2012, increasing to 15.0 percent in Jul 2012 and 14.7 percent in both Aug and Sep 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 28.7 million in job stress of unemployment/underemployment in Jul 2012, not seasonally adjusted, corresponding to 17.8 percent of the labor force (Table I-4 http://cmpassocregulationblog.blogspot.com/2012/10/twenty-nine-million-unemployed-or.html).

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

	U1	U2	U3	U4	U5	U6
Sep 2012	4.3	4.2	7.8	8.3	9.3	14.7
Aug	4.4	4.5	8.1	8.6	9.6	14.7
Jul	4.5	4.6	8.3	8.8	9.7	15.0
Jun	4.6	4.6	8.2	8.7	9.7	14.9
May	4.6	4.5	8.2	8.7	9.6	14.8
Apr	4.5	4.4	8.1	8.7	9.5	14.5
Mar	4.6	4.5	8.2	8.7	9.6	14.5
Feb	4.8	4.7	8.3	8.9	9.8	14.9
Jan	4.9	4.7	8.3	8.9	9.9	15.1
Dec 2011	5.0	4.9	8.5	9.1	10.0	15.2
Nov	5.0	4.9	8.7	9.3	10.2	15.6
Oct	5.1	5.1	8.9	9.5	10.4	16.0
Sep	5.3	5.2	9.0	9.6	10.5	16.4
Aug	5.3	5.3	9.1	9.6	10.6	16.2
Jul	5.3	5.3	9.1	9.7	10.7	16.1
Jun	5.3	5.4	9.1	9.7	10.7	16.2
May	5.3	5.4	9.0	9.5	10.3	15.8
Apr	5.2	5.3	9.0	9.6	10.4	15.9
Mar	5.3	5.4	8.9	9.4	10.3	15.7
Feb	5.4	5.4	9.0	9.6	10.6	15.9
Jan	5.5	5.5	9.1	9.7	10.7	16.1

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

Chart I-16 provides U6 on a monthly basis from 2001 to 2012. There was a steep climb from 2007 into 2009 and then this measure of unemployment and underemployment stabilized at that high level but declined into 2012. The low of U16 SA was 7.9 percent in Dec 2006 and the peak was 17.2 percent in Oct 2009. The low NSA was 7.6 percent in Oct 2006 and the peak was 18.0 percent in Jan 2010.

Chart I-16, US, U6, total unemployed, plus all marginally attached workers, plus total employed part Month, SA, 2001-2012

Source: US Bureau of Labor Statistics

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

Chart I-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 8.031 million in Aug 2012, seasonally adjusted, or decline of 1.024 million in nine months, as shown in Table I-9, but then rebounded to 8.164 million in Sep 2012 for increase of 582,000 in one month from Aug to Sep 2012. The number employed full-time increased from 112.479 million in Sep 2011 to 115.290 million in Mar 2012 or 2.811 million but then fell to 114.212 million in May 2012 or 1.078 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.388 million in Aug 2012 to 115.226 in Sep 2012 or increase of 838,000 full-time jobs in one month. There is a jump in the level of full-time SA to 114.573 million in Jun 2012 or 361,000 relative to May 2012 but then decline to 114.345 million in Jul 2012 or decline of 228,000 full time jobs from Jun 2012 into Jul 2012 and further decline to 114.388 million in Aug 2012 or decline of 185,000 full-time jobs relative to Jun 2012. The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.0151 million and to 7.694 million in Apr 2012 or 1.224 million fewer relative to Jan 2012. In Aug 2012, the number employed part-time for economic reasons reached 7.842 million NSA or 148,000 more than in Apr 2012. The number employed part-time for economic reasons increased from 7.842 million in Aug 2012 to 8.110 million in Sep 2012 or by 3.4 percent. The number employed full time without seasonal adjustment fell from 113.138 million in Nov 2011 to 113.050 million in Dec 2011 or by 88,000 and fell further to 111.879 in Jan 2012 for cumulative decrease of 1.259 million. The number employed full-time not seasonally adjusted fell from 113.138 million in Nov 2011 to 112.587 million in Feb 2012 or by 551.000 but increased to 116.214 million in Aug 2012 or 3.076 million more full-time jobs than in Nov 2011. The number employed full-time not seasonally adjusted decreased from 116.214 million in Aug 2012 to loss of 536,000 full-time jobs. Comparisons over long periods require use of NSA data. The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in Sep 2012 is 115.678 million, which is lower by 7.541 million relative to the peak of 123.219 million in Jul 2007. There appear to be around 10 million fewer full-time jobs in the US than before the global recession. Growth at 2.2 percent on average in the eleven quarters of expansion from IIIQ2009 to IIQ2012 compared with 6.2 percent on average in expansions from postwar cyclical contractions is the main culprit of the fractured US labor market (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html).

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

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Sep 2012	8,613	115.226
Aug 2012	8,031	114.388
Jul 2012	8,246	114.345
Jun 2012	8,210	114.573
May 2012	8,098	114.212
Apr 2012	7,853	114.478
Mar 2012	7,672	115.290
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
Jul 2011	8,437	112.006
Not Seasonally Adjusted
Sep 2012	8,110	115.678
Aug 2012	7,842	116.214
Jul 2012	8,316	116.131
Jun 2012	8,394	116.024
May 2012	7,837	114.634
Apr 2012	7,694	113.999
Mar 2012	7,867	113.916
Feb 2012	8,455	112.587
Jan 2012	8,918	111.879
Dec 2011	8,428	113.050
Nov 2011	8,271	113.138
Oct 2011	8,258	113.456
Sep 2011	8,541	112.980
Aug 2011	8,604	114.286
Jul 2011	8,514	113.759
Jun 2011	8,738	113.255
May 2011	8,270	112.618
Apr 2011	8,425	111.844
Mar 2011	8,737	111.186
Feb 2011	8,749	110.731
Jan 2011	9,187	110.373
Dec 2010	9,205	111.207
Nov 2010	8,670	111.348
Oct 2010	8,408	112.342
Sep 2010	8,628	112.385
Aug 2010	8,628	113.508
Jul 2010	8,737	113.974
Jun 2010	8,867	113.856
May 2010	8,513	112.809
Apr 2010	8,921	111.391
Mar 2010	9,343	109.877
Feb 2010	9,282	109.100
Jan 2010	9,290	108.777 (low)
Dec 2009	9,354 (high)	109.875
Sep 2009	8,255	111.991
Aug 2009	8,835	113.863
Jul 2009	9,103	114.184
Jun 2009	9,301	114.014
May 2009	8,785	113.083
Apr 2009	8,648	112.746
Mar 2009	9,305	112.215
Feb 2009	9,170	112.947
Jan 2009	8,829	113.815
Sep 2008	5,701	120.213
Aug 2008	5,736	121.556
Jul 2008	6,054	122.378
Jun 2008	5,697	121.845
May 2008	5,096	120.809
Apr 2008	5,071	120.027
Mar 2008	5,038	119.875
Feb 2008	5,114	119.452
Jan 2008	5,340	119.322
Sep 2007	4,137	121.278
Aug 2007	4,494	122.870
Jul 2007	4,516	123.219 (high)
Jun 2007	4,469	122.150
May 2007	4,315	120.846
Apr 2007	4,205	119.609
Mar 2007	4,384	119.640
Feb 2007	4,417	119.041
Jan 2007	4,726	119.094
Sep 2006	3,735 (low)	120.780
Aug 2006	4,104	121.979
Jul 2006	4,450	121.951
Jun 2006	4,456	121.070
May 2006	3,968	118.925
Apr 2006	3,787	118.559
Mar 2006	4,097	117.693
Feb 2006	4,403	116.823
Jan 2006	4,597	116.395

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

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

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

Sources: US Bureau of Labor Statistics

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

Chart I-19, US, Marginally Attached to the Labor Force, NSA Month 2001-2012

Sources: US Bureau of Labor Statistics

IA3 Ten Million Fewer Full-time Jobs. Chart I-20 reveals the fracture in the US labor market. The number of workers with full-time jobs not-seasonally-adjusted rose with fluctuations from 2002 to a peak in 2007, collapsing during the global recession. The terrible state of the job market is shown in the segment from 2009 to 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 I-20, US, Full-time Employed, Thousands, NSA, 2001-2012

Sources: US Bureau of Labor Statistics

IA4 Youth Unemployment and Middle-Aged Unemployment. The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.9 million in Jul 2006. There are two hardships behind these data. First, young people cannot find employment after finishing high-school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

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

Year	May	Jun	Jul	Aug	Sep	Annual
2001	19648	21212	22042	20529	19706	20088
2002	19484	20828	21501	20653	19466	19683
2003	19032	20432	20950	20181	18909	19351
2004	19237	20587	21447	20660	19158	19630
2005	19356	20949	21749	20814	19503	19770
2006	19769	21268	21914	21167	19604	20041
2007	19457	21098	21717	20413	19498	19875
2008	19254	20466	21021	20096	18818	19202
2009	17588	18726	19304	18270	16972	17601
2010	17039	17920	18564	18061	16874	17077
2011	17045	18180	18632	18067	17238	17362
2012	17681	18907	19461	18171	17687

Sources: US Bureau of Labor Statistics

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

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2012

Sources: US Bureau of Labor Statistics

Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million. This situation may persist for many years.

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

Year	May	Jun	Jul	Aug	Sep	Oct	Annual
2001	2171	2775	2585	2461	2301	2424	2371
2002	2568	3167	3034	2688	2506	2468	2683
2003	2838	3542	3200	2724	2698	2522	2746
2004	2684	3191	3018	2585	2493	2572	2638
2005	2619	3010	2688	2519	2339	2285	2521
2006	2254	2860	2750	2467	2297	2252	2353
2007	2203	2883	2622	2388	2419	2258	2342
2008	2952	3450	3408	2990	2904	2842	2830
2009	3851	4653	4387	4004	3774	3789	3760
2010	3854	4481	4374	3903	3604	3731	3857
2011	3628	4248	4110	3820	3541	3386	3634
2012	3438	4180	4011	3672	3174

Sources: US Bureau of Labor Statistics

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

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2012

Sources: US Bureau of Labor Statistics

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

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

Year	Apr	May	Jun	Jul	Aug	Sep	Annual
2002	11.6	11.6	13.2	12.4	11.5	11.4	12.0
2003	12.0	13.0	14.8	13.3	11.9	12.5	12.4
2004	11.1	12.2	13.4	12.3	11.1	11.5	11.8
2005	11.2	11.9	12.6	11.0	10.8	10.7	11.3
2006	9.7	10.2	11.9	11.2	10.4	10.5	10.5
2007	9.7	10.2	12.0	10.8	10.5	11.0	10.5
2008	10.3	13.3	14.4	14.0	13.0	13.4	12.8
2009	15.8	18.0	19.9	18.5	18.0	18.2	17.6
2010	18.5	18.4	20.0	19.1	17.8	17.6	18.4
2011	16.5	17.5	18.9	18.1	17.5	17.0	17.3
2012	15.4	16.3	18.1	17.1	16.8	15.2

Sources: US Bureau of Labor Statistics

Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2002 to 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 twelve consecutive quarters of expansion of the economy since IIIQ2009 because of much lower growth at 2.2 percent annual equivalent on average compared with 6.2 percent on average in cyclical expansions since World War II Table I -5 (http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html).

Chart I-23, US, Unemployment Rate 16-24 Years, Thousands, NSA, 2001-2012

Sources: US Bureau of Labor Statistics

Chart I-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 NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984 while the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 18.2 percent in Sep 2009, 17.6 percent in Sep 2010, 17.0 percent in Sep 2011 and 15.2 percent in Sep 2012. The difference originates in the vigorous seasonally-adjusted annual equivalent average rate of GDP growth of 5.7 percent during the recovery from IQ1983 to IVQ1985 compared with 2.2 percent on average during the first eleven quarters of expansion from IIIQ2009 to IIQ2012 (see table I-5 in http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html). The fractured US labor market denies an early start for young people.

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2012

Sources: US Bureau of Labor Statistics

It is more difficult to move to other jobs after a certain age because of fewer available opportunities for matured individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.985 million in Jul 2006 to 4.821 million in July 2010 or by 142.9 percent. The number of unemployed ages 45 years and over declined to 4.405 million in Jul 2012 that is still higher by 121.9 percent than in Jul 2006. The number unemployed age 45 and over jumped from 1.869 million in Aug 2006 to 5.128 million in Aug 2010 or 174.4 percent and at 4.179 million in Aug 2012 is higher by 2.310 million or 123.6 percent than 1.869 million in Aug 2006. The number unemployed ages 45 and over increased from 1.710 million in Sep 2006 to 4.640 million in Sep 2010, which is higher by 2.930 million or 161.1 percent, declining to 3.899 million in Sep 2012, which is higher by 2.189 million or 128.0 percent than in Sep 2006.

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

Year	Apr	May	Jun	Jul	Aug	Sep	Annual
2001	1421	1259	1371	1539	1640	1586	1576
2002	2101	1999	2190	2173	2114	1966	2114
2003	2287	2112	2212	2281	2301	2157	2253
2004	2160	2025	2182	2116	2082	1951	2149
2005	1939	1844	1868	2119	1895	1992	2009
2006	1843	1784	1813	1985	1869	1710	1848
2007	1871	1803	1805	2053	1956	1854	1966
2008	2104	2095	2211	2492	2695	2595	2540
2009	4172	4175	4505	4757	4683	4560	4500
2010	4770	4565	4564	4821	5128	4640	4879
2011	4373	4356	4559	4772	4592	4426	4537
2012	4037	4083	4084	4405	4179	3899

Sources: US Bureau of Labor Statistics

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

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2012

Sources: US Bureau of Labor Statistics

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

IB Collapse of United States Dynamism of Income Growth and Employment Creation. This blog has analyzed systematically the weakness of the United States recovery in the current business cycle from IIIQ2009 to the present in comparison with the recovery from the recessions in the 1980s from IQ1983 to IVQ1985. The United States has grown on average at 2.2 percent annual equivalent in the 12 quarters of expansion since IIIQ2009 while growth was 6.2 percent on average in recoveries after World War II and 5.7 percent from IQ1983 to IVQ1985. The conventional explanation is that the recession from IVQ2007 (Dec) to IIQ2009 (Jun) was so profound that it caused subsequent weak recovery and that historically growth after recessions with financial crises has been weaker. Michael D. Bordo (2012Sep27) and Bordo and Haubrich (2012DR) provide evidence contradicting the conventional explanation: recovery is much stronger on average after profound contractions and also much stronger after recessions with financial crises than after recessions without financial crises. Insistence on the conventional explanation prevents finding policies that can accelerate growth, employment and prosperity.

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

Table IB-1 provides the data required for broader comparison of the cyclical expansions of IQ1983 to IVQ1985 and the current one from 2009 to 2012. First, in the 13 quarters from IQ1983 to IVQ1985, GDP increased 19.6 percent at the annual equivalent rate of 5.7 percent; real disposable personal income (RDPI) increased 14.5 percent at the annual equivalent rate of 4.3 percent; RDPI per capita increased 11.5 percent at the annual equivalent rate of 3.4 percent; and population increased 2.7 percent at the annual equivalent rate of 0.8 percent. Second, in the 12 quarters of the current cyclical expansion from IIIQ2009 to IIQ2012, GDP increased 6.7 percent at the annual equivalent rate of 2.2 percent; real disposable personal income (RDPI) increased 3.8 percent at the annual equivalent rate of 1.3 percent; RDPI per capita increased 1.4 percent at the annual equivalent rate of 0.5 percent; and population increased 2.3 percent at the annual equivalent rate of 0.8 percent. Third, since the beginning of the recession in IVQ2007 to IIQ2012, GDP increased 1.7 percent, or barely above the level before the recession; real disposable personal income increased 3.5 percent; population increased 3.7 percent; and real disposable personal income per capita is 0.2 percent lower than the level before the recession. Real disposable personal income is the actual take home pay after inflation and taxes and real disposable income per capita is what is left per inhabitant. The current cyclical expansion is the worst in the period after World War II in terms of growth of economic activity and income. The United States grew during its history at high rates of per capita income that made its economy the largest in the world. That dynamism is disappearing. Bordo (2012 Sep27) and Bordo and Haubrich (2012DR) provide strong evidence that recoveries have been faster after deeper recessions and recessions with financial crises, casting serious doubts on the conventional explanation of weak growth during the current expansion allegedly because of the depth of the contraction from IVQ2007 to IIQ2009 of 4.7 percent and the financial crisis.

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

	# Quarters	∆%	∆% Annual Equivalent
IQ1983 to IVQ1985	13
GDP		19.6	5.7
RDPI		14.5	4.3
RDPI Per Capita		11.5	3.4
Population		2.7	0.8
IIIQ2009 to IIQ2012	12
GDP		6.7	2.2
RDPI		3.8	1.3
RDPI per Capita		1.4	0.5
Population		2.3	0.8
IVQ2007 to IIQ2012	19
GDP		1.7	0.4
RDPI		3.5	0.7
RDPI per Capita		-0.2
Population		3.7	0.8

RDPI: Real Disposable Personal Income

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

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

1. Trend Growth.

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

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

Period IVQ2007 to IIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIQ2012	13,548.5
∆% IVQ2007 to IIQ2012 Actual	1.7
∆% IVQ2007 to IIQ2012 Trend	14.2

2. Decline of Per Capita Real Disposable Income

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

Period IQ1980 to IVQ1985

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

Period IVQ2007 to IIQ2012

Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIQ2012 Chained 2005 USD	32,779
∆% IVQ2007 to IIQ2012	-0.2
∆% Trend Growth	9.3

3. Number of Employed Persons

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

Period IQ1980 to IVQ1985

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

Period IVQ2007 to IIQ2012

Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIQ2012 NSA End of Quarter	143.202
∆% Employed IVQ2007 to IIQ2012	-2.1

4. Number of Full-Time Employed Persons

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

Period IQ1980 to IVQ1985

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

Period IVQ2007 to IIQ2012

Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIQ2012 NSA End of Quarter	116.024
∆% Full-time Employed IVQ2007 to IIQ2012	-4.1

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

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

Period IQ1980 to IVQ1985

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

Period IVQ2007 to IIQ2012

Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIQ2012 NSA End of Quarter	8.4
Unemployed IVQ2007 Millions End of Quarter	7.371
Unemployed IIQ2009 Millions End of Quarter	13.184
∆%	78.9
Employed Part-time Economic Reasons IVQ2007 Millions End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 End of Quarter	8.394
∆%	76.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007 Dec	8.7
IIQ2012	14.2

6. Wealth of Households and Nonprofit Organizations.

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

ii. In contrast, as shown in the following block and in Table IB-2, net worth of households and nonprofit organizations fell from $66,057.1 billion in IVQ2007 to $62,668.4 billion in IIQ2012 by $3,388.7 billion or 5.1 percent. The US consumer price index was 210.036 in Dec 2007 and 229.478 in Jun 2012 for increase of 9.3 percent. In purchasing power of Dec 2007, wealth of households and nonprofit organizations is lower by 13.2 percent in Jun 2012 after 12 consecutive quarters of expansion from IIIQ2009 to IIQ2012 relative to IVQ2012 when the recession began. The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. The average growth rate from IIIQ2009 to IIQ2012 has been 2.2 percent, which is substantially lower than the average of 6.2 percent in cyclical expansions after World War II and 5.7 percent in the expansion from IQ1983 to IVQ1985 (see Table I-5 http://cmpassocregulationblog.blogspot.com/2012/09/historically-sharper-recoveries-from.html). The US missed the opportunity of high growth rates that has been available in past cyclical expansions.

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

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


Period IQ1980 to IVQ1985
GDP SAAR USD Billions
IQ1980	5,903.4
IVQ1985	6,950.0
∆% IQ1980 to IVQ1985	17.7
∆% Trend Growth IQ1980 to IVQ1985	18.5
Real Disposable Personal Income per Capita IQ1980 Chained 2005 USD	18,938
Real Disposable Personal Income per Capita IVQ1985 Chained 2005 USD	21,687
∆% IQ1980 to IVQ1985	14.5
∆% Trend Growth	12.1
Employed Millions IQ1980 NSA End of Quarter	98.527
Employed Millions IV1985 NSA End of Quarter	107.819
∆% Employed IQ1980 to IV1985	9.4
Employed Full-time Millions IQ1980 NSA End of Quarter	81.280
Employed Full-time Millions IV1985 NSA End of Quarter	88.757
∆% Full-time Employed IQ1980 to IV1985	9.2
Unemployment Rate IQ1980 NSA End of Quarter	6.6
Unemployment Rate IV1985 NSA End of Quarter	6.7
Unemployed IQ1980 Millions NSA End of Quarter	6.983
Unemployed IV 1985 Millions NSA End of Quarter	7.717
∆%	11.9
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 NSA End of Quarter	8.394
∆%	76.7
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ1979	8,326.4
IVQ1985	14,395.2
∆ USD Billions	+6,068.8
Period IVQ2007 to IIQ2012
GDP SAAR USD Billions
IVQ2007	13,326.0
IIQ2012	13,548.5
∆% IVQ2007 to IIQ2012	1.7
∆% IVQ2007 to IIQ2012 Trend Growth	14.2
Real Disposable Personal Income per Capita IVQ2007 Chained 2005USD	32,837
Real Disposable Personal Income per Capita IIQ2012 Chained 2005 USD	32,779
∆% IVQ2007 to IIQ2012	-0.2
∆% Trend Growth	9.3
Employed Millions IVQ2007 NSA End of Quarter	146.334
Employed Millions IIQ2012 NSA End of Quarter	143.202
∆% Employed IVQ2007 to IIQ2012	-2.1
Employed Full-time Millions IVQ2007 NSA End of Quarter	121.042
Employed Full-time Millions IIQ2012 NSA End of Quarter	116.024
∆% Full-time Employed IVQ2007 to IIQ2012	-4.1
Unemployment Rate IVQ2007 NSA End of Quarter	4.8
Unemployment Rate IIQ2012 NSA End of Quarter	8.4
Unemployed IVQ2007 Millions NSA End of Quarter	7.371
Unemployed IIQ2009 Millions NSA End of Quarter	13.184
∆%	78.9
Employed Part-time Economic Reasons IVQ2007 Millions NSA End of Quarter	4.750
Employed Part-time Economic Reasons Millions IIQ2009 NSA End of Quarter	8.394
∆%	76.7
U6 Total Unemployed plus all marginally attached workers plus total employed part time for economic reasons as percent of all civilian labor force plus all marginally attached workers NSA
IVQ2007	8.7
IIQ2012	14.2
Net Worth of Households and Nonprofit Organizations USD Billions
IVQ2007	66,057.1
IIQ2012	62,668.4
∆ USD Billions	-3,388.7

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

IIA IMF View of World Economy and Finance. The International Financial Institutions (IFI) consist of the International Monetary Fund, World Bank Group, Bank for International Settlements (BIS) and the multilateral development banks, which are the European Investment Bank, Inter-American Development Bank and the Asian Development Bank (Pelaez and Pelaez, International Financial Architecture (2005), The Global Recession Risk (2007), 8-19, 218-29, Globalization and the State, Vol. II (2008b), 114-48, Government Intervention in Globalization (2008c), 145-54). There are four types of contributions of the IFIs:

1. Safety Net. The IFIs contribute to crisis prevention and crisis resolution.

i. Crisis Prevention. An important form of contributing to crisis prevention is by surveillance of the world economy and finance by regions and individual countries. The IMF and World Bank conduct periodic regional and country evaluations and recommendations in consultations with member countries and also jointly with other international organizations. The IMF and the World Bank have been providing the Financial Sector Assessment Program (FSAP) by monitoring financial risks in member countries that can serve to mitigate them before they can become financial crises.

ii. Crisis Resolution. The IMF jointly with other IFIs provides assistance to countries in resolution of those crises that do occur. Currently, the IMF is cooperating with the government of Greece, European Union and European Central Bank in resolving the debt difficulties of Greece as it has done in the past in numerous other circumstances. Programs with other countries involved in the European debt crisis may also be developed.

2. Surveillance. The IMF conducts surveillance of the world economy, finance and public finance with continuous research and analysis. Important documents of this effort are the World Economic Outlook of which the current one is IMF (2012WEOOct http://www.imf.org/external/pubs/ft/weo/2012/02/pdf/text.pdf), Global Financial Stability Report of which the current one is IMF (2012GFSROct http://www.imf.org/External/Pubs/FT/GFSR/2012/02/pdf/text.pdf) and Fiscal Monitor of which the current one is IMF (2012FMOct http://www.imf.org/external/pubs/ft/fm/2012/02/pdf/fm1202.pdf).

3. Infrastructure and Development. The IFIs also engage in infrastructure and development, in particular the World Bank Group and the multilateral development banks.

4. Soft Law. Significant activity by IFIs has consisted of developing standards and codes under multiple forums. It is easier and faster to negotiate international agreements under soft law that are not binding but can be very effective (on soft law see Pelaez and Pelaez, Globalization and the State, Vol. II (2008c), 114-25). These norms and standards can solidify world economic and financial arrangements.

The objective of this section is to analyze current projections of the IMF database for the most important indicators.

Table IIA-1 is constructed with the database of the IMF (http://www.imf.org/external/datamapper/index.php?db=WEO) to show GDP in dollars in 2011 and the growth rate of real GDP of the world and selected regional countries from 2012 to 2015. The data illustrate the concept often repeated of “two-speed recovery” of the world economy from the recession of 2007 to 2009. The IMF has lowered its forecast of the world economy to 3.3 percent in 2012 but accelerating to 3.6 percent in 2013, 4.2 percent in 2014 and 4.4 percent in 2015. Slow-speed recovery occurs in the “major advanced economies” of the G7 that account for $33,697 billion of world output of $69,899 billion, or 48.2 percent, but are projected to grow at much lower rates than world output, 1.9 percent on average from 2012 to 2015 in contrast with 3.9 percent for the world as a whole. While the world would grow 16.4 percent in the four years from 2012 to 2015, the G7 as a whole would grow 7.8 percent. The difference in dollars of 2011 is rather high: growing by 16.4 percent would add $11.5 trillion of output to the world economy, or roughly two times the output of the economy of Japan of $5,867 but growing by 7.8 percent would add $5.2 trillion of output to the world, or somewhat below the output of Japan in 2011. The “two speed” concept is in reference to the growth of the 150 countries labeled as emerging and developing economies (EMDE) with joint output in 2011 of $25,438 billion, or 36.4 percent of world output. The EMDEs would grow cumulatively 24.9 percent or at the average yearly rate of 5.7 percent, contributing $6.3 trillion from 2012 to 2015 or the equivalent of 86.8 percent of $7,298 billion of China in 2011. The final four countries in Table IIA-1 often referred as BRIC (Brazil, Russia, India, China), are large, rapidly growing emerging economies. Their combined output adds to $13,468 billion, or 19.3 percent of world output, which is equivalent to 39.9 percent of the combined output of the major advanced economies of the G7.

Table IIA-1, IMF World Economic Outlook Database Projections of Real GDP Growth

	GDP USD 2011	Real GDP ∆% 2012	Real GDP ∆% 2013	Real GDP ∆% 2014	Real GDP ∆% 2015
World	69,899	3.3	3.6	4.2	4.4
G7	33,697	1.4	1.5	2.2	2.5
Canada	1,739	1.9	2.0	2.4	2.4
France	2,778	0.1	0.4	1.1	1.5
DE	3,607	0.9	0.9	1.4	1.4
Italy	2,199	-2.3	-0.7	0.5	1.2
Japan	5,867	2.2	1.2	1.1	1.2
UK	2,431	-0.4	1.1	2.2	2.6
US	15,076	2.2	2.1	2.9	3.4
Euro Area	13,114	-0.4	0.2	1.2	1.5
DE	3,607	0.9	0.9	1.4	1.4
France	2,778	0.1	0.4	1.1	1.5
Italy	2,199	-2.3	-0.7	0.5	1.2
POT	238	-3.0	-1.0	1.2	1.9
Ireland	221	0.4	1.4	2.5	2.9
Greece	299	-6.0	-4.0	0.0	2.8
Spain	1,480	-1.5	-1.3	1.0	1.6
EMDE	25,438	5.3	5.6	5.9	6.1
Brazil	2,493	1.5	3.9	4.2	4.2
Russia	1,850	3.7	3.8	3.9	3.9
India	1,827	4.9	6.0	6.4	6.7
China	7,298	7.8	8.2	8.5	8.5

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries); POT: Portugal

Source: IMF World Economic Outlook databank http://www.imf.org/external/datamapper/index.php?db=WEO

Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (http://www.imf.org/external/datamapper/index.php?db=WEO). Table IIA-2 is constructed with the WEO database to provide rates of unemployment from 2011 to 2015 for major countries and regions. In fact, unemployment rates for 2011 in Table IIA-2 are high for all countries: unusually high for countries with high rates most of the time and unusually high for countries with low rates most of the time. Estimated rates of unemployment for 2012 are particularly high for the countries with sovereign debt difficulties in Europe: 15.5 percent for Portugal (POT), 14.8 percent for Ireland, 23.8 percent for Greece, 24.9 percent for Spain and 10.6 percent for Italy, which is lower but still high. The G7 rate of unemployment is estimated at 7.5 percent. Unemployment rates are not likely to decrease substantially if slow growth persists in advanced economies.

Table IIA-2, IMF World Economic Outlook Database Projections of Unemployment Rate as Percent of Labor Force

	% Labor Force 2011	% Labor Force 2012	% Labor Force 2013	% Labor Force 2014	% Labor Force 2015
World	NA	NA	NA	NA	NA
G7	7.7	7.5	7.5	7.3	6.9
Canada	7.5	7.3	7.3	7.1	6.9
France	9.6	10.1	10.5	10.3	9.8
DE	6.0	5.2	5.3	5.2	5.2
Italy	8.4	10.6	11.1	11.3	11.0
Japan	4.6	4.5	4.4	4.5	4.4
UK	8.0	8.1	8.1	7.9	7.6
US	8.9	8.2	8.1	7.7	7.1
Euro Area	10.2	11.2	11.5	11.2	10.8
DE	6.0	5.2	5.3	5.2	5.2
France	9.6	10.1	10.5	10.3	9.8
Italy	8.4	10.6	11.1	11.3	11.0
POT	12.7	15.5	16.0	15.3	14.7
Ireland	14.4	14.8	14.4	13.7	13.1
Greece	17.3	23.8	25.4	24.5	22.4
Spain	21.7	24.9	25.1	24.1	23.2
EMDE	NA	NA	NA	NA	NA
Brazil	6.0	6.0	6.5	7.0	7.0
Russia	6.5	6.0	6.0	6.0	6.0
India	NA	NA	NA	NA	NA
China	4.1	4.1	4.1	4.1	4.1

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)

Source: IMF World Economic Outlook databank http://www.imf.org/external/datamapper/index.php?db=WEO

The database of the WEO (http://www.imf.org/external/datamapper/index.php?db=WEO) is used to construct the debt/GDP ratios of regions and countries in Table IIA-3. The concept used is general government debt, which consists of central government debt, such as Treasury debt in the US, and all state and municipal debt. Net debt is provided for all countries except for gross debt for China, Russia and India. The net debt/GDP ratio of the G7 jumps from 84.1 in 2011 to 94.9 in 2015. G7 debt is pulled by the high debt of Japan that grows from 126.4 percent of GDP in 2011 to 152.4 percent of GDP in 2015. US general government debt grows from 80.3 percent of GDP in 2011 to 89.5 percent of GDP in 2015. Debt/GDP ratios of countries with sovereign debt difficulties in Europe are particularly worrisome. General government net debts of Italy, Ireland, Greece and Portugal exceed 100 percent of GDP or are expected to exceed 100 percent of GDP by 2015. The only country with relatively low debt/GDP ratio is Spain with 57.5 in 2011 but growing to 88.3 in 2015. Fiscal adjustment, voluntary or forced by defaults, may squeeze further economic growth and employment in many countries as analyzed by Blanchard (2012WEOApr). Defaults could feed through exposures of banks and investors to financial institutions and economies in countries with sounder fiscal affairs.

Table IIA-3, IMF World Economic Outlook Database Projections, General Government Net Debt as Percent of GDP

	% Debt/ GDP 2011	% Debt/ GDP 2012	% Debt/ GDP 2013	% Debt/ GDP 2014	% Debt/ GDP 2015
World	NA	NA	NA	NA	NA
G7	84.1	89.0	92.8	94.3	94.9
Canada	33.1	35.8	37.5	38.1	37.8
France	78.8	83.7	85.9	86.7	86.1
DE	55.3	58.4	57.5	56.2	56.2
Italy	99.6	103.1	103.9	103.7	102.4
Japan	126.4	135.4	144.7	148.7	152.4
UK	76.6	83.7	88.2	90.9	91.5
US	80.3	83.8	87.7	89.3	89.5
Euro Area	68.0	73.4	74.8	74.8	74.4
DE	55.3	58.4	57.5	56.2	56.2
France	78.8	83.7	85.9	86.7	86.1
Italy	99.6	103.1	103.9	103.7	102.4
POT	100.4	110.9	113.9	112.9	111.4
Ireland	94.9	103.0	107.6	108.7	107.2
Greece	165.4	170.7	181.8	180.2	173.9
Spain	57.5	78.6	84.4	87.3	88.3
EMDE	NA	NA	NA	NA	NA
Brazil	36.4	34.4	31.9	30.1	28.7
Russia*	11.9	11.0	9.9	10.8	11.5
India*	67.0	67.6	66.7	65.6	65.1
China*	25.8	22.2	19.6	17.3	14.9

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)

Source: IMF World Economic Outlook databank http://www.imf.org/external/datamapper/index.php?db=WEO

The primary balance consists of revenues less expenditures but excluding interest revenues and interest payments. It measures the capacity of a country to generate sufficient current revenue to meet current expenditures. Brazil is the only country in Table IIA-4 with sizeable surplus of primary net lending/borrowing of 3.1 percent in 2011 followed by 1.9 percent for Russia and smaller ones of 0.8 percent for Italy and 0.9 percent for Germany. Most countries in Table IIA-4 face significant fiscal adjustment in the future without “fiscal space.” Investors in government securities may require higher yields when the share of individual government debts hit saturation shares in portfolios. The tool of analysis of Cochrane (2011Jan, 27, equation (16)) is the government debt valuation equation:

(M_t + B_t)/P_t = E_t∫(1/R_t_{, t+τ})s_t_+τdτ (1)

Equation (1) expresses the monetary, M_t, and debt, B_t, liabilities of the government, divided by the price level, P_t, in terms of the expected value discounted by the ex-post rate on government debt, R_t_{, t+τ}, of the future primary surpluses s_t_+τ, which are equal to T_t_+τ – G_t_+τ or difference between taxes, T, and government expenditures, G. Cochrane (2010A) provides the link to a web appendix demonstrating that it is possible to discount by the ex post R_t_{, t+τ}. Expectations by investors of future primary balances of indebted governments may be less optimistic than those in Table IIA-4 because of government revenues constrained by low growth and government expenditures rigid because of entitlements. Political realities may also jeopardize structural reforms and fiscal austerity.

Table IIA-4, IMF World Economic Outlook Database Projections of Primary General Government Net Lending/Borrowing as Percent of GDP

	% GDP 2011	% GDP 2012	% GDP 2013	% GDP 2014	% GDP 2015
World	NA	NA	NA	NA	NA
G7	-5.7	-5.1	-4.1	-2.6	-1.7
Canada	-3.9	-3.2	-2.7	-1.9	-1.3
France	-2.7	-2.2	-1.1	-0.5	0.4
DE	0.9	1.4	1.3	1.3	1.2
Italy	0.8	2.6	3.6	3.9	4.2
Japan	-8.9	-9.1	-7.9	-5.7	-4.6
UK	-5.7	-5.6	-4.7	-3.0	-1.5
US	-7.8	-6.5	-5.1	-3.3	-2.2
Euro Area	-1.5	-0.5	0.2	0.7	1.2
DE	0.9	1.4	1.3	1.3	1.2
France	-2.7	-2.2	-1.1	-0.5	0.4
Italy	0.8	2.6	3.6	3.9	4.2
POT	-0.6	-0.7	-0.1	2.3	2.9
Ireland	-9.6	-4.4	-2.2	0.5	-2.5
Greece	-2.2	-1.7	0.0	1.5	3.0
Spain	-7.0	-4.5	-2.2	-0.8	0.1
EMDE*	-1.2	-1.4	-1.4	-1.4	-1.4
Brazil	3.1	2.7	3.2	3.1	3.1
Russia	1.9	1.1	0.9	0.1	-1.0
India	-4.8	-5.2	-4.8	-4.5	-4.3
China*	-1.2	-1.3	-1.0	-0.6	-0.1

*General Government Net Lending/Borrowing

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)

Source: IMF World Economic Outlook databank http://www.imf.org/external/datamapper/index.php?db=WEO

The database of the World Economic Outlook of the IMF (http://www.imf.org/external/datamapper/index.php?db=WEO) is used to obtain government net lending/borrowing as percent of GDP in Table IIA-5. Interest on government debt is added to the primary balance to obtain overall government fiscal balance in Table IIA-5. For highly indebted countries there is an even tougher challenge of fiscal consolidation. Adverse expectations on the success of fiscal consolidation may drive up yields on government securities that could create hurdles to adjustment, growth and employment.

Table IIA-5, IMF World Economic Outlook Database Projections of General Government Net Lending/Borrowing as Percent of GDP

	% GDP 2011	% GDP 2012	% GDP 2013	% GDP 2014	% GDP 2015
World	NA	NA	NA	NA	NA
G7	-7.8	-7.1	-6.1	-4.7	-4.0
Canada	-4.4	-3.8	-3.0	-2.2	-1.4
France	-5.2	-4.7	-3.5	-2.8	-2.1
DE	-0.8	-0.4	-0.4	-0.3	-0.1
Italy	-3.8	-2.7	-1.8	-1.6	-1.4
Japan	-9.8	-10.0	-9.1	-7.2	-6.3
UK	-8.5	-8.2	-7.3	-5.8	-4.3
US	-10.1	-8.7	-7.8	-5.6	-4.6
Euro Area	-4.1	-3.3	-2.6	-2.1	-1.6
DE	-0.8	-0.4	-0.4	-0.3	-0.1
France	-5.2	-4.7	-3.5	-2.8	-2.1
Italy	-3.8	-2.7	-1.8	-1.6	-1.4
POT	-4.2	-5.0	-4.5	-2.5	-1.9
Ireland	-9.6	-4.4	-2.2	0.5	2.5
Greece	-9.1	-7.5	-4.7	-3.4	-2.5
Spain	-8.9	-7.0	-5.7	-4.6	-3.9
EMDE	-1.2	-1.4	-1.4	-1.4	-1.4
Brazil	-2.6	-2.1	-1.6	-2.0	-1.9
Russia	1.6	0.5	0.2	-0.5	-1.6
India	-9.0	-9.5	-9.1	-8.9	-8.7
China	-1.2	-1.3	-1.0	-0.6	-0.1

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)

Source: IMF World Economic Outlook databank http://www.imf.org/external/datamapper/index.php?db=WEO

There were some hopes that the sharp contraction of output during the global recession would eliminate current account imbalances. Table I-6 constructed with the database of the WEO (http://www.imf.org/external/datamapper/index.php?db=WEO) shows that external imbalances have been maintained in the form of current account deficits and surpluses. China’s current account surplus is 2.8 percent of GDP for 2011 and is projected to climb to 3.2 percent of GDP in 2015. At the same time the current account deficit of the US is 3.1 percent of GDP and is projected to remain almost unchanged at 3.2 percent of GDP in 2015. The current account surplus of Germany is 5.7 percent of GDP for 2011 and remains at a high 4.4 percent of GDP in 2015. Japan’s current account surplus is 2.0 percent of GDP in 2011 and increases slightly to 2.4 percent of GDP in 2015.

Table IIA-6, IMF World Economic Outlook Databank Projections, Current Account of Balance of Payments as Percent of GDP

	% CA/ GDP 2011	% CA/ GDP 2012	% CA/ GDP 2013	% CA/ GDP 2014	% CA/ GDP 2015
World	NA	NA	NA	NA	NA
G7	-1.1	-1.3	-1.2	-1.2	-1.2
Canada	-2.8	-3.4	-3.7	-3.7	-3.5
France	-1.9	-1.7	-1.7	-1.6	-1.2
DE	5.7	5.4	4.7	4.4	4.4
Italy	-3.2	-1.5	-1.4	-1.3	-1.2
Japan	2.0	1.6	2.3	2.5	2.4
UK	-1.9	-3.3	-2.7	-2.2	-1.5
US	-3.1	-3.1	-3.1	-3.1	-3.2
Euro Area	0.4	1.1	1.3	1.4	1.5
DE	5.7	5.4	4.7	4.4	4.4
France	-1.9	-1.7	-1.7	-1.6	-1.2
Italy	-3.2	-1.5	-1.4	-1.3	-1.2
POT	-6.4	-2.9	-1.7	-1.2	-0.8
Ireland	1.1	1.8	2.7	3.7	3.8
Greece	-9.8	-5.8	-2.9	-2.6	-1.7
Spain	-3.5	-2.0	-0.1	0.7	1.3
EMDE	1.9	1.4	1.1	0.8	0.7
Brazil	-2.1	-2.6	-2.8	-3.3	-3.3
Russia	5.3	5.2	3.8	2.3	0.9
India	-3.4	-3.8	-3.3	-2.8	-2.5
China	2.8	2.3	2.5	2.8	3.2

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries)

Source: IMF World Economic Outlook databank http://www.imf.org/external/datamapper/index.php?db=WEO

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

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

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

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

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

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

In emerging Asia, particularly China, greater flexibility in exchange rates is critical to allow necessary appreciations, as is strengthening domestic demand, lessening reliance on export-led growth strategies, and actions to strengthen financial sectors.

In oil-producing countries, accelerated investment in capacity, increased economic diversification, enhanced exchange rate flexibility in some cases.

Other current account surplus countries should encourage domestic consumption and investment, increase micro-economic flexibility and improve investment climates.

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

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

The database of the WEO (http://www.imf.org/external/datamapper/index.php?db=WEO) is used to contract Table IIA-7 with fiscal and current account imbalances projected for 2012 and 2015. The WEO finds the need to rebalance external and domestic demand (IMF 2011WEOSep xvii):

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

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

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

Table IIA-7, Fiscal Deficit, Current Account Deficit and Government Debt as % of GDP and 2011 Dollar GDP

	GDP $B 2012	FD %GDP 2011	CAD %GDP 2011	Debt %GDP 2011	FD%GDP 2015	CAD%GDP 2015	Debt %GDP 2015
US	15653	-7.8	-3.1	80.3	-2.2	-3.2	89.5
Japan	5984	-8.9	2.0	126.4	-4.6	2.4	152.4
UK	2434	-5.7	-1.9	76.6	-1.5	-1.5	91.5
Euro	15653	-1.5	0.4	68.0	1.2	1.5	74.4
Ger	3366	0.9	5.7	55.3	1.2	4.4	56.2
France	2580	-2.7	-1.9	78.8	0.4	-1.2	86.1
Italy	1980	0.8	-3.2	99.6	4.2	-1.2	102.4
Can	1770	-3.9	-2.8	33.1	-1.3	-3.5	37.8
China	8250	-1.2	2.8	25.8	-0.1	3.2	14.9
Brazil	2425	3.1	-2.1	34.4	3.1	-3.3	28.7

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

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

Source: IMF World Economic Outlook databank http://www.imf.org/external/datamapper/index.php?db=WEO

Brazil faced in the debt crisis of 1982 a more complex policy mix. Between 1977 and 1983, Brazil’s terms of trade, export prices relative to import prices, deteriorated 47 percent and 36 percent excluding oil (Pelaez 1987, 176-79; Pelaez 1986, 37-66; see Pelaez and Pelaez, The Global Recession Risk (2007), 178-87). Brazil had accumulated unsustainable foreign debt by borrowing to finance balance of payments deficits during the 1970s. Foreign lending virtually stopped. The German mark devalued strongly relative to the dollar such that Brazil’s products lost competitiveness in Germany and in multiple markets in competition with Germany. The resolution of the crisis was devaluation of the Brazilian currency by 30 percent relative to the dollar and subsequent maintenance of parity by monthly devaluation equal to inflation and indexing that resulted in financial stability by parity in external and internal interest rates avoiding capital flight. With a combination of declining imports, domestic import substitution and export growth, Brazil followed rapid growth in the US and grew out of the crisis with surprising GDP growth of 4.5 percent in 1984.

The euro zone faces a critical survival risk because several of its members may default on their sovereign obligations if not bailed out by the other members. The valuation equation of bonds is essential to understanding the stability of the euro area. An explanation is provided in this paragraph and readers interested in technical details are referred to the Subsection IIIF Appendix on Sovereign Bond Valuation. Contrary to the Wriston doctrine, investing in sovereign obligations is a credit decision. The value of a bond today is equal to the discounted value of future obligations of interest and principal until maturity. On Dec 30 the yield of the 2-year bond of the government of Greece was quoted around 100 percent. In contrast, the 2-year US Treasury note traded at 0.239 percent and the 10-year at 2.871 percent while the comparable 2-year government bond of Germany traded at 0.14 percent and the 10-year government bond of Germany traded at 1.83 percent. There is no need for sovereign ratings: the perceptions of investors are of relatively higher probability of default by Greece, defying Wriston (1982), and nil probability of default of the US Treasury and the German government. The essence of the sovereign credit decision is whether the sovereign will be able to finance new debt and refinance existing debt without interrupting service of interest and principal. Prices of sovereign bonds incorporate multiple anticipations such as inflation and liquidity premiums of long-term relative to short-term debt but also risk premiums on whether the sovereign’s debt can be managed as it increases without bound. The austerity measures of Italy are designed to increase the primary surplus, or government revenues less expenditures excluding interest, to ensure investors that Italy will have the fiscal strength to manage its debt of 120 percent of GDP, which is the third largest in the world after the US and Japan. Appendix IIIE links the expectations on the primary surplus to the real current value of government monetary and fiscal obligations. As Blanchard (2011SepWEO) analyzes, fiscal consolidation to increase the primary surplus is facilitated by growth of the economy. Italy and the other indebted sovereigns in Europe face the dual challenge of increasing primary surpluses while maintaining growth of the economy (for the experience of Brazil in the debt crisis of 1982 see Pelaez 1986, 1987).

Much of the analysis and concern over the euro zone centers on the lack of credibility of the debt of a few countries while there is credibility of the debt of the euro zone as a whole. In practice, there is convergence in valuations and concerns toward the fact that there may not be credibility of the euro zone as a whole. The fluctuations of financial risk assets of members of the euro zone move together with risk aversion toward the countries with lack of debt credibility. This movement raises the need to consider analytically sovereign debt valuation of the euro zone as a whole in the essential analysis of whether the single-currency will survive without major changes.

Welfare economics considers the desirability of alternative states, which in this case would be evaluating the “value” of Germany (1) within and (2) outside the euro zone. Is the sum of the wealth of euro zone countries outside of the euro zone higher than the wealth of these countries maintaining the euro zone? On the choice of indicator of welfare, Hicks (1975, 324) argues:

“Partly as a result of the Keynesian revolution, but more (perhaps) because of statistical labours that were initially quite independent of it, the Social Product has now come right back into its old place. Modern economics—especially modern applied economics—is centered upon the Social Product, the Wealth of Nations, as it was in the days of Smith and Ricardo, but as it was not in the time that came between. So if modern theory is to be effective, if it is to deal with the questions which we in our time want to have answered, the size and growth of the Social Product are among the chief things with which it must concern itself. It is of course the objective Social Product on which attention must be fixed. We have indexes of production; we do not have—it is clear we cannot have—an Index of Welfare.”

If the burden of the debt of the euro zone falls on Germany and France or only on Germany, is the wealth of Germany and France or only Germany higher after breakup of the euro zone or if maintaining the euro zone? In practice, political realities will determine the decision through elections.

The prospects of survival of the euro zone are dire. Table IIA-8 is constructed with IMF World Economic Outlook database (http://www.imf.org/external/datamapper/index.php?db=WEO) for GDP in USD billions, primary net lending/borrowing as percent of GDP and general government debt as percent of GDP for selected regions and countries in 2010.

Table IIA-8, World and Selected Regional and Country GDP and Fiscal Situation

	GDP 2012 USD Billions	Primary Net Lending Borrowing % GDP 2012	General Government Net Debt % GDP 2012
World	71,277
Euro Zone	12,065	-0.5	73.4
Portugal	211	-0.7	110.9
Ireland	205	-4.4	103.0
Greece	255	-1.7	170.7
Spain	1,340	-4.5	78.6
Major Advanced Economies G7	33,769	-5.1	89.0
United States	15,653	-6.5	83.8
UK	2,434	-5.6	83.7
Germany	3,367	1.4	58.4
France	2,580	-2.2	83.7
Japan	5,984	-9.1	135.4
Canada	1,770	-3.2	35.8
Italy	1,980	2.6	103.1
China	8,250	-1.3*	22.2**

*Net Lending/borrowing**Gross Debt

Source: IMF World Economic Outlook databank http://www.imf.org/external/datamapper/index.php?db=WEO

The data in Table IIA-8 are used for some very simple calculations in Table IIA-9. The column “Net Debt USD Billions” in Table IIA-9 is generated by applying the percentage in Table IIA-8 column “General Government Net Debt % GDP 2010” to the column “GDP USD Billions.” The total debt of France and Germany in 2012 is $4155.8 billion, as shown in row “B+C” in column “Net Debt USD Billions” The sum of the debt of Italy, Spain, Portugal, Greece and Ireland is $3975.1 billion, adding rows D+E+F+G+H in column “Net Debt USD billions.” There is some simple “unpleasant bond arithmetic” in the two final columns of Table IIA-9. 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 shown in column “Debt as % of Germany plus France GDP” to reach $8130.8 billion, which would be equivalent to 136.7 percent of their combined GDP in 2012. Under this arrangement the entire debt of the euro zone including debt of France and Germany would not have nil probability of default. The final column provides “Debt as % of Germany GDP” that would exceed 241.5 percent if including debt of France and 177.4 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. Wriston (1982) would prove to be wrong again that countries do not bankrupt but would have a consolation prize that similar to LBOs the sum of the individual values of euro zone members outside the current agreement exceeds the value of the whole euro zone. Internal rescues of French and German banks may be less costly than bailing out other euro zone countries so that they do not default on French and German banks.

Table IIA-9, Guarantees of Debt of Sovereigns in Euro Area as Percent of GDP of Germany and France, USD Billions and %

	Net Debt USD Billions	Debt as % of Germany Plus France GDP	Debt as % of Germany GDP
A Euro Area	8,855.7
B Germany	1,996.3		$8130.9 as % of $3367 =241.5% $5971.4 as % of $3367 =177.4%
C France	2,159.5
B+C	4,155.8	GDP $5,947.0 Total Debt $8130.9 Debt/GDP: 136.7%
D Italy	2,041.4
E Spain	1,053.2
F Portugal	234.0
G Greece	435.3
H Ireland	211.2
Subtotal D+E+F+G+H	3,975.1

Source: calculation with IMF data http://www.imf.org/external/datamapper/index.php?db=WEO

The United States Census Bureau has released revisions of trade statistics from Jan 2009 to Mar 2012 (http://www.census.gov/foreign-trade/Press-Release/2011pr/final_revisions/). Table IIB-1 provides the trade balance of the US and monthly growth of exports and imports seasonally adjusted with the latest release and revisions (http://www.census.gov/foreign-trade/). Because of heavy dependence on imported oil, fluctuations in the US trade account originate largely in fluctuations of commodity futures prices caused by carry trades from zero interest rates into commodity futures exposures in a process similar to world inflation waves (http://cmpassocregulationblog.blogspot.com/2012/09/recovery-without-hiring-world-inflation.html). The US trade balance improved from deficit of $51,647 million in Mar 2012 to deficit of $49,826 million in Apr 2012 and lower deficits of $47,596 million in May, $41,899 million in Jun and $42,466 million in Jul 2012 but with increase to $44,217 million in Aug 2012. The decline of exports in Aug of 1.0 percent was higher than decline of imports of 0.1 percent, resulting in an increase of the trade deficit. The deterioration of the trade deficit from $44,507 million in Feb 2012 to $51,647 million in Mar 2012 resulted from growth of exports of 2.5 percent while imports jumped 5.2 percent. The US trade balance had improved from deficit of $52,209 million in Jan 2012 to lower deficit of $44,507 million in Feb 2012 mostly because of decline of imports by 2.7 percent while exports increased 0.9 percent. The US trade balance deteriorated sharply from Nov 2011 to Jan 2012 with growth of imports by cumulative 3.0 percent and cumulative increase of exports of 0.1 percent, resulting in deficits of $48,835 million in Nov, $51,748 million in Dec and $52,209 million in Jan, which are the highest since $50,234 million in Jun 2011. In the months of Jun to Oct 2011, exports increased 1.8 percent while imports increased 0.5 percent, resulting in improvement of the trade deficit from $50,234 million in Jun to $45,703 million in Oct. The trade balance deteriorated from cumulative deficit of $493,737 million in Jan-Dec 2010 to deficit of $559,880 million in Jan-Dec 2011.

Table IIB1-1, US, Trade Balance of Goods and Services Seasonally Adjusted Millions of Dollars and ∆%

	Trade Balance	Exports	Month ∆%	Imports	Month ∆%
Aug 2012	-44,217	181,282	-1.0	225,499	-0.1
Jul	-42,466	183,188	-1.1	225,654	-0.6
Jun	-41,899	185,182	1.2	227,081	-1.5
May	-47,596	183,058	0.1	230,654	-0.9
Apr	-49,826	182,825	-1.1	232,651	-1.6
Mar	-51,647	184,867	2.5	236,514	5.2
Feb	-44,507	180,348	0.9	224,855	-2.7
Jan	-52,209	178,802	0.6	231,011	0.7
Dec 2011	-51,748	177,751	0.6	229,499	1.8
Nov	-48,835	176,710	-1.1	225,545	0.5
Oct	-45,703	178,742	-1.0	224,445	-0.3
Sep	-44,467	180,629	1.3	225,096	0.9
Aug	-44,775	178,382	0.0	223,157	-0.3
Jul	-45,580	178,339	3.3	223,919	0.4
Jun	-50,234	172,664	-1.7	222,988	-0.2
May	-47,669	175,673	0.0	223,343	1.9
Apr	-43,556	175,662	0.9	219,218	0.1
Mar	-44,902	174,169	4.6	219,071	3.7
Feb	-44,801	166,545	-0.9	211,346	-2.0
Jan	-47,523	168,098	1.6	215,621	4.6
Dec 2010	-40,677	165,499	1.7	206,176	2.2
Jan-Dec 2011	-559,880	2,103,367		2,663,247
Jan-Dec 2010	-494,737	1,842,485		2,337,222

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

Table IIB1-2 provides the US international trade balance, exports and imports on an annual basis from 1992 to 2011. The trade balance deteriorated sharply over the long term. The US has a large deficit in goods or exports less imports of goods but it has a surplus in services that helps to reduce the trade account deficit or exports less imports of goods and services. The current account deficit of the US decreased from $124.5 billion in IIQ2011, or 3.2 percent of GDP to $123.2 billion in IIQ2012, or 3.1 percent of GDP (http://cmpassocregulationblog.blogspot.com/2012/09/collapse-of-united-states-creation-of.html). The ratio of the current account deficit to GDP has stabilized around 3 percent of GDP compared with much higher percentages before the recession (see Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State, Vol. II (2008b), 183-94, Government Intervention in Globalization (2008c), 167-71).

Table IIB1-2, US, International Trade Balance, Exports and Imports SA, Millions of Dollars

Period	Balance	Exports	Imports
Total
Annual
1992	-39,212	616,882	656,094
1993	-70,311	642,863	713,174
1994	-98,493	703,254	801,747
1995	-96,384	794,387	890,771
1996	-104,065	851,602	955,667
1997	-108,273	934,453	1,042,726
1998	-166,140	933,174	1,099,314
1999	-263,160	967,008	1,230,168
2000	-376,749	1,072,783	1,449,532
2001	-361,771	1,007,726	1,369,496
2002	-417,432	980,879	1,398,311
2003	-490,984	1,023,519	1,514,503
2004	-605,357	1,163,146	1,768,502
2005	-708,624	1,287,441	1,996,065
2006	-753,288	1,459,823	2,213,111
2007	-696,728	1,654,561	2,351,289
2008	-698,338	1,842,682	2,541,020
2009	-379,154	1,578,945	1,958,099
2010	-494,737	1,842,485	2,337,222
2011	-559,880	2,103,367	2,663,247

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

Chart IIB-1 of the US Census Bureau of the Department of Commerce shows that the trade deficit (gap between exports and imports) fell during the economic contraction after 2007 but has grown again during the expansion. There was slight improvement at the margin from Jul to Oct 2011 but new increase in the gap from Nov 2011 to Jan 2012 and again in Mar as exports grow less rapidly than imports. There is improvement in Apr 2012 with imports declining at a faster rate of 1.6 percent than decline of exports by 1.1 percent and growth of exports of 0.1 percent in May 2012 with imports declining 0.9 percent. Further improvement occurred in Jun with importing increasing 1.2 percent and exports declining 1.5 percent. There was deterioration in Jul with exports declining 1.1 percent and imports only 0.6 percent but deterioration in Aug with exports decreasing 1.0 percent while imports declined only 0.1 percent. Weaker world and internal demand and fluctuating commodity price increases explain the declining or less dynamic changes in exports and imports in Chart IIB1-1.

Chart IIB1-1, US Balance, Exports and Imports of Goods and Services $ Billions

Source: US Census Bureau

Chart IIB1-2 of the US Census Bureau provides the US trade account in goods and services SA from Jan 1992 to Aug 2012. There is a long-term trend of deterioration of the US trade deficit shown vividly by Chart IIB1-2. The trend of deterioration was reversed by the global recession from IVQ2007 to IIQ2009. Deterioration resumed together with incomplete recovery and was influenced significantly by the carry trade from zero interest rates to commodity futures exposures (these arguments are elaborated in Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4 http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html). Earlier research focused on the long-term external imbalance of the US in the form of trade and current account deficits (Pelaez and Pelaez, The Global Recession Risk (2007), Globalization and the State Vol. II (2008b) 183-94, Government Intervention in Globalization (2008c), 167-71). US external imbalances have not been fully resolved and tend to widen together with improving world economic activity and commodity price shocks.

Chart IIB1-2. US, Balance of Trade SA, Monthly, Millions of Dollars, Jan 1992-Aug 2012

Source: US Census Bureau

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

Chart VA-6 of the US Census Bureau provides US exports SA from Jan 1992 to Aug 2012. There was sharp acceleration from 2003 to 2007 during worldwide economic boom and increasing inflation. Exports fell sharply during the financial crisis and global recession from IVQ2007 to IIQ2009. Growth picked up again together with world trade and inflation but stalled in the final segment.

Chart IIB1-3. US, Exports SA, Monthly, Millions of Dollars Jan 1992-Aug 2012

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

Chart IIB1-4 of the US Census Bureau provides US imports SA from Jan 1992 to Aug 2012. Growth was stronger between 2003 and 2007 with worldwide economic boom and inflation. There was sharp drop during the financial crisis and global recession. There is stalling import levels in the final segment resulting from weaker world economic growth and diminishing inflation because of risk aversion.

Chart IIB1-4. US, Imports SA, Monthly, Millions of Dollars Jan 1992-Aug 2012

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

The balance of international trade in goods of the US seasonally-adjusted is shown in Table IIB1-3. The US has a dynamic surplus in services that reduces the large deficit in goods for a still very sizeable deficit in international trade of goods and services. The balance in international trade of goods improved from $60.2 billion in Aug 2011 to $59.3 billion in Aug 2012. Improvement of the goods balance in Aug 2012 relative to Aug 2011 occurred mostly in the petroleum balance, exports less imports of goods other than petroleum, in the magnitude of reducing the deficit by $2.1 billion, while there was moderate deterioration in the nonpetroleum balance, exports less imports of petroleum goods, in the magnitude of increasing the deficit by $1.7 billion. US terms of trade, export prices relative to import prices, and the US trade account fluctuate in accordance with the carry trade from zero interest rates to commodity futures exposures, especially oil futures. Exports rose 2.8 percent with non-petroleum exports growing 2.8 percent. Total imports rose 0.6 percent with petroleum imports declining 9.4 percent and nonpetroleum imports increasing 3.3 percent.

Table IIB1-3, US, International Trade in Goods Balance, Exports and Imports $ Millions and ∆% SA

	Aug 2012	Aug 2011	∆%
Total Balance	-59,331	-60,205
Petroleum	-23,493	-25,610
Non Petroleum	-35,288	-33,597
Total Exports	128,215	126,523	1.3
Petroleum	9,022	10,265	-12.1
Non Petroleum	118,079	114,918	2.8
Total Imports	187,847	186,728	0.6
Petroleum	32,515	35,875	-9.4
Non Petroleum	153,367	148,515	3.3

Details may not add because of rounding and seasonal adjustment

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

US exports and imports of goods not seasonally adjusted in Jan-Jun 2012 and Jan-Jun 2011 are shown in Table IB1-4. The rate of growth of exports was 5.6 percent and 4.7 percent for imports. The US has partial hedge of commodity price increases in exports of agricultural commodities that fell 2.2 percent and of mineral fuels that increased 8.1 percent both because of higher prices of raw materials and commodities increase and fall recurrently because of shocks of risk aversion. The US exports an insignificant amount of crude oil. US exports and imports consist mostly of manufactured products, with less rapidly increasing prices. US manufactured exports rose 6.8 percent while imports rose 7.2 percent. Significant part of the US trade imbalance originates in imports of mineral fuels decreasing 4.2 percent and crude oil decreasing 2.1 percent with significant oscillations in oil prices. The limited hedge in exports of agricultural commodities and mineral fuels compared with substantial imports of mineral fuels and crude oil results in waves of deterioration of the terms of trade of the US, or export prices relative to import prices, originating in commodity price increases caused by carry trades from zero interest rates. These waves are similar to those in worldwide inflation (Section II World Inflation Waves http://cmpassocregulationblog.blogspot.com/2012/09/recovery-without-hiring-world-inflation.html).

Table IIB1-4, US, Exports and Imports of Goods, Not Seasonally Adjusted Millions of Dollars and %

	Jan-Aug 2012 $ Millions	Jan-Aug 2011 $ Millions	∆%
Exports	1,023,821	969,531	5.6
Manufactured	680,420	636,846	6.8
Agricultural Commodities	88,275	90,227	-2.2
Mineral Fuels	88,933	82,260	8.1
Crude Oil	1,213	883	37.4
Imports	1,519,355	1,451,746	4.7
Manufactured	1,126,631	1,051,290	7.2
Agricultural Commodities	70,330	65,892	6.7
Mineral Fuels	293,537	306,369	-4.2
Crude Oil	219,996	224,812	-2.1

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

IIB2 Import Export Prices. Chart IIB2-1 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 global 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 because of 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 IIB2-1, US, Prices of Total US Imports 2001=100, 2001-2012

Chart IIB2-2 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 originating in 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 IIB2-2, US, Prices of Total US Imports, 12-Month Percentage Changes, 2001-2012

Chart IIB2-3 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 IIB2-3, US, Prices of Total US Imports, 2001=100, 1982-2012

Chart IIB2-4 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 IIB2-4, US, Prices of Total US Imports, 12-Month Percentage Changes, 1982-2012

Chart IIB2-5 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 IIB2-5 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 IIB2-5, US, Prices of Total US Exports, 2001=100, 2001-2012

Chart IIB2-6 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 and is followed by another steep increase after risk aversion moderated in IQ2009.

Chart IIB2-6, US, Prices of Total US Exports, 2001=100, 1982-2012

Chart IIB2-7 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 IIB2-7, 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 IIB2-1. 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 13.1 percent in the twelve months ending in Sep 2008 and fell 12.0 percent in the 12 months ending in Sep 2009 when risk aversion developed in 2008 until mid 2009. Import prices rose again sharply in Sep 2010 by 3.6 percent and in Sep 2011 by 12.7 percent in the presence of zero interest rates with relaxed mood of risk aversion until carry trades were unwound in May 2011 and following months as shown by decline of import prices by 0.6 percent in the 12 months ending in Sep 2012 and of 0.5 percent in exports. Fluctuations are much sharper in imports because of the high content of oil that as all commodities futures contracts increases sharply with zero interest rates and risk appetite, contracting under 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. A critical event resulting from unconventional monetary policy driving higher commodity prices by carry trades is the deterioration of the terms of trade, or export prices relative to import prices, that has adversely affected US real income growth relative to what it would have been in the absence of unconventional monetary policy. Europe, Japan and other advanced economies have experienced similar deterioration of their terms of trade. Because of unwinding carry trades of commodity futures as a result of risk aversion, import prices fell 0.6 percent in the 12 months ending in Sep 2012, export prices fell 0.5 percent and prices of nonagricultural exports fell 1.5 percent. Imports excluding fuel fell 0.5 in the 12 months ending in Sep 2012. At the margin, prices in world exports and imports are increasing again because of carry trades in a temporary mood of risk appetite.

Table IIB2-1, US, Twelve-Month Percentage Rates of Change of Prices of Exports and Imports

	Imports	Imports Ex Fuels	Exports	Exports Non-Ag
Sep 2012	-0.6	-0.5	-0.5	-1.5
Sep 2011	12.7	5.4	9.4	7.9
Sep 2010	3.6	2.5	4.9	4.3
Sep 2009	-12.0	-4.2	-5.6	-4.4
Sep 2008	13.1	6.1	7.0	5.8
Sep 2007	4.8	2.1	4.5	2.9
Sep 2006	1.6	2.9	3.9	3.8
Sep 2005	9.9	1.4	3.6	3.6
Sep 2004	8.2	2.8	4.0	4.3
Sep 2003	0.7	0.5	1.0	0.6
Sep 2002	-0.4	NA	-0.2	-0.6
Sep 2001	-5.6	NA	-1.4	-1.9

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

Chart IIB2-8 shows the US monthly import price index of all commodities excluding fuels from 2001 to 2012. 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 while under strong risk aversion even with zero interest rates there are declines of nominal values.

Chart IIB2-8, US, Import Price Index All Commodities Excluding Fuels, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IIB2-9 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 IIB2-9, US, Import Price Index All Commodities Excluding Fuels, 12-Month Percentage Changes, 2002-2012

Source: US Bureau of Labor Statistics

Chart IIB2-10 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 IIB2-10, US, Import Price Index ex Petroleum, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IIB2-11 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 IIB2-11, US, Import Price Index ex Petroleum, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

Chart IIB2-12 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 IIB2-12, 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 IIB2-13 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 IIB2-13, 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 IIB2-14. There is similar behavior of the curves all driven by the same impulses of monetary policy.

Chart IIB2-14, US, Import Price Index of Petroleum and Petroleum Products, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IIB2-15 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 IIB2-15, US, Import Price Index of Petroleum and Petroleum Products, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

Chart IIB2-16 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 IIB2-16, 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 IIB2-17 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 followed by another decline in Jun 2012.

Chart IIB2-17, US, Exports Price Index of Agricultural Commodities, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IIB2-18 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 IIB2-18, US, Exports Price Index of Agricultural Commodities, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

Chart IIB2-19 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 IIB2-19, US, Exports Price Index of Agricultural Commodities, 12-Month Percentage Changes, 1986-2012

Source: US Bureau of Labor Statistics

Chart IIB2-20 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 IIB2-20, US, Exports Price Index of Nonagricultural Commodities, 2001=100, 2001-2012

Source: US Bureau of Labor Statistics

Chart IIB2-21 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 IIB2-21, US, Exports Price Index of Nonagricultural Commodities, 2001=100, 1982-2012

Source: US Bureau of Labor Statistics

Finally, Chart IIB2-22 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 IIB-22, US, Exports Price Index of Nonagricultural Commodities, 12-Month Percentage Changes, 1986-2012

Source: US Bureau of Labor Statistics