CMP Associates Regulation Blog: Recovering GDP of Major World Economies Still Underperforming Below Trend, Cyclically Stagnating US Real Disposable Income Per Capita, Financial Repression, Rules, Discretionary Authorities and Slow Productivity Growth, Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Collapse of United States Dynamism of Income Growth and Employment Creation in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, World Cyclical Slow Growth, and Government Intervention in Globalization: Part II

Recovering GDP of Major World Economies Still Underperforming Below Trend, Cyclically Stagnating US Real Disposable Income Per Capita, Financial Repression, Rules, Discretionary Authorities and Slow Productivity Growth, Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Collapse of United States Dynamism of Income Growth and Employment Creation in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, World Cyclical Slow Growth, and Government Intervention in Globalization

Carlos M. Pelaez

I Stagnating Real Disposable Income and Consumption Expenditures

IIB1 Stagnating Real Disposable Income and Consumption Expenditures

IB2 Financial Repression

II Rules, Discretionary Authorities and Slow Productivity Growth

IIB D estruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide

II IB Collapse of United States Dynamism of Income Growth and Employment Creation in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide

III World Financial Turbulence

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

II Rules, Discretionary Authorities and Slow Productivity Growth. The Bureau of Labor Statistics (BLS) of the Department of Labor provides the quarterly report on productivity and costs. The operational definition of productivity used by the BLS is (https://www.bls.gov/news.release/pdf/prod2.pdf 1): “Labor productivity, or output per hour, is calculated by dividing an index of real output by an index of hours worked by all persons, including employees, proprietors, and unpaid family workers.” The BLS has revised the estimates for productivity and unit costs. Table II-1 provides revised estimates for IIIQ2020 and revision of the estimates for IIQ2020 and IQ2020 together with data for nonfarm business sector productivity and unit labor costs in seasonally adjusted annual equivalent (SAAE) rate and the percentage change from the same quarter a year earlier. Reflecting increase in output at 43.4 percent and increase at 37.1 percent in hours worked, nonfarm business sector labor productivity increased at the SAAE rate of 4.6 percent in IIIQ2020, as shown in column 2 “IIIQ2020 SAEE.” The increase of labor productivity from IIIQ2019 to IIIQ2020 was 4.0 percent, reflecting decrease in output of 3.4 percent and decrease of hours worked of 7.1 percent, as shown in column 3 “IIIQ2020 YOY.” Hours worked decreased from minus 6.1 percent in IQ2020 to minus 42.9 percent in IIQ2020 and increased at 37.1 percent in IIIQ2020 while output growth decreased from minus 6.4 percent in IQ2020 at SAAE to minus 36.8 percent in IIQ2020, increasing at 43.4 percent in IIIQ2020. The BLS defines unit labor costs as (https://www.bls.gov/news.release/pdf/prod2.pdf 1): “BLS calculates unit labor costs as the ratio of hourly compensation to labor productivity. Increases in hourly compensation tend to increase unit labor costs and increases in output per hour tend to reduce them.” Unit labor costs decreased at the SAAE rate of 6.6 percent in IIIQ2020 and increased 4.0 percent in IIIQ2020 relative to III2019. Hourly compensation decreased at the SAAE rate of 2.3 percent in IIIQ2020, which deflating by the estimated inflation increase SAAE rate in IIIQ2020 results in decrease of real hourly compensation at 7.1 percent. Real hourly compensation increased 6.8 percent in IIIQ2020 relative to IIIQ2019.

Table II-1, US, Nonfarm Business Sector Productivity and Costs %

	IIIQ2020 SAAE	IIIQ2020 YOY	IIQ2020 SAAE	IIQ2020 YOY	IQ2020 SAAE	IQ2020 YOY
Productivity	4.6	4.0	10.6	2.9	-0.3	0.9
Output	43.4	-3.4	-36.8	-11.1	-6.4	0.1
Hours	37.1	-7.1	-42.9	-13.6	-6.1	-0.8
Hourly Comp.	-2.3	8.2	24.3	8.8	9.2	3.4
Real Hourly Comp.	-7.1	6.8	28.8	8.3	7.9	1.2
Unit Labor Costs	-6.6	4.0	12.3	5.7	9.6	2.5
Unit Nonlabor Payments	22.9	-3.6	-22.7	-7.8	-9.8	0.2
Implicit Price Deflator	4.4	0.7	-3.6	-0.2	0.8	1.5

Notes: SAAE: seasonally adjusted annual equivalent; Comp.: compensation; YoY: Quarter on Same Quarter Year Earlier

https://www.bls.gov/lpc/

The analysis by Kydland (https://www.nobelprize.org/prizes/economic-sciences/2004/kydland/biographical/) and Prescott (https://www.nobelprize.org/prizes/economic-sciences/2004/prescott/biographical/) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:

U_t = Uⁿ_t – α(π_t – π^e) α > 0 (1)

Where U_t is the rate of unemployment at current time t, Uⁿ_t is the natural rate of unemployment, π_t is the current rate of inflation and π^e is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:

W = W(π_t, U_t) (2)

The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (π_t, U_t- Uⁿ) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). Professor Edward P. Lazear (2017Feb27), writing in the Wall Street Journal, on Feb 27, 2017 (https://www.wsj.com/articles/how-trump-can-hit-3-growthmaybe-1488239746), finds that productivity growth was 7 percent between 2009 and 2016 at annual equivalent 1 percent. Lazear measures productivity growth at 2.3 percent per year from 2001 to 2008. Herkenhoff, Ohanian and Prescott (2017) and Ohanian and Prescott (2017Dec) analyze how restriction of land use by states in the United States have been depressing economic activity. Professor Edmund S. Phelps (https://www.nobelprize.org/prizes/economic-sciences/2006/phelps/auto-biography/) argues that there is failed analysis that fiscal stimulus in the form of higher government expenditures and tax reductions caused the recovery of the economy to normal levels by 2017 (Phelps, Edmund S. 2018. The fantasy of fiscal stimulus. The Wall Street Journal Oct 29, 2018 https://www.wsj.com/articles/the-fantasy-of-fiscal-stimulus-1540852299?mod=searchresults&page=1&pos=2). The evidence analyzed by Phelps leads to the conclusion that countries with disorderly government finance grew less rapidly than those with sounder fiscal performance. Phelps concludes convincingly that “there is a strong relationship between the speed of recovery and a proxy of its dynamism—the long-term growth rate of total factor productivity from 1990 to 2007. Some countries have preexisting social institutions and cultural capital that enables them to bounce back from an economic downturn. Much credit of the U.S.’s relatively speedy recovery is owed to this country’s endemic culture of innovation and enterprise.” Professor Edward P. Lazear, writing on “Mind the productivity gap to reduce inequality,” published in the Wall Street Journal on May 6, 2019 (https://www.wsj.com/articles/mind-the-productivity-gap-to-reduce-inequality-11557181134?mod=searchresults&page=1&pos=1), analyzes the causes of the growing differential of wages between the income of the 90^th percentile and the 50^th percentile in terms of technological change. The improvement of the lower half of wage earners would consist of increasing their skills. Professors John F. Cogan and John B. Taylor, writing in the Wall Street Journal on Oct 6, 2020, measure productivity growth increasing from 0.8 percent per year in 2013-2016 to 1.5 percent per year in 2016-2019 because of deregulation and market-oriented policies. The Bureau of Labor Statistics important report on productivity and costs released Mar 5, 2020 (https://www.bls.gov/lpc/) supports the argument of decline of productivity growth in the US analyzed by Prescott and Ohanian (2014Feb), Lazear (2017Feb27), Phelps (2018) and Cogan and Taylor (2020Oct6). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2019. The estimates incorporate the yearly revision of the US national accounts (https://www.bea.gov/information-updates-national-income-and-product-accounts) and the comprehensive revisions since 1929 (https://apps.bea.gov/national/pdf/2018-ComprehensiveUpdate-Results.pdf). The data confirm the argument of Prescott and Ohanian (2014Feb), Lazear (2017Feb27) and Cogan and Taylor (2020Oct6): productivity increased cumulatively 8.8 percent from 2011 to 2019 at the average annual rate of 0.9 percent. Confirming measurement by Cogan and Taylor (2020Oct6), productivity increased at average 0.8 percent from 2013 to 2016 and at 1.4 percent from 2017 to 2019, using revised data. Average productivity growth for the entire economic cycle from 2007 to 2019 is only 1.4 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.6 percent and 3.4 percent in 2010 consisted of reducing labor hours.

Table II-2, US, Revised Nonfarm Business Sector Productivity and Costs Annual Average, ∆% Annual Average

	2017 ∆%	2018 ∆%	2019 ∆%
Productivity	1.2	1.4	1.7
Real Hourly Compensation	1.3	0.9	1.8
Unit Labor Costs	2.2	1.9	1.9
	2016 ∆%	2015 ∆%	2014 ∆%	2013 ∆%	2012 ∆%	2011 ∆%
Productivity	0.3	1.6	0.9	0.5	0.9	0.0
Real Hourly Compensation	-0.2	3.0	1.1	-0.2	0.5	-0.9
Unit Labor Costs	0.7	1.6	1.9	0.8	1.8	2.2

	2010 ∆%	2009 ∆%	2008 ∆%	2007∆%
Productivity	3.4	3.6	1.1	1.7
Real Hourly Compensation	0.2	1.3	-0.9	1.5
Unit Labor Costs	-1.5	-2.5	1.7	2.6

Source: US Bureau of Labor Statistics

https://www.bls.gov/lpc/

Table II-3, US, Nonfarm Business Output per Productivity jumped in the recovery after the recession from Mar IQ2001 to Nov IVQ2001 (https://www.nber.org/cycles.html) Table II-3 provides quarter on quarter and annual percentage changes in nonfarm business output per hour, or productivity, from 1999 to 2020. The annual average jumped from 2.7 percent in 2001 to 4.3 percent in 2002. Nonfarm business productivity increased at the SAAE rate of 9.0 percent in the first quarter after the recession in IQ2002. Productivity increases decline later in the expansion period. Productivity increases were mediocre during the recession from Dec IVQ2007 to Jun IIIQ2009 (https://www.nber.org/cycles.html) and increased during the first phase of expansion from IIQ2009 to IQ2010, trended lower and collapsed in 2011 and 2012 with sporadic jumps and declines. Productivity increased at 3.1 percent in IVQ2013 and contracted at 3.9 percent in IQ2014. Productivity increased at 4.2 percent in IIQ2014 and at 3.9 percent in IIIQ2014. Productivity contracted at 1.9 percent in IVQ2014 and increased at 3.7 percent in IQ2015. Productivity grew at 1.5 percent in IIQ2015 and increased at 1.1 percent in IIIQ2015. Productivity contracted at 2.2 percent in IVQ2015 and increased at 0.9 percent in IQ2016. Productivity decreased at 0.1 percent in IIQ2016 and expanded at 1.2 percent in IIIQ2016. Productivity grew at 2.5 percent in IVQ2016 and increased at 1.0 percent in IQ2017. Productivity decreased at 0.1 percent in IIQ2017 and increased at 2.5 percent in IIIQ2017. Productivity increased at 1.3 percent in IVQ2017 and increased at 2.3 percent in IQ2018. Productivity increased at 1.1 percent in IIQ2018 and increased at 0.5 percent in IIIQ2018. Productivity increased at 0.8 percent in IVQ2018. Productivity increased at 3.7 percent in IQ2019. Productivity increased at 2.0 percent in IIQ2019 and increased at 0.3 percent in IIIQ2019. Productivity increased at 1.6 percent in IVQ2019. Productivity decreased at 0.3 percent in IQ2020, increasing at 10.6 percent in IIQ2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. Productivity increased at 4.6 percent in IIIQ2020.

Table II-3, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2020

Year	Qtr1	Qtr2	Qtr3	Qtr4	Annual
1999	5.4	1.1	3.8	6.3	3.8
2000	-0.6	8.4	-0.3	4.4	3.3
2001	-1.8	7.5	1.6	5.2	2.7
2002	9.0	0.5	3.1	-0.2	4.3
2003	4.3	5.1	9.3	4.0	3.8
2004	-1.4	3.8	1.8	1.9	2.9
2005	4.6	-1.0	3.2	0.3	2.2
2006	2.9	-0.3	-1.2	3.4	1.1
2007	1.1	1.7	4.0	3.2	1.7
2008	-3.1	4.2	1.2	-2.7	1.1
2009	3.9	8.5	6.1	5.7	3.6
2010	2.0	1.0	2.2	1.4	3.4
2011	-2.8	0.8	-1.5	2.6	0.0
2012	1.5	1.9	-0.9	-1.4	0.9
2013	2.4	-1.4	1.9	3.1	0.5
2014	-3.9	4.2	3.9	-1.9	0.9
2015	3.7	1.5	1.1	-2.2	1.6
2016	0.9	-0.1	1.2	2.5	0.3
2017	1.0	-0.1	2.5	1.3	1.2
2018	2.3	1.1	0.5	0.8	1.4
2019	3.7	2.0	0.3	1.6	1.7
2020	-0.3	10.6	4.6

Source: US Bureau of Labor Statistics

https://www.bls.gov/lpc/

Chart II-1 of the Bureau of Labor Statistics (BLS) provides SAAE rates of nonfarm business productivity from 1999 to 2020. There is a clear pattern in both episodes of economic cycles in 2001 and 2007 of rapid expansion of productivity in the transition from contraction to expansion followed by more subdued productivity expansion. Part of the explanation is the reduction in labor utilization resulting from adjustment of business to the sudden shock of collapse of revenue. Productivity rose briefly in the expansion after 2009 but then collapsed and moved to negative change with some positive changes recently at lower rates. Contractions in the cycle from 2007 to 2019 have been more frequent and sharper. Productivity increased in 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event as hours worked collapsed.

Chart II-1, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2020

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

Percentage changes from prior quarter at SAAE rates and annual average percentage changes of nonfarm business unit labor costs are provided in Table II-4. Unit labor costs fell during the contractions with continuing negative percentage changes in the early phases of the recovery. Weak labor markets partly explain the decline in unit labor costs. As the economy moves toward full employment, labor markets tighten with increase in unit labor costs. The expansion beginning in IIIQ2009 has been characterized by high unemployment and underemployment. Table II-4 shows continuing subdued increases in unit labor costs in 2011 but with increase at 8.2 percent in IQ2012 followed by increase at 0.3 percent in IIQ2012, increase at 1.2 percent in IIIQ2012 and increase at 12.6 percent in IVQ2012. Unit labor costs decreased at 7.8 percent in IQ2013 and increased at 4.4 percent in IIQ2013. Unit labor costs decreased at 2.9 percent in IIIQ2013 and decreased at 0.2 percent in IVQ2013. Unit labor costs increased at 12.4 percent in IQ2014 and at minus 5.7 percent in IIQ2014. Unit labor costs decreased at 1.1 percent in IIIQ2014 and increased at 6.2 percent in IVQ2014. Unit labor costs increased at 1.6 percent in IQ2015 and increased at 1.7 percent in IIQ2015. Unit labor costs increased at 0.5 percent in IIIQ2015 and increased at 2.0 percent in IVQ2015. Unit labor costs decreased at 0.9 percent in IQ2016 and increased at 1.3 percent in IIQ2016. Unit labor costs increased at 0.5 percent in IIIQ2016 and increased at 1.7 percent in IVQ2016. Unit labor costs increased at 2.9 percent in IQ2017 and increased at 2.5 percent in IIQ2017. United labor costs increased at 2.7 percent in IIIQ2017 and increased at 4.1 percent in IVQ2017. Unit labor costs changed at 0.0 percent in IQ2018 and increased at 0.2 percent in IIQ2018. Unit labor costs increased at 4.5 percent in IIIQ2018 and increased at 1.0 percent in IVQ2018. Unit labor costs increased at 4.8 percent in IQ2019 and decreased at 0.6 percent in IIQ2019. Unit labor costs decreased at 0.4 percent in IIIQ2019 and increased at 1.7 percent in IVQ2019. Unit labor costs increased at 9.6 percent in IQ2020 and increased at 12.3 percent in IIQ2020. Unit labor costs decreased at 6.6 percent in IIIQ2020.

Table II-4, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2020

Year	Qtr1	Qtr2	Qtr3	Qtr4	Annual
1999	1.8	0.6	-0.2	1.9	0.8
2000	15.6	-6.8	8.3	-2.1	3.6
2001	11.3	-5.5	-1.1	-1.4	1.6
2002	-6.5	3.0	-1.0	1.3	-1.9
2003	-1.7	1.9	-3.0	1.7	-0.1
2004	0.7	4.0	5.4	-0.2	1.6
2005	-1.7	3.4	1.8	2.2	1.4
2006	5.2	0.6	1.9	3.7	2.7
2007	8.9	-1.9	-2.3	1.3	2.6
2008	7.4	-3.4	2.6	6.9	1.7
2009	-13.4	1.7	-3.6	-3.1	-2.5
2010	-4.4	3.3	-0.5	0.8	-1.5
2011	10.5	-3.4	4.5	-7.6	2.2
2012	8.2	0.3	1.2	12.6	1.8
2013	-7.8	4.4	-2.9	-0.2	0.8
2014	12.4	-5.7	-1.1	6.2	1.9
2015	1.6	1.7	0.5	2.0	1.6
2016	-0.9	1.3	0.5	1.7	0.7
2017	2.9	2.5	2.7	4.1	2.2
2018	0.0	0.2	4.5	1.0	1.9
2019	4.8	-0.6	-0.4	1.7	1.9
2020	9.6	12.3	-6.6

Source: US Bureau of Labor Statistics

https://www.bls.gov/lpc/

Chart II-2 provides change of unit labor costs at SAAE from 1999 to 2020. There are multiple oscillations recently with negative changes alternating with positive changes. There is sharp contraction in 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event.

Chart II-2, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2020

Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/

Table II-5, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate, 1999-2020

Year	Qtr1	Qtr2	Qtr3	Qtr4	Annual
1999	5.8	-1.4	0.5	5.0	2.5
2000	10.4	-2.1	4.1	-0.5	3.5
2001	5.2	-1.3	-0.5	4.2	1.5
2002	0.5	0.3	-0.1	-1.3	0.7
2003	-1.6	7.8	3.0	4.1	1.4
2004	-4.0	4.7	4.6	-2.6	1.8
2005	0.8	-0.4	-1.0	-1.3	0.3
2006	6.0	-3.3	-3.0	9.0	0.6
2007	6.0	-4.6	-1.0	-0.4	1.5
2008	-0.4	-4.4	-2.3	14.2	-0.9
2009	-7.5	8.0	-1.1	-0.7	1.3
2010	-3.1	4.4	0.4	-1.0	0.2
2011	3.0	-6.9	0.3	-7.0	-0.9
2012	7.2	1.3	-1.6	8.2	0.5
2013	-7.2	3.3	-3.2	1.4	-0.2
2014	5.2	-3.9	1.6	5.3	1.1
2015	8.0	0.5	0.1	-0.3	3.0
2016	0.2	-1.7	-0.2	1.7	-0.2
2017	1.0	2.0	3.0	2.3	1.3
2018	-1.0	-0.9	2.9	0.5	0.9
2019	7.7	-1.6	-2.0	0.9	1.8
2020	7.9	28.8	-7.1

Source: US Bureau of Labor Statistics

https://www.bls.gov/lpc/

Chart II-3 provides percentage change from prior quarter at annual rate of nonfarm business real hourly compensation. There have been multiple negative percentage quarterly changes in the current cycle since IVQ2007. There is meager growth recently. There is sharp increase followed by sharp decrease in 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event.

Chart II-3, US, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate 1999-2020

Source: US Bureau of Labor Statistics https://www.bls.gov/lpc/

Chart II-4 provides percentage change of nonfarm business output per hour in a quarter relative to the same quarter a year earlier. As in most series of real output, productivity increased sharply in 2010 but the momentum was lost after 2011 as with the rest of the real economy. There are more negative yearly changes during the current cycle than in cycle after 1999. There is sharp increase in 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event.

Chart II-4, US, Nonfarm Business Output per Hour, Percent Change from Same Quarter a Year Earlier 1999-2020

Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/

Chart II-5 provides percentage changes of nonfarm business unit labor costs relative to the same quarter a year earlier. Softening of labor markets caused relatively high yearly percentage changes in the recession of 2001 repeated in the recession in 2009. Recovery was strong in 2010 but then weakened.

Chart II-5, US, Nonfarm Business Unit Labor Costs, Percent Change from Same Quarter a Year Earlier 1999-2020

Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/

Chart II-6 provides percentage changes of real hourly compensation in a month relative to the same month a year earlier. There is significant volatility in part because of recurring world inflation waves originating in carry trades from artificially low interest rates.

Chart II-6, US, Nonfarm Business Real Hourly Compensation, Percent Change from Same Quarter a Year Earlier 1999-2020

2012=100

Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/

In the analysis of Hansen (1939, 3) of secular stagnation, economic progress consists of growth of real income per person driven by growth of productivity. The “constituent elements” of economic progress are “(a) inventions, (b) the discovery and development of new territory and new resources, and (c) the growth of population” (Hansen 1939, 3). Secular stagnation originates in decline of population growth and discouragement of inventions. According to Hansen (1939, 2), US population grew by 16 million in the 1920s but grew by one half or about 8 million in the 1930s with forecasts at the time of Hansen’s writing in 1938 of growth of around 5.3 million in the 1940s. Hansen (1939, 2) characterized demography in the US as “a drastic decline in the rate of population growth.” Hansen’s plea was to adapt economic policy to stagnation of population in ensuring full employment. In the analysis of Hansen (1939, 8), population caused half of the growth of US GDP per year. Growth of output per person in the US and Europe was caused by “changes in techniques and to the exploitation of new natural resources.” In this analysis, population caused 60 percent of the growth of capital formation in the US. Declining population growth would reduce growth of capital formation. Residential construction provided an important share of growth of capital formation. Hansen (1939, 12) argues that market power of imperfect competition discourages innovation with prolonged use of obsolete capital equipment. Trade unions would oppose labor-savings innovations. The combination of stagnating and aging population with reduced innovation caused secular stagnation. Hansen (1939, 12) concludes that there is role for public investments to compensate for lack of dynamism of private investment but with tough tax/debt issues.

The current application of Hansen’s (1938, 1939, 1941) proposition argues that secular stagnation occurs because full employment equilibrium can be attained only with negative real interest rates between minus 2 and minus 3 percent. Professor Lawrence H. Summers (2013Nov8) finds that “a set of older ideas that went under the phrase secular stagnation are not profoundly important in understanding Japan’s experience in the 1990s and may not be without relevance to America’s experience today” (emphasis added). Summers (2013Nov8) argues there could be an explanation in “that the short-term real interest rate that was consistent with full employment had fallen to -2% or -3% sometime in the middle of the last decade. Then, even with artificial stimulus to demand coming from all this financial imprudence, you wouldn’t see any excess demand. And even with a relative resumption of normal credit conditions, you’d have a lot of difficulty getting back to full employment.” The US economy could be in a situation where negative real rates of interest with fed funds rates close to zero as determined by the Federal Open Market Committee (FOMC) do not move the economy to full employment or full utilization of productive resources. Summers (2013Oct8) finds need of new thinking on “how we manage an economy in which the zero nominal interest rates is a chronic and systemic inhibitor of economy activity holding our economies back to their potential.”

Former US Treasury Secretary Robert Rubin (2014Jan8) finds three major risks in prolonged unconventional monetary policy of zero interest rates and quantitative easing: (1) incentive of delaying action by political leaders; (2) “financial moral hazard” in inducing excessive exposures pursuing higher yields of risker credit classes; and (3) major risks in exiting unconventional policy. Rubin (2014Jan8) proposes reduction of deficits by structural reforms that could promote recovery by improving confidence of business attained with sound fiscal discipline.

Professor John B. Taylor (2014Jan01, 2014Jan3) provides clear thought on the lack of relevance of Hansen’s contention of secular stagnation to current economic conditions. The application of secular stagnation argues that the economy of the US has attained full-employment equilibrium since around 2000 only with negative real rates of interest of minus 2 to minus 3 percent. At low levels of inflation, the so-called full-employment equilibrium of negative interest rates of minus 2 to minus 3 percent cannot be attained and the economy stagnates. Taylor (2014Jan01) analyzes multiple contradictions with current reality in this application of the theory of secular stagnation:

Secular stagnation would predict idle capacity, in particular in residential investment when fed fund rates were fixed at 1 percent from Jun 2003 to Jun 2004. Taylor (2014Jan01) finds unemployment at 4.4 percent with house prices jumping 7 percent from 2002 to 2003 and 14 percent from 2004 to 2005 before dropping from 2006 to 2007. GDP prices doubled from 1.7 percent to 3.4 percent when interest rates were low from 2003 to 2005.
Taylor (2014Jan01, 2014Jan3) finds another contradiction in the application of secular stagnation based on low interest rates because of savings glut and lack of investment opportunities. Taylor (2009) shows that there was no savings glut. The savings rate of the US in the past decade is significantly lower than in the 1980s.
Taylor (2014Jan01, 2014Jan3) finds another contradiction in the low ratio of investment to GDP currently and reduced investment and hiring by US business firms.
Taylor (2014Jan01, 2014Jan3) argues that the financial crisis and global recession were caused by weak implementation of existing regulation and departure from rules-based policies.

Taylor (2014Jan01, 2014Jan3) argues that the recovery from the global recession was constrained by a change in the regime of regulation and fiscal/monetary policies.

U_t = Uⁿ_t – α(π_t – π^e) α > 0 (1)

W = W(π_t, U_t) (2)

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

Y = ∑_is_iy_i (1)

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

∆Y = ∑_i∆s_iy*_i+ ∑_i∆y_is*_i (2)

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

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

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. 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), 11-6). Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:

“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated.Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”

Chart II-7 provides nonfarm-business labor productivity, measured by output per hour, from 1947 to 2020. The rate of productivity increase continued in the early part of the 2000s but then softened and fell during the global recession. The interruption of productivity increases occurred exclusively in the current business cycle. Lazear and Spletzer (2012JHJul22) find “primarily cyclic” factors in explaining the frustration of currently depressed labor markets in the United States. Stagnation of productivity is another cyclic event and not secular trend. The theory and application of secular stagnation to current US economic conditions is void of reality.

Chart II-7, US, Nonfarm Business Labor Productivity, Output per Hour, 1947-2020, Index 2012=100

Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/

Table II-6 expands Table II-2 providing more complete measurements of the Productivity and Cost research of the Bureau of Labor Statistics. The proper emphasis of Prescott and Ohanian (2014Feb) is on the low productivity increases from 2011 to 2019. Labor productivity increased 3.4 percent in 2010 and 3.6 percent in 2009. There is much stronger yet not sustained performance in 2010 with productivity growing 3.4 percent because of growth of output of 3.3 percent with decline of hours worked of 0.1 percent. Productivity growth of 3.6 percent in 2009 consists of decline of output by 3.9 percent while hours worked collapsed 7.2 percent, which is not a desirable route to progress. The expansion phase of the economic cycle concentrated in one year, 2010, with underperformance in the remainder of the expansion from 2011 to 2019 of productivity growth at average 0.9 percent per year.

Table II-6, US, Productivity and Costs, Annual Percentage Changes 2007-2019

	2017	2018	2019
Productivity	1.2	1.4	17
Output	2.8	3.5	2.5
Hours Worked	1.5	2.0	0.7
Employment	1.6	1.9	1.2
Average Weekly Hours Worked	0.0	0.1	-0.5
Unit Labor Costs	2.2	1.9	1.9
Hourly Compensation	3.5	3.4	3.6
Consumer Price Inflation	2.1	2.4	1.8
Real Hourly Compensation	1.3	0.9	1.8
Non-labor Payments	3.7	6.3	3.5
Output per Job	1.2	1.6	1.2
	2016	2015	2014	2013	2012
Productivity	0.3	1.6	0.9	0.5	0.9
Output	1.8	3.7	3.2	2.2	3.1
Hours Worked	1.5	2.1	2.3	1.7	2.3
Employment	1.8	2.2	2.0	1.8	2.0
Average Weekly Hours Worked	-0.3	-0.1	0.2	-0.1	0.3
Unit Labor Costs	0.7	1.6	1.9	0.8	1.8
Hourly Compensation	1.1	3.1	2.8	1.3	2.7
Consumer Price Inflation	1.3	0.1	1.6	1.5	2.1
Real Hourly Compensation	-0.2	3.0	1.1	-0.2	0.5
Non-labor Payments	3.2	3.3	4.8	4.6	5.2
Output per Job	0.0	1.5	1.1	0.4	1.1

	2011	2010	2009	2008	2007
Productivity	0.0	3.4	3.6	1.1	1.7
Output	2.0	3.3	-3.9	-1.0	2.4
Hours Worked	2.0	-0.1	-7.2	-2.1	0.7
Employment	1.6	-1.2	-5.7	-1.4	0.9
Average Weekly Hours Worked	0.4	1.1	-1.6	-0.7	-0.2
Unit Labor Costs	2.2	-1.5	-2.5	1.7	2.6
Hourly Compensation	2.2	1.9	0.9	2.9	4.3
Consumer Price Inflation	3.2	1.6	-0.4	3.8	2.8
Real Hourly Compensation	-0.9	0.2	1.3	-0.9	1.5
Non-labor Payments	3.6	7.8	1.0	0.3	3.6
Output per Job	0.4	4.5	1.9	0.4	1.5

Source: US Bureau of Labor Statistics https://www.bls.gov/lpc/

Productivity growth can bring about prosperity while productivity regression can jeopardize progress. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Table II-7 provides average growth rates of indicators in the research of productivity and growth of the US Bureau of Labor Statistics. There is dramatic decline of productivity growth from 2.1 percent per year on average from 1947 to 2019 to 1.4 percent per year on average in the whole cycle from 2007 to 2019. Productivity increased at the average rate of 2.3 percent from 1947 to 2007. There is profound drop in the average rate of output growth from 3.4 percent on average from 1947 to 2019 to 1.9 percent from 2007 to 2019. Output grew at 3.7 percent per year on average from 1947 to 2007. 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 1.8 percent on average in the cyclical expansion in the 45 quarters from IIIQ2009 to IIIQ2020 and in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. 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 IIIQ2020 (https://www.bea.gov/sites/default/files/2020-12/gdp3q20_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 2.8 percent obtained by dividing GDP of $15,557.3 billion in IIQ2010 by GDP of $15,134.1 billion in IIQ2009 {[($15,557.3/$15,134.1) -1]100 = 2.8%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2020/12/us-gdp-growing-at-saar-334-percent-in.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/dollar-devaluation-increasing.html). The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.3 percent from IQ1983 to IIIQ1986, 5.1 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, 4.6 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991, 3.7 percent from IQ1983 to IVQ1991, 3.7 percent from IQ1983 to IQ1992, 3.7 percent from IQ1983 to IIQ1992, 3.7 percent from IQ1983 to IIIQ1992, 3.8 percent from IQ1983 to IVQ1992, 3.7 percent from IQ1983 to IQ1993, 3.6 percent from IQ1983 to IIQ1993, 3.6 percent from IQ1983 to IIIQ1993, 3.7 percent from IQ1983 to IVQ1993, 3.7 percent from IQ1983 to IQ1994 and at 7.9 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2020/12/us-gdp-growing-at-saar-334-percent-in.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/dollar-devaluation-increasing.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). 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 IIIQ2020 and in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event would have accumulated to 45.8 percent. GDP in IIIQ2020 would be $22,981.0 billion (in constant dollars of 2012) if the US had grown at trend, which is higher by $4384.5 billion than actual $18,596.5 billion. There are more than four trillion dollars of GDP less than at trend, explaining the 31.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 18.0 percent of the effective labor force with the largest part originating in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event (https://cmpassocregulationblog.blogspot.com/2020/12/dollar-devaluation-increasing.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/increase-in-oct-2020-of-nonfarm-payroll.html). Unemployment is decreasing while employment is increasing in initial adjustment of the lockdown of economic activity in the global recession resulting from the COVID-19 event (https://www.bls.gov/covid19/employment-situation-covid19-faq-november-2020.htm). US GDP in IIIQ2020 is 19.1 percent lower than at trend. US GDP grew from $15,762.0 billion in IVQ2007 in constant dollars to $18,596.5 billion in IIIQ2020 or 18.0 percent at the average annual equivalent rate of 1.3 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 2.9 percent per year from Nov 1919 to Nov 2020. Growth at 2.9 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 156.6710 in Nov 2020. The actual index NSA in Nov 2020 is 100.6075 which is 35.8 percent below trend. The underperformance of manufacturing in Mar-Aug 2020 originates partly in the earlier global recession augmented by the current global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19. Manufacturing grew at the average annual rate of 3.3 percent between Dec 1986 and Dec 2006. Growth at 3.3 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 164.7223 in Nov 2020. The actual index NSA in Nov 2020 is 100.6075, which is 38.9 percent below trend. Manufacturing output grew at average 1.8 percent between Dec 1986 and Nov 2020. Using trend growth of 1.8 percent per year, the index would increase to 136.3637 in Nov 2020. The output of manufacturing at 100.6075 in Nov 2020 is 26.2 percent below trend under this alternative calculation. Using the NAICS (North American Industry Classification System), manufacturing output fell from the high of 110.5147 in Jun 2007 to the low of 86.3800 in Apr 2009 or 21.8 percent. The NAICS manufacturing index increased from 86.3800 in Apr 2009 to 101.9023 in Nov 2020 or 18.0 percent. The NAICS manufacturing index increased at the annual equivalent rate of 3.5 percent from Dec 1986 to Dec 2006. Growth at 3.5 percent would increase the NAICS manufacturing output index from 106.6777 in Dec 2007 to 166.3617 in Nov 2020. The NAICS index at 101.9023 in Nov 2020 is 38.7 below trend. The NAICS manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999 to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output index from 106.6777 in Dec 2007 to 132.6282 in Nov 2020. The NAICS index at 101.9023 in Nov 2020 is 23.2 percent below trend under this alternative calculation.

Table II-7, US, Productivity and Costs, Average Annual Percentage Changes 2007-2019, 1947-2007 and 1947-2019

	Average Annual Percentage Rate 2007-2019	Average Annual Percentage Rate 1947-2007	Average Annual Percentage Rate 1947-2019
Productivity	1.4	2.3	2.1
Output	1.9	3.7	3.4
Hours	0.5	1.4	1.2
Employment	0.6	1.6	1.5
Average Weekly Hours	-1.2*	-14.4*	-15.5*
Hourly Compensation	2.4	5.4	4.9
Consumer Price Inflation	1.8	3.8	3.4
Real Hourly Compensation	0.6	1.7	1.5
Unit Labor Costs	1.0	3.0	2.7
Unit Non-Labor Payments	2.0	3.5	3.2
Output per Job	1.3	2.0	1.9

* Percentage Change

Source: US Bureau of Labor Statistics https://www.bls.gov/lpc/

Unit labor costs increased sharply during the Great Inflation from the late 1960s to 1981 as shown by sharper slope in Chart II-8. Unit labor costs continued to increase but at a lower rate because of cyclic factors and not because of imaginary secular stagnation.

Chart II-8, US, Nonfarm Business, Unit Labor Costs, 1947-2020, Index 2012=100

Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/

Real hourly compensation increased at relatively high rates after 1947 to the early 1970s but reached a plateau that lasted until the early 1990s, as shown in Chart II-9. There were rapid increases until the global recession. Cyclic factors and not alleged secular stagnation explain the interruption of increases in real hourly compensation.

Chart II-9, US, Nonfarm Business, Real Hourly Compensation, 1947-2020, Index 2012=100

Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/

IIA Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth. The valuable report on Financial Accounts of the United States formerly Flow of Funds Accounts of the United States provided by the Board of Governors of the Federal Reserve System (https://www.federalreserve.gov/releases/z1/default.htm https://www.federalreserve.gov/apps/fof/) is rich in important information and analysis. Table IIA-1, updated in this blog for every new quarterly release, shows the balance sheet of US households combined with nonprofit organizations in 2007, 2018, 2019 and IIIQ2020. Assets increased to $121.5 trillion in 2018 by $36.4 trillion relative to 2007 or 42.7 percent. Assets increased to $134.7 trillion in 2019 by $49.5 trillion or 58.2 percent. Assets increased to $140.3 trillion in IIIQ2020 by $55.1 trillion or 64.8 percent. Liabilities increased from $14.5 trillion in 2007 to $15.9 trillion in 2018, by $1403.0 billion or increase of 9.7 percent. Liabilities increased $1909.1 billion or 13.2 percent from 2007 to 2019. Liabilities increased $2288.4 billion or 15.8 percent from 2007 to IIIQ2020. Net worth increased from $70,659.4 billion in 2007 to $123,519.7 billion in IIIQ2020 by $52,860.3 billion or 74.8 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 260.280 in Sep 2020 (https://www.bls.gov/cpi/data.htm) or 23.9 percent. Net worth adjusted by CPI inflation increased 41.1 percent from 2007 to IIIQ2020. Nonfinancial assets increased $11,057.5 billion from $30,539.8 billion in 2007 to $41,597.3 billion in IIIQ2020 or 33.9 percent. There was increase from 2007 to IIIQ2020 of $9,118.2 billion in real estate assets or by 35.4 percent. Real estate assets adjusted for CPI inflation increased 9.3 percent between 2007 and IIIQ2020. The National Association of Realtors estimated that the gains in net worth in homes by Americans were about $4 trillion between 2000 and 2005 (quoted in Pelaez and Pelaez, The Global Recession Risk (2007), 224-5). Net worth increased 67.4 percent from IVQ2007 to IVQ2019 or 36.8 percent adjusting for inflation, 57.7 percent from IVQ2007 to IQ2020 or 28.3 percent adjusting for inflation, 69.4 percent from IVQ2007 to IIQ2020 or 38.0 percent adjusting for inflation and 74.8 percent from IVQ2007 to IIIQ2020 or 41.1 percent adjusting for inflation. Net worth increased 4.4 percent from IVQ2019 to IIIQ2020 or 3.1 percent adjusting for inflation.

Net worth decreased by $6,885.9 billion from IVQ2019 to IQ2020 or by 5.8 percent in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. Net worth increased $8,293.9 billion from IQ2020 to IIQ2020 or 7.4 percent. Net worth increased 1.2 percent from IVQ2019 to IIQ2020. Net worth increased $5,2253.3 billion from IVQ2019 to IIIQ2020 or 4.4 percent. Real estate increased $1,340.7 billion from IVQ2019 to IIIQ2020 or 4.0 percent. Financial assets increased $3,932.8 billion from IVQ2019 to IIIQ2020 or 4.1 percent. Stock markets recovered in Apr to Dec 2020. Corporate equities increased $1,089.7 billion from IVQ2019 to IIIQ2020 or 5.1 percent.

Table IIA-1, US, Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars Outstanding End of Period, NSA

	2007	2018	2019	IIIQ2020
Assets	85,161.3	121,530.6	134,705.5	140,310.1
Nonfinancial	30,539.8	37,846.8	39,925.4	41,597.3
Real Estate	25,748.3	31,702.4	33,525.8	34,866.5
Durable Goods	4,473.9	5,521.7	5,750.1	6,064.7
Financial	54,621.5	83,683.8	94,780.0	98,712.8
Deposits	5,916.5	9,628.6	10,161.4	11,289.3
Debt Secs.	3,516.2	5,106.3	5,584.8	4,904.6
Mutual Fund Shares	4,535.9	8,005.8	10,049.7	10,103.8
Equities Corporate	9757.7	16,558.9	21,232.5	22,322.2
Equity Noncorporate	8,927.4	11,540.2	12,328.4	12,754.2
Pension	16,414.9	25,743.2	27,744.5	28,357.8
Liabilities	14,501.9	15,904.9	16,411.0	16,790.3
Home Mortgages	10,625.0	10,211.5	10,483.7	10,787.5
Consumer Credit	2,609.5	3998.1	4180.7	4,136.2
Net Worth	70,659.4	105,625.8	118,294.4	123,519.7

Notes: Deposits: Total Time and Savings Deposits FL15303005; Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2020. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2020. Washington, DC, Federal Reserve System, Dec 10. https://www.federalreserve.gov/releases/z1/current/default.htm

The explanation of the sharp contraction of household wealth can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:

“On the maturity date T, the firm must either pay the promised payment of B to the debtholders or else the current equity will be valueless. Clearly, if at time T, V(T) > B, the firm should pay the bondholders because the value of equity will be V(T) – B > 0 whereas if they do not, the value of equity would be zero. If V(T) ≤ B, then the firm will not make the payment and default the firm to the bondholders because otherwise the equity holders would have to pay in additional money and the (formal) value of equity prior to such payments would be (V(T)- B) < 0.”

Pelaez and Pelaez (The Global Recession Risk (2007), 208-9) apply this analysis to the US housing market in 2005-2006 concluding:

“The house market [in 2006] is probably operating with low historical levels of individual equity. There is an application of structural models [Duffie and Singleton 2003] to the individual decisions on whether or not to continue paying a mortgage. The costs of sale would include realtor and legal fees. There could be a point where the expected net sale value of the real estate may be just lower than the value of the mortgage. At that point, there would be an incentive to default. The default vulnerability of securitization is unknown.”

There are multiple important determinants of the interest rate: “aggregate wealth, the distribution of wealth among investors, expected rate of return on physical investment, taxes, government policy and inflation” (Ingersoll 1987, 405). Aggregate wealth is a major driver of interest rates (Ibid, 406). Unconventional monetary policy, with zero fed funds rates and flattening of long-term yields by quantitative easing, causes uncontrollable effects on risk taking that can have profound undesirable effects on financial stability. Excessively aggressive and exotic monetary policy is the main culprit and not the inadequacy of financial management and risk controls.

The net worth of the economy depends on interest rates. In theory, “income is generally defined as the amount a consumer unit could consume (or believe that it could) while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is a flow that is obtained by applying a rate of return, r, to a stock of wealth, W, or Y = rW (Ibid). According to a subsequent restatement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption decisions is the long-run expected yield from wealth r*W. This yield was named permanent income: Y* = r*W” (Darby 1974, 229), where * denotes permanent. The simplified relation of income and wealth can be restated as:

W = Y/r (1)

Equation (1) shows that as r goes to zero, r →0, W grows without bound, W→∞.

Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment but the exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at close to zero interest rates, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).

The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4).

There are significant elements of the theory of bank financial fragility of Diamond and Dybvig (1983) and Diamond and Rajan (2000, 2001a, 2001b) that help to explain the financial fragility of banks during the credit/dollar crisis (see also Diamond 2007). The theory of Diamond and Dybvig (1983) as exposed by Diamond (2007) is that banks funding with demand deposits have a mismatch of liquidity (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 58-66). A run occurs when too many depositors attempt to withdraw cash at the same time. All that is needed is an expectation of failure of the bank. Three important functions of banks are providing evaluation, monitoring and liquidity transformation. Banks invest in human capital to evaluate projects of borrowers in deciding if they merit credit. The evaluation function reduces adverse selection or financing projects with low present value. Banks also provide important monitoring services of following the implementation of projects, avoiding moral hazard that funds be used for, say, real estate speculation instead of the original project of factory construction. The transformation function of banks involves both assets and liabilities of bank balance sheets. Banks convert an illiquid asset or loan for a project with cash flows in the distant future into a liquid liability in the form of demand deposits that can be withdrawn immediately.

In the theory of banking of Diamond and Rajan (2000, 2001a, 2001b), the bank creates liquidity by tying human assets to capital. The collection skills of the relationship banker convert an illiquid project of an entrepreneur into liquid demand deposits that are immediately available for withdrawal. The deposit/capital structure is fragile because of the threat of bank runs. In these days of online banking, the run on Washington Mutual was through withdrawals online. A bank run can be triggered by the decline of the value of bank assets below the value of demand deposits.

Pelaez and Pelaez (Regulation of Banks and Finance 2009b, 60, 64-5) find immediate application of the theories of banking of Diamond, Dybvig and Rajan to the credit/dollar crisis after 2007. It is a credit crisis because the main issue was the deterioration of the credit portfolios of securitized banks as a result of default of subprime mortgages. It is a dollar crisis because of the weakening dollar resulting from relatively low interest rate policies of the US. It caused systemic effects that converted into a global recession not only because of the huge weight of the US economy in the world economy but also because the credit crisis transferred to the UK and Europe. Management skills or human capital of banks are illustrated by the financial engineering of complex products. The increasing importance of human relative to inanimate capital (Rajan and Zingales 2000) is revolutionizing the theory of the firm (Zingales 2000) and corporate governance (Rajan and Zingales 2001). Finance is one of the most important examples of this transformation. Profits were derived from the charter in the original banking institution. Pricing and structuring financial instruments was revolutionized with option pricing formulas developed by Black and Scholes (1973) and Merton (1973, 1974, 1998) that permitted the development of complex products with fair pricing. The successful financial company must attract and retain finance professionals who have invested in human capital, which is a sunk cost to them and not of the institution where they work.

The complex financial products created for securitized banking with high investments in human capital are based on houses, which are as illiquid as the projects of entrepreneurs in the theory of banking. The liquidity fragility of the securitized bank is equivalent to that of the commercial bank in the theory of banking (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65). Banks created off-balance sheet structured investment vehicles (SIV) that issued commercial paper receiving AAA rating because of letters of liquidity guarantee by the banks. The commercial paper was converted into liquidity by its use as collateral in SRPs at the lowest rates and minimal haircuts because of the AAA rating of the guarantor bank. In the theory of banking, default can be triggered when the value of assets is perceived as lower than the value of the deposits. Commercial paper issued by SIVs, securitized mortgages and derivatives all obtained SRP liquidity on the basis of illiquid home mortgage loans at the bottom of the pyramid. The run on the securitized bank had a clear origin (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65):

“The increasing default of mortgages resulted in an increase in counterparty risk. Banks were hit by the liquidity demands of their counterparties. The liquidity shock extended to many segments of the financial markets—interbank loans, asset-backed commercial paper (ABCP), high-yield bonds and many others—when counterparties preferred lower returns of highly liquid safe havens, such as Treasury securities, than the risk of having to sell the collateral in SRPs at deep discounts or holding an illiquid asset. The price of an illiquid asset is near zero.”

Gorton and Metrick (2010H, 507) provide a revealing quote to the work in 1908 of Edwin R. A. Seligman, professor of political economy at Columbia University, founding member of the American Economic Association and one of its presidents and successful advocate of progressive income taxation. The intention of the quote is to bring forth the important argument that financial crises are explained in terms of “confidence” but as Professor Seligman states in reference to historical banking crises in the US, the important task is to explain what caused the lack of confidence. It is instructive to repeat the more extended quote of Seligman (1908, xi) on the explanations of banking crises:

“The current explanations may be divided into two categories. Of these the first includes what might be termed the superficial theories. Thus it is commonly stated that the outbreak of a crisis is due to lack of confidence,--as if the lack of confidence was not in itself the very thing which needs to be explained. Of still slighter value is the attempt to associate a crisis with some particular governmental policy, or with some action of a country’s executive. Such puerile interpretations have commonly been confined to countries like the United States, where the political passions of democracy have had the fullest way. Thus the crisis of 1893 was ascribed by the Republicans to the impending Democratic tariff of 1894; and the crisis of 1907 has by some been termed the ‘[Theodore] Roosevelt panic,” utterly oblivious of the fact that from the time of President Jackson, who was held responsible for the troubles of 1837, every successive crisis had had its presidential scapegoat, and has been followed by a political revulsion. Opposed to these popular, but wholly unfounded interpretations, is the second class of explanations, which seek to burrow beneath the surface and to discover the more occult and fundamental causes of the periodicity of crises.”

Scholars ignore superficial explanations in the effort to seek good and truth. The problem of economic analysis of the credit/dollar crisis is the lack of a structural model with which to attempt empirical determination of causes (Gorton and Metrick 2010SB). There would still be doubts even with a well-specified structural model because samples of economic events do not typically permit separating causes and effects. There is also confusion is separating the why of the crisis and how it started and propagated, all of which are extremely important.

In true heritage of the principles of Seligman (1908), Gorton (2009EFM) discovers a prime causal driver of the credit/dollar crisis. The objective of subprime and Alt-A mortgages was to facilitate loans to populations with modest means so that they could acquire a home. These borrowers would not receive credit because of (1) lack of funds for down payments; (2) low credit rating and information; (3) lack of information on income; and (4) errors or lack of other information. Subprime mortgage “engineering” was based on the belief that both lender and borrower could benefit from increases in house prices over the short run. The initial mortgage would be refinanced in two or three years depending on the increase of the price of the house. According to Gorton (2009EFM, 13, 16):

“The outstanding amounts of Subprime and Alt-A [mortgages] combined amounted to about one quarter of the $6 trillion mortgage market in 2004-2007Q1. Over the period 2000-2007, the outstanding amount of agency mortgages doubled, but subprime grew 800%! Issuance in 2005 and 2006 of Subprime and Alt-A mortgages was almost 30% of the mortgage market. Since 2000 the Subprime and Alt-A segments of the market grew at the expense of the Agency (i.e., the government sponsored entities of Fannie Mae and Freddie Mac) share, which fell from almost 80% (by outstanding or issuance) to about half by issuance and 67% by outstanding amount. The lender’s option to rollover the mortgage after an initial period is implicit in the subprime mortgage. The key design features of a subprime mortgage are: (1) it is short term, making refinancing important; (2) there is a step-up mortgage rate that applies at the end of the first period, creating a strong incentive to refinance; and (3) there is a prepayment penalty, creating an incentive not to refinance early.”

The prime objective of successive administrations in the US during the past 20 years and actually since the times of Roosevelt in the 1930s has been to provide “affordable” financing for the “American dream” of home ownership. The US housing finance system is mixed with public, public/private and purely private entities. The Federal Home Loan Bank (FHLB) system was established by Congress in 1932 that also created the Federal Housing Administration in 1934 with the objective of insuring homes against default. In 1938, the government created the Federal National Mortgage Association, or Fannie Mae, to foster a market for FHA-insured mortgages. Government-insured mortgages were transferred from Fannie Mae to the Government National Mortgage Association, or Ginnie Mae, to permit Fannie Mae to become a publicly-owned company. Securitization of mortgages began in 1970 with the government charter to the Federal Home Loan Mortgage Corporation, or Freddie Mac, with the objective of bundling mortgages created by thrift institutions that would be marketed as bonds with guarantees by Freddie Mac (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 42-8). In the third quarter of 2008, total mortgages in the US were $12,057 billion of which 43.5 percent, or $5423 billion, were retained or guaranteed by Fannie Mae and Freddie Mac (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 45). In 1990, Fannie Mae and Freddie Mac had a share of only 25.4 percent of total mortgages in the US. Mortgages in the US increased from $6922 billion in 2002 to $12,088 billion in 2007, or by 74.6 percent, while the retained or guaranteed portfolio of Fannie and Freddie rose from $3180 billion in 2002 to $4934 billion in 2007, or by 55.2 percent.

According to Pinto (2008) in testimony to Congress:

“There are approximately 25 million subprime and Alt-A loans outstanding, with an unpaid principal amount of over $4.5 trillion, about half of them held or guaranteed by Fannie and Freddie. Their high risk activities were allowed to operate at 75:1 leverage ratio. While they may deny it, there can be no doubt that Fannie and Freddie now own or guarantee $1.6 trillion in subprime, Alt-A and other default prone loans and securities. This comprises over 1/3 of their risk portfolios and amounts to 34% of all the subprime loans and 60% of all Alt-A loans outstanding. These 10.5 million unsustainable, nonprime loans are experiencing a default rate 8 times the level of the GSEs’ 20 million traditional quality loans. The GSEs will be responsible for a large percentage of an estimated 8.8 million foreclosures expected over the next 4 years, accounting for the failure of about 1 in 6 home mortgages. Fannie and Freddie have subprimed America.”

In perceptive analysis of growth and macroeconomics in the past six decades, Rajan (2012FA) argues that “the West can’t borrow and spend its way to recovery.” The Keynesian paradigm is not applicable in current conditions. Advanced economies in the West could be divided into those that reformed regulatory structures to encourage productivity and others that retained older structures. In the period from 1950 to 2000, Cobet and Wilson (2002) find that US productivity, measured as output/hour, grew at the average yearly rate of 2.9 percent while Japan grew at 6.3 percent and Germany at 4.7 percent (see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). In the period from 1995 to 2000, output/hour grew at the average yearly rate of 4.6 percent in the US but at lower rates of 3.9 percent in Japan and 2.6 percent in the US. Rajan (2012FA) argues that the differential in productivity growth was accomplished by deregulation in the US at the end of the 1970s and during the 1980s. In contrast, Europe did not engage in reform with the exception of Germany in the early 2000s that empowered the German economy with significant productivity advantage. At the same time, technology and globalization increased relative remunerations in highly-skilled, educated workers relative to those without skills for the new economy. It was then politically appealing to improve the fortunes of those left behind by the technological revolution by means of increasing cheap credit. As Rajan (2012FA) argues:

“In 1992, Congress passed the Federal Housing Enterprises Financial Safety and Soundness Act, partly to gain more control over Fannie Mae and Freddie Mac, the giant private mortgage agencies, and partly to promote affordable homeownership for low-income groups. Such policies helped money flow to lower-middle-class households and raised their spending—so much so that consumption inequality rose much less than income inequality in the years before the crisis. These policies were also politically popular. Unlike when it came to an expansion in government welfare transfers, few groups opposed expanding credit to the lower-middle class—not the politicians who wanted more growth and happy constituents, not the bankers and brokers who profited from the mortgage fees, not the borrowers who could now buy their dream houses with virtually no money down, and not the laissez-faire bank regulators who thought they could pick up the pieces if the housing market collapsed. The Federal Reserve abetted these shortsighted policies. In 2001, in response to the dot-com bust, the Fed cut short-term interest rates to the bone. Even though the overstretched corporations that were meant to be stimulated were not interested in investing, artificially low interest rates acted as a tremendous subsidy to the parts of the economy that relied on debt, such as housing and finance. This led to an expansion in housing construction (and related services, such as real estate brokerage and mortgage lending), which created jobs, especially for the unskilled. Progressive economists applauded this process, arguing that the housing boom would lift the economy out of the doldrums. But the Fed-supported bubble proved unsustainable. Many construction workers have lost their jobs and are now in deeper trouble than before, having also borrowed to buy unaffordable houses. Bankers obviously deserve a large share of the blame for the crisis. Some of the financial sector’s activities were clearly predatory, if not outright criminal. But the role that the politically induced expansion of credit played cannot be ignored; it is the main reason the usual checks and balances on financial risk taking broke down.”

In fact, Raghuram G. Rajan (2005) anticipated low liquidity in financial markets resulting from low interest rates before the financial crisis that caused distortions of risk/return decisions provoking the credit/dollar crisis and global recession from IVQ2007 to IIQ2009. Near zero interest rates of unconventional monetary policy induced excessive risks and low liquidity in financial decisions that were critical as a cause of the credit/dollar crisis after 2007. Rajan (2012FA) argues that it is not feasible to return to the employment and income levels before the credit/dollar crisis because of the bloated construction sector, financial system and government budgets.

Table IIA-2 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 65.9 percent in the US national home price index between Oct 2000 and Oct 2005. Prices rose 70.9 percent in the US national index from Oct 2000 to Oct 2006. House prices rose 29.5 percent between Oct 2003 and Oct 2005 for the US national propelled by low fed funds rates of 1.0 percent between Jul 2003 and Jul 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Jun 2004 until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decrease of yields of mortgage-backed securities with intended increase in mortgage rates. Similarly, between Oct 2003 and Oct 2006 the US national increased 33.4 percent. House prices have increased from Oct 2006 to Oct 2020 by 24.9 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Oct 2020, house prices increased 8.4 percent in the US national. Table IIA-1 also shows that house prices increased 113.4 percent between Oct 2000 and Oct 2020 for the US national. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The US national increased 24.6 percent in Oct 2020 from the peak in Jun 2006 and increased 24.5 percent from the peak in Jul 2006. The final part of Table II-2 provides average annual percentage rates of growth of the house price indexes of Standard & Poor’s Case-Shiller. The average rate for the US national was 3.6 percent from Dec 1987 to Dec 2019 and 3.6 percent from Dec 1987 to Dec 2000. Although the global recession affecting the US between IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly above 30 percent, the average annual growth rate between Dec 2000 and Dec 2019 was 3.6 percent for the US national.

Table IIA-2, US, Percentage Changes of Standard & Poor’s Case-Shiller National Home Price Indices, Not Seasonally Adjusted, ∆%

	US National
∆% Oct 2000 to Oct 2003	28.1
∆% Oct 2000 to Oct 2005	65.9
∆% Oct 2003 to Oct 2005	29.5
∆% Oct 2000 to Oct 2006	70.9
∆% Oct 2003 to Oct 2006	33.4
∆% Oct 2005 to Oct 2020	28.6
∆% Oct 2006 to Oct 2020	24.9
∆% Oct 2009 to Oct 2020	54.8
∆% Oct 2010 to Oct 2020	60.6
∆% Oct 2011 to Oct 2020	66.1
∆% Oct 2012 to Oct 2020	59.7
∆% Oct 2013 to Oct 2020	44.1
∆% Oct 2014 to Oct 2020	37.7
∆% Oct 2015 to Oct 2020	31.3
∆% Oct 2016 to Oct 2020	24.9
∆% Oct 2017 to Oct 2020	17.8
∆% Oct 2018 to Oct 2020	11.9
∆% Oct 2019 to Oct 2020	8.4
∆% Oct 2000 to Oct 2020	113.4
∆% Peak Jun 2006 to Oct 2020	24.6
∆% Peak Jul 2006 to Oct 2020	24.5
Average ∆% Dec 1987-Dec 2019	3.6
Average ∆% Dec 1987-Dec 2000	3.6
Average ∆% Dec 1992-Dec 2000	4.5
Average ∆% Dec 2000-Dec 2019	3.6

Source: https://www.spglobal.com/spdji/en/index-family/indicators/sp-corelogic-case-shiller/sp-corelogic-case-shiller-composite/#overview

Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the SA and NSA national house price, as shown in Table IIA-3. In Jan 2013, the seasonally adjusted national house price index increased 0.9 percent and the NSA increased 0.3. House prices increased at high monthly percentage rates from Feb to Nov 2013. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. With seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Jul 2011 but fell in every month from Aug 2011 to Feb 2012. The not seasonally adjusted index registers increase in Mar 2012 of 1.4 percent. Not seasonally adjusted house prices increased 1.9 percent in Apr 2012 and at high monthly percentage rates through Aug 2012. House prices not seasonally adjusted stalled from Oct 2012 to Dec 2012 and surged from Feb to Sep 2013, decelerating in Oct 2013-Jan 2014. House prices grew at fast rates in Mar-Jul 2014. The SA national house price index increased 1.7 percent in Oct 2020 and the NSA index increased 1.4 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

Table IIA-3, US, Monthly Percentage Change of S&P Corelogic Case-Shiller National Home Price Indices, Seasonally Adjusted and Not Seasonally Adjusted, ∆%

	∆% SA	∆% NSA
December 2010	-0.1	-0.8
January 2011	-0.4	-1.1
February 2011	-0.8	-0.9
March 2011	-0.3	0.0
April 2011	0.0	1.0
May 2011	-0.1	1.1
June 2011	0.0	0.9
July 2011	-0.1	0.3
August 2011	-0.3	-0.4
September 2011	-0.5	-1.1
October 2011	-0.5	-1.3
November 2011	-0.6	-1.3
December 2011	-0.3	-1.1
January 2012	0.0	-0.7
February 2012	-0.1	-0.1
March 2012	1.0	1.4
April 2012	0.9	1.9
May 2012	0.7	1.9
June 2012	0.6	1.5
July 2012	0.5	0.8
August 2012	0.4	0.3
September 2012	0.4	-0.2
October 2012	0.5	-0.3
November 2012	0.7	0.0
December 2012	0.6	-0.1
January 2013	0.9	0.3
February 2013	0.6	0.6
March 2013	1.5	1.9
April 2013	1.0	2.0
May 2013	0.9	1.9
June 2013	0.9	1.7
July 2013	0.9	1.2
August 2013	0.9	0.7
September 2013	0.8	0.2
October 2013	0.6	-0.1
November 2013	0.5	-0.1
December 2013	0.6	-0.1
January 2014	0.6	0.1
February 2014	0.4	0.3
March 2014	0.3	0.8
April 2014	0.2	1.1
May 2014	0.2	1.1
June 2014	0.2	0.9
July 2014	0.3	0.6
August 2014	0.4	0.2
September 2014	0.4	-0.1
October 2014	0.4	-0.2
November 2014	0.4	-0.1
December 2014	0.4	-0.1
January 2015	0.4	-0.1
February 2015	0.3	0.2
March 2015	0.4	0.9
April 2015	0.3	1.1
May 2015	0.3	1.1
June 2015	0.3	0.9
July 2015	0.4	0.6
August 2015	0.5	0.3
September 2015	0.5	0.1
October 2015	0.6	0.0
November 2015	0.5	0.1
December 2015	0.5	0.0
January 2016	0.4	0.0
February 2016	0.2	0.1
March 2016	0.3	0.8
April 2016	0.3	1.1
May 2016	0.4	1.0
June 2016	0.4	0.9
July 2016	0.4	0.6
August 2016	0.6	0.4
September 2016	0.5	0.2
October 2016	0.5	0.0
November 2016	0.5	0.1
December 2016	0.5	0.1
January 2017	0.6	0.1
February 2017	0.3	0.2
March 2017	0.4	0.8
April 2017	0.4	1.1
May 2017	0.4	1.1
June 2017	0.4	0.9
July 2017	0.5	0.7
August 2017	0.6	0.4
September 2017	0.6	0.2
October 2017	0.5	0.1
November 2017	0.6	0.2
December 2017	0.6	0.2
January 2018	0.6	0.1
February 2018	0.5	0.4
March 2018	0.4	0.8
April 2018	0.4	1.0
May 2018	0.3	0.9
June 2018	0.4	0.8
July 2018	0.3	0.4
August 2018	0.4	0.2
September 2018	0.3	0.0
October 2018	0.4	0.0
November 2018	0.3	-0.1
December 2018	0.2	-0.2
January 2019	0.2	-0.2
February 2019	0.2	0.1
March 2019	0.3	0.7
April 2019	0.3	0.9
May 2019	0.3	0.8
June 2019	0.2	0.6
July 2019	0.2	0.4
August 2019	0.3	0.2
September 2019	0.3	0.1
October 2019	0.4	0.0
November 2019	0.5	0.1
December 2019	0.4	0.1
January 2020	0.5	0.0
February 2020	0.5	0.4
March 2020	0.5	0.9
April 2020	0.4	1.0
May 2020	0.0	0.6
June 2020	0.2	0.6
July 2020	0.6	0.8
August 2020	1.3	1.1
September 2020	1.4	1.2
October 2020	1.7	1.4

Source: https://www.spglobal.com/spdji/en/index-family/indicators/sp-corelogic-case-shiller/sp-corelogic-case-shiller-composite/#overview

Table IIA-4 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2008 and 2009. Total assets fell $9.1 trillion or 10.7 percent from 2007 to 2008 and $8.1 trillion or 9.5 percent to 2009. Net worth fell $9.0 trillion from 2007 to 2008 or 12.8 percent and $7.9 trillion to 2009 or 11.2 percent. Subsidies to housing prolonged over decades together with interest rates at 1.0 percent from Jun 2003 to Jun 2004 inflated valuations of real estate and risk financial assets such as equities. The increase of fed funds rates by 25 basis points until 5.25 percent in Jun 2006 reversed carry trades through exotic vehicles such as subprime adjustable-rate mortgages (ARM) and world financial markets. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9).

Table IIA-4, Difference of Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars from 2007 to 2008 and 2009

	2007	2008	Change to 2008	2009	Change to 2009
A	85,161.3	76,048.3	-9,113.0	77,047.4	-8,113.9
Non FIN	30,539.8	27,985.8	-2,554.0	26,014.7	-4,525.1
RE	25,748.3	23,071.5	-2,676.8	21,084.1	-4,664.2
FIN	54,621.5	48,062.5	-6,559.0	51,032.7	-3,588.8
LIAB	14,501.9	14,398.3	-103.6	14,275.8	-226.1
NW	70,659.4	61,649.9	-9,009.5	62,771.6	-7,887.8

The apparent improvement in Table IIA-4A is mostly because of increases in valuations of risk financial assets by the carry trade from zero interest rates to leveraged exposures in risk financial assets such as stocks, high-yield bonds, emerging markets, commodities and so on. Zero interest rates also act to increase net worth by reducing debt or liabilities. The net worth of households has become an instrument of unconventional monetary policy by zero interest rates in the theory that increases in net worth increase consumption that accounts for 68.0 percent of GDP in IIIQ2020 (https://cmpassocregulationblog.blogspot.com/2020/12/us-gdp-growing-at-saar-334-percent-in.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/dollar-devaluation-increasing.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IIIQ2020, real estate increased in value by $9118.2 billion and financial assets increased $44,091.3 billion for net gain of real estate and financial assets of $53,209.5 billion, explaining most of the increase in net worth of $52,860.3 billion obtained by deducting the increase in liabilities of $2288.4 billion from the increase of assets of $55,148.8 billion (with minor rounding error). Net worth increased from $70,659.3 billion in IVQ2007 to $123,519.7 billion in IIIQ2020 by $53,860.3 billion or 74.8 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 260.280 in Sep 2020 (https://www.bls.gov/cpi/data.htm) or 23.9 percent. Net worth adjusted by CPI inflation increased 41.1 percent from 2007 to IIIQ2020. Real estate assets adjusted for CPI inflation increased 9.3 percent from 2007 to IIIQ2020. There are multiple complaints that unconventional monetary policy concentrates income on wealthier individuals because of their holdings of financial assets while the middle class has gained less because of fewer holdings of financial assets and higher share of real estate in family wealth. There is nothing new in these arguments. Interest rate ceilings on deposits and loans have been commonly used. The Banking Act of 1933 imposed prohibition of payment of interest on demand deposits and ceilings on interest rates on time deposits. These measures were justified by arguments that the banking panic of the 1930s was caused by competitive rates on bank deposits that led banks to engage in high-risk loans (Friedman, 1970, 18; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 74-5). The objective of policy was to prevent unsound loans in banks. Savings and loan institutions complained of unfair competition from commercial banks that led to continuing controls with the objective of directing savings toward residential construction. Friedman (1970, 15) argues that controls were passive during periods when rates implied on demand deposit were zero or lower and when Regulation Q ceilings on time deposits were above market rates on time deposits. The Great Inflation or stagflation of the 1960s and 1970s changed the relevance of Regulation Q. Friedman (1970, 26-7) predicted the future:

“The banks have been forced into costly structural readjustments, the European banking system has been given an unnecessary competitive advantage, and London has been artificially strengthened as a financial center at the expense of New York.”

In short, Depression regulation exported the US financial system to London and offshore centers. What is vividly relevant currently from this experience is the argument by Friedman (1970, 27) that the controls affected the most people with lower incomes and wealth who were forced into accepting controlled-rates on their savings that were lower than those that would be obtained under freer markets. As Friedman (1970, 27) argues:

“These are the people who have the fewest alternative ways to invest their limited assets and are least sophisticated about the alternatives.” 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 1.8 percent on average in the cyclical expansion in the 45 quarters from IIIQ2009 to IIIQ2020 and in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. 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 IIIQ2020 (https://www.bea.gov/sites/default/files/2020-12/gdp3q20_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 2.8 percent obtained by dividing GDP of $15,557.3 billion in IIQ2010 by GDP of $15,134.1 billion in IIQ2009 {[($15,557.3/$15,134.1) -1]100 = 2.8%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2020/12/us-gdp-growing-at-saar-334-percent-in.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/dollar-devaluation-increasing.html). The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.3 percent from IQ1983 to IIIQ1986, 5.1 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, 4.6 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991, 3.7 percent from IQ1983 to IVQ1991, 3.7 percent from IQ1983 to IQ1992, 3.7 percent from IQ1983 to IIQ1992, 3.7 percent from IQ1983 to IIIQ1992, 3.8 percent from IQ1983 to IVQ1992, 3.7 percent from IQ1983 to IQ1993, 3.6 percent from IQ1983 to IIQ1993, 3.6 percent from IQ1983 to IIIQ1993, 3.7 percent from IQ1983 to IVQ1993, 3.7 percent from IQ1983 to IQ1994 and at 7.9 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2020/12/us-gdp-growing-at-saar-334-percent-in.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/dollar-devaluation-increasing.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). 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 IIIQ2020 and in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event would have accumulated to 45.8 percent. GDP in IIIQ2020 would be $22,981.0 billion (in constant dollars of 2012) if the US had grown at trend, which is higher by $4384.5 billion than actual $18,596.5 billion. There are more than four trillion dollars of GDP less than at trend, explaining the 31.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 18.0 percent of the effective labor force with the largest part originating in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event (https://cmpassocregulationblog.blogspot.com/2020/12/dollar-devaluation-increasing.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/increase-in-oct-2020-of-nonfarm-payroll.html). Unemployment is decreasing while employment is increasing in initial adjustment of the lockdown of economic activity in the global recession resulting from the COVID-19 event (https://www.bls.gov/covid19/employment-situation-covid19-faq-november-2020.htm). US GDP in IIIQ2020 is 19.1 percent lower than at trend. US GDP grew from $15,762.0 billion in IVQ2007 in constant dollars to $18,596.5 billion in IIIQ2020 or 18.0 percent at the average annual equivalent rate of 1.3 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 2.9 percent per year from Nov 1919 to Nov 2020. Growth at 2.9 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 156.6710 in Nov 2020. The actual index NSA in Nov 2020 is 100.6075 which is 35.8 percent below trend. The underperformance of manufacturing in Mar-Aug 2020 originates partly in the earlier global recession augmented by the current global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19. Manufacturing grew at the average annual rate of 3.3 percent between Dec 1986 and Dec 2006. Growth at 3.3 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 164.7223 in Nov 2020. The actual index NSA in Nov 2020 is 100.6075, which is 38.9 percent below trend. Manufacturing output grew at average 1.8 percent between Dec 1986 and Nov 2020. Using trend growth of 1.8 percent per year, the index would increase to 136.3637 in Nov 2020. The output of manufacturing at 100.6075 in Nov 2020 is 26.2 percent below trend under this alternative calculation. Using the NAICS (North American Industry Classification System), manufacturing output fell from the high of 110.5147 in Jun 2007 to the low of 86.3800 in Apr 2009 or 21.8 percent. The NAICS manufacturing index increased from 86.3800 in Apr 2009 to 101.9023 in Nov 2020 or 18.0 percent. The NAICS manufacturing index increased at the annual equivalent rate of 3.5 percent from Dec 1986 to Dec 2006. Growth at 3.5 percent would increase the NAICS manufacturing output index from 106.6777 in Dec 2007 to 166.3617 in Nov 2020. The NAICS index at 101.9023 in Nov 2020 is 38.7 below trend. The NAICS manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999 to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output index from 106.6777 in Dec 2007 to 132.6282 in Nov 2020. The NAICS index at 101.9023 in Nov 2020 is 23.2 percent below trend under this alternative calculation.

Table IIA-4A, US, Difference of Balance Sheet of Households and Nonprofit Organizations Billions of Dollars from 2007 to 2018, 2019 and IIIQ2020

	Value 2007	Change to 2018	Change to 2019	Change to IIIQ2020
Assets	85,161.3	36,369.3	49,544.2	55,148.8
Nonfinancial	30,539.8	7,307.0	9,385.6	11,057.5
Real Estate	25,748.3	5,954.1	7,777.5	9,118.2
Financial	54,621.5	29,062.3	40,158.5	44,091.3
Liabilities	14,501.9	1,403.0	1,909.1	2,288.4
Net Worth	70,659.4	34,966.4	47,635.0	52,860.3

Notes: Deposits: Total Time and Savings Deposits FL15303005; Net Worth = Assets – Liabilities

The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and from IVQ1979) to IQ1994 and from IVQ2007 to IVQ2019 is in Table IIA-5. There is also the comparison of net worth from IV2019 to IIIQ2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. The data reveal the following facts for the cycles in the 1980s:

IVQ1979 to IQ1994. Net worth increased 194.3 percent from IVQ1979 to IQ1994, the all items CPI index increased 91.9 percent from 76.7 in Dec 1979 to 147.2 in Mar 1994 and real net worth increased 53.4 percent.
IQ1980 to IVQ1985. Net worth increased 66.5 percent, the all items CPI index increased 36.5 percent from 80.1 in Mar 1980 to 109.3 in Dec 1985 and real net worth increased 22.0 percent.
IVQ1979 to IVQ1985. Net worth increased 70.0 percent, the all items CPI index increased 42.5 percent from 76.7 in Dec 1979 to 109.3 in Dec 1985 and real net worth increased 19.3 percent.
IQ1980 to IQ1989. Net worth increased 121.5 percent, the all items CPI index increased 52.7 percent from 80.1 in Mar 1980 to 122.3 in Mar 1989 and real net worth increased 45.0 percent.
IQ1980 to IIQ1989. Net worth increased 126.0 percent, the all items CPI index increased 54.9 percent from 80.1 in Mar 1980 to 124.1 in Jun 1989 and real net worth increased 45.9 percent.
IQ1980 to IIIQ1989. Net worth increased 131.8 percent, the all items CPI index increased 56.1 percent from 80.1 in Mar 1980 to 125.0 in Sep 1989 and real net worth increased 48.6 percent.
IQ1980 to IVQ1989. Net worth increased 136.2 percent, the all items CPI index increased 57.4 from 80.1 in Mar 1980 to 126.1 in Dec 1989 and real net worth increased 50.0 percent.
IQ1980 to IQ1990. Net worth increased 137.6 percent, the all items CPI index increased 60.7 percent from 80.1 in Mar 1980 to 128.7 in Mar 1990 and real net worth increased 47.9 percent.
IQ1980 to IIQ1990. Net worth increased 140.1 percent, the all items CPI index increased 62.2 percent from 80.1 in Mar 1980 to 129.9 in Jun 1990 and real net worth increased 48.1 percent
IQ1980 to IIIQ1990. Net worth increased 138.3 percent, the all items CPI index increased 65.7 percent from 80.1 in Mar 1980 to 132.7 in Jun 1990 and real net worth increased 43.9 percent.
IQ1980 to IVQ1990. Net worth increased 143.0 percent, the all items CPI index increased 67.0 percent from 80.1 in Mar 1980 to 133.8 in Dec 1990 and real net worth increased 45.5 percent. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). This new cyclical contraction explains the contraction of net worth in IIIQ1990
IQ1980 to IQ1991. Net worth increased 149.3 percent, the all items CPI index increased 68.5 percent from 80.1 in Mar 1980 to 135.0 in Mar 1991 and real net worth increased 47.9 percent.
IQ1980 to IIQ1991. Net worth increased 149.8 percent, the all items CPI index increased 69.8 percent from 80.1 in Mar 1980 to 136.0 in Jun 1991 and real net worth increased 47.1 percent.
IQ1980 to IIIQ1991. Net worth increased 152.8 percent, the all items CPI index increased 71.3 percent from 80.1 in Mar 1980 to 137.2 in Sep 1991 and real net worth increased 47.6 percent.
IQ1980 to IVQ1991. Net worth increased 159.1 percent, the all items CPI index increased 72.2 percent from 80.1 in Mar 1980 to 137.9 in Dec 1991 and real net worth increased 50.5 percent.
IQ1980 to IQ1992. Net worth increased 160.1 percent, the all items CPI index increased 73.9 percent from 80.1 in Mar 1980 to 139.3 in Mar 1992 and real net worth increased 49.6 percent.
IQ1980 to IIQ1992. Net worth increased 161.0 percent, the all items CPI index increased 75.0 percent from 80.1 in Mar 1980 to 140.2 in Jun 1992 and real net worth increased 49.1 percent.
IQ1980 to IIIQ1992. Net worth increased 164.8 percent, the all items CPI index increased 76.4 percent from 80.1 in Mar 1980 to 141.3 in Sep 1992 and real net worth increased 50.1 percent.
IQ1980 to IVQ1992. Net worth increased 171.2, the all items CPI index increased 77.2 percent from 80.1 in Mar 1980 to 141.9 in Dec 1992 and real net worth increased 53.1 percent.
IQ1980 to IQ1993. Net worth increased 174.8 percent, the all items CPI increased 79.3 percent from 80.1 in Mar 1980 to 143.6 in Mar 1993 and real net worth increased 53.3 percent.
IQ1980 to IIQ1993. Net worth increased 177.6 percent, the all items CPI increased 80.3 percent from 80.1 in Jun 1980 to 144.4 in Jun 1993 and real net worth increased 54.0 percent.
IQ1980 to IIIQ1993. Net worth increased 181.9 percent, the all items CPI increased 81.1 percent from 80.1 in Jun 1980 to 145.1 in Sep 1993 and real net worth increased 55.6 percent.
IQ1980 to IVQ1993. Net worth increased 186.5 percent, the all items CPI increased 82.0 percent from 80.1 in Jun 1980 to 145.8 in Dec 1993 and real net worth increased 57.4 percent.
IQ1980 to IQ1994. Net worth increased 188.2 percent, the all items CPI increased 83.8 percent from 80.1 in Jun 1980 to 147.2 in Mar 1994 and real net worth increased 56.8 percent.

There is comparatively weaker performance in the economic cycle of the global recession of 2007:

IVQ2007 to IVQ2019. Net worth increased 67.4 percent, the all items CPI increased 22.3 percent from 210.036 in Dec 2007 to 256.974 in Dec 2019 and real net worth increased 36.8 percent.

There is sharp contraction followed by recovery in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event:

IVQ2019 to IIIQ2020. Net worth increased 4.4 percent, the all items CPI increased 1.3 percent from 256.974 in IVQ2019 to 250.280 in IIIQ2020 and real net worth increased 3.1 percent. Net worth decreased by $6,885.9 billion from IVQ2019 to IQ2020 or by 5.8 percent in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. Net worth increased $8,293.9 billion from IQ2020 to IIQ2020 or 7.4 percent. Net worth increased 1.2 percent from IVQ2019 to IIQ2020. Net worth increased $5,2253.3 billion from IVQ2019 to IIIQ2020 or 4.4 percent. Real estate increased $1,340.7 billion from IVQ2019 to IIIQ2020 or 4.0 percent. Financial assets increased $3,932.8 billion from IVQ2019 to IIIQ2020 or 4.1 percent. Stock markets recovered in Apr to Dec 2020. Corporate equities increased $1,089.7 billion from IVQ2019 to IIIQ2020 or 5.1 percent.

The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. 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 1.8 percent on average in the cyclical expansion in the 45 quarters from IIIQ2009 to IIIQ2020 and in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. 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 IIIQ2020 (https://www.bea.gov/sites/default/files/2020-12/gdp3q20_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 2.8 percent obtained by dividing GDP of $15,557.3 billion in IIQ2010 by GDP of $15,134.1 billion in IIQ2009 {[($15,557.3/$15,134.1) -1]100 = 2.8%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2020/12/us-gdp-growing-at-saar-334-percent-in.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/dollar-devaluation-increasing.html). The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.3 percent from IQ1983 to IIIQ1986, 5.1 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, 4.6 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991, 3.7 percent from IQ1983 to IVQ1991, 3.7 percent from IQ1983 to IQ1992, 3.7 percent from IQ1983 to IIQ1992, 3.7 percent from IQ1983 to IIIQ1992, 3.8 percent from IQ1983 to IVQ1992, 3.7 percent from IQ1983 to IQ1993, 3.6 percent from IQ1983 to IIQ1993, 3.6 percent from IQ1983 to IIIQ1993, 3.7 percent from IQ1983 to IVQ1993, 3.7 percent from IQ1983 to IQ1994 and at 7.9 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2020/12/us-gdp-growing-at-saar-334-percent-in.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/dollar-devaluation-increasing.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). 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 IIIQ2020 and in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event would have accumulated to 45.8 percent. GDP in IIIQ2020 would be $22,981.0 billion (in constant dollars of 2012) if the US had grown at trend, which is higher by $4384.5 billion than actual $18,596.5 billion. There are more than four trillion dollars of GDP less than at trend, explaining the 31.2 million unemployed or underemployed equivalent to actual unemployment/underemployment of 18.0 percent of the effective labor force with the largest part originating in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event (https://cmpassocregulationblog.blogspot.com/2020/12/dollar-devaluation-increasing.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/increase-in-oct-2020-of-nonfarm-payroll.html). Unemployment is decreasing while employment is increasing in initial adjustment of the lockdown of economic activity in the global recession resulting from the COVID-19 event (https://www.bls.gov/covid19/employment-situation-covid19-faq-november-2020.htm). US GDP in IIIQ2020 is 19.1 percent lower than at trend. US GDP grew from $15,762.0 billion in IVQ2007 in constant dollars to $18,596.5 billion in IIIQ2020 or 18.0 percent at the average annual equivalent rate of 1.3 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 2.9 percent per year from Nov 1919 to Nov 2020. Growth at 2.9 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 156.6710 in Nov 2020. The actual index NSA in Nov 2020 is 100.6075 which is 35.8 percent below trend. The underperformance of manufacturing in Mar-Aug 2020 originates partly in the earlier global recession augmented by the current global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19. Manufacturing grew at the average annual rate of 3.3 percent between Dec 1986 and Dec 2006. Growth at 3.3 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 164.7223 in Nov 2020. The actual index NSA in Nov 2020 is 100.6075, which is 38.9 percent below trend. Manufacturing output grew at average 1.8 percent between Dec 1986 and Nov 2020. Using trend growth of 1.8 percent per year, the index would increase to 136.3637 in Nov 2020. The output of manufacturing at 100.6075 in Nov 2020 is 26.2 percent below trend under this alternative calculation. Using the NAICS (North American Industry Classification System), manufacturing output fell from the high of 110.5147 in Jun 2007 to the low of 86.3800 in Apr 2009 or 21.8 percent. The NAICS manufacturing index increased from 86.3800 in Apr 2009 to 101.9023 in Nov 2020 or 18.0 percent. The NAICS manufacturing index increased at the annual equivalent rate of 3.5 percent from Dec 1986 to Dec 2006. Growth at 3.5 percent would increase the NAICS manufacturing output index from 106.6777 in Dec 2007 to 166.3617 in Nov 2020. The NAICS index at 101.9023 in Nov 2020 is 38.7 below trend. The NAICS manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999 to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output index from 106.6777 in Dec 2007 to 132.6282 in Nov 2020. The NAICS index at 101.9023 in Nov 2020 is 23.2 percent below trend under this alternative calculation.

Table IIA-5, Net Worth of Households and Nonprofit Organizations in Billions of Dollars, IVQ1979 to IQ1994 and IVQ2007 to IIIQ2020

Period IQ1980 to IQ1994
Net Worth of Households and Nonprofit Organizations USD Millions
IVQ1979 IQ1980	9,104.3 9,297.0
IVQ1985 IIIQ1986 IVQ1986 IQ1987 IIQ1987 IIIQ1987 IVQ1987 IQ1988 IIQ1988 IIIQ1988 IVQ1988 IQ1989 IIQ1989 IIIQ1989 IVQ1989 IQ1990 IIQ1990	15,481.3 16,537.2 17,107.6 17,731.7 18,023.6 18,435.6 18,381.2 18,890.3 19,328.2 19,649.2 20,156.4 20,589.4 21,011.8 21,554.4 21,957.1 22,086.0 22,324.4
III1990	22,156.6
IV1990	22,590.8
I1991	23,175.6
IIQ1991	23,224.1
IIIQ1991	23,503.9
IVQ1991	24,090.5
IQ1992	24,181.0
IIQ1992	24,266.7
IIIQ1992	24,617.2
IVQ1992	25,216.3
IQ1993	25,546.1
IIQ1993	25,808.7
IIIQ1993	26,205.4
IVQ1993	26,639.4
IQ1994	26,797.7
∆ USD IVQ1979 to IVQ1985 IVQ1979 to IQ1994 IQ1980-IVQ1985 IQ1980-IIIQ1986 IQ1980-IVQ1986 IQ1980-IQ1987 IQ1980-IIQ1987 IQ1980-IIIQ1987 IQ1980-IVQ1987 IQ1980-IQ1988 IQ1980-IIQ1988 IQ1980-IIIQ1988 IQ1980-IVQ1988 IQ1980-IQ1989 IQ1980-IIQ1989 IQ1980-IIIQ1989 IQ1980-IVQ1989 IQ1980-IQ1990 IQ1980-IIQ1990	+6,377.0 ∆%70.0 R∆19.3 +17,657.4 ∆%194.3 R∆%53.4 +6,184.3∆%66.5 R∆%22.0 +7,240.2 ∆%77.9 R∆%29.3 +7,810.6 ∆%84.0 R∆%33.4 +8,434.7 ∆%90.7 R∆%36.3 +8,726.6 ∆%93.9 R∆%36.8 +9,138.6 ∆%98.3 R∆%38.1 +9084.2 ∆%97.7 R∆%37.2 +9593.3 ∆%103.2 R∆%39.7 10,031.2 ∆%107.9 R∆%41.1 +10,352.2 ∆%111.3 R∆%41.3 +10,859.4 ∆%116.8 R∆%44.1 +11292.4 ∆%121.5 R∆%45.0 +11,714.8 ∆%126.0 R∆% 45.9 +12,257.4 ∆%131.8 R∆% 48.6 +12,660.1 ∆%136.2 R∆%50.0 +12,789.0 ∆%137.6 R∆%47.9 +13,027.4 ∆%140.1 R∆%48.1
IQ1980-IIIQ1990	+12,859.6∆%138.3 R∆%43.9
IQ1980-IVQ1990	+13,293.8 ∆%143.0 R∆%45.5
IQ1980-IQ1991	+13,878.6 ∆%149.3 R∆%47.9
IQ1980-IIQ1991	+13,927.1 ∆%149.8 R∆%47.1
IQ1980-IIIQ1991	+14,206.9 ∆%152.8 R∆%47.6
IQ1980-IVQ1991	+14,793.5 ∆%159.1 R∆%50.5
IQ1980-IQ1992	+14,884.0 ∆%160.1 R∆%49.6
IQ1980-IIQ1992	+14,969.6 ∆%161.0 R∆%49.1
IQ1980-IIIQ1992	+15,320.6 ∆%164.8 R∆%50.1
IQ1980-IVQ1992	+15,919.9 ∆%171.2 R∆%53.1
IQ1980-IQ1993	+16,249.1 ∆%174.8 R∆%53.3
IQ1980-IIQ1993	+16,511.7 ∆%177.6 R∆% 54.0
IQ1980-IIIQ1993	+16,908.4 ∆%181.9 R∆% 55.6
IQ1980-IVQ1993	+17342.4 ∆%186.5 R∆% 57.4
IQ1980-IQ1994	+17500.7 ∆%188.2 R∆% 56.8
Period IVQ2007 to IVQ2019
Net Worth of Households and Nonprofit Organizations USD Millions
IVQ2007	70,659.4
IVQ2019	118,294.4
∆ USD Billions	+47635.0 ∆%67.4 R∆% 36.8
Period IVQ2019 to IIIQ2020
IVQ2019	118,294.4
IIIQ2020	123,519.7
IVQ2019 to IIIQ2020
∆ USD Billions	+5,225.3 ∆%4.4 R∆%3.1

Net Worth = Assets – Liabilities. R∆% real percentage change or adjusted for CPI percentage change.

Notes: Deposits: Total Time and Savings Deposits FL15303005; Net Worth = Assets – Liabilities

Chart IIA-1 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ2007 to IIIQ2020. There is remarkable stop and go behavior in this series with two sharp declines and two standstills in the 44 quarters of expansion of the economy beginning in IIIQ2009. The increase in net worth of households and nonprofit organizations is the result of increases in valuations of risk financial assets and compressed liabilities resulting from zero interest rates. Wealth of households and nonprofits organization increased 41.1 percent from IVQ2007 to IIIQ2020 when adjusting for consumer price inflation. Net worth of households and nonprofit organizations fell 3.4 percent from 109,311.4 billion in IIIQ2018 to 105,625.8 billion in IVQ2018 or $3,685.6 billion. Financial assets decreased 4.6 percent from 87,686.0 billion in IIIQ2018 to 83,683.8 billion in IVQ2018 or $4002.2 billion. Corporate equities fell 13.9 percent from $19,231.8 billion in IIIQ2018 to $16,558.9 billion in IVQ2018 or $2,672.9 billion. These are the revised data in the report of Dec 10, 2020, for IIQ20120. Net worth increased 4.4 percent, the all items CPI increased 1.3 percent from 256.974 in IVQ2019 to 250.280 in IIIQ2020 and real net worth increased 3.1 percent. Net worth decreased by $6,885.9 billion from IVQ2019 to IQ2020 or by 5.8 percent in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. Net worth increased $8,293.9 billion from IQ2020 to IIQ2020 or 7.4 percent. Net worth increased 1.2 percent from IVQ2019 to IIQ2020. Net worth increased $5,2253.3 billion from IVQ2019 to IIIQ2020 or 4.4 percent. Real estate increased $1,340.7 billion from IVQ2019 to IIIQ2020 or 4.0 percent. Financial assets increased $3,932.8 billion from IVQ2019 to IIIQ2020 or 4.1 percent. Stock markets recovered in Apr to Dec 2020. Corporate equities increased $1,089.7 billion from IVQ2019 to IIIQ2020 or 5.1 percent.

Chart IIA-1, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ2007 to IIIQ2020

Source: Source: Board of Governors of the Federal Reserve System. 2020. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2020. Washington, DC, Federal Reserve System, Dec 10. https://www.federalreserve.gov/releases/z1/current/default.htm

Chart IIA-2 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1979 to IQ1994. There are changes in the rates of growth of wealth suggested by the changing slopes but there is smooth upward trend. There was significant financial turmoil during the 1980s. Benston and Kaufman (1997, 139) find that there was failure of 1150 US commercial and savings banks between 1983 and 1990, or about 8 percent of the industry in 1980, which is nearly twice more than between the establishment of the Federal Deposit Insurance Corporation in 1934 through 1983. More than 900 savings and loans associations, representing 25 percent of the industry, were closed, merged or placed in conservatorships (see Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 74-7). The Financial Institutions Reform, Recovery and Enforcement Act of 1989 (FIRREA) created the Resolution Trust Corporation (RTC) and the Savings Association Insurance Fund (SAIF) that received $150 billion of taxpayer funds to resolve insolvent savings and loans. The GDP of the US in 1989 was $5641.6 billion (https://apps.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.66 percent of GDP in a year. The Bureau of Economic Analysis estimates US GDP in 2019 at $21,433.2 billion, such that the bailout would be equivalent to cost to taxpayers of about $570.1 billion in current GDP terms. A major difference with the Troubled Asset Relief Program (TARP) for private-sector banks is that most of the costs were recovered with interest gains whereas in the case of savings and loans there was no recovery. Money center banks were under extraordinary pressure from the default of sovereign debt by various emerging nations that represented a large share of their net worth (see Pelaez 1986). Net worth of households and nonprofit organizations increased 188.2 percent from IQ1980 to IQ1994 and 56.8 percent when adjusting for consumer price inflation. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). This new cyclical contraction explains the contraction followed by stability of net worth in the final segment followed by mild increase and then rising trend in Chart IIA-2.

Chart IIA-2, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1979 to IQ1994

Chart IIA-3 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1945 at $806.6 billion to IIIQ2020 at $123,519.7 billion or increase of 15,213.6 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 260.280 in IIIQ2020 or increase of 1,330.1 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 74.75 years with inflation-adjusted increase from $44.319 in dollars of 1945 to $474.565 in IIIQ2020 or 970.8 percent. In a simple formula: {[($123,519.7÷806.6)÷(260.280/18.2)-1]100 = 970.8%}. Wealth of households and nonprofit organizations increased from $806.6 billion at year-end 1945 to $123,519.7 billion at the end of IIIQ2020 or 15,213.6 percent. The consumer price index increased from 18.2 in Dec 1945 to 260.280 in Sep 2020 or 1,330.1 percent. Net wealth of households and nonprofit organizations in dollars of 1945 increased from $44.319 in 1945 to $474.565 in IIIQ2020 or 970.8 percent at the average yearly rate of 3.2 percent. US real GDP grew at the average rate of 2.9 percent from 1945 to 2019 (https://apps.bea.gov/iTable/index_nipa.cfm). The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIIQ2009 caused sharp contraction of net worth of US households and nonprofit organizations. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 74.75 years when US GDP grew at 1.8 percent on average in the forty-five quarters between IIIQ2009 and IIIQ2020 (https://cmpassocregulationblog.blogspot.com/2020/12/us-gdp-growing-at-saar-334-percent-in.html and earlier https://cmpassocregulationblog.blogspot.com/2020/11/dollar-devaluation-increasing.html). US GDP was $228.0 billion in 1945 and net worth of households and nonprofit organizations $806.6 billion for ratio of wealth to GDP of 3.54. The ratio of net worth of households and nonprofits of $70,659.4 billion in 2007 to GDP of $14,451.9 billion was 4.89. The ratio of net worth of households and nonprofits of $118,294.4 billion in 2019 to GDP of $21,433.2 billion was 5.52. The final data point in Chart IIA-3 is net worth of household and nonprofit institutions at $123,519.7 billion in IIIQ2020 for increase of 15,213.6 percent relative to $806.6 billion in IVQ1945. CPI adjusted net worth of household and nonprofit institutions increased from $44.319 in IVQ1945 to $474.565 in IIIQ2020 or 970.8 percent at the annual equivalent rate of 3.2 percent. Net worth of households and nonprofit organizations fell 3.4 percent from 109,311.4 billion in IIIQ2018 to 105,625.8 billion in IVQ2018 or $3,685.6 billion. Financial assets decreased 4.6 percent from 87,686.0 billion in IIIQ2018 to 83,683.8 billion in IVQ2018 or $4002.2 billion. Corporate equities fell 13.9 percent from $19,231.8 billion in IIIQ2018 to $16,558.9 billion in IVQ2018 or $2,672.9 billion. These are the revised data in the report of Dec 10, 2020, for IIQ20120. Net worth increased 4.4 percent, the all items CPI increased 1.3 percent from 256.974 in IVQ2019 to 250.280 in IIIQ2020 and real net worth increased 3.1 percent. Net worth decreased by $6,885.9 billion from IVQ2019 to IQ2020 or by 5.8 percent in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. Net worth increased $8,293.9 billion from IQ2020 to IIQ2020 or 7.4 percent. Net worth increased 1.2 percent from IVQ2019 to IIQ2020. Net worth increased $5,2253.3 billion from IVQ2019 to IIIQ2020 or 4.4 percent. Real estate increased $1,340.7 billion from IVQ2019 to IIIQ2020 or 4.0 percent. Financial assets increased $3,932.8 billion from IVQ2019 to IIIQ2020 or 4.1 percent. Stock markets recovered in Apr to Dec 2020. Corporate equities increased $1,089.7 billion from IVQ2019 to IIIQ2020 or 5.1 percent.

Chart IIA-3, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1945 to IIIQ2019

Table IIA-6 provides percentage changes of nonfinancial domestic sector debt. Households increased debt by 10.5 percent in 2006 but reduced debt from 2010 to 2011. Households have increased debt moderately since 2012. Financial repression by zero fed funds rates or negative interest rates intends to increase debt and reduce savings. Business had not been as exuberant in acquiring debt and has been increasing debt benefitting from historically low costs while increasing cash holdings to around $2 trillion by swelling undistributed profits because of the uncertainty of capital budgeting. The key to growth and hiring consists in creating the incentives for business to invest and hire. States and local government were forced into increasing debt by the decline in revenues but began to contract in IQ2011, decreasing again from IQ2011 to IVQ2011, increasing at 2.1 percent in IIQ2012 and decreasing at 0.2 percent in IIIQ2012 and 2.6 percent in IVQ2012. State and local government increased debt at 1.9 percent in IQ2013 and decreased at 1.1 percent in IIQ2013. State and local government decreased debt at 3.0 percent in IIIQ2013 and at 2.8 percent in IVQ2013. State and local government reduced debt at 1.7 percent in IQ2014 and decreased at 0.4 percent in IIQ2014. State and local government reduced debt at 2.7 percent in IIIQ2014 and increased at 0.7 percent in IVQ2014. State and local government increased debt at 1.6 percent in IQ2015 and increased at 0.2 percent in IIIQ2015. State and local government decreased debt at 0.9 percent in IVQ2015. State and local government increased debt at 0.7 percent in IQ2016 and increased at 2.4 percent in IIQ2016. State and local government increased debt at 0.7 percent in IIIQ2016. Opposite behavior is for the federal government that has been rapidly accumulating debt but without success in the self-assigned goal of promoting economic growth. Financial repression constitutes seigniorage of government debt (http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-financial.html http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-monetary.html).

Table IIA-6, US, Percentage Change of Nonfinancial Domestic Sector Debt

	Total	Households	Business	Federal	State & Local Govern-ment
IIIQ2020	5.0	5.6	-0.9	9.1	5.6
IIQ2020	25.4	0.8	14.2	58.9	3.5
IQ2020	10.7	3.8	18.6	11.4	0.9
IVQ2019	3.3	3.4	1.9	4.5	2.9
IIIQ2019	5.8	3.3	5.7	8.9	0.9
IIQ2019	3.5	4.1	4.4	3.1	-1.8
IQ2019	5.9	2.2	6.8	9.6	-0.7
IVQ2018	3.5	2.8	4.6	4.1	-2.7
IIIQ2018	3.9	3.6	4.6	4.4	-1.2
IIQ2018	4.3	3.5	3.3	6.7	0.2
IQ2018	6.7	3.1	3.9	14.3	-3.2
IVQ2017	3.8	5.1	4.8	1.8	4.0
IIIQ2017	4.5	2.6	6.1	6.0	-0.6
IIQ2017	4.6	4.2	6.4	4.4	-1.0
IQ2017	3.3	3.8	6.0	1.7	-2.2
IVQ2016	2.0	2.6	1.8	2.1	-0.3
IIIQ2016	5.2	4.4	6.0	6.1	0.7
IIQ2016	4.5	3.7	4.2	6.0	2.4
IQ2016	5.5	2.4	9.2	6.2	0.7
IVQ2015	8.0	4.1	5.9	15.6	-0.9
IIIQ2015	2.1	1.3	5.3	0.6	0.3
IIQ2015	4.7	3.8	8.2	3.4	0.2
IQ2015	3.0	2.2	7.5	-0.3	1.6
IVQ2014	3.7	2.3	6.4	3.1	0.7
2019	4.7	3.3	4.8	6.7	0.3
2018	4.7	3.4	4.2	7.6	-1.6
2017	4.3	3.9	6.3	3.7	0.0
2016	4.4	3.1	5.4	5.6	1.0
2015	4.4	2.2	7.1	5.0	0.4
2014	3.8	1.2	6.7	5.4	-2.5
2013	4.1	2.3	4.7	6.7	-0.3
2012	4.6	0.6	5.4	10.1	-0.3
2011	3.7	0.1	2.5	10.8	-1.0
2010	4.5	-0.4	-0.7	18.5	3.0
2009	3.7	0.5	-3.9	20.4	4.7
2008	5.7	0.0	5.7	21.4	1.4
2007	8.1	7.1	12.5	4.7	6.2
2006	8.4	10.5	9.8	3.9	4.4

Note: Quarterly data for IQ2016 and earlier and annual data for 2007 and earlier are from prior reports.

Net Worth = Assets – Liabilities. R∆% real percentage change or adjusted for CPI percentage change.

Notes: Deposits: Total Time and Savings Deposits FL15303005; Net Worth = Assets – Liabilities

Table IIA-7 provides wealth of US households and nonprofit organizations since 2005 in billions of current dollars at the end of period, NSA. Wealth fell from $70,659 billion in 2007 to $62,772 billion in 2009 or 11.2 percent and to $67,700 billion in 2011 or 4.2 percent. Wealth increased 74.8 percent from 2007 to IIIQ2020, increasing 41.1 percent after adjustment for inflation, primarily because of bloating financial assets while nonfinancial assets declined/stagnated cyclically in real terms. Net worth of households and nonprofit organizations fell 3.4 percent from 109,311.4 billion in IIIQ2018 to 105,625.8 billion in IVQ2018 or $3,685.6 billion. Financial assets decreased 4.6 percent from 87,686.0 billion in IIIQ2018 to 83,683.8 billion in IVQ2018 or $4002.2 billion. Corporate equities fell 13.9 percent from $19,231.8 billion in IIIQ2018 to $16,558.9 billion in IVQ2018 or $2,672.9 billion. These are the revised data in the report of Dec 10, 2020, for IIQ20120. Net worth increased 4.4 percent, the all items CPI increased 1.3 percent from 256.974 in IVQ2019 to 250.280 in IIIQ2020 and real net worth increased 3.1 percent. Net worth decreased by $6,885.9 billion from IVQ2019 to IQ2020 or by 5.8 percent in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. Net worth increased $8,293.9 billion from IQ2020 to IIQ2020 or 7.4 percent. Net worth increased 1.2 percent from IVQ2019 to IIQ2020. Net worth increased $5,2253.3 billion from IVQ2019 to IIIQ2020 or 4.4 percent. Real estate increased $1,340.7 billion from IVQ2019 to IIIQ2020 or 4.0 percent. Financial assets increased $3,932.8 billion from IVQ2019 to IIIQ2020 or 4.1 percent. Stock markets recovered in Apr to Dec 2020. Corporate equities increased $1,089.7 billion from IVQ2019 to IIIQ2020 or 5.1 percent.

Table IIA-7, US, Net Worth of Households and Nonprofit Organizations, Billions of Dollars, Amounts Outstanding at End of Period, NSA

Quarter	Net Worth
IIIQ2020	123,520
IIQ2020	119,702
IQ2020	111,408
IVQ2019	118,294
IIIQ2019	114,752
IIQ2019	113,713
IQ2019	111,613
IVQ2018	105,626
IIIQ2018	109,311
IIQ2018	107,349
IQ2018	105,741
IVQ2017	105,039
IIIQ2017	102,325
IIQ2017	100,366
IQ2017	98,628
IVQ2016	96,111
IIIQ2016	95,336
IIQ2016	93,472
IQ2016	92,016
IVQ2015	90,812
IIIQ2015	89,217
IIQ2015	90,172
IQ2015	89,619
IVQ2014	87,723
IIIQ2014	85,828
IIQ2014	85,218
IQ2014	83,332
IVQ2013	81,638
IIIQ2013	79,548
IIQ2013	76,993
IQ2013	75,809
IVQ2012	72,869
2019	118,294
2018	105,626
2017	105,039
2016	96,111
2015	90,812
2014	87,723
2013	81,638
2012	72,869
2011	67,700
2010	66,440
2009	62,772
2008	61,650
2007	70,659
2006	69,116
2005	64,551

Net Worth = Assets – Liabilities. R∆% real percentage change or adjusted for CPI percentage change.

Notes: Deposits: Total Time and Savings Deposits FL15303005; Net Worth = Assets – Liabilities

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