Dollar Carry Trades Induced from Zero Interest Rates to Risk Financial Assets, Mediocre Cyclical United States Economic Growth with GDP Five Trillion Dollars below Trend in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Cyclically Stagnating Real Private Fixed Investment, Swelling Undistributed Corporate Profits, United States Terms of International Trade, United States Housing, United States House Prices, United States House Prices, World Cyclical Slow Growth, and Government Intervention in Globalization: Part II
Carlos M. Pelaez
© Carlos M. Pelaez, 2009,
2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.
IA Mediocre
Cyclical United States Economic Growth
IA1
Stagnating Real Private Fixed Investment
IA2
Swelling Undistributed Corporate Profits
IID United States Terms of International Trade
IIA United States
Housing Collapse
IIA1 Sales of New Houses
IIA2
United States House Prices
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
IA1 Stagnating Real Private Fixed Investment.
Table IA1-1 provides quarterly seasonally adjusted annual rates (SAAR) of
growth of private fixed investment for the recessions of the 1980s and the
current economic cycle. In the cyclical expansion beginning in IQ1983 (https://www.nber.org/cycles.html), real
private fixed investment in the United States grew at the average annual rate
of 14.7 percent in the first eight quarters from IQ1983 to IVQ1984. Growth
rates fell to an average of 2.2 percent in the following eight quarters from
IQ1985 to IVQ1986 and to an average of 1.9 percent in the 12 quarters of 1985,
1986 and 1987. The average rate of growth in the four quarters of 1988 was 3.7
percent. There were only four quarters of contraction of private fixed investment
from IQ1983 to IVQ1987. The National Bureau of Economic Research dates another
cycle from Jul 1990 (IIIQ1981) to Mar 1991 (IQ1991) (https://www.nber.org/cycles.html), showing
in Table III-1 with contractions of fixed investment in the final three
quarters of 1990 and the first quarter of 1991. There is quite different
behavior of private fixed investment in the thirty-six quarters of cyclical
expansion from IIIQ2009 to IIQ2018. The average annual growth rate in the first
eight quarters of expansion from IIIQ2009 to IIQ2011 was 4.6 percent, which is
significantly lower than 14.7 percent in the first eight quarters of expansion
from IQ1983 to IVQ1984. There is only robust growth of private fixed investment
in the four quarters of expansion from IIQ2011 to IQ2012 at the average annual
rate of 12.8 percent. Growth has fallen from the SAAR of 17.9 percent in
IIIQ2011 to 0.6 percent in IIIQ2012, recovering to 7.4 percent in IVQ2012 and
increasing to 7.0 percent in IQ2013. The SAAR of fixed investment fell to 7.1
percent in IIIQ2013 and to 5.5 percent in IVQ2013. The SAAR of fixed investment
decreased to 4.1 percent in IQ2014. Fixed investment grew at the SAAR of 11.6
percent in IIQ2014 and at 7.9 percent in IIIQ2014. Fixed investment grew at 4.7
percent in IVQ2014, 1.1 percent in IQ2015 and 3.5 percent in IIQ2015. Fixed
investment grew at 3.4 percent in IIIQ2015 and fell at 1.1 percent in IVQ2015.
Fixed investment increased at 2.0 percent in IQ2016 and increased at 1.5
percent in IIQ2016. Fixed investment increased at 3.2 percent in IIIQ2016 and
increased at 2.7 percent in IVQ2016. Fixed investment increased at 7.1 percent
in IQ2017 and increased at 1.6 percent in IIQ2017. Fixed investment grew at 1.2
percent in IIIQ2017. Fixed investment grew at 9.5 percent in IVQ2017 and
increased at 8.5 percent in IQ2018. Fixed investment grew at 4.4 percent in
IIQ2018. Fixed investment increased at 0.8 percent in IIIQ2018 and increased at
2.6 percent in IVQ2018. Fixed investment increased at 2.9 percent in IQ2019 and
decreased at 0.4 percent in IIQ2019. Fixed investment decreased at 2.4 percent
in IIIQ2019. Fixed investment increased at 1.0 percent in IVQ2019. Fixed
investment decreased at 1.4 percent in IQ2020 and decreased at 29.2 percent in
IIQ2020 in the global recession, with output in the US reaching a high in Feb
2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. Sudeep Reddy and Scott
Thurm, writing on “Investment falls off a cliff,” on Nov 18, 2012, published in
the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324595904578123593211825394.html?mod=WSJPRO_hpp_LEFTTopStories) analyze
the decline of private investment in the US and inform that a review by the Wall Street Journal of filing and
conference calls finds that 40 of the largest publicly traded corporations in
the US have announced intentions to reduce capital expenditures in 2012.
Table IA1-1,
US, Quarterly Growth Rates of Real Private Fixed Investment, % Annual
Equivalent SA
|
Q |
1981 |
1982 |
1983 |
1984 |
2008 |
2009 |
2010 |
|
I |
3.8 |
-10.6 |
9.3 |
13.2 |
-6.1 |
-28.2 |
-0.2 |
|
II |
3.2 |
-12.0 |
15.9 |
16.6 |
-3.2 |
-13.7 |
15.4 |
|
III |
0.2 |
-9.2 |
24.4 |
8.2 |
-9.7 |
1.5 |
2.2 |
|
IV |
-1.3 |
0.2 |
24.3 |
7.4 |
-23.9 |
2.0 |
7.8 |
|
|
|
|
|
1985 |
|
|
2011 |
|
I |
|
|
|
3.7 |
|
|
-0.7 |
|
II |
|
|
|
5.2 |
|
|
9.7 |
|
III |
|
|
|
-1.6 |
|
|
17.9 |
|
IV |
|
|
|
7.8 |
|
|
10.6 |
|
|
|
|
|
1986 |
|
|
2012 |
|
I |
|
|
|
1.1 |
|
|
13.1 |
|
II |
|
|
|
0.1 |
|
|
8.3 |
|
III |
|
|
|
-1.8 |
|
|
0.6 |
|
IV |
|
|
|
3.1 |
|
|
7.4 |
|
|
|
|
|
1987 |
|
|
2013 |
|
I |
|
|
|
-6.7 |
|
|
7.0 |
|
II |
|
|
|
6.3 |
|
|
3.3 |
|
III |
|
|
|
7.1 |
|
|
7.1 |
|
IV |
|
|
|
-0.2 |
|
|
5.5 |
|
|
|
|
|
1988 |
|
|
2014 |
|
I |
|
|
|
0.2 |
|
|
4.1 |
|
II |
|
|
|
8.1 |
|
|
11.6 |
|
III |
|
|
|
1.9 |
|
|
7.9 |
|
IV |
|
|
|
4.8 |
|
|
4.7 |
|
|
|
|
|
1989 |
|
|
2015 |
|
IQ |
|
|
|
3.6 |
|
|
1.1 |
|
IIQ |
|
|
|
0.5 |
|
|
3.5 |
|
IIIQ |
|
|
|
7.2 |
|
|
3.4 |
|
IVQ |
|
|
|
-5.1 |
|
|
-1.1 |
|
|
|
|
|
1990 |
|
|
2016 |
|
IQ |
|
|
|
4.8 |
|
|
2.0 |
|
IIQ |
|
|
|
-7.7 |
|
|
1.5 |
|
IIIQ |
|
|
|
-3.2 |
|
|
3.2 |
|
IVQ |
|
|
|
-9.9 |
|
|
2.7 |
|
|
|
|
|
1991 |
|
|
2017 |
|
I |
|
|
|
-10.6 |
|
|
7.1 |
|
II |
|
|
|
1.2 |
|
|
1.6 |
|
III |
|
|
|
0.5 |
|
|
1.2 |
|
IV |
|
|
|
1.7 |
|
|
9.5 |
|
|
|
|
|
1992 |
|
|
2018 |
|
I |
|
|
|
4.5 |
|
|
8.5 |
|
II |
|
|
|
13.8 |
|
|
4.4 |
|
III |
|
|
|
4.7 |
|
|
0.8 |
|
IV |
|
|
|
12.2 |
|
|
2.6 |
|
1993 |
|
|
|
|
|
|
2019 |
|
I |
|
|
|
3.0 |
|
|
2.9 |
|
II |
|
|
|
7.4 |
|
|
-0.4 |
|
III |
|
|
|
6.4 |
|
|
2.4 |
|
IV |
|
|
|
17.1 |
|
|
1.0 |
|
1994 |
|
|
|
|
|
|
2020 |
|
I |
|
|
|
4.8 |
|
|
-1.4 |
|
II |
|
|
|
8.3 |
|
|
-29.2 |
|
III |
|
|
|
3.3 |
|
|
|
|
IV |
|
|
|
10.0 |
|
|
|
Source: US
Bureau of Economic Analysis https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-1 of the US
Bureau of Economic Analysis (BEA) provides seasonally adjusted annual rates of
growth of real private fixed investment from 1980 to 1993. Growth rates
recovered sharply during the first eight quarters, which was essential in
returning the economy to trend growth and eliminating unemployment and most
underemployment accumulated during the contractions. The National
Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990
(Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The
expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP
contracted 1.3 percent from the pre-recession peak of $8983.9 billion of
chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm).
Chart IA1-1, US, Real Private Fixed Investment, Seasonally
Adjusted Annual Rates Percent Change from Prior Quarter, 1980-1993
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Weak behavior
of real private fixed investment from 2007 to 2020 is in Chart IA1-2. Growth
rates of real private fixed investment were much lower during the initial phase
of the current economic cycle, entered sharp trend of decline and recovered
recently, with another decline followed by increase and renewed decline. Fixed
investment contracted sharply, at 1.4 percent in IQ2020 and at 27.2 percent in
IIQ2020. There is a downward effect in the global recession, with output in the
US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event.
Chart IA1-2, US, Real Private Fixed Investment, Seasonally
Adjusted Annual Rates Percent Change from Prior Quarter, 2007-2020
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Table IA1-2 provides real private fixed
investment at seasonally adjusted annual rates from IVQ2007 to IIQ2020 or for
the complete economic cycle. The first column provides the quarter, the second
column percentage change relative to IVQ2007, the third column the quarter
percentage change in the quarter relative to the prior quarter and the final
column percentage change in a quarter relative to the same quarter a year
earlier. In IQ1980, real gross private domestic
investment in the US was $933.1 billion of chained 2012 dollars, growing to
$1,372.1 billion in IVQ1993 or 47.0 percent. The National
Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990
(Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The
expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP
contracted 1.3 percent from the pre-recession peak of $8983.9 billion of
chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). Real gross private domestic investment
in the US increased 7.4 percent from $2,653.1 billion in IVQ2007 to $2,849.8
billion in IIQ2020. Real private fixed investment increased 17.7 percent from
$2,630.0 billion of chained 2012 dollars in IVQ2007 to $3,096.3 billion in IIQ2020.
Real gross private domestic investment fell at SAAR 46.6 percent in IIQ2020,
and private fixed investment fell at SAAR 29.2 percent in the
global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. Private fixed investment fell relative
to IVQ2007 in all quarters preceding IVQ2012 and increased 0.8 percent in IIIQ2016,
increasing 0.4 percent in IIQ2016 and increasing 0.5 percent in IQ2016. Private
fixed investment increased 0.7 percent in IVQ2016. Private fixed investment
increased 1.7 percent in IQ2017 and increased 0.4 percent in IIQ2017. Private
fixed investment increased 0.3 percent in IIIQ2017 and increased 2.3 percent in
IVQ2017. Private fixed investment increased 2.1 percent in IQ2018, increasing
1.1 percent in IIQ2018. Private fixed investment increased 0.2 percent in
IIIQ2018, increasing 0.7 percent in IVQ2018. Private fixed investment increased
0.7 percent in IQ2019, decreasing 0.1 percent in IIQ2019. Private fixed
investment increased 0.6 percent in IIIQ2019. Private fixed investment
increased 0.2 percent in IVQ2019. Private fixed investment decreased 0.3
percent in IQ2020. Private fixed investment decreased 8.3 percent in IIQ2020.
Growth of real private investment in Table IA1-2 is mediocre for all but four
quarters from IIQ2011 to IQ2012. There is recent robust growth followed by
sharp contraction in the global recession, with output in the US reaching a
high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. The investment decision of United
States corporations is fractured in the current economic cycle in preference of
cash.
Table IA1-2,
US, Real Private Fixed Investment and Percentage Change Relative to IVQ2007 and
Prior Quarter, Billions of Chained 2012 Dollars and ∆%
|
|
Real PFI, Billions
Chained 2012 Dollars |
∆% Relative
to IVQ2007 |
∆% Relative
to Prior Quarter |
∆% |
|
IVQ2007 |
2630.0 |
NA |
-1.0 |
-1.1 |
|
IQ2008 |
2589.1 |
-1.6 |
-1.6 |
-2.6 |
|
IIQ2008 |
2567.9 |
-2.4 |
-0.8 |
-3.8 |
|
IIIQ2008 |
2503.0 |
-4.8 |
-2.5 |
-5.7 |
|
IV2008 |
2337.8 |
-11.1 |
-6.6 |
-11.1 |
|
IQ2009 |
2151.9 |
-18.2 |
-8.0 |
-16.9 |
|
IIQ2009 |
2073.9 |
-21.1 |
-3.6 |
-19.2 |
|
IIIQ2009 |
2081.6 |
-20.9 |
0.4 |
-16.8 |
|
IVQ2009 |
2092.0 |
-20.5 |
0.5 |
-10.5 |
|
IQ2010 |
2091.0 |
-20.5 |
0.0 |
-2.8 |
|
IIQ2010 |
2167.1 |
-17.6 |
3.6 |
4.5 |
|
IIIQ2010 |
2178.7 |
-17.2 |
0.5 |
4.7 |
|
IVQ2010 |
2220.0 |
-15.6 |
1.9 |
6.1 |
|
IQ2011 |
2216.2 |
-15.7 |
-0.2 |
6.0 |
|
IIQ2011 |
2268.0 |
-13.8 |
2.3 |
4.7 |
|
IIIQ2011 |
2363.3 |
-10.1 |
4.2 |
8.5 |
|
IVQ2011 |
2423.7 |
-7.8 |
2.6 |
9.2 |
|
IQ2012 |
2499.4 |
-5.0 |
3.1 |
12.8 |
|
IIQ2012 |
2549.8 |
-3.0 |
2.0 |
12.4 |
|
IIIQ2012 |
2553.6 |
-2.9 |
0.1 |
8.1 |
|
IVQ2012 |
2599.4 |
-1.2 |
1.8 |
7.2 |
|
IQ2013 |
2643.9 |
0.5 |
1.7 |
5.8 |
|
IIQ2013 |
2665.3 |
1.3 |
0.8 |
4.5 |
|
IIIQ2013 |
2711.3 |
3.1 |
1.7 |
6.2 |
|
IVQ2013 |
2748.0 |
4.5 |
1.4 |
5.7 |
|
IQ2014 |
2775.6 |
5.5 |
1.0 |
5.0 |
|
IIQ2014 |
2852.8 |
8.5 |
2.8 |
7.0 |
|
IIIQ2014 |
2907.3 |
10.5 |
1.9 |
7.2 |
|
IVQ2014 |
2941.2 |
11.8 |
1.2 |
7.0 |
|
IQ2015 |
2949.5 |
12.1 |
0.3 |
6.3 |
|
IIQ2015 |
2974.9 |
13.1 |
0.9 |
4.3 |
|
IIIQ2015 |
2999.8 |
14.1 |
0.8 |
3.2 |
|
IVQ2015 |
2991.8 |
13.8 |
-0.3 |
1.7 |
|
IQ2016 |
3006.8 |
14.3 |
0.5 |
1.9 |
|
IIQ2016 |
3018.0 |
14.8 |
0.4 |
1.4 |
|
IIIQ2016 |
3041.8 |
15.7 |
0.8 |
1.4 |
|
IVQ2016 |
3062.2 |
16.4 |
0.7 |
2.4 |
|
IQ2017 |
3115.5 |
18.5 |
1.7 |
3.6 |
|
IIQ2017 |
3127.7 |
18.9 |
0.4 |
3.6 |
|
IIIQ2017 |
3137.1 |
19.3 |
0.3 |
3.1 |
|
IVQ2017 |
3209.2 |
22.0 |
2.3 |
4.8 |
|
IQ2018 |
3275.2 |
24.5 |
2.1 |
5.1 |
|
IIQ2018 |
3310.6 |
25.9 |
1.1 |
5.8 |
|
IIIQ2018 |
3317.0 |
26.1 |
0.2 |
5.7 |
|
IVQ2018 |
3338.7 |
26.9 |
0.7 |
4.0 |
|
IQ2019 |
3362.3 |
27.8 |
0.7 |
2.7 |
|
IIQ2019 |
3358.6 |
27.7 |
-0.1 |
1.4 |
|
IIIQ2019 |
3378.9 |
28.5 |
0.6 |
1.9 |
|
IVQ2019 |
3387.2 |
28.8 |
0.2 |
1.5 |
|
IQ2020 |
3375.4 |
28.3 |
-0.3 |
0.4 |
|
IIQ2020 |
3096.3 |
17.7 |
-8.3 |
-7.8 |
PFI: Private
Fixed Investment
Source: US Bureau of Economic Analysis https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-3
provides real private fixed investment in chained dollars of 2009 from 2007 to
2020. Real private fixed investment increased 17.7 percent from $2,630.0
billion of chained 2012 dollars in IVQ2007 to $3,096.3 billion in IIQ2020. Real
private fixed investment decreased at SAAR 29.2 percent in IIQ2020 after
decreasing at SAAR 1.4 percent in IQ2020.
Chart IA1-3, US, Real Private Fixed Investment, Billions of
Chained 2009 Dollars, 2007 to 2020
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-4 provides real gross private domestic investment
in chained dollars of 2012 from 1980 to 1993. Real gross private domestic
investment climbed 47.0 percent to $1,372.1 billion of 2012 dollars in IIIQ1993
above the level of $933.1 billion in IQ1980. The National
Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990
(Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The
expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP
contracted 1.3 percent from the pre-recession peak of $8983.9 billion of
chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm).
Chart IA1-4, US, Real Gross Private Domestic Investment,
Billions of Chained 2009 Dollars at Seasonally Adjusted Annual Rate, 1980-1993
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-5 provides real gross private
domestic investment in the United States in billions of chained dollars of 2012
from 2007 to 2020. Real gross private domestic investment reached a level of
$2,849.8 billion in IIQ2020, which was 7.4 percent higher than the level of
$2,653.1 billion in IVQ2007 (https://apps.bea.gov/iTable/index_nipa.cfm).
Chart IA1-5, US, Real Gross Private Domestic Investment,
Billions of Chained 2009 Dollars at Seasonally Adjusted Annual Rate, 2007-2020
Source: US Bureau of Economic Analysis https://apps.bea.gov/iTable/index_nipa.cfm
Table IA1-3 shows that
the share of gross private domestic investment in GDP has decreased from 20.3
percent in IIQ2000 and 19.7 percent in IIQ2006 to 16.0 percent in IIQ2020.
There are declines in percentage shares in GDP of all components with sharp
reduction of residential investment from 4.7 percent in IIQ2000 and 6.2 percent
in IIQ2006 to 4.0 percent in IIQ2020. The share of fixed investment in GDP fell
from 19.4 percent in IIQ2000 and 19.2 percent in IIQ2006 to 17.6 percent in
IIQ2020.
Table IA1-3,
Percentage Shares of Gross Private Domestic Investment and Components in
Gross Domestic Product, % of GDP
|
|
IIQ2020 |
IIQ2006 |
IIQ2000 |
|
Gross Private
Domestic Investment |
16.0 |
19.7 |
20.3 |
|
Fixed
Investment |
17.6 |
19.2 |
19.4 |
|
Nonresidential |
13.6 |
12.9 |
14.6 |
|
Structures |
3.0 |
3.1 |
3.1 |
|
Equipment
and Software |
5.4 |
6.2 |
7.6 |
|
Intellectual |
5.2 |
3.6 |
4.0 |
|
Residential |
4.0 |
6.2 |
4.7 |
|
Change in Private Inventories |
-1.5 |
0.5 |
0.9 |
Source: US
Bureau of Economic Analysis https://apps.bea.gov/iTable/index_nipa.cfm
Broader perspective is in Chart IA1-6 with the
percentage share of gross private domestic investment in GDP in annual data
from 1929 to 2019. There was sharp drop during the current economic cycle with
incomplete recovery in contrast with sharp recovery after the recessions of the
1980s.
Chart IA1-6, US, Percentage Share of Gross Private Domestic
Investment in Gross Domestic Product, Annual, 1929-2019
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-7
provides percentage shares of private fixed investment in GDP with annual data
from 1929 to 2019. The sharp contraction after the recessions of the 1980s was
followed by sustained recovery while the sharp drop in the current economic
cycle has not been recovered.
Chart IA1-7, US, Percentage Share of Private Fixed Investment
in Gross Domestic Product, Annual, 1929-2019
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-8
provides percentage shares in GDP of nonresidential investment from 1929 to
2019. There is again recovery from sharp contraction in the 1980s but
inadequate recovery in the current economic cycle.
Chart IA1-8, US, Percentage Share of Nonresidential
Investment in Gross Domestic Product, Annual, 1929-2019
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-9
provides percentage shares of business equipment and software in GDP with
annual data from 1929 to 2019. There is again inadequate recovery in the
current economic cycle.
Chart IA1-9, US, Percentage Share of Business Equipment and
Software in Gross Domestic Product, Annual, 1929-2019
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-10
provides percentage shares of residential investment in GDP with annual data
from 1929 to 2019. The salient characteristic of Chart IA1-10 is the vertical
increase of the share of residential investment in GDP up to 2006 and
subsequent collapse.
Chart IA1-10, US, Percentage Share of Residential Investment
in Gross Domestic Product, Annual, 1929-2019
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Finer detail is provided by the quarterly share of
residential investment in GDP from 1979 to 2020 in Chart IA1-11. There was
protracted growth of that share, accelerating sharply into 2006 followed with
nearly vertical drop. The explanation
of the sharp contraction of United States housing 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
(Ingersoll 1987, 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).
Chart IA1-11, US, Percentage Share of Residential Investment
in Gross Domestic Product, Quarterly, 1979-2020
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-12 provides the share of intellectual property products
investment in GDP with annual data from 1929 to 2019. This is an important
addition in the revision and enhancement of GDP provided by the Bureau of
Economic Analysis. The share rose sharply over time.
Chart IA1-12, US, Percentage Share of Intellectual Property
Products Investment in Gross Domestic Product, Annual, 1929-2019
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-13 provides the percentage share of intellectual property
investment in GDP on a quarterly basis from 1979 to 2019.
Chart IA1-13, US, Percentage Share of Intellectual Property
Investment in Gross Domestic Product, Quarterly, 1979-2020
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Table IA1-4
provides the seasonally adjusted annual rate of real GDP percentage change and
contributions in percentage points in annual equivalent rate of gross domestic
investment (GDI), real private fixed investment (PFI), nonresidential
investment (NRES), business equipment and software (EQP), residential
investment (RES), intellectual property products (IPP) and change in
inventories (∆INV) for the cyclical expansions from IQ1983 to IVQ1993 and from
IIIQ2009 to IIQ2020. GDI contributed 2.46 percentage points to GDP in IQ2015
with 0.19 percentage points by PFI, 2.28 percentage points by inventory
accumulation and deduction of 0.12 percentage points by intellectual property
products. GDI contributed 0.23 percentage points to GDP growth in IIQ2015: 0.58
percentage points in PFI, 0.24 percentage points in NRES and 0.34 percentage
points in RES. Inventory investment deducted 0.35 percentage points and IPP added
0.06 percentage points. GDI deducted
0.13 percentage points from GDP growth in IIIQ2015 with deduction of 0.69
percentage points by inventory divestment while EQP added 0.39 percentage
points. PFI added 0.56 percentage points, nonresidential investment added 0.19
percentage points and residential investment added 0.37 percentage points. IPP
added 0.22 percentage points. GDI deducted 0.83 percentage points in IVQ2015
with percentage point deductions of 0.44 by NRES, 0.19 by PFI, 0.32 by EQP and
0.64 by inventory divestment. Percentage point contributions were 0.39 by IPP
and 0.25 by RES. GDI deducted 0.39 percentage points from GDP growth in IQ2016
with percentage point contribution of 0.34 by fixed investment, deduction of
0.15 by nonresidential investment and deduction of 0.73 by inventory change.
Residential investment added 0.49 percentage points and intellectual property
products contributed 0.45 percentage points. GDI deducted 0.58 percentage
points from GDP growth in IIQ2016 with deductions of 0.06 by RES and 0.83
percentage points by inventory change. IPP added 0.35 percentage points, NRES
contributed 0.31 and PFI added 0.25. GDI contributed 0.03 percentage points to
GDP growth in IIIQ2016 with contributions by NRES, and IPP and deduction by
inventory divestment. PFI added 0.53 percentage points and RES deducted 0.08
percentage points. GDI contributed 1.80 percentage points to GDP growth in
IVQ2016 with contributions by NRES, RES and inventory investment. PFI added
0.45 percentage points, RES added 0.26 percentage points and inventory
investment added 1.35 percentage points. GDI deducted 0.23 percentage points
from GDP growth in IQ2017 with contributions by all segments except for
deduction of 1.41 percentage points by inventory divestment. PFI contributed
1.17 percentage points. NRES contributed 0.75 percentage points and RES added
0.43 percentage points. EQP contributed 0.26 percentage points and IPP added
0.25 percentage points. GDI added 0.61 percentage points to GDP growth in
IIQ2017 with contributions of 0.27 PPs by PFI, 0.31 PPs by NRES, 0.28 PPs by
EQP and 0.05 PPs by IPP. RES deducted 0.04 PPs and inventory change added 0.34
PPs. GDI added 1.26 percentage points to GDP growth in IIIQ2017 with
contributions of 0.21 PPs by PFI, 0.28 PPs by NRES and 0.28 PPs by IPP. EQP
contributed 0.35 PPs, RES deducted 0.07 PPs and inventory change added 1.05
PPs. GDI added 1.07 percentage points to GDP growth in IVQ2017 with
contributions of 1.57 PPs by PFI, 1.18 PPs by NRES and 0.26 PPs by IPP. EQP
contributed 0.78 PPs, RES added 0.39 PPs and inventory change deducted 0.50
PPs. GDI added 1.83 percentage points to GDP growth in IQ2018 with
contributions of 1.42 PPs by PFI, 1.55 PPs by NRES and 0.38 PPs by IPP. EQP
contributed 0.57 PPs, RES deducted 0.13 PPs and inventory change contributed
0.41 PPs. GDI deducted 0.19 PPs from GDP growth in IIQ2018 with contributions
of 0.76 by PFI, 0.82 by NRES, 0.15 by EQP and 0.52 by IPP. RES deducted 0.07
and inventory divestment deducted 0.94. GDI added 1.72
PPs to GDP growth in IIIQ2018 with contributions of 0.36 by NRSE, 0.35 by EQP,
0.19 by IPP and 1.58 by inventory change. RES added 0.36 and PFI added 0.14.
GDI added 0.69 PPs to GDP growth in IVQ2018 with contributions of 0.66 by NRSE,
0.54 by EQP, 0.52 by IPP and 0.23 by inventory change. RES deducted 0.21 and
PFI added 0.46. GDI added 0.71 PPs to GDP growth in IQ2019 with contributions
of 0.56 by NRSE, 0.20 by IPP and 0.21 by inventory change. RES deducted 0.06
and EQP added 0.12. PFI added 0.50. GDI deducted 1.04 PPs from GDP in IIQ2019.
PFI deducted 0.07, NRES added 0.01, RES deducted 0.08 and inventory divestment
deducted 0.97. EQP deducted 0.23 and IPP added 0.19. GDI contributed 0.34 PPs
to GDP in IIIQ2019. PFI added 0.42, NRES contributed 0.25, EQP deducted 0.10
and inventory divestment deducted 0.09. RES added 0.17 and IPP added 0.24. GDI
deducted 0.64 PPs from GDP in IVQ2019. PFI added 0.17, NRES deducted 0.04, EQP
deducted 0.10 and inventory divestment deducted 0.82. RES added 0.22 and IPP
added 0.21. GDP contracted at 5.0 percent SAAR in IQ2020 in the global
recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. GDI deducted 1.56 PPs from
GDP in IQ2020. PFI deducted 0.23, NRES deducted 0.91, EQP deducted 0.91 and
inventory divestment deducted 1.34. RES added 0.68 and IPP added 0.11. GDP
contracted at 31.4 percent SAAR in IIQ2020 in the global recession, with output
in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. GDI deducted 8.77 PPs from
GDP in IIQ2020. PFI deducted 5.27, NRES deducted 3.67, EQP added 2.03, IPP
deducted 0.53, RES deducted 1.60 and inventory divestment deducted 3.50.
Table IA1-4,
US, Contributions to the Rate of Growth of Real GDP in Percentage Points
|
|
GDP |
GDI |
PFI |
NRES |
EQP |
IPP |
RES |
∆INV |
|
2020 |
|
|
|
|
|
|
|
|
|
I |
-5.0 |
-1.56 |
-0.23 |
-0.91 |
-0.91 |
0.11 |
0.68 |
-1.34 |
|
II |
-31.4 |
-8.77 |
-5.27 |
-3.67 |
2.03 |
-0.53 |
-1.60 |
-3.50 |
|
2019 |
|
|
|
|
|
|
|
|
|
I |
2.9 |
0.71 |
0.50 |
0.56 |
0.12 |
0.20 |
-0.06 |
0.21 |
|
II |
1.5 |
-1.04 |
-0.07 |
0.01 |
-0.23 |
0.19 |
-0.08 |
-0.97 |
|
III |
2.6 |
0.34 |
0.42 |
0.25 |
-0.10 |
0.24 |
0.17 |
-0.09 |
|
IV |
2.4 |
-0.64 |
0.17 |
-0.04 |
-0.10 |
0.21 |
0.22 |
-0.82 |
|
2018 |
|
|
|
|
|
|
|
|
|
I |
3.8 |
1.83 |
1.42 |
1.55 |
0.57 |
0.38 |
-0.13 |
0.41 |
|
II |
2.7 |
-0.19 |
0.76 |
0.82 |
0.15 |
0.52 |
-0.07 |
-0.94 |
|
III |
2.1 |
1.72 |
0.14 |
0.36 |
0.35 |
0.19 |
-0.22 |
1.58 |
|
IV |
1.3 |
0.69 |
0.46 |
0.66 |
0.54 |
0.52 |
-0.21 |
0.23 |
|
2017 |
|
|
|
|
|
|
|
|
|
I |
2.3 |
-0.23 |
1.17 |
0.75 |
0.26 |
0.25 |
0.43 |
-1.41 |
|
II |
1.7 |
0.61 |
0.27 |
0.31 |
0.28 |
0.05 |
-0.04 |
0.34 |
|
III |
2.9 |
1.26 |
0.21 |
0.28 |
0.35 |
0.28 |
-0.07 |
1.05 |
|
IV |
3.9 |
1.07 |
1.57 |
1.18 |
0.78 |
0.26 |
0.39 |
-0.50 |
|
2016 |
|
|
|
|
|
|
|
|
|
I |
2.3 |
-0.39 |
0.34 |
-0.15 |
-0.15 |
0.45 |
0.49 |
-0.73 |
|
II |
1.3 |
-0.58 |
0.25 |
0.31 |
-0.26 |
0.35 |
-0.06 |
-0.83 |
|
III |
2.2 |
0.03 |
0.53 |
0.61 |
-0.08 |
0.23 |
-0.08 |
-0.50 |
|
IV |
2.5 |
1.80 |
0.45 |
0.19 |
-0.04 |
0.04 |
0.26 |
1.35 |
|
2015 |
|
|
|
|
|
|
|
|
|
I |
3.8 |
2.46 |
0.19 |
-0.07 |
0.20 |
-0.12 |
0.26 |
2.28 |
|
II |
2.7 |
0.23 |
0.58 |
0.24 |
0.09 |
0.06 |
0.34 |
-0.35 |
|
III |
1.5 |
-0.13 |
0.56 |
0.19 |
0.39 |
0.22 |
0.37 |
-0.69 |
|
IV |
0.6 |
-0.83 |
-0.19 |
-0.44 |
-0.32 |
0.39 |
0.25 |
-0.64 |
|
2014 |
|
|
|
|
|
|
|
|
|
I |
-1.1 |
-0.74 |
0.66 |
0.75 |
0.21 |
0.10 |
-0.09 |
-1.40 |
|
II |
5.5 |
2.92 |
1.86 |
1.47 |
0.62 |
0.38 |
0.40 |
1.05 |
|
III |
5.0 |
1.47 |
1.30 |
1.11 |
0.76 |
0.30 |
0.19 |
0.17 |
|
IV |
2.3 |
0.09 |
0.78 |
0.33 |
-0.23 |
0.34 |
0.46 |
-0.69 |
|
2013 |
|
|
|
|
|
|
|
|
|
I |
3.6 |
2.43 |
1.10 |
0.69 |
0.44 |
0.50 |
0.41 |
1.33 |
|
II |
0.5 |
0.75 |
0.52 |
0.14 |
-0.05 |
-0.14 |
0.37 |
0.23 |
|
III |
3.2 |
2.60 |
1.12 |
0.90 |
0.00 |
0.31 |
0.22 |
1.48 |
|
IV |
3.2 |
0.27 |
0.89 |
1.08 |
0.92 |
0.05 |
-0.20 |
-0.62 |
|
2012 |
|
|
|
|
|
|
|
|
|
I |
3.2 |
1.32 |
1.90 |
1.30 |
0.73 |
0.04 |
0.60 |
-0.59 |
|
II |
1.7 |
1.47 |
1.25 |
1.16 |
0.68 |
0.21 |
0.09 |
0.21 |
|
III |
0.5 |
0.29 |
0.09 |
-0.18 |
-0.07 |
0.03 |
0.27 |
0.20 |
|
IV |
0.5 |
-0.58 |
1.13 |
0.57 |
0.48 |
0.32 |
0.56 |
-1.70 |
|
2011 |
|
|
|
|
|
|
|
|
|
I |
-1.0 |
-1.10 |
-0.09 |
-0.05 |
0.53 |
0.16 |
-0.03 |
-1.02 |
|
II |
2.9 |
2.36 |
1.34 |
1.23 |
0.31 |
0.26 |
0.11 |
1.03 |
|
III |
-0.1 |
0.19 |
2.42 |
2.25 |
1.32 |
0.32 |
0.17 |
-2.23 |
|
IV |
4.7 |
4.60 |
1.55 |
1.29 |
0.54 |
0.37 |
0.25 |
3.06 |
|
2010 |
|
|
|
|
|
|
|
|
|
I |
1.5 |
1.28 |
-0.02 |
0.32 |
1.32 |
-0.27 |
-0.34 |
1.30 |
|
II |
3.7 |
2.95 |
2.03 |
1.49 |
1.28 |
-0.08 |
0.53 |
0.92 |
|
III |
3.0 |
2.60 |
0.32 |
1.26 |
1.11 |
0.30 |
-0.94 |
2.28 |
|
IV |
2.0 |
-0.17 |
1.08 |
0.92 |
0.44 |
0.29 |
0.16 |
-1.25 |
|
2009 |
|
|
|
|
|
|
|
|
|
I |
-4.4 |
-7.21 |
-5.07 |
-3.89 |
-2.35 |
-0.41 |
-1.18 |
-2.14 |
|
II |
-0.6 |
-3.15 |
-2.11 |
-1.44 |
-0.74 |
0.39 |
-0.68 |
-1.04 |
|
III |
1.5 |
-0.08 |
0.25 |
-0.24 |
0.46 |
0.16 |
0.49 |
-0.33 |
|
IV |
4.5 |
4.76 |
0.32 |
0.33 |
0.86 |
0.48 |
-0.02 |
4.44 |
|
1982 |
|
|
|
|
|
|
|
|
|
I |
-6.1 |
-7.33 |
-2.00 |
-1.19 |
-0.57 |
0.14 |
-0.81 |
-5.33 |
|
II |
1.8 |
-0.05 |
-2.32 |
-1.88 |
-1.20 |
0.08 |
-0.44 |
2.27 |
|
III |
-1.5 |
-0.62 |
-1.73 |
-1.71 |
-0.55 |
0.06 |
-0.02 |
1.11 |
|
IV |
0.2 |
-5.38 |
-0.04 |
-1.05 |
-0.57 |
0.00 |
1.01 |
-5.34 |
|
1983 |
|
|
|
|
|
|
|
|
|
I |
5.4 |
2.34 |
1.44 |
-0.93 |
-0.27 |
0.16 |
2.36 |
0.91 |
|
II |
9.4 |
5.95 |
2.53 |
0.67 |
1.24 |
0.29 |
1.86 |
3.42 |
|
III |
8.2 |
4.40 |
3.83 |
2.13 |
1.43 |
0.31 |
1.70 |
0.57 |
|
IV |
8.6 |
6.95 |
3.93 |
3.14 |
2.32 |
0.35 |
0.79 |
3.01 |
|
1984 |
|
|
|
|
|
|
|
|
|
I |
8.1 |
7.23 |
2.29 |
1.71 |
0.46 |
0.30 |
0.58 |
4.94 |
|
II |
7.1 |
2.57 |
2.87 |
2.53 |
1.36 |
0.29 |
0.34 |
-0.29 |
|
III |
3.9 |
1.70 |
1.48 |
1.70 |
0.89 |
0.25 |
-0.22 |
0.21 |
|
IV |
3.3 |
-1.07 |
1.36 |
1.34 |
0.86 |
0.29 |
0.02 |
-2.43 |
|
1985 |
|
|
|
|
|
|
|
|
|
I |
3.9 |
-2.14 |
0.72 |
0.67 |
-0.23 |
0.14 |
0.05 |
-2.86 |
|
II |
3.6 |
1.34 |
0.99 |
0.83 |
0.65 |
0.20 |
0.16 |
0.35 |
|
III |
6.2 |
-0.43 |
-0.28 |
-0.62 |
-0.38 |
0.13 |
0.34 |
-0.15 |
|
IV |
3.0 |
2.81 |
1.40 |
1.00 |
0.53 |
0.26 |
0.40 |
1.40 |
|
1986 |
|
|
|
|
|
|
|
|
|
I |
3.8 |
0.04 |
0.21 |
-0.55 |
-0.28 |
0.17 |
0.76 |
-0.17 |
|
II |
1.8 |
-1.30 |
0.00 |
-1.12 |
0.34 |
0.15 |
1.12 |
-1.30 |
|
III |
3.9 |
-1.97 |
-0.34 |
-0.63 |
-0.17 |
0.10 |
0.28 |
-1.62 |
|
IV |
2.2 |
0.25 |
0.54 |
0.48 |
0.30 |
0.10 |
0.05 |
-0.29 |
|
1987 |
|
|
|
|
|
|
|
|
|
I |
3.0 |
1.99 |
-1.30 |
-1.26 |
-0.97 |
0.07 |
-0.04 |
3.29 |
|
II |
4.4 |
0.08 |
1.07 |
1.00 |
0.76 |
0.08 |
0.07 |
-1.00 |
|
III |
3.5 |
0.03 |
1.23 |
1.40 |
0.70 |
0.11 |
-0.17 |
-1.20 |
|
IV |
7.0 |
4.96 |
-0.01 |
-0.05 |
-0.48 |
0.16 |
0.04 |
4.97 |
|
1988 |
|
|
|
|
|
|
|
|
|
I |
2.1 |
-3.64 |
0.06 |
0.41 |
0.82 |
0.15 |
-0.36 |
-3.69 |
|
II |
5.4 |
1.73 |
1.39 |
1.15 |
0.67 |
0.18 |
0.25 |
0.33 |
|
III |
2.4 |
0.38 |
0.33 |
0.32 |
0.29 |
0.22 |
0.01 |
0.05 |
|
IV |
5.4 |
1.12 |
0.84 |
0.71 |
0.35 |
0.40 |
0.13 |
0.28 |
|
1989 |
|
|
|
|
|
|
|
|
|
I |
4.1 |
2.43 |
0.62 |
0.81 |
0.32 |
0.27 |
-0.19 |
1.80 |
|
II |
3.1 |
-0.71 |
0.09 |
0.68 |
0.57 |
0.27 |
-0.59 |
-0.80 |
|
III |
3.0 |
-0.64 |
1.20 |
1.28 |
0.52 |
0.29 |
-0.08 |
-1.84 |
|
IV |
0.8 |
-0.54 |
-0.91 |
-0.53 |
-0.74 |
0.30 |
-0.38 |
0.37 |
|
1990 |
|
|
|
|
|
|
|
|
|
I |
4.4 |
0.70 |
0.80 |
0.64 |
0.11 |
0.23 |
0.16 |
-0.10 |
|
II |
1.5 |
0.03 |
-1.35 |
-0.67 |
-0.79 |
0.19 |
-0.69 |
1.38 |
|
III |
0.3 |
-1.29 |
-0.56 |
0.33 |
0.34 |
0.05 |
-0.89 |
-0.74 |
|
IV |
-3.6 |
-3.66 |
-1.69 |
-0.79 |
-0.38 |
0.20 |
-0.90 |
-1.97 |
|
1991 |
|
|
|
|
|
|
|
|
|
I |
-1.9 |
-2.04 |
-1.78 |
-1.00 |
-0.90 |
0.18 |
-0.78 |
-0.26 |
|
II |
3.2 |
0.05 |
0.17 |
-0.26 |
-0.17 |
0.26 |
0.43 |
-0.12 |
|
III |
2.0 |
1.21 |
0.05 |
-0.43 |
0.33 |
0.04 |
0.48 |
1.16 |
|
IV |
1.4 |
2.15 |
0.24 |
-0.05 |
-0.13 |
0.31 |
0.29 |
1.91 |
|
1992 |
|
|
|
|
|
|
|
|
|
I |
4.9 |
-1.16 |
0.64 |
-0.20 |
-0.21 |
0.15 |
0.84 |
-1.81 |
|
II |
4.4 |
3.40 |
1.96 |
1.44 |
1.29 |
0.14 |
0.53 |
1.44 |
|
III |
4.0 |
0.50 |
0.70 |
0.69 |
0.52 |
0.07 |
0.01 |
-0.19 |
|
IV |
4.2 |
1.92 |
1.78 |
1.18 |
0.85 |
0.19 |
0.60 |
0.14 |
|
1993 |
|
|
|
|
|
|
|
|
|
I |
0.7 |
1.49 |
0.46 |
0.45 |
0.44 |
0.15 |
0.01 |
1.04 |
|
II |
2.3 |
0.39 |
1.11 |
0.89 |
0.95 |
0.12 |
0.22 |
-0.72 |
|
III |
1.9 |
-0.42 |
0.96 |
0.35 |
0.26 |
0.07 |
0.61 |
-1.38 |
|
IV |
5.6 |
3.40 |
2.52 |
1.66 |
1.34 |
0.00 |
0.87 |
0.87 |
GDP: Gross
Domestic Product; GDI: Gross Domestic Investment; PFI: Private Fixed
Investment; NRES: Nonresidential; EQP: Business Equipment and Software; IPP:
Intellectual Property Products; RES: Residential; ∆INV: Change in Private
Inventories.
GDI = PFI +
∆INV, may not add exactly because of errors of rounding.
GDP: Seasonally
adjusted annual equivalent rate of growth in a quarter; components: percentage
points at annual rate.
Source: US Bureau of Economic Analysis https://apps.bea.gov/iTable/index_nipa.cfm
IA2 Swelling
Undistributed Corporate Profits. Table IA1-5 provides value added of
corporate business, dividends and corporate profits in billions of current
dollars at seasonally adjusted annual rates (SAAR) in IVQ2007 and IIQ2020
together with percentage changes. The last three rows of Table IA1-5 provide
gross value added of nonfinancial corporate business, consumption of fixed
capital and net value added in billions of chained 2012 dollars at SAARs.
Deductions from gross value added of corporate profits down the rows of Table
IA1-5 end with undistributed corporate profits. Profits
after taxes with inventory valuation adjustment (IVA) and capital consumption
adjustment (CCA) increased 68.8 percent in nominal terms from IVQ2007 to IIQ2020
while net dividends increased to $1,016.0 billion in IIQ2020 and undistributed corporate profits swelled 37.2
percent from $138.3 billion in IQ2007 to $189.3 billion in IIQ2020 and changed
signs from minus $4.0 billion in current dollars in IVQ2007. Net
dividends decreased from $968.7 billion in IVQ2009 to $813.0 billion in IQ2020,
increasing to $1,016.0 billion in IIQ2020, as corporations distributed dividends
to halt decrease in stock valuations in the global recession, with output in the
US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. The investment
decision of United States corporations has been fractured in the current
economic cycle in preference of cash. Gross value added of
nonfinancial corporate business adjusted for inflation increased 4.7 percent
from IVQ2007 to IIQ2020, which is much lower than nominal increase of 30.8
percent in the same period for gross value added of total corporate business.
Table IA1-5, US, Value Added of Corporate Business, Corporate
Profits and Dividends, IVQ2007-IIQ2020
|
|
IVQ2007 |
IIQ2020 |
∆% |
|
Current Billions of Dollars Seasonally Adjusted Annual Rates
(SAAR) |
|
|
|
|
Gross Value Added of Corporate Business |
8,177.7 |
10,697.8 |
30.8 |
|
Consumption of Fixed Capital |
1,209.3 |
1,934.1 |
59.9 |
|
Net Value Added |
6,968.4 |
8,763.8 |
25.8 |
|
Compensation of Employees |
4,948.5 |
6,719.5 |
35.8 |
|
Taxes on Production and Imports Less Subsidies |
686.7 |
223.4 |
-67.5 |
|
Net Operating Surplus |
1,333.2 |
1,820.9 |
36.6 |
|
Net Interest and Misc |
190.1 |
250.1 |
31.6 |
|
Business Current Transfer Payment Net |
70.1 |
128.2 |
82.9 |
|
Corporate Profits with IVA and CCA Adjustments |
1,073.1 |
1,442.5 |
34.4 |
|
Taxes on Corporate Income |
359.0 |
236.8 |
-34.0 |
|
Profits after Tax with IVA and CCA Adjustment |
714.4 |
1,205.8 |
68.8 |
|
Net Dividends |
718.4 |
1,016.0 |
41.4 |
|
Undistributed Profits with IVA and CCA Adjustment |
-4.0 |
189.7 |
NA ∆% 37.2 relative to 138.3 in IQ2007 |
|
Billions of Chained USD 2012 SAAR |
|
|
|
|
Gross Value Added of Nonfinancial Corporate Business |
7,882.0 |
8,255.4 |
4.7 |
|
Consumption of Fixed Capital |
1,107.7 |
1,629.0 |
47.1 |
|
Net Value Added |
6,774.3 |
6,626.4 |
-2.2 |
IVA: Inventory Valuation Adjustment; CCA: Capital Consumption
Adjustment
Source: US Bureau of Economic Analysis https://apps.bea.gov/iTable/index_nipa.cfm
Table
IA1-6 provides comparable United States value added of corporate business,
corporate profits and dividends from IQ1980 to IVQ1993. There is significant
difference both in nominal and inflation-adjusted data. Between IQ1980 and IVQ1993,
profits after tax with IVA and CCA increased 192.1 percent with dividends
growing 300.8 percent and undistributed profits increasing 95.3 percent. There
was much higher inflation in the 1980s than in the current cycle. For example,
the consumer price index increased 82.0 percent from Mar 1980 to Dec 1993 but
only 22.7 percent between Dec 2007 and Jun 2020 (https://www.bls.gov/cpi/data.htm).
The comparison is still valid in terms of inflation-adjusted data: gross value
added of nonfinancial corporate business adjusted for inflation increased 53.6
percent between IQ1980 and IVQ1993 but only 4.7 percent between IVQ2007 and IIQ2020
while net value added adjusted for inflation increased 51.5 percent between
IQ1980 and IVQ1993 but decreased 2.2 percent between IVQ2007 and IIQ2020. The National
Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990
(Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The
expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP
contracted 1.3 percent from the pre-recession peak of $8983.9 billion of
chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). The
global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event, sets downward pressure on
profits in IIQ2020.
Table IA1-6,
US, Value Added of Corporate Business, Corporate Profits and Dividends, IQ1980-IVQ1993
|
|
IQ1980 |
IVQ1993 |
∆% |
|
Current
Billions of Dollars Seasonally Adjusted Annual Rates (SAAR) |
|
|
|
|
Gross Value
Added of Corporate Business |
1,653.6 |
4,049.1 |
144.9 |
|
Consumption
of Fixed Capital |
200.5 |
527.1 |
162.9 |
|
Net Value
Added |
1,453.1 |
3,522.1 |
142.4 |
|
Compensation
of Employees |
1,072.9 |
2,570.7 |
139.6 |
|
Taxes on
Production and Imports Less Subsidies |
121.5 |
355.2 |
192.3 |
|
Net Operating
Surplus |
258.7 |
596.2 |
130.5 |
|
Net Interest
and Misc. |
50.0 |
61.0 |
22.0 |
|
Business
Current Transfer Payment Net |
11.5 |
30.7 |
167.0 |
|
Corporate
Profits with IVA and CCA Adjustments |
197.2 |
504.6 |
155.9 |
|
Taxes on
Corporate Income |
85.4 |
178.0 |
108.4 |
|
Profits after
Tax with IVA and CCA Adjustment |
111.8 |
326.6 |
192.1 |
|
Net Dividends |
52.6 |
210.8 |
300.8 |
|
Undistributed
Profits with IVA and CCA Adjustment |
59.3 |
115.8 |
95.3 |
|
Billions of
Chained USD 2012 SAAR |
|
|
|
|
Gross Value
Added of Nonfinancial Corporate Business |
3,140.9 |
4,825.4 |
53.6 |
|
Consumption
of Fixed Capital |
319.3 |
550.7 |
72.5 |
|
Net Value
Added |
2,821.6 |
4,274.7 |
51.5 |
IVA: Inventory
Valuation Adjustment; CCA: Capital Consumption Adjustment
Source: US
Bureau of Economic Analysis https://apps.bea.gov/iTable/index_nipa.cfm
Chart IA1-14
of the US Bureau of Economic Analysis provides quarterly corporate profits
after tax and undistributed profits with IVA and CCA from 1979 to 2020. There
is tightness between the series of quarterly corporate profits and
undistributed profits in the 1980s with significant gap developing from 1988
and to the present with the closest approximation peaking in IVQ2005 and
surrounding quarters. These gaps widened during all recessions including in
1991 and 2001 and recovered in expansions with exceptionally weak performance
in the current expansion. The global recession, with output in the US reaching
a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event, sets downward pressure on
profits in IIQ2020.
Chart IA1-14, US, Corporate Profits after Tax and
Undistributed Profits with Inventory Valuation Adjustment and Capital
Consumption Adjustment, Quarterly, 1979-2020
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Table IA1-7
provides price, costs and profit per unit of gross value added of nonfinancial
domestic corporate income for IVQ2007 and IIQ2020 in the upper block and for
IQ1980 and IVQ1993 in the lower block. Compensation of employees or labor costs
per unit of gross value added of nonfinancial domestic corporate income increased
from 0.551 in IVQ2007 to 0.722 in IIQ2020 in a fractured labor market but
increased from 0.320 in IQ1980 to 0.481 in IVQ1993 in a more vibrant labor
market. Unit nonlabor costs increased mildly from 0.259 per unit of gross value
added in IVQ2007 to 0.267 in IIQ2020 but increased from 0.116 in IQ1980 to 0.195
in IVQ1993 in an economy closer to full employment of resources. Profits after
tax with IVA and CCA per unit of gross value added of nonfinancial domestic
corporate income increased from 0.079 in IVQ2007 to 0.100 in IIQ2020 and from
0.027 in IQ1980 to 0.054 in IVQ1993.
Table IA1-7,
US, Price, Costs and Profit per Unit of Gross Value Added of Nonfinancial
Domestic Corporate Income
|
|
IVQ2007 |
IIQ2020 |
|
Price per
Unit of Real Gross Value Added of Nonfinancial Corporate Business |
0.921 |
1.108 |
|
Compensation
of Employees (Unit Labor Cost) |
0.551 |
0.722 |
|
Unit Nonlabor
Cost |
0.259 |
0.267 |
|
Consumption
of Fixed Capital |
0.135 |
0.206 |
|
Taxes on
Production and Imports less Subsidies plus Business Current Transfer Payments
(net) |
0.088 |
0.031 |
|
Net Interest
and Misc. Payments |
0.036 |
0.030 |
|
Corporate
Profits with IVA and CCA Adjustment (Unit Profits from Current Production) |
0.112 |
0.119 |
|
Taxes on
Corporate Income |
0.032 |
0.019 |
|
Profits after
Tax with IVA and CCA Adjustment |
0.079 |
0.100 |
|
|
IQ1980 |
IVQ1993 |
|
Price per
Unit of Real Gross Value Added of Nonfinancial Corporate Business |
0.487 |
0.755 |
|
Compensation
of Employees (Unit Labor Cost) |
0.320 |
0.481 |
|
Unit Nonlabor
Cost |
0.116 |
0.195 |
|
Consumption
of Fixed Capital |
0.060 |
0.096 |
|
Taxes on Production
and Imports less Subsidies plus Business Current Transfer Payments (net) |
0.039 |
0.075 |
|
Net Interest
and Misc. Payments |
0.017 |
0.024 |
|
Corporate
Profits with IVA and CCA Adjustment (Unit Profits from Current Production) |
0.052 |
0.080 |
|
Taxes on Corporate
Income |
0.024 |
0.025 |
|
Profits after
Tax with IVA and CCA Adjustment |
0.027 |
0.054 |
IVA: Inventory
Valuation Adjustment; CCA: Capital Consumption Adjustment
Source: US
Bureau of Economic Analysis http://bea.gov/iTable/index_nipa.cfm
Chart IA1-15
provides quarterly profits after tax with IVA and CCA per unit of gross value
added of nonfinancial domestic corporate income from 1980 to 2020. In an
environment of idle labor and other productive resources, nonfinancial
corporate income increased after tax profits with IVA and CCA per unit of gross
value added at a faster pace at a slower pace in the weak economy from IVQ2007
to IIQ2020 than in the vibrant expansion following the cyclical contractions of
the 1980s. There is strong downward pressure on profits in the global
recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. Part of the profits was
distributed as dividends and significant part was retained as undistributed
profits in the current economy cycle with frustrated investment decision.
Chart IA1-15, US, Profits after Tax with Inventory Valuation
Adjustment and Capital Consumption Adjustment per Unit of Gross Value Added of
Nonfinancial Domestic Corporate Income, 1980-2020
Source: US Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Corporate
profits with IVA and CCA decreased at 0.7 percent in IIIQ2019 and increased at
0.3 percent after taxes, as shown in Table IA1-8. Corporate profits with IVA and CCA increased
at 2.9 percent in IVQ2019 and increased at 1.8 percent after taxes. Corporate
profits with IVA and CCA decreased at 12.0 percent in IQ2020 and decreased at
11.0 percent after taxes. Corporate profits decreased at 10.3 percent in
IIQ2020 and decreased at 10.7 percent after taxes. Corporate profits with IVA
and CCA decreased at 19.3 percent in IIQ2020 relative to IIQ2019 and profits
after tax with IVA and CCA decreased 18.8 percent in IIQ2020 relative to IIQ2019
in the
global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. Net dividends
decreased at 1.5 percent in IIIQ2019. Net dividends increased at 0.6 percent in
IVQ2019. Net dividends increased at 1.7 percent in IQ2020. Net dividends
decreased at 1.1 percent in IIQ2020. Net dividends decreased 0.4 percent in IIQ2020
relative to a year earlier. Undistributed profits increased at 4.4 percent in
IIIQ2019. Undistributed profits
increased at 4.5 percent in IVQ2019. Undistributed profits decreased at 37.8
percent in IQ2020. Undistributed profits decreased at 43.8 percent in IIQ2020. Undistributed
profits decreased at 61.8 percent in IIQ2020 relative to IIQ2019.
Table IA1-8,
Quarterly Seasonally Adjusted Annual Equivalent Percentage Rates of Change of
Corporate Profits, ∆%
|
2018 |
2019 |
III Q219 |
IV 2019 |
IQ 2020 |
IIQ 2020 |
IIQ20/ IIQ19 |
|
|
Corporate
Profits with IVA and CCA |
6.1 |
0.3 |
-0.7 |
2.9 |
-12.0 |
-10.3 |
-19.3 |
|
Corporate
Income Taxes |
-9.1 |
5.6 |
-7.2 |
10.3 |
-18.2 |
-7.3 |
-22.3 |
|
After Tax
Profits with IVA and CCA |
8.7 |
-0.4 |
0.3 |
1.8 |
-11.0 |
-10.7 |
-18.8 |
|
Net Dividends |
9.4 |
-2.1 |
-1.5 |
0.6 |
1.7 |
-1.1 |
-0.4 |
|
Und Profits
with IVA and CCA |
7.0 |
3.7 |
4.4 |
4.5 |
-37.8 |
-43.8 |
-61.8 |
Source: US
Bureau of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
Table IA1-9 provides change from
prior quarter of the level of seasonally adjusted annual rates of US corporate
profits. There are three aspects.
First, there is fluctuation in corporate profits. Corporate
profits decreased at $16.7 billion in IIIQ2019. Corporate profits increased at
$64.8 billion in IVQ2019. Corporate profits decreased at $276.2 billion in
IQ2020. Corporate profits decreased at $208.9 billion in IIQ2020 in the
global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. Profits after tax
with IVA and CCA increased at $5.2 billion in IIIQ2019. Profits after tax with
IVA and CCA increased at $35.5 billion in IVQ2019. Profits after tax with IVA
and CCA decreased at $219.4 billion in IQ2020. Profits after tax with IVA and CCA decreased
at 190.1 percent in IIQ2020. Net dividends decreased at $20.8 billion in
IIIQ2019. Net dividends increased at $7.8 billion in IVQ2019. Net dividends
increased at $23.2 billion in IQ2020. Net dividends decreased at $15.0 billion
in IIQ2020. Undistributed corporate profits increased at $26.1 billion in
IIIQ2019. Undistributed profits increased at $27.7 billion in IVQ2019.
Undistributed profits decreased at $242.7 billion in IQ2020. Undistributed
corporate profits decreased at $175.1 billion in IIQ2020. Undistributed
corporate profits swelled 37.2 percent from $138.3 billion in IQ2007 to $189.3
billion in IIQ2020 and changed signs from minus $4.0 billion in current dollars
in IVQ2007. Net dividends decreased from $968.7 billion in IVQ2009 to $813.0
billion in IQ2020, increasing to $1,016.0 billion in IIQ2020, as corporations
distributed dividends to halt decrease in stock valuations in the
global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. Second,
sharp and continuing strengthening of the dollar, with recent depreciation/fluctuations
at the margin in global carry trades, is affecting balance sheets of US
corporations with foreign operations (https://www.fasb.org/summary/stsum52.shtml)
and the overall US economy. The bottom part of Table IA1-9 provides the
breakdown of corporate profits with IVA and CCA in domestic industries and the
rest of the world. Corporate profits
with IVA and CCA decreased at $16.7 billion in IIIQ2019. Profits from domestic
industries decreased at $25.0 billion and profits from nonfinancial business decreased
at $18.0 billion. Profits from the rest of the world increased at $8.3 billion.
Corporate profits with IVA and CCA increased at $64.8 billion in IVQ2019.
Profits from domestic industries increased at $62.7 billion and profits from
nonfinancial business increased at $46.0 billion. Profits from the rest of the
world increased at $2.1 billion. Corporate profits with IVA and CCA decreased
at $276.2 billion in IQ2020. Profits from domestic industries decreased at $232.7
billion and profits from nonfinancial business decreased at $190.5 billion.
Profits from the rest of the world decreased at $43.5 billion. Corporate
profits with IVA and CCA decreased at $208.9 billion in IIQ2020. Profits from
domestic industries decreased at $119.4 billion and profits from nonfinancial
business decreased at $145.9 billion. Profits from the rest of the world decreased
at $89.5 billion. Total corporate profits with IVA and CCA were $1826.1 billion
in IIQ2020 of which $1442.5 billion from domestic industries, or 79.0 percent
of the total, and $383.6 billion, or 21.0 percent, from the rest of the world.
Nonfinancial corporate profits of $984.8 billion account for 53.9 percent of
the total. Third, there is reduction in the use of corporate cash for
investment. Vipal Monga, David Benoit and Theo Francis, writing on “Companies
send more cash back to shareholders,” published on May 26, 2015 in the Wall
Street Journal (http://www.wsj.com/articles/companies-send-more-cash-back-to-shareholders-1432693805?tesla=y),
use data of a study by Capital IQ conducted for the Wall Street Journal.
This study shows that companies in the S&P 500 reduced investment in plant
and equipment to median 29 percent of operating cash flow in 2013 from 33
percent in 2003 while increasing dividends and buybacks to median 36 percent in
2013 from 18 percent in 2003.
Table IA1-9, Change
from Prior Quarter of Level of Seasonally Adjusted Annual Equivalent Rates of
Corporate Profits, Billions of Dollars
|
2018 |
2019 |
III Q2019 |
IV Q2019 |
IQ 2020 |
IIQ 2020 |
|
|
Corporate
Profits with IVA and CCA |
128.5 |
7.6 |
-16.7 |
64.8 |
-276.2 |
-208.9 |
|
Corporate
Income Taxes |
-28.4 |
15.8 |
-21.9 |
29.3 |
-56.7 |
-18.8 |
|
After Tax
Profits with IVA and CCA |
156.9 |
-8.3 |
5.2 |
35.5 |
-219.4 |
-190.1 |
|
Net Dividends |
119.7 |
-29.3 |
-20.8 |
7.8 |
23.2 |
-15.0 |
|
Und Profits
with IVA and CCA |
37.2 |
21.0 |
26.1 |
27.7 |
-242.7 |
-175.1 |
|
Corporate
Profits with IVA and CCA |
128.5 |
7.6 |
-16.7 |
64.8 |
-276.2 |
-208.9 |
|
Domestic
Industries |
113.1 |
14.6 |
-25.0 |
62.7 |
-232.7 |
-119.4 |
|
Financial |
6.1 |
38.0 |
-7.0 |
16.7 |
-42.2 |
26.5 |
|
Nonfinancial |
107.0 |
-23.3 |
-18.0 |
46.0 |
-190.5 |
-145.9 |
|
Rest of the
World |
15.3 |
-7.1 |
8.3 |
2.1 |
-43.5 |
-89.5 |
|
Receipts from
Rest of the World |
62.9 |
4.9 |
-2.2 |
3.5 |
-90.3 |
-134.5 |
|
Payments to
the Rest of the World |
47.5 |
12.0 |
-10.5 |
1.4 |
-46.8 |
-45.0 |
Source: Bureau
of Economic Analysis
https://apps.bea.gov/iTable/index_nipa.cfm
IID. United States
International Terms of Trade. Delfim Netto (1959) partly reprinted in Pelaez (1973)
conducted two classical nonparametric tests (Mann 1945, Wallis and Moore 1941;
see Kendall and Stuart 1968) with coffee-price data in the period of free
markets from 1857 to 1906 with the following conclusions (Pelaez, 1976a, 280):
“First, the null hypothesis of no trend was accepted
with high confidence; secondly, the null hypothesis of no oscillation was
rejected also with high confidence. Consequently, in the nineteenth century
international prices of coffee fluctuated but without long-run trend. This
statistical fact refutes the extreme argument of structural weakness of the
coffee trade.”
In his
classic work on the theory of international trade, Jacob Viner (1937, 563)
analyzed the “index of total gains from trade,” or “amount of gain per unit of
trade,” denoted as T:
T= (∆Pe/∆Pi)∆Q
Where ∆Pe
is the change in export prices, ∆Pi
is the change in import prices and ∆Q
is the change in export volume. Dorrance (1948, 52) restates “Viner’s index of
total gain from trade” as:
“What should be done is to
calculate an index of the value (quantity multiplied by price) of exports and
the price of imports for any country whose foreign accounts are to be analysed.
Then the export value index should be divided by the import price index. The
result would be an index which would reflect, for the country concerned, changes
in the volume of imports obtainable from its export income (i.e. changes in its
"real" export income, measured in import terms). The present writer
would suggest that this index be referred to as the ‘income terms of trade’
index to differentiate it from the other indexes at present used by
economists.”
What really matters for an export activity especially
during modernization is the purchasing value of goods that it exports in terms
of prices of imports. For a primary producing country, the purchasing power of
exports in acquiring new technology from the country providing imports is the
critical measurement. The barter terms of trade of Brazil improved from 1857 to
1906 because international coffee prices oscillated without trend (Delfim Netto
1959) while import prices from the United Kingdom declined at the rate of 0.5
percent per year (Imlah 1958). The accurate measurement of the opportunity
afforded by the coffee exporting economy was incomparably greater when
considering the purchasing power in British prices of the value of coffee
exports, or Dorrance’s (1948) income terms of trade.
The
conventional theory that the terms
of trade of Brazil deteriorated over the long term is without reality (Pelaez 1976a, 280-281):
“Moreover,
physical exports of coffee by Brazil increased at the high average rate of 3.5
per cent per year. Brazil's exchange receipts from coffee-exporting in sterling
increased at the average rate of 3.5 per cent per year and receipts in domestic
currency at 4.5 per cent per year. Great Britain supplied nearly all the
imports of the coffee economy. In the period of the free coffee market, British
export prices declined at the rate of 0.5 per cent per year. Thus, the income
terms of trade of the coffee economy improved at the relatively satisfactory
average rate of 4.0 per cent per year. This is only a lower bound of the rate
of improvement of the terms of trade. While the quality of coffee remained
relatively constant, the quality of manufactured products improved
significantly during the fifty-year period considered. The trade data and the
non-parametric tests refute conclusively the long-run hypothesis. The valid
historical fact is that the tropical export economy of Brazil experienced an
opportunity of absorbing rapidly increasing quantities of manufactures from the
"workshop" countries. Therefore, the coffee trade constituted a
golden opportunity for modernization in nineteenth-century Brazil.”
Imlah (1958) provides decline of British export prices
at 0.5 percent in the nineteenth century and there were no lost decades,
depressions or unconventional monetary policies in the highly dynamic economy
of England that drove the world’s growth impulse. Inflation in the United
Kingdom between 1857 and 1906 is measured by the composite price index of
O’Donoghue and Goulding (2004) at minus 7.0 percent or average rate of decline
of 0.2 percent per year.
Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:
“The major breakthroughs in the advance of
human knowledge, those that constituted dominant sources of sustained growth
over long periods and spread to a substantial part of the world, may be termed
epochal innovations. And the changing course of economic history can perhaps be
subdivided into economic epochs, each identified by the epochal innovation with
the distinctive characteristics of growth that it generated. Without
considering the feasibility of identifying and dating such economic epochs, we
may proceed on the working assumption that modern economic growth represents
such a distinct epoch - growth dating back to the late eighteenth century and
limited (except in significant partial effects) to
economically developed countries. These countries, so classified because they
have managed to take adequate advantage of the potential of modern technology, include
most of Europe, the overseas offshoots of Western Europe, and Japan—barely one
quarter of world population.”
Cameron
(1961) analyzes the mechanism by which the Industrial Revolution in Great
Britain spread throughout Europe and Cameron (1967) analyzes the financing by
banks of the Industrial Revolution in Great Britain. O’Donoghue and Goulding
(2004) provide consumer price inflation in England since 1750 and MacFarlane
and Mortimer-Lee (1994) analyze inflation in England over 300 years. Lucas (2004)
estimates world population and production since the year 1000 with sustained
growth of per capita incomes beginning to accelerate for the first time in
English-speaking countries and in particular in the Industrial Revolution in
Great Britain. The conventional theory is unequal distribution of the gains
from trade and technical progress between the industrialized countries and
developing economies (Singer 1950, 478):
“Dismissing, then, changes in productivity as a
governing factor in changing terms of trade, the following explanation presents
itself: the fruits of technical progress may be distributed either to producers
(in the form of rising incomes) or to consumers (in the form of lower prices).
In the case of manufactured commodities produced in more developed countries,
the former method, i.e., distribution to producers through higher incomes, was
much more important relatively to the second method, while the second method
prevailed more in the case of food and raw material production in the underdeveloped
countries. Generalizing, we may say -that technical progress in manufacturing
industries showed in a rise in incomes while technical progress in the
production of food and raw materials in underdeveloped countries showed in a
fall in prices”
Temin (1997, 79) uses a Ricardian trade
model to discriminate between two views on the Industrial Revolution with an
older view arguing broad-based increases in productivity and a new view
concentration of productivity gains in cotton manufactures and iron:
“Productivity advances in British
manufacturing should have lowered their prices relative to imports. They did.
Albert Imlah [1958] correctly recognized this ‘severe deterioration’ in the net
barter terms of trade as a signal of British success, not distress. It is no
surprise that the price of cotton manufactures fell rapidly in response to
productivity growth. But even the price of woolen manufactures, which were
declining as a share of British exports, fell almost as rapidly as the price of
exports as a whole. It follows, therefore, that the traditional ‘old-hat’ view
of the Industrial Revolution is more accurate than the new, restricted image.
Other British manufactures were not inefficient and stagnant, or at least, they
were not all so backward. The spirit that motivated cotton manufactures
extended also to activities as varied as hardware and haberdashery, arms, and
apparel.”
Phyllis
Deane (1968, 96) estimates growth of United Kingdom gross national product
(GNP) at around 2 percent per year for several decades in the nineteenth
century. The facts that the terms of trade of Great Britain deteriorated during
the period of epochal innovation and high rates of economic growth while the
income terms of trade of the coffee economy of nineteenth-century Brazil improved
at the average yearly rate of 4.0 percent from 1857 to 1906 disprove the
hypothesis of weakness of trade as an explanation of relatively lower income
and wealth. As Temin (1997) concludes, Britain did pass on lower prices and
higher quality the benefits of technical innovation. Explanation of late
modernization must focus on laborious historical research on institutions and
economic regimes together with economic theory, data gathering and measurement
instead of grand generalizations of weakness of trade and alleged neocolonial
dependence (Stein and Stein 1970, 134-5):
“Great Britain, technologically and
industrially advanced, became as important to the Latin American economy as to
the cotton-exporting southern United States. [After Independence in the
nineteenth century] Latin America fell back upon traditional export activities,
utilizing the cheapest available factor of production, the land, and the
dependent labor force.”
Summerhill (2015) contributes momentous
solid facts and analysis with an ideal method combining economic theory,
econometrics, international comparisons, data reconstruction and exhaustive
archival research. Summerhill (2015) finds that Brazil committed to service of
sovereign foreign and internal debt. Contrary to conventional wisdom, Brazil
generated primary fiscal surpluses during most of the Empire until 1889
(Summerhill 2015, 37-8, Figure 2.1). Econometric tests by Summerhill (2015,
19-44) show that Brazil’s sovereign debt was sustainable. Sovereign credibility
in the North-Weingast (1989) sense spread to financial development that
provided the capital for modernization in England and parts of Europe (see
Cameron 1961, 1967). Summerhill (2015, 3, 194-6, Figure 7.1) finds that
“Brazil’s annual cost of capital in London fell from a peak of 13.9 percent in
1829 to only 5.12 percent in 1889. Average rates on secured loans in the
private sector in Rio, however, remained well above 12 percent through 1850.”
Financial development would have financed diversification of economic
activities, increasing productivity and wages and ensuring economic growth.
Brazil restricted creation of limited liability enterprises (Summerhill 2015,
151-82) that prevented raising capital with issue of stocks and corporate
bonds. Cameron (1961) analyzed how the industrial revolution in England spread
to France and then to the rest of Europe. The Société Générale de Crédit Mobilier of Émile and Isaac Péreire
provided the “mobilization of credit” for the new economic activities (Cameron
1961). Summerhill (2015, 151-9) provides facts and analysis demonstrating that
regulation prevented the creation of a similar vehicle for financing
modernization by Irineu Evangelista de
Souza, the legendary Visconde de Mauá.
Regulation also prevented the use of negotiable bearing notes of the Caisse Générale of Jacques Lafitte
(Cameron 1961, 118-9). The government also restricted establishment and
independent operation of banks (Summerhill 2015, 183-214). Summerhill (2015,
198-9) measures concentration in banking that provided economic rents or a
social loss. The facts and analysis of Summerhill (2015) provide convincing
evidence in support of the economic theory of regulation, which postulates that
regulated entities capture the process of regulation to promote their
self-interest. There appears to be a case that excessively centralized
government can result in regulation favoring private instead of public
interests with adverse effects on economic activity. The contribution of
Summerhill (2015) explains why Brazil did not benefit from trade as an engine
of growth—as did regions of recent
settlement in the vision of nineteenth-century trade and development of
Ragnar Nurkse (1959)—partly because of restrictions on financing and
incorporation. Professor Rondo E. Cameron, in his memorable A Concise Economic History of the World
(Cameron 1989, 307-8), finds that “from a broad spectrum of possible forms of
interaction between the financial sector and other sectors of the economy that
requires its services, one can isolate three type-cases: (1) that in which the
financial sector plays a positive, growth-inducing role; (2) that in which the
financial sector is essentially neutral or merely permissive; and (3) that in
which inadequate finance restricts or hinders industrial and commercial
development.” Summerhill (2015) proves exhaustively that Brazil failed to
modernize earlier because of the restrictions of an inadequate institutional
financial arrangement plagued by regulatory capture for self-interest.
There is
analysis of the origins of current tensions in the world economy (Pelaez and
Pelaez, Financial Regulation after the Global Recession (2009a), Regulation
of Banks and Finance (2009b), International Financial Architecture
(2005), The Global Recession Risk (2007), Globalization and the State Vol. I (2008a), Globalization and the State Vol. II (2008b), Government
Intervention in Globalization (2008c)).
The
US Bureau of Economic Analysis (BEA) measures the terms of trade index of the
United States quarterly since 1947 and annually since 1929. Chart IID-1
provides the terms of trade of the US quarterly since 1947 with significant
long-term deterioration from 150.474 in IQ1947 to 107.721 in IIQ2020,
decreasing from 109.980 in IVQ2019 and increasing from 109.680 in IQ2020.
Significant part of the deterioration occurred from the 1960s to the 1980s
followed by some recovery and then stability.
Chart IID-1,
United States Terms of Trade Quarterly Index 1947-2020
Source:
Bureau of Economic Analysis
Chart
IID-1A provides the annual US terms of trade from 1929 to 2019. The index fell
from 142.590 in 1929 to 109.740 in 2019. There is decline from 1971 to a much
lower plateau.
Chart
IID-1A, United States Terms of Trade Annual Index 1929-2019, Annual
Source:
Bureau of Economic Analysis
Chart IID-1B provides the US terms of trade
index, index of terms of trade of nonpetroleum goods and index of terms of
trade of goods. The terms of trade of nonpetroleum goods dropped sharply from
the mid-1980s to 1995, recovering significantly until 2014, dropping and then
recovering again into 2019. There is relative stability in the terms of trade
of nonpetroleum goods from 1967 to 2019 but sharp deterioration in the overall
index and the index of goods.
Chart
IID-1B, United States Terms of Trade Annual Indexes 1967-2019, Annual
Source:
Bureau of Economic Analysis
The US Bureau of
Labor Statistics (BLS) provides measurements of US international terms of
trade. The measurement by the BLS is as follows (https://www.bls.gov/mxp/terms-of-trade.htm):
“BLS terms of trade indexes measure the change in the U.S. terms
of trade with a specific country, region, or grouping over time. BLS terms of
trade indexes cover the goods sector only.
To calculate the U.S. terms of trade index, take the U.S.
all-export price index for a country, region, or grouping, divide by the
corresponding all-import price index and then multiply the quotient by 100.
Both locality indexes are based in U.S. dollars and are rounded to the tenth
decimal place for calculation. The locality indexes are normalized to 100.0 at
the same starting point.
TTt=(LODt/LOOt)*100,
where
TTt=Terms of Trade Index at time t
LODt=Locality of Destination Price Index at time t
LOOt=Locality of Origin Price Index at time t
The terms of trade index measures whether the U.S. terms of trade are improving
or deteriorating over time compared to the country whose price indexes are the
basis of the comparison. When the index rises, the terms of trade are said to
improve; when the index falls, the terms of trade are said to deteriorate. The
level of the index at any point in time provides a long-term comparison; when
the index is above 100, the terms of trade have improved compared to
the base period, and when the index is below 100, the terms of trade have
deteriorated compared to the base period.”
Chart IID-3 provides the BLS terms of
trade of the US with Canada. The index increases from 100.0 in Dec 2017 to
117.8 in Dec 2018 and decreases to 104.0 in Feb 2020. The index increases to
121.5 in Apr 2020. The index decreased to 101.6 in Aug 2020.
Chart IID-3,
US Terms of Trade, Monthly, All Goods, Canada, NSA, Dec 2017=100
Source:
Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Chart IID-4 provides
the BLS terms of trade of the US with the European Union. There is improvement from
100.0 in Dec 2017 to 102.8 in Jan 2020 followed by decrease to 100.2 in Aug
2020.
Chart IID-4,
US Terms of Trade, Monthly, All Goods, European Union, NSA, Dec 2017=100
Source:
Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Chart
IID-5 provides the BLS terms of trade of the US with Mexico. There is
deterioration from 100.0 in Dec 2017 to 96.8 in Aug 2020.
Chart IID-5,
US Terms of Trade, Monthly, All Goods, Mexico, NSA, Dec 2017=100
Source:
Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Chart IID-6 provides the BLS terms of trade of the US with China. There is deterioration
from 100.0 in Dec 2017 to 98.0 in Sep 2018, improvement to 100.6 in Apr 2019
with deterioration to 99.4 in Aug 2020.
Chart IID-6,
US Terms of Trade, Monthly, All Goods, China, NSA, Dec 2017=100
Source:
Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Chart IID-7 provides the BLS terms of trade
of the US with Japan. There is deterioration from 100.0 in Dec 2017 to 99.2 in
Dec 2019 and deterioration to 97.0 in Aug 2020.
Chart IID-7,
US Terms of Trade, Monthly, All Goods, Japan, NSA, Dec 2017=100
Source:
Bureau of Labor Statistics https://www.bls.gov/mxp/data.htm
Manufacturing is
underperforming in the lost cycle of the global recession. Manufacturing (NAICS)
in Aug 2020 is lower by 9.1 percent relative to the peak in Jun 2007, as shown
in Chart V-3A. Manufacturing (SIC) in Aug 2020 at 99.2841 is lower by 11.6
percent relative to the peak at 112.3113 in Jun 2007. There is cyclical
uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar
behavior in manufacturing. There is classic research on analyzing deviations of
output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975,
Sargent and Sims 1977). The long-term trend is growth of manufacturing at
average 2.9 percent per year from Aug 1919 to Aug 2020. Growth at 2.9 percent
per year would raise the NSA index of manufacturing output (SIC, Standard
Industrial Classification) from 108.2987 in Dec 2007 to 155.5554 in Aug 2020.
The actual index NSA in Aug 2020 is 99.2841 which is 36.2 percent below trend.
The underperformance of manufacturing in Mar-Aug 2020 originates partly in the
earlier global recession augmented by the current global recession with output
in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19.
Manufacturing grew at the average annual rate of 3.3 percent between Dec 1986
and Dec 2006. Growth at 3.3 percent per year would raise the NSA index of
manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in
Dec 2007 to 163.3909 in Aug 2020. The actual index NSA in Aug 2020 is 99.2841,
which is 39.2 percent below trend. Manufacturing output grew at average 1.7
percent between Dec 1986 and Aug 2020. Using trend growth of 1.7 percent per
year, the index would increase to 134.0774 in Aug 2020. The output of
manufacturing at 99.2841 in Aug 2020 is 26.0 percent below trend under this
alternative calculation. Using the NAICS (North American Industry Classification
System), manufacturing output fell from the high of 110.5147 in Jun 2007 to the
low of 86.3800 in Apr 2009 or 21.8 percent. The NAICS manufacturing index
increased from 86.3800 in Apr 2009 to 100.4257 in Aug 2020 or 16.3 percent. The
NAICS manufacturing index increased at the annual equivalent rate of 3.5
percent from Dec 1986 to Dec 2006. Growth at 3.5 percent would increase the
NAICS manufacturing output index from 106.6777 in Dec 2007 to 164.9372 in Aug
2020. The NAICS index at 100.4257 in Aug 2020 is 39.1 below trend. The NAICS
manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999
to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output
index from 106.6777 in Dec 2007 to 132.0705 in Aug 2020. The NAICS index at
100.4257 in Aug 2020 is 24.0 percent below trend under this alternative
calculation.
Chart V-3A,
United States Manufacturing NSA, Dec 2007 to Aug 2020
Board of
Governors of the Federal Reserve System
https://www.federalreserve.gov/releases/g17/Current/default.htm
Chart V-3A,
United States Manufacturing (NAICS) NSA, Jun 2007 to Aug 2020
Board of
Governors of the Federal Reserve System
https://www.federalreserve.gov/releases/g17/Current/default.htm
Chart V-3B
provides the civilian noninstitutional population of the United States, or
those available for work. The civilian noninstitutional population increased
from 231.713 million in Jun 2007 to 260.558 million in Aug 2020 or 28.845
million.
Chart V-3B,
United States, Civilian Noninstitutional Population, Million, NSA, Jan 2007 to
Aug 2020
Source: US
Bureau of Labor Statistics
Chart V-3C,
United States, Payroll Manufacturing Jobs, NSA, Jan 2007 to Aug 2020, Thousands
Source: US
Bureau of Labor Statistics
Chart V-3D provides the index of US
manufacturing (NAICS) from Jan 1972 to Aug 2020. The index continued increasing
during the decline of manufacturing jobs after the early 1980s. There are
likely effects of changes in the composition of manufacturing with also changes
in productivity and trade. There is sharp decline in the global recession, with output in the US reaching a
high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19
event. There is initial recovery in May-Aug 2020.
Chart V-3D,
United States Manufacturing (NAICS) NSA, Jan 1972 to Aug 2020
Source:
Board of Governors of the Federal Reserve System
https://www.federalreserve.gov/releases/g17/Current/default.htm
Chart V-3E provides
the US noninstitutional civilian population, or those in condition of working,
from Jan 1948, when first available, to Aug 2020. The noninstitutional civilian
population increased from 170.042 million in Jun 1981 to 260.558 million in Aug
2020, or 90.516 million.
Chart V-3E,
United States, Civilian Noninstitutional Population, Million, NSA, Jan 1948 to
Aug 2020
Source: US
Bureau of Labor Statistics
Chart V-3F,
United States, Payroll Manufacturing Jobs, NSA, Jan 1939 to Aug 2020, Thousands
Source: US
Bureau of Labor Statistics
Table
I-13A provides national income without capital consumption by industry with
estimates based on the Standard Industrial Classification (SIC). The share of
agriculture declines from 8.7 percent in 1948 to 1.7 percent in 1987 while the
share of manufacturing declines from 30.2 percent in 1948 to 19.4 percent in
1987. Colin Clark (1957) pioneered the analysis of these trends over long
periods.
Table I-13A,
US, National Income without Capital Consumption Adjustment by Industry, Annual Rates,
Billions of Dollars, % of Total
|
1948 |
% Total |
1987 |
% Total |
|
|
National
Income WCCA |
249.1 |
100.0 |
4,029.9 |
100.0 |
|
Domestic
Industries |
247.7 |
99.4 |
4,012.4 |
99.6 |
|
Private
Industries |
225.3 |
90.4 |
3,478.8 |
86.3 |
|
Agriculture |
21.7 |
8.7 |
66.5 |
1.7 |
|
Mining |
5.8 |
2.3 |
42.5 |
1.1 |
|
Construction |
11.1 |
4.5 |
201.0 |
5.0 |
|
Manufacturing |
75.2 |
30.2 |
780.2 |
19.4 |
|
Durable Goods |
37.5 |
15.1 |
458.4 |
11.4 |
|
Nondurable
Goods |
37.7 |
15.1 |
321.8 |
8.0 |
|
Transportation
PUT |
21.3 |
8.5 |
317.7 |
7.9 |
|
Transportation |
13.8 |
5.5 |
127.2 |
3.2 |
|
Communications |
3.8 |
1.5 |
96.7 |
2.4 |
|
Electric,
Gas, SAN |
3.7 |
1.5 |
93.8 |
2.3 |
|
Wholesale
Trade |
17.1 |
6.9 |
283.1 |
7.0 |
|
Retail Trade |
28.8 |
11.6 |
400.4 |
9.9 |
|
Finance, INS,
RE |
22.9 |
9.2 |
651.7 |
16.2 |
|
Services |
21.4 |
8.6 |
735.7 |
18.3 |
|
Government |
22.4 |
9.0 |
533.6 |
13.2 |
|
Rest of World |
1.5 |
0.6 |
17.5 |
0.4 |
|
|
2003.9 |
11.6 |
2016.3 |
11.5 |
|
|
252.6 |
1.5 |
257.9 |
1.5 |
Notes: Using
1972 Standard Industrial Classification (SIC). Percentages Calculates from
Unrounded Data; WCCA: Without Capital Consumption Adjustment by Industry; RE:
Real Estate; PUT: Public Utilities; SAN: Sanitation
Source: US
Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Table
I-13B provides national income without capital consumption estimated based on
the 2012 North American Industry Classification (NAICS). The share of manufacturing
fell from 14.9 percent in 1998 to 9.5 percent in 2018.
Table I-13B,
US, National Income without Capital Consumption Adjustment by Industry,
Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total
|
1998 |
% Total |
2018 |
% Total |
|
|
National
Income WCCA |
7,744.4 |
100.0 |
17,136.5 |
100.0 |
|
Domestic
Industries |
7,727.0 |
99.8 |
16,868.6 |
98.4 |
|
Private
Industries |
6,793.3 |
87.7 |
14,889.6 |
86.9 |
|
Agriculture |
72.7 |
0.9 |
119.7 |
0.7 |
|
Mining |
74.2 |
1.0 |
202.7 |
1.2 |
|
Utilities |
134.4 |
1.7 |
157.7 |
0.9 |
|
Construction |
379.2 |
4.9 |
902.5 |
5.3 |
|
Manufacturing |
1156.4 |
14.9 |
1635.3 |
9.5 |
|
Durable Goods |
714.9 |
9.2 |
964.9 |
5.6 |
|
Nondurable
Goods |
441.5 |
5.7 |
670.4 |
3.9 |
|
Wholesale
Trade |
512.8 |
6.6 |
958.2 |
5.6 |
|
Retail Trade |
610.0 |
7.9 |
1124.1 |
6.6 |
|
Transportation
& WH |
246.1 |
3.2 |
554.4 |
3.2 |
|
Information |
294.3 |
3.8 |
629.7 |
3.7 |
|
Finance,
Insurance, RE |
1280.9 |
16.5 |
3058.8 |
17.8 |
|
Professional
& Business Services |
889.8 |
11.5 |
2522.6 |
14.7 |
|
Education,
Health Care |
607.1 |
7.8 |
1764.8 |
10.3 |
|
Arts,
Entertainment |
290.5 |
3.8 |
756.6 |
4.4 |
|
Other Services |
244.9 |
3.3 |
502.5 |
2.9 |
|
Government |
933.7 |
12.1 |
1979.0 |
11.5 |
|
Rest of the
World |
17.4 |
0.2 |
267.9 |
1.6 |
Notes:
Estimates based on 2012 North American Industry Classification System (NAICS).
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
© Carlos M. Pelaez, 2009,
2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.
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