Saturday, June 23, 2018

World Inflation Waves, United States Industrial Production, 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, United States Current Account, Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates, 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 Financial Turbulence, World Cyclical Slow Growth and Global Recession Risk: Part II

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World Inflation Waves, United States Industrial Production, 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, United States Current Account, Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates, 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 Financial Turbulence, World Cyclical Slow Growth and Global Recession Risk

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018

I World Inflation Waves

IA Appendix: Transmission of Unconventional Monetary Policy

IB1 Theory

IB2 Policy

IB3 Evidence

IB4 Unwinding Strategy

IC United States Inflation

IC Long-term US Inflation

ID Current US Inflation

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

II United States Industrial Production

IIB 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

IIC United States Current Account

IID Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates

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

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

I United States Industrial Production. There is socio-economic stress in the combination of adverse events and cyclical performance:

and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/exchange-rate-conflicts-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/imf-view-squeeze-of-economic-activity.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html)

Industrial production decreased 0.1 percent in May 2018 and increased 0.9 percent in Apr 2018 after increasing 0.5 percent in Mar 2018, with all data seasonally adjusted, as shown in Table I-1. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 23, 2018 (https://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] On net, the revisions to total IP for recent years were negative: For the 2015–17 period, the current estimates show rates of change that are 0.4 to 0.7 percentage point lower in each year.[2] Total IP is still reported to have moved up about 22 1/2 percent from the end of the recession in mid-2009 through late 2014. Subsequently, the index declined in 2015, edged down in 2016, and increased in 2017. The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2016 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

Revisions to capacity for total industry were mixed. Capacity growth was revised up about 1/2 percentage point for 2016, but revisions to other recent years were negative. Capacity for total industry is estimated to have expanded less than 1 percent in 2015, 2016, and 2017, but it is expected to increase about 2 percent in 2018.

In the fourth quarter of 2017, capacity utilization for total industry stood at 77.0 percent, about 1/2 percentage point below its previous estimate and about 3 percentage points below its long-run (1972–2017) average. The utilization rate for 2016 is also lower than the previous estimate.”

The report of the Board of Governors of the Federal Reserve System states (https://www.federalreserve.gov/releases/g17/Current/default.htm):

“Industrial production edged down 0.1 percent in May after rising 0.9 percent in April. Manufacturing production fell 0.7 percent in May, largely because truck assemblies were disrupted by a major fire at a parts supplier. Excluding motor vehicles and parts, factory output moved down 0.2 percent. The index for mining rose 1.8 percent, its fourth consecutive month of growth; the output of utilities moved up 1.1 percent. At 107.3 percent of its 2012 average, total industrial production was 3.5 percent higher in May than it was a year earlier. Capacity utilization for the industrial sector decreased 0.2 percentage point in May to 77.9 percent, a rate that is 1.9 percentage points below its long-run (1972–2017) average.” In the six months ending in May 2018, United States national industrial production accumulated change of 1.9 percent at the annual equivalent rate of 3.9 percent, which is higher than growth of 3.5 percent in the 12 months ending in May 2018. Excluding growth of 0.9 percent in Apr 2018, growth in the remaining five months from Dec to May 2018 accumulated to 1.0 percent or 2.4 percent annual equivalent. Industrial production increased 0.9 percent in one of the past six months, increased 0.5 percent in two months and increased 0.4 percent in one month, decreasing 0.3 percent in one month and decreasing 0.1 percent in one month. Industrial production increased at annual equivalent 5.3 percent in the most recent quarter from Mar 2018 to May 2018 and increased at 2.4 percent in the prior quarter Dec 2017 to Feb 2018. Business equipment accumulated change of minus 0.1 percent in the six months from Dec 2017 to May 2018, at the annual equivalent rate of minus 0.2 percent, which is lower than growth of 1.0 percent in the 12 months ending in May 2018. The Fed analyzes capacity utilization of total industry in its report (https://www.federalreserve.gov/releases/g17/Current/default.htm): “Capacity utilization for the industrial sector decreased 0.2 percentage point in May to 77.9 percent, a rate that is 1.9 percentage points below its long-run (1972–2017) average.” United States industry apparently decelerated to a lower growth rate followed by possible acceleration and weakening growth in past months. There could be renewed growth.

Table I-1, US, Industrial Production and Capacity Utilization, SA, ∆% 

May 18

Apr 18

Mar 18

Feb 18

Jan 18

Dec 17

May 18/

May 17

Total

-0.1

0.9

0.5

0.4

-0.3

0.5

3.5

Market
Groups

Final Products

-0.9

1.1

0.4

0.0

0.2

0.3

1.6

Consumer Goods

-1.0

1.0

0.4

-0.3

0.3

0.6

1.5

Business Equipment

-1.1

1.1

0.1

0.1

0.0

-0.3

1.0

Non
Industrial Supplies

0.1

0.5

0.0

0.7

-0.8

0.6

2.2

Construction

0.1

0.5

-1.0

3.1

-1.5

0.9

3.6

Materials

0.5

0.9

0.8

0.7

-0.7

0.5

5.5

Industry Groups

Manufacturing

-0.7

0.6

-0.1

1.4

-0.5

0.0

1.7

Mining

1.8

1.0

1.4

2.9

-1.0

1.1

12.6

Utilities

1.1

3.2

4.1

-9.6

2.1

3.2

4.0

Capacity

77.9

78.1

77.5

77.2

77.0

77.3

1.3

Sources: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Manufacturing decreased 0.7 percent in May 2018 and increased 0.6 percent in Apr 2018 after decreasing 0.1 percent in Mar 2018, seasonally adjusted, increasing 1.7 percent not seasonally adjusted in the 12 months ending in May 2018, as shown in Table I-2. Manufacturing increased cumulatively 0.7 percent in the six months ending in May 2018 or at the annual equivalent rate of 1.4 percent. Excluding the increase of 1.4 percent in Feb 2018, manufacturing changed minus 0.7 percent from Dec 2017 to May 2018 or at the annual equivalent rate of minus 1.7 percent. Table I-2 provides a longer perspective of manufacturing in the US. There has been evident deceleration of manufacturing growth in the US from 2010 and the first three months of 2011 with recovery followed by renewed deterioration/improvement in more recent months as shown by 12 months’ rates of growth. Growth rates appeared to be increasing again closer to 5 percent in Apr-Jun 2012 but deteriorated. The rates of decline of manufacturing in 2009 are quite high with a drop of 18.6 percent in the 12 months ending in Apr 2009. Manufacturing recovered from this decline and led the recovery from the recession. Rates of growth appeared to be returning to the levels at 3 percent or higher in the annual rates before the recession, but the pace of manufacturing fell steadily with some strength at the margin. There is renewed deterioration and improvement. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 23, 2018 (https://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] On net, the revisions to total IP for recent years were negative: For the 2015–17 period, the current estimates show rates of change that are 0.4 to 0.7 percentage point lower in each year.[2] Total IP is still reported to have moved up about 22 1/2 percent from the end of the recession in mid-2009 through late 2014. Subsequently, the index declined in 2015, edged down in 2016, and increased in 2017. The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2016 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

Revisions to capacity for total industry were mixed. Capacity growth was revised up about 1/2 percentage point for 2016, but revisions to other recent years were negative. Capacity for total industry is estimated to have expanded less than 1 percent in 2015, 2016, and 2017, but it is expected to increase about 2 percent in 2018.

In the fourth quarter of 2017, capacity utilization for total industry stood at 77.0 percent, about 1/2 percentage point below its previous estimate and about 3 percentage points below its long-run (1972–2017) average. The utilization rate for 2016 is also lower than the previous estimate.”

The bottom part of Table I-2 shows manufacturing decreasing 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increasing 16.1 percent from the trough in Apr 2009 to Dec 2017. Manufacturing grew 19.1 percent from the trough in Apr 2009 to May 2018. Manufacturing in May 2018 is lower by 7.5 percent relative to the peak in Jun 2007. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 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 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://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 (http://www.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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2018/06/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from May 1919 to May 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 150.3883 in May 2018. The actual index NSA in May 2018 is 103.9274, which is 30.9 percent below trend. Manufacturing output grew at average 1.9 percent between Dec 1986 and May 2018. Using trend growth of 1.9 percent per year, the index would increase to 131.7847 in May 2018. The output of manufacturing at 103.9274 in May 2018 is 21.1 percent below trend under this alternative calculation.

Table I-2, US, Monthly and 12-Month Rates of Growth of Manufacturing ∆%

Month SA ∆%

12-Month NSA ∆%

May 2018

-0.7

1.7

Apr

0.6

3.2

Mar

-0.1

2.3

Feb

1.4

2.1

Jan

-0.5

0.9

Dec 2017

0.0

1.8

Nov

0.2

2.1

Oct

1.3

1.8

Sep

-0.1

0.7

Aug

-0.2

1.2

Jul

-0.3

1.4

Jun

0.1

1.5

May

-0.4

1.8

Apr

1.1

0.4

Mar

-0.5

1.1

Feb

0.1

0.7

Jan

0.3

0.1

Dec 2016

0.3

0.4

Nov

0.0

-0.2

Oct

0.2

-0.3

Sep

0.3

-0.2

Aug

-0.3

-1.5

Jul

0.2

-1.4

Jun

0.3

-0.8

May

-0.1

-1.5

Apr

-0.3

-0.8

Mar

-0.2

-1.8

Feb

-0.4

-0.6

Jan

0.5

-0.7

Dec 2015

-0.2

-1.9

Nov

-0.2

-1.7

Oct

0.0

-0.8

Sep

-0.4

-1.7

Aug

-0.3

-0.7

Jul

0.6

-0.4

Jun

-0.4

-1.1

May

-0.1

-0.3

Apr

-0.1

-0.1

Mar

0.3

-0.1

Feb

-0.6

0.5

Jan

-0.5

1.9

Dec 2014

-0.3

1.5

Nov

0.8

1.7

Oct

-0.1

0.9

Sep

0.0

1.1

Aug

-0.4

1.3

Jul

0.3

2.0

Jun

0.3

1.4

May

0.2

1.3

Apr

-0.1

0.9

Mar

0.8

1.6

Feb

1.1

0.3

Jan

-1.2

-0.5

Dec 2013

0.0

0.1

Nov

0.0

1.2

Oct

0.1

1.9

Sep

0.1

1.2

Aug

1.0

1.3

Jul

-1.0

0.3

Jun

0.2

0.8

May

0.3

0.9

Apr

-0.4

1.0

Mar

-0.1

0.6

Feb

0.5

0.7

Jan

-0.3

0.8

Dec 2012

0.8

1.7

Nov

0.7

1.7

Oct

-0.4

0.7

Sep

-0.1

1.6

Aug

-0.2

2.1

Jul

-0.1

2.5

Jun

0.2

3.4

May

-0.4

3.4

Apr

0.6

3.8

Mar

-0.5

2.8

Feb

0.4

4.1

Jan

0.8

3.5

Dec 2011

0.7

3.1

Nov

-0.3

2.7

Oct

0.6

2.8

Sep

0.3

2.6

Aug

0.4

2.1

Jul

0.6

2.3

Jun

0.1

1.7

May

0.1

1.5

Apr

-0.6

2.7

Mar

0.6

4.2

Feb

0.1

4.8

Jan

0.2

4.8

Dec 2010

0.5

5.4

Nov

0.0

4.5

Oct

0.1

5.8

Sep

0.0

6.1

Aug

0.1

6.8

Jul

0.6

7.4

Jun

-0.1

9.2

May

1.4

8.9

Apr

0.8

7.3

Mar

1.2

5.2

Feb

-0.1

1.7

Jan

1.1

1.7

Dec 2009

-0.2

-2.9

Nov

1.0

-5.8

Oct

0.2

-8.9

Sep

0.9

-10.4

Aug

1.1

-13.5

Jul

1.5

-15.3

Jun

-0.3

-17.9

May

-1.0

-17.9

Apr

-0.7

-18.6

Mar

-1.8

-17.8

Feb

-0.2

-16.7

Jan

-3.1

-17.0

Dec 2008

-3.5

-14.5

Nov

-2.4

-11.7

Oct

-0.6

-9.2

Sep

-3.4

-8.8

Aug

-1.2

-5.2

Jul

-1.2

-3.7

Jun

-0.7

-3.2

May

-0.6

-2.4

Apr

-1.1

-1.0

Mar

-0.3

-0.5

Feb

-0.6

1.1

Jan

-0.4

2.5

Dec 2007

0.2

2.1

Nov

0.5

3.5

Oct

-0.3

2.9

Sep

0.5

3.0

Aug

-0.3

2.7

Jul

0.1

3.6

Jun

0.3

3.1

May

-0.1

3.2

Apr

0.7

3.6

Mar

0.8

2.6

Feb

0.4

1.6

Jan

-0.5

1.2

Dec 2006

2.7

Dec 2005

3.6

Dec 2004

4.1

Dec 2003

2.2

Dec 2002

2.4

Dec 2001

-5.3

Dec 2000

0.8

Dec 1999

5.2

Average ∆% Dec 1986-Dec 2017

2.0

Average ∆% Dec 1986-Dec 2016

2.0

Average ∆% Dec 1986-Dec 2015

2.0

Average ∆% Dec 1986-Dec 2014

2.2

Average ∆% Dec 1986-Dec 2013

2.2

Average ∆% Dec 1986-Dec 1999

4.3

Average ∆% Dec 1999-Dec 2006

1.5

Average ∆% Dec 1999-Dec 2017

0.3

∆% Peak 112.3300 in 06/2007 to 101.3446 in 12/2017

-9.8

∆% Peak 112.3300 in 06/2007 to Trough 87.2739 in 4/2009

-22.3

∆% Trough 87.2739 in 04/2009 to 101.3446 in 12/2017

16.1

∆% Trough 87.2739 in 04/2009 to 103.9274 in 05/2018

19.1

∆% Peak 112.3300 in 06/2007 to 103.9274 in 05/2018

-7.5

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Chart I-1 of the Board of Governors of the Federal Reserve System provides industrial production, manufacturing and capacity since the 1970s. There was acceleration of growth of industrial production, manufacturing and capacity in the 1990s because of rapid growth of productivity in the US (Cobet and Wilson (2002); see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). The slopes of the curves flatten in the 2000s. Production and capacity have not recovered sufficiently above levels before the global recession, remaining like GDP below historical trend. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Apr 1919 to Apr 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 154.7937 in Apr 2018. The actual index NSA in Apr 2018 is 104.3625, which is 32.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Apr 2018. Using trend growth of 2.0 percent per year, the index would increase to 135.5768 in Apr 2018. The output of manufacturing at 104.3625 in Apr 2018 is 23.0 percent below trend under this alternative calculation.

Chart I-1, US, Industrial Production, Capacity and Utilization

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/ipg1.gif

The modern industrial revolution of Jensen (1993) is captured in Chart I-2 of the Board of Governors of the Federal Reserve System (for the literature on M&A and corporate control see Pelaez and Pelaez, Regulation of Banks and Finance (2009a), 143-56, Globalization and the State, Vol. I (2008a), 49-59, Government Intervention in Globalization (2008c), 46-49). The slope of the curve of total industrial production accelerates in the 1990s to a much higher rate of growth than the curve excluding high-technology industries. Growth rates decelerate into the 2000s and output and capacity utilization have not recovered fully from the strong impact of the global recession. Growth in the current cyclical expansion has been more subdued than in the prior comparably deep contractions in the 1970s and 1980s. Chart I-2 shows that the past recessions after World War II are the relevant ones for comparison with the recession after 2007 instead of common comparisons with the Great Depression (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The bottom left-hand part of Chart II-2 shows the strong growth of output of communication equipment, computers and semiconductor that continued from the 1990s into the 2000s. Output of semiconductors has already surpassed the level before the global recession.

Chart I-2, US, Industrial Production, Capacity and Utilization of High Technology Industries

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/ipg3.gif

Additional detail on industrial production and capacity utilization is in Chart I-3 of the Board of Governors of the Federal Reserve System. Production of consumer durable goods fell sharply during the global recession by more than 30 percent and is oscillating above the level before the contraction. Output of nondurable consumer goods fell around 10 percent and is some 5 percent below the level before the contraction. Output of business equipment fell sharply during the contraction of 2001 but began rapid growth again after 2004. An important characteristic is rapid growth of output of business equipment in the cyclical expansion after sharp contraction in the global recession, stalling in the final segment. Output of defense and space only suffered reduction in the rate of growth during the global recession and surged ahead of the level before the contraction, declining in the final segment. Output of construction supplies collapsed during the global recession and is well below the level before the contraction. Output of energy materials was stagnant before the contraction but recovered sharply above the level before the contraction with alternating recent decline/improvement.

Chart I-3, US, Industrial Production and Capacity Utilization

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/ipg2.gif

United States manufacturing output from 1919 to 2018 monthly is in Chart I-4 of the Board of Governors of the Federal Reserve System. The second industrial revolution of Jensen (1993) is quite evident in the acceleration of the rate of growth of output given by the sharper slope in the 1980s and 1990s. Growth was robust after the shallow recession of 2001 but dropped sharply during the global recession after IVQ2007. Manufacturing output recovered sharply but has not reached earlier levels and is losing momentum at the margin. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from May 1919 to May 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 150.3883 in May 2018. The actual index NSA in May 2018 is 103.9274, which is 30.9 percent below trend. Manufacturing output grew at average 1.9 percent between Dec 1986 and May 2018. Using trend growth of 1.9 percent per year, the index would increase to 131.7847 in May 2018. The output of manufacturing at 103.9274 in May 2018 is 21.1 percent below trend under this alternative calculation.

Chart I-4, US, Manufacturing Output, 1919-2018

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Manufacturing jobs not seasonally adjusted increased 262,000 from May 2017 to
May 2018 or at the average monthly rate of 21,833. Industrial production decreased 0.1 percent in May 2018 and increased 0.9 percent in Apr 2018 after increasing 0.5 percent in Mar 2018, with all data seasonally adjusted, as shown in Table I-1. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 23, 2018 (https://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] On net, the revisions to total IP for recent years were negative: For the 2015–17 period, the current estimates show rates of change that are 0.4 to 0.7 percentage point lower in each year.[2] Total IP is still reported to have moved up about 22 1/2 percent from the end of the recession in mid-2009 through late 2014. Subsequently, the index declined in 2015, edged down in 2016, and increased in 2017. The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2016 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

Revisions to capacity for total industry were mixed. Capacity growth was revised up about 1/2 percentage point for 2016, but revisions to other recent years were negative. Capacity for total industry is estimated to have expanded less than 1 percent in 2015, 2016, and 2017, but it is expected to increase about 2 percent in 2018.

In the fourth quarter of 2017, capacity utilization for total industry stood at 77.0 percent, about 1/2 percentage point below its previous estimate and about 3 percentage points below its long-run (1972–2017) average. The utilization rate for 2016 is also lower than the previous estimate.”

Manufacturing decreasing 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increased 16.1 percent from the trough in Apr 2009 to Dec 2017. Manufacturing grew 19.1 percent from the trough in Apr 2009 to May 2018. Manufacturing in May 2018 is lower by 7.5 percent relative to the peak in Jun 2007. 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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2018/06/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from May 1919 to May 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 150.3883 in May 2018. The actual index NSA in May 2018 is 103.9274, which is 30.9 percent below trend. Manufacturing output grew at average 1.9 percent between Dec 1986 and May 2018. Using trend growth of 1.9 percent per year, the index would increase to 131.7847 in May 2018. The output of manufacturing at 103.9274 in May 2018 is 21.1 percent below trend under this alternative calculation. Table I-13 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 86.8 percent in IVQ2017. Most of US national income is in the form of services. In May 2018, there were 149.309 million nonfarm jobs NSA in the US, according to estimates of the establishment survey of the Bureau of Labor Statistics (BLS) (http://www.bls.gov/news.release/empsit.nr0.htm Table B-1). Total private jobs of 126.650 million NSA in May 2018 accounted for 84.8 percent of total nonfarm jobs of 149.309 million, of which 12.651 million, or 10.0 percent of total private jobs and 8.5 percent of total nonfarm jobs, were in manufacturing. Private service-providing jobs were 105.986 million NSA in May 2018, or 71.0 percent of total nonfarm jobs and 83.7 percent of total private-sector jobs. Manufacturing has share of 9.9 percent in US national income in IVQ2017 and durable goods 5.9 percent, as shown in Table I-13. Most income in the US originates in services. Subsidies and similar measures designed to increase manufacturing jobs will not increase economic growth and employment and may actually reduce growth by diverting resources away from currently employment-creating activities because of the drain of taxation.

Table I-13, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total

SSAR IVQ2017

% Total

SSAR IQ2018

% Total

National Income WCCA

16,402.5

100.0

16,604.5

100.0

Domestic Industries

16,180.2

98.6

16,388.3

98.7

Private Industries

14,238.3

86.8

14,435.1

86.9

Agriculture

115.1

0.7

Mining

137.5

0.8

Utilities

187.8

1.1

Construction

850.0

5.2

Manufacturing

1630.3

9.9

Durable Goods

971.3

5.9

Nondurable Goods

659.0

4.0

Wholesale Trade

907.3

5.5

Retail Trade

1132.9

6.9

Transportation & WH

487.0

3.0

Information

589.0

3.6

Finance, Insurance, RE

2936.0

17.9

Professional & Business Services

2374.8

14.5

Education, Health Care

1669.0

10.2

Arts, Entertainment

732.6

4.5

Other Services

489.0

3.0

Government

1942.0

11.8

1953.2

11.8

Rest of the World

222.3

1.4

216.2

1.3

Notes: SSAR: Seasonally-Adjusted Annual Rate; Percentages Calculates from Unrounded Data; WCCA: Without Capital Consumption Adjustment by Industry; WH: Warehousing; RE, includes rental and leasing: Real Estate; Art, Entertainment includes recreation, accommodation and food services; BS: business services

Source: US Bureau of Economic Analysis

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

Motor vehicle sales and production in the US have been in long-term structural change. Table VA-1A provides the data on new motor vehicle sales and domestic car production in the US from 1990 to 2010. New motor vehicle sales grew from 14,137 thousand in 1990 to the peak of 17,806 thousand in 2000 or 29.5 percent. In that same period, domestic car production fell from 6,231 thousand in 1990 to 5,542 thousand in 2000 or -11.1 percent. New motor vehicle sales fell from 17,445 thousand in 2005 to 11,772 in 2010 or 32.5 percent while domestic car production fell from 4,321 thousand in 2005 to 2,840 thousand in 2010 or 34.3 percent. In Mar 2018, light vehicle sales accumulated to 4,110,545, which is higher by 1.9 percent relative to 4,032,790 a year earlier (http://www.motorintelligence.com/m_frameset.html). The seasonally adjusted annual rate of light vehicle sales in the US reached 16.91 million in May 2018, lower than 17.17 million in Apr 2018 and higher than 16.79 million in May 2017. (http://www.motorintelligence.com/m_frameset.html).

Table VA-1A, US, New Motor Vehicle Sales and Car Production, Thousand Units 7

New Motor Vehicle Sales

New Car Sales and Leases

New Truck Sales and Leases

Domestic Car Production

1990

14,137

9,300

4,837

6,231

1991

12,725

8,589

4,136

5,454

1992

13,093

8,215

4,878

5,979

1993

14,172

8,518

5,654

5,979

1994

15,397

8,990

6,407

6,614

1995

15,106

8,536

6,470

6,340

1996

15,449

8,527

6,922

6,081

1997

15,490

8,273

7,218

5,934

1998

15,958

8,142

7,816

5,554

1999

17,401

8,697

8,704

5,638

2000

17,806

8,852

8,954

5,542

2001

17,468

8,422

9,046

4,878

2002

17,144

8,109

9,036

5,019

2003

16,968

7,611

9,357

4,510

2004

17,298

7,545

9,753

4,230

2005

17,445

7,720

9,725

4,321

2006

17,049

7,821

9,228

4,367

2007

16,460

7,618

8,683

3,924

2008

13,494

6,814

6.680

3,777

2009

10,601

5,456

5,154

2,247

2010

11,772

5,729

6,044

2,840

Source: US Census Bureau

http://www.census.gov/compendia/statab/cats/wholesale_retail_trade/motor_vehicle_sales.html

Chart I-5 of the Board of Governors of the Federal Reserve provides output of motor vehicles and parts in the United States from 1972 to 2018. Output virtually stagnated since the late 1990s with recent increase.

Chart 1-5, US, Motor Vehicles and Parts Output, 1972-2018

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Chart I-6 of the Board of Governors of the Federal Reserve System provides output of computers and electronic products in the United States from 1972 to 2018. Output accelerated sharply in the 1990s and 2000s and surpassed the level before the global recession beginning in IVQ2007.

Chart I-6, US, Output of Computers and Electronic Products, 1972-2018

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Chart I-7 of the Board of Governors of the Federal Reserve System shows that output of durable manufacturing accelerated in the 1980s and 1990s with slower growth in the 2000s perhaps because processes matured. Growth was robust after the major drop during the global recession but appears to vacillate in the final segment.

Chart I-7, US, Output of Durable Manufacturing, 1972-2018

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Chart I-8 of the Board of Governors of the Federal Reserve System provides output of aerospace and miscellaneous transportation equipment from 1972 to 2018. There is long-term upward trend with oscillations around the trend and cycles of large amplitude.

Chart I-8, US, Output of Aerospace and Miscellaneous Transportation Equipment, 1972-2018

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

The Empire State Manufacturing Survey Index in Table VA-1 provides continuing deterioration that started in Jun 2012 well before Hurricane Sandy in Oct 2012. The current general index has been in negative contraction territory from minus 2.3 in Aug 2012 to minus 7.5 in Jan 2013 and minus 0.4 in May 2013. The current general index changed to 25.0 in Jun 2018. The index of current orders has also been in negative contraction territory from minus 2.9 in Aug 2012 to minus 10.9 in Jan 2013 and minus 7.8 in Jun 2013. The index of current new orders changed to 21.3 in Jun 2018. There is strengthening in the general index for the next six months at 38.9 in Jun 2018 and new orders at 33.4.

Table VA-1, US, New York Federal Reserve Bank Empire State Manufacturing Survey Index SA

Current General Index

Current New Orders

Future General Index

Future New Orders

9/30/2011

-3.9

-4.2

22.4

23.4

10/31/2011

-5.3

1.9

14.4

19.5

11/30/2011

5.1

1.7

35.5

30.9

12/31/2011

11.6

10.2

46

43.8

1/31/2012

11.4

8.6

51

44.4

2/29/2012

16.5

7

46.5

38

3/31/2012

15.1

4.4

44

38

4/30/2012

7.3

3.7

40

37.7

5/31/2012

14.8

7

32.2

31.5

6/30/2012

1.5

3

27.7

27.7

7/31/2012

3.5

-3.4

24.2

21.6

8/31/2012

-2.3

-2.9

18.7

14.5

9/30/2012

-6.4

-9.9

26.9

27.8

10/31/2012

-4

-6.2

20

22.4

11/30/2012

-0.5

6.3

18.2

16.3

12/31/2012

-5.7

0.4

19.8

19.8

1/31/2013

-7.5

-10.9

21.7

23.4

2/28/2013

7.5

12

32.4

27.5

3/31/2013

4.5

4.7

35.2

33.3

4/30/2013

3.7

1.9

29.7

34.8

5/31/2013

-0.4

-3

26

29.7

6/30/2013

4.4

-7.8

27.7

21.5

7/31/2013

5.7

2.3

33.8

33.1

8/31/2013

10.3

3.1

35.8

30.8

9/30/2013

8.2

3.4

40.1

38

10/31/2013

4.4

10

41.3

37

11/30/2013

2.9

-2.1

38.4

40.7

12/31/2013

3.3

1.3

37.3

28.6

1/31/2014

12.4

8

36

37.2

2/28/2014

4.3

1.2

40.6

44.3

3/31/2014

2.4

0.8

35.4

36.8

4/30/2014

2.9

-1.7

37.6

33.6

5/31/2014

19

8.7

42.9

37.8

6/30/2014

15.6

13.1

41.1

43.3

7/31/2014

21.5

16.5

30.5

27.5

8/31/2014

16.9

15.8

45.7

50.3

9/30/2014

29.9

18

46.5

45.6

10/31/2014

7.2

2.5

42.1

42.3

11/30/2014

13

11

48.1

48.8

12/31/2014

-2.4

0.7

36.5

36.9

1/31/2015

11.9

6.3

46.8

40.4

2/28/2015

7.7

2.2

28.3

30.1

3/31/2015

3.3

-6.3

31.2

26.9

4/30/2015

-1.5

-6.8

35.8

32.9

5/31/2015

5.5

3.9

30.2

34

6/30/2015

-5

-6.8

26

25.4

7/31/2015

2.5

-5

29.2

33.6

8/31/2015

-12.6

-14

32.9

30.7

9/30/2015

-12.6

-11.3

23.3

23.8

10/31/2015

-12.1

-14.2

22.2

22.7

11/30/2015

-8.5

-10.2

23.1

22.3

12/31/2015

-6

-5.5

35.1

26.1

1/31/2016

-16.6

-22.1

10

13.4

2/29/2016

-16.9

-11.1

15.8

21.7

3/31/2016

-3.1

2.9

26

37.6

4/30/2016

7.5

8.3

28.5

35.9

5/31/2016

-5.8

-2.3

28.2

22.9

6/30/2016

2.5

6.5

33.2

35.9

7/31/2016

2.2

-1.7

31.1

31.7

8/31/2016

-4.1

1.4

25.2

28.7

9/30/2016

-1.6

-5.8

34.3

32.1

10/31/2016

-7.6

-1.2

35.2

37.8

11/30/2016

3.5

5

30.7

29.8

12/31/2016

9.3

10.7

49.4

47.7

1/31/2017

6.7

3.6

49

39.2

2/28/2017

17.1

12.3

41.3

41.6

3/31/2017

14.6

17.4

38.3

35.1

4/30/2017

4.1

7.3

39.4

32.5

5/31/2017

3

-1.9

39.8

34.3

6/30/2017

18.1

16.1

41.4

40

7/31/2017

12.7

13.4

36.6

35.7

8/31/2017

24.2

20.9

44

41.3

9/30/2017

23.8

24.4

40.8

43.6

10/31/2017

28.1

21

44.9

44.6

11/30/2017

20.9

21.3

49.8

52.5

12/31/2017

19.6

19

46.3

42.7

1/31/2018

17.7

11.9

48.6

47.6

2/28/2018

13.1

13.5

50.5

47.2

3/31/2018

22.5

16.8

44.1

43

4/30/2018

15.8

9

18.3

18.5

5/31/2018

20.1

16

31.1

33.7

6/30/2018

25

21.3

38.9

33.4

Source: Federal Reserve Bank of New York

http://www.ny.frb.org/survey/empire/empiresurvey_overview.html

Chart VA-1 of the Federal Reserve Bank of New York provides indexes of current and expected economic activity. There were multiple contractions in current activity after the global recession shown in shade. Current activity is weakening relative to strong recovery in the initial expansion in 2010 and 2011 with recent recovery.

Chart VA-1, US, US, Federal Reserve Bank of New York, Diffusion Index of Current and Expected Activity, Seasonally Adjusted

Source: Federal Reserve Bank of New York

http://www.ny.frb.org/survey/empire/empiresurvey_overview.html

Table VA-2 shows improvement after prior deterioration followed by current soft improvement of the Business Outlook survey of the Federal Reserve Bank of Philadelphia. The general index moved out of contraction of 6.2 in Feb 2013 to expansion at 19.9 in Jun 2018. New orders moved from minus 1.1 in Feb 2013 to 17.9 in Jun 2018. There is expansion in the future general index at 34.8 in Jun 2018 and in future new orders at 38.2 in Jun 2018.

Table VA-2, US, Federal Reserve Bank of Philadelphia Business Outlook Survey, SA

Current General Index

Current New Orders

Future General Index

Future New orders

Jan-11

16.5

20.8

43.4

36.1

Feb-11

28.7

20.8

41.9

38.8

Mar-11

36.4

34.5

57

55.5

Apr-11

12.9

14.2

35.7

30.8

May-11

6.1

8.1

26.2

25.2

Jun-11

-0.4

-4.9

8.5

8.4

Jul-11

7.1

3.6

28.7

32.1

Aug-11

-19.6

-17.9

12.7

26.7

Sep-11

-10.6

-6.5

18.3

19.6

Oct-11

6.2

5.5

26.3

28.7

Nov-11

4.1

1

36.5

36.2

Dec-11

2.5

4.8

33.8

38.6

Jan-12

7.5

11

42.9

43.8

Feb-12

10

11.7

30.3

32.2

Mar-12

8.8

0.8

30.5

37.1

Apr-12

5.6

1.2

39.9

42.3

May-12

-0.8

2.1

24.9

35.4

Jun-12

-12.5

-17.4

25.4

33.9

Jul-12

-12.6

-3.7

21.6

25.5

Aug-12

-2.5

0.6

20.2

25.6

Sep-12

0.3

0.1

31.8

42.8

Oct-12

-1.1

-4.1

17.3

20.8

Nov-12

-10.4

-7.8

16.9

23.1

Dec-12

2.5

2.9

22.7

29

Jan-13

-1.4

-2.3

27.4

31.9

Feb-13

-6.2

-1.1

32.1

39.1

Mar-13

2

2

35.7

38.1

Apr-13

0.5

1.1

30.8

34.2

May-13

0.3

-3.7

39.4

42.1

Jun-13

12.8

11.8

37.1

39.5

Jul-13

16

8

41.7

52.1

Aug-13

8.2

7.9

38.7

38.9

Sep-13

20.8

19.1

49.1

51.6

Oct-13

13.5

23.6

55.7

61.1

Nov-13

4.9

8.8

42.4

47.3

Dec-13

3.9

11.9

41.6

44.8

Jan-14

15.4

7.2

35.6

40.3

Feb-14

0.5

1.9

44.1

39.6

Mar-14

12.6

9.4

42.9

39

Apr-14

17.1

17.4

39.5

38.2

May-14

18.5

14.9

43.5

42.3

Jun-14

14.3

10.3

52.8

54.3

Jul-14

21.7

30.2

53.8

48.2

Aug-14

23

14.6

62.2

51.4

Sep-14

22.1

14.1

46.7

44.7

Oct-14

18.2

17.4

51.2

49.3

Nov-14

36

29.5

50.8

46.6

Dec-14

21.6

13.5

48.1

44.7

Jan-15

13.1

9

51.2

46

Feb-15

7.9

4.9

35.3

46.4

Mar-15

7.6

5.6

38.6

38.4

Apr-15

10

4.1

39.9

32.8

May-15

6.5

5.3

37.3

34.4

Jun-15

8

10.4

42.1

45.8

Jul-15

4.9

5.1

40.5

43.8

Aug-15

6.4

5.2

35.2

39.5

Sep-15

-2.9

11.3

38

41.5

Oct-15

-4.3

-6.1

35.1

37.4

Nov-15

-3.3

-7.9

38.3

47.9

Dec-15

-9.5

-10.6

20.2

31.7

Jan-16

-4.5

-4

14.6

19.8

Feb-16

-10.3

-9.4

16.5

20.3

Mar-16

9.3

11.6

28.2

36

Apr-16

-1.2

-1.8

39.7

42

May-16

-4.2

-2.3

38.1

38.6

Jun-16

3.7

-2.3

34.3

35.3

Jul-16

2.3

14.1

36.8

33.2

Aug-16

6.2

-3.6

42.7

43.4

Sep-16

13.6

4.6

38.3

37.8

Oct-16

11.7

20.4

36.7

42.2

Nov-16

10

18.1

30.7

40.3

Dec-16

21.6

13.8

47.9

48

Jan-17

24.1

24.6

51

50.2

Feb-17

35.3

31.2

51.1

49.3

Mar-17

31.6

37.4

57.6

58.8

Apr-17

22.8

25.9

45.2

52.9

May-17

35.5

24.7

37.9

47

Jun-17

26.9

24.8

35.3

36.9

Jul-17

23.2

10.6

39.9

42.4

Aug-17

22.1

20.7

44

51.1

Sep-17

25.8

28.9

55

57.7

Oct-17

28.8

23.3

47.2

46.9

Nov-17

24.3

24.2

48.7

55.5

Dec-17

27.9

28.2

52.7

59

Jan-18

22.2

10.1

42.2

46.2

Feb-18

25.8

24.5

41.2

49.1

Mar-18

22.3

35.7

47.9

48.8

Apr-18

23.2

18.4

40.7

37.2

May-18

34.4

40.6

38.7

40.3

Jun-18

19.9

17.9

34.8

38.2

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart VA-2 of the Federal Reserve Bank of Philadelphia Manufacturing Business Outlook Survey provides the current and future general activity indexes from Jan 2006 to May 2018. The shaded areas are the recession cycle dates of the National Bureau of Economic Research (NBER) (http://www.nber.org/cycles.html). The Philadelphia Fed index dropped during the initial period of recession and then led the recovery, as industry overall. There was a second decline of the index into 2011 followed now by what appeared as renewed strength from late 2011 into Jan 2012. There is decline to negative territory of the current activity index in Nov 2012 and return to positive territory in Dec 2012 with decline of current conditions into contraction in Jan-Feb 2013 and rebound to mild expansion in Mar-Apr 2013. The index of current activity moved into expansion in Jun-Oct 2013 with weakness in Nov-Dec 2013, improving in Jan 2014. There is renewed deterioration in Feb 2014 with rebound in Apr-Sep 2014 and mild deterioration in Oct 2014 followed by improvement in Nov 2014. The index deteriorated in Jan-Feb 2015, stabilizing in Mar-May 2015 and improving in Jun 2015. The index deteriorated in Jul 2015, improved in Aug 2015 and deteriorated in Sep-Oct 2015. The index shows contraction in Nov 2015 to Feb 2016 with recovery in Mar 2016. There is deterioration in Apr-May 2016 with improvement in Jun 2016 and deterioration in Jul 2016. There is improvement in Aug-Sep 2016 with moderate weakening in Oct-Nov 2016. The indexes improved sharply in Dec 2016 and Jan-Feb 2017, softening in Mar-Apr 2017. The current index weakened in Jun 2017 with stability in the six-month forecast. The current index deteriorated in Jul 2017 with improvement in the six-month forecast. The current index deteriorated in Aug 2017 with improvement in the six-month forecast. The current index improved in Sep 2017 with improvement in the six-month forecast. The current index improved and the future index deteriorated in Oct 2017. There is deterioration in Nov 2017 of the current index and improvement of the future index. Both the current and future indexes improved in Dec 2017, deteriorating in Jan 2018. There is improvement of the current index in Feb 2018 with mild deterioration in the future index. The current index improves in Apr 2018 while the future index weakens. There is improvement in the current index in May 2018 with weakening of the future index. There is weakening in the current index in Jun 2018 while the future index weakens.

Chart VA-2, Federal Reserve Bank of Philadelphia Business Outlook Survey, Current and Future Activity Indexes

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

The index of current new orders of the Business Outlook Survey of the Federal Reserve Bank of Philadelphia in Chart VA-2 illustrates the weakness of the cyclical expansion. The index weakened in 2006 and 2007 and then fell sharply into contraction during the global recession. There have been twelve readings into contraction from Jan 2012 to May 2013 and generally weak readings with some exceptions. The index of new orders moved into expansion in Jun-Oct 2013 with moderation in Nov-Dec 2013 and into Jan 2014. The index fell into contraction in Feb 2014, recovering in Mar-Apr 2014 but weaker reading in May 2014. There is marked improvement in Jun-Jul 2014 with slowing in Aug-Oct 2014 followed by acceleration in Nov 2014. New orders deteriorated in Jan-Apr 2015, improving in May-Jun 2015. New orders deteriorated in Jul-Aug 2015 and improved in Sep 2015. New orders deteriorated in Oct-2015 to Dec 2015, contracting at slower pace in Jan 2016. There is sharper contraction in Feb 2016 and an upward jump in Mar 2016 followed by deterioration in Apr-Jun 2016. New orders improved in Jul 2016, deteriorating in Aug 2016 and improving in Sep 2016. Improvement continued in Oct-Nov 2016 with mild deterioration in Dec 2016 followed by improvement in Jan-Feb 2017, softening in Mar-Jul 2017, recovering in Aug-Sep 2017. There is deterioration in Oct 2017 followed by improvement in Nov-Dec 2017. There is deterioration in Jan 2018 followed by improvement in Feb 2018 and improvement in Mar 2018. The index deteriorates in Apr 2018, improving in May 2018. The index deteriorates in Jun 2018.

Chart VA-3, Federal Reserve Bank of Philadelphia Business Outlook Survey, Current New Orders Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

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 (http://www.federalreserve.gov/releases/z1/Current/ http://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, 2016, 2017 and IQ2018. Assets increased to $106.9 trillion in 2016 by $26.0 trillion relative to 2007 or 32.1 percent. Assets increased to $115.3 trillion in 2017 by $34.3 trillion relative to 2007 or 42.4 percent. Assets increased to $116.3 billion in IQ2018 by $35.4 billion relative to 2007 or 43.8 percent. Liabilities increased from $14.5 trillion in 2007 to $15.0 trillion in 2016, by $463.4 billion or increase of 3.2 percent. Liabilities increased from $14.5 trillion in 2007 to $15.5 trillion in 2017, by $1015.2 billion or increase of 7.0 percent. Liabilities increased $1058.7 billion or 7.3 percent from 2007 to IQ2018. Net worth increased from $66,415.0 billion in 2007 to $100,768.3 billion in IQ2018 by $34,353.3 billion or 51.7 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 249.554 in Mar 2018 (http://www.bls.gov/cpi/data.htm) or 18.8 percent. Net worth adjusted by CPI inflation increased 27.7 percent from 2007 to IQ2018. Nonfinancial assets increased $6,529.4 billion from $28,068.0 billion in 2007 to $34,597.4 billion in IQ2018 or 23.3 percent. There was increase from 2007 to IQ2018 of $5,115.8 billion in real estate assets or by 22.0 percent. Real estate assets adjusted for CPI inflation increased 2.7 percent between 2007 and IQ2018. 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).

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

2007

2016

2017

IQ2018

Assets

80,930.4

106,934.3

115,270.7

116,342.5

Nonfinancial

28,068.0

32,041.9

34,036.1

34,597.4

  Real Estate

23,258.6

26,172.2

27,884.8

28,374.4

  Durable Goods

  4,476.0

5,388.1

5,650.8

5,717.5

Financial

52,862.4

74,892.4

81,234.6

81,754.2

  Deposits

  5,918.2

9,085.7

9,283.5

9,429.5

  Debt Secs.

  3,903.4

4,591.9

4,320.3

4,849.0

  Mutual Fund Shares

   4,343.0

7,240.3

8,628.6

8,676.8

  Equities Corporate

   10,075.3

15,221.4

17,949.5

17,626.5

  Equity Noncorporate

   8,796.1

11,139.4

11,821.6

11,925.2

  Pension

15,095.0

21,836.5

23,292.6

23,315.7

Liabilities

14,515.5

14,978.9

15,530.7

15,574.2

  Home Mortgages

10,638.0

9,777.9

10,076.2

10,110.5

  Consumer Credit

   2,609.5

3,644.2

3,832.7

3,822.4

Net Worth

66,415.0

91,955.4

99,740.0

100,768.3

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

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. 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-1 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 94.8 percent in the 10-city composite of the Case-Shiller home price index, 77.8 percent in the 20-city composite and 62.2 percent in the US national home price index between Mar 2000 and Mar 2005. Prices rose around 100 percent from Mar 2000 to Mar 2006, increasing 1218.8 percent for the 10-city composite, 99.8 percent for the 20-city composite and 80.1 percent in the US national index. House prices rose 37.5 percent between Mar 2003 and Mar 2005 for the 10-city composite, 32.1 percent for the 20-city composite and 27.3 percent for the US national propelled by low fed funds rates of 1.0 percent between Mar 2003 and Jun 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 decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Mar 2003 and Mar 2006, the 10-city index gained 54.5 percent; the 20-city index increased 48.4 percent; and the US national 41.3 percent. House prices have fallen from Mar 2006 to Mar 2018 by 0.5 percent for the 10-city composite, increasing 2.4 percent for the 20-city composite and increasing 8.9 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 Mar 2018, house prices increased 6.5 percent in the 10-city composite, increasing 6.8 percent in the 20-city composite and 6.5 percent in the US national. Table IIA-1 also shows that house prices increased 117.6 percent between Mar 2000 and Mar 2018 for the 10-city composite, increasing 104.6 percent for the 20-city composite and 96.1 percent 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 10-city composite fell 1.7 percent from the peak in Jun 2006 to Mar 2018 and the 20-city composite increased 1.0 percent from the peak in Jul 2006 to Mar 2018. The US national increased 7.8 percent in Mar 2018 from the peak of the 10-city composite in Jun 2006 and increased 7.8 percent from the peak of the 20-city composite in Jul 2016. 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 annual growth rate between Dec 1987 and Dec 2017 for the 10-city composite was 3.9 percent and 3.6 percent for the US national. Data for the 20-city composite are available only beginning in Mar 2000. House prices accelerated in the 1990s with the average rate of the 10-city composite of 5.0 percent between Dec 1992 and Dec 2000 while the average rate for the period Dec 1987 to Dec 2000 was 3.8 percent. The average rate for the US national was 3.6 percent from Dec 1987 to Dec 2017 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 of the 10-city composite between Dec 2000 and Dec 2017 was 3.9 percent while the rate of the 20-city composite was 3.6 percent and 3.5 percent for the US national.

Table IIA-1, US, Percentage Changes of Standard & Poor’s Case-Shiller Home Price Indices, Not Seasonally Adjusted, ∆%

10-City Composite

20-City Composite

US National

∆% Mar 2000 to Mar 2003

41.7

34.6

27.4

∆% Mar 2000 to Mar 2005

94.8

77.8

62.2

∆% Mar 2003 to Mar 2005

37.5

32.1

27.3

∆% Mar 2000 to Mar 2006

118.8

99.8

80.1

∆% Mar 2003 to Mar 2006

54.5

48.4

41.3

∆% Mar 2005 to Mar 2018

11.7

15.1

20.9

∆% Mar 2006 to Mar 2018

-0.5

2.4

8.9

∆% Mar 2009 to Mar 2018

46.9

49.0

35.8

∆% Mar 2010 to Mar 2018

42.4

45.5

38.5

∆% Mar 2011 to Mar 2018

47.5

51.6

44.4

∆% Mar 2012 to Mar 2018

51.9

55.6

46.4

∆% Mar 2013 to Mar 2018

38.1

40.5

34.4

∆% Mar 2014 to Mar 2018

22.6

25.1

23.4

∆% Mar 2015 to Mar 2018

17.3

19.2

18.3

∆% Mar 2016 to Mar 2018

12.0

13.1

12.6

∆% Mar 2017 to Mar 2018

6.5

6.8

6.5

∆% Mar 2000 to Mar 2018

117.6

104.6

96.1

∆% Peak Jun 2006 Mar 2018

-1.7

7.8

∆% Peak Dec 2006 to Mar 2018

1.0

7.8

Average ∆% Dec 1987-Dec 2017

3.9

NA

3.6

Average ∆% Dec 1987-Dec 2000

3.8

NA

3.6

Average ∆% Dec 1992-Dec 2000

5.0

NA

4.5

Average ∆% Dec 2000-Dec 2017

3.9

3.6

3.5

Source: https://us.spindices.com/index-family/real-estate/sp-corelogic-case-shiller

Price increases measured by the Case-Shiller house price indices show in data for Mar 2017 that “home prices continued their rise across the country over the last 12 months” (https://www.spice-indices.com/idpfiles/spice-assets/resources/public/documents/715351_cshomeprice-release-0529.pdf?force_download=true). Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the 10- and 20-city composites, as shown in Table IIA-2. In Jan 2013, the seasonally adjusted 10-city composite increased 0.8 percent and the 20-city increased 0.8 percent while the 10-city not seasonally adjusted changed 0.0 percent and the 20-city changed 0.0 percent. House prices increased at high monthly percentage rates from Feb to Nov 2013. House prices seasonally adjusted declined in most months for both the 10-city and 20-city Case-Shiller composites from Dec 2010 to Jan 2012, as shown in Table IIA-2. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. Without seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Aug 2011 but fell in every month from Sep 2011 to Feb 2012. The not seasonally adjusted index registers decline in Mar 2012 of 0.1 percent for the 10-city composite and is flat for the 20-city composite. Not seasonally adjusted house prices increased 1.4 percent in Apr 2012 and at high monthly percentage rates until Sep 2012. House prices not seasonally adjusted stalled from Oct 2012 to Jan 2013 and surged from Feb to Sep 2013, decelerating in Oct 2013-Feb 2014. House prices grew at fast rates in Mar 2014. The 10-city NSA index increased 0.9 percent in Mar 2018 and the 20-city increased 1.0 percent. The 10-city SA increased 0.4 percent in Mar 2018 and the 20-city composite SA increased 0.5 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-2, US, Monthly Percentage Change of S&P Corelogic Case-Shiller Home Price Indices, Seasonally Adjusted and Not Seasonally Adjusted, ∆%

10-City Composite SA

10-City Composite NSA

20-City Composite SA

20-City Composite NSA

March 2018

0.4

0.9

0.5

1.0

February 2018

0.8

0.7

0.8

0.7

January 2018

0.7

0.3

0.8

0.3

December 2017

0.6

0.2

0.7

0.2

November 2017

0.7

0.3

0.7

0.2

October 2017

0.7

0.2

0.6

0.2

September 2017

0.9

0.4

1.1

0.4

August 2017

0.3

0.4

0.3

0.4

July 2017

0.4

0.8

0.2

0.7

June 2017

0.1

0.6

0.2

0.7

May 2017

0.1

0.8

0.2

0.9

April 2017

0.3

0.8

0.4

1.0

March 2017

0.4

0.9

0.5

1.0

February 2017

0.4

0.3

0.5

0.4

January 2017

0.7

0.3

0.7

0.2

December 2016

0.7

0.2

0.7

0.2

November 2016

0.7

0.2

0.7

0.2

October 2016

0.4

-0.1

0.5

0.0

September 2016

0.5

0.0

0.7

0.1

August 2016

0.2

0.3

0.3

0.3

July 2016

0.2

0.5

0.1

0.6

June 2016

0.2

0.7

0.3

0.8

May 2016

0.0

0.8

0.1

0.9

April 2016

0.5

1.0

0.5

1.1

March 2016

0.4

0.9

0.5

1.0

February 2016

0.4

0.2

0.4

0.2

January 2016

0.4

-0.1

0.5

0.0

December 2015

0.4

-0.1

0.5

0.0

November 2015

0.5

0.0

0.6

0.0

October 2015

0.5

-0.1

0.6

0.0

September 2015

0.5

0.1

0.7

0.1

August 2015

0.2

0.2

0.2

0.3

July 2015

0.2

0.6

0.1

0.7

June 2015

0.2

0.9

0.3

1.0

May 2015

0.2

1.0

0.2

1.1

April 2015

0.5

1.1

0.4

1.1

March 2015

0.3

0.8

0.4

0.9

February 2015

0.8

0.5

0.8

0.5

January 2015

0.5

-0.1

0.5

-0.1

December 2014

0.6

0.0

0.6

0.0

November 2014

0.4

-0.3

0.4

-0.2

October 2014

0.5

-0.1

0.5

-0.1

September 2014

0.3

-0.1

0.4

-0.1

August 2014

0.1

0.2

0.1

0.2

July 2014

0.0

0.6

0.0

0.6

June 2014

0.2

1.0

0.2

1.0

May 2014

0.1

1.1

0.1

1.1

April 2014

0.4

1.1

0.4

1.2

March 2014

0.5

0.8

0.4

0.9

February 2014

0.4

0.0

0.4

0.0

January 2014

0.6

-0.1

0.6

-0.1

December 2013

0.5

-0.1

0.5

-0.1

November 2013

0.7

0.0

0.7

-0.1

October 2013

0.9

0.2

0.9

0.2

September 2013

1.1

0.7

1.1

0.7

August 2013

1.2

1.3

1.2

1.3

July 2013

1.2

1.9

1.1

1.8

June 2013

1.2

2.2

1.2

2.2

May 2013

1.4

2.5

1.4

2.5

April 2013

2.0

2.6

1.9

2.6

March 2013

1.0

1.3

0.9

1.3

February 2013

0.9

0.3

0.9

0.2

January 2013

0.8

0.0

0.8

0.0

December 2012

0.9

0.2

0.9

0.2

November 2012

0.6

-0.3

0.7

-0.2

October 2012

0.6

-0.2

0.7

-0.1

September 2012

0.6

0.3

0.6

0.3

August 2012

0.6

0.8

0.7

0.9

July 2012

0.6

1.5

0.7

1.6

June 2012

1.0

2.1

1.1

2.3

May 2012

1.0

2.2

1.1

2.4

April 2012

0.8

1.4

0.9

1.4

March 2012

-0.2

-0.1

-0.3

0.0

February 2012

-0.2

-0.9

-0.1

-0.8

January 2012

-0.3

-1.1

-0.2

-1.0

December 2011

-0.5

-1.2

-0.4

-1.1

November 2011

-0.6

-1.4

-0.5

-1.3

October 2011

-0.5

-1.3

-0.5

-1.4

September 2011

-0.3

-0.6

-0.4

-0.7

August 2011

-0.2

0.1

-0.2

0.1

July 2011

0.0

0.9

0.0

1.0

June 2011

-0.1

1.0

0.0

1.2

May 2011

-0.2

1.0

-0.2

1.0

April 2011

0.1

0.6

0.2

0.6

March 2011

-0.9

-1.0

-1.1

-1.0

February 2011

-0.5

-1.3

-0.4

-1.2

January 2011

-0.3

-1.1

-0.3

-1.1

December 2010

-0.2

-0.9

-0.2

-1.0

Source: https://us.spindices.com/index-family/real-estate/sp-corelogic-case-shiller

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 $10.9 trillion or 13.5 percent from 2007 to 2008 and $8.5 trillion or 10.6 percent to 2009. Net worth fell $10.1 trillion from 2007 to 2008 or 15.3 percent and $8.3 trillion to 2009 or 12.5 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

80,930.4

70,033.4

-10,897.0

72,385.7

-8,544.7

Non
FIN

28,068.0

24,425.3

-3,642.7

23,516.7

-4,551.3

RE

23,258.6

19,491.0

-3,767.6

18,560.0

-4,698.6

FIN

52,862.4

46,278.1

-6,584.3

48,869.0

-3,993.4

LIAB

14,515.5

14,429.5

-86.0

14,303.4

-212.1

NW

66,415.0

56,273.9

-10,141.1

58,082.3

-8,332.7

A: Assets; Non FIN: Nonfinancial Assets; RE: Real Estate; FIN: Financial Assets; LIAB: Liabilities; NW: Net Worth

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. https://www.federalreserve.gov/releases/z1/current/default.htm

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 69.0 percent of GDP in IQ2018 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IQ2018, real estate increased in value by $5115.8 billion and financial assets increased $28,891.8 billion for net gain of real estate and financial assets of $34,007.6 billion, explaining most of the increase in net worth of $34,353.3 billion obtained by deducting the increase in liabilities of $1058.7 billion from the increase of assets of $35,412.1 billion (with minor rounding error). Net worth increased from $66,415.0 billion in 2007 to $100,768.3 billion in IQ2018 by $34,353.3 billion or 51.7 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 249.554 in Mar 2018 (http://www.bls.gov/cpi/data.htm) or 18.8 percent. Net worth adjusted by CPI inflation increased 27.7 percent from 2007 to IQ2018. Real estate assets adjusted for CPI inflation increased 2.7 percent from 2007 to IQ2018. 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 2.2 percent on average in the cyclical expansion in the 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 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 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://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 (http://www.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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2018/06/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from May 1919 to May 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 150.3883 in May 2018. The actual index NSA in May 2018 is 103.9274, which is 30.9 percent below trend. Manufacturing output grew at average 1.9 percent between Dec 1986 and May 2018. Using trend growth of 1.9 percent per year, the index would increase to 131.7847 in May 2018. The output of manufacturing at 103.9274 in May 2018 is 21.1 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 2015, 2016 and IIQ2017

Value 2007

Change to 2016

Change to 2017

Change to IQ2018

Assets

80,930.4

26,003.9

34,340.3

35,412.1

Nonfinancial

28,068.0

3,973.9

5,968.1

6,529.4

Real Estate

23,258.6

2,913.6

4,626.2

5,115.8

Financial

52,862.4

22,030.2

28,372.2

28,891.8

Liabilities

14,515.5

463.4

1,015.2

1,058.7

Net Worth

66,415.0

25,540.4

33,325.0

34,353.3

Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. https://www.federalreserve.gov/releases/z1/current/default.htm

The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and from IVQ1979) to IIIQ1991 and from IVQ2007 to IQ2018 is in Table IIA-5. The data reveal the following facts for the cycles in the 1980s:

  • IVQ1979 to IIIQ1991. Net worth increased 154.0 percent from IVQ1979 to IIIQ1991, the all items CPI index increased 79.0 percent from 76.7 in Dec 1979 to 137.2 in Sep 1991 and real net worth increased 42.0 percent.
  • IQ1980 to IVQ1985. Net worth increased 65.8 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 21.5 percent.
  • IVQ1979 to IVQ1985. Net worth increased 69.2 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 18.8 percent.
  • IQ1980 to IQ1989. Net worth increased 118.7 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 43.3 percent.
  • IQ1980 to IIQ1989. Net worth increased 123.1 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 44.0 percent.
  • IQ1980 to IIIQ1989. Net worth increased 129.1 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 46.8 percent.
  • IQ1980 to IVQ1989. Net worth increased 133.1 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 48.0 percent.
  • IQ1980 to IQ1990. Net worth increased 134.2 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 45.8 percent.
  • IQ1980 to IIQ1990. Net worth increased 136.7 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 46.0 percent
  • IQ1980 to IIIQ1990. Net worth increased 134.2 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 41.4 percent.
  • IQ1980 to IVQ1990. Net worth increased 139.1 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 43.1 percent. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://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 (http://www.bea.gov/iTable/index_nipa.cfm). This new cyclical contraction explains the contraction of net worth in IIIQ1990
  • IQ1980 to IQ1991. Net worth increased 145.7 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 45.8 percent.
  • IQ1980 to IIQ1991. Net worth increased 146.0 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 44.9 percent.
  • IQ1980 to IIIIQ1991. Net worth increased 148.8 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 45.3 percent.

There is disastrous performance in the current economic cycle:

  • IVQ2007 to IQ2018. Net worth increased 51.7 percent, the all items CPI increased 18.8 percent from 210.036 in Dec 2007 to 249.554 in Mar 2018 and real or inflation adjusted net worth increased 27.7 percent. Real estate assets adjusted for inflation increased 2.7 percent. Growth of real net worth at the long-term average of 3.1 percent per year from IVQ1945 to IQ2018 would have accumulated to 36.7 percent in the entire cycle from IVQ2007 to IQ2018, much higher than actual 27.7 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 2.2 percent on average in the cyclical expansion in the 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 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 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://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 (http://www.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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2018/06/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from May 1919 to May 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 150.3883 in May 2018. The actual index NSA in May 2018 is 103.9274, which is 30.9 percent below trend. Manufacturing output grew at average 1.9 percent between Dec 1986 and May 2018. Using trend growth of 1.9 percent per year, the index would increase to 131.7847 in May 2018. The output of manufacturing at 103.9274 in May 2018 is 21.1 percent below trend under this alternative calculation.

Table IIA-5, Net Worth of Households and Nonprofit Organizations in Billions of Dollars, IVQ1979 to IQ1991 and IVQ2007 to IVQ2017

Period IQ1980 to IIQ1991

Net Worth of Households and Nonprofit Organizations USD Millions

IVQ1979

IQ1980

8,994.9

9,181.1

IVQ1985

IIIQ1986

IVQ1986

IQ1987

IIQ1987

IIIQ1987

IVQ1987

IQ1988

IIQ1988

IIIQ1988

IVQ1988

IQ1989

IIQ1989

IIIQ1989

IVQ1989

IQ1990

IIQ1990

15,221.5

16,234.6

16,787.0

17,449.6

17,734.6

18,150.2

17,996.8

18,469.1

18,872.0

19,161.0

19,649.1

20,082.8

20,486.6

21,033.1

21,397.7

21,502.5

21,733.0

III1990

21,502.9

IV1990

21,949.8

I1991

22,561.5

IIQ1991

22,586.3

IIIQ1991

22,842.7

∆ USD Billions IVQ1985

IVQ1979 to IIIQ1991

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

+6,266.6 ∆%69.2 R∆18.8

+13,847.8 ∆%154.0 R∆%42.0

+6,040.4.0∆%65.8 R∆%21.5

+7,053.5 ∆%76.8 R∆%28.5

+7,605.9 ∆%82.8 R∆%32.5

+8,268.5 ∆%90.1 R∆%35.8

+8,553.5 ∆%93.2 R∆%36.3

+8,969.1 ∆%97.7 R∆%37.7

+8815.7 ∆%96.0 R∆%36.1

+9288.0 ∆%101.2 R∆%38.3

+9690.9 ∆%105.6 R∆%39.5

+9979.9 ∆%108.7 R∆%39.5

+10,468.0 ∆%114.0 R∆%42.3

+10901.7 ∆%118.7 R∆%43.3

+11,305.5 ∆%123.1 R∆% 44.0

+11,852.0 ∆%129.1 R∆% 46.8

+12,216.6 ∆%133.1 R∆%48.0

+12,321.4 ∆%134.2 R∆%45.8

+12,551.9 ∆%136.7 R∆%46.0

IQ1980-IIIQ1990

+12,321.8 ∆%134.2 R∆%41.4

IQ1980-IVQ1990

+12,768.7 ∆%139.1 R∆%43.1

IQ1980-IQ1991

+13,380.4 ∆%145.7 R∆%45.8

IQ1980-IIQ1991

+13,405.2 ∆%146.0 R∆%44.9

IQ1980-IIIQ1991

+13,661.6 ∆%148.8 R∆%45.3

Period IVQ2007 to IQ2018

Net Worth of Households and Nonprofit Organizations USD Millions

IVQ2007

66,415.0

IQ2018

100,768.3

∆ USD Billions

+34,353.3 ∆%51.7 R∆%27.7

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

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. https://www.federalreserve.gov/releases/z1/current/default.htm

Chart IIA-1 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ2007 to IQ2018. There is remarkable stop and go behavior in this series with two sharp declines and two standstills in the 35 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 27.7 percent from IVQ2007 to IQ2018 when adjusting for consumer price inflation.

Chart IIA-1, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ2007 to IQ2018

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. 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 IIIQ1991. 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 $5657.7 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.65 percent of GDP in a year. The Bureau of Economic Analysis estimates US GDP in 2017 at $19,390.6 billion, such that the bailout would be equivalent to cost to taxpayers of about $513.9 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 154.0 percent from IVQ1979 to IIIQ1991 and 42.0 percent when adjusting for consumer price inflation. Net worth of households and nonprofit organizations increased 148.8 percent from IQ1980 to IIIQ1991 and 45.3 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) (http://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 (http://www.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 in Chart IIA-2.

Chart IIA-2, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1979 to IIIQ1991

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. https://www.federalreserve.gov/releases/z1/current/default.htm

Chart IIA-3 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1945 at $803.1 billion to IQ2018 at $100,768.3 billion or increase of 12,447.4 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 249.554 in IQ2018 or increase of 1,271.2 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 72.25 years with inflation-adjusted increase from $44.126 in dollars of 1945 to $403.794 in IQ2018 or 815.1 percent. In a simple formula: {[($100,768.3/803.1)/(249.554/18.2)-1]100 = 815.1%}. Wealth of households and nonprofit organizations increased from $803.1 billion at year-end 1945 to $100,768.3 billion at the end of IQ2018 or 12,447.4 percent. The consumer price index increased from 18.2 in Dec 1945 to 249.554 in Mar 2018 or 1,271.2 percent. Net wealth of households and nonprofit organizations in dollars of 1945 increased from $44.126 in 1945 to $403.794 in IQ2018 or 815.1 percent at the average yearly rate of 3.1 percent. US real GDP grew at the average rate of 2.9 percent from 1945 to 2017 (http://www.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 IIQ2009 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 72.25 years when US GDP grew at 2.2 percent on average in the thirty-five quarters between IIIQ2009 and IQ2018 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). US GDP was $228.2 billion in 1945 and net worth of households and nonprofit organizations $803.1 billion for ratio of wealth to GDP of 3.52. The ratio of net worth of households and nonprofits of $66,415.0 billion in 2007 to GDP of $14,477.6 billion was 4.59. The ratio of net worth of households and nonprofits of $99,740.0 billion in 2017 to GDP of $19,390.6 billion was 5.14. The final data point in Chart IIA-3 is net worth of household and nonprofit institutions at $100,768.3 billion in IQ2018 for increase of 12,447.4 percent relative to $803.1 billion in IVQ1945. CPI adjusted net worth of household and nonprofit institutions increased from $44.126 in IVQ1945 to $403.794 in IQ2018 or 815.1 percent at the annual equivalent rate of 3.1 percent.

Chart IIA-3, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1945 to IQ2018

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. https://www.federalreserve.gov/releases/z1/current/default.htm

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 0.3 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 2.2 percent in IIQ2016. State and local government increased debt at 0.8 percent in IIIQ2016. State and local government decreased debt at 4.2 percent in IQ2018. 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

IQ2018

7.2

3.3

4.4

15.3

-4.2

IVQ2017

2.9

4.6

4.4

-0.2

4.3

IIIQ2017

6.0

2.7

6.0

10.3

-0.2

IIQ2017

4.1

3.9

5.9

3.6

-1.2

IQ2017

1.8

3.9

6.1

-2.6

-3.3

IVQ2016

2.7

2.8

2.2

3.6

0.4

IIIQ2016

5.2

4.2

6.1

6.3

0.8

IIQ2016

4.4

3.7

4.1

5.7

2.2

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

2017

3.8

3.8

5.7

2.8

-0.1

2016

4.5

3.3

5.5

5.6

1.0

2015

4.3

2.3

6.8

5.0

0.3

2014

4.1

2.2

6.2

5.4

-1.2

2013

3.8

1.6

4.7

6.7

-1.7

2012

4.6

1.1

4.5

10.1

0.0

2011

3.7

0.0

2.7

10.8

-1.3

2010

4.4

-0.6

-0.7

18.5

2.5

2009

3.6

0.4

-4.0

20.4

4.6

2008

5.8

0.1

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

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. https://www.federalreserve.gov/releases/z1/current/default.htm

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 $66,415 billion in 2007 to $58,082 billion in 2009 or 12.5 percent and to $63,117 billion in 2011 or 5.0 percent. Wealth increased 51.7 percent from 2007 to IQ2018, increasing 27.7 percent after adjustment for inflation, primarily because of bloating financial assets while nonfinancial assets declined/stagnated in real terms.

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

Quarter

Net Worth

IQ2018

100,768

IVQ2017

99,740

IIIQ2017

97,266

IIQ2017

95,482

IQ2017

94,138

IVQ2016

91,955

IIIQ2016

90,091

IIQ2016

87,807

IQ2016

87,063

IVQ2015

86,536

IIIQ2015

84,580

IIQ2015

85,740

IQ2015

85,253

IVQ2014

83,517

IIIQ2014

81,628

IIQ2014

81,266

IQ2014

79,849

IVQ2013

78,552

IIIQ2013

75,829

IIQ2013

73,362

IQ2013

71,780

IVQ2012

68,806

2017

99,740

2016

91,955

2015

86,535

2014

83,517

2013

78,552

2012

68,806

2011

63,117

2010

62,045

2009

58,082

2008

56,274

2007

66,415

2006

66,374

2005

61,895

Source: Board of Governors of the Federal Reserve System. 2018. Flow of funds, balance sheets and integrated macroeconomic accounts: first quarter 2018. Washington, DC, Federal Reserve System, Jun 7. https://www.federalreserve.gov/releases/z1/current/default.htm

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018.

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