IMF View of World Economy and Finance, Recovery without Hiring, Ten Million Fewer Full-time Jobs, Youth and Middle-Age Unemployment, United States Producer Price Index, Collapse of United States Dynamism of Income Growth and Employment Creation, World Cyclical Slow Growth and Global Recession Risk: Part II

 

IMF View of World Economy and Finance, Recovery without Hiring, Ten Million Fewer Full-time Jobs, Youth and Middle-Age Unemployment, United States Producer Price Index, Collapse of United States Dynamism of Income Growth and Employment Creation, World Cyclical Slow Growth and Global Recession Risk

Carlos M. Pelaez

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016

I IMF View of World Economy and Finance

IA Recovery without Hiring

IA1 Hiring Collapse

IA2 Labor Underutilization

ICA3 Ten Million Fewer Full-time Jobs

IA4 Theory and Reality of Cyclical Slow Growth Not Secular Stagnation: Youth and Middle-Age Unemployment

II United States Producer Price Index

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

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

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

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during the Debt Crisis of the 1980s

 

I 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 (http://www.imf.org/external/ns/cs.aspx?id=29), Global Financial Stability Report (http://www.imf.org/external/pubs/ft/gfsr/index.htm) and Fiscal Monitor (http://www.imf.org/external/ns/cs.aspx?id=262).

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 I-1 is constructed with the database of the IMF (http://www.imf.org/external/ns/cs.aspx?id=29) to show GDP in dollars in 2015 and the growth rate of real GDP of the world and selected regional countries from 2015 to 2018. 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 changed its forecast of the world economy to 3.2 percent in 2015 and 3.1 percent in 2016 but accelerating to 3.4 percent in 2017 and 3.6 percent in 2018. Slow-speed recovery occurs in the “major advanced economies” of the G7 that account for $34.171 billion of world output of $73,599 billion, or 46.4 percent, but are projected to grow at much lower rates than world output, 1.7 percent on average from 2015 to 2018, in contrast with 3.3 percent for the world as a whole. While the world would grow 14.0 percent in the four years from 2015 to 2017, the G7 as a whole would grow 6.9 percent. The difference in dollars of 2015 is high: growing by 14.0 percent would add around $10.3 trillion of output to the world economy, or roughly, two times the output of the economy of Japan of $4,124 billion but growing by 6.9 percent would add $5.1 trillion of output to the world, or about the output of Japan in 2015. 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 2019 of $29,039 billion, or 39.5 percent of world output. The EMDEs would grow cumulatively 18.8 percent or at the average yearly rate of 4.4 percent, contributing $5.5 trillion from 2015 to 2017 or the equivalent of somewhat more than one half the GDP of $11,182 billion of China in 2014. The final four countries in Table I-1 often referred as BRIC (Brazil, Russia, India, China), are large, rapidly growing emerging economies. Their combined output in 2015 adds to $16,354 billion, or 22.2 percent of world output, which is equivalent to 47.9 percent of the combined output of the major advanced economies of the G7.

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

	GDP USD 2015	Real GDP ∆% 2015	Real GDP ∆% 2016	Real GDP ∆% 2017	Real GDP ∆% 2018
World	73,599	3.2	3.1	3.4	3.6
G7	34,171	1.9	1.4	1.7	1.7
Canada	1,551	1.1	1.2	1.9	1.9
France	2,420	1.3	1.3	1.4	1.6
DE	3,365	1.5	1.7	1.4	1.4
Italy	1,816	0.8	0.8	0.9	1.1
Japan	4,124	0.5	0.5	0.6	0.5
UK	2,858	2.2	1.8	1.1	1.7
US	18,037	2.6	1.6	2.2	2.1
Euro Area	11,601	2.1	1.7	1.5	1.6
DE	3,365	1.5	1.7	1.4	1.4
France	2,420	1.3	1.3	1.4	1.6
Italy	1,816	0.8	0.8	0.9	1.1
POT	199	1.5	1.1	1.1	1.2
Ireland	283	26.3	4.9	3.2	3.1
Greece	195	-0.2	0.1	2.8	3.1
Spain	1,200	3.2	3.1	2.2	1.9
EMDE	29,039	4.0	4.2	4.6	4.8
Brazil	1,773	-3.8	-3.3	0.5	1.5
Russia	1,326	-3.7	-0.8	1.1	1.2
India	2,073	7.6	7.6	7.6	7.7
China	11,182	6.9	6.6	6.2	6.0

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx). Table I-2 is constructed with the WEO database to provide rates of unemployment from 2014 to 2018 for major countries and regions. In fact, unemployment rates for 2014 in Table I-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. The rates of unemployment are particularly high in 2014 for the countries with sovereign debt difficulties in Europe: 13.9 percent for Portugal (POT), 11.3 percent for Ireland, 26.5 percent for Greece, 24.4 percent for Spain and 12.6 percent for Italy, which is lower but still high. The G7 rate of unemployment is 6.4 percent. Unemployment rates are not likely to decrease substantially if slow growth persists in advanced economies.

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

	% Labor Force 2014	% Labor Force 2015	% Labor Force 2016	% Labor Force 2017	% Labor Force 2018
World	NA	NA	NA	NA	NA
G7	6.4	5.8	5.5	5.4	5.4
Canada	6.9	6.9	7.0	7.1	6.9
France	10.3	10.4	9.8	9.6	9.3
DE	5.0	4.6	4.3	4.5	4.6
Italy	12.6	11.9	11.5	11.2	10.8
Japan	3.6	3.4	3.2	3.2	3.2
UK	6.2	5.4	5.0	5.2	5.4
US	6.2	5.3	5.0	4.8	4.7
Euro Area	11.7	10.9	10.0	9.7	9.3
DE	5.0	4.6	4.3	4.5	4.6
France	10.3	10.4	9.8	9.6	9.3
Italy	12.6	11.9	11.5	11.2	10.8
POT	13.9	12.4	11.2	10.7	10.3
Ireland	11.3	9.5	8.3	7.7	7.2
Greece	26.5	25.0	23.3	21.5	20.7
Spain	24.4	22.1	19.4	18.0	17.0
EMDE	NA	NA	NA	NA	NA
Brazil	6.8	8.5	11.2	11.5	11.1
Russia	5.2	5.6	5.8	5.9	5.5
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

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

The database of the WEO (http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx) is used to construct the debt/GDP ratios of regions and countries in Table I-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 the only available gross debt for China, Russia and India. The net debt/GDP ratio of the G7 increases from 82.8 in 2014 to 84.4 in 2017. G7 debt is pulled by the high debt of Japan that grows from 126.2 percent of GDP in 2014 to 132.6 percent of GDP in 2018. US general government debt increases from 80.3 percent of GDP in 2014 to 82.1 percent of GDP in 2018. Debt/GDP ratios of countries with sovereign debt difficulties in Europe are particularly worrisome. General government net debts of Italy, Greece and Portugal exceed 100 percent of GDP or are expected to exceed 100 percent of GDP by 2018. The only country with relatively lower debt/GDP ratio is Spain with 78.6 in 2015, increasing to 82.3 in 2018. Ireland’s debt/GDP ratio decreases from 86.3 in 2014 to 59.8 in 2018. 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 I-3, IMF World Economic Outlook Database Projections, General Government Net Debt as Percent of GDP

	% Debt/ GDP 2014	% Debt/ GDP 2015	% Debt/ GDP 2016	% Debt/ GDP 2017	% Debt/ GDP 2018
World	NA	NA	NA	NA	NA
G7	82.8	82.1	84.3	84.7	84.4
Canada	28.1	26.3	26.9	25.3	23.6
France	87.4	88.2	89.2	89.8	90.0
DE	50.1	47.5	45.4	43.7	42.0
Italy	112.5	113.3	113.8	113.9	112.7
Japan	126.2	125.3	127.9	130.7	132.6
UK	79.5	80.4	80.5	80.3	80.0
US	80.3	79.8	82.2	82.3	82.1
Euro Area	68.3	67.6	67.4	67.0	66.2
DE	50.1	47.5	45.4	43.7	42.0
France	87.4	88.2	89.2	89.8	90.0
Italy	112.5	113.3	113.8	113.9	112.7
POT	120.0	121.6	121.9	122.2	122.2
Ireland	86.3	67.0	63.8	62.3	59.8
Greece*	180.1	176.9	183.4	184.7	184.7
Spain	78.6	79.7	81.4	82.1	82.3
EMDE*	40.7	44.6	47.2	48.9	50.3
Brazil	33.1	36.2	45.8	50.4	53.6
Russia*	15.9	16.4	17.1	17.9	18.6
India*	68.3	69.1	68.5	67.2	65.6
China*	39.8	42.9	46.3	49.9	52.6

Notes; DE: Germany; EMDE: Emerging and Developing Economies (150 countries); *General Government Gross Debt as percent of GDP

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

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. There are various countries with primary surpluses in 2014: Germany 1.7 percent and Italy 1.4 percent. There are also various countries with expected primary surpluses by 2018: Portugal 1.2 percent, Italy 2.1 percent and so on. Most countries in Table I-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 I-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 I-4, IMF World Economic Outlook Database Projections of General Government Primary Net Lending/Borrowing as Percent of GDP

	% GDP 2014	% GDP 2015	% GDP 2016	% GDP 2017	% GDP 2018
World	NA	NA	NA	NA	NA
G7	-2.0	-1.5	-1.9	-1.8	-1.4
Canada	0.0	-0.6	-2.0	-2.0	-1.9
France	-1.9	-1.6	-1.5	-1.5	-1.2
DE	1.7	2.0	1.2	1.0	0.9
Italy	1.4	1.4	1.3	1.4	2.1
Japan	-5.6	-4.9	-5.2	-5.3	-4.7
UK	-3.8	-2.8	-1.6	-1.0	-0.4
US	-2.2	-1.5	-2.1	-1.8	-1.3
Euro Area	-0.2	0.1	-0.1	0.0	0.3
DE	1.7	2.0	1.2	1.0	0.9
France	-1.9	-1.6	-1.5	-1.5	-1.2
Italy	1.4	1.4	1.3	1.4	2.1
POT	-2.8	-0.2	1.3	1.2	1.2
Ireland	-0.3	0.3	1.3	1.4	1.5
Greece	0.0	0.7	0.1	0.7	1.6
Spain	-2.9	-2.4	-2.0	-0.8	-0.5
EMDE	-0.9	-2.7	-2.9	-2.4	-1.7
Brazil	-0.6	-1.9	-2.8	-2.2	-1.2
Russia	-0.7	-3.2	-3.4	-0.8	0.1
India	-2.8	-2.3	-2.1	-2.1	-1.8
China	-0.4	-2.1	-2.2	-2.3	-1.7

*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/pubs/ft/weo/2016/02/weodata/index.aspx

The database of the World Economic Outlook of the IMF (http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx) is used to obtain government net lending/borrowing as percent of GDP in Table I-5. Interest on government debt is added to the primary balance to obtain overall government fiscal balance in Table I-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 I-5, IMF World Economic Outlook Database Projections of General Government Net Lending/Borrowing as Percent of GDP

	% GDP 2014	% GDP 2015	% GDP 2016	% GDP 2017	% GDP 2018
World	NA	NA	NA	NA	NA
G7	-3.8	-3.2	-3.6	-3.3	-2.8
Canada	-0.5	-1.3	-2.5	-2.3	-2.0
France	-4.0	-3.5	-3.4	-3.0	-2.7
DE	0.3	0.7	0.1	0.1	0.2
Italy	-3.0	-2.6	-2.5	-2.2	-1.3
Japan	-6.2	-5.2	-5.2	-5.1	-4.4
UK	-5.6	-4.2	-3.3	-2.7	-2.2
US	-4.2	-3.5	-4.1	-3.7	-3.3
Euro Area	-2.6	-2.1	-2.0	-1.7	-1.4
DE	0.3	0.7	0.1	0.1	0.2
France	-4.0	-3.5	-3.4	-3.0	-2.7
Italy	-3.0	-2.6	-2.5	-2.2	-1.3
POT	-7.2	-4.4	-3.0	-3.0	-2.9
Ireland	-3.7	-1.9	-0.7	-0.5	-0.3
Greece	-4.1	-3.1	-3.4	-2.7	-1.7
Spain	-5.9	-5.1	-4.5	-3.1	-2.7
EMDE	-2.5	-4.5	-4.7	-4.4	-3.8
Brazil	-6.0	-10.3	-10.4	-9.1	-8.0
Russia	-1.1	-3.5	-3.9	-1.5	-0.8
India	-7.3	-6.9	-6.7	-6.6	-6.2
China	-0.9	-2.7	-3.0	-3.3	-3.0

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

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/pubs/ft/weo/2016/02/weodata/index.aspx) shows that external imbalances have been maintained in the form of current account deficits and surpluses. China’s current account surplus is 2.6 percent of GDP for 2014 and is projected to stabilize at 1.4 percent of GDP in 2018. At the same time, the current account deficit of the US is 2.3 percent of GDP in 2015 and is projected at 2.8 percent of GDP in 2018. The current account surplus of Germany is 7.3 percent for 2014 and remains at a high 7.7 percent of GDP in 2018. Japan’s current account surplus is 0.8 percent of GDP in 2015 and increases to 3.3 percent of GDP in 2018.

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

	% CA/ GDP 2014	% CA/ GDP 2015	% CA/ GDP 2016	% CA/ GDP 2017	% CA/ GDP 2018
World	NA	NA	NA	NA	NA
G7	-0.7	-0.6	-0.5	-0.5	-0.6
Canada	-2.3	-3.2	-3.7	-3.1	-2.8
France	-1.1	-0.2	-0.5	-0.4	-0.3
DE	7.3	8.4	8.6	8.1	7.7
Italy	1.9	2.2	2.2	1.9	1.5
Japan	0.8	3.3	3.7	3.3	3.3
UK	-4.7	-5.4	-5.9	-4.3	-3.9
US	-2.3	-2.6	-2.5	-2.7	-2.8
Euro Area	2.5	3.2	3.4	3.1	2.9
DE	7.3	8.4	8.6	8.1	7.7
France	-1.1	-0.2	-0.5	-0.4	-0.3
Italy	1.9	2.2	2.2	1.9	1.5
POT	0.1	0.4	0.0	-0.7	-0.8
Ireland	1.7	10.2	9.5	9.1	8.8
Greece	-2.1	0.0	0.0	0.0	0.1
Spain	1.0	1.3	1.9	1.7	1.7
EMDE	0.6	-0.1	-0.3	-0.4	-0.5
Brazil	-4.3	-3.3	-0.8	-1.3	-1.5
Russia	2.8	5.2	3.0	3.5	3.9
India	-1.3	-1.1	-1.4	-2.0	-2.2
China	2.6	3.0	2.4	1.6	1.4

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

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

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

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

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

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

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

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

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

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

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

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

The database of the WEO (http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx) is used to construct Table I-7 with fiscal and current account imbalances projected for 2016 and 2018. 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.”

The IMF (http://www.imf.org/external/pubs/ft/weo/2014/02/pdf/c4.pdf) analyzes global imbalances as:

• Global current account imbalances have narrowed by more than a third from

their peak in 2006. Key imbalances—the large deficit of the United States and

the large surpluses of China and Japan—have more than halved.

• The narrowing in imbalances has largely been driven by demand contraction

(“expenditure reduction”) in deficit economies.

• Exchange rate adjustment has facilitated rebalancing in China and the United

States, but in general the contribution of exchange rate changes (“expenditure

switching”) to current account adjustment has been relatively modest.

• The narrowing of imbalances is expected to be durable, as domestic demand in

deficit economies is projected to remain well below pre-crisis trends.

• Since flow imbalances have narrowed but not reversed, net creditor and debtor

positions have widened further. Weak growth has also contributed to still high

ratios of net external liabilities to GDP in some debtor economies.

• Risks of a disruptive adjustment in global current account balances have

decreased, but global demand rebalancing remains a policy priority. Stronger

external demand will be instrumental for reviving growth in debtor countries and

reducing their net external liabilities.”

Table I-7, Fiscal Deficit, Current Account Deficit and Government Debt as % of GDP and 2015 Dollar GDP

	GDP $B 2016	FD %GDP 2016	CAD %GDP 2016	Debt %GDP 2016	FD%GDP 2018	CAD%GDP 2018	Debt %GDP 2018
US	18562	-2.1	-2.5	82.2	-1.3	-2.8	82.1
Japan	4730	-5.2	3.7	127.9	-4.7	3.3	132.6
UK	2650	-1.6	-5.9	80.5	-0.4	-3.9	80.0
Euro	11991	-0.1	3.4	67.4	0.3	2.9	66.2
Ger	3495	1.2	8.6	45.4	0.9	7.7	42.0
France	2488	-1.5	-0.5	89.2	-1.2	-0.3	90.0
Italy	1853	1.3	2.2	113.8	2.1	1.5	112.7
Can	1532	-2.0	-3.7	26.9	-1.9	-2.8	23.6
China	11392	-2.2	2.4	46.3	-1.7	1.4	52.6
Brazil	1770	-2.8	-0.8	45.8	-1.2	-1.5	53.6

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

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

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, 2011, 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 exceeding 100 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 I-8 is constructed with IMF World Economic Outlook database (http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx) 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 2016.

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

	GDP 2016 USD Billions	Primary Net Lending Borrowing % GDP 2016	General Government Net Debt % GDP 2016
World	75,213
Euro Zone	11,991	-0.1	67.4
Portugal	206	1.3	121.9
Ireland	308	1.3	63.8
Greece	195	-3.4	183.4**
Spain	1,252	-2.0	81.4
Major Advanced Economies G7	35,310	-1.9	84.3
United States	18,562	-2.1	82.2
UK	2,650	-1.6	80.5
Germany	3,495	1.2	45.4
France	2,488	-1.5	89.2
Japan	4,730	-5.2	127.9
Canada	1,532	-2.0	26.9
Italy	1,852	1.3	113.8
China	11,392	-2.2	46.3***

*Net Lending/borrowing**Gross Debt

Source: IMF World Economic Outlook

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

The data in Table I-8 are used for some very simple calculations in Table I-9. The column “Net Debt USD Billions 2016” in Table I-9 is generated by applying the percentage in Table I-8 column “General Government Net Debt % GDP 2016” to the column “GDP 2016 USD Billions.” The total debt of France and Germany in 2016 is $3806.0 billion, as shown in row “B+C” in column “Net Debt USD Billions 2016.” The sum of the debt of Italy, Spain, Portugal, Greece and Ireland is $3391.9 billion, adding rows D+E+F+G+H in column “Net Debt USD billions 2016.” There is some simple “unpleasant bond arithmetic” in the two final columns of Table I-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 $7197.9 billion, which would be equivalent to 120.3 percent of their combined GDP in 2016. Under this arrangement, the entire debt of selected members 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 205.9 percent if including debt of France and 142.4 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. Analysis of fiscal stress is quite difficult without including another global recession in an economic cycle that is already mature by historical experience.

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

	Net Debt USD Billions 2016	Debt as % of Germany Plus France GDP	Debt as % of Germany GDP
A Euro Area	8,081.9
B Germany	1,586.7		$7197.9 as % of $3495 =205.9% $4978.6 as % of $3495 =142.4%
C France	2,219.3
B+C	3,806.0	GDP $5983 Total Debt $7,197.9 Debt/GDP: 120.3%
D Italy	2,107.6
E Spain	1,019.1
F Portugal	251.1
G Greece	357.6
H Ireland	196.5
Subtotal D+E+F+G+H	3,391.9

Source: calculation with IMF data IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

World trade projections of the IMF are in Table I-10. There is decreasing growth of the volume of world trade of goods and services from 2.6 percent in 2015 to 2.3 percent in 2016, increasing to 3.8 percent in 2017. Growth improves to 4.1 percent on average from 2017 to 2021. World trade would be slower for advanced economies while emerging and developing economies (EMDE) experience faster growth. World economic slowdown would be more challenging with lower growth of world trade.

Table I-10, IMF, Projections of World Trade, USD Billions, USD/Barrel and Annual ∆%

	2015	2016	2017	Average ∆% 2017-2021
World Trade Volume (Goods and Services)	2.6	2.3	3.8	4.1
Exports Goods & Services	2.7	2.2	3.5	4.0
Imports Goods & Services	2.4	2.3	4.0	4.2
Average Oil Price USD/Barrel	50.79	42.96	50.64	Average ∆% 2008-2017 79.16
Average Annual ∆% Export Unit Value of Manufactures	-2.9	-2.1	1.4	Average ∆% 2008-2017 0.4
Exports of Goods & Services	2015	2016	2017	Average ∆% 2008-2017
EMDE	1.3	2.9	3.6	3.7
G7	3.6	1.8	3.5	2.5
Imports Goods & Services
EMDE	-0.6	2.3	4.1	4.5
G7	4.2	2.4	3.9	2.1
Terms of Trade of Goods & Services
EMDE	-4.1	-1.0	-0.1	-0.1
G7	1.8	0.9	0.1	0.1
Terms of Trade of Goods
EMDE	-4.0	-1.0	0.1	-0.1
G7	1.8	1.2	0.2	0.0

Notes: Commodity Price Index includes Fuel and Non-fuel Prices; Commodity Industrial Inputs Price includes agricultural raw materials and metal prices; Oil price is average of WTI, Brent and Dubai

Source: International Monetary Fund World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx

I Recovery without Hiring. Professor Edward P. Lazear (2012Jan19) at Stanford University finds that recovery of hiring in the US to peaks attained in 2007 requires an increase of hiring by 30 percent while hiring levels increased by only 4 percent from Jan 2009 to Jan 2012. The high level of unemployment with low level of hiring reduces the statistical probability that the unemployed will find a job. According to Lazear (2012Jan19), the probability of finding a new job in early 2012 is about one third of the probability of finding a job in 2007. Improvements in labor markets have not increased the probability of finding a new job. Lazear (2012Jan19) quotes an essay coauthored with James R. Spletzer in the American Economic Review (Lazear and Spletzer 2012Mar, 2012May) on the concept of churn. A dynamic labor market occurs when a similar amount of workers is hired as those who are separated. This replacement of separated workers is called churn, which explains about two-thirds of total hiring. Typically, wage increases received in a new job are higher by 8 percent. Lazear (2012Jan19) argues that churn has declined 35 percent from the level before the recession in IVQ2007. Because of the collapse of churn, there are no opportunities in escaping falling real wages by moving to another job. As this blog argues, there are meager chances of escaping unemployment because of the collapse of hiring and those employed cannot escape falling real wages by moving to another job (Section II and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rate-uncertainty-and-valuation.html). Lazear and Spletzer (2012Mar, 1) argue that reductions of churn reduce the operational effectiveness of labor markets. Churn is part of the allocation of resources or in this case labor to occupations of higher marginal returns. The decline in churn can harm static and dynamic economic efficiency. Losses from decline of churn during recessions can affect an economy over the long-term by preventing optimal growth trajectories because resources are not used in the occupations where they provide highest marginal returns. Lazear and Spletzer (2012Mar 7-8) conclude that: “under a number of assumptions, we estimate that the loss in output during the recession [of 2007 to 2009] and its aftermath resulting from reduced churn equaled $208 billion. On an annual basis, this amounts to about .4% of GDP for a period of 3½ years.”

There are two additional facts discussed below: (1) there are about ten million fewer full-time jobs currently than before the recession of 2008 and 2009; and (2) the extremely high and rigid rate of youth unemployment is denying an early start to young people ages 16 to 24 years while unemployment of ages 45 years or over has swelled. There are four subsections. IA1 Hiring Collapse provides the data and analysis on the weakness of hiring in the United States economy. IA2 Labor Underutilization provides the measures of labor underutilization of the Bureau of Labor Statistics (BLS). Statistics on the decline of full-time employment are in IA3 Ten Million Fewer Full-time Jobs. IA4 Theory and Reality of Cyclical Slow Growth Not Secular Stagnation: Youth and Middle-Age Unemployment provides the data on high unemployment of ages 16 to 24 years and of ages 45 years or over.

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

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

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

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

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

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

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

There is socio-economic stress in the combination of adverse events and cyclical performance:

• Mediocre economic growth below potential and long-term trend, resulting in idle productive resources with GDP two trillion dollars below trend (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). US GDP grew at the average rate of 3.2 percent per year from 1929 to 2015, with similar performance in whole cycles of contractions and expansions, but only at 1.2 percent per year on average from 2007 to 2015. GDP in IIQ2016 is 14.0 percent lower than what it would have been had it grown at trend of 3.0 percent
• Private fixed investment stagnating at increase of 7.4 percent in the entire cycle from IVQ2007 to IIQ2016 (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html)
• Twenty four million or 14.0 percent of the effective labor force unemployed or underemployed in involuntary part-time jobs with stagnating or declining real wages (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/fluctuating-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/02/fluctuating-risk-financial-assets-in.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/weakening-equities-with-exchange-rate.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-fed-funds-rate-followed-by.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/live-possibility-of-interest-rates.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/labor-market-uncertainty-and-interest.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/turbulence-of-financial-asset.html)

• Stagnating real disposable income per person or income per person after inflation and taxes (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/02/fluctuating-risk-financial-assets-in.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/dollar-revaluation-and-decreasing.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/dollar-revaluation-constraining.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/dollar-revaluation-constraining.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/live-possibility-of-interest-rates.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/labor-market-uncertainty-and-interest.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/dollar-devaluation-and-carry-trade.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html)
• Depressed hiring that does not afford an opportunity for reducing unemployment/underemployment and moving to better-paid jobs (Section II and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rate-uncertainty-and-valuation.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/oscillating-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/considerable-uncertainty-about-economic.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/recovery-without-hiring-ten-million.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-reducing.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/contraction-of-united-states-corporate.html and earlier http://cmpassocregulationblog.blogspot.com/2016/02/subdued-foreign-growth-and-dollar.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/unconventional-monetary-policy-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-interest-rates-with-volatile_17.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-policy-conundrum-recovery.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/impact-of-monetary-policy-on-exchange.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what_13.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/exchange-rate-and-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/oscillating-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/volatility-of-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/dollar-revaluation-recovery-without.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/global-exchange-rate-struggle-recovery.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/02/g20-monetary-policy-recovery-without.html)

• Productivity growth fell from 2.2 percent per year on average from 1947 to 2015 and average 2.3 percent per year from 1947 to 2007 to 1.3 percent per year on average from 2007 to 2015, deteriorating future growth and prosperity (http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/rising-valuations-of-risk-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/considerable-uncertainty-about-economic.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/closely-monitoring-global-economic-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-fed-funds-rate-followed-by.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/live-possibility-of-interest-rates.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/exchange-rate-and-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/quite-high-equity-valuations-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/global-competitive-devaluation-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2015/02/job-creation-and-monetary-policy-twenty.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/financial-risks-twenty-six-million.html)
• Output of manufacturing in Aug 2016 at 25.8 percent below long-term trend since 1919 and at 19.2 percent below trend since 1986 (http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-volatility-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/interest-rate-policy-uncertainty-and.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/07/unresolved-us-balance-of-payments.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/05/most-fomc-participants-judged-that-if.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/04/contracting-united-states-industrial.html and earlier (http://cmpassocregulationblog.blogspot.com/2016/03/monetary-policy-and-competitive.html and earlier http://cmpassocregulationblog.blogspot.com/2016/02/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/unconventional-monetary-policy-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-interest-rates-with-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-liftoff-followed-by.html http://cmpassocregulationblog.blogspot.com/2015/10/interest-rate-policy-quagmire-world.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-increase-on-hold-because.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/exchange-rate-and-financial-asset.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/exchange-rate-conflicts-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/imf-view-squeeze-of-economic-activity.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html)
• Unsustainable government deficit/debt and balance of payments deficit (http://cmpassocregulationblog.blogspot.com/2016/07/unresolved-us-balance-of-payments.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-reducing.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/weakening-equities-and-dollar.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/monetary-policy-designed-on-measurable.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html http://cmpassocregulationblog.blogspot.com/2014/08/monetary-policy-world-inflation-waves.html http://cmpassocregulationblog.blogspot.com/2014/06/valuation-risks-world-inflation-waves.html http://cmpassocregulationblog.blogspot.com/2014/02/theory-and-reality-of-cyclical-slow.html http://cmpassocregulationblog.blogspot.com/2014/03/interest-rate-risks-world-inflation.html http://cmpassocregulationblog.blogspot.com/2013/12/tapering-quantitative-easing-mediocre.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/duration-dumping-and-peaking-valuations.html)
• Worldwide waves of inflation (http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-volatility-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/interest-rate-policy-uncertainty-and.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/oscillating-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/most-fomc-participants-judged-that-if.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/contracting-united-states-industrial.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/monetary-policy-and-competitive.html and earlier http://cmpassocregulationblog.blogspot.com/2016/02/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/uncertainty-of-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-interest-rates-with-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-liftoff-followed-by.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/interest-rate-policy-quagmire-world.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-increase-on-hold-because.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/global-decline-of-values-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/interest-rate-policy-and-dollar.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/dollar-revaluation-and-financial-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/competitive-currency-conflicts-world.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier (http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/financial-oscillations-world-inflation.html http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/08/monetary-policy-world-inflation-waves.html http://cmpassocregulationblog.blogspot.com/2014/07/world-inflation-waves-united-states.html)
• Deteriorating terms of trade and net revenue margins of production across countries in squeeze of economic activity by carry trades induced by zero interest rates (http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-volatility-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/unresolved-us-balance-of-payments.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/fomc-projections-world-inflation-waves.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/most-fomc-participants-judged-that-if.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/imf-view-of-world-economy-and-finance.html and earlier) (http://cmpassocregulationblog.blogspot.com/2016/03/monetary-policy-and-competitive.html and earlier http://cmpassocregulationblog.blogspot.com/2016/02/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/uncertainty-of-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/liftoff-of-interest-rates-with-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-liftoff-followed-by.html http://cmpassocregulationblog.blogspot.com/2015/10/interest-rate-policy-quagmire-world.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-increase-on-hold-because.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/global-decline-of-values-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html http://cmpassocregulationblog.blogspot.com/2015/01/exchange-rate-conflicts-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/imf-view-squeeze-of-economic-activity.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html)
• Financial repression of interest rates and credit affecting the most people without means and access to sophisticated financial investments with likely adverse effects on income distribution and wealth disparity (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/global-competitive-easing-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/financial-turbulence-twenty-four.html and earlier http://cmpassocregulationblog.blogspot.com/2016/05/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/04/proceeding-cautiously-in-monetary.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/twenty-five-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/closely-monitoring-global-economic-and.html and earlier http://cmpassocregulationblog.blogspot.com/2015/12/dollar-revaluation-and-decreasing.html and earlier http://cmpassocregulationblog.blogspot.com/2015/11/dollar-revaluation-constraining.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/11/live-possibility-of-interest-rates.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/labor-market-uncertainty-and-interest.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/interest-rate-policy-dependent-on-what.html and earlier http://cmpassocregulationblog.blogspot.com/2015/08/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/higher-volatility-of-asset-prices-at.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/dollar-devaluation-and-carry-trade.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/volatility-of-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/global-competitive-devaluation-rules.html and earlier http://cmpassocregulationblog.blogspot.com/2015/02/job-creation-and-monetary-policy-twenty.html and earlier (http://cmpassocregulationblog.blogspot.com/2014/12/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/growth-uncertainties-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/world-financial-turbulence-twenty-seven.html)
• 43 million in poverty and 29 million without health insurance with family income adjusted for inflation regressing to 1999 levels (http://cmpassocregulationblog.blogspot.com/2016/09/the-economic-outlook-is-inherently.html and earlier http://cmpassocregulationblog.blogspot.com/2015/10/interest-rate-policy-uncertainty-imf.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2013/09/duration-dumping-and-peaking-valuations.html)
• Net worth of households and nonprofits organizations increasing by 16.7 percent after adjusting for inflation in the entire cycle from IVQ2007 to IIQ2016 when it would have grown over 29.6 percent at trend of 3.1 percent per year in real terms from IVQ1945 to IIQ2016 (http://cmpassocregulationblog.blogspot.com/2016/09/the-economic-outlook-is-inherently.html and earlier http://cmpassocregulationblog.blogspot.com/2016/06/of-course-considerable-uncertainty.html and earlier http://cmpassocregulationblog.blogspot.com/2016/03/monetary-policy-and-fluctuations-of_13.html and earlier http://cmpassocregulationblog.blogspot.com/2016/01/weakening-equities-and-dollar.html and earlier http://cmpassocregulationblog.blogspot.com/2015/09/monetary-policy-designed-on-measurable.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/dollar-revaluation-and-financial-risk.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/valuations-of-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/financial-volatility-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/06/financial-indecision-mediocre-cyclical.html and earlier http://cmpassocregulationblog.blogspot.com/2014/03/global-financial-risks-recovery-without.html and earlier http://cmpassocregulationblog.blogspot.com/2013/12/collapse-of-united-states-dynamism-of.html). Financial assets increased $19.5 trillion while nonfinancial assets increased $3.3 trillion with likely concentration of wealth in those with access to sophisticated financial investments. Real estate assets adjusted for inflation fell 4.1 percent.

The Bureau of Labor Statistics (BLS) revised on Mar 17, 2016 “With the release of January 2016 data on March 17, job openings, hires, and separations data have been revised from December 2000 forward to incorporate annual updates to the Current Employment Statistics employment estimates and the Job Openings and Labor Turnover Survey (JOLTS) seasonal adjustment factors. In addition, all data series are now available on a seasonally adjusted basis. Tables showing the revisions from 2000 through 2015 can be found using this link:http://www.bls.gov/jlt/revisiontables.htm.” (http://www.bls.gov/jlt/). Hiring in the nonfarm sector (HNF) has declined from 63.491 million in 2006 to 61.680 million in 2015 or by 1.811 million while hiring in the private sector (HP) has declined from 59.206 million in 2006 to 57.557 million in 2015 or by 1.649 million, as shown in Table I-1. The ratio of nonfarm hiring to employment (RNF) has fallen from 47.1 in 2005 to 43.5 in 2015 and in the private sector (RHP) from 52.8 in 2005 to 48.0 in 2015. Hiring has not recovered as in previous cyclical expansions because of the low rate of economic growth in the current cyclical expansion. The civilian noninstitutional population or those in condition to work increased from 228.815 million in 2006 to 250.801 million in 2015 or by 21.986 million. Hiring has not recovered prerecession levels while needs of hiring multiplied because of growth of population by more than 21 million. Private hiring of 59.206 million in 2006 was equivalent to 25.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 57.557 million in 2015 or 22.9 percent of the civilian noninstitutional population of 250.801 million in 2015. The percentage of hiring in civilian noninstitutional population of 25.9 percent in 2006 would correspond to 64.957 million of hiring in 2015, which would be 7.400 million higher than actual 57.557 million in 2015. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 28 quarters from IIIQ2009 to IIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp2q16_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2696.4 billion than actual $16,583.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html). US GDP in IIQ2016 is 14.0 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,583.1 billion in IIQ2016 or 10.6 percent at the average annual equivalent rate of 1.2 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Aug 1919 to Aug 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0258 in Aug 2016. The actual index NSA in Aug 2016 is 104.6251, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.5532 in Aug 2016. The output of manufacturing at 104.6251 in Aug 2016 is 19.2 percent below trend under this alternative calculation.

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

	HNF	Rate RNF	HP	Rate HP
2001	62,727	47.5	58,616	52.8
2002	58,416	44.7	54,592	50.0
2003	56,919	43.7	53,529	49.2
2004	60,236	45.7	56,567	51.3
2005	63,089	47.1	59,298	52.8
2006	63,491	46.5	59,206	51.7
2007	62,239	45.1	57,816	49.9
2008	54,764	39.9	51,260	44.7
2009	46,190	35.2	42,882	39.4
2010	48,659	37.3	44,831	41.6
2011	50,253	38.1	47,166	42.9
2012	52,354	39.0	48,914	43.6
2013	54,318	39.8	50,879	44.4
2014	58,632	42.2	54,980	47.0
2015	61,680	43.5	57,557	48.0

Source: Bureau of Labor Statistics

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

Chart I-1 shows the annual level of total nonfarm hiring (HNF) that collapsed during the global recession after 2007 in contrast with milder decline in the shallow recession of 2001. Nonfarm hiring has not recovered, remaining at a depressed level. The civilian noninstitutional population or those in condition to work increased from 228.815 million in 2006 to 250.801 million in 2015 or by 21.986 million. Hiring has not recovered precession levels while needs of hiring multiplied because of growth of population by more than 21 million.

Chart I-1, US, Level Total Nonfarm Hiring (HNF), Annual, 2001-2015

Source: US Bureau of Labor Statistics

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

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

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

Source: US Bureau of Labor Statistics

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

Yearly percentage changes of total nonfarm hiring (HNF) are provided in Table I-2. There were much milder declines in 2002 of 6.9 percent and 2.6 percent in 2003 followed by strong rebounds of 5.8 percent in 2004 and 4.7 percent in 2005. In contrast, the contractions of nonfarm hiring in the recession after 2007 were much sharper in percentage points: 2.0 in 2007, 12.0 in 2008 and 15.7 percent in 2009. On a yearly basis, nonfarm hiring grew 5.3 percent in 2010 relative to 2009, 3.3 percent in 2011, 4.2 percent in 2012 and 3.8 percent in 2013. Nonfarm hiring grew 7.9 percent in 2014 and increased 5.2 percent in 2015. The relatively large length of 27 quarters of the current expansion reduces the likelihood of significant recovery of hiring levels in the United States because lower rates of growth and hiring in the final phase of expansions.

Table I-2, US, Annual Total Nonfarm Hiring (HNF), Annual Percentage Change, 2002-2015

Year	Annual ∆%
2002	-6.9
2003	-2.6
2004	5.8
2005	4.7
2006	0.6
2007	-2.0
2008	-12.0
2009	-15.7
2010	5.3
2011	3.3
2012	4.2
2013	3.8
2014	7.9
2015	5.2

Source: US Bureau of Labor Statistics

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

Total private hiring (HP) 12-month percentage changes of annual data are in Chart I-3. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2015.

Chart I-3, US, Total Nonfarm Hiring Level, Annual, ∆%, 2001-2015

Source: Bureau of Labor Statistics

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

Total private hiring (HP) annual data are in Chart I-5. There has been sharp contraction of total private hiring in the US and only milder recovery from 2010 to 2015.

Chart I-5, US, Total Private Hiring, Annual, 2001-2015

Source: Bureau of Labor Statistics

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

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

Chart I-5A, US, Rate Total Private Hiring, Annual, 2001-2015

Source: Bureau of Labor Statistics

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

Total nonfarm hiring (HNF), total private hiring (HP) and their respective rates are in Table I-3 for the month of Aug in the years from 2001 to 2016. Hiring numbers are in thousands. There is recovery in HNF from 4185 thousand (or 4.2 million) in Aug 2009 to 4317 thousand in Aug 2010, 4602 thousand in Aug 2011, 4918 thousand in Aug 2012, 5256 thousand in Aug 2013, 5264 thousand in Aug 2014, 5640 thousand in Aug 2015 and 5761 thousand in Aug 2016 for cumulative gain of 37.7 percent at average rate of 4.7 percent per year. HP rose from 3702 thousand in Aug 2009 to 3888 thousand in Aug 2010, 4189 thousand in Aug 2011, 4381 thousand in Aug 2012, 4713 thousand in Aug 2013, 4792 thousand in Aug 2014, 5011 in Aug 2015 and 5119 thousand in Aug 2016 for cumulative gain of 38.3 percent at the average yearly rate of 4.7 percent. HNF has decreased from 5772 thousand in Aug 2006 to 5761 thousand in Aug 2016 or by 0.2 percent. HP has decreased from 5142 thousand in Aug 2006 to 5119 thousand in Aug 2016 or by 0.4 percent. The civilian noninstitutional population of the US, or those in condition of working, rose from 229.167 million in Aug 2006 to 253.854 million in Aug 2016, by 24.687 million or 10.8 percent. There is often ignored ugly fact that hiring decreased by around 0.4 percent while population available for working increased around 10.8 percent. Private hiring of 59.206 million in 2006 was equivalent to 25.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 57.557 million in 2015 or 22.9 percent of the civilian noninstitutional population of 250.801 million in 2015. The percentage of hiring in civilian noninstitutional population of 25.9 percent in 2006 would correspond to 64.957 million of hiring in 2015, which would be 7.400 million higher than actual 57.557 million in 2015. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html) explains the fact that there are many million fewer hires in the US than before the global recession. The labor market continues to be fractured, failing to provide an opportunity to exit from unemployment/underemployment or to find an opportunity for advancement away from declining inflation-adjusted earnings.

Table I-3, US, Total Nonfarm Hiring (HNF) and Total Private Hiring (HP) in the US in

Thousands and in Percentage of Total Employment Not Seasonally Adjusted

	HNF	Rate RNF	HP	Rate HP
2001 Aug	5421	4.1	4867	4.4
2002 Aug	5238	4.0	4696	4.3
2003 Aug	4985	3.8	4621	4.2
2004 Aug	5540	4.2	5057	4.5
2005 Aug	5903	4.4	5394	4.7
2006 Aug	5772	4.2	5142	4.4
2007 Aug	5662	4.1	5011	4.3
2008 Aug	4964	3.6	4504	3.9
2009 Aug	4185	3.2	3702	3.4
2010 Aug	4317	3.3	3888	3.6
2011 Aug	4602	3.5	4189	3.8
2012 Aug	4918	3.7	4381	3.9
2013 Aug	5256	3.9	4713	4.1
2014 Aug	5264	3.8	4792	4.0
2015 Aug	5640	4.0	5011	4.1
2016 Aug	5761	4.0	5119	4.2

Source: Bureau of Labor Statistics

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

Chart I-6 provides total nonfarm hiring on a monthly basis from 2001 to 2016. Nonfarm hiring rebounded in early 2010 but then fell and stabilized at a lower level than the early peak not-seasonally adjusted (NSA) of 4815 in May 2010 until it surpassed it with 5006 in Jun 2011 but declined to 3092 in Dec 2012. Nonfarm hiring fell to 2997 in Dec 2011 from 3814 in Nov 2011 and to revised 3629 in Feb 2012, increasing to 4197 in Mar 2012, 3092 in Dec 2012 and 4238 in Jan 2013 and declining to 3690 in Feb 2013. Nonfarm hires not seasonally adjusted increased to 4257 in Nov 2013 and 3223 in Dec 2013. Nonfarm hires reached 3730 in Dec 2014, 3919 in Dec 2015 and 5761 in Aug 2016. Chart I-6 provides seasonally adjusted (SA) monthly data. The number of seasonally-adjusted hires in Oct 2011 was 4239 thousand, increasing to revised 4470 thousand in Feb 2012, or 5.4 percent, moving to 4345 in Dec 2012 for cumulative increase of 2.6 percent from 4234 in Dec 2011 and 4488 in Dec 2013 for increase of 3.3 percent relative to 4345 in Dec 2012. The number of hires not seasonally adjusted was 5006 in Jun 2011, falling to 2997 in Dec 2011 but increasing to 4110 in Jan 2012 and declining to 3092 in Dec 2012. The number of nonfarm hiring not seasonally adjusted fell by 40.1 percent from 5006 in Jun 2011 to 2997 in Dec 2011 and fell 40.1 percent from 5162 in Jun 2012 to 3092 in Dec 2012 in a yearly-repeated seasonal pattern. The number of nonfarm hires not seasonally adjusted fell from 5114 in Jun 2013 to 3223 in Dec 2013, or decline of 37.0 percent, showing strong seasonality. The number of nonfarm hires not seasonally adjusted fell from 5570 in Jun 2014 to 3730 in Dec 2014 or 33.0 percent. The level of nonfarm hires fell from 5918 in Jun 2015 to 3919 in Dec 2015 or 33.8 percent.

Chart I-6, US, Total Nonfarm Hiring (HNF), 2001-2016 Month SA

Source: Bureau of Labor Statistics

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

Similar behavior occurs in the rate of nonfarm hiring in Chart I-7. Recovery in early 2010 was followed by decline and stabilization at a lower level but with stability in monthly SA estimates of 3.2 in Aug 2011 to 3.2 in Jan 2012, increasing to 3.3 in May 2012 and stabilizing to 3.3 in Jun 2012. The rate stabilized at 3.2 in Jul 2012, increasing to 3.3 in Aug 2012 but falling to 3.2 in Dec 2012 and 3.3 in Dec 2013. The rate not seasonally adjusted fell from 3.8 in Jun 2011 to 2.2 in Dec 2011, climbing to 3.8 in Jun 2012 but falling to 2.3 in Dec 2012. The rate of nonfarm hires not seasonally adjusted fell from 3.7 in Jun 2013 to 2.3 in Dec 2013. The NSA rate of nonfarm hiring fell from 4.0 in Jun 2014 to 2.6 in Dec 2014. The NSA rate fell from 4.1 in Jun 2015 to 2.7 in Dec 2015. Rates of nonfarm hiring NSA were in the range of 2.7 (Dec) to 4.4 (Jun) in 2006. The rate of nonfarm hiring SA stood at 3.6 in Aug 2016 and at 4.0 NSA.

Chart I-7, US, Rate Total Nonfarm Hiring, Month SA 2001-2016

Source: Bureau of Labor Statistics

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

There is only milder improvement in total private hiring shown in Chart I-8. Hiring private (HP) rose in 2010 with stability and renewed increase in 2011 followed by almost stationary series in 2012. The number of private hiring seasonally adjusted fell from 4043 thousand in Sep 2011 to 3933 in Dec 2011 or by 2.7 percent, decreasing to 4015 in Jan 2012 or decline by 0.7 percent relative to the level in Sep 2011. Private hiring fell to 3961 in Sep 2012 or lower by 2.0 percent relative to Sep 2011, moving to 4049 in Dec 2012 for increase of 0.8 percent relative to 4015 in Jan 2012. The number of private hiring not seasonally adjusted fell from 4626 in Jun 2011 to 2817 in Dec 2011 or by 39.1 percent, reaching 3855 in Jan 2012 or decline of 16.7 percent relative to Jun 2011 and moving to 2911 in Dec 2012 or 38.8 percent lower relative to 4757 in Jun 2012. Hires not seasonally adjusted fell from 4761 in Jun 2013 to 3059 in Dec 2013. The level of private hiring NSA fell from 5151 in Jun 2014 to 3532 in Dec 2014 or 31.4 percent. The level of private hiring fell from 5475 in Jun 2015 to 3697 in Dec 2015 or 32.5 percent. Companies reduce hiring in the latter part of the year that explains the high seasonality in year-end employment data. For example, NSA private hiring fell from 5614 in Jun 2006 to 3579 in Dec 2006 or by 36.2 percent. Private hiring NSA data are useful in showing the huge declines from the period before the global recession. HNF has decreased from 5772 thousand in Aug 2006 to 5761 thousand in Aug 2016 or by 0.2 percent. HP has decreased from 5142 thousand in Aug 2006 to 5119 thousand in Aug 2016 or by 0.4 percent. The civilian noninstitutional population of the US, or those in condition of working, rose from 229.167 million in Aug 2006 to 253.854 million in Aug 2016, by 24.687 million or 10.8 percent. There is often ignored ugly fact that hiring decreased by around 0.4 percent while population available for working increased around 10.8 percent. Private hiring of 59.206 million in 2006 was equivalent to 25.9 percent of the civilian noninstitutional population of 228.815, or those in condition of working, falling to 57.557 million in 2015 or 22.9 percent of the civilian noninstitutional population of 250.801 million in 2015. The percentage of hiring in civilian noninstitutional population of 25.9 percent in 2006 would correspond to 64.957 million of hiring in 2015, which would be 7.400 million higher than actual 57.557 million in 2015. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. Cyclical slow growth over the entire business cycle from IVQ2007 to the present in comparison with earlier cycles and long-term trend (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html) explains the fact that there are many million fewer hires in the US than before the global recession. The labor market continues to be fractured, failing to provide an opportunity to exit from unemployment/underemployment or to find an opportunity for advancement away from declining inflation-adjusted earnings.

Chart I-8, US, Total Private Hiring Month SA 2001-2016

Source: Bureau of Labor Statistics

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

Chart I-9 shows similar behavior in the rate of private hiring. The rate in 2011 in monthly SA data did not rise significantly above the peak in 2010. The rate seasonally adjusted fell from 3.7 in Sep 2011 to 3.5 in Dec 2011 and reached 3.6 in Dec 2012 and 3.6 in Dec 2013. The rate not seasonally adjusted (NSA) fell from 3.7 in Sep 2011 to 2.5 in Dec 2011, increasing to 3.8 in Oct 2012 but falling to 2.6 in Dec 2012 and 3.4 in Mar 2013. The NSA rate of private hiring fell from 4.8 in Jul 2006 to 3.4 in Aug 2009 but recovery was insufficient to only 3.9 in Aug 2012, 2.6 in Dec 2012 and 2.6 in Dec 2013. The NSA rate increased to 3.0 in Dec 2015 and 4.6 in Aug

2016.

Chart I-9, US, Rate Total Private Hiring Month SA 2001-2016

Source: Bureau of Labor Statistics

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

The JOLTS report of the Bureau of Labor Statistics also provides total nonfarm job openings (TNF JOB), TNF JOB rate and TNF LD (layoffs and discharges) shown in Table I-4 for the month of Jun from 2001 to 2016. The final column provides annual TNF LD for the years from 2001 to 2015. Nonfarm job openings (TNF JOB) increased from a peak of 4586 in Aug 2007 to 5562 in Aug 2016 or by 21.3 percent while the rate increased from 3.2 to 3.7. This was mediocre performance because the civilian noninstitutional population of the US, or those in condition of working, rose from 232.211 million in Aug 2007 to 253.854 million in Aug 2016, by 21.643 million or 9.3 percent. Nonfarm layoffs and discharges (TNF LD) rose from 1960 in Aug 2007 to 2265 in Aug 2009 or by 15.6 percent. The annual data show layoffs and discharges rising from 20.9 million in 2006 to 26.6 million in 2009 or by 27.3 percent. Business pruned payroll jobs to survive the global recession but there has not been hiring because of the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions.

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

	TNF JOB	TNF JOB Rate	TNF LD	TNF LD Annual
Aug 2001	4143	3.0	1976	24271
Aug 2002	3504	2.6	1939	22719
Aug 2003	3293	2.5	2121	23420
Aug 2004	3637	2.7	2085	22584
Aug 2005	4096	3.0	2044	22151
Aug 2006	4587	3.3	1742	20856
Aug 2007	4586	3.2	1960	21997
Aug 2008	3699	2.6	2238	23969
Aug 2009	2356	1.8	2265	26557
Aug 2010	2961	2.2	1935	21703
Aug 2011	3236	2.4	1889	20756
Aug 2012	3738	2.7	2003	20952
Aug 2013	4028	2.9	1912	19903
Aug 2014	5065	3.5	1847	20420
Aug 2015	5435	3.7	1910	20942
Aug 2016	5562	3.7	1785

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

Source: Bureau of Labor Statistics

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

Chart I-10 shows monthly job openings rising from the trough in 2009 to a high in the beginning of 2010. Job openings then stabilized into 2011 but have surpassed the peak of 3220 seasonally adjusted in Apr 2010 with 3576 seasonally adjusted in Dec 2012, which is higher by 11.1 percent relative to Apr 2010 but higher by 0.6 percent relative to 3556 in Nov 2012 and lower by 7.2 percent than 3852 in Mar 2012. Nonfarm job openings increased from 3576 in Dec 2012 to 3742 in Dec 2013 or by 4.6 percent and to 4815 in Dec 2014 or 28.7 percent relative to 2013. The high of job openings not seasonally adjusted was 3408 in Apr 2010 that was surpassed by 3647 in Jul 2011, increasing to 3905 in Oct 2012 but declining to 3218 in Dec 2012 and increasing to 3369 in Dec 2013. The level of job opening NSA increased to 4844 in Dec 2015. The level of job opening NSA increased to 562 in Aug 2016. The level of job openings not seasonally adjusted fell to 3218 in Dec 2012 or by 17.3 percent relative to 3891 in Apr 2012. There is here again the strong seasonality of year-end labor data. Job openings fell from 4199 in Apr 2013 to 3369 in Dec 2013 and from 4829 in Apr 2014 to 44033 in Dec 2014, showing strong seasonal effects. The level of nonfarm job openings decreased from 5862 in Apr 2015 to 4844 in Dec 2015 or by 17.4 percent. Nonfarm job openings (TNF JOB) increased from a peak of 4586 in Aug 2007 to 5562 in Aug 2016 or by 21.3 percent while the rate increased from 3.2 to 3.7. This was mediocre performance because the civilian noninstitutional population of the US, or those in condition of working, rose from 232.211 million in Aug 2007 to 253.854 million in Aug 2016, by 21.643 million or 9.3 percent. Nonfarm layoffs and discharges (TNF LD) rose from 1960 in Aug 2007 to 2265 in Aug 2009 or by 15.6 percent. The annual data show layoffs and discharges rising from 20.9 million in 2006 to 26.6 million in 2009 or by 27.3 percent. Business pruned payroll jobs to survive the global recession but there has not been hiring because of the low rate of GDP growth. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions.

Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions.

Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 28 quarters from IIIQ2009 to IIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp2q16_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2696.4 billion than actual $16,583.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html). US GDP in IIQ2016 is 14.0 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,583.1 billion in IIQ2016 or 10.6 percent at the average annual equivalent rate of 1.2 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Aug 1919 to Aug 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0258 in Aug 2016. The actual index NSA in Aug 2016 is 104.6251, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.5532 in Aug 2016. The output of manufacturing at 104.6251 in Aug 2016 is 19.2 percent below trend under this alternative calculation.

Chart I-10, US Job Openings, Thousands NSA, 2001-2016

Source: US Bureau of Labor Statistics

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

The rate of job openings in Chart I-11 shows similar behavior. The rate seasonally adjusted increased from 2.2 in Jan 2011 to 2.5 in Dec 2011, 2.6 in Dec 2012, 2.7 in Dec 2013 and 3.3 in Dec 2014. The rate seasonally adjusted stood at 3.6 in Dec 2015 and 3.6 in Aug 2016. The rate not seasonally adjusted rose from the high of 2.6 in Apr 2010 to 3.0 in Apr 2013, easing to 2.4 in Dec 2013. The rate of job openings NSA fell from 3.3 in Jul 2007 to 1.6 in Nov-Dec 2009, recovering to 3.3 in Dec 2015. The rate of job opening NSA stood at 3.7 in Aug 2016.

Chart I-11, US, Rate of Job Openings, NSA, 2001-2016

Source: US Bureau of Labor Statistics

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

Total separations are in Chart I-12. Separations are lower in 2012-16 than before the global recession but hiring has not recovered.

Chart I-12, US, Total Nonfarm Separations, Month Thousands SA, 2001-2016

Source: US Bureau of Labor Statistics

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

Chart I-13 provides annual total separations. Separations fell sharply during the global recession but hiring has not recovered relative to population growth.

Chart I-13, US, Total Separations, Annual, Thousands, 2001-2015

Source: US Bureau of Labor Statistics

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

Table I-5 provides total nonfarm total separations from 2001 to 2015. Separations fell from 61.3 million in 2006 to 47.6 million in 2010 or by 13.6 million and 48.2 million in 2011 or by 13.1 million. Total separations increased from 48.2 million in 2011 to 52.0 million in 2013 or by 3.7 million and to 55.6 million in 2014 or by 7.4 million relative to 2011. Total separations increased to 58.943 million in 2015 or by 10.7 million relative to 2011.

Table I-5, US, Total Nonfarm Total Separations, Thousands, 2001-2015

Year	Annual Thousands
2001	64560
2002	58942
2003	56961
2004	58224
2005	60633
2006	61284
2007	60984
2008	58209
2009	51358
2010	47649
2011	48214
2012	50143
2013	51951
2014	55625
2015	58943

Source: US Bureau of Labor Statistics

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

Monthly data of layoffs and discharges reach a peak in early 2009, as shown in Chart I-14. Layoffs and discharges dropped sharply with the recovery of the economy in 2010 and 2011 once employers reduced their job count to what was required for cost reductions and loss of business. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth. Growth rates have been unusually low in the expansion of the current economic cyle.

Chart I-14, US, Total Nonfarm Layoffs and Discharges, Monthly Thousands SA, 2001-2016

Source: US Bureau of Labor Statistics

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

Layoffs and discharges in Chart I-15 rose sharply to a peak in 2009. There was pronounced drop into 2010 and 2011 with mild increase into 2012 and renewed decline into 2013. There is mild increase into 2014-2015.

Chart I-15, US, Total Nonfarm Layoffs and Discharges, Annual, 2001-2015

Source: US Bureau of Labor Statistics

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

Annual layoff and discharges are in Table I-6. Layoffs and discharges increased sharply from 20.856 million in 2006 to 26.557 million in 2009 or 27.3 percent. Layoff and discharges fell to 19.903 million in 2013 or 25.1 percent relative to 2009 and increased to 20.420 million in 2014 or 2.6 percent relative to 2013. Layoffs and discharges increased to 20.942 million in 2015 or 2.6 percent relative to 2014.

Table I-6, US, Total Nonfarm Layoffs and Discharges, Thousands, 2001-2015

Year	Annual Thousands
2001	24271
2002	22719
2003	23420
2004	22584
2005	22151
2006	20856
2007	21997
2008	23969
2009	26557
2010	21703
2011	20756
2012	20952
2013	19903
2014	20420
2015	20942

Source: US Bureau of Labor Statistics

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

IA2 Labor Underutilization. The Bureau of Labor Statistics also provides alternative measures of labor underutilization shown in Table I-7. The most comprehensive measure is U6 that consists of total unemployed plus total employed part time for economic reasons plus all marginally attached workers as percent of the labor force. U6 not seasonally adjusted has risen from 8.2 percent in 2006 to 9.3 percent in Sep 2016.

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

	U1	U2	U3	U4	U5	U6
2016
Sep	1.9	2.2	4.8	5.1	5.9	9.3
Aug	1.8	2.4	5.0	5.3	6.0	9.7
Jul	1.9	2.4	5.1	5.5	6.3	10.1
Jun	1.9	2.3	5.1	5.4	6.1	9.9
May	2.0	2.1	4.5	4.9	5.6	9.4
Apr	2.2	2.3	4.7	5.0	5.7	9.3
Mar	2.3	2.6	5.1	5.5	6.1	9.9
Feb	2.2	2.7	5.2	5.6	6.3	10.1
Jan	2.1	2.7	5.3	5.7	6.5	10.5
2015
Dec	2.1	2.4	4.8	5.2	5.9	9.8
Nov	2.1	2.3	4.8	5.2	5.8	9.6
Oct	2.1	2.3	4.8	5.2	6.0	9.5
Sep	2.0	2.2	4.9	5.3	6.0	9.6
Aug	2.1	2.5	5.2	5.6	6.3	10.3
Jul	2.0	2.7	5.6	6.0	6.7	10.7
Jun	2.1	2.5	5.5	5.8	6.6	10.8
May	2.4	2.5	5.3	5.6	6.4	10.4
Apr	2.4	2.5	5.1	5.5	6.4	10.4
Mar	2.6	2.9	5.6	6.0	6.8	11.0
Feb	2.7	3.0	5.8	6.3	7.1	11.4
Jan	2.7	3.1	6.1	6.5	7.4	12.0
2014
Dec	2.5	2.8	5.4	5.8	6.7	11.1
Nov	2.7	2.7	5.5	5.9	6.8	11.0
Oct	2.7	2.6	5.5	6.0	6.8	11.1
Sep	2.7	2.7	5.7	6.2	7.1	11.3
Aug	2.8	3.0	6.3	6.7	7.5	12.0
Jul	2.8	3.1	6.5	7.0	7.8	12.6
Jun	2.8	3.0	6.3	6.7	7.5	12.4
May	3.1	3.0	6.1	6.5	7.3	11.7
Apr	3.3	3.2	5.9	6.3	7.2	11.8
Mar	3.7	3.7	6.8	7.2	8.1	12.8
Feb	3.6	3.9	7.0	7.5	8.4	13.1
Jan	3.5	4.0	7.0	7.5	8.6	13.5
2013
Dec	3.5	3.5	6.5	7.0	7.9	13.0
Nov	3.7	3.5	6.6	7.1	7.9	12.7
Oct	3.7	3.6	7.0	7.4	8.3	13.2
Sep	3.7	3.5	7.0	7.5	8.4	13.1
Aug	3.7	3.8	7.3	7.9	8.7	13.6
Jul	3.7	3.8	7.7	8.3	9.1	14.3
Jun	3.9	3.8	7.8	8.4	9.3	14.6
May	4.1	3.7	7.3	7.7	8.5	13.4
Apr	4.3	3.9	7.1	7.6	8.5	13.4
Mar	4.3	4.3	7.6	8.1	9.0	13.9
Feb	4.3	4.6	8.1	8.6	9.6	14.9
Jan	4.3	4.9	8.5	9.0	9.9	15.4
2012
Dec	4.2	4.3	7.6	8.3	9.2	14.4
Nov	4.2	3.9	7.4	7.9	8.8	13.9
Oct	4.3	3.9	7.5	8.0	9.0	13.9
Sep	4.2	4.0	7.6	8.0	9.0	14.2
Aug	4.3	4.4	8.2	8.7	9.7	14.6
Jul	4.3	4.6	8.6	9.1	10.0	15.2
Jun	4.5	4.4	8.4	8.9	9.9	15.1
May	4.7	4.3	7.9	8.4	9.3	14.3
Apr	4.8	4.3	7.7	8.3	9.1	14.1
Mar	4.9	4.8	8.4	8.9	9.7	14.8
Feb	4.9	5.1	8.7	9.3	10.2	15.6
Jan	4.9	5.4	8.8	9.4	10.5	16.2
2011
Dec	4.8	5.0	8.3	8.8	9.8	15.2
Nov	4.9	4.7	8.2	8.9	9.7	15.0
Oct	5.0	4.8	8.5	9.1	10.0	15.3
Sep	5.2	5.0	8.8	9.4	10.2	15.7
Aug	5.2	5.1	9.1	9.6	10.6	16.1
Jul	5.2	5.2	9.3	10.0	10.9	16.3
Jun	5.1	5.1	9.3	9.9	10.9	16.4
May	5.5	5.1	8.7	9.2	10.0	15.4
Apr	5.5	5.2	8.7	9.2	10.1	15.5
Mar	5.7	5.8	9.2	9.7	10.6	16.2
Feb	5.6	6.0	9.5	10.1	11.1	16.7
Jan	5.6	6.2	9.8	10.4	11.4	17.3
Dec  2010	5.4	5.9	9.1	9.9	10.7	16.6
Annual
2015	2.3	2.6	5.3	5.7	6.4	10.4
2014	3.0	3.1	6.2	6.6	7.5	12.0
2013	3.9	3.9	7.4	7.9	8.8	13.8
2012	4.5	4.4	8.1	8.6	9.5	14.7
2011	5.3	5.3	8.9	9.5	10.4	15.9
2010	5.7	6.0	9.6	10.3	11.1	16.7
2009	4.7	5.9	9.3	9.7	10.5	16.2
2008	2.1	3.1	5.8	6.1	6.8	10.5
2007	1.5	2.3	4.6	4.9	5.5	8.3
2006	1.5	2.2	4.6	4.9	5.5	8.2
2005	1.8	2.5	5.1	5.4	6.1	8.9
2004	2.1	2.8	5.5	5.8	6.5	9.6
2003	2.3	3.3	6.0	6.3	7.0	10.1
2002	2.0	3.2	5.8	6.0	6.7	9.6
2001	1.2	2.4	4.7	4.9	5.6	8.1
2000	0.9	1.8	4.0	4.2	4.8	7.0

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/

Monthly seasonally adjusted measures of labor underutilization are provided in Table I-8. U6 climbed from 16.1 percent in Aug 2011 to 16.4 percent in Sep 2011 and then fell to 14.6 percent in Mar 2012, reaching 9.7 percent in Sep 2016. 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 23.6 million in job stress of unemployment/underemployment in Sep 2016, not seasonally adjusted, corresponding to 14.0 percent of the labor force (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html).

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

	U1	U2	U3	U4	U5	U6
Sep 2016	2.0	2.5	5.0	5.3	6.0	9.7
Aug	1.9	2.4	4.9	5.3	5.9	9.7
Jul	2.0	2.3	4.9	5.2	6.0	9.7
Jun	2.0	2.4	4.9	5.2	6.0	9.6
May	1.9	2.3	4.7	5.0	5.7	9.7
Apr	2.1	2.4	5.0	5.3	6.0	9.7
Mar	2.1	2.4	5.0	5.3	6.0	9.8
Feb	2.1	2.4	4.9	5.3	6.0	9.7
Jan	2.0	2.3	4.9	5.3	6.2	9.9
Dec 2015	2.1	2.4	5.0	5.4	6.1	9.9
Nov	2.1	2.5	5.0	5.4	6.1	9.9
Oct	2.1	2.5	5.0	5.4	6.2	9.8
Sep	2.1	2.5	5.1	5.4	6.2	10.0
Aug	2.2	2.6	5.1	5.5	6.2	10.3
Jul	2.1	2.6	5.3	5.7	6.4	10.4
Jun	2.2	2.6	5.3	5.7	6.4	10.5
May	2.4	2.7	5.5	5.8	6.6	10.7
Apr	2.3	2.6	5.4	5.9	6.7	10.8
Mar	2.4	2.7	5.5	5.9	6.7	10.9
Feb	2.5	2.7	5.5	6.0	6.8	11.0
Jan	2.6	2.7	5.7	6.1	7.0	11.3
Dec 2014	2.6	2.8	5.6	6.0	6.9	11.2
Nov	2.7	2.9	5.8	6.2	7.0	11.4
Oct	2.8	2.8	5.7	6.2	7.1	11.5
Sep	2.8	2.9	6.0	6.4	7.3	11.8
Aug	2.9	3.1	6.2	6.6	7.4	12.0
July	3.0	3.1	6.2	6.6	7.5	12.2
Jun	3.0	3.1	6.1	6.5	7.3	12.0
May	3.1	3.2	6.2	6.7	7.5	12.1
Apr	3.2	3.3	6.2	6.7	7.5	12.3
Mar	3.4	3.5	6.7	7.1	7.9	12.6
Feb	3.4	3.5	6.7	7.1	8.0	12.6
Jan	3.4	3.5	6.6	7.1	8.1	12.7
Dec 2013	3.6	3.5	6.7	7.3	8.1	13.1
Nov	3.7	3.7	6.9	7.4	8.2	13.1
Oct	3.8	4.0	7.2	7.7	8.6	13.7
Sep	3.8	3.8	7.3	7.8	8.6	13.7
Aug	3.9	3.8	7.3	7.8	8.6	13.6
Jul	3.9	3.8	7.3	7.9	8.7	13.8
Jun	4.0	3.9	7.5	8.1	9.1	14.2
May	4.1	3.9	7.5	7.9	8.8	13.8
Apr	4.1	4.1	7.6	8.1	8.9	14.0
Mar	4.1	4.1	7.5	8.0	8.9	13.8
Feb	4.1	4.1	7.7	8.2	9.2	14.3
Jan	4.2	4.3	8.0	8.4	9.4	14.5
Dec 2012	4.3	4.2	7.9	8.5	9.4	14.4
Nov	4.2	4.2	7.7	8.3	9.2	14.4
Oct	4.4	4.2	7.8	8.3	9.2	14.4
Sep	4.4	4.2	7.8	8.3	9.3	14.8
Aug	4.5	4.4	8.1	8.6	9.6	14.6
Jul	4.5	4.6	8.2	8.7	9.6	14.8
Jun	4.7	4.6	8.2	8.7	9.6	14.8
May	4.6	4.5	8.2	8.7	9.6	14.8
Apr	4.6	4.4	8.2	8.8	9.6	14.6
Mar	4.6	4.5	8.2	8.7	9.6	14.6
Feb	4.7	4.6	8.3	8.9	9.8	15.0
Jan	4.8	4.7	8.3	8.9	9.9	15.2
Dec 2011	4.9	4.9	8.5	9.1	10.0	15.2
Nov	5.0	5.0	8.6	9.3	10.1	15.5
Oct	5.1	5.1	8.8	9.4	10.3	15.8
Sep	5.4	5.2	9.0	9.7	10.5	16.4
Aug	5.4	5.2	9.0	9.6	10.5	16.1
Jul	5.3	5.3	9.0	9.6	10.6	15.9
Jun	5.3	5.3	9.1	9.7	10.7	16.1
May	5.3	5.4	9.0	9.5	10.3	15.8
Apr	5.2	5.4	9.1	9.7	10.5	16.1
Mar	5.3	5.4	9.0	9.5	10.4	15.9
Feb	5.3	5.5	9.0	9.6	10.6	16.0
Jan	5.5	5.5	9.1	9.7	10.8	16.2

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart I-16 provides U6 on a monthly basis from 2001 to 2016. There was a steep climb from 2007 into 2009 and then this measure of unemployment and underemployment stabilized at that high level but declined into 2012. The low of U6 SA was 8.0 percent in Mar 2007 and the peak was 17.1 percent in Apr 2010. 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-Time for Economic Reasons, Month, SA, 2001-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/

Chart I-17 provides the number employed part-time for economic reasons or who cannot find full-time employment. There are sharp declines at the end of 2009, 2010 and 2011 but an increase in 2012 followed by relative stability in 2013-2016.

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

Thousands, Month SA 2001-2016

Sources: US Bureau of Labor Statistics

http://www.bls.gov/

ICA3 Ten Million Fewer Full-time Jobs. There is strong seasonality in US labor markets around the end of the year.

• Seasonally adjusted part-time for economic reasons. The number employed part-time for economic reasons because they could not find full-time employment fell from 9.166 million in Sep 2011 to 7.793 million in Mar 2012, seasonally adjusted, or decline of 1.373 million in six months, as shown in Table I-9. The number employed part-time for economic reasons rebounded to 8.667 million in Sep 2012 for increase of 669,000 in one month from Aug to Sep 2012. The number employed part-time for economic reasons declined to 8.229 million in Oct 2012 or by 438,000 again in one month, further declining to 8.150 million in Nov 2012 for another major one-month decline of 79,000 and 7.922 million in Dec 2012 or fewer 228,000 in just one month. The number employed part-time for economic reasons increased to 8.030 million in Jan 2013 or 108,000 more than in Dec 2012 and to 8.089 million in Feb 2013, declining to 7.901 million in May 2013 but increasing to 8.104 million in Jun 2013. The number employed part-time for economic reasons fell to 7.837 million in Aug 2013 for decline of 256,000 in one month from 8.093 million in Jul 2013. The number employed part-time for economic reasons increased 171,000 from 7.837 million in Aug 2013 to 8.008 million in Sep 2013. The number part-time for economic reasons rose to 8.028 million in Oct 2013, falling by 320,000 to 7.708 million in Nov 2013. The number part-time for economic reasons increased to 7.763 million in Dec 2013, decreasing to 7.250 million in Jan 2014. The number employed part-time for economic reasons fell from 7.250 million in Jan 2014 to 7.230 million in Feb 2014. The number employed part-time for economic reasons increased to 7.428 million in Mar 2014 and 7.452 million in Apr 2014. The number employed part-time for economic reasons fell to 7.219 million in May 2014, increasing to 7.473 million in Jun 2014. The level employed part-time for economic reasons fell to 7.440 million in Jul 2014 and 7.213 million in Aug 2014. The level employed part-time for economic reasons fell to 7.124 million in Sep 2014, 7.065 million in Oct 2014 and 6.844 million in Nov 2014. The level employed part-time for economic reasons fell to 6.786 million in Dec 2014, increasing to 6.784 million in Jan 2015. The level employed part-time for economic reasons fell to 6.630 million in Feb 2015, increasing to 6.673 million in Mar 2015. The level of employed part-time for economic reasons fell to 6.549 million in Apr 2015, increasing to 6.600 million in May 2015. The level employed part-time for economic reasons fell to 6.465 million in Jun 2015 and 6.300 million in Jul 2015. The level employed part-time for economic reasons increased to 6.481 million in Aug 2015, declining to 6.034 million in Sep 2015. The level employed part-time for economic reasons fell to 5.761 million in Oct 2015, increasing to 6.085 million in Nov 2015. The level of part-time for economic reasons fell to 6.022 million in Dec 2015, decreasing to 5.998 million in Jan 2016. The level employed part-time for economic reasons did not change to 5.988 in Feb 2016 and increased to 6.123 million in Mar 2016. The level employed part-time for economic reasons fell to 5.962 million in Apr 2016 and increased to 6.430 million in May 2016. The level of part-time for economic reasons fell to 5.843 million in Jun 2016, increasing to 5.940 million in Jul 2016. The level of part-time for economic reasons increased to 6.053 million in Aug 2016, decreasing to 5.894 million in Sep 2016. There is an increase of 231,000 in part-time for economic reasons from Aug 2012 to Oct 2012 and of 152,000 from Aug 2012 to Nov 2012.
• Seasonally adjusted full-time. The number employed full-time increased from 112.923 million in Oct 2011 to 115.023 million in Mar 2012 or 2.100 million but then fell to 114.224 million in May 2012 or 0.799 million fewer full-time employed than in Mar 2012. The number employed full-time increased from 114.750 million in Aug 2012 to 115.558 million in Oct 2012 or increase of 0.808 million full-time jobs in two months and further to 115.759 million in Jan 2013 or increase of 1.009 million more full-time jobs in five months from Aug 2012 to Jan 2013. The number of full time jobs decreased slightly to 115.689 million in Feb 2013, increasing to 116.211 million in May 2013 and 116.120 million in Jun 2013. Then number of full-time jobs increased to 116.156 million in Jul 2013, 116.475 million in Aug 2013 and 116.907 million in Sep 2013. The number of full-time jobs fell to 116.345 million in Oct 2013 and increased to 117.044 in Nov 2013. The level of full-time jobs increased to 117.307 million in Dec 2013, increasing to 117.568 million in Jan 2014 and 117.765 million in Feb 2014. The level of employment full-time increased to 117.950 million in Mar 2014 and 118.466 million in Apr 2014. The level of full-time employment reached 118.746 million in May 2014, decreasing to 118.233 million in Jun 2014. The level of full-time jobs increased to 118.454 million in Jul 2014 and 118.778 million in Aug 2014. The level of full-time jobs increased to 119.364 million in Sep 2014, 119.745 million in Oct 2014 and 119.641 million in Nov 2014. The level of full-time jobs increased to 119.999 million in Dec 2014 and 120.662 million in Jan 2015. The level of full-time jobs increased to 120.788 million in Feb 2015 and 120.976 million in Mar 2015. The level of full-time jobs decreased to 120.799 million in Apr 2015, increasing to 121.415 million in May 2015 and decreasing to 121.056 million in Jun 2015. The level of full-time jobs increased to 121.641 million in Jul 2015 and increased to 122.045 million in Aug 2015, decreasing to 121.873 million in Sep 2015. The level of full-time jobs increased to 122.054 million in Oct 2015 and increased to 122.099 million in Nov 2015. The level of full-time jobs increased to 122.603 million in Dec 2015 and 123.141 million in Jan 2016. The level of full-time jobs increased to 123.206 million in Feb 2016 and increased to 123.447 million in Mar 2016. The level of full-time jobs decreased to 123.194 million in Apr 2016 and 123.135 million in May 2016. The level of full-time jobs increased to 123.586 million in Jun 2016, increasing to 123.892 million in Jul 2016. The level of full-time jobs increased to 124.301 million in Aug 2016, decreasing to 124.296 million in Sep 2016. Adjustments of benchmark and seasonality-factors at the turn of every year could affect comparability of labor market indicators (http://cmpassocregulationblog.blogspot.com/2016/02/fluctuating-risk-financial-assets-in.html http://cmpassocregulationblog.blogspot.com/2015/02/job-creation-and-monetary-policy-twenty.html http://cmpassocregulationblog.blogspot.com/2014/02/financial-instability-rules.html http://cmpassocregulationblog.blogspot.com/2013/02/thirty-one-million-unemployed-or.html).
• Not seasonally adjusted part-time for economic reasons. The number of employed part-time for economic reasons actually increased without seasonal adjustment from 8.271 million in Nov 2011 to 8.428 million in Dec 2011 or by 157,000 and then to 8.918 million in Jan 2012 or by an additional 490,000 for cumulative increase from Nov 2011 to Jan 2012 of 647,000. The level of employed part-time for economic reasons then fell from 8.918 million in Jan 2012 to 7.867 million in Mar 2012 or by 1.051 million and to 7.694 million in Apr 2012 or 1.224 million fewer relative to Jan 2012. In Aug 2012, the number employed part-time for economic reasons reached 7.842 million NSA or 148,000 more than in Apr 2012. The number employed part-time for economic reasons increased from 7.842 million in Aug 2012 to 8.110 million in Sep 2012 or by 3.4 percent. The number part-time for economic reasons fell from 8.110 million in Sep 2012 to 7.870 million in Oct 2012 or by 240.000 in one month. The number employed part-time for economic reasons NSA increased to 8.628 million in Jan 2013 or 758,000 more than in Oct 2012. The number employed part-time for economic reasons fell to 8.298 million in Feb 2013, which is lower by 330,000 relative to 8.628 million in Jan 2013 but higher by 428,000 relative to 7.870 million in Oct 2012. The number employed part time for economic reasons fell to 7.734 million in Mar 2013 or 564,000 fewer than in Feb 2013 and fell to 7.709 million in Apr 2013. The number employed part-time for economic reasons reached 7.618 million in May 2013. The number employed part-time for economic reasons jumped from 7.618 million in May 2013 to 8.440 million in Jun 2013 or 822,000 in one month. The number employed part-time for economic reasons fell to 8.324 million in Jul 2013 and 7.690 million in Aug 2013. The number employed part-time for economic reasons NSA fell to 7.522 million in Sep 2013, increasing to 7.700 million in Oct 2013. The number employed part-time for economic reasons fell to 7.563 million in Nov 2013 and increased to 7.990 million in Dec 2013. The number employed part-time for economic reasons fell to 7.771 million in Jan 2014 and 7.397 million in Feb 2014. The level of part-time for economic reasons increased to 7.455 million in Mar 2014 and fell to 7.243 million in Apr 2014. The number of part-time for economic reasons fell to 6.960 million in May 2014, increasing to 7.805 million in Jun 2014. The level of part-time for economic reasons fell to 7.665 million in Jul 2014 and 7.083 million in Aug 2014. The level of part-time for economic reasons fell to 6.711 million in Sep 2014 and increased to 6.787 million in Oct 2014. The level of part-time for economic reasons reached 6.713 million in Nov 2014 and 6.970 million in Dec 2014, increasing to 7.269 million in Jan 2015. The level of part-time for economic reasons fell to 6.772 million in Feb 2015 and 6.672 million in Mar 2015, falling to 6.356 million in Apr 2015. The level of part-time for economic reasons increased to 6.363 million in May 2015 and to 6.776 million in Jun 2015, decreasing to 6.511 million in Jul 2015. The level of part-time for economic reasons fell to 6.361 million in Aug 2015 and 5.693 million in Sep 2015. The level of part-time for economic reasons fell to 5.536 million in Oct 2015, increasing to 5.967 million in Nov 2015. The level of part-time for economic reasons increased to 6.179 million in Dec 2015, increasing to 6.406 million in Jan 2016. The level of part-time for economic reasons decreased to 6.106 million in Feb 2016 and increased to 6.138 million in Mar 2016. The level of part-time for economic reasons decreased to 5.771 million in Apr 2016 and increased to 6.238 million in May 2016. The level of part-time for economic reasons decreased to 6.119 million in Jun 2016, increasing to 6.157 million in Jul 2016. The level of part-time for economic reasons fell to 5.963 million in Aug 2016, decreasing to 5.550 million in Sep 2016.
• Not seasonally adjusted full-time. The number employed full time without seasonal adjustment fell from 113.138 million in Nov 2011 to 113.050 million in Dec 2011 or by 88,000 and fell further to 111.879 in Jan 2012 for cumulative decrease of 1.259 million. The number employed full-time not seasonally adjusted fell from 113.138 million in Nov 2011 to 112.587 million in Feb 2012 or by 551.000 but increased to 116.214 million in Aug 2012 or 3.076 million more full-time jobs than in Nov 2011. The number employed full-time not seasonally adjusted decreased from 116.214 million in Aug 2012 to 115.678 million in Sep 2012 for loss of 536,000 full-time jobs and rose to 116.045 million in Oct 2012 or by 367,000 full-time jobs in one month relative to Sep 2012. The number employed full-time NSA fell from 116.045 million in Oct 2012 to 115.515 million in Nov 2012 or decline of 530.000 in one month. The number employed full-time fell from 115.515 in Nov 2012 to 115.079 million in Dec 2012 or decline by 436,000 in one month. The number employed full time fell from 115.079 million in Dec 2012 to 113.868 million in Jan 2013 or decline of 1.211 million in one month. The number of full time jobs increased to 114.191 in Feb 2012 or by 323,000 in one month and increased to 114.796 million in Mar 2013 for cumulative increase from Jan by 928,000 full-time jobs but decrease of 283,000 from Dec 2012. The number employed full time reached 117.400 million in Jun 2013 and increased to 117.688 in Jul 2013 or by 288,000. The number employed full-time reached 117.868 million in Aug 2013 for increase of 180,000 in one month relative to Jul 2013. The number employed full-time fell to 117.308 million in Sep 2013 or by 560,000. The number employed full-time fell to 116.798 million in Oct 2013 or decline of 510.000 in one month. The number employed full-time rose to 116.875 million in Nov 2013, falling to 116.661 million in Dec 2013. The number employed full-time fell to 115.744 million in Jan 2014 but increased to 116.323 million in Feb 2014. The level of full-time jobs increased to 116.985 in Mar 2014 and 118.073 million in Apr 2014. The number of full-time jobs increased to 119.179 million in May 2014, increasing to 119.472 million in Jun 2014. The level of full-time jobs increased to 119.900 million in Jul 2014. Comparisons over long periods require use of NSA data. The number with full-time jobs fell from a high of 123.219 million in Jul 2007 to 108.777 million in Jan 2010 or by 14.442 million. The number with full-time jobs in Sep 2016 is 124.278 million, which is higher by 1.059 million relative to the peak of 123.219 million in Jul 2007.
• Loss of full-time jobs. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 254.091 million in Sep 2016 or by 22.133 million (http://www.bls.gov/data/). The number with full-time jobs in Sep 2016 is 124.278 million, which is higher by 1.059 million relative to the peak of 123.219 million in Jul 2007. The ratio of full-time jobs of 123.219 million in Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 134.922 million full-time jobs with population of 254.091 million in Sep 2016 (0.531 x 254.091) or 10.644 million fewer full-time jobs relative to actual 124.278 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 20 million. Mediocre GDP growth is the main culprit of the fractured US labor market. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 28 quarters from IIIQ2009 to IIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp2q16_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2696.4 billion than actual $16,583.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html). US GDP in IIQ2016 is 14.0 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,583.1 billion in IIQ2016 or 10.6 percent at the average annual equivalent rate of 1.2 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Aug 1919 to Aug 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0258 in Aug 2016. The actual index NSA in Aug 2016 is 104.6251, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.5532 in Aug 2016. The output of manufacturing at 104.6251 in Aug 2016 is 19.2 percent below trend under this alternative calculation.

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

	Part-time Thousands	Full-time Millions
Seasonally Adjusted
Sep 2016	5,894	124.296
Aug 2016	6,053	124.301
Jul 2016	5,940	123.892
Jun 2016	5,843	123.586
May 2016	6,430	123.135
Apr 2016	5,962	123.194
Mar 2016	6,123	123.447
Feb 2016	5,988	123.206
Jan 2016	5,988	123.141
Dec 2015	6,022	122.603
Nov 2015	6,085	122.099
Oct 2015	5,761	122.054
Sep 2015	6,034	121.873
Aug 2015	6,481	122.045
Jul 2015	6,300	121.641
Jun 2015	6,465	121.056
May 2015	6,600	121.415
Apr 2015	6,549	120.799
Mar 2015	6,673	120.976
Feb 2015	6,630	120.788
Jan 2015	6,784	120.662
Dec 2014	6,786	119.999
Nov 2014	6,844	119.641
Oct 2014	7,065	119.745
Sep 2014	7,124	119.364
Aug 2014	7,213	118.778
Jul 2014	7,440	118.454
Jun 2014	7,473	118.233
May 2014	7,219	118.746
Apr 2014	7,452	118.466
Mar 2014	7,428	117.950
Feb 2014	7,230	117.765
Jan 2014	7,250	117.568
Dec 2013	7,763	117.307
Nov 2013	7,708	117.044
Oct 2013	8,028	116.345
Sep 2013	8,008	116.907
Aug 2013	7,837	116.475
Jul 2013	8,093	116.156
Jun 2013	8,104	116.120
May 2013	7,901	116.211
Apr 2013	7,924	116.017
Mar 2013	7,682	115.789
Feb 2013	8,089	115.689
Jan 2013	8,030	115.759
Dec 2012	7,922	115.774
Nov 2012	8,150	115.656
Oct 2012	8,229	115.558
Sep 2012	8,667	115.254
Aug 2012	7,998	114.750
Jul 2012	8,092	114.575
Jun 2012	8,081	114.742
May 2012	8,123	114.224
Apr 2012	7,907	114.358
Mar 2012	7,793	115.023
Feb 2012	8,214	114.151
Jan 2012	8,267	113.767
Dec 2011	8,171	113.774
Nov 2011	8,447	113.213
Oct 2011	8,657	112.923
Sep 2011	9,166	112.544
Aug 2011	8,788	112.723
Jul 2011	8,281	112.193
Not Seasonally Adjusted
Sep 2016	5,550	124.278
Aug 2016	5,963	125.892
Jul 2016	6,157	125.507
Jun 2016	6,119	124.903
May 2016	6,238	123.548
Apr 2016	5,771	122.742
Mar 2016	6,138	122.522
Feb 2016	6,106	121.757
Jan 2016	6,406	121.411
Dec 2015	6,179	122.013
Nov 2015	5,967	121.897
Oct 2015	5,536	122.466
Sep 2015	5,693	122.303
Aug 2015	6,361	123.420
Jul 2015	6,511	123.142
Jun 2015	6,776	122.268
May 2015	6,363	121.863
Apr 2015	6,356	120.402
Mar 2015	6,672	119.981
Feb 2015	6,772	119.313
Jan 2015	7,269	118.840
Dec 2014	6,970	119.394
Nov 2014	6,713	119.441
Oct 2014	6,787	120.176
Sep 2014	6,711	119.791
Aug 2014	7,083	120.110
Jul 2014	7,665	119.900
Jun 2014	7,805	119.472
May 2014	6,960	119.179
Apr 2014	7,243	118.073
Mar 2014	7,455	116.985
Feb 2014	7,397	116.323
Jan 2014	7,771	115.774
Dec 2013	7,990	116.661
Nov 2013	7,563	116.875
Oct 2013	7,700	116.798
Sep 2013	7,522	117.308
Aug 2013	7,690	117.868
Jul 2013	8,324	117.688
Jun 2013	8,440	117.400
May 2013	7,618	116.643
Apr 2013	7,709	115.674
Mar 2013	7,734	114.796
Feb 2013	8,298	114.191
Jan 2013	8,628	113.868
Dec 2012	8,166	115.079
Nov 2012	7,994	115.515
Oct 2012	7,870	116.045
Sep 2012	8,110	115.678
Aug 2012	7,842	116.214
Jul 2012	8,316	116.131
Jun 2012	8,394	116.024
May 2012	7,837	114.634
Apr 2012	7,694	113.999
Mar 2012	7,867	113.916
Feb 2012	8,455	112.587
Jan 2012	8,918	111.879
Dec 2011	8,428	113.050
Nov 2011	8,271	113.138
Oct 2011	8,258	113.456
Sep 2011	8,541	112.980
Aug 2011	8,604	114.286
Jul 2011	8,514	113.759
Jun 2011	8,738	113.255
May 2011	8,270	112.618
Apr 2011	8,425	111.844
Mar 2011	8,737	111.186
Feb 2011	8,749	110.731
Jan 2011	9,187	110.373
Dec 2010	9,205	111.207
Nov 2010	8,670	111.348
Oct 2010	8,408	112.342
Sep 2010	8,628	112.385
Aug 2010	8,628	113.508
Jul 2010	8,737	113.974
Jun 2010	8,867	113.856
May 2010	8,513	112.809
Apr 2010	8,921	111.391
Mar 2010	9,343	109.877
Feb 2010	9,282	109.100
Jan 2010	9,290	108.777 (low)
Dec 2009	9,354 (high)	109.875
Nov 2009	8,894	111.274
Oct 2009	8,474	111.599
Sep 2009	8,255	111.991
Aug 2009	8,835	113.863
Jul 2009	9,103	114.184
Jun 2009	9,301	114.014
May 2009	8,785	113.083
Apr 2009	8,648	112.746
Mar 2009	9,305	112.215
Feb 2009	9,170	112.947
Jan 2009	8,829	113.815
Dec 2008	8,250	116.422
Nov 2008	7,135	118.432
Oct 2008	6,267	120.020
Sep 2008	5,701	120.213
Aug 2008	5,736	121.556
Jul 2008	6,054	122.378
Jun 2008	5,697	121.845
May 2008	5,096	120.809
Apr 2008	5,071	120.027
Mar 2008	5,038	119.875
Feb 2008	5,114	119.452
Jan 2008	5,340	119.332
Dec 2007	4,750	121.042
Nov 2007	4,374	121.846
Oct 2007	4,028	122.006
Sep 2007	4,137	121.728
Aug 2007	4,494	122.870
Jul 2007	4,516	123.219 (high)
Jun 2007	4,469	122.150
May 2007	4,315	120.846
Apr 2007	4,205	119.609
Mar 2007	4,384	119.640
Feb 2007	4,417	119.041
Jan 2007	4,726	119.094
Dec 2006	4,281	120.371
Nov 2006	4,054	120.507
Oct 2006	4,010	121.199
Sep 2006	3,735 (low)	120.780
Aug 2006	4,104	121.979
Jul 2006	4,450	121.951
Jun 2006	4,456	121.070
May 2006	3,968	118.925
Apr 2006	3,787	118.559
Mar 2006	4,097	117.693
Feb 2006	4,403	116.823
Jan 2006	4,597	116.395

Source: US Bureau of Labor Statistics

http://www.bls.gov/

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

Chart I-18, US, Number Unemployed for 27 Weeks or Over, Thousands SA Month 2001-2016

Sources: US Bureau of Labor Statistics

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

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

Chart I-19, US, Marginally Attached to the Labor Force, NSA Month, Thousands, 2001-2016

Sources: US Bureau of Labor Statistics

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

Chart I-20 provides the level of full-time jobs from 2001 to 2016. The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 254.091 million in Sep 2016 or by 22.133 million (http://www.bls.gov/data/). The number with full-time jobs in Sep 2016 is 124.278 million, which is higher by 1.059 million relative to the peak of 123.219 million in Jul 2007. The ratio of full-time jobs of 123.219 million in Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 134.922 million full-time jobs with population of 254.091 million in Sep 2016 (0.531 x 254.091) or 10.644 million fewer full-time jobs relative to actual 124.278 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 20 million. Mediocre GDP growth is the main culprit of the fractured US labor market.

There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:

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

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

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

Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2016

Sources: US Bureau of Labor Statistics

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

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2016. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2016

Sources: US Bureau of Labor Statistics

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

Chart I-20B provides number of full-time jobs in the US from 1968 to 2016. There were multiple recessions followed by expansions without contraction of full-time jobs and without recovery as during the period after 2008. The problem is specific of the current cycle and not secular.

Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2016

Sources: US Bureau of Labor Statistics

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

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2016. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.

Chart I-20C, US, Noninstitutional Civilian Population, Thousands, 1968-2016

Sources: US Bureau of Labor Statistics

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

IA4 Theory and Reality of Secular Stagnation: Youth and Middle-Age Unemployment. Three tables support the argument that the proper comparison of the business cycle is between the recessions of the 1980s and the global recession after IVQ2007 and not as argued erroneously with the Great Depression of the 1930s. Table I-9A provides percentage change of real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Data are available for the 1930s only on a yearly basis. US GDP fell 4.7 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1982 and 4.2 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. In contrast, GDP grew 2.5 percent in 2010, 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014 and 2.6 percent in 2015. Actual annual equivalent GDP growth in the four quarters of 2012, twelve quarters from IQ2013 to IVQ2015, IQ2016 and IIQ2016 is 2.0 percent and 1.3 percent in the four quarters ending in IIQ2016. GDP grew at 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. The forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 1.7 to 1.9 percent in 2016 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20160921.pdf) with less reliable forecast of 1.9 to 2.2 percent in 2017 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20160921.pdf). Growth of GDP in the expansion from IIIQ2009 to IIQ2016 has been at average 2.1 percent in annual equivalent.

Table I-9A, US, Percentage Change of GDP in the 1930s, 1980s and 2000s, ∆%

Year	GDP ∆%	Year	GDP ∆%	Year	GDP ∆%
1930	-8.5	1980	-0.2	2000	4.1
1931	-6.4	1981	2.6	2001	1.0
1932	-12.9	1982	-1.9	2002	1.8
1933	-1.3	1983	4.6	2003	2.8
1934	10.8	1984	7.3	2004	3.8
1935	8.9	1985	4.2	2005	3.3
1936	12.9	1986	3.5	2006	2.7
1937	5.1	1987	3.5	2007	1.8
1938	-3.3	1988	4.2	2008	-0.3
1939	8.0	1989	3.7	2009	-2.8
1940	8.8	1990	1.9	2010	2.5
1941	17.7	1991	-0.1	2011	1.6
1942	18.9	1992	3.6	2012	2.2
1943	17.0	1993	2.7	2013	1.7
1944	8.0	1994	4.0	2014	2.4
1945	-1.0	1995	2.7	2015	2.6

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

Characteristics of the four cyclical contractions are in Table I-9B with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.7 percent, which is almost equal to the decline of 4.2 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

Table I-9B, US, Number of Quarters, GDP Cumulative Percentage Contraction and Average Percentage Annual Equivalent Rate in Cyclical Contractions   

	Number of Quarters	Cumulative Percentage Contraction	Average Percentage Rate
IIQ1953 to IIQ1954	3	-2.4	-0.8
IIIQ1957 to IIQ1958	3	-3.0	-1.0
IVQ1973 to IQ1975	5	-3.1	-0.6
IQ1980 to IIIQ1980	2	-2.2	-1.1
IIIQ1981 to IVQ1982	4	-2.5	-0.64
IVQ2007 to IIQ27009	6	-4.2	-0.72

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

Table I-9C shows the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the twenty-eight quarters of the current cyclical expansion from IIIQ2009 to IIQ2016. In sharp contrast, the average growth rate of GDP was:

• 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986
• 5.4 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986
• 5.2 percent in the first sixteen quarters of expansion from IQ1983 to IVQ1986
• 5.0 percent in the first seventeen quarters of expansion from IQ1983 to IQ1987
• 5.0 percent in the first eighteen quarters of expansion from IQ1983 to IIQ1987
• 4.9 percent in the first nineteen quarters of expansion from IQ1983 to IIIQ1987
• 5.0 percent in the first twenty quarters of expansion from IQ1983 to IVQ1987
• 4.9 percent in the first twenty-first quarters of expansion from IQ1983 to IQ1988
• 4.9 percent in the first twenty-two quarters of expansion from IQ1983 to IIQ1988
• 4.8 percent in the first twenty-three quarters of expansion from IQ1983 to IIIQ1988
• 4.8 percent in the first twenty-four quarters of expansion from IQ1983 to IVQ1988
• 4.8 percent in the first twenty-five quarters of expansion from IQ1983 to IQ1989
• 4.7 percent in the first twenty-six quarters of expansion from IQ1983 to IIQ1989
• 4.7 percent in the first twenty-seven quarters of expansion from IQ1983 to IIIQ1989
• 4.5 percent in the first twenty-eight quarters of expansion from IQ1093 to IVQ1989

The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill with annual growth of 2.5 percent in 2010 decelerating to 1.6 percent annual growth in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014 and 2.6 percent in 2015 (http://www.bea.gov/iTable/index_nipa.cfm) The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988. 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989. 4.5 percent from IQ1983 to IVQ1989 and at 7.8 percent from IQ1983 to IVQ1983. GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the four quarters of 2012, the four quarters of 2013, the four quarters of 2014, the four quarters of Q2015, IQ2016 and IIQ2016 accumulated to 9.2 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IIQ2016 of $16,583.1 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/18: {[($16,583.1/$15,190.3)^4/18 -1]100 = 2.0 percent}.

Table I-9C shows that GDP grew 15.5 percent in the first twenty-eight quarters of expansion from IIIQ2009 to IIQ2016 at the annual equivalent rate of 2.1 percent.

Table I-9C, US, Number of Quarters, Cumulative Growth and Average Annual Equivalent Growth Rate in Cyclical Expansions

	Number of Quarters	Cumulative Growth ∆%	Average Annual Equivalent Growth Rate
IIIQ 1954 to IQ1957	11	12.8	4.5
First Four Quarters IIIQ1954 to IIQ1955	4	7.8
IIQ1958 to IIQ1959	5	10.0	7.9
First Four Quarters IIIQ1958 to IIQ1959	4	9.2
IIQ1975 to IVQ1976	8	8.3	4.1
First Four Quarters IIIQ1975 to IIQ1976	4	6.1
IQ1983-IQ1986 IQ1983-IIIQ1986 IQ1983-IVQ1986 IQ1983-IQ1987 IQ1983-IIQ1987 IQ1983 to IIIQ1987 IQ1983 to IVQ1987 IQ1983 to IQ1988 IQ1983 to IIQ1988 IQ1983 to IIIQ1988 IQ1983 to IVQ1988 IQ1983 to IQ1989 IQ1983 to IIQ1989 IQ1983 to IIIQ1989 IQ1983 to IVQ1989	13 15 16 17 18 19 20 21 22 23 24 25 26 27 28	19.9 21.6 22.3 23.1 24.5 25.6 27.7 28.4 30.1 30.9 32.6 34.0 35.0 36.0 36.3	5.7 5.4 5.2 5.0 5.0 4.9 5.0 4.9 4.9 4.8 4.8 4.8 4.7 4.7 4.5
First Four Quarters IQ1983 to IVQ1983	4	7.8
Average First Four Quarters in Four Expansions*		7.7
IIIQ2009 to IIQ2016	28	15.5	2.1
First Four Quarters IIIQ2009 to IIQ2010		2.7

*First Four Quarters: 7.8% IIIQ1954-IIQ1955; 9.2% IIIQ1958-IIQ1959; 6.1% IIIQ1975-IQ1976; 7.8% IQ1983-IVQ1983

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

Table EMP provides the comparison between the labor market in the current whole cycle from 2007 to 2015 and the whole cycle from 1979 to 1989. In the entire cycle from 2007 to 2015, the number employed increased 2.787 million, full-time employed increased 0.401 million, part-time for economic reasons increased 1.970 million and population increased 18.934 million. The number employed increased 1.9 percent, full-time employed increased 0.3 percent, part-time for economic reasons increased 44.8 percent and population increased 8.2 percent. There is sharp contrast with the contractions of the 1980s and with most economic history of the United States. In the whole cycle from 1979 to 1989, the number employed increased 18.518 million, full-time employed increased 14.715 million, part-time for economic reasons increased 1.317 million and population increased 21.530 million. In the entire cycle from 1979 to 1989, the number employed increased 18.7 percent, full-time employed increased 17.8 percent, part-time for economic reasons increased 36.8 percent and population increased 13.1 percent. The difference between the 1980s and the current cycle after 2007 is in the high rate of growth after the contraction that maintained trend growth around 3.0 percent for the entire cycle and per capital growth at 2.0 percent. The evident fact is that current weakness in labor markets originates in cyclical slow growth and not in imaginary secular stagnation.

Table EMP, US, Annual Level of Employed, Full-Time Employed, Employed Part-Time for Economic Reasons and Noninstitutional Civilian Population, Millions

	Employed	Full-Time Employed	Part Time Economic Reasons	Noninstitutional Civilian Population
2000s
2000	136.891	113.846	3.227	212.577
2001	136.933	113.573	3.715	215.092
2002	136.485	112.700	4.213	217.570
2003	137.736	113.324	4.701	221.168
2004	139.252	114.518	4.567	223.357
2005	141.730	117.016	4.350	226.082
2006	144.427	119.688	4.162	228.815
2007	146.047	121.091	4.401	231.867
2008	145.362	120.030	5.875	233.788
2009	139.877	112.634	8.913	235.801
2010	139.064	111.714	8.874	237.830
2011	139.869	112.556	8.560	239.618
2012	142.469	114.809	8.122	243.284
2013	143.929	116.314	7.935	245.679
2014	146.305	118.718	7.213	247.947
2015	148.834	121.492	6.371	250.801
∆2007-2015	2.787	0.401	1.970	18.934
∆% 2007-2015	1.9	0.3	44.8	8.2
1980s
1979	98.824	82.654	3.577	164.863
1980	99.303	82.562	4.321	167.745
1981	100.397	83.243	4.768	170.130
1982	99.526	81.421	6.170	172.271
1983	100.834	82.322	6.266	174.215
1984	105.005	86.544	5.744	176.383
1985	107.150	88.534	5.590	178.206
1986	109.597	90.529	5.588	180.587
1987	112.440	92.957	5.401	182.753
1988	114.968	95.214	5.206	184.613
1989	117.342	97.369	4.894	186.393
∆1979-1989	18.518	14.715	1.317	21.530
∆% 1979-1989	18.7	17.8	36.8	13.1

Source: Bureau of Labor Statistics

http://www.bls.gov/

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. There are accentuated cyclic factors for both the entire population and the young population of ages 16 to 24 years. Table Summary Total provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment level (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would spread over long periods instead of immediately. All indicators of the labor market weakened sharply during the contraction and did not recover. Population continued to grow but all other variables collapsed and did not recover. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-16). Hansen (1938, 1939) finds secular stagnation in lower growth of an aging population. In the current US economy, Table Summary shows that population is dynamic while the labor market is fractured. There is key explanation in the behavior of the civilian labor force participation rate (CLFP) and the employment population ratio (EPOP) that collapsed during the global recession with inadequate recovery. Abandoning job searches are difficult to capture in labor statistics but likely explain the decline in the participation of the population in the labor force. Allowing for abandoning job searches, the total number of people unemployed or underemployed is 23.6 million or 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html).

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

	ICP	FTE	EMP	CLF	CLFP	EPOP	UNE
2006	228.8	119.7	144.4	151.4	66.2	63.1	7.0
2009	235.8	112.6	139.9	154.1	65.4	59.3	14.3
2012	243.3	114.8	142.5	155.0	63.7	58.6	12.5
2013	245.7	116.3	143.9	155.4	63.2	58.6	11.5
2014	247.9	118.7	146.3	155.9	62.9	59.0	9.6
2015	250.8	121.5	148.8	157.1	62.7	59.3	8.3
12/07	233.2	121.0	146.3	153.7	65.9	62.8	7.4
9/09	236.3	112.0	139.1	153.6	65.0	58.9	14.5
9/16	254.1	124.7	152.0	159.6	62.8	59.8	7.7

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

Source: Bureau of Labor Statistics

http://www.bls.gov/

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

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

	ICP	EMP	CLF	CLFP	EPOP	UNE	UNER
2006	36.9	20.0	22.4	60.6	54.2	2.4	10.5
2009	37.6	17.6	21.4	56.9	46.9	3.8	17.6
2012	38.8	17.8	21.3	54.9	46.0	3.5	16.2
2013	38.8	18.1	21.4	55.0	46.5	3.3	15.5
2014	38.7	18.4	21.3	55.0	47.6	2.9	13.4
2015	38.6	18.8	21.2	55.0	48.6	2.5	11.6
12/07	37.5	19.4	21.7	57.8	51.6	2.3	10.7
9/09	37.6	17.0	20.7	55.2	45.1	3.8	18.2
9/16	38.4	18.7	20.8	54.2	48.7	2.1	10.2

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

Source: Bureau of Labor Statistics

http://www.bls.gov/

The United States is experiencing high youth unemployment as in European economies. Table I-10 provides the employment level for ages 16 to 24 years of age estimated by the Bureau of Labor Statistics. On an annual basis, youth employment fell from 20.041 million in 2006 to 17.362 million in 2011 or 2.679 million fewer youth jobs and to 17.834 million in 2012 or 2.207 million fewer jobs. Youth employment fell from 20.041 million in 2006 to 18.057 million in 2013 or 1.984 million fewer jobs. Youth employment fell from 20.041 million in 2006 to 18.442 million in 2014 or 1.599 million. Youth employment fell from 20.041 million in 2006 to 18.756 million in 2015 or 1.285 million. The level of youth jobs fell from 20.129 million in Dec 2006 to 18.347 million in Dec 2014 for 1.782 million fewer youth jobs. The level of youth jobs fell from 20.129 million in Dec 2006 to 18.720 million in Dec 2015 or 1.409 million fewer jobs. Youth jobs fell from 21.268 million in Jun 2006 to 19.967 million in Jun 2016 or 1.301 million. During the seasonal peak months of youth employment in the summer from Jun to Aug, youth employment has fallen by more than two million jobs relative to 21.167 million in Aug 2006 to 18.972 million in Aug 2014 for 2.195 million fewer jobs. Youth employment fell from 21.914 million in Jul 2006 to 20.085 million in Jul 2014 for 1.829 million fewer youth jobs. The number of youth jobs fell from 21.268 million in Jun 2006 million to 19.421 million in Jun 2014 or 1.847 million fewer youth jobs. The number of jobs ages 16 to 24 years fell from 21.167 million in Aug 2006 to 18.636 million in Aug 2013 or by 2.531 million. The number of youth jobs fell from 19.604 million in Sep 2006 to 18.043 million in Sep 2013 or 1.561 million fewer youth jobs. The number of youth jobs fell from 20.129 million in Dec 2006 to 18.106 million in Dec 2013 or 2.023 million fewer jobs. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The youth civilian noninstitutional population increased 1.464 million from 37.302 in Feb 2007 to 38.766 million in Feb 2014 while the number of youth jobs decreased 2.058 million. The civilian noninstitutional population increased 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 while jobs for ages 16 to 24 years decreased 1.599 million from 19.538 million in Mar 2007 to 17.939 million in Mar 2014. The civilian noninstitutional population ages 16 to 24 years increased 1.410 million from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 while the number of youth jobs fell 1.347 million. The civilian noninstitutional population increased 1.370 million from 37.379 million in May 2007 to 38.749 million in May 2014 while the number of youth jobs decreased 1.128 million. The civilian noninstitutional population increased 1.330 million from 37.410 million in Jun 2007 to 38.740 million in Jun 2014 while the number of youth jobs fell 1.847 million from 21.268 million in Jun 2006 to 19.421 million in Jun 2014. The youth civilian noninstitutional population increased by 1.292 million from 37.443 million in Jul 2007 to 38.735 million in Jul 2014 while the number of youth jobs fell 1.632 million. The youth civilian noninstitutional population increased from 37.445 million in Aug 2007 to 38.706 million in Aug 2014 or 1.251 million while the number of youth jobs fell 1.441 million. The youth civilian noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014 while the number of youth jobs fell 1.500 million. The youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million while the number of youth jobs fell 1.072 million. The youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million while the number of youth jobs fell 1.327 million. The civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million while the number of youth jobs fell 1.782 million. The civilian noninstitutional population increased 1.971 million from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 while the number of youth jobs fell 1.091 million. The civilian noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015 while the number of youth jobs fell 0.960 million. The civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015 while the number of youth jobs fell 1.215 million. The youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015 while the number of youth jobs fell 1.165 million. The youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015 while the number of youth jobs fell 1.060 million. The youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015 while the number of youth jobs fell 1.479 million. The youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015 while the number of youth jobs fell 1.581 million. The youth civilian noninstitutional population increased 1.548 million from 37.008 million in Aug 2006 to 38.556 million in Aug 2015 while the number of youth jobs fell 1.590 million. The youth civilian noninstitutional population increased 1,498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015 while the number of youth jobs fell 1.249 million. The youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015 while the number of youth jobs fell 1.199 million. The youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015 while the number of youth jobs fell 1.418 million. The youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015 while the level of youth jobs 1.409 million. The youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016 while the level of youth jobs fell 0.844 million. The youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016 while the number of youth jobs fell 0.726 million. The youth civilian noninstitutional population increased 1,662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016 while the number of youth jobs fell 0.711 million. The youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016 while the number of youth jobs fell 0.895 million. The youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016 while the number of youth jobs fell 0.894 million. The youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016 while the number of youth jobs fell 1.301 million. The youth civilian noninstitutional population increased 1.461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016 while the number of youth jobs fell 1.458 million. The youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016 while the number of youth jobs fell 1.291 million. The youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016 while the number of youth jobs fell 0.911 million. The hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

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

Year	May	Jun	Jul	Aug	Sep	Dec	Annual
2001	19648	21212	22042	20529	19706	19547	20088
2002	19484	20828	21501	20653	19466	19394	19683
2003	19032	20432	20950	20181	18909	19136	19351
2004	19237	20587	21447	20660	19158	19619	19630
2005	19356	20949	21749	20814	19503	19733	19770
2006	19769	21268	21914	21167	19604	20129	20041
2007	19457	21098	21717	20413	19498	19361	19875
2008	19254	20466	21021	20096	18818	18378	19202
2009	17588	18726	19304	18270	16972	16615	17601
2010	17039	17920	18564	18061	16874	16727	17077
2011	17045	18180	18632	18067	17238	17234	17362
2012	17681	18907	19461	18171	17687	17604	17834
2013	17704	19125	19684	18636	18043	18106	18057
2014	18329	19421	20085	18972	18104	18347	18442
2015	18709	19789	20333	19577	18355	18720	18756
2016	18875	19967	20456	19876	18693

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

Chart I-21 provides US employment level ages 16 to 24 years from 2002 to 2016. Employment level is sharply lower in Sep 2015 relative to the peak in 2007. The following Chart I-21A relates youth employment and youth civilian noninstitutional population.

Chart I-21, US, Employment Level 16-24 Years, Thousands SA, 2001-2016

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

Chart I-21A provides the US civilian noninstitutional population ages 16 to 24 years not seasonally adjusted from 2001 to 2016. The civilian noninstitutional population ages 16 to 24 years increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013 or by 1.418 million while the number of jobs for ages 16 to 24 years fell by 2.230 million from 21.914 million in Jul 2006 to 19.684 million in Jul 2013. The civilian noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013 or by 1.386 million while the number of youth jobs fell by 1.777 million. The civilian noninstitutional population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 or by 1.355 million while the number of youth jobs fell by 1.455 million. The civilian noninstitutional population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013 or by 1.324 million while the number of youth jobs decreased 1.877 million from Oct 2006 to Oct 2013. The civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million while the number of youth jobs fell 1.799 million. The civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013 or by 1.272 million while the number of youth jobs fell 2.023 million from Dec 2006 to Dec 2013. The youth civilian noninstitutional population increased 1.488 million from 37.282 million in in Jan 2007 to 38.770 million in Jan 2014 while the number of youth jobs fell 2.035 million. The youth civilian noninstitutional population increased 1.464 million from 37.302 in Feb 2007 to 38.766 million in Feb 2014 while the number of youth jobs decreased 2.058 million. The civilian noninstitutional population increased 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 while jobs for ages 16 to 24 years decreased 1.599 million from 19.538 million in Mar 2007 to 17.939 million in Mar 2014. The civilian noninstitutional population ages 16 to 24 years increased 1.410 million from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 while the number of youth jobs fell 1.347 million. The civilian noninstitutional population increased 1.370 million from 37.379 million in May 2007 to 38.749 million in May 2014 while the number of youth jobs decreased 1.128 million. The civilian noninstitutional population increased 1.330 million from 37.410 million in Jun 2007 to 38.740 million in Jun 2014 while the number of youth jobs fell 1.847 million from 21.268 million in Jun 2006 to 19.421 million in Jun 2014. The youth civilian noninstitutional population increased by 1.292 million from 37.443 million in Jul 2007 to 38.735 million in Jul 2014 while the number of youth jobs fell 1.632 million. The youth civilian noninstitutional population increased from 37.445 million in Aug 2007 to 38.706 million in Aug 2014 or 1.251 million while the number of youth jobs fell 1.441 million. The youth civilian noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014 while the number of youth jobs fell 1.500 million. The youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million while the number of youth jobs fell 1.072 million. The youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million while the number of youth jobs fell 1.327 million. The civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million while the number of youth jobs fell 1.782 million. The civilian noninstitutional population increased 1.971 million from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 while the number of youth jobs fell 1.091 million. The civilian noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015 while the number of youth jobs fell 0.960 million. The civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015 while the number of youth jobs fell 1.215 million. The youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015 while the number of youth jobs fell 1.165 million. The youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015 while the number of youth jobs fell 1.060 million. The youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015 while the number of youth jobs fell 1.479 million. The youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015 while the number of youth jobs fell 1.581 million. The youth civilian noninstitutional population increased 1.548 million from 37.008 million in Aug 2006 to 38.556 million in Aug 2015 while the number of youth jobs fell 1.590 million. The youth civilian noninstitutional population increased 1,498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015 while the number of youth jobs fell 1.249 million. The youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015 while the number of youth jobs fell 1.199 million. The youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015 while the number of youth jobs fell 1.418 million. The youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015 while the level of youth jobs 1.409 million. The youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016 while the level of youth jobs fell 0.844 million. The youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016 while the number of youth jobs fell 0.726 million. The youth civilian noninstitutional population increased 1,662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016 while the number of youth jobs fell 0.711 million. The youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016 while the number of youth jobs fell 0.895 million. The youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016 while the number of youth jobs fell 0.894 million. The youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016 while the number of youth jobs fell 1.301 million. The youth civilian noninstitutional population increased 1.461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016 while the number of youth jobs fell 1.458 million. The youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016 while the number of youth jobs fell 1.291 million. The youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016 while the number of youth jobs fell 0.911 million. The hardship does not originate in low growth of population but in underperformance of the economy in the expansion from the business cycle. There are two hardships behind these data. First, young people cannot find employment after finishing high school and college, reducing prospects for achievement in older age. Second, students with more modest means cannot find employment to keep them in college.

Chart I-21A, US, Civilian Noninstitutional Population Ages 16 to 24 Years, Thousands NSA, 2001-2016

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

Chart I-21B provides the civilian labor force of the US ages 16 to 24 years NSA from 2001 to 2015. The US civilian labor force ages 16 to 24 years fell from 24.339 million in Jul 2007 to 23.506 million in Jul 2013, by 0.833 million or decline of 3.4 percent, while the civilian noninstitutional population NSA increased from 37.443 million in Jul 2007 to 38.861 million in Jul 2013, by 1.418 million or 3.8 percent. The US civilian labor force ages 16 to 24 fell from 22.801 million in Aug 2007 to 22.089 million in Aug 2013, by 0.712 million or 3.1 percent, while the noninstitutional population for ages 16 to 24 years increased from 37.455 million in Aug 2007 to 38.841 million in Aug 2013, by 1.386 million or 3.7 percent. The US civilian labor force ages 16 to 24 years fell from 21.917 million in Sep 2007 to 21.183 million in Sep 2013, by 0.734 million or 3.3 percent while the civilian noninstitutional youth population increased from 37.467 million in Sep 2007 to 38.822 million in Sep 2013 by 1.355 million or 3.6 percent. The US civilian labor force fell from 21.821 million in Oct 2007 to 21.003 million in Oct 2013, by 0.818 million or 3.7 percent while the noninstitutional youth population increased from 37.480 million in Oct 2007 to 38.804 million in Oct 2013, by 1.324 million or 3.5 percent. The US youth civilian labor force fell from 21.909 million in Nov 2007 to 20.825 million in Nov 2013, by 1.084 million or 4.9 percent while the civilian noninstitutional youth population increased from 37.076 million in Nov 2006 to 38.798 million in Nov 2013 or by 1.722 million. The US youth civilian labor force fell from 21.684 million in Dec 2007 to 20.642 million in Dec 2013, by 1.042 million or 4.8 percent, while the civilian noninstitutional population increased from 37.518 million in Dec 2007 to 38.790 million in Dec 2013, by 1.272 million or 3.4 percent. The youth civilian labor force of the US fell from 21.770 million in Jan 2007 to 20.423 million in Jan 2014, by 1.347 million or 6.2 percent while the youth civilian noninstitutional population increased 37.282 million in Jan 2007 to 38.770 million in Jan 2014, by 1.488 million or 4.0 percent. The youth civilian labor force of the US fell 1.255 million from 21.645 million in Feb 2007 to 20.390 million in Feb 2014 while the youth civilian noninstitutional population increased 1.464 million from 37.302 million in Feb 2007 to 38.766 million in Feb 2014. The youth civilian labor force of the US fell 0.693 million from 21.634 million in Mar 2007 to 20.941 million in Mar 2014 or 3.2 person while the youth noninstitutional civilian population 1.437 million from 37.324 million in Mar 2007 to 38.761 million in Mar 2014 or 3.9 percent. The US youth civilian labor force fell 981 thousand from 21.442 million in Apr 2007 to 20.461 million in Apr 2014 while the youth civilian noninstitutional population increased from 37.349 million in Apr 2007 to 38.759 million in Apr 2014 by 1.410 thousand or 3.8 percent. The youth civilian labor force decreased from 21.659 million in May 2007 to 21.160 million in May 2014 by 499 thousand or 2.3 percent while the youth civilian noninstitutional population increased 1.370 million from 37.739 million in May 2007 to 38.749 million in May 2007 or by 2.7 percent. The youth civilian labor force decreased from 24.128 million in Jun 2006 to 22.851 million in Jun 2014 by 1.277 million or 5.3 percent while the civilian noninstitutional population increased from 36.943 million in Jun 2006 to 38.740 million in Jun 2014 by 1.797 million or 4.9 percent. The youth civilian labor force fell from 24.664 million in Jul 2006 to 23.437 million in Jul 2014 while the civilian noninstitutional population increased from 36.989 million in Jul 2006 to 38.735 million in Jul 2014. The youth civilian labor force fell 1.818 million from 23.634 million in Aug 2006 to 21.816 million in Aug 2014 while the civilian noninstitutional population increased from 37.008 million in Aug 2006 to 38.706 million in Aug 2914 or 1.698 million. The youth civilian labor force fell 0.942 million from 21.901 million in Sep 2006 to 20.959 million in Sep 2014 while the noninstitutional population increased 1.652 million from 37.027 million in Sep 2006 to 38.679 million in Sep 2014. The youth civilian labor force decreased 0.702 million from 22.105 million in Oct 2006 to 21.403 million in Oct 2014 while the youth civilian noninstitutional population increased from 37.047 million in Oct 2006 to 38.650 million in Oct 2014 or 1.603 million. The youth civilian labor force decreased 1.111 million from 22.145 million in Nov 2006 to 21.034 million in Nov 2014 while the youth civilian noninstitutional population increased from 37.076 million in Nov 2006 to 38.628 million in Nov 2014 or 1.552 million. The youth civilian labor force decreased 1.472 million from 22.136 million in Dec 2006 to 20.664 million in Dec 2014 while the youth civilian noninstitutional population increased from 37.100 million in Dec 2006 to 38.606 million in Dec 2014 or 1.506 million. The youth civilian labor force decreased 0.831 million from 21.368 million in Jan 2006 to 20.555 million in Jan 2015 while the youth noninstitutional population increased from 36.761 million in Jan 2006 to 38.732 million in Jan 2015 or 1.971 million. The youth civilian labor force decreased 0.864 million from 21.615 million in Feb 2006 to 20.751 million in Feb 2015 while the youth noninstitutional population increased 1.914 million from 36.791 million in Feb 2006 to 38.705 million in Feb 2015. The youth civilian labor force decreased 0.907 million from 21.507 million in Mar 2006 to 20.600 million in Mar 2015 while the civilian noninstitutional population increased 1.858 million from 36.821 million in Mar 2006 to 38.679 million in Mar 2015. The youth civilian labor force decreased 1.082 million from 21.498 million in Apr 2006 to 20.416 million in Apr 2015 while the youth civilian noninstitutional population increased 1.800 million from 36.854 million in Apr 2006 to 38.654 million in Apr 2015. The youth civilian labor force decreased 0.681 million from 22.023 million in May 2006 to 21.342 million in May 2015 while the youth civilian noninstitutional population increased 1,733 million from 36.897 million in May 2006 to 38.630 million in May 2015. The youth civilian labor force decreased 1.202 million from 24.128 million in Jun 2006 to 22.926 million in Jun 2015 while the youth civilian noninstitutional population increased 1.666 million from 36.943 million in Jun 2006 to 38.609 million in Jun 2015. The youth civilian labor force decreased 1.502 million from 24.664 million in Jul 2007 to 23.162 million in Jul 2015 while the youth civilian noninstitutional population increased 1.600 million from 36.989 million in Jul 2006 to 38.589 million in Jul 2015. The youth civilian labor force decreased 1.667 million from 23.634 million in Aug 2006 to 21.967 million in Aug 2015 while the youth civilian noninstitutional population increased 1.548 million from 37.008 in Aug 2006 to 38.556 million in Aug 2015. The youth civilian labor force decreased 1.290 million from 21.901 million in Sep 2006 to 20.611 in Sep 2015 while the youth civilian noninstitutional population increased 1.498 million from 37.027 million in Sep 2006 to 38.525 million in Sep 2015. The youth civilian labor force decreased 1.228 million from 22.105 million in Oct 2006 to 20.877 million in Oct 2015 while the youth civilian noninstitutional population increased 1.444 million from 37.047 million in Oct 2006 to 38.491 million in Oct 2015. The youth civilian labor force decreased 1.513 million from 22.145 million in Nov 2006 to 20.632 million in Nov 2015 while the youth civilian noninstitutional population increased 1.392 million from 37.076 million in Nov 2006 to 38.468 million in Nov 2015. The youth civilian labor force decreased 1.301 million from 22.136 million in Dec 2006 to 20.835 million in Dec 2015 while the youth civilian noninstitutional population increased 1.341 million from 37.100 million in Dec 2006 to 38.441 million in Dec 2015. The youth civilian labor force decreased 1.004 million from 21.368 million in Jan 2006 to 20.364 million in Jan 2016 while the youth civilian noninstitutional population increased 1.734 million from 36.761 million in Jan 2006 to 38.495 million in Jan 2016. The youth civilian labor force decreased 0.930 million from 21.615 million in Feb 2006 to 20.685 million in Feb 2016 while the youth civilian noninstitutional population increased 1.698 million from 36.791 million in Feb 2006 to 38.489 million in Feb 2016. The youth civilian labor force decreased 0.767 million from 21.507 million in Mar 2006 to 20.740 million in Mar 2016 while the youth civilian noninstitutional population increased 1.662 million from 36.821 million in Mar 2006 to 38.483 million in Mar 2016. The youth civilian labor force decreased 0.950 million from 21.498 million in Apr 2006 to 20.548 million in Apr 2016 while the youth civilian noninstitutional population increased 1.626 million from 36.854 million in Apr 2006 to 38.480 million in Apr 2016. The youth civilian labor force decreased 0.921 million from 22.023 million in May 2006 to 21.102 million in May 2016 while the youth civilian noninstitutional population increased 1.571 million from 36.897 million in May 2006 to 38.468 million in May 2016. The youth civilian labor force decreased 1.373 million from 24.128 million in Jun 2006 to 22.755 million in Jun 2016 while the youth civilian noninstitutional population increased 1.516 million from 36.943 million in Jun 2006 to 38.459 million in Jun 2016. The youth civilian labor force decreased 1.560 million from 24.664 million in Jul 2006 to 23.104 million in Jul 2016 while the youth civilian noninstitutional population increased 1,461 million from 36.989 million in Jul 2006 to 38.450 million in Jul 2016. The youth civilian labor force decreased 1.536 million from 23.634 million in Aug 2006 to 22.098 million in Aug 2016 while the youth civilian noninstitutional population increased 1.414 million from 37.008 million in Aug 2006 to 38.422 million in Aug 2016. The youth civilian labor force decreased 1.082 million from 21.901 million in Sep 2006 to 20.891 million in Sep 2016 while the youth civilian noninstitutional population increased 1.368 million from 37.027 million in Sep 2006 to 38.395 million in Sep 2016. Youth in the US abandoned their participation in the labor force because of the frustration that there are no jobs available for them.

Chart I-21B, US, Civilian Labor Force Ages 16 to 24 Years, Thousands NSA, 2001-2016

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

Chart I-21C provides the ratio of labor force to noninstitutional population or labor force participation of ages 16 to 24 years not seasonally adjusted. The US labor force participation rates for ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2013 because of the frustration of young people who believe there may not be jobs available for them. The US labor force participation rate of young people fell from 63.9 in Aug 2006 to 56.9 in Aug 2013. The US labor force participation rate of young people fell from 59.1 percent in Sep 2006 to 54.6 percent in Sep 2013. The US labor force participation rate of young people fell from 59.7 percent in Oct 2006 to 54.1 in Oct 2013. The US labor force participation rate of young people fell from 59.7 percent in Nov 2006 to 53.7 percent in Nov 2013. The US labor force participation rate fell from 57.8 in Dec 2007 to 53.2 in Dec 2013. The youth labor force participation rate fell from 58.4 in Jan 2007 to 52.7 in Jan 2014. The US youth labor force participation rate fell from 58.0 percent in Feb 2007 to 52.6 percent in Feb 2013. The labor force participation rate of ages 16 to 24 years fell from 58.0 in Mar 2007 to 54.0 in Mar 2014. The labor force participation rate of ages 16 to 24 years fell from 57.4 in Apr 2007 to 52.8 in Apr 2014. The labor force participation rate of ages 16 to 24 years fell from 57.9 in May 2007 to 54.6 in May 2014. The labor force participation rate of ages 16 to 24 years fell from 65.3 in Jun 2006 to 59.0 in Jun 2014. The labor force participation rate ages 16 to 24 years fell from 66.7 in Jul 2006 to 60.5 in Jul 2014. The labor force participation rate ages 16 to 24 years fell from 63.9 in Aug 2006 to 56.4 in Aug 2014. The labor force participation rate ages 16 to 24 years fell from 59.1 in Sep 2006 to 54.2 in Sep 2014. The labor force participation rate ages 16 to 24 years fell from 59.7 in Oct 2006 to 55.4 in Oct 2014. The labor force participation rate ages 16 to 24 years fell from 59.7 in Nov 2006 to 54.5 in Nov 2014. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 53.5 in Dec 2014. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 53.1 in Jan 2015. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 53.6 in Feb 2015. The labor force participation rate ages 16 to 64 fell from 58.4 in Mar 2006 to 53.3 in Mar 2015. The labor force participation rate ages 16 to 64 fell from 58.7 in Apr 2005 to 52.8 in Apr 2006. The labor force participation rate ages 16 to 64 fell from 59.7 in May 2006 to 55.2 in May 2015. The labor force participation rate ages 16 to 64 fell from 65.3 in Jun 2006 to 59.4 in Jun 2015. The labor force participation rate ages 16 to 24 fell from 66.7 in Jul 2006 to 60.0 in Jul 2014. The labor force participation rate ages 16 to 24 fell from 63.9 in Aug 2006 to 57.0 in Aug 2015. The labor force participation rate ages 16 to 24 fell from 59.1 in Sep 2006 to 53.5 in Sep 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Oct 2006 to 54.2 in Oct 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Nov 2006 to 53.6 in Nov 2015. The labor force participation rate ages 16 to 24 fell from 59.7 in Dec 2006 to 54.2 in Dec 2015. The labor force participation rate ages 16 to 24 fell from 58.1 in Jan 2006 to 52.9 in Jan 2016. The labor force participation rate ages 16 to 24 fell from 58.8 in Feb 2006 to 53.7 in Feb 2016. The labor force participation rate ages 16 to 24 fell from 58.4 in Mar 2006 to 53.9 in Mar 2016. The labor force participation rate ages 16 to 24 fell from 58.3 in Apr 2006 to 53.4 in Apr 2016. The labor force participation rate ages 16 to 24 fell from 59.7 in May 2006 to 54.9 in May 2016. The labor force participation rate ages 16 to 24 fell from 65.3 in Jun 2006 to 59.2 in Jun 2016. The labor force participation rate ages 16 to 24 fell from 66.7 in Jul 2006 to 60.1 in Jul 2016. The labor force participation rate ages 16 to 24 fell from 63.9 in Aug 2006 to 57.5 in Aug 2016. The labor force participation rate ages 16 to 24 fell from 59.1 in Sep 2006 to 54.2 in Sep 2016. Many young people abandoned searches for employment, dropping from the labor force.

Chart I-21C, US, Labor Force Participation Rate Ages 16 to 24 Years, NSA, 2001-2016

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

An important measure of the job market is the number of people with jobs relative to population available for work (civilian noninstitutional population) or employment/population ratio. Chart I-21D provides the employment population ratio for ages 16 to 24 years. The US employment/population ratio NSA for ages 16 to 24 years collapsed from 59.2 in Jul 2006 to 50.7 in Jul 2013. The employment population ratio for ages 16 to 24 years dropped from 57.2 in Aug 2006 to 48.0 in Aug 2013. The employment population ratio for ages to 16 to 24 years declined from 52.9 in Sep 2006 to 46.5 in Sep 2013. The employment population ratio for ages 16 to 24 years fell from 53.6 in Oct 2006 to 46.3 in Oct 2013. The employment population ratio for ages 16 to 24 years fell from 53.7 in Nov 2007 to 46.7 in Nov 2013. The US employment population ratio for ages 16 to 24 years fell from 51.6 in Dec 2007 to 46.7 in Dec 2013. The US employment population ratio fell from 52.1 in Jan 2007 to 44.8 in Jan 2014. The US employment population ratio for ages 16 to 24 fell from 52.0 in Feb 2007 to 44.8 in Feb 2014. The US employment population ratio for ages 16 to 24 years fell from 52.3 in Mar 2007 to 46.3 in Mar 2014. The US employment population ratio for ages 16 to 24 years fell from 51.9 in Apr 2007 to 46.5 in Apr 2014. The US employment population ratio for ages 16 to 24 years fell from 52.1 in May 2007 to 47.3 in May 2014. The US employment population ratio for ages 16 to 24 years fell from 57.6 in Jun 2006 to 50.1 in Jun 2014. The US employment population ratio for ages 16 to 24 years fell from 59.2 in Jul 2006 to 50.1 in Jul 2014. The employment population ratio for ages 16 to 24 years fell from 57.2 in Aug 2006 to 49.0 in Aug 2014. The employment population ratio for ages 16 to 24 fell from 52.9 in Sep 2006 to 46.8 in Sep 2014. The employment population ratio for ages 16 to 24 fell from 53.6 in Oct 2006 to 48.6 in Oct 2014. The employment population ratio for ages 16 to 24 fell from 53.7 in Nov 2006 to 48.1 in Nov 2014. The employment population ration for ages 16 to 24 fell from 54.3 in Dec 2006 to 47.5 in Dec 2014. The employment population ration for ages 16 to 24 years fell from 51.7 in Jan 2006 to 46.2 in Jan 2015. The employment population ratio for ages 16 to 24 fell from 52.1 in Feb 2006 to 47.1 in Feb 2015. The employment population ratio for ages 16 to 24 years fell from 52.4 in Mar 2006 to 46.7 in Mar 2015. The employment population ratio for ages 16 to 24 years fell from 52.7 in Apr 2006 to 47.2 in Apr 2015. The employment population ratio for ages 16 to 24 fell from 53.6 in May 206 to 48.4 in May 2015. The employment population ratio for ages 16 to 24 fell from 57.6 in Jun 2006 to 51.3 in Jun 2015. The employment population ratio for ages 16 to 24 fell from 59.2 in Jul 2006 to 52.7 in Jul 2015. The employment population ratio for ages 16 to 24 fell from 57.2 in Aug 2006 to 50.8 in Aug 2015. The employment population ratio for ages 16 to 24 years fell from 52.9 in Sep 2006 to 47.6 in Sep 2015. The employment population ratio for ages 16 to 24 years fell from 53.6 in Oct 2006 to 48.5 in Oct 2015. The employment population ratio for ages 16 to 24 years fell from 53.7 in Nov 2006 to 48.1 in Nov 2015. The employment population ratio for ages 16 to 24 years fell from 54.3 in Dec 2006 to 48.7 in Dec 2015. The employment population ratio for ages 16 to 24 years fell from 51.7 in Jan 2006 to 47.2 in Jan 2016. The employment population ration for ages 16 to 24 years fell from 52.1 in Feb 2006 to 48.0 in Feb 2016. The employment population ratio for ages 16 to 24 fell from 52.4 in Mar 2006 to 48.3 in Mar 2016. The employment population ratio for ages 16 to 24 fell from 52.7 in Apr 2006 to 48.1 in Apr 2016. The employment population ratio for ages 16 to 24 fell from 53.6 in May 2006 to 49.1 in May 2016. The employment population ratio for ages 16 to 24 fell from 57.6 in Jun 2006 to 51.9 in Jun 2016. The employment population ratio for ages 16 to 24 fell from 59.2 in Jul 2006 to 53.2 in Jul 2016. The employment population ratio for ages 16 to 24 fell from 57.2 in Aug 2006 to 51.7 in Aug 2016. The employment population ratio for ages 16 to 24 fell from 52.9 in Sep 2006 to 48.7 in Sep 2016. Chart I-21D shows vertical drop during the global recession without recovery.

Chart I-21D, US, Employment Population Ratio Ages 16 to 24 Years, Thousands NSA, 2001-2016

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

Table I-11 provides US unemployment level ages 16 to 24 years. The number unemployed ages 16 to 24 years increased from 2342 thousand in 2007 to 3634 thousand in 2011 or by 1.292 million and 3451 thousand in 2012 or by 1.109 million. The unemployment level ages 16 to 24 years increased from 2342 in 2007 to 3324 thousand in 2013 or by 0.982 million. The unemployment level ages 16 to 24 years increased from 2342 thousand in 2007 to 2853 thousand in 2014 or by 0.511 million. The unemployment level for ages 16 to 24 increased from 2342 thousand in 2007 to 2467 thousand in 2015. The unemployment level ages 16 to 24 years decreased from 2.297 million in Sep 2006 to 2.126 million in Sep 2016 or decrease by 0.171 million. This situation may persist for many years.

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

Year	Mar	Apr	May	Jun	Jul	Aug	Sep	Dec	Annual
2001	2253	2095	2171	2775	2585	2461	2301	2412	2371
2002	2822	2515	2568	3167	3034	2688	2506	2374	2683
2003	2601	2572	2838	3542	3200	2724	2698	2248	2746
2004	2588	2387	2684	3191	3018	2585	2493	2294	2638
2005	2520	2398	2619	3010	2688	2519	2339	2055	2521
2006	2216	2092	2254	2860	2750	2467	2297	2007	2353
2007	2096	2074	2203	2883	2622	2388	2419	2323	2342
2008	2347	2196	2952	3450	3408	2990	2904	2928	2830
2009	3371	3321	3851	4653	4387	4004	3774	3532	3760
2010	3748	3803	3854	4481	4374	3903	3604	3352	3857
2011	3520	3365	3628	4248	4110	3820	3541	3161	3634
2012	3294	3175	3438	4180	4011	3672	3174	3153	3451
2013	3261	3129	3478	4198	3821	3453	3139	2536	3324
2014	3002	2440	2831	3429	3353	2844	2854	2317	2853
2015	2524	2175	2633	3138	2829	2390	2256	2114	2467
2016	2160	2037	2227	2789	2648	2221	2126

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

Chart I-22 provides the unemployment level for ages 16 to 24 from 2001 to 2016. The level rose sharply from 2007 to 2010 with tepid improvement into 2012 and deterioration into 2013-2014 with recent marginal improvement in 2015-16 alternating with deterioration.

Chart I-22, US, Unemployment Level 16-24 Years, Thousands SA, 2001-2016

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

Table I-12 provides the rate of unemployment of young peoples in ages 16 to 24 years. The annual rate jumped from 10.5 percent in 2007 to 18.4 percent in 2010, 17.3 percent in 2011 and 16.2 percent in 2012. The rate of youth unemployment fell marginally to 15.5 percent in 2013, declining to 13.4 percent in Dec 2014. During the seasonal peak in Jul, the rate of youth unemployed was 18.1 percent in Jul 2011, 17.1 percent in Jul 2012 and 16.3 percent in Jul 2013 compared with 10.8 percent in Jul 2007. The rate of youth unemployment rose from 11.2 percent in Jul 2006 to 16.3 percent in Jul 2013 and likely higher if adding those who ceased searching for a job in frustration none may be available. The rate of youth unemployment rose from 10.8 in Jul 2007 to 14.3 in Jul 2014. The rate of youth unemployment increased from 9.1 percent in Dec 2006 to 12.3 percent in Dec 2013. The rate of youth unemployment increased from 10.9 percent in Jan 2007 to 14.9 percent in Jan and Feb 2014. The rate of youth unemployment increased from 9.7 percent in Mar 2007 to 14.3 percent in Mar 2014. The rate of youth unemployment increased from 9.7 percent in Apr 2007 to 11.9 percent in Apr 2014. The rate of youth unemployment increased from 10.2 percent in May 2007 to 13.4 percent in May 2014. The rate of youth unemployment increased from 12.0 percent in Jun 2007 to 15.0 percent in Jun 2014. The rate of youth unemployment increased from 10.8 in Jul 2007 to 14.3 in Jul 2014. The rate of youth unemployment increased from 10.5 in Aug 2007 to 13.0 in Aug 2014. The rate of youth unemployment increased from 11.0 in Sep 2007 to 13.6 in Sep 2014. The rate of youth unemployment increased from 10.3 in Oct 2007 to 12.2 in Oct 2014. The rate of youth unemployment increased from 10.3 in Nov 2007 to 11.7 in Nov 2014. The rate of youth unemployment increased from 10.7 in Dec 2007 to 11.2 in Dec 2014. The rate of youth unemployment increased from 10.9 in Jan 2007 to 12.9 in Jan 2015. The rate of youth unemployment increased from 10.3 percent in Feb 2007 to 12.2 percent in Feb 2015. The rate of youth unemployment increased from 9.7 in Mar 2007 to 12.3 in Mar 2015. The rate of youth unemployment increased from 9.7 in Apr 2007 to 10.7 in Apr 2015. The rate of youth unemployment increased from 10.2 in May 2007 to 12.3 in May 2015. The rate of youth unemployment increased from 11.9 in Jun 2006 to 13.7 in Jun 2015. The rate of youth unemployment increased from 10.8 in Jul 2007 to 12.2 in Jul 2015. The rate of youth unemployment increased from 10.5 in Aug 2007 to 10.9 in Aug 2015. The rate of youth unemployment decreased from 11.0 in Sep 2007 to 10.9 in Sep 2015. The rate of youth unemployment increased from 10.3 in Oct 2007 to 10.6 in Oct 2015. The rate of youth unemployment increased from 10.3 in Nov 2007 to 10.4 in Nov 2015. The rate of youth unemployment decreased from 10.7 in Dec 2007 to 10.1 in Dec 2015. The rate of youth unemployment decreased from 10.9 in Jan 2007 to 10.8 in Jan 2016. The rate of youth unemployment increased from 10.3 in Feb 2007 to 10.8 in Feb 2016. The rate of youth unemployment increased from 9.7 in Mar 2007 to 10.4 in Mar 2016. The rate of youth unemployment increased from 9.7 in Apr 2007 to 9.9 in Apr 2016. The rate of youth unemployment increased from 10.2 in May 2007 to 10.6 in May 2016. The rate of youth unemployment increased from 12.0 in Jun 2007 to 12.3 in Jun 2016. The rate of youth unemployment increased from 10.8 in Jul 2007 to 11.5 in Jul 2016. The rate of youth unemplopyment fell from 10.5 in Aug 2007 to 10.1 in Aug 2016. The rate of youth unemployment fell from 11.0 in Sep 2007 to 10.2 in Sep 2016. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them.

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

Year	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Annual
2001	10.3	10.3	10.2	9.6	10.0	11.6	10.5	10.7	10.5	11.0	11.2	11.0	10.6
2002	12.9	12.5	12.9	11.6	11.6	13.2	12.4	11.5	11.4	11.2	11.7	10.9	12.0
2003	12.7	12.7	12.2	12.0	13.0	14.8	13.3	11.9	12.5	11.6	11.6	10.5	12.4
2004	12.8	12.3	12.1	11.1	12.2	13.4	12.3	11.1	11.5	11.6	11.1	10.5	11.8
2005	12.4	13.0	11.7	11.2	11.9	12.6	11.0	10.8	10.7	10.3	10.7	9.4	11.3
2006	11.1	11.3	10.3	9.7	10.2	11.9	11.2	10.4	10.5	10.2	10.1	9.1	10.5
2007	10.9	10.3	9.7	9.7	10.2	12.0	10.8	10.5	11.0	10.3	10.3	10.7	10.5
2008	12.3	11.8	11.1	10.3	13.3	14.4	14.0	13.0	13.4	13.2	13.3	13.7	12.8
2009	15.8	16.4	16.1	15.8	18.0	19.9	18.5	18.0	18.2	18.5	18.1	17.5	17.6
2010	19.8	19.2	18.4	18.5	18.4	20.0	19.1	17.8	17.6	18.1	17.4	16.7	18.4
2011	18.9	18.2	17.2	16.5	17.5	18.9	18.1	17.5	17.0	16.2	15.9	15.5	17.3
2012	16.8	17.0	16.0	15.4	16.3	18.1	17.1	16.8	15.2	15.5	14.8	15.2	16.2
2013	17.6	16.7	15.9	15.1	16.4	18.0	16.3	15.6	14.8	14.4	13.1	12.3	15.5
2014	14.9	14.9	14.3	11.9	13.4	15.0	14.3	13.0	13.6	12.2	11.7	11.2	13.4
2015	12.9	12.2	12.3	10.7	12.3	13.7	12.2	10.9	10.9	10.6	10.4	10.1	11.6
2016	10.8	10.8	10.4	9.9	10.6	12.3	11.5	10.1	10.2

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

Chart I-23 provides the BLS estimate of the not-seasonally-adjusted rate of youth unemployment for ages 16 to 24 years from 2001 to 2016. The rate of youth unemployment increased sharply during the global recession of 2008 and 2009 but has failed to drop to earlier lower levels because of low growth of GDP. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E. Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent.

Chart I-23, US, Unemployment Rate 16-24 Years, Percent, NSA, 2001-2016

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

Chart I-24 provides longer perspective with the rate of youth unemployment in ages 16 to 24 years from 1948 to 2016. The rate of youth unemployment rose to 20 percent during the contractions of the early 1980s and also during the contraction of the global recession in 2008 and 2009. The data illustrate again the argument in this blog that the contractions of the early 1980s are the valid framework for comparison with the global recession of 2008 and 2009 instead of misleading comparisons with the 1930s. During the initial phase of recovery, the rate of youth unemployment 16 to 24 years NSA fell from 18.9 percent in Jun 1983 to 14.5 percent in Jun 1984. In contrast, the rate of youth unemployment 16 to 24 years was nearly the same during the expansion after IIIQ2009: 17.5 percent in Dec 2009, 16.7 percent in Dec 2010, 15.5 percent in Dec 2011, 15.2 percent in Dec 2012, 17.6 percent in Jan 2013, 16.7 percent in Feb 2013, 15.9 percent in Mar 2013, 15.1 percent in Apr 2013. The rate of youth unemployment was 16.4 percent in May 2013, 18.0 percent in Jun 2013, 16.3 percent in Jul 2013 and 15.6 percent in Aug 2013. In Sep 2006, the rate of youth unemployment was 10.5 percent, increasing to 14.8 percent in Sep 2013. The rate of youth unemployment was 10.3 in Oct 2007, increasing to 14.4 percent in Oct 2013. The rate of youth unemployment was 10.3 percent in Nov 2007, increasing to 13.1 percent in Nov 2013. The rate of youth unemployment was 10.7 percent in Dec 2013, increasing to 12.3 percent in Dec 2013. The rate of youth unemployment was 10.9 percent in Jan 2007, increasing to 14.9 percent in Jan 2014. The rate of youth unemployment was 10.3 percent in Feb 2007, increasing to 14.9 percent in Feb 2014. The rate of youth unemployment was 9.7 percent in Mar 2007, increasing to 14.3 percent in Mar 2014. The rate of youth unemployment was 9.7 percent in Apr 2007, increasing to 11.9 percent in Apr 2014. The rate of youth unemployment was 10.2 percent in May 2007, increasing to 13.4 percent in May 2014. The rate of youth unemployment was 12.0 percent in Jun 2007, increasing to 15.0 percent in Jun 2014. The rate of youth unemployment was 10.8 percent in Jul 2007, increasing to 14.3 percent in Jul 2014. The rate of youth unemployment was 10.5 percent in Aug 2007, increasing to 13.0 percent in Aug 2014. The rate of youth unemployment was 11.0 percent in Sep 2007, increasing to 13.6 percent in Sep 2014. The rate of youth unemployment increased from 10.3 in Oct 2007 to 12.2 in Oct 2014. The rate of youth unemployment increased from 10.3 percent in Nov 2007 to 11.7 percent in Nov 2014. The rate of youth unemployment increased from 10.7 in Dec 2007 to 11.2 in Dec 2014. The rate of youth unemployment increased from 9.7 in Mar 2007 to 12.3 in Mar 2015. The rate of youth unemployment increased from 9.7 in Apr 2007 to 10.7 in Apr 2015. The rate of youth unemployment increased from 10.2 in May 2007 to 12.3 in May 2015. The rate of youth unemployment increased from 12.0 in Jun 2007 to 13.7 in Jun 2015. The rate of youth unemployment increased from 10.8 in Jul 2007 to 12.2 in Jul 2015. The rate of youth unemployment increased from 10.5 in Aug 2007 to 10.9 in Aug 2015. The rate of youth unemployment decreased from 11.0 in Sep 2007 to 10.9 in Sep 2015. The rate of youth unemployment increased from 10.3 in Oct 2007 to 10.6 in Oct 2015, decreasing to 10.4 in Nov 2015. The rate of youth unemployment decreased to 10.1 in Dec 2015. The rate of youth unemployment stood at 10.8 in Jan 2016, 10.8 in Feb 2016, 10.4 in Mar 2016 and 9.9 in Apr 2016. The rate of youth unemployment increased to 10.6 in May 2016 and 12.3 in Jun 2016. The rate of youth unemployment fell to 11.5 in Jul 2016, decreasing to 10.1 in Aug 2016. The rate of youth unemployment increased to 10.2 in Sep 2016. The actual rate is higher because of the difficulty in counting those dropping from the labor force because they believe there are no jobs available for them. The difference originates in the vigorous seasonally adjusted annual equivalent average rate of GDP growth of 5.9 percent during the recovery from IQ1983 to IVQ1985 and 4.5 percent from IQ1983 to IVQ1989 compared with 2.1 percent on average during the first 28 quarters of expansion from IIIQ2009 to IIQ2016. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 28 quarters from IIIQ2009 to IIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp2q16_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2696.4 billion than actual $16,583.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html). US GDP in IIQ2016 is 14.0 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,583.1 billion in IIQ2016 or 10.6 percent at the average annual equivalent rate of 1.2 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Aug 1919 to Aug 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0258 in Aug 2016. The actual index NSA in Aug 2016 is 104.6251, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.5532 in Aug 2016. The output of manufacturing at 104.6251 in Aug 2016 is 19.2 percent below trend under this alternative calculation.

Chart I-24, US, Unemployment Rate 16-24 Years, Percent NSA, 1948-2016

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

It is more difficult to move to other jobs after a certain age because of fewer available opportunities for mature individuals than for new entrants into the labor force. Middle-aged unemployed are less likely to find another job. Table I-13 provides the unemployment level ages 45 years and over. The number unemployed ages 45 years and over rose from 1.607 million in Oct 2006 to 4.576 million in Oct 2010 or by 184.8 percent. The number of unemployed ages 45 years and over declined to 3.800 million in Oct 2012 that is still higher by 136.5 percent than in Oct 2006. The number unemployed age 45 and over increased from 1.704 million in Nov 2006 to 3.861 million in Nov 2012, or 126.6 percent. The number unemployed age 45 and over is still higher by 98.5 percent at 3.383 million in Nov 2013 than 1.704 million in Nov 2006. The number unemployed age 45 and over jumped from 1.794 million in Dec 2006 to 4.762 million in Dec 2010 or 165.4 percent. At 3.927 million in Dec 2012, mature unemployment is higher by 2.133 million or 118.9 percent higher than 1.794 million in Dec 2006. The level of unemployment of those aged 45 year or more of 3.632 million in Oct 2013 is higher by 2.025 million than 1.607 million in Oct 2006 or higher by 126.0 percent. The number of unemployed 45 years and over increased from 1.794 million in Dec 2006 to 3.378 million in Nov 2013 or 88.3 percent. The annual number of unemployed 45 years and over increased from 1.848 million in 2006 to 3.719 million in 2013 or 101.2 percent. The number of unemployed 45 years and over increased from 2.126 million in Jan 2006 to 4.394 million in Jan 2013, by 2.618 million or 106.7 percent. The number of unemployed 45 years and over rose from 2.126 million in Jan 2006 to 3.508 million in Jan 2014, by 1.382 million or 65.0 percent. The level of unemployed 45 years or older increased 2.051 million or 99.8 percent from 2.056 million in Feb 2006 to 4.107 million in Feb 2013 and at 3.490 million in Feb 2014 is higher by 69.7 percent than in Feb 2006. The number of unemployed 45 years and over increased 2.048 million or 108.9 percent from 1.881 million in Mar 2006 to 3.929 million in Mar 2013 and at 3.394 million in Mar 2014 is higher by 80.4 percent than in Mar 2006. The number of unemployed 45 years and over increased 1.846 million or 100.2 percent from 1.843 million in Apr 2006 to 3.689 million in Apr 2013 and at 3.006 million in Apr 2014 is higher by 1.163 million or 63.1 percent. The number of unemployed ages 45 years and over increased 102.1 percent from 1.784 million in May 2006 to 3.605 million in May 2014 and at 2.913 million in May 2014 is higher by 63.3 percent than in May 2007.

The number of unemployed ages 45 years and over increased 102.1 percent from 1.805 million in Jun 2007 to 3.648 million in Jun 2013 and at 2.832 million in Jun 2014 is higher by 56.9 percent than in Jun 2007. The number of unemployed ages 45 years and over increased 81.5 percent from 2.053 million in Jul 2007 to 3.727 million in Jul 2013 and at 3.083 million in Jul 2014 is higher by 50.2 percent than in Jul 2007. The level unemployed ages 45 years and over increased 84.4 percent from 1.956 million in Aug 2007 to 3.607 million in Aug 2013 and at 3.037 million in Aug 2014 is 55.2 percent higher than in Aug 2007. The level unemployed ages 45 years and over increased 90.7 percent from 1.854 million in Sep 2007 to 3.535 million in Sep 2013 and at 2.640 million in Sep 2014 is 42.4 percent higher than in Sep 2007. The level unemployed ages 45 years and over increased 1.747 million from 1.885 million in Oct 2007 to 3.632 million in Oct 2013 and at 2.606 million in Oct 2014 is 38.2 percent higher than in Oct 2007. The level unemployed ages 45 years and over increased 1.458 million from 1.925 million in Nov 2007 to 3.383 million in Nov 2013 and at 2.829 million in Nov 2014 is 47.0 percent higher than in Nov 2007. The level of unemployed ages 45 years and over increased 1.258 million from Dec 2007 to Dec 2013 and at 2.667 million in Dec 2014 is 25.8 higher than in Dec 2007. The level unemployed ages 45 years and over increased 1.353 million from Jan 2007 to Jan 2015 and at 3.077 million in Jan 2015 is 42.8 percent higher than in Jan 2007. The level unemployed ages 45 years and over increased 1.352 million from 2.138 million in Feb 2007 to 3.490 million in Feb 2014 and at 2.991 million in Feb 2015 is 39.9 percent higher than in Feb 2007. The level of unemployed ages 45 years and over increased 1.363 million from 2.031 million in Mar 2007 to 3.394 million in Mar 2014 and at 2.724 million in Mar 2015 is 34.1 percent higher than in Mar 2007. The level of unemployed ages 45 years and over increased from 1.871 million in Apr 2007 to 3.006 million in Apr 2014 and at 2.579 million in Apr 2015 is 37.8 higher than in Apr 2007. The level of unemployed ages 45 years and over increased from 1.803 million in May 2007 to 2.913 million in Jun 2014 and at 2.457 million in May 2015 is 36.3 percent higher than in May 2007. The level of unemployed ages 45 years and over increased from 1.805 million in Jun 2007 to 2.832 million in Jun 2014 and at 2.359 million in Jun 2015 is 30.7 percent higher than in Jun 2007. The level of unemployed ages 45 years and over increased from 2.053 million in Jul 2007 to 3.083 million in Jul 2014 and at 2.666 million in Jul 2015 is 30.0 percent higher than in Jul 2007. The level of unemployed ages 45 years and over increased from 1.956 million in Aug 2007 to 3.037 million in Aug 2014 and at 2.693 million in Aug 2015 is 37.7 higher than in Aug 2007. The level of unemployed ages 45 years and over increased from 1.854 million in Sep 2007 to 2.640 million in Sep 2015 and at 2.388 million in Sep 2015 is 28.8 percent higher than in Sep 2007. The level of unemployment ages 45 years and over increased from 1.885 million in Oct 2007 to 2.606 million in Oct 2014 and at 2.290 million in Oct 2015 is 21.5 percent higher than in Oct 2007. The level of unemployment ages 45 years and over increased from 1.925 million in Nov 2007 to 2.829 million in Nov 2014 and at 2.349 million in Nov 2015 is 22.0 percent higher than in Nov 2007. The level of unemployment ages 45 years and over increased from 2.120 million in Dec 2007 to 2.667 million in Dec 2014 and at 2.317 million in Dec 2015 is 9.3 percent higher than in Dec 2007. The level of unemployment ages 45 and over increased from 2.155 million in Jan 2007 to 3.077 million in Jan 2015 and at 2.736 million in Jan 2016 is 27.0 percent higher than in Jan 2007. The level of unemployment ages 45 and over increased from 2.138 million in Feb 2007 to 2.991 million in Feb 2015 and at 2.744 million in Feb 2016 is 28.3 percent higher than in Feb 2007. The level of unemployment ages 45 and over increased from 2.031 million in Mar 2007 to 2.724 million in Mar 2015 and at 2.747 million in Mar 2016 is 35.3 percent higher than in Mar 2007. The level of unemployment ages 45 and over increased from 1.871 million in Apr 2007 to 2.579 million in Apr 2015 and at 2.410 million in Apr 2016 is 28.8 percent higher than in Apr 2007. The level of unemployment ages 45 and over increased from 1.803 million in May 2007 to 2.457 million in May 2015 and at 2.190 million in May 2016 is 21.5 percent higher than in May 2007. The level of unemployment ages 45 and over increased from 1.805 million in Jun 2007 to 2.359 million in Jun 2015 and at 2.345 million in Jun 2016 is 29.9 percent higher than in Jun 2007. The level of unemployment ages 45 and over increased from 2.053 million in Jul 2007 to 2.666 million in Jul 2015 and at 2.619 million in Jul 2016 is 27.6 percent higher than in Jul 2007. The level of unemployment ages 45 and over increased from 1.956 million in Aug 2007 to 2.693 million in Aug 2015 and at 2.565 million in Aug 2016 is 31.1 percent higher than in Aug 2007. The level of unemployment ages 45 and over increased from 1.854 million in Sep 2007 to 2.388 million in Sep 2015 and at 2.414 million in Sep 2016 is 30.2 percent higher than in Sep 2007. The actual number unemployed is likely much higher because many are not accounted who abandoned job searches in frustration there may not be a job for them. Recent improvements may be illusory. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 28 quarters from IIIQ2009 to IIQ2016. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIQ2016 (http://www.bea.gov/newsreleases/national/gdp/2016/pdf/gdp2q16_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by diving GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[$14,745.9/$14,355.6 -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989 and at 7.8 percent from IQ1983 to IVQ1983 (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIQ2016 would have accumulated to 28.6 percent. GDP in IIQ2016 would be $19,279.5 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2696.4 billion than actual $16,583.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 23.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 14.0 percent of the effective labor force (http://cmpassocregulationblog.blogspot.com/2016/10/twenty-four-million-unemployed-or.html and earlier http://cmpassocregulationblog.blogspot.com/2016/09/interest-rates-and-valuations-of-risk.html). US GDP in IIQ2016 is 14.0 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,583.1 billion in IIQ2016 or 10.6 percent at the average annual equivalent rate of 1.2 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.1 percent per year from Aug 1919 to Aug 2016. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2316 in Dec 2007 to 141.0258 in Aug 2016. The actual index NSA in Aug 2016 is 104.6251, which is 27.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Dec 2015. Using trend growth of 2.1 percent per year, the index would increase to 129.5532 in Aug 2016. The output of manufacturing at 104.6251 in Aug 2016 is 19.2 percent below trend under this alternative calculation.

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

Year	Mar	Apr	May	Jun	Jul	Aug	Sep	Dec	Annual
2000	1291	1062	1074	1163	1253	1339	1254	1217	1249
2001	1533	1421	1259	1371	1539	1640	1586	1901	1576
2002	2138	2101	1999	2190	2173	2114	1966	2210	2114
2003	2485	2287	2112	2212	2281	2301	2157	2130	2253
2004	2354	2160	2025	2182	2116	2082	1951	2086	2149
2005	2126	1939	1844	1868	2119	1895	1992	1963	2009
2006	1881	1843	1784	1813	1985	1869	1710	1794	1848
2007	2031	1871	1803	1805	2053	1956	1854	2120	1966
2008	2326	2104	2095	2211	2492	2695	2595	3485	2540
2009	4518	4172	4175	4505	4757	4683	4560	4960	4500
2010	5194	4770	4565	4564	4821	5128	4640	4762	4879
2011	4748	4373	4356	4559	4772	4592	4426	4182	4537
2012	4390	4037	4083	4084	4405	4179	3899	3927	4133
2013	3929	3689	3605	3648	3727	3607	3535	3378	3719
2014	3394	3006	2913	2832	3083	3037	2640	2667	3000
2015	2724	2579	2457	2359	2666	2693	2388	2317	2574
2016	2747	2410	2190	2345	2619	2565	2414

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

Chart I-25 provides the level unemployed ages 45 years and over. There was an increase in the recessions of the 1980s, 1991 and 2001 followed by declines to earlier levels. The current expansion of the economy after IIIQ2009 has not been sufficiently vigorous to reduce significantly middle-age unemployment. Recent improvements could be illusory because many abandoned job searches in frustration that there may not be jobs for them and are not counted as unemployed.

Chart I-25, US, Unemployment Level Ages 45 Years and Over, Thousands, NSA, 1976-2016

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

II United States Producer Price Index. Unconventional monetary policy of zero interest rates and large-scale purchases of long-term securities for the balance sheet of the central bank is proposed to prevent deflation. The data of CPI inflation of all goods and CPI inflation excluding food and energy for the past six decades does not show even one negative change, as shown in Table CPIEX.

Table CPIEX, Annual Percentage Changes of the CPI All Items Excluding Food and Energy

Year	Annual ∆%
1958	2.4
1959	2.0
1960	1.3
1961	1.3
1962	1.3
1963	1.3
1964	1.6
1965	1.2
1966	2.4
1967	3.6
1968	4.6
1969	5.8
1970	6.3
1971	4.7
1972	3.0
1973	3.6
1974	8.3
1975	9.1
1976	6.5
1977	6.3
1978	7.4
1979	9.8
1980	12.4
1981	10.4
1982	7.4
1983	4.0
1984	5.0
1985	4.3
1986	4.0
1987	4.1
1988	4.4
1989	4.5
1990	5.0
1991	4.9
1992	3.7
1993	3.3
1994	2.8
1995	3.0
1996	2.7
1997	2.4
1998	2.3
1999	2.1
2000	2.4
2001	2.6
2002	2.4
2003	1.4
2004	1.8
2005	2.2
2006	2.5
2007	2.3
2008	2.3
2009	1.7
2010	1.0
2011	1.7
2012	2.1
2013	1.8
2014	1.7
2015	1.8

Source: Bureau of Labor Statistics

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

The history of producer price inflation in the past five decades does not provide evidence of deflation. The finished core PPI does not register even one single year of decline, as shown in Table PPIEX.

Table PPIEX, Annual Percentage Changes of the PPI Finished Goods Excluding Food

Year	Annual ∆%
1974	11.4
1975	11.4
1976	5.7
1977	6.0
1978	7.5
1979	8.9
1980	11.2
1981	8.6
1982	5.7
1983	3.0
1984	2.4
1985	2.5
1986	2.3
1987	2.4
1988	3.3
1989	4.4
1990	3.7
1991	3.6
1992	2.4
1993	1.2
1994	1.0
1995	2.1
1996	1.4
1997	0.3
1998	0.9
1999	1.7
2000	1.3
2001	1.4
2002	0.1
2003	0.2
2004	1.5
2005	2.4
2006	1.5
2007	1.9
2008	3.4
2009	2.6
2010	1.2
2011	2.4
2012	2.6
2013	1.5
2014	1.9
2015	2.0

Source: Bureau of Labor Statistics

http://www.bls.gov/ppi/

Chart I-1 provides US nominal GDP from 1929 to 2015. The chart disguises the decline of nominal GDP during the 1930s from $104.6 billion in 1929 to $57.2 billion in 1933 or by 45.3 percent (data from the US Bureau of Economic Analysis at http://www.bea.gov/iTable/index_nipa.cfm). The level of nominal GDP reached $102.9 billion in 1940 and exceeded the $104.6 billion of 1929 only with $129.4 billion in 1941. The only major visible bump in the chart occurred in the recession of IVQ2007 to IIQ2009 with revised cumulative decline of real GDP of 4.2 percent. US nominal GDP fell from $14,718.6 billion in 2008 to $14,418.7 billion in 2009 or by 2.0 percent. US nominal GDP rose to $14,964.4 billion in 2010 or by 3.8 percent and to $15,517.9 billion in 2011 for an additional 3.7 percent for cumulative increase of 7.6 percent relative to 2009 and to $16,155.3 billion in 2012 for an additional 4.1 percent and cumulative increase of 12.0 percent relative to 2009. US nominal GDP increased from $14,477.6 in 2007 to $18,036.6 billion in 2015 or by 24.6 percent at the average annual rate of 2.8 percent per year (http://www.bea.gov/iTable/index_nipa.cfm). Tendency for deflation would be reflected in persistent bumps. In contrast, during the Great Depression in the four years of 1929 to 1933, GDP in constant dollars fell 26.3 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7). The comparison of the global recession after 2007 with the Great Depression is entirely misleading (http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html and earlier http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html).

Chart I-1, US, Nominal GDP 1929-2015

Source: US Bureau of Economic Analysis

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

Chart I-2 provides US real GDP from 1929 to 2015. The chart also disguises the Great Depression of the 1930s. In the four years of 1929 to 1933, GDP in constant dollars fell 26.3 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7; data from the US Bureau of Economic Analysis at http://www.bea.gov/iTable/index_nipa.cfm). Persistent deflation threatening real economic activity would also be reflected in the series of long-term growth of real GDP. There is no such behavior in Chart I-2 except for periodic recessions in the US economy that have occurred throughout history.

Chart I-2, US, Real GDP 1929-2015

Source: US Bureau of Economic Analysis

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

Deflation would also be in evidence in long-term series of prices in the form of bumps. The GDP implicit deflator series in Chart I-3 from 1929 to 2015 shows sharp dynamic behavior over time. There is decline of the implicit price deflator of GDP by 25.8 percent from 1929 to 1933 (data from the US Bureau of Economic Analysis at http://www.bea.gov/iTable/index_nipa.cfm). In contrast, the implicit price deflator of GDP of the US increased from 97.337 (2009 =100) in 2007 to 100.00 in 2009 or by 2.7 percent and increased to 109.998 in 2015 or by 10.0 percent relative to 2009 and 13.0 percent relative to 2007. The implicit price deflator of US GDP increased in every quarter from IVQ2007 to IVQ2012 with only two declines from 100.062 in IQ2009 to 99.895 in IIQ2009 or by 0.2 percent and to 99.873 in IIIQ2009 for cumulative 0.2 percent relative to IQ2009 and -0.02 percent relative to IIQ2009 (http://www.bea.gov/iTable/index_nipa.cfm). Wars are characterized by rapidly rising prices followed by declines when peace is restored. The US economy is not plagued by deflation but by long-run inflation.

Chart I-3, US, GDP Implicit Price Deflator 1929-2015

Source: US Bureau of Economic Analysis

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

Chart I-4 provides percent change from preceding quarter in prices of GDP at seasonally adjusted annual rates (SAAR) from 1980 to 2016. There is one case of negative change by 0.6 percent in IIQ2009 that was adjustment from 2.8 percent in IIIQ2008 following 2.3 percent in IQ2008 and 1.8 percent IIQ2008 caused by carry trades from policy interest rates being moved to zero into commodity futures. These positions were reversed because of the fear of toxic assets in banks in the proposal of TARP in late 2008 (Cochrane and Zingales 2009). Prices of GDP increased at 0.5 percent in IVQ2014. GDP prices decreased at 0.1 percent in IQ2015, increasing at 2.3 percent in IIQ015 and at 1.3 percent in IIIQ2015. Prices of GDP increased at 0.8 percent in IVQ2015 and at 0.5 percent in IQ2016. Prices of GDP increased at 2.3 percent in IIQ2016. There has not been actual deflation or risk of deflation threatening depression in the US that would justify unconventional monetary policy.

Chart I-4, Percent Change from Preceding Period in Prices for GDP Seasonally Adjusted at Annual Rates 1980-2016

Source: US Bureau of Economic Analysis

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

Chart I-5 provides percent change from preceding year in prices of GDP from 1929 to 2015. There are four consecutive years of declines of prices of GDP during the Great Depression: 3.8 percent in 1930, 9.9 percent in 1931, 11.4 percent in 1932 and 2.7 percent in 1933. There were two consecutive declines of 1.8 percent in 1938 and 1.3 percent in 1939. Prices of GDP fell 0.1 percent in 1949 after increasing 12.6 percent in 1946, 11.2 percent in 1947 and 5.6 percent in 1948, which is similar to experience with wars in other countries. There are no other negative changes of annual prices of GDP in 74 years from 1939 to 2015.

Chart I-5, Percent Change from Preceding Year in Prices for Gross Domestic Product 1930-2015

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

The producer price index of the US from 1947 to 2016 in Chart I-6 shows various periods of more rapid or less rapid inflation but no bumps. The major event is the decline in 2008 when risk aversion because of the global recession caused the collapse of oil prices from $148/barrel to less than $80/barrel with most other commodity prices also collapsing. The event had nothing in common with explanations of deflation but rather with the concentration of risk exposures in commodities after the decline of stock market indexes. Eventually, there was a flight to government securities because of the fears of insolvency of banks caused by statements supporting proposals for withdrawal of toxic assets from bank balance sheets in the Troubled Asset Relief Program (TARP), as explained by Cochrane and Zingales (2009). The bump in 2008 with decline in 2009 is consistent with the view that zero interest rates with subdued risk aversion induce carry trades into commodity futures.

Chart I-6, US, Producer Price Index, Finished Goods, NSA, 1947-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Chart I-7 provides 12-month percentage changes of the producer price index from 1948 to 2016. The distinguishing event in Chart I-7 is the Great Inflation of the 1970s. The shape of the two-hump Bactrian camel of the 1970s resembles the double hump from 2007 to 2016.

Chart I-7, US, Producer Price Index, Finished Goods, 12-Month Percentage Change, NSA, 1948-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Annual percentage changes of the producer price index from 1948 to 2015 are shown in Table I-1A. The producer price index fell 2.8 percent in 1949 following the adjustment to World War II and fell 0.6 percent in 1952 and 1.0 percent in 1953 around the Korean War. There are two other mild decline of 0.3 percent in 1959 and 0.3 percent in 1963. There are only few subsequent and isolated declines of the producer price index of 1.4 percent in 1986, 0.8 percent in 1998, 1.3 percent in 2002 and 2.6 percent in 2009. The decline of 2009 was caused by unwinding of carry trades in 2008 that had lifted oil prices to $140/barrel during deep global recession because of the panic of probable toxic assets in banks that would be removed with the Troubled Asset Relief Program (TARP) (Cochrane and Zingales 2009). Producer prices fell 3.2 percent in 2015 during collapse of commodity prices form high prices induced by zero interest rates. There is no evidence in this history of 65 years of the US producer price index suggesting that there is frequent and persistent deflation shock requiring aggressive unconventional monetary policy. The design of such anti-deflation policy could provoke price and financial instability because of lags in effect of monetary policy, model errors, inaccurate forecasts and misleading analysis of current economic conditions.

Table I-1A, US, Annual PPI Inflation ∆% 1948-2015

Year	Annual ∆%
1948	8.0
1949	-2.8
1950	1.8
1951	9.2
1952	-0.6
1953	-1.0
1954	0.3
1955	0.3
1956	2.6
1957	3.8
1958	2.2
1959	-0.3
1960	0.9
1961	0.0
1962	0.3
1963	-0.3
1964	0.3
1965	1.8
1966	3.2
1967	1.1
1968	2.8
1969	3.8
1970	3.4
1971	3.1
1972	3.2
1973	9.1
1974	15.4
1975	10.6
1976	4.5
1977	6.4
1978	7.9
1979	11.2
1980	13.4
1981	9.2
1982	4.1
1983	1.6
1984	2.1
1985	1.0
1986	-1.4
1987	2.1
1988	2.5
1989	5.2
1990	4.9
1991	2.1
1992	1.2
1993	1.2
1994	0.6
1995	1.9
1996	2.7
1997	0.4
1998	-0.8
1999	1.8
2000	3.8
2001	2.0
2002	-1.3
2003	3.2
2004	3.6
2005	4.8
2006	3.0
2007	3.9
2008	6.3
2009	-2.6
2010	4.2
2011	6.1
2012	1.9
2013	1.2
2014	1.9
2015	-3.2

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

The producer price index excluding food and energy from 1973 to 2016, the first historical date of availability in the dataset of the Bureau of Labor Statistics (BLS), shows similarly dynamic behavior as the overall index, as shown in Chart I-8. There is no evidence of persistent deflation in the US PPI.

Chart I-8, US Producer Price Index, Finished Goods Excluding Food and Energy, NSA, 1973-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

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

Chart I-9, US Producer Price Index, Finished Goods Excluding Food and Energy, 12-Month Percentage Change, NSA, 1974-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

The producer price index of energy goods from 1974 to 2016 is provided in Chart I-10. The first jump occurred during the Great Inflation of the 1970s analyzed in various comments of this blog (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html) and in Appendix I. There is relative stability of producer prices after 1986 with another jump and decline in the late 1990s into the early 2000s. The episode of commodity price increases during a global recession in 2008 could only have occurred with interest rates dropping toward zero, which stimulated the carry trade from zero interest rates to leveraged positions in commodity futures. Commodity futures exposures were dropped in the flight to government securities after Sep 2008. Commodity future exposures were created again when risk aversion diminished around Mar 2010 after the finding that US bank balance sheets did not have the toxic assets that were mentioned in proposing TARP in Congress (see Cochrane and Zingales 2009). Fluctuations in commodity prices and other risk financial assets originate in carry trade when risk aversion ameliorates. There are also fluctuations originating in shifts in preference for asset classes such as between commodities and equities.

Chart I-10, US, Producer Price Index, Finished Energy Goods, NSA, 1974-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Chart I-11 shows 12-month percentage changes of the producer price index of finished energy goods from 1975 to 2016. This index is only available after 1974 and captures only one of the humps of energy prices during the Great Inflation. Fluctuations in energy prices have occurred throughout history in the US but without provoking deflation. Two cases are the decline of oil prices in 2001 to 2002 that has been analyzed by Barsky and Kilian (2004) and the collapse of oil prices from over $140/barrel with shock of risk aversion to the carry trade in Sep 2008.

Chart I-11, US, Producer Price Index, Finished Energy Goods, 12-Month Percentage Change, NSA, 1974-2016

Source: US Bureau of Labor Statistics

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

Headline and core producer price indexes are in Table I-6. The headline PPI SA increased 0.8 percent in Sep 2016 and decreased 0.1 percent NSA in the 12 months ending in Sep 2016. The core PPI SA increased 0.4 percent in Sep 2016 and rose 1.4 percent in 12 months. Analysis of annual equivalent rates of change shows inflation waves similar to those worldwide. In the first wave, the absence of risk aversion from the sovereign risk crisis in Europe motivated the carry trade from zero interest rates into commodity futures that caused the annual equivalent rate of 11.1 percent in the headline PPI in Jan-Apr 2011 and 3.7 percent in the core PPI. In the second wave, commodity futures prices collapsed in Jun 2011 with the return of risk aversion originating in the sovereign risk crisis of Europe. The annual equivalent rate of headline PPI inflation collapsed to 0.6 percent in May-Jun 2011 but the core annual equivalent inflation rate was higher at 2.4 percent. In the third wave, headline PPI inflation resuscitated with annual equivalent at 4.1 percent in Jul-Sep 2011 and core PPI inflation at 3.2 percent. Core PPI inflation was persistent throughout 2011, jumping from annual equivalent at 2.0 percent in the first three months of 2010 to 3.0 percent in 12 months ending in Dec 2011. Unconventional monetary policy is based on the proposition that core rates reflect more fundamental inflation and are thus better predictors of the future. In practice, the relation of core and headline inflation is as difficult to predict as future inflation (see IIID Supply Shocks in http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html). In the fourth wave, risk aversion originating in the lack of resolution of the European debt crisis caused unwinding of carry trades with annual equivalent headline PPI inflation of 0.0 percent in Oct-Dec 2011 and 2.0 percent in the core annual equivalent. In the fifth wave from Jan to Mar 2012, annual equivalent inflation was 2.8 percent for the headline index but 3.2 percent for the core index excluding food and energy. In the sixth wave, annual equivalent inflation in Apr-May 2012 during renewed risk aversion was minus 4.1 percent for the headline PPI and 1.2 percent for the core. In the seventh wave, continuing risk aversion caused reversal of carry trades into commodity exposures with annual equivalent headline inflation of minus 1.2 percent in Jun-Jul 2012 while core PPI inflation was at annual equivalent 3.7 percent. In the eighth wave, relaxed risk aversion because of the announcement of the impaired bond buying program or Outright Monetary Transactions (OMT) of the European Central Bank (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html) induced carry trades that drove annual equivalent inflation of producer prices of the United States at 14.0 percent in Aug-Sep 2012 and 1.2 percent in the core index. In the ninth wave, renewed risk aversion caused annual equivalent inflation of minus 2.4 percent in Oct 2011-Dec 2012 in the headline index and 1.2 percent in the core index. In the tenth wave, annual equivalent inflation was 6.2 percent in the headline index in Jan-Feb 2013 and 1.8 percent in the core index. In the eleventh wave, annual equivalent inflation was minus 7.0 percent in Mar-Apr 2012 and 1.8 percent for the core index. In the twelfth wave, annual equivalent inflation returned at 3.0 percent in May-Aug 2013 and 1.5 percent in the core index. In the thirteenth wave, portfolio reallocations away from commodities and into equities reversed commodity carry trade with annual equivalent inflation of 0.8 percent in Sep-Nov 2013 in the headline PPI and 1.2 percent in the core. In the fourteenth wave, annual equivalent inflation returned at 5.3 percent annual equivalent for the headline index in Dec 2013-Feb 2014 and 3.7 percent for the core index. In the fifteenth wave, annual equivalent inflation was 1.2 percent for the general PPI index in Mar 2014 and 0.0 percent for the core PPI index. In the sixteenth wave, annual equivalent headline PPI inflation increased at 2.4 percent in Apr-Jul 2014 and 1.8 percent for the core PPI. In the seventeenth wave, annual equivalent inflation in Aug-Nov 2014 was minus 3.0 percent and 2.4 percent for the core index. In the eighteenth wave, annual equivalent inflation fell at 17.1 percent for the general index in Dec 2014 to Jan 2015 and increased at 3.0 percent in the core index. In the nineteenth wave, annual equivalent inflation changed at 0.0 percent in Feb 2015 and increased at 3.7 percent for the core index. In the twentieth wave, annual equivalent producer prices increased at 1.2 percent in Mar 2015 and the core at 2.4 percent. In the twenty-first wave, producer prices fell at 4.7 percent annual equivalent in Apr 2015 while the core index increased at 1.2 percent. In the twenty-second wave, producer prices increased at annual equivalent 12.7 percent in May-Jun 2015 and core producer prices at 3.7 percent. In the twenty-third wave, producer prices fell at 3.5 percent in Jul 2015 and the core index increased at 1.2 percent. In the twenty-fourth wave, annual equivalent inflation fell at 7.0 percent in Aug-Oct 2015 and the core index changed at 0.0 percent annual equivalent. In the twenty-fifth wave, annual equivalent inflation was 2.4 percent in Nov 2015 with the core at 1.2 percent. In the twenty-sixth wave, the headline PPI fell at annual equivalent 7.3 percent and the core increased at 2.4 percent in Dec 2015-Feb 2016. In the twenty-seventh wave, annual equivalent inflation was 4.5 percent for the central index in Mar-May 2016 and 2.4 percent for the core. In the twenty-eighth wave, annual equivalent inflation was 8.7 percent for the headline index in Jun 2016 and 2.4 percent for the core. In the twenty-ninth wave, producer prices fell at annual equivalent 5.8 percent in Jul 2016 and core producer prices fell at 2.4 percent. In the thirtieth wave, producer prices fell at 3.5 percent annual equivalent in Aug 2016 while core producer prices increased at 2.4 percent. In the thirty-first wave, producer prices increased at annual equivalent 10.0 percent in Sep 2016 while core prices increased at 4.9 percent. It is almost impossible to forecast PPI inflation and its relation to CPI inflation. “Inflation surprise” by monetary policy could be proposed to climb along a downward sloping Phillips curve, resulting in higher inflation but lower unemployment (see Kydland and Prescott 1977, Barro and Gordon 1983 and past comments of this blog http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). The architects of monetary policy would require superior inflation forecasting ability compared to forecasting naivety by everybody else. In practice, we are all naïve in forecasting inflation and other economic variables and events.

Table I-6, US, Headline and Core PPI Inflation Monthly SA and 12-Month NSA ∆%

	Finished Goods SA Month	Finished Goods NSA 12 months	Finished Core SA Month	Finished Core NSA 12 months
Sep 2016	0.8	-0.1	0.4	1.4
AE Sep	10.0		4.9
Aug	-0.3	-2.1	0.2	1.2
AE Aug	-3.5		2.4
Jul	-0.5	-2.2	-0.2	1.0
AE Jul	-5.8		-2.4
Jun	0.7	-2.0	0.2	1.2
AE Jun	8.7		2.4
May	0.7	-2.2	0.2	1.6
Apr	0.4	-1.5	0.2	1.6
Mar	0.0	-2.3	0.2	1.5
AE Mar-May	4.5		2.4
Feb	-0.8	-2.0	0.1	1.5
Jan	-0.4	-1.2	0.2	1.7
Dec 2015	-0.7	-2.7	0.2	1.8
AE Dec-Feb	-7.3		2.4
Nov	0.2	-3.3	0.1	1.7
AE Nov	2.4		1.2
Oct	-0.3	-4.0	-0.2	1.8
Sep	-1.1	-4.1	0.2	2.1
Aug	-0.4	-3.1	0.0	2.1
AE ∆% Aug-Oct	-7.0		0.0
Jul	-0.3	-2.8	0.1	2.3
AE ∆% Jul	-3.5		1.2
Jun	0.5	-2.6	0.5	2.3
May	1.5	-2.9	0.1	2.0
AE ∆% May-Jun	12.7		3.7
Apr	-0.4	-4.5	0.1	2.0
AE ∆% Apr	-4.7		1.2
Mar	0.1	-3.3	0.2	2.1
AE ∆% Mar	1.2		2.4
Feb	0.0	-3.2	0.3	1.9
AE ∆% Feb	0.0		3.7
Jan	-1.8	-3.0	0.4	1.7
Dec 2014	-1.3	-0.6	0.1	1.7
AE ∆% Dec-Jan	-17.1		3.0
Nov	-0.5	1.1	0.1	2.0
Oct	-0.3	1.8	0.2	2.2
Sep	-0.1	2.2	0.1	2.1
Aug	-0.1	2.3	0.2	1.9
AE ∆% Aug-Nov	-3.0		2.4
July	0.0	2.9	0.1	1.9
Jun	0.2	2.8	0.2	1.9
May	0.0	2.5	0.2	1.8
Apr	0.6	3.1	0.1	1.7
AE ∆% Apr-Jul	2.4		1.8
Mar	0.1	1.8	0.0	1.7
AE ∆% Mar	1.2		0.0
Feb	0.1	1.3	0.1	1.9
Jan	0.7	1.6	0.4	2.0
Dec 2013	0.5	1.4	0.4	1.6
AE ∆% Dec-Feb	5.3		3.7
Nov	0.1	0.8	0.2	1.3
Oct	0.2	0.3	0.1	1.2
Sep	-0.1	0.2	0.0	1.2
AE ∆% Sep-Nov	0.8		1.2
Aug	0.4	1.2	0.1	1.2
Jul	-0.1	2.1	0.1	1.3
Jun	0.1	2.3	0.2	1.6
May	0.6	1.6	0.1	1.7
AE ∆%  May-Aug	3.0		1.5
Apr	-0.6	0.5	0.1	1.7
Mar	-0.6	1.1	0.2	1.7
AE ∆%  Mar-Apr	-7.0		1.8
Feb	0.5	1.8	0.2	1.8
Jan	0.5	1.5	0.1	1.8
AE ∆%  Jan-Feb	6.2		1.8
Dec 2012	-0.2	1.4	0.1	2.1
Nov	-0.5	1.4	0.1	2.2
Oct	0.1	2.3	0.1	2.2
AE ∆%  Oct-Dec	-2.4		1.2
Sep	1.0	2.1	0.0	2.4
Aug	1.2	1.9	0.2	2.6
AE ∆% Aug-Sep	14.0		1.2
Jul	0.2	0.5	0.4	2.6
Jun	-0.4	0.7	0.2	2.6
AE ∆% Jun-Jul	-1.2		3.7
May	-0.6	0.6	0.1	2.7
Apr	-0.1	1.8	0.1	2.7
AE ∆% Apr-May	-4.1		1.2
Mar	0.1	2.7	0.2	2.9
Feb	0.3	3.4	0.2	3.1
Jan	0.3	4.1	0.4	3.1
AE ∆% Jan-Mar	2.8		3.2
Dec 2011	-0.1	4.7	0.2	3.0
Nov	0.3	5.7	0.1	3.0
Oct	-0.2	5.9	0.2	2.9
AE ∆% Oct-Dec	0.0		2.0
Sep	0.9	7.1	0.3	2.8
Aug	-0.3	6.6	0.2	2.7
Jul	0.4	7.2	0.3	2.7
AE ∆% Jul-Sep	4.1		3.2
Jun	-0.4	7.0	0.3	2.3
May	0.5	7.1	0.1	2.1
AE ∆%  May-Jun	0.6		2.4
Apr	0.9	6.7	0.3	2.3
Mar	0.7	5.7	0.3	2.0
Feb	1.1	5.5	0.2	1.8
Jan	0.8	3.7	0.4	1.6
AE ∆%  Jan-Apr	11.1		3.7
Dec 2010	0.9	3.8	0.2	1.4
Nov	0.4	3.4	0.0	1.2
Oct	0.8	4.3	0.0	1.6
Sep	0.3	3.9	0.2	1.6
Aug	0.6	3.3	0.1	1.3
Jul	0.1	4.1	0.1	1.5
Jun	-0.3	2.7	0.1	1.1
May	0.0	5.1	0.3	1.3
Apr	0.0	5.4	0.0	0.9
Mar	0.7	5.9	0.2	0.9
Feb	-0.7	4.1	0.1	1.0
Jan	1.0	4.5	0.2	1.0

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

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

The US producer price index NSA from 2000 to 2016 is in Chart I-24. There are two episodes of decline of the PPI during recessions in 2001 and in 2008. Barsky and Kilian (2004) consider the 2001 episode as one in which real oil prices were declining when recession began. Recession and the fall of commodity prices instead of generalized deflation explain the behavior of US inflation in 2008. There is similar collapse of producer prices into 2015 as in 2009 caused by the drop of commodity prices.

Chart I-24, US, Producer Price Index, NSA, 2000-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Twelve-month percentage changes of the PPI NSA from 2000 to 2016 are in Chart I-25. It may be possible to forecast trends a few months in the future under adaptive expectations but turning points are almost impossible to anticipate especially when related to fluctuations of commodity prices in response to risk aversion. In a sense, monetary policy has been tied to behavior of the PPI in the negative 12-month rates in 2001 to 2003 and then again in 2009 to 2010. There is similar sharp decline of inflation into 2015 caused by the drop of commodities. Monetary policy following deflation fears caused by commodity price fluctuations would introduce significant volatility and risks in financial markets and eventually in consumption and investment.

Chart I-25, US, Producer Price Index, 12-Month Percentage Change NSA, 2000-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

The US PPI excluding food and energy from 2000 to 2016 is in Chart I-26. There is here again a smooth trend of inflation instead of prolonged deflation as in Japan.

Chart I-26, US, Producer Price Index Excluding Food and Energy, NSA, 2000-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Twelve-month percentage changes of the producer price index excluding food and energy are in Chart I-27. Fluctuations replicate those in the headline PPI. There is an evident trend of increase of 12 months rates of core PPI inflation in 2011 but lower rates in 2012-2014. Prices rose less rapidly into 2015-2016 as during earlier fluctuations.

Chart I-27, US, Producer Price Index Excluding Food and Energy, NSA, 12-Month Percentage Changes, 2000-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

The US producer price index of energy goods from 2000 to 2016 is in Chart I-28. There is a clear upward trend with fluctuations, which would not occur under persistent deflation.

Chart I-28, US, Producer Price Index Finished Energy Goods, NSA, 2000-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Chart I-29 provides 12-month percentage changes of the producer price index of energy goods from 2000 to 2016. Barsky and Killian (2004) relate the episode of declining prices of energy goods in 2001 to 2002 to the analysis of decline of real oil prices. Interest rates dropping to zero during the global recession in 2008 induced carry trades that explain the rise of the PPI of energy goods toward 30 percent. Bouts of risk aversion with policy interest rates held close to zero explain the fluctuations in the 12-month rates of the PPI of energy goods in the expansion phase of the economy. Symmetric inflation targets induce significant instability in inflation and interest rates with adverse effects on financial markets and the overall economy.

Chart I-29, US, Producer Price Index Energy Goods, 12-Month Percentage Change, NSA, 2000-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Effective with the January 2014 Producer Price Index (PPI) data release in February 2014, BLS transitioned from the Stage of Processing (SOP) to the Final Demand-Intermediate Demand (FD-ID) aggregation system. This shift resulted in significant changes to the PPI news release, as well as other documents available from PPI. The transition to the FD-ID system was the culmination of a long-standing PPI objective to improve the current SOP aggregation system by incorporating PPIs for services, construction, government purchases, and exports. In comparison to the SOP system, the FD-ID system more than doubled PPI coverage of the United States economy to over 75 percent of in-scope domestic production. The FD-ID system was first introduced as a set of experimental indexes in January 2011. Nearly all new FD-ID goods, services, and construction indexes provide historical data back to either November 2009 or April 2010, while the indexes for goods that correspond with the historical SOP indexes go back to the 1970s or earlier.”

Headline and core final demand producer price indexes are in Table I-6A. The headline FD PPI SA increased 0.3 percent in Sep 2016 and increased 0.7 percent NSA in the 12 months ending in Sep 2016. The core FD PPI SA increased 0.1 percent in Aug 2016 and increased 1.0 percent in 12 months. Analysis of annual equivalent rates of change shows inflation waves similar to those worldwide. In the first wave, the absence of risk aversion from the sovereign risk crisis in Europe motivated the carry trade from zero interest rates into commodity futures that caused the average equivalent rate of 7.4 percent in the headline FD PPI in Jan-Apr 2011 and 4.6 percent in the core FD PPI. In the second wave, commodity futures prices collapsed in Jun 2011 with the return of risk aversion originating in the sovereign risk crisis of Europe. The annual equivalent rate of headline FD PPI inflation collapsed to 2.4 percent in May-Jun 2011 but the core annual equivalent inflation rate was at 2.4 percent. In the third wave, headline FD PPI inflation resuscitated with annual equivalent at 3.2 percent in Jul-Sep 2011 and core PPI inflation at 3.2 percent. Core FD PPI inflation was persistent throughout 2011, from annual equivalent at 4.6 percent in the first four months of 2011 to 2.6 percent in 12 months ending in Dec 2011. Unconventional monetary policy is based on the proposition that core rates reflect more fundamental inflation and are thus better predictors of the future. In practice, the relation of core and headline inflation is as difficult to predict as future inflation (see IIID Supply Shocks in http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html). In the fourth wave, risk aversion originating in the lack of resolution of the European debt crisis caused unwinding of carry trades with annual equivalent headline FD PPI inflation of minus 0.8 percent in Oct-Dec 2011 and minus 0.4 percent in the core annual equivalent. In the fifth wave from Jan to Mar 2012, annual equivalent inflation was 3.7 percent for the headline index and 3.7 percent for the core index excluding food and energy. In the sixth wave, annual equivalent inflation in Apr-May 2012 during renewed risk aversion was 1.2 percent for the headline FD PPI and 3.0 percent for the core. In the seventh wave, continuing risk aversion caused reversal of carry trades into commodity exposures with annual equivalent headline inflation of minus 2.4 percent in Jun-Jul 2012 while core FD PPI inflation was at annual equivalent minus 1.2 percent. In the eighth wave, relaxed risk aversion because of the announcement of the impaired bond buying program or Outright Monetary Transactions (OMT) of the European Central Bank (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html) induced carry trades that drove annual equivalent inflation of final demand producer prices of the United States at 6.2 percent in Aug-Sep 2012 and 1.2 percent in the core index. In the ninth wave, renewed risk aversion caused annual equivalent inflation of 1.2 percent in Oct 2011-Dec 2012 in the headline index and 2.8 percent in the core index. In the tenth wave, annual equivalent inflation was 2.4 percent in the headline index in Jan-Feb 2013 and 0.6 percent in the core index. In the eleventh wave, annual equivalent price change was minus 1.2 percent in Mar-Apr 2012 and 2.4 percent for the core index. In the twelfth wave, annual equivalent inflation returned at 1.8 percent in May-Aug 2013 and 1.2 percent in the core index. In the thirteenth wave, portfolio reallocations away from commodities and into equities reversed commodity carry trade with annual equivalent inflation of 1.6 percent in Sep-Nov 2013 in the headline FD PPI and 2.0 percent in the core. In the fourteenth wave, annual equivalent inflation was 2.4 percent annual equivalent for the headline index in Dec 2013-Feb 2014 and 1.6 percent for the core index. In the fifteenth wave, annual equivalent inflation increased to 2.7 percent in the headline FD PPI and 2.7 percent in the core in Mar-Jul 2014. In the sixteenth wave, annual equivalent inflation was minus 1.8 percent for the headline FD index and minus 1.2 percent for the core FD index in Aug-Sep 2014. In the seventeenth wave, annual equivalent inflation was 2.4 percent for the headline FD and 6.2 percent for the core FD in Oct 2014. In the eighteenth wave, annual equivalent inflation was minus 3.0 percent for the headline FDI and 1.2 percent for the core in Nov-Dec 2014. In the nineteenth wave, annual equivalent inflation was minus 6.4 percent for the general index and minus 2.4 percent for the core in Jan-Feb 2015. In the twentieth wave, annual equivalent inflation was 0.0 percent for the general index in Mar 2015 and 0.0 percent for the core. In the twenty-first wave, final demand prices changed at annual equivalent 0.0 percent for the headline index in Apr 2015 and increased at 2.4 percent for the core index. In the twenty-second wave, annual equivalent inflation returned at 3.7 percent for the headline index in May-Jul 2015 and at 1.8 percent for the core index. In the twenty-third wave, the headline final demand index fell at 2.4 percent annual equivalent in Aug 2015 and the core decreased at 2.4 percent annual equivalent. In the twenty-fourth wave, FD prices fell at annual equivalent 4.1 percent in Sep-Oct 2015. In the twenty-fifth wave, FD prices increased at 1.2 percent annual equivalent in Nov 2015. In the twenty-sixth wave, FD prices decreased at 1.2 percent annual equivalent in Dec 2015. In the twenty-seventh wave, FD prices increased at 4.9 percent annual equivalent in Jan 2016 and the core FD increased at 8.7 percent. In the twenty-eighth wave, FD prices fell at annual equivalent 3.0 percent in Feb-Mar 2016 while the core decreased at 1.2 percent. In the twenty-ninth wave, FD prices increased at 4.5 percent annual equivalent in Apr-Jun 2016 and core FT increased at 2.8 percent. In the thirtieth wave, final demand prices fell at 4.7 percent in annual equivalent in Jul 2016 while the core fell at 3.5 percent. In the thirty-first wave, final demand prices changed at annual equivalent 0.0 percent in Aug 2016 and the core increased at 1.2 percent. In the thirty-second wave, final demand prices increased at annual equivalent 3.7 percent in Sep 2016 while core final demand increased at 2.4 percent. It is almost impossible to forecast PPI inflation and its relation to CPI inflation. “Inflation surprise” by monetary policy could be proposed to climb along a downward sloping Phillips curve, resulting in higher inflation but lower unemployment (see Kydland and Prescott 1977, Barro and Gordon 1983 and past comments of this blog http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). The architects of monetary policy would require superior inflation forecasting ability compared to forecasting naivety by everybody else. In practice, we are all naïve in forecasting inflation and other economic variables and events.

Table I-6B, US, Headline and Core Final Demand Producer Price Inflation Monthly SA and 12-Month NSA ∆%

	Final Demand SA Month	Final Demand NSA 12 months	Final Demand Core SA Month	Final Demand Core NSA 12 months
Sep 2016	0.3	0.7	0.2	1.2
AE ∆% Sep	3.7		2.4
Aug	0.0	0.0	0.1	1.0
AE ∆% Aug	0.0		1.2
July	-0.4	-0.2	-0.3	0.7
AE ∆% Jul	-4.7		-3.5
Jun	0.5	0.3	0.4	1.3
May	0.3	0.0	0.1	1.2
Apr	0.3	0.2	0.2	1.1
AE ∆% Apr-Jun	4.5		2.8
Mar	-0.2	-0.1	-0.1	1.1
Feb	-0.3	0.1	-0.1	1.3
AE ∆% Mar-Feb	-3.0		-1.2
Jan	0.4	0.0	0.7	0.8
AE ∆% Jan	4.9		8.7
Dec 2015	-0.1	-1.1	0.1	0.2
AE ∆% Dec	-1.2		1.2
Nov	0.1	-1.3	0.1	0.3
AE ∆% Nov	1.2		1.2
Oct	-0.2	-1.4	-0.2	0.2
Sep	-0.5	-1.1	0.0	0.7
AE ∆% Sep-Oct	-4.1		-1.2
Aug	-0.2	-1.0	-0.2	0.6
AE ∆% Aug	-2.4		-2.4
Jul	0.1	-0.7	0.3	0.8
Jun	0.3	-0.5	0.3	1.1
May	0.5	-0.8	0.0	0.7
AE ∆% May-Jul	3.7		1.8
Apr	0.0	-1.1	0.2	1.0
AE ∆% Apr	0.0		2.4
Mar	0.0	-0.9	0.0	0.8
AE ∆% Mar	0.0		0.0
Feb	-0.5	-0.5	-0.4	1.0
Jan	-0.6	0.0	0.0	1.7
AE ∆% Jan-Feb	-6.4		-2.4
Dec 2014	-0.3	0.9	0.2	2.0
Nov	-0.2	1.3	0.0	1.7
AE ∆% Nov-Dec	-3.0		1.2
Oct	0.2	1.5	0.5	1.9
AE ∆% Oct	2.4		6.2
Sep	-0.2	1.6	-0.2	1.6
Aug	-0.1	1.9	0.0	1.9
AE ∆% Aug-Sep	-1.8		-1.2
Jul	0.4	1.9	0.5	1.9
Jun	0.0	1.8	0.0	1.6
May	0.2	2.1	0.3	2.1
Apr	0.2	1.8	0.0	1.5
Mar	0.3	1.6	0.3	1.6
AE ∆% Mar-Jul	2.7		2.7
Feb	0.2	1.2	0.2	1.6
Jan	0.3	1.3	0.3	1.4
Dec 2013	0.1	1.2	-0.1	1.2
AE ∆% Dec-Feb	2.4		1.6
Nov	0.1	1.1	0.2	1.4
Oct	0.2	1.3	0.2	1.7
Sep	0.1	1.1	0.1	1.6
AE ∆% Sep-Nov	1.6		2.0
Aug	0.0	1.7	-0.1	1.8
Jul	0.3	2.0	0.3	1.7
Jun	0.4	1.7	0.5	1.3
May	-0.1	0.9	-0.3	0.9
AE ∆%  May-Aug	1.8		1.2
Apr	-0.1	0.9	0.2	1.3
Mar	-0.1	1.3	0.2	1.5
AE ∆%  Mar-Apr	-1.2		2.4
Feb	0.2	1.6	0.0	1.4
Jan	0.2	1.6	0.1	1.7
AE ∆%  Jan-Feb	2.4		0.6
Dec 2012	0.1	1.9	0.1	2.0
Nov	0.1	1.7	0.5	1.8
Oct	0.1	1.9	0.1	1.6
AE ∆%  Oct-Dec	1.2		2.8
Sep	0.7	1.5	0.3	1.4
Aug	0.3	1.2	-0.1	1.2
AE ∆% Aug-Sep	6.2		1.2
Jul	-0.1	1.0	-0.1	1.7
Jun	-0.3	1.3	-0.1	1.9
AE ∆% Jun-Jul	-2.4		-1.2
May	0.0	1.6	0.2	2.2
Apr	0.2	2.0	0.3	2.1
AE ∆% Apr-May	1.2		3.0
Mar	0.2	2.4	0.2	2.3
Feb	0.3	2.8	0.3	2.6
Jan	0.4	3.1	0.4	2.5
AE ∆% Jan-Mar	3.7		3.7
Dec 2011	-0.1	3.2	0.0	2.6
Nov	0.3	3.7	0.2	2.7
Oct	-0.4	3.7	-0.3	2.7
AE ∆% Oct-Dec	-0.8		-0.4
Sep	0.4	4.5	0.2	2.9
Aug	0.2	4.4	0.4	3.0
Jul	0.2	4.5	0.2	2.7
AE ∆% Jul-Sep	3.2		3.2
Jun	0.1	4.3	0.2	2.6
May	0.3	4.2	0.2	2.3
AE ∆%  May-Jun	2.4		2.4
Apr	0.5	4.2	0.3	2.5
Mar	0.7	4.0	0.5	NA
Feb	0.6	3.3	0.3	NA
Jan	0.6	2.4	0.4	NA
AE ∆%  Jan-Apr	7.4		4.6
Dec 2010	0.3	2.8	0.1	NA
Nov	0.3	2.6	0.1	NA
Oct	0.4	NA	0.1	NA
Sep	0.3	NA	0.2	NA
Aug	0.2	NA	0.0	NA
Jul	0.2	NA	0.2	NA
Jun	-0.2	NA	-0.1	NA
May	0.2	NA	0.3	NA
Apr	0.3	NA	NA	NA
Mar	0.1	NA	NA	NA
Feb	-0.2	NA	NA	NA
Jan	0.9	NA	NA	NA

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

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

Chart I-24B provides the FD PPI NSA from 2009 to 2016. There is persistent inflation with periodic declines in inflation waves similar to those worldwide.

Chart I-24B, US, Final Demand Producer Price Index, NSA, 2009-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Twelve-month percentage changes of the FD PPI from 2010 to 2016 are in Chart I-25B. There are fluctuations in the rates with evident trend of decline to more subdued inflation. Reallocations of investment portfolios of risk financial assets from commodities to stocks explain much lower FD PPI inflation.

Chart I-25B, US, Final Demand Producer Price Index, 12-Month Percentage Change NSA, 2010-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

The core FD PPI NSA is in Chart I-26B. The behavior is similar to the headline index but with less fluctuation.

Chart I-26B, US, Final Demand Producer Price Index Excluding Food and Energy, NSA, 2009-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Percentage changes in 12 months of the core FD PPI are in Chart I-27B. There are fluctuations in 12 months percentage changes but with evident declining trend to more moderate inflation.

Chart I-27B, US, Final Demand Producer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2010-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

The energy FD PPI NSA is in Chart I-28B. The index increased during the reposition of carry trades after the discovery of lack of toxic assets in banks that caused flight away from risk financial assets into government obligations of the US (Cochrane and Zingales 2009). Alternating risk aversion and appetite with reallocations among classes of risk financial assets explain the behavior of the index after late 2010.

Chart I-28B, US, Final Demand Energy Producer Price Index, NSA, 2009-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Twelve-month percentage changes of the FD energy PPI are in Chart I-29B. Rates moderated from late 2010 to the present. There are multiple negative rates. Investors create and reverse carry trades from zero interest rates to derivatives of commodities in accordance with relative risk evaluations of classes of risk financial assets.

Chart I-29B, US, Final Demand Energy Producer Price Index, 12-Month Percentage Change, NSA, 2010-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016.