Sunday, April 30, 2017

Dollar Devaluation, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, IMF View of World Economy and Finance, Stagnating Real Private Fixed Investment, United States Housing, Decline of United States Homeownership, World Cyclical Slow Growth and Global Recession Risk: Part I

 

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Dollar Devaluation, Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend, IMF View of World Economy and Finance, Stagnating Real Private Fixed Investment, United States Housing, Decline of United States Homeownership, World Cyclical Slow Growth and Global Recession Risk

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

I Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend

IA Mediocre Cyclical United States Economic Growth

IA1 Stagnating Real Private Fixed Investment

II IMF View of World Economy and Finance

IIA United States Housing Collapse

IIA1 Sales of New Houses

IIA2 United States House Prices

IIB Decline of United States Homeownership

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

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

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during the Debt Crisis of the 1980s

I Mediocre Cyclical United States Economic Growth with GDP Two Trillion Dollars below Trend. Section IA Mediocre Cyclical United States Economic Growth provides the analysis of long-term and cyclical growth of GDP in the US with GDP two trillion dollars or 14.1 percent below trend. Section IA1 Stagnating Real Private Fixed Investment analyzes weakness in investment. There is socio-economic stress in the combination of adverse events and cyclical performance:

Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.1 percent on average in the cyclical expansion in the 31 quarters from IIIQ2009 to IQ2017. 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 first estimate of GDP for IQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp1q17_adv.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 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/04/mediocre-cyclical-economic-growth-with.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.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 and at 7.8 percent from IQ1983 to IVQ1983 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/04/mediocre-cyclical-economic-growth-with.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.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 IQ2017 would have accumulated to 31.4 percent. GDP in IQ2017 would be $19,699.2 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2856.8 billion than actual $16,842.4 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.6 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/04/twenty-three-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html). US GDP in IQ2017 is 14.5 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,842.4 billion in IQ2017 or 12.3 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Mar 1919 to Mar 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 144.8512 in Mar 2017. The actual index NSA in Mar 2017 is 103.4144, which is 28.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Mar 2017. Using trend growth of 2.1 percent per year, the index would increase to 131.1817 in Mar 2017. The output of manufacturing at 103.4144 in Mar 2017 is 21.2 percent below trend under this alternative calculation.

The economy of the US can be summarized in growth of economic activity or GDP as fluctuating from mediocre growth of 2.5 percent on an annual basis in 2010 to 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014 and 2.6 percent in 2015. GDP growth was 1.6 percent in 2016. The following calculations show that actual growth is around 2.1 percent per year. The rate of growth of 1.3 percent in the entire cycle from 2007 to 2016 is well below 3 percent per year in trend from 1870 to 2010, which the economy of the US always attained for entire cycles in expansions after events such as wars and recessions (Lucas 2011May). Revisions and enhancements of United States GDP and personal income accounts by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) provides valuable information on long-term growth and cyclical behavior. Table Summary provides relevant data.

Table Summary, Long-term and Cyclical Growth of GDP, Real Disposable Income and Real Disposable Income per Capita

 

GDP

  

Long-Term

    

1929-2016

3.2

  

1947-2016

3.2

  

Whole Cycles

    

1980-1989

3.5

  

2006-2016

1.3

  

2007-2016

1.3

  

Cyclical Contractions ∆%

    

IQ1980 to IIIQ1980, IIIQ1981 to IVQ1982

-4.7

  

IVQ2007 to IIQ2009

-4.2

  

Cyclical Expansions Average Annual Equivalent ∆%

    

IQ1983 to IVQ1985

IQ1983-IQ1986

IQ1983-IIIQ1986

IQ1983-IVQ1986

IQ1983-IQ1987

IQ1983-IIQ1987

IQ1983-IIIQ1987

IQ1983 to IVQ1987

IQ1983 to IQ1988

IQ1983 to IIQ1988

IQ1983 to IIIQ1988

IQ1983 to IVQ1988

IQ1983 to IQ1989

IQ1983 to IIQ1989

IQ1983 to IIIQ1989

IQ1983 to IVQ1989

IQ1983 to IQ1990

IQ1983 to IIQ1990

IQ1983 to IIIQ1990

5.9

5.7

5.4

5.2

5.0

5.0

4.9

5.0

4.9

4.9

4.8

4.8

4.8

4.7

4.7

4.5

4.5

4.4

4.3

  

First Four Quarters IQ1983 to IVQ1983

7.8

  

IIIQ2009 to IQ2017

2.1

  

First Four Quarters IIIQ2009 to IIQ2010

2.7

  
 

Real Disposable Income

Real Disposable Income per Capita

Long-Term

    

1929-2016

3.2

2.0

1947-1999

3.7

2.3

Whole Cycles

    

1980-1989

3.5

2.6

2006-2016

1.8

1.0

Source: Bureau of Economic Analysis

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

The revisions and enhancements of United States GDP and personal income accounts by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) also provide critical information in assessing the current rhythm of US economic growth. The economy appears to be moving at a pace around 2.1 percent per year. Table Summary GDP provides the data.

1. Average Annual Growth in the Past Twenty-One Quarters. GDP growth in the four quarters of 2012, the four quarters of 2013, the four quarters of 2014, the four quarters of Q2015, the four quarters of 2016 and the first quarter of 2017 accumulated to 10.7 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IQ2017 of $16,842.4 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/21: {[($16,842.4/$15,190.3)4/21 -1]100 = 2.0 percent}.

2. Average Annual Growth in the Past Four Quarters. GDP growth in the four quarters from IQ2016 to IQ2017 accumulated to 1.9 percent that is equivalent to 1.9 percent in a year. This is obtained by dividing GDP in IQ2017 of $16,842.4 billion by GDP in IQ206 of $16,525.0 billion and compounding by 4/4: {[($16,842.4/$16,525.0)4/4 -1]100 = 1.9%}. The US economy grew 1.9 percent in IQ2017 relative to the same quarter a year earlier in IQ2016. Growth was at annual equivalent 4.0 percent in IIQ2014 and 5.0 percent IIIQ2014 and only at 2.3 percent in IVQ2014. GDP grew at annual equivalent 2.0 percent in IQ2015, 2.6 percent in IIQ2015, 2.0 percent in IIIQ2015 and 0.9 percent in IVQ2015. GDP grew at annual equivalent 0.8 percent in IQ2016 and at 1.4 percent annual equivalent in IIQ2016. GDP increased at 3.5 percent annual equivalent in IIIQ2016 and at 2.1 percent in IVQ2016. Another important revelation of the revisions and enhancements is that GDP was flat in IVQ2012, which is in the borderline of contraction, and negative in IQ2014. US GDP fell 0.3 percent in IQ2014. The rate of growth of GDP in the revision of IIIQ2013 is 3.1 percent in seasonally adjusted annual rate (SAAR).

Table Summary GDP, US, Real GDP and Percentage Change Relative to IVQ2007 and Prior Quarter, Billions Chained 2009 Dollars and ∆%

 

Real GDP, Billions Chained 2009 Dollars

∆% Relative to IVQ2007

∆% Relative to Prior Quarter

∆%
over
Year Earlier

IVQ2007

14,991.8

NA

0.4

1.9

IVQ2011

15,190.3

1.3

1.1

1.7

IQ2012

15,291.0

2.0

0.7

2.8

IIQ2012

15,362.4

2.5

0.5

2.5

IIIQ2012

15,380.8

2.6

0.1

2.4

IVQ2012

15,384.3

2.6

0.0

1.3

IQ2013

15,491.9

3.3

0.7

1.3

IIQ2013

15,521.6

3.5

0.2

1.0

IIIQ2013

15,641.3

4.3

0.8

1.7

IVQ2013

15,793.9

5.4

1.0

2.7

IQ2014

15,747.0

5.0

-0.3

1.6

IIQ2014

15,900.8

6.1

1.0

2.4

IIIQ2014

16,094.5

7.4

1.2

2.9

IVQ2014

16,186.7

8.0

0.6

2.5

IQ2015

16,269.0

8.5

0.5

3.3

IIQ2015

16,374.2

9.2

0.6

3.0

IIIQ2015

16,454.9

9.8

0.5

2.2

IVQ2015

16,490.7

10.0

0.2

1.9

IQ2016

16,525.0

10.2

0.2

1.6

IIQ2016

16,583.1

10.6

0.4

1.3

IIIQ2016

16,727.0

11.6

0.9

1.7

IVQ2016

16,813.3

12.1

0.5

2.0

IQ2017

16,842.4

12.3

0.2

1.9

Cumulative ∆% IQ2012 to IQ2017

10.9

  

11.0

  

Annual Equivalent ∆%

2.0

  

2.0

  

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

Chart GDP of the US Bureau of Economic Analysis provides the rates of growth of GDP at SAAR (seasonally adjusted annual rate) in the 16 quarters from IIQ2013 to IQ2017. Growth has been fluctuating.

Chart GDP, Seasonally Adjusted Quarterly Rates of Growth of United States GDP, ∆%

Source: US Bureau of Economic Analysis

http://www.bea.gov/newsreleases/national/gdp/gdp_glance.htm

Historical parallels are instructive but have all the limitations of empirical research in economics. The more instructive comparisons are not with the Great Depression of the 1930s but rather with the recessions in the 1950s, 1970s and 1980s. The growth rates and job creation in the expansion of the economy away from recession are subpar in the current expansion compared to others in the past. Four recessions are initially considered, following the reference dates of the National Bureau of Economic Research (NBER) (http://www.nber.org/cycles/cyclesmain.html ): IIQ1953-IIQ1954, IIIQ1957-IIQ1958, IIIQ1973-IQ1975 and IQ1980-IIIQ1980. The data for the earlier contractions illustrate that the growth rate and job creation in the current expansion are inferior. The sharp contractions of the 1950s and 1970s are considered in Table I-1, showing the Bureau of Economic Analysis (BEA) quarter-to-quarter, seasonally adjusted (SA), yearly-equivalent growth rates of GDP. The recovery from the recession of 1953 consisted of four consecutive quarters of high percentage growth rates from IIIQ1954 to IIIQ1955: 4.6, 8.0, 11.9 and 6.7. The recession of 1957 was followed by four consecutive high percentage growth rates from IIIQ1958 to IIQ1959: 9.6, 9.7, 7.7 and 10.1. The recession of 1973-1975 was followed by high percentage growth rates from IIQ1975 to IQ1976: 3.1, 6.8, 5.5 and 9.3. The disaster of the Great Inflation and Unemployment of the 1970s, which made stagflation notorious, is even better in growth rates during the expansion phase in comparison with the current slow-growth recession.

Table I-1, US, Seasonally Adjusted Quarterly Percentage Growth Rates in Annual Equivalent of GDP in Cyclical Recessions and Following Four Quarter Expansions ∆%

 

IQ

IIQ

IIIQ

IV

R IIQ1953-IIQ1954

        

1953

    

-2.2

-5.9

1954

-1.8

      

E IIIQ1954-IIQ1955

        

1954

    

4.6

8.0

1955

11.9

6.7

    

R IIIQ1957-IIQ1958

        

1957

      

-4.0

1958

-10.0

      

E IIIQ1958-IIQ1959

        

1958

    

9.6

9.7

1959

7.7

10.1

    

R IVQ1969-IV1970

        

1969

      

-1.7

1970

-0.7

      

E IIQ1970-IQ1971

        

1970

  

0.7

3.6

-4.0

1971

11.1

      

R IVQ1973-IQ1975

        

1973

      

3.8

1974

-3.3

1.1

-3.8

-1.6

1975

-4.7

      

E IIQ1975-IQ1976

        

1975

  

3.1

6.8

5.5

1976

9.3

      

R IQ1980-IIIQ1980

        

1980

1.3

-7.9

-0.6

  

R IQ1981-IVQ1982

        

1981

8.5

-2.9

4.7

-4.6

1982

-6.5

2.2

-1.4

0.4

E IQ1983-IVQ1983

        

1983

5.3

9.4

8.1

8.5

R IVQ2007-IIQ2009

        

2008

-2.7

2.0

-1.9

-8.2

2009

-5.4

-0.5

    

E IIIQ2009-IIQ2010

        

2009

    

1.3

3.9

2010

1.7

3.9

    

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

The NBER dates another recession in 1980 that lasted about half a year. If the two recessions from IQ1980s to IIIQ1980 and IIIQ1981 to IVQ1982 are combined, the impact of lost GDP of 4.7 percent is more comparable to the latest revised 4.2 percent drop of the recession from IVQ2007 to IIQ2009. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Table I-2 provides the Bureau of Economic Analysis (BEA) quarterly growth rates of GDP in SA yearly equivalents for the recessions of 1981 to 1982 and 2007 to 2009, using the latest major revision published on Jul 27, 2016 and the first estimate for IQ2017 GDP (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp1q17_adv.pdf), which are available in the dataset of the US Bureau of Economic Analysis (http://www.bea.gov/iTable/index_nipa.cfm). There were four quarters of contraction in 1981-1982 ranging in rate from -1.4 percent to -6.5 percent and five quarters of contraction in 2007-2009 ranging in rate from -0.5 percent to -8.2 percent. The striking difference is that in the first thirty-one quarters of expansion from IQ1983 to IIIQ1990, shown in Table I-2 in relief, GDP grew at the high quarterly percentage growth rates of 5.3, 9.4, 8.1, 8.5, 8.2, 7.2, 4.0, 3.2, 4.0, 3.7, 6.4, 3.0, 3.8, 1.9, 4.1, 2.1, 2.8, 4.6, 3.7, 6.8, 2.3, 5.4, 2.3, 5.4, 4.1, 3.2, 3.0, 0.9, 4.5, 1.6, 0.1, minus 3.4 and minus 1.9. 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). Table III-1 shows weaker performance in IIQ1990 and IIIQ1990 and contractions of 3.4 percent in IVQ1990 and 1.9 percent in IQ1991. In contrast, the percentage growth rates in the first thirty-one quarters of expansion from IIIQ2009 to IQ2017 shown in relief in Table I-2 were mediocre: 1.3, 3.9, 1.7, 3.9, 2.7, 2.5, -1.5, 2.9, 0.8, 4.6, 2.7, 1.9, 0.5, 0.1, 2.8, 0.8, 3.1, 4.0, minus 1.2, 4.0, 5.0, 2.3, 2.0, 2.6, 2.0, 0.9, 0.8, 1.4, 3.5, 2.1 and 0.7. Economic growth and employment creation continued at slow rhythm during 2012 and in 2013-2016 while much stronger growth would be required in movement to full employment. The cycle is now long by historical standards and growth rates are typically weaker in the final periods of cyclical expansions.

Table I-2, US, Quarterly Growth Rates of GDP, % Annual Equivalent SA

Q

1981

1982

1983

1984

2008

2009

2010

I

8.5

-6.5

5.3

8.2

-2.7

-5.4

1.7

II

-2.9

2.2

9.4

7.2

2.0

-0.5

3.9

III

4.7

-1.4

8.1

4.0

-1.9

1.3

2.7

IV

-4.6

0.4

8.5

3.2

-8.2

3.9

2.5
       

1985

    

2011

I

      

4.0

    

-1.5

II

      

3.7

    

2.9

III

      

6.4

    

0.8

IV

      

3.0

    

4.6
       

1986

    

2012

I

      

3.8

    

2.7

II

      

1.9

    

1.9

III

      

4.1

    

0.5

IV

      

2.1

    

0.1

       

1987

    

2013

I

      

2.8

    

2.8

II

      

4.6

    

0.8

III

      

3.7

    

3.1

IV

      

6.8

    

4.0
       

1988

    

2014

I

      

2.3

    

-1.2

II

      

5.4

    

4.0

III

      

2.3

    

5.0

IV

      

5.4

    

2.3
       

1989

    

2015

I

      

4.1

    

2.0

II

      

3.2

    

2.6

III

      

3.0

    

2.0

IV

      

0.9

    

0.9
       

1990

    

2016

I

      

4.5

    

0.8

II

      

1.6

    

1.4

III

      

0.1

    

3.5

IV

      

-3.4

    

2.1
       

1991

    

2017

I

      

-1.9

    

0.7

II

      

3.1

      

III

      

1.9

      

iv

      

1.8

      

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

Chart I-1 of the Bureau of Economic Analysis (BEA) provides strong growth of real GDP in the US between 1929 and 1999 at the yearly average rate of 3.5 percent. There is an evident acceleration of the rate of GDP growth in the 1990s as shown by a much sharper slope of the growth curve. Cobet and Wilson (2002) define labor productivity as the value of manufacturing output produced per unit of labor input used (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). Between 1950 and 2000, labor productivity in the US grew less rapidly than in Germany and Japan. The major part of the increase in productivity in Germany and Japan occurred between 1950 and 1973 while the rate of productivity growth in the US was relatively subdued in several periods. While Germany and Japan reached their highest growth rates of productivity before 1973, the US accelerated its rate of productivity growth in the second half of the 1990s. Between 1950 and 2000, the rate of productivity growth in the US of 2.9 percent per year was much lower than 6.3 percent in Japan and 4.7 percent in Germany. Between 1995 and 2000, the rate of productivity growth of the US of 4.6 percent exceeded that of Japan of 3.9 percent and the rate of Germany of 2.6 percent.

Chart I-1, US, Real GDP 1929-1999

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

Chart I-1A provides real GDP annually from 1929 to 2016. Growth after the global recession from IVQ2007 to IIQ2009 has not been sufficiently high to compensate for the contraction as it had in past economic cycles. The drop of output in the recession from IVQ2007 to IIQ2009 has been followed by anemic recovery compared with return to trend at 3.0 percent from 1870 to 2010 after events such as wars and recessions (Lucas 2011May) and a standstill that can lead to growth recession, or low rates of economic growth. The expansion is relatively long compared to earlier expansion and there could be even another contraction or conventional recession in the future. The average rate of growth from 1947 to 2016 is 3.2 percent. The average growth rate from IV2007 to IQ2017 is only 1.3 percent with 2.8 percent annual equivalent from the end of the recession in IVQ2001 to the end of the expansion in IVQ2007. 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 IQ2017 would have accumulated to 31.4 percent. GDP in IQ2017 would be $19,699.2 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2856.8 billion than actual $16,842.4 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.6 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/04/twenty-three-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html). US GDP in IQ2017 is 14.5 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,842.4 billion in IQ2017 or 12.3 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Mar 1919 to Mar 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 144.8512 in Mar 2017. The actual index NSA in Mar 2017 is 103.4144, which is 28.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Mar 2017. Using trend growth of 2.1 percent per year, the index would increase to 131.1817 in Mar 2017. The output of manufacturing at 103.4144 in Mar 2017 is 21.2 percent below trend under this alternative calculation.

Chart I-1A, US, Real GDP 1929-2016

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

Chart I-2 provides the growth of real quarterly GDP in the US between 1947 and 2017. The drop of output in the recession from IVQ2007 to IIQ2009 has been followed by anemic recovery compared with return to trend at 3.0 percent from 1870 to 2010 after events such as wars and recessions (Lucas 2011May) and a standstill that can lead to growth recession, or low rates of economic growth. The expansion is relatively long compared to earlier expansions and there could be another contraction or conventional recession in the future. The average rate of growth from 1947 to 2016 is 3.2 percent. The annual equivalent growth rate from IVQ2007 to IQ2017 is only 1.3 percent with 2.8 percent from the end of the recession in IVQ2001 to the end of the expansion in IVQ2007.

Chart I-2, US, Real GDP, Quarterly, 1947-2017

Source: US Bureau of Economic Analysis

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

Chart I-3 provides real GDP percentage change on the quarter a year earlier for 1983-1990. The objective is simply to compare expansion in two recoveries from sharp contractions as shown in Table I-5. Growth rates in the early phase of the recovery in 1983 and 1984 were very high, which is the opportunity to reduce unemployment that has characterized cyclical expansion in the postwar US economy. 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).

Chart I-3, Real GDP Percentage Change on Quarter a Year Earlier 1983-1990

Source: US Bureau of Economic Analysis

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

In contrast, growth rates in the comparable first thirty quarters of expansion from 2009 to 2016 in Chart I-4 have been mediocre. As a result, growth has not provided the exit from unemployment and underemployment as in other cyclical expansions in the postwar period. Growth rates did not rise in V shape as in earlier expansions and then declined close to the standstill of growth recessions.

Chart I-4, US, Real GDP Percentage Change on Quarter a Year Earlier 2009-2017

Source: US Bureau of Economic Analysis

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

Table I-3 provides percentage change of real GDP in the United States in the 1930s, 1980s and 2000s. The recession in 1981-1982 is quite similar on its own to the 2007-2009 recession. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). Data are available for the 1930s only on a yearly basis. US GDP fell 4.7 percent in the two recessions (1) from IQ1980 to IIIQ1980 and (2) from III1981 to IVQ1982 and 4.2 percent cumulatively in the recession from IVQ2007 to IIQ2009. It is instructive to compare the first years of the expansions in the 1980s and the current expansion. GDP grew at 4.6 percent in 1983, 7.3 percent in 1984, 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. In contrast, GDP grew 2.5 percent in 2010, 1.6 percent in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014 and 2.6 percent in 2015. GDP grew 1.6 percent in 2016. Actual annual equivalent GDP growth in the twenty quarters from 2012 to 2016 is 2.1 percent and 2.0 percent in the four quarters ending in IVQ2016. GDP grew at 4.2 percent in 1985, 3.5 percent in 1986, 3.5 percent in 1987, 4.2 percent in 1988 and 3.7 percent in 1989. The forecasts of the central tendency of participants of the Federal Open Market Committee (FOMC) are in the range of 2.0 to 2.2 percent in 2017 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20170315.pdf) with less reliable forecast of 1.8 to 2.3 percent in 2018 (https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20170315.pdf). Growth of GDP in the expansion from IIIQ2009 to IVQ2016 has been at average 2.1 percent in annual equivalent.

Table I-3, US, Percentage Change of GDP in the 1930s, 1980s and 2000s, ∆%

Year

GDP ∆%

Year

GDP ∆%

Year

GDP ∆%

1930

-8.5

1980

-0.2

2000

4.1

1931

-6.4

1981

2.6

2001

1.0

1932

-12.9

1982

-1.9

2002

1.8

1933

-1.3

1983

4.6

2003

2.8

1934

10.8

1984

7.3

2004

3.8

1935

8.9

1985

4.2

2005

3.3

1936

12.9

1986

3.5

2006

2.7

1937

5.1

1987

3.5

2007

1.8

1938

-3.3

1988

4.2

2008

-0.3

1939

8.0

1989

3.7

2009

-2.8

1940

8.8

1990

1.9

2010

2.5

1941

17.7

1991

-0.1

2011

1.6

1942

18.9

1992

3.6

2012

2.2

1943

17.0

1993

2.7

2013

1.7

1944

8.0

1994

4.0

2014

2.4

1945

-1.0

1995

2.7

2015

2.6

1946

-11.6

1996

3.8

2016

1.6

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

Chart I-5 provides percentage change of GDP in the US during the 1930s. There is vast literature analyzing the Great Depression (Pelaez and Pelaez, Regulation of Banks and Finance (2009), 198-217). Cole and Ohanian (1999) find that US real per capita output was lower by 11 percent in 1939 than in 1929 while the typical expansion of real per capita output in the US during a decade is 31 percent. Private hours worked in the US were 25 percent lower in 1939 relative to 1929.

Chart I-5, US, Percentage Change of GDP in the 1930s

Source: US Bureau of Economic Analysis

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

In contrast, Chart I-6 shows rapid recovery from the recessions in the 1980s. High growth rates in the initial quarters of expansion eliminated the unemployment and underemployment created during the contraction. The economy then returned to grow at the trend of expansion, interrupted by another contraction in 1991. 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).

Chart I-6, US, Percentage Change of GDP in the 1980s

Source: US Bureau of Economic Analysis

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

Chart I-7 provides the rates of growth during the 2000s. Growth rates in the initial twenty-nine quarters of expansion have been relatively lower than during recessions after World War II. As a result, unemployment and underemployment continue at the rate of 13.6 percent of the effective US labor force (https://cmpassocregulationblog.blogspot.com/2017/04/twenty-three-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html).

Chart I-7, US, Percentage Change of GDP in the 2000s

Source: US Bureau of Economic Analysis

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

Characteristics of the four cyclical contractions are in Table I-4 with the first column showing the number of quarters of contraction; the second column the cumulative percentage contraction; and the final column the average quarterly rate of contraction. There were two contractions from IQ1980 to IIIQ1980 and from IIIQ1981 to IVQ1982 separated by three quarters of expansion. The drop of output combining the declines in these two contractions is 4.7 percent, which is almost equal to the decline of 4.2 percent in the contraction from IVQ2007 to IIQ2009. In contrast, during the Great Depression in the four years of 1930 to 1933, GDP in constant dollars fell 26.4 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7 and revisions in http://bea.gov/iTable/index_nipa.cfm). The comparison of the global recession after 2007 with the Great Depression is entirely misleading.

Table I-4, US, Number of Quarters, GDP Cumulative Percentage Contraction and Average Percentage Annual Equivalent Rate in Cyclical Contractions   

 

Number of Quarters

Cumulative Percentage Contraction

Average Percentage Rate

IIQ1953 to IIQ1954

3

-2.4

-0.8

IIIQ1957 to IIQ1958

3

-3.0

-1.0

IVQ1973 to IQ1975

5

-3.1

-0.6

IQ1980 to IIIQ1980

2

-2.2

-1.1

IIIQ1981 to IVQ1982

4

-2.5

-0.64

IVQ2007 to IIQ2009

6

-4.2

-0.72

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

Table I-5 shows the mediocre average annual equivalent growth rate of 2.1 percent of the US economy in the thirty-one quarters of the current cyclical expansion from IIIQ2009 to IQ2017. In sharp contrast, the average growth rate of GDP was:

  • 5.7 percent in the first thirteen quarters of expansion from IQ1983 to IQ1986
  • 5.4 percent in the first fifteen quarters of expansion from IQ1983 to IIIQ1986
  • 5.2 percent in the first sixteen quarters of expansion from IQ1983 to IVQ1986
  • 5.0 percent in the first seventeen quarters of expansion from IQ1983 to IQ1987
  • 5.0 percent in the first eighteen quarters of expansion from IQ1983 to IIQ1987
  • 4.9 percent in the first nineteen quarters of expansion from IQ1983 to IIIQ1987
  • 5.0 percent in the first twenty quarters of expansion from IQ1983 to IVQ1987
  • 4.9 percent in the first twenty-first quarters of expansion from IQ1983 to IQ1988
  • 4.9 percent in the first twenty-two quarters of expansion from IQ1983 to IIQ1988
  • 4.8 percent in the first twenty-three quarters of expansion from IQ1983 to IIIQ1988
  • 4.8 percent in the first twenty-four quarters of expansion from IQ1983 to IVQ1988
  • 4.8 percent in the first twenty-five quarters of expansion from IQ1983 to IQ1989
  • 4.7 percent in the first twenty-six quarters of expansion from IQ1983 to IIQ1989
  • 4.7 percent in the first twenty-seven quarters of expansion from IQ1983 to IIIQ1989
  • 4.5 percent in the first twenty-eight quarters of expansion from IQ1983 to IVQ1989
  • 4.5 percent in the first twenty-nine quarters of expansion from IQ1983 to IQ1990
  • 4.4 percent in the first thirty quarters of expansion from IQ1983 to IIQ1990
  • 4.3 percent in the first thirty-one quarters of expansion from IQ1983 to IIIQ1990

The line “average first four quarters in four expansions” provides the average growth rate of 7.7 percent with 7.8 percent from IIIQ1954 to IIQ1955, 9.2 percent from IIIQ1958 to IIQ1959, 6.1 percent from IIIQ1975 to IIQ1976 and 7.8 percent from IQ1983 to IVQ1983. The United States missed this opportunity of high growth in the initial phase of recovery. BEA data show the US economy in standstill relative to historical experience with annual growth of 2.5 percent in 2010 decelerating to 1.6 percent annual growth in 2011, 2.2 percent in 2012, 1.7 percent in 2013, 2.4 percent in 2014, 2.6 percent in 2015 and 1.6 percent in 2016 (http://www.bea.gov/iTable/index_nipa.cfm). The expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.2 percent from IQ1983 to IVQ1986, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IQ1988, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988. 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989. 4.5 percent from IQ1983 to IVQ1989, 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990 and at 7.8 percent from IQ1983 to IVQ1983. 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). GDP grew 2.7 percent in the first four quarters of the expansion from IIIQ2009 to IIQ2010. GDP growth in the twenty-one quarters from 2012 to 2017 accumulated to 10.9 percent. This growth is equivalent to 2.0 percent per year, obtained by dividing GDP in IQ2017 of $16,842.4 billion by GDP in IVQ2011 of $15,190.3 billion and compounding by 4/21: {[($16,842.4/$15,190.3)4/21 -1]100 = 2.0 percent}.

Table I-5 shows that GDP grew 17.1 percent in the first thirty quarters of expansion from IIIQ2009 to IVQ2016 at the annual equivalent rate of 2.1 percent.

Table I-5, US, Number of Quarters, Cumulative Growth and Average Annual Equivalent Growth Rate in Cyclical Expansions

 

Number
of
Quarters

Cumulative Growth

∆%

Average Annual Equivalent Growth Rate

IIIQ 1954 to IQ1957

11

12.8

4.5

First Four Quarters IIIQ1954 to IIQ1955

4

7.8

  

IIQ1958 to IIQ1959

5

10.0

7.9

First Four Quarters

IIIQ1958 to IIQ1959

4

9.2

  

IIQ1975 to IVQ1976

8

8.3

4.1

First Four Quarters IIIQ1975 to IIQ1976

4

6.1

  

IQ1983-IQ1986

IQ1983-IIIQ1986

IQ1983-IVQ1986

IQ1983-IQ1987

IQ1983-IIQ1987

IQ1983 to IIIQ1987

IQ1983 to IVQ1987

IQ1983 to IQ1988

IQ1983 to IIQ1988

IQ1983 to IIIQ1988

IQ1983 to IVQ1988

IQ1983 to IQ1989

IQ1983 to IIQ1989

IQ1983 to IIIQ1989

IQ1983 to IVQ1989

IQ1983 to IQ1990

IQ1983 to IIQ1990

IQ1983 to III1990

13

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

19.9

21.6

22.3

23.1

24.5

25.6

27.7

28.4

30.1

30.9

32.6

34.0

35.0

36.0

36.3

37.8

38.3

38.4

5.7

5.4

5.2

5.0

5.0

4.9

5.0

4.9

4.9

4.8

4.8

4.8

4.7

4.7

4.5

4.5

4.4

4.3

First Four Quarters IQ1983 to IVQ1983

4

7.8

  

Average First Four Quarters in Four Expansions*

  

7.7

  

IIIQ2009 to IQ2017

31

17.3

2.1

First Four Quarters IIIQ2009 to IIQ2010

  

2.7

  

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

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

Chart I-8 shows US real quarterly GDP growth from 1980 to 1990. The economy contracted during the recession and then expanded vigorously throughout the 1980s, rapidly eliminating the unemployment caused by the contraction. 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).

Chart I-8, US, Real GDP, 1980-1990

Source: US Bureau of Economic Analysis

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

Chart I-9 shows the entirely different situation of real quarterly GDP in the US between 2007 and 2017. The economy has underperformed during the first thirty quarters of expansion for the first time in the comparable contractions since the 1950s. The US economy is now in a perilous standstill.

Chart I-9, US, Real GDP, 2007-2017

Source: US Bureau of Economic Analysis

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

As shown in Tables I-4 and I-5 above the loss of real GDP in the US during the contraction was 4.2 percent but the gain in the cyclical expansion has been only 17.3 percent (first to the last row in Table I-5), using all latest revisions. As a result, the level of real GDP in IQ2017 with the first estimate and revisions is higher by only 12.3 percent than the level of real GDP in IVQ2007. 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 IQ2017 would have accumulated to 31.4 percent. GDP in IQ2017 would be $19,699.2 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2856.8 billion than actual $16,842.4 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.6 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/04/twenty-three-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html). US GDP in IQ2017 is 14.5 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,842.4 billion in IQ2017 or 12.3 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Mar 1919 to Mar 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 144.8512 in Mar 2017. The actual index NSA in Mar 2017 is 103.4144, which is 28.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Mar 2017. Using trend growth of 2.1 percent per year, the index would increase to 131.1817 in Mar 2017. The output of manufacturing at 103.4144 in Mar 2017 is 21.2 percent below trend under this alternative calculation.

Table I-6 shows that the contraction concentrated in two quarters: decline of 2.1 percent in IVQ2008 relative to the prior quarter and decline of 1.4 percent in IQ2009 relative to IVQ2008. The combined fall of GDP in IVQ2008 and IQ2009 was 3.5 percent {[(1-0.021) x (1-0.014) -1]100 = -3.5%}, or {[(IQ2009 $14,375.0)/(IIIQ2008 $14,891.6) – 1]100 = -3.5%} except for rounding. Those two quarters coincided with the worst effects of the financial crisis (Cochrane and Zingales 2009). GDP fell 0.1 percent in IIQ2009 but grew 0.3 percent in IIIQ2009, which is the beginning of recovery in the cyclical dates of the NBER. Most of the recovery occurred in five successive quarters from IVQ2009 to IVQ2010 of growth of 1.0 percent in IVQ2009, 0.4 percent in IQ2010, 1.0 percent in IIQ2010 and nearly equal growth at 0.7 percent in IIIQ2010 and 0.6 percent in IVQ2010 for cumulative growth in those five quarters of 3.8 percent, obtained by accumulating the quarterly rates {[(1.01 x 1.004 x 1.01 x 1.007 x 1.006) – 1]100 = 3.8%} or {[(IVQ2010 $14,939.0)/(IIIQ2009 $14,402.5) – 1]100 = 3.7%} with minor rounding difference. The economy then stalled during the first half of 2011 with decline of 0.4 percent in IQ2011 and growth of 0.7 percent in IIQ2011 for combined annual equivalent rate of 0.6 percent {(0.996 x 1.007)2}. The economy grew 0.2 percent in IIIQ2011 for annual equivalent growth of 0.7 percent in the first three quarters {[(0.996 x 1.007 x 1.002)4/3 -1]100 = 0.7%}. Growth picked up in IVQ2011 with 1.1 percent relative to IIIQ2011. Growth in a quarter relative to a year earlier in Table I-6 slows from over 2.7 percent during three consecutive quarters from IIQ2010 to IVQ2010 to 1.9 percent in IQ2011, 1.7 percent in IIQ2011, 1.2 percent in IIIQ2011 and 1.7 percent in IVQ2011. As shown below, growth of 1.1 percent in IVQ2011 was partly driven by inventory accumulation. In IQ2012, GDP grew 0.7 percent relative to IVQ2011 and 2.8 percent relative to IQ2011, decelerating to 0.5 percent in IIQ2012 and 2.5 percent relative to IIQ2011 and 0.1 percent in IIIQ2012 and 2.4 percent relative to IIIQ2011. Growth was 0.0 percent in IVQ2012 with 1.3 percent relative to a year earlier but mostly because of deduction of 1.54 percentage points of inventory divestment and 0.42 percentage points of reduction of one-time national defense expenditures. Growth was 0.7 percent in IQ2013 and 1.3 percent relative to IQ2012 in large part because of burning savings to consume caused by financial repression of zero interest rates. There is similar growth of 0.2 percent in IIQ2013 and 1.0 percent relative to a year earlier. In IIIQ2013, GDP grew 0.8 percent relative to the prior quarter and 1.7 percent relative to the same quarter a year earlier with inventory accumulation contributing 1.60 percentage points to growth at 3.1 percent SAAR in IIIQ2013. GDP increased 1.0 percent in IVQ2013 and 2.7 percent relative to a year earlier. GDP fell 0.3 percent in IQ2014 and grew 1.6 percent relative to a year earlier. Inventory divestment deducted 1.89 percentage points from GDP growth in IQ2014. GDP grew 1.0 percent in IIQ2014, 2.4 percent relative to a year earlier and at 4.0 SAAR with inventory change contributing 0.67 percentage points. GDP grew 1.2 percent in IIIQ2014 and 2.9 percent relative to a year earlier. GDP grew 0.6 percent in IVQ2014 and 2.5 percent relative to a year earlier. GDP increased 0.5 percent in IQ2015 and increased 3.3 percent relative to a year earlier partly because of low level during contraction of 0.3 percent in IQ2014. GDP grew 0.6 percent in IIQ2015 and 3.0 percent relative to a year earlier. GDP grew 0.5 percent in IIIQ2015 and 2.2 percent relative to a year earlier. GDP grew 0.2 percent in IVQ2015 and increased 1.9 percent relative to a year earlier. GDP grew 0.2 percent in IQ2016 and increased 1.6 percent relative to a year earlier. GDP grew 0.4 percent in IIQ2016 and increased 1.3 percent relative to a year earlier. GDP grew 0.9 percent in IIIQ2016 and increased 1.7 percent relative to a year earlier. GDP grew 0.5 percent in IVQ2016 and increased 2.0 percent relative to a year earlier. GDP grew 0.2 percent in IQ2017 and increased 1.9 percent relative to a year earlier. Rates of a quarter relative to the prior quarter capture better deceleration of the economy than rates on a quarter relative to the same quarter a year earlier. The critical question for which there is not yet definitive solution is whether what lies ahead is continuing growth recession with the economy crawling and unemployment/underemployment at extremely high levels or another contraction or conventional recession. Forecasts of various sources continued to maintain high growth in 2011 without taking into consideration the continuous slowing of the economy in late 2010 and the first half of 2011. The sovereign debt crisis in the euro area and growth in China are common sources of doubts on the rate and direction of economic growth in the US. There is weak internal demand in the US with almost no investment and spikes of consumption driven by burning saving because of financial repression in the form of zero interest rates and bloated balance sheet of the Fed.

Table I-6, US, Real GDP and Percentage Change Relative to IVQ2007 and Prior Quarter, Billions Chained 2009 Dollars and ∆%

 

Real GDP, Billions Chained 2009 Dollars

∆% Relative to IVQ2007

∆% Relative to Prior Quarter

∆%
over
Year Earlier

IVQ2007

14,991.8

NA

0.4

1.9

IQ2008

14,889.5

-0.7

-0.7

1.1

IIQ2008

14,963.4

-0.2

0.5

0.8

IIIQ2008

14,891.6

-0.7

-0.5

-0.3

IVQ2008

14,577.0

-2.8

-2.1

-2.8

IQ2009

14,375.0

-4.1

-1.4

-3.5

IIQ2009

14,355.6

-4.2

-0.1

-4.1

IIIQ2009

14,402.5

-3.9

0.3

-3.3

IV2009

14,541.9

-3.0

1.0

-0.2

IQ2010

14,604.8

-2.6

0.4

1.6

IIQ2010

14,745.9

-1.6

1.0

2.7

IIIQ2010

14,845.5

-1.0

0.7

3.1

IVQ2010

14,939.0

-0.4

0.6

2.7

IQ2011

14,881.3

-0.7

-0.4

1.9

IIQ2011

14,989.6

0.0

0.7

1.7

IIIQ2011

15,021.1

0.2

0.2

1.2

IVQ2011

15,190.3

1.3

1.1

1.7

IQ2012

15,291.0

2.0

0.7

2.8

IIQ2012

15,362.4

2.5

0.5

2.5

IIIQ2012

15,380.8

2.6

0.1

2.4

IVQ2012

15,384.3

2.6

0.0

1.3

IQ2013

15,491.9

3.3

0.7

1.3

IIQ2013

15,521.6

3.5

0.2

1.0

IIIQ2013

15,641.3

4.3

0.8

1.7

IVQ2013

15,793.9

5.4

1.0

2.7

IQ2014

15,747.0

5.0

-0.3

1.6

IIQ2014

15,900.8

6.1

1.0

2.4

IIIQ2014

16,094.5

7.4

1.2

2.9

IVQ2014

16,186.7

8.0

0.6

2.5

IQ2015

16,269.0

8.5

0.5

3.3

IIQ2015

16,374.2

9.2

0.6

3.0

IIIQ2015

16,454.9

9.8

0.5

2.2

IVQ2015

16,490.7

10.0

0.2

1.9

IQ2016

16,525.0

10.2

0.2

1.6

IIQ2016

16,583.1

10.6

0.4

1.3

IIIQ2016

16,727.0

11.6

0.9

1.7

IVQ2016

16,813.3

12.1

0.5

2.0

IQ2017

16,842.4

12.3

0.2

1.9

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

Chart I-10 provides the percentage change of real GDP from the same quarter a year earlier from 1980 to 1990. There were two contractions almost in succession in 1980 and from 1981 to 1983. The expansion was marked by initial high rates of growth as in other recession in the postwar US period during which employment lost in the contraction was recovered. Growth rates continued to be high after the initial phase of expansion. 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).

Chart I-10, Percentage Change of Real Gross Domestic Product from Quarter a Year Earlier 1980-1990

Source: US Bureau of Economic Analysis

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

The experience of recovery after 2009 is not as complete as during the 1980s. Chart I-11 shows the much lower rates of growth in the early phase of the current expansion and sharp decline from an early peak. The US missed the initial high growth rates in cyclical expansions that eliminate unemployment and underemployment.

Chart I-11, Percentage Change of Real Gross Domestic Product from Quarter a Year Earlier 2007-2017

Source: US Bureau of Economic Analysis

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

Chart I-12 provides growth rates from a quarter relative to the prior quarter during the 1980s. There is the same strong initial growth followed by a long period of sustained growth. 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).

Chart I-12, Percentage Change of Real Gross Domestic Product from Prior Quarter 1980-1990

Source: US Bureau of Economic Analysis

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

Chart I-13 provides growth rates in a quarter relative to the prior quarter from 2007 to 2017. Growth in the current expansion after IIIQ2009 has not been as strong as in other postwar cyclical expansions.

Chart I-13, Percentage Change of Real Gross Domestic Product from Prior Quarter 2007-2017

Source: US Bureau of Economic Analysis

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

The revised estimates and earlier estimates from IQ2008 to IQ2016 in seasonally adjusted annual equivalent rates are shown in Table I-7. The strongest revision is for IVQ2008 for which the contraction of GDP is revised from minus 6.8 percent to minus 8.9 percent and minus 8.2 percent. IQ2009 is also revised from contraction of minus 4.9 percent to minus 6.7 percent but then lowered to contraction of 5.3 percent and 5.4 percent. There is only minor revision in IIIQ2008 of the contraction of minus 4.0 percent to minus 3.7 percent and much lower to minus 1.9 percent. Growth of 5.0 percent in IV2009 is revised to 3.8 percent and then increased to 4.0 percent but lowered to 3.9 percent. Growth in IQ2010 is lowered from 3.9 percent to 2.3 percent and 1.7 percent. Growth in IIQ2010 is upwardly revised to 3.8 percent but then lowered to 2.2 percent. The final revision increased growth in IIQ2010 to 3.9 percent. Revisions lowered growth of 1.9 percent in IQ2011 to minus 1.5 percent. The revisions increased growth of 1.8 percent in IQ2013 to 2.7 percent and increased growth of 2.0 percent in IQ2012 to 2.3 percent. The revision reduced the decline of GDP from 2.9 percent in IQ2014 to 2.1 percent. The revision of Jul 20, 2015, reduced significantly the rate of growth in 2013. The revision of Jul 27, 2016, increased the growth rate in 2013 and 2014. The revisions do not alter the conclusion that the current expansion is much weaker than historical sharp contractions since the 1950s and is now changing into slow growth recession with higher risks of contraction and continuing underperformance.

Table I-7, US, Quarterly Growth Rates of GDP, % Annual Equivalent SA, Revised and Earlier Estimates

Quarters

Rev Jul 29, 2016

Rev Jul 30, 2015

Rev Jul 30, 2014

Rev

Jul 31, 2013

Rev

Jul 27, 2012

Rev

Jul 29, 2011

Earlier Estimate

2008

              

I

    

-2.7

-2.7

  

-1.8

-0.7

II

    

2.0

2.0

  

1.3

0.6

III

    

-1.9

-2.0

  

-3.7

-4.0

IV

    

-8.2

-8.3

  

-8.9

-6.8

2009

              

I

    

-5.4

-5.4

-5.3

-6.7

-4.9

II

    

-0.5

-0.4

-0.3

-0.7

-0.7

III

    

1.3

1.3

1.4

1.7

1.6

IV

    

3.9

3.9

4.0

3.8

5.0

2010

              

I

    

1.7

1.6

2.3

3.9

3.7

II

    

3.9

3.9

2.2

3.8

1.7

III

    

2.7

2.8

2.6

2.5

2.6

IV

    

2.5

2.8

2.4

2.3

3.1

2011

              

I

    

-1.5

-1.3

0.1

0.4

1.9

II

    

2.9

3.2

2.5

    

III

    

0.8

1.4

1.3

    

IV

    

4.6

4.9

4.1

    

2012

              

I

  

2.7

2.3

3.7

2.0

    

II

  

1.9

1.6

1.2

1.3

    

III

  

0.5

2.5

2.8

3.1

    

IV

  

0.1

0.1

0.1

0.4

    

2013

              

I

2.8

1.9

2.7

1.1

1.8

    

II

0.8

1.1

1.8

2.5

      

III

3.1

3.0

4.5

4.1

      

IV

4.0

3.8

3.5

2.6

      

2014

              

I

-1.2

-0.9

-2.1

-2.9

      

II

4.0

4.6

          

III

5.0

4.3

          

IV

2.3

2.1

          

2015

              

I

2.0

0.6

          

II

2.6

            

III

2.0

            

IV

0.9

            

2016

              

I

0.8

            

Note: Rev: Revision

Source: US Bureau of Economic Analysis

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

Aggregate demand, personal consumption expenditures (PCE) and gross private domestic investment (GDI) were much stronger during the expansion phase from IQ1983 to IQ1990 than from IIIQ2009 to IQ2017, as shown in Table I-8. GDI provided the impulse of growth in 1983 and 1984, which has not been the case from 2009 to 2017. The investment decision in the US economy has been frustrated in the current cyclical expansion. Growth of GDP in IIIQ2013 at seasonally adjusted annual rate of 3.1 percent consisted of positive contribution of 1.28 percentage points of personal consumption expenditures (PCE) plus positive contribution of 2.08 percentage points of gross private domestic investment (GDI) of which 1.60 percentage points of inventory investment (∆PI), contribution of net exports (trade or exports less imports) of 0.13 percentage points and deduction of 0.37 percentage points of government consumption expenditures and gross investment (GOV) partly because of one-time deduction of national defense expenditures of 0.31 percentage points. Growth at 4.0 percent in IVQ2013 had strongest contributions of 2.29 percentage points of PCE and 1.29 percentage points of trade. Growth of GDP at minus 1.2 percent in IQ2014 is mostly contribution of 1.26 percentage points by PCE with deduction of 1.10 percentage points by GDI, inventory divestment of 1.89 percentage points and trade deducting 1.16 percentage points. Growth at 4.0 percent in IIQ2014 consists of contributions of 2.56 percentage points by PCE and 1.79 percentage points by GDI with 0.67 percentage points by inventory change. Trade deducted 0.41 percentage points and government added 0.02 percentage points mostly because of contribution of 0.22 percentage points of expenditures by state and local government. Growth at 5.0 percent in IIIQ2014 consists of contribution of 2.52 percentage points by PCE, 1.49 percentage points by GDI, 0.50 percentage points by trade and 0.46 percentage points by government of which 0.17 percentage points by national defense expenditures growing at 4.0 percent in annual equivalent. Growth at 2.3 percent in IVQ2014 consists of contribution of 3.07 percentage points by PCE, 0.45 percentage points by GDI with contribution of 0.23 percentage points by inventory investment. Net trade deducted 1.14 percentage points while government deducted 0.07 percentage mostly because of deduction of 0.52 percentage points by national defense expenditure declining at 11.6 percent in IVQ2014. Growth of GDP at 2.0 percent in IQ2015 consisted mostly of contributions of 1.63 percentage points by personal consumption expenditures and 1.01 percentage points by inventory accumulation while trade deducted 1.65 percentage points and government contributed 0.45 percentage points. Growth at 2.6 percentage points in IIQ2015 consisted mostly of contributions of 1.94 percentage points by personal consumption expenditures, 0.18 percentage points by gross domestic investment, deduction of 0.08 percentage points by net trade and contribution of 0.57 percentage points by government consumption and expenditures. Growth at 2.0 percent in IIIQ2015 consisted mostly of contribution of personal consumption expenditures (PCE) of 1.81 percentage points with government adding 0.34 percentage points. Gross domestic investment (GDI) contributed 0.35 percentage points with deduction of inventory divestment of 0.57 percentage points while net trade deducted 0.52 percentage points. Growth at 0.9 percent in IVQ2015 consisted mostly of contribution of 1.53 percentage points by personal consumption expenditures (PCE). GDI deducted 0.39 percentage points while trade deducted 0.45 percentage points and inventory divestment deducted 0.36 percentage points. Growth at 0.8 percent in IQ2016 consisted mostly of contribution of 1.11 percentage points by personal consumption expenditures (PCE). There were deduction of 0.56 percentage points by gross domestic investment (GDI) and 0.41 percentage points by inventory change. Net trade contributed 0.01 percentage points and government added 0.28 percentage points. Growth at 1.4 percent in IIQ2016 consisted mostly of contribution of 2.88 percentage points by PCE with GDI deducting 1.34 percentage points. Inventory divestment deducted 1.16 percentage points. Growth at 3.5 percent in IIIQ2016 consisted mostly of contribution of 2.03 by PCE with GDI adding 0.50 percentage points. Inventory investment contributed 0.49 percentage points and trade added 0.85 percentage points. Growth at 2.1 percent in IVQ2016 had positive contributions of 2.40 percentage points of PCE, 1.47 of GDI and 0.03 of GOV. Inventory investment added 1.01 percentage points and net trade deducted 1.82 percentage points. Growth at 0.7 percent in IQ2017 originated in contributions of 0.69 percentage points by GDI, 0.23 percentage points by PCE and 0.07 percentage points by net trade. GOV deducted 0.30 percentage points and inventory divestment subtracted 0.93 percentage points. The economy of the United States has lost the dynamic growth impulse of earlier cyclical expansions with mediocre growth resulting from consumption forced by one-time effects of financial repression, national defense expenditures and inventory accumulation.

Table I-8, US, Contributions to the Rate of Growth of GDP in Percentage Points

 

GDP

PCE

GDI

∆ PI

Trade

GOV

2017

            

I

0.7

0.23

0.69

-0.93

0.07

-0.30

2016

            

I

0.8

1.11

-0.56

-0.41

0.01

0.28

II

1.4

2.88

-1.34

-1.16

0.18

-0.30

III

3.5

2.03

0.50

0.49

0.85

0.14

IV

2.1

2.40

1.47

1.01

-1.82

0.03

2015

            

I

2.0

1.63

1.62

1.01

-1.65

0.45

II

2.6

1.94

0.18

-0.52

-0.08

0.57

III

2.0

1.81

-0.35

-0.57

-0.52

0.34

IV

0.9

1.53

-0.39

-0.36

-0.45

0.18

2014

            

I

-1.2

1.26

-1.10

-1.89

-1.16

-0.19

II

4.0

2.56

1.79

0.67

-0.41

0.02

III

5.0

2.52

1.49

0.32

0.50

0.46

IV

2.3

3.07

0.45

0.23

-1.14

-0.07

2013

            

I

2.8

1.32

2.04

0.92

0.30

-0.83

II

0.8

0.58

0.78

0.08

-0.21

-0.37

III

3.1

1.28

2.08

1.60

0.13

-0.37

IV

4.0

2.29

0.91

-0.11

1.29

-0.53

2012

            

I

2.7

1.63

1.47

-0.53

-0.02

-0.40

II

1.9

0.45

1.53

0.56

0.28

-0.39

III

0.5

0.72

-0.18

-0.18

0.16

-0.22

IV

0.1

0.78

-0.51

-1.54

0.58

-0.75

2011

            

I

-1.5

1.38

-1.07

-0.96

-0.24

-1.60

II

2.9

0.57

2.14

1.04

0.31

-0.08

III

0.8

1.20

0.15

-2.10

0.01

-0.52

IV

4.6

0.94

4.16

2.80

-0.21

-0.31

2010

            

I

1.7

1.46

1.77

1.66

-0.85

-0.63

II

3.9

2.23

2.86

1.09

-1.77

0.61

III

2.7

1.77

1.86

1.90

-0.83

-0.07

IV

2.5

2.79

-0.51

-1.63

1.12

-0.87

2009

            

I

-5.4

-0.86

-7.02

-2.26

2.30

0.15

II

-0.5

-1.19

-3.25

-1.12

2.34

1.56

III

1.3

1.68

-0.40

-0.38

-0.45

0.48

IV

3.9

-0.01

4.05

4.40

0.06

-0.17

1982

            

I

-6.5

1.61

-7.59

-5.33

-0.49

-0.05

II

2.2

0.89

-0.06

2.26

0.81

0.56

III

-1.4

1.88

-0.62

1.11

-3.22

0.53

IV

0.4

4.51

-5.37

-5.33

-0.10

1.35

1983

            

I

5.3

2.45

2.36

0.92

-0.29

0.82

II

9.4

5.06

5.96

3.43

-2.46

0.89

III

8.1

4.50

4.40

0.57

-2.25

1.42

IV

8.5

4.06

6.94

3.01

-1.14

-1.36

1984

            

I

8.2

2.26

7.23

4.94

-2.31

1.01

II

7.2

3.64

2.57

-0.29

-0.87

1.87

III

4.0

1.95

1.69

0.21

-0.36

0.70

IV

3.2

3.29

-1.08

-2.44

-0.56

1.58

1985

            

I

4.0

4.23

-2.14

-2.86

0.94

1.01

II

3.7

2.35

1.34

0.35

-1.90

1.93

III

6.4

4.82

-0.43

-0.15

-0.01

1.98

IV

3.0

0.62

2.80

1.40

-0.66

0.27

1986

            

I

3.8

2.10

0.04

-0.17

0.92

0.70

II

1.9

2.77

-1.30

-1.30

-1.33

1.70

III

4.1

4.55

-1.97

-1.62

-0.45

1.95

IV

2.1

1.62

0.24

-0.29

0.71

-0.48

1987

            

I

2.8

0.05

1.98

3.28

0.23

0.57

II

4.6

3.54

0.08

-0.99

0.14

0.81

III

3.7

2.97

0.03

-1.19

0.45

0.23

IV

6.8

0.57

4.94

4.95

0.18

1.08

1988

            

I

2.3

4.49

-3.62

-3.68

1.94

-0.54

II

5.4

1.89

1.72

0.33

1.44

0.34

III

2.3

2.17

0.38

0.05

-0.31

0.08

IV

5.4

2.93

1.11

0.27

-0.21

1.56

1989

            

I

4.1

1.18

2.41

1.80

0.85

-0.35

II

3.2

1.20

-0.70

-0.79

1.35

1.34

III

3.0

2.52

-0.64

-1.84

0.44

0.70

IV

0.9

1.13

-0.53

0.37

-0.20

0.45

1990

            

I

4.5

2.21

0.69

-0.10

0.25

1.30

Note: PCE: personal consumption expenditures; GDI: gross private domestic investment; ∆ PI: change in private inventories; Trade: net exports of goods and services; GOV: government consumption expenditures and gross investment; – is negative and no sign positive

GDP: percent change at annual rate; percentage points at annual rates

Source: US Bureau of Economic Analysis

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

The Bureau of Economic Analysis (BEA) (pages 1-2) explains growth of GDP in IVQ2016 as follows (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp1q17_adv.pdf):

“Real gross domestic product (GDP) increased at an annual rate of 0.7 percent in the first quarter of 2017 (table 1), according to the "advance" estimate released by the Bureau of Economic Analysis. In the fourth quarter of 2016, real GDP increased 2.1 percent.

The Bureau emphasized that the first-quarter advance estimate released today is based on source data that are incomplete or subject to further revision by the source agency (see “Source Data for the Advance Estimate” on page 2). The "second" estimate for the first quarter, based on more complete data, will be released on May 26, 2017. The increase in real GDP in the first quarter reflected positive contributions from nonresidential fixed investment, exports, residential fixed investment, and personal consumption expenditures (PCE), that were offset by negative contributions from private inventory investment, state and local government spending, and federal government spending. Imports, which are a subtraction in the calculation of GDP, increased (table 2).

The deceleration in real GDP in the first quarter reflected a deceleration in PCE and downturns in private inventory investment and in state and local government spending that were partly offset by an upturn in exports and accelerations in both nonresidential and residential fixed investment.”

There are positive contributions to growth in IQ2017 shown in Table I-9:

  • Personal consumption expenditures (PCE) growing at 0.3 percent
  • Growth of nonresidential fixed investment (NRFI) at 9.4 percent
  • Growth of residential fixed investment at 13.7 percent
  • Growth of exports at 5.8 percent

There were negative contributions in IQ2017:

· Durable goods contracting at 2.5 percent

  • Inventory investment deducting 0.93 percentage points
  • Imports, which are a deduction from growth, growing at 4.1 percent
  • Government expenditures contracting at 1.7 percent; Federal government expenditures contracting at 1.9 percent; contraction of national defense expenditures at 4.0 percent; and state and local government expenditures contracting at 1.6 percent

The BEA explains deceleration in real GDP growth in IQ2017 by:

· Growth of PCE at 0.3 percent compared with growth at 3.5 percent in IVQ2016

  • Contraction of consumption of durable goods at 2.5 percent in IQ2017 compared with growth at 11.4 percent in IVQ2016
  • Contraction of government expenditures at 1.7 percent compared with growth at 0.2 percent in IVQ2016
  • Contraction of federal government expenditures at 1.9 percent in IQ2017 compared with contraction at 1.2 percent in IVQ2016
  • Contraction of national defense expenditures at 4.0 percent in IQ2017 compared with contraction at 3.6 percent in IVQ2016
  • Deduction of 0.93 percentage points by inventory investment in IQ2017 compared with contribution of 1.01 percentage points in IVQ2016

The BEA finds offsetting accelerating factors:

· Growth of residential fixed investment at 13.7 percent in IQ2017 compared with growth at 9.6 percent in IVQ2016

· Growth of nonresidential fixed investment at 9.4 percent in IQ2017 compared with growth at 0.9 percent in IVQ2016

· Growth of exports at 5.8 percent in IQ2017 compared with contraction at 4.5 percent in IVQ2016

· Growth of imports at 4.1 percent in IQ2017 compared with growth at 9.0 percent in IVQ2016

An important aspect of growth in the US is the decline in growth of real disposable personal income, or what is left after taxes and inflation, which decreased at the rate of 0.5 percent in IIIQ2013 compared with a year earlier. Contraction of real disposable income of 2.8 percent in IVQ2013 relative to a year earlier is largely due to comparison with an artificially higher level in anticipations of income in Nov and Dec 2012 to avoid increases in taxes in 2013, an episode known as “fiscal cliff.” Real disposable personal income increased 2.5 percent in IQ2014 relative to a year earlier and 3.2 percent in IIQ2014 relative to a year earlier. Real disposable personal income increased 3.7 percent in IIIQ2014 relative to a year earlier and 4.5 percent in IVQ2014 compared with a year earlier. Real disposable personal income grew 3.9 percent in IQ2015 relative to a year earlier partly because of contraction of energy prices and increased at 3.6 percent in IIQ2015. Real disposable personal income grew at 3.3 percent in IIIQ2015 relative to a year earlier and at 3.0 percent in IVQ2015 relative to a year earlier. Real disposable income grew at 3.1 percent in IQ2016 relative to a year earlier and at 2.8 percent in IIQ2016 relative to a year earlier. Real disposable income grew at 2.7 percent in IIIQ2016 relative to a year earlier and at 2.5 percent in IVQ2016 compared with a year earlier. Real disposable income grew at 2.2 percent in IQ2017 relative to a year earlier. The effects of financial repression, or zero interest, are vividly shown in the decline of the savings rate, or personal saving as percent of disposable income from 9.2 percent in IVQ2012 to 5.3 percent in IIIQ2013 and 4.7 percent in IVQ2013. The savings rate eased to 5.3 percent in IQ2014, increasing to 5.7 percent in IIQ2014 and stabilizing to 5.7 percent in IIIQ2014. The savings rate fell to 5.6 percent in IVQ2014, increasing to 5.5 percent in IQ2015. The savings rate increased to 5.7 percent in IIQ2015, 5.9 percent in IIIQ2015 and 6.0 percent in IVQ2015. The savings ratio moved to 6.1 percent in IQ2016 and 5.9 percent in IIQ2016. The savings ratio stabilized at 5.9 percent in IIIQ2016 and at 5.5 percent in IVQ2016. The savings ratio reached 5.7 percent in IQ2017. Anticipation of income in IVQ2012 to avoid higher taxes in 2013 caused increases in income and savings while higher payroll taxes in 2013 restricted income growth and savings in IQ2013. Zero interest rates induce risky investments with high leverage and can contract balance sheets of families, business and financial institutions when interest rates inevitably increase in the future. There is a tradeoff of weaker economy in the future when interest rates increase by meager growth in the present with forced consumption by zero interest rates. Microeconomics consists of the analysis of allocation of scarce resources to alternative and competing ends. Zero interest rates cloud he calculus of risk and returns in consumption and investment, disrupting decisions that maintain the economy in its long-term growth path.

Table I-9, US, Percentage Seasonally Adjusted Annual Equivalent Quarterly Rates of Increase, %

 

IQ2016

IIQ   

2016

IIIQ 

2016

IVQ 

2016

IQ 2017

GDP

0.8

1.4

3.5

2.1

0.7

PCE

1.6

4.3

3.0

3.5

0.3

Durable Goods

-0.6

9.8

11.6

11.4

-2.5

NRFI

-3.4

1.0

1.4

0.9

9.4

RFI

7.8

-7.7

-4.1

9.6

13.7

Exports

-0.7

1.8

10.0

-4.5

5.8

Imports

-0.6

0.2

2.2

9.0

4.1

GOV

1.6

-1.7

0.8

0.2

-1.7

Federal GOV

-1.5

-0.4

2.4

-1.2

-1.9

National Defense

-3.2

-3.2

2.0

-3.6

-4.0

Cont to GDP Growth % Points

-0.13

-0.13

0.08

-0.14

-0.16

State/Local GOV

3.5

-2.5

-0.2

1.0

-1.6

∆ PI (PP)

-0.41

-1.16

0.49

1.01

-0.93

Final Sales of Domestic Product

1.2

2.6

3.0

1.1

1.6

Gross Domestic Purchases

0.8

1.2

2.6

3.9

0.6

Prices Gross
Domestic Purchases

0.2

2.1

1.5

2.0

2.6

Prices of GDP

0.5

2.3

1.4

2.1

2.3

Prices of GDP Excluding Food and Energy

1.5

2.1

1.9

1.8

2.3

Prices of PCE

0.3

2.0

1.5

2.0

2.4

Prices of PCE Excluding Food and Energy

2.1

1.8

1.7

1.3

2.0

Prices of Market Based PCE

-0.2

1.9

1.3

2.1

2.4

Prices of Market Based PCE Excluding Food and Energy

1.8

1.6

1.6

1.3

1.9

Real Disposable Personal Income*

3.1

2.8

2.7

2.5

2.2

Personal Saving As % Disposable Income

6.1

5.9

5.9

5.5

5.7

Note: PCE: personal consumption expenditures; NRFI: nonresidential fixed investment; RFI: residential fixed investment; GOV: government consumption expenditures and gross investment; ∆ PI: change in

private inventories; GDP - ∆ PI: final sales of domestic product; PP: percentage points; Personal savings rate: savings as percent of disposable income

*Percent change from quarter one year ago

Source: Bureau of Economic Analysis

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

Percentage shares of GDP are in Table I-10. PCE (personal consumption expenditures) is equivalent to 68.9 percent of GDP and is under pressure with stagnant real disposable income per person, elevated levels of unemployment and underemployment and higher savings rates than before the global recession, temporarily interrupted by financial repression in the form of zero interest rates. Gross private domestic investment is also growing slowly even with about two trillion dollars in cash holdings by companies. In a slowing world economy, it may prove more difficult to grow exports faster than imports to generate higher growth. Bouts of risk aversion revalue the dollar relative to most currencies in the world as investors increase their holdings of dollar-denominated assets.

Table I-10, US, Percentage Shares of GDP, %

 

IQ2017

GDP

100.0

PCE

68.9

   Goods

22.2

            Durable

7.5

            Nondurable

14.6

   Services

46.7

Gross Private Domestic Investment

16.6

    Fixed Investment

16.5

        NRFI

12.5

            Structures

2.8

            Equipment & Software

5.7

            Intellectual Property

4.1

        RFI

4.0

     Change in Private
      Inventories

0.0

Net Exports of Goods and Services

-2.9

       Exports

12.2

                    Goods

8.0

                    Services

4.2

       Imports

15.1

                     Goods

12.4

                     Services

2.7

Government

17.5

        Federal

6.6

           National Defense

3.9

           Nondefense

2.8

        State and Local

10.9

PCE: personal consumption expenditures; NRFI: nonresidential fixed investment; RFI: residential fixed investment

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

Table I-11 shows percentage point (PP) contributions to the annual levels of GDP growth in the earlier recessions 1958-1959, 1975-1976, 1982-1983 and 2009, 2010, 2011, 2012, 2013, 2014 2015 and 2016. The data incorporate the new revisions released by the BEA. The most striking contrast is in the rates of growth of annual GDP in the expansion phases of 6.9 percent in 1959, 5.4 percent in 1976, and 4.6 percent in 1983 followed by 7.3 percent in 1984 and 4.2 percent in 1985. In contrast, GDP grew 2.5 percent in 2010 after six consecutive quarters of growth, 1.6 percent in 2011 after ten consecutive quarters of expansion, 2.2 percent in 2012 after 14 quarters of expansion, 1.7 percent in 2013 after 18 consecutive quarters of expansion, 2.4 percent in 2014 after 22 consecutive quarters of expansion and 2.6 percent in 2015 after twenty-six consecutive quarters of expansion. GDP grew at 1.6 percent in 2016 after thirty consecutive quarters of expansion. Annual levels also show much stronger growth of PCEs in the expansions after the earlier contractions than in the expansion after the global recession of 2007. Gross domestic investment was much stronger in the earlier expansions than in 2010, 2011, 2012, 2013, 2014, 2015 and 2016.

Table I-11, US, Percentage Point Contributions to the Annual Growth Rate of GDP

 

GDP

PCE

GDI

∆ PI

Trade

GOV

1958

-0.7

0.52

-1.16

-0.17

-0.87

0.77

1959

6.9

3.49

2.82

0.83

0.00

0.59

1975

-0.2

1.36

-2.90

-1.23

0.86

0.49

1976

5.4

3.41

2.91

1.37

-1.05

0.12

1982

-1.9

0.86

-2.55

-1.30

-0.59

0.38

1983

4.6

3.54

1.60

0.28

-1.32

0.81

1984

7.3

3.32

4.73

1.90

-1.54

0.76

1985

4.2

3.25

-0.01

-1.03

-0.39

1.38

1986

3.5

2.63

0.03

-0.31

-0.29

1.14

1987

3.5

2.14

0.53

0.41

0.17

0.63

1988

4.2

2.66

0.45

-0.13

0.81

0.28

1989

3.7

1.86

0.72

0.17

0.51

0.59

1990

1.9

1.31

-0.45

-0.21

0.40

0.66

2009

-2.8

-1.08

-3.52

-0.76

1.19

0.64

2010

2.5

1.32

1.66

1.45

-0.46

0.02

2011

1.6

1.55

0.73

-0.14

-0.02

-0.65

2012

2.2

1.01

1.52

0.14

0.08

-0.38

2013

1.7

1.00

0.95

0.19

0.29

-0.56

2014

2.4

1.95

0.73

-0.14

-0.15

-0.16

2015

2.6

2.16

0.82

0.17

-0.71

0.32

2016

1.6

1.86

-0.26

-0.37

-0.13

0.14

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

Table I-12 provides more detail of the contributions to growth of GDP from 2009 to 2016 using annual-level data. PCEs contributed 1.32 PPs to GDP growth in 2010 of which 0.77 percentage points (PP) in goods and 0.55 PP in services. Gross private domestic investment (GPDI) deducted 3.52 PPs of GDP growth in 2009 of which -2.77 PPs by fixed investment and -0.76 PPs of inventory change (∆PI) and added 1.66 PPs of GDI in 2010 of which 0.21 PPs of fixed investment and 1.45 PPs of inventory accumulation (∆PI). Trade, or exports of goods and services net of imports, contributed 1.19 PPs in 2009 of which exports deducted 1.07 PPs and imports added 2.26 PPs. In 2010, trade deducted 0.46 PPs with exports contributing 1.33 PPs and imports deducting 1.79 PPs likely benefitting from dollar revaluation. In 2009, government added 0.64 PP of which 0.44 PPs by the federal government and 0.20 PPs by state and local government; in 2010, government added 0.02 PPs of which 0.37 PPs by the federal government with state and local government deducting 0.35 PPs. Table I-12 provides the estimates for 2011, 2012, 2013, 2014, 2015 and 2016. PCE contributed 1.55 PPs in 2011 after 1.32 PPs in 2010. The contribution of PCE fell to 1.01 points in 2012 and to 1.00 PPs in 2013, increasing to 1.95 PPs in 2014. PCE contributed 2.16 percentage points in 2015 and added 1.86 PPs in 2016. The breakdown into goods and services is similar but with contributions in 2012 of 0.63 PPs of goods and 0.38 PPs of services. In 2013, goods contributed 0.71 PPs and services 0.28 PPs. Goods contributed 0.89 PPs in 2014 and services contributed 1.06 PPS. Goods contributed 0.91 percentage points in 2015 and services 1.26 percentage points. Gross private domestic investment contributed 1.66 PPs in 2010 with 1.45 PPs of change of private inventories but the contribution of gross private domestic investment was only 0.73 PPs in 2011. The contribution of GDI in 2012 increased to 1.52 PPs with fixed investment increasing its contribution to 1.38 PPs and residential investment contributing 0.33 PPs for the first time since 2009. GDI contributed 1.52 PPs in 2012 with 1.38 PPs from fixed investment and 0.14 PPs from inventory change. GDI contribute 0.95 PPs in 2013, 0.73 PPs in 2014 and 0.82 PPs in 2015. GDI deducted 0.26 PPs in 2016 with 0.11 PPs of fixed investment and deduction of 0.37 PPP by inventory change. Net exports of goods and services deducted marginally in 2011 with 0.02 PPs and added 0.08 PPs in 2012. Net trade contributed 0.29 PPs in 2013 and deducted 0.15 PPs in 2014. Net trade deducted 0.71 percentage points in 2015 and deducted 0.13 PPs in 2016. The contribution of exports fell from 1.33 PPs in 2010 and 0.87 PPs in 2011 to only 0.46 PPs in 2012, 0.47 PPs in 2013 and 0.58 PPs in 2014. Exports contributed only 0.01 percentage points in 2015 and 0.04 percentage points in 2016. Government deducted 0.65 PPs in 2011, 0.38 PPs in 2012 and 0.56 PPs in 2013. Government deducted 0.16 PPs in 2014 and contributed 0.32 PPs in 2015, contributing 0.14 PPs in 2016. Demand weakened in 2013 with lower contribution of personal consumption expenditures of 1.00 PPs and of gross domestic investment of 0.76 PPs. PCE contributed 1.95 PPs in 2014 and GDI 0.73 PPs. PCE contributed 2.16 PPs in 2015 and GDI contributed 0.82 PPs. PCE contributed 1.86 PPs in 2016 and GDI deducted 0.26 PPs. Net trade contributed only 0.29 PPs in 2013 and deducted 0.15 PPs in 2014, deducting 0.71 PPs in 2015. Net trade deducted 0.13 PPs in 2016. The expansion since IIIQ2009 has been characterized by weak contributions of aggregate demand, which is the sum of personal consumption expenditures plus gross private domestic investment. The US did not recover strongly from the global recessions as typical in past cyclical expansions. Recoveries tend to be more sluggish as expansions mature. At the margin in IVQ2011, the acceleration of expansion was driven by inventory accumulation instead of aggregate demand of consumption and investment. Growth of PCE was partly the result of burning savings because of financial repression, which may not be sustainable in the future while creating multiple distortions of resource allocation and growth restraint.

Table I-12, US, Contributions to Growth of Gross Domestic Product in Percentage Points

 

2009

2010

2011

2012

2013

2014

2015

GDP Growth ∆%

-2.8

2.5

1.6

2.2

1.7

2.4

2.6

Personal Consumption Expenditures (PCE)

-1.08

1.32

1.55

1.01

1.00

1.95

2.16

  Goods

-0.68

0.77

0.71

0.63

0.71

0.89

0.91

     Durable

-0.41

0.43

0.43

0.53

0.45

0.49

0.51

     Nondurable

-0.27

0.34

0.28

0.10

0.27

0.40

0.40

  Services

-0.40

0.55

0.84

0.38

0.28

1.06

1.26

Gross Private Domestic Investment (GPDI)

-3.52

1.66

0.73

1.52

0.95

0.73

0.82

Fixed Investment

-2.77

0.21

0.86

1.38

0.76

0.87

0.65

    Nonresidential

-2.04

0.28

0.85

1.05

0.43

0.76

0.27

      Structures

-0.70

-0.49

0.06

0.32

0.04

0.29

-0.13

     Equipment, software

-1.29

0.70

0.66

0.58

0.26

0.32

0.21

      Intellectual Property

-0.05

0.07

0.13

0.15

0.13

0.15

0.19

    Residential

-0.73

-0.07

0.01

0.33

0.33

0.11

0.39

Change Private Inventories

-0.76

1.45

-0.14

0.14

0.19

-0.14

0.17

Net Exports of Goods and Services

1.19

-0.46

-0.02

0.08

0.29

-0.15

-0.71

   Exports

-1.07

1.33

0.87

0.46

0.47

0.58

0.01

      Goods

-1.03

1.08

0.57

0.34

0.29

0.41

-0.06

      Services

-0.04

0.25

0.29

0.12

0.18

0.17

0.07

   Imports

2.26

-1.79

-0.89

-0.38

-0.18

-0.72

-0.73

      Goods

2.15

-1.69

-0.78

-0.30

-0.17

-0.65

-0.65

      Services

0.10

-0.10

-0.11

-0.09

-0.02

-0.07

-0.08

Government Consumption Expenditures and Gross Investment

0.64

0.02

-0.65

-0.38

-0.56

-0.16

0.32

  Federal

0.44

0.37

-0.24

-0.15

-0.46

-0.19

0.00

    National Defense

0.27

0.18

-0.13

-0.18

-0.34

-0.19

-0.09

    Nondefense

0.17

0.19

-0.11

0.03

-0.12

0.00

0.09

  State and Local

0.20

-0.35

-0.41

-0.22

-0.09

0.03

0.32
 

2013

2014

2015

2016

GDP Growth ∆%

1.7

2.4

2.6

1.6

Personal Consumption Expenditures (PCE)

1.00

1.95

2.16

1.86

  Goods

0.71

0.89

0.91

0.79

     Durable

0.45

0.49

0.51

0.42

     Nondurable

0.27

0.40

0.40

0.36

  Services

0.28

1.06

1.26

1.08

Gross Private Domestic Investment (GPDI)

0.95

0.73

0.82

-0.26

Fixed Investment

0.76

0.87

0.65

0.11

    Nonresidential

0.43

0.76

0.27

-0.07

      Structures

0.04

0.29

-0.13

-0.08

     Equipment, software

0.26

0.32

0.21

-0.17

      Intellectual Property

0.13

0.15

0.19

0.19

    Residential

0.33

0.11

0.39

0.18

Change Private Inventories

0.19

-0.14

0.17

-0.37

Net Exports of Goods and Services

0.29

-0.15

-0.71

-0.13

   Exports

0.47

0.58

0.01

0.04

      Goods

0.29

0.41

-0.06

0.05

      Services

0.18

0.17

0.07

0.00

   Imports

-0.18

-0.72

-0.73

-0.17

      Goods

-0.17

-0.65

-0.65

-0.09

      Services

-0.02

-0.07

-0.08

-0.08

Government Consumption Expenditures and Gross Investment

-0.56

-0.16

0.32

0.14

  Federal

-0.46

-0.19

0.00

0.04

    National Defense

-0.34

-0.19

-0.09

-0.03

    Nondefense

-0.12

0.00

0.09

0.07

  State and Local

-0.09

0.03

0.32

0.10

Source: US Bureau of Economic Analysis

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

Manufacturing jobs not seasonally adjusted increased 41,000 from Mar 2016 to
Mar 2017 or at the average monthly rate of 3417. Industrial production increased 0.5 percent in Mar 2017 and increased 0.1 percent in Feb 2017 after decreasing 0.3 percent in Jan 2017, 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 31, 2017 (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 were small, and the contour of total IP is little changed. Total IP is still reported to have moved up about 22 percent from the end of the recession in mid-2009 through late 2014, to have declined in 2015, and to have moved sideways in 2016. The most notable difference between the current and the previous estimates is that total IP is now reported to have decreased about 2 3/4 percent in 2015, whereas it previously showed a decline of about 1 3/4 percent.[2] The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2015 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

Capacity for total industry is now reported to have expanded about 1 percent in 2015, a lower rate of increase than was reported earlier. Capacity was little changed in 2016 and is expected to increase 1 percent in 2017. Compared with prior reports, the rates of change in 2016 and 2017 are now a little smaller.

In the fourth quarter of 2016, capacity utilization for total industry stood at 75.8 percent, a rate 0.4 percentage point higher than previously published but still 4.1 percentage points below its long-run (1972–2016) average. Relative to earlier estimates, the utilization rates in recent years are now a little higher.”

The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 31, 2017 (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 were small, and the contour of total IP is little changed. Total IP is still reported to have moved up about 22 percent from the end of the recession in mid-2009 through late 2014, to have declined in 2015, and to have moved sideways in 2016. The most notable difference between the current and the previous estimates is that total IP is now reported to have decreased about 2 3/4 percent in 2015, whereas it previously showed a decline of about 1 3/4 percent.[2] The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2015 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

Capacity for total industry is now reported to have expanded about 1 percent in 2015, a lower rate of increase than was reported earlier. Capacity was little changed in 2016 and is expected to increase 1 percent in 2017. Compared with prior reports, the rates of change in 2016 and 2017 are now a little smaller. In the fourth quarter of 2016, capacity utilization for total industry stood at 75.8 percent, a rate 0.4 percentage point higher than previously published but still 4.1 percentage points below its long-run (1972–2016) average. Relative to earlier estimates, the utilization rates in recent years are now a little higher.”

Manufacturing fell 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increased 15.5 percent from the trough in Apr 2009 to Dec 2016. Manufacturing grew 18.3 percent from the trough in Apr 2009 to Mar 2017. Manufacturing in Mar 2017 is lower by 8.1 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 IQ2017 would have accumulated to 31.4 percent. GDP in IQ2017 would be $19,699.2 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2856.8 billion than actual $16,842.4 billion. There are about two trillion dollars of GDP less than at trend, explaining the 22.9 million unemployed or underemployed equivalent to actual unemployment/underemployment of 13.6 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/04/twenty-three-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/increasing-interest-rates-twenty-four.html). US GDP in IQ2017 is 14.5 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $16,842.4 billion in IQ2017 or 12.3 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Mar 1919 to Mar 2017. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 144.8512 in Mar 2017. The actual index NSA in Mar 2017 is 103.4144, which is 28.6 percent below trend. Manufacturing output grew at average 2.1 percent between Dec 1986 and Mar 2017. Using trend growth of 2.1 percent per year, the index would increase to 131.1817 in Mar 2017. The output of manufacturing at 103.4144 in Mar 2017 is 21.2 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 87.0 percent in IVQ2016. Most of US national income is in the form of services. In Mar 2017, there were 144.949 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 122.258 million NSA in Mar 2017 accounted for 84.3 percent of total nonfarm jobs of 144.949 million, of which 12.329 million, or 10.1 percent of total private jobs and 8.5 percent of total nonfarm jobs, were in manufacturing. Private service-providing jobs were 102.659 million NSA in Mar 2017, or 70.8 percent of total nonfarm jobs and 84.0 percent of total private-sector jobs. Manufacturing has share of 10.2 percent in US national income in IVQ2016 and durable goods 6.0 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

 

SAAR IIIQ2016

% Total

SAAR
IVQ2016

% Total

National Income WCCA

16,173.7

100.0

16,335.7

100.0

Domestic Industries

15,969.7

98.7

16,092.7

98.5

Private Industries

14,095.4

87.2

14,207.5

87.0

Agriculture

122.0

0.8

113.3

0.7

Mining

187.7

1.2

189.4

1.2

Utilities

172.0

1.1

173.9

1.1

Construction

771.3

4.8

788.6

4.8

Manufacturing

1676.5

10.4

1665.7

10.2

Durable Goods

977.4

6.0

980.7

6.0

Nondurable Goods

699.2

4.3

685.0

4.2

Wholesale Trade

957.9

5.9

951.8

5.8

Retail Trade

1136.2

7.0

1138.5

7.0

Transportation & WH

505.7

3.1

502.5

3.1

Information

596.0

3.7

593.0

3.6

Finance, Insurance, RE

2862.6

17.7

2922.5

17.9

Professional & Business Services

2293.6

14.2

2313.0

14.2

Education, Health Care

1651.7

10.2

1666.1

10.2

Arts, Entertainment

688.0

4.3

706.9

4.3

Other Services

474.2

2.9

482.4

3.0

Government

1874.3

11.6

1885.1

11.5

Rest of the World

204.0

1.3

243.0

1.5

Notes: SSAR: Seasonally-Adjusted Annual Rate; 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

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 (http://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) (http://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 quarters of cyclical expansion from IIIQ2009 to IVQ2016. The average annual growth rate in the first eight quarters of expansion from IIIQ2009 to IIQ2011 was 3.2 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 12.5 percent. Growth has fallen from the SAAR of 17.3 percent in IIIQ2011 to 0.1 percent in IIIQ2012, recovering to 6.9 percent in IVQ2012 and increasing to 7.0 percent in IQ2013. The SAAR of fixed investment fell to 2.9 percent in IIIQ2013 and to 6.6 percent in IVQ2013. The SAAR of fixed investment decreased to 5.3 percent in IQ2014. Fixed investment grew at the SAAR of 7.2 percent in IIQ2014 and at 7.4 percent in IIIQ2014. Fixed investment grew at 1.3 percent in IVQ2014, 3.7 percent in IQ2015 and 4.3 percent in IIQ2015. Fixed investment grew at 5.7 percent in IIIQ2015 and fell at 0.2 percent in IVQ2015. Fixed investment decreased at 0.9 percent in IQ2016 and fell at 1.1 percent in IIQ2016. Fixed investment increased at 0.1 percent in IIIQ2016 and increased at 2.9 percent in IVQ2016. Fixed investment increased at 10.4 percent in IQ2017. 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

-12.2

9.4

13.1

-7.1

-27.4

0.8

II

3.2

-12.1

16.0

16.6

-5.5

-14.2

13.6

III

0.1

-9.3

24.4

8.2

-12.1

-0.5

-0.4

IV

-1.5

0.2

24.3

7.3

-23.9

-2.8

8.5
       

1985

    

2011

I

      

3.7

    

-0.9

II

      

5.2

    

8.2

III

      

-1.6

    

17.3

IV

      

7.8

    

9.9
       

1986

    

2012

I

      

1.1

    

14.7

II

      

0.1

    

6.9

III

      

-1.8

    

0.1

IV

      

3.1

    

6.9
       

1987

    

2013

I

      

-6.7

    

7.0

II

      

6.3

    

4.3

III

      

7.1

    

2.9

IV

      

-0.2

    

6.6
       

1988

    

2014

I

      

0.2

    

5.3

II

      

8.1

    

7.2

III

      

1.9

    

7.4

IV

      

4.8

    

1.3
       

1989

    

2015

IQ

      

3.6

    

3.7

IIQ

      

0.5

    

4.3

IIIQ

      

7.2

    

5.7

IVQ

      

-5.0

    

-0.2
       

1990

    

2016

IQ

      

4.8

    

-0.9

IIQ

      

-7.7

    

-1.1

IIIQ

      

-3.3

    

0.1

IVQ

      

-9.8

    

2.9
       

1991

    

2017

I

      

-10.6

    

10.4

Source: US Bureau of Economic Analysis http://www.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 1990. 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) (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).

Chart IA1-1, US, Real Private Fixed Investment, Seasonally-Adjusted Annual Rates Percent Change from Prior Quarter, 1980-1990

Source: US Bureau of Economic Analysis

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

Weak behavior of real private fixed investment from 2007 to 2017 is in Chart IA1-2. Growth rates of real private fixed investment were much lower during the initial phase of the current economic cycle and have entered sharp trend of decline.

Chart IA1-2, US, Real Private Fixed Investment, Seasonally-Adjusted Annual Rates Percent Change from Prior Quarter, 2007-2017

Source: US Bureau of Economic Analysis

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

Table IA1-2 provides real private fixed investment at seasonally adjusted annual rates from IVQ2007 to IQ2017 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 $951.6 billion of chained 2009 dollars, growing to $1,245.6 billion in IIIQ1990 or 30.9 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). Real gross private domestic investment in the US increased 11.3 percent from $2605.2 billion in IVQ2007 to $2,898.4 billion in IQ2017. Real private fixed investment increased 10.9 percent from $2,586.3 billion of chained 2009 dollars in IVQ2007 to $2,869.1 billion in IQ2017. Private fixed investment fell relative to IVQ2007 in all quarters preceding IQ2014 and changed 0.0 percent in IIIQ2016, declining 0.3 percent in IIQ2016 and falling 0.2 percent in IQ2016. Private fixed investment changed 0.0 percent in IIIQ2016 and increased 0.7 percent in IVQ2016. Growth of real private investment in Table IA1-2 is mediocre for all but four quarters from IIQ2011 to IQ2012. 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 2009 Dollars and ∆%

 

Real PFI, Billions Chained 2009 Dollars

∆% Relative to IVQ2007

∆% Relative to Prior Quarter

∆%
over
Year Earlier

IVQ2007

2586.3

NA

-0.9

-1.4

IQ2008

2539.1

-1.8

-1.8

-3.0

IIQ2008

2503.4

-3.2

-1.4

-4.6

IIIQ2008

2424.1

-6.3

-3.2

-7.1

IV2008

2263.8

-12.5

-6.6

-12.5

IQ2009

2089.3

-19.2

-7.7

-17.7

IIQ2009

2011.0

-22.2

-3.7

-19.7

IIIQ2009

2008.4

-22.3

-0.1

-17.1

IVQ2009

1994.1

-22.9

-0.7

-11.9

IQ2010

1997.9

-22.8

0.2

-4.4

IIQ2010

2062.8

-20.2

3.2

2.6

IIIQ2010

2060.8

-20.3

-0.1

2.6

IVQ2010

2103.1

-18.7

2.1

5.5

IQ2011

2098.4

-18.9

-0.2

5.0

IIQ2011

2140.2

-17.2

2.0

3.8

IIIQ2011

2227.5

-13.9

4.1

8.1

IVQ2011

2280.6

-11.8

2.4

8.4

IQ2012

2360.4

-8.7

3.5

12.5

IIQ2012

2399.8

-7.2

1.7

12.1

IIIQ2012

2400.4

-7.2

0.0

7.8

IVQ2012

2441.0

-5.6

1.7

7.0

IQ2013

2482.7

-4.0

1.7

5.2

IIQ2013

2508.8

-3.0

1.1

4.5

IIIQ2013

2526.7

-2.3

0.7

5.3

IVQ2013

2567.2

-0.7

1.6

5.2

IQ2014

2600.5

0.5

1.3

4.7

IIQ2014

2646.1

2.3

1.8

5.5

IIIQ2014

2693.4

4.1

1.8

6.6

IVQ2014

2702.3

4.5

0.3

5.3

IQ2015

2727.2

5.4

0.9

4.9

IIQ2015

2756.0

6.6

1.1

4.2

IIIQ2015

2794.5

8.1

1.4

3.8

IVQ2015

2793.3

8.0

0.0

3.4

IQ2016

2786.7

7.7

-0.2

2.2

IIQ2016

2778.8

7.4

-0.3

0.8

IIIQ2016

2779.3

7.5

0.0

-0.5

IVQ2016

2798.9

8.2

0.7

0.2

IQ2017

2869.1

10.9

2.5

3.0

PFI: Private Fixed Investment

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

Chart IA1-3 provides real private fixed investment in chained dollars of 2009 from 2007 to 2017. Real private fixed investment increased 10.9 percent from $2,586.3 billion of chained 2009 dollars in IVQ2007 to $2,869.1 billion in IQ2017.

Chart IA1-3, US, Real Private Fixed Investment, Billions of Chained 2009 Dollars, 2007 to 2017

Source: US Bureau of Economic Analysis

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

Chart IA1-4 provides real gross private domestic investment in chained dollars of 2009 from 1980 to 1990. Real gross private domestic investment climbed 30.9 percent to $1,245.6 billion of 2009 dollars in IIIQ1990 above the level of $951.6 billion in IQ1980. 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).

Chart IA1-4, US, Real Gross Private Domestic Investment, Billions of Chained 2009 Dollars at Seasonally Adjusted Annual Rate, 1980-1990

Source: US Bureau of Economic Analysis

http://www.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 2009 from 2007 to 2017. Real gross private domestic investment reached a level of $2,898.4 billion in IQ2017, which was only 11.3 percent higher than the level of $2605.2 billion in IVQ2007 (http://www.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, 2007-2017

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

Table IA1-3 shows that the share of gross private domestic investment in GDP has fallen from 19.4 percent in IQ2000 and 19.8 percent in IQ2006 to 16.6 percent in IQ2017. There are declines in percentage shares in GDP of all components with sharp reduction of residential investment from 4.8 percent in IQ2000 and 6.6 percent in IQ2006 to 4.0 percent in IQ2017. The share of fixed investment in GDP fell from 19.2 percent in IQ2000 and 19.2 percent in IQ2006 to 16.5 percent in IQ2017.

Table IA1-3, Percentage Shares of Gross Private Domestic Investment and Components in Gross Domestic Product, % of GDP

 

IQ2017

IQ2006

IQ2000

Gross Private Domestic Investment

16.6

19.8

19.4

  Fixed Investment

16.5

19.2

19.2

     Nonresidential

12.5

12.7

14.4

          Structures

2.8

2.8

3.0

          Equipment

          and Software

5.7

6.2

7.5

          Intellectual
           Property

4.1

3.6

4.0

     Residential

4.0

6.6

4.8

   Change in Private Inventories

0.0

0.5

0.2

Source: US Bureau of Economic Analysis http://www.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 2016. There was sharp drop during the current economic cycle with almost no 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, 1929-2016

Source: US Bureau of Economic Analysis

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

Chart IA1-7 provides percentage shares of private fixed investment in GDP with annual data from 1929 to 2016. 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, 1929-2016

Source: US Bureau of Economic Analysis

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

Chart IA1-8 provides percentage shares in GDP of nonresidential investment from 1929 to 2016. 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, 1929-2016

Source: US Bureau of Economic Analysis

http://www.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 2016. 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, 1929-2016

Source: US Bureau of Economic Analysis

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

Chart IA1-10 provides percentage shares of residential investment in GDP with annual data from 1929 to 2016. 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, 1929-2016

Source: US Bureau of Economic Analysis

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

Finer detail is provided by the quarterly share of residential investment in GDP from 1979 to 2016 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, 1979-2017

Source: US Bureau of Economic Analysis

http://www.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 2016. 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 but stabilized at a lower level in the past decade.

Chart IA1-12, US, Percentage Share of Intellectual Property Products Investment in Gross Domestic Product, Annual, 1929-2016

Source: US Bureau of Economic Analysis

http://www.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 2016. The share stabilized in the 2000s.

Chart IA1-13, US, Percentage Share of Intellectual Property Investment in Gross Domestic Product, Quarterly, 1979-2017

Source: US Bureau of Economic Analysis

http://www.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 (BES), residential investment (RES), intellectual property products (IPP) and change in inventories (∆INV) for the cyclical expansions from IQ1983 to IVQ1988 and from IIIQ2009 to IVQ2016. GDI contributed 1.62 percentage points to GDP in IQ2015 with 0.61 percentage points by PFI, 1.01 percentage points by inventory accumulation and 0.03 percentage points by intellectual property products. GDI contributed 0.18 percentage points to GDP growth in IIQ2015: 0.70 percentage points in PFI, 0.21 percentage points in NRES and 0.49 percentage points in RES. Inventory investment deducted 0.52 percentage points and IPP added 0.31 percentage points. GDI added 0.35 percentage points to GDP growth in IIIQ2015 with deduction of 0.57 percentage points by inventory divestment while BSE deducted 0.12 percentage points. PFI added 0.92 percentage points, nonresidential investment added 0.49 percentage points and residential investment added 0.43 percentage points. IPP added 0.08 percentage points. GDI deducted 0.39 percentage points in IVQ2015 with percentage point deductions of 0.43 by NRES, 0.03 by PFI, 0.45 by BES, 0.45 by NRES and 0.36 by inventory divestment. Percentage point contributions were 0.18 by IPP and 0.40 by RES. GDI deducted 0.56 percentage points from GDP growth in IQ2016 with percentage point deduction of 0.15 by fixed investment, 0.44 by nonresidential investment and 0.41 by inventory change. Residential investment added 0.29 percentage points and intellectual property products contributed 0.15 percentage points. GDI deducted 1.34 percentage points from GDP growth in IIQ2016 with deductions of 0.18 by PFI, 0.06 by BES and 0.31 by RES. Inventory investment deducted 1.16. IPP added 0.35 and NRES contributed 0.12. GDI contributed 0.50 percentage points to GDP growth in IIIQ2016 with contributions by NRES, BES, IPP and inventory investment. PFI added 0.02 percentage points and RES deducted 0.16 percentage points. GDI contributed 1.47 percentage points to GDP growth in IVQ2016 with contributions by NRES, IPP, RES and inventory investment. PFI added 0.46 percentage points, RES added 0.35 percentage points and inventory investment added 1.01 percentage points. GDI contributed 0.69 percentage points to GDP growth in IQ2017 with contributions by all segments except for deduction of 0.93 percentage points by inventory divestment. PFI contributed 1.62 percentage points. NRES contributed 1.12 percentage points and RES added 0.50 percentage points. BES contributed 0.55 percentage points and IPP added 0.08 percentage points.

Table IA1-4, US, Contributions to the Rate of Growth of Real GDP in Percentage Points

 

GDP

GDI

PFI

NRES

BES

IPP

RES

∆INV

2017

                

I

0.7

0.69

1.62

1.12

0.55

0.08

0.50

-0.93

2016

                

I

0.8

-0.56

-0.15

-0.44

0.00

0.15

0.29

-0.41

II

1.4

-1.34

-0.18

0.12

-0.06

0.35

-0.31

-1.16

III

3.5

0.50

0.02

0.18

0.30

0.13

-0.16

0.49

IV

2.1

1.47

0.46

0.11

-0.05

0.05

0.35

1.01

2015

                

I

2.0

1.62

0.61

0.18

-0.39

0.03

0.43

1.01

II

2.6

0.18

0.70

0.21

-0.07

0.31

0.49

-0.52

III

2.0

0.35

0.92

0.49

-0.12

0.08

0.43

-0.57

IV

0.9

-0.39

-0.03

-0.43

-0.45

0.18

0.40

-0.36

2014

                

I

-1.2

-1.10

0.79

0.84

0.66

0.18

-0.04

-1.89

II

4.0

1.79

1.12

0.76

0.22

0.17

0.36

0.67

III

5.0

1.49

1.16

1.05

-0.08

0.27

0.12

0.32

IV

2.3

0.45

0.22

-0.14

0.13

0.29

0.36

0.23

2013

                

I

2.8

2.04

1.12

0.72

-0.14

0.29

0.41

0.92

II

0.8

0.78

0.70

0.35

0.27

-0.13

0.35

0.08

III

3.1

2.08

0.48

0.29

0.44

0.14

0.18

1.60

IV

4.0

0.91

1.01

1.16

0.06

0.04

-0.15

-0.11

2012

                

I

2.7

1.47

2.00

1.37

0.48

0.07

0.63

-0.53

II

1.9

1.53

0.98

0.88

0.27

0.14

0.10

0.56

III

0.5

-0.18

0.00

-0.27

-0.12

0.05

0.27

-0.18

IV

0.1

-0.51

1.03

0.46

-0.21

0.26

0.57

-1.54

2011

                

I

-1.5

-1.07

-0.11

-0.09

-0.73

0.05

-0.02

-0.96

II

2.9

2.14

1.10

0.97

0.63

0.12

0.13

1.04

III

0.8

0.15

2.25

2.06

0.56

0.19

0.19

-2.10

IV

4.6

4.16

1.36

1.08

0.34

0.26

0.28

2.80

2010

                

I

1.7

1.77

0.11

0.46

1.25

-0.07

-0.35

1.66

II

3.9

2.86

1.76

1.21

1.02

-0.08

0.56

1.09

III

2.7

1.86

-0.04

0.90

0.83

0.22

-0.94

1.90

IV

2.5

-0.51

1.13

0.94

0.57

0.19

0.19

-1.63

2009

                

I

-5.4

-7.02

-4.75

-3.58

-2.25

-0.23

-1.17

-2.26

II

-0.5

-3.25

-2.13

-1.46

-0.60

0.16

-0.66

-1.12

III

1.3

-0.40

-0.02

-0.54

0.25

0.04

0.52

-0.38

IV

3.9

4.05

-0.36

-0.37

0.36

0.25

0.01

4.40

1982

                

I

-6.5

-7.59

-2.26

-1.45

-0.83

0.14

-0.81

-5.33

II

2.2

-0.06

-2.32

-1.89

-1.20

0.08

-0.44

2.26

III

-1.4

-0.62

-1.73

-1.72

-0.55

0.06

-0.02

1.11

IV

0.4

-5.37

-0.03

-1.05

-0.57

0.00

1.01

-5.33

1983

                

I

5.3

2.36

1.44

-0.92

-0.27

0.16

2.36

0.92

II

9.4

5.96

2.53

0.67

1.24

0.29

1.86

3.43

III

8.1

4.40

3.82

2.13

1.43

0.31

1.70

0.57

IV

8.5

6.94

3.93

3.14

2.32

0.35

0.79

3.01

1984

                

I

8.2

7.23

2.29

1.71

0.46

0.30

0.58

4.94

II

7.2

2.57

2.86

2.52

1.36

0.29

0.34

-0.29

III

4.0

1.69

1.48

1.70

0.88

0.25

-0.22

0.21

IV

3.2

-1.08

1.36

1.34

0.86

0.29

0.02

-2.44

1985

                

I

4.0

-2.14

0.72

0.67

-0.23

0.14

0.05

-2.86

II

3.7

1.34

0.99

0.83

0.64

0.20

0.16

0.35

III

6.4

-0.43

-0.28

-0.62

-0.38

0.13

0.34

-0.15

IV

3.0

2.80

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

1.9

-1.30

0.00

-1.12

0.34

0.15

1.12

-1.30

III

4.1

-1.97

-0.34

-0.63

-0.17

0.10

0.28

-1.62

IV

2.1

0.24

0.53

0.48

0.30

0.10

0.05

-0.29

1987

                

I

2.8

1.98

-1.30

-1.26

-0.97

0.07

-0.04

3.28

II

4.6

0.08

1.07

1.00

0.76

0.08

0.07

-0.99

III

3.7

0.03

1.22

1.39

0.70

0.11

-0.17

-1.19

IV

6.8

4.94

-0.01

-0.05

-0.48

0.16

0.04

4.95

1988

                

I

2.3

-3.62

0.06

0.41

0.82

0.15

-0.36

-3.68

II

5.4

1.72

1.39

1.14

0.67

0.18

0.25

0.33

III

2.3

0.38

0.33

0.32

0.29

0.22

0.01

0.05

IV

5.4

1.11

0.84

0.71

0.34

0.40

0.13

0.27

GDP: Gross Domestic Product; GDI: Gross Domestic Investment; PFI: Private Fixed Investment; NRES: Nonresidential; BES: 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 http://www.bea.gov/iTable/index_nipa.cfm

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

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

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

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

2. Surveillance. The IMF conducts surveillance of the world economy, finance and public finance with continuous research and analysis. Important documents of this effort are the World Economic Outlook (http://www.imf.org/external/ns/cs.aspx?id=29), Global Financial Stability Report (http://www.imf.org/external/pubs/ft/gfsr/index.htm) and Fiscal Monitor (http://www.imf.org/external/ns/cs.aspx?id=262).

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

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

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

Table I-1 is constructed with the database of the IMF (http://www.imf.org/external/ns/cs.aspx?id=29) to show GDP in dollars in 2015 and the growth rate of real GDP of the world and selected regional countries from 2015 to 2018. The data illustrate the concept often repeated of “two-speed recovery” of the world economy from the recession of 2007 to 2009. The IMF has changed its forecast of the world economy to 3.1 percent in 2016 but accelerating to 3.5 percent in 2017 and 3.6 percent in 2018. Slow-speed recovery occurs in the “major advanced economies” of the G7 that account for $34,446 billion of world output of $74,197 billion, or 46.4 percent, but are projected to grow at much lower rates than world output, 1.8 percent on average from 2015 to 2019, in contrast with 3.4 percent for the world as a whole. While the world would grow 14.3 percent in the four years from 2015 to 2018, the G7 as a whole would grow 7.5 percent. The difference in dollars of 2015 is high: growing by 14.3 percent would add around $10.6 trillion of output to the world economy, or roughly, over two times the output of the economy of Japan of $4,382 billion but growing by 7.5 percent would add $5.6 trillion of output to the world, or about the output of Japan in 2015. The “two speed” concept is in reference to the growth of the 150 countries labeled as emerging and developing economies (EMDE) with joint output in 2015 of $29,333 billion, or 39.5 percent of world output. The EMDEs would grow cumulatively 18.8 percent or at the average yearly rate of 4.4 percent, contributing $5.5 trillion from 2015 to 2019 or the equivalent of somewhat more than one half the GDP of $11,226 billion of China in 2015. The final four countries in Table I-1 often referred as BRIC (Brazil, Russia, India, China), are large, rapidly growing emerging economies. Their combined output in 2015 adds to $16,479 billion, or 22.2 percent of world output, which is equivalent to 47.8 percent of the combined output of the major advanced economies of the G7.

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

 

GDP USD Billions 2015

Real GDP ∆%
2015

Real GDP ∆%
2016

Real GDP ∆%
2017

Real GDP ∆%
2018

World

74,197

3.4

3.1

3.5

3.6

G7

34,446

2.0

1.5

1.9

1.9

Canada

1,553

0.9

1.4

1.9

2.0

France

2,420

1.3

1.2

1.4

1.7

DE

3,365

1.5

1.8

1.6

1.5

Italy

1,826

0.8

0.9

0.8

0.8

Japan

4,382

1.2

1.0

1.3

0.6

UK

2,863

2.2

1.8

2.0

1.5

US

18,037

2.6

1.6

2.3

2.5

Euro Area

11,606

2.0

1.7

1.7

1.6

DE

3,365

1.5

1.8

1.6

1.5

France

2,420

1.3

1.2

1.4

1.7

Italy

1,826

0.8

0.9

0.8

0.8

POT

199

1.6

1.4

1.7

1.5

Ireland

283

26.3

5.2

3.5

3.2

Greece

195

-0.2

0.0

2.2

2.7

Spain

1,194

3.2

3.2

2.6

2.1

EMDE

29,333

4.2

4.1

4.5

4.8

Brazil

1,799

-3.8

-3.6

0.2

1.7

Russia

1,366

-2.8

-0.3

1.4

1.4

India

2,088

7.9

6.8

7.2

7.7

China

11,226

6.9

6.7

6.6

6.2

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

Continuing high rates of unemployment in advanced economies constitute another characteristic of the database of the WEO (http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx). Table I-2 is constructed with the WEO database to provide rates of unemployment from 2014 to 2018 for major countries and regions. In fact, unemployment rates for 2014 in Table I-2 are high for all countries: unusually high for countries with high rates most of the time and unusually high for countries with low rates most of the time. The rates of unemployment are particularly high in 2014 for the countries with sovereign debt difficulties in Europe: 13.9 percent for Portugal (POT), 11.3 percent for Ireland, 26.5 percent for Greece, 24.4 percent for Spain and 12.6 percent for Italy, which is lower but still high. The G7 rate of unemployment is 6.4 percent. Unemployment rates are not likely to decrease substantially if slow growth persists in advanced economies.

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

 

% Labor Force 2014

% Labor Force 2015

% Labor Force 2016

% Labor Force 2017

% Labor Force 2018

World

NA

NA

NA

NA

NA

G7

6.4

5.8

5.4

5.3

5.2

Canada

6.9

6.9

7.0

6.9

6.8

France

10.3

10.4

10.0

9.6

9.3

DE

5.0

4.6

4.2

4.2

4.2

Italy

12.6

11.9

11.7

11.4

11.0

Japan

3.6

3.4

3.1

3.1

3.1

UK

6.2

5.4

4.9

4.9

5.1

US

6.2

5.3

4.9

4.7

4.6

Euro Area

11.7

10.9

10.0

9.4

9.1

DE

5.0

4.6

4.2

4.2

4.2

France

10.3

10.4

10.0

9.6

9.3

Italy

12.6

11.9

11.7

11.4

11.0

POT

13.9

12.4

11.1

10.6

10.1

Ireland

11.3

9.4

7.9

6.5

6.3

Greece

26.5

24.9

23.8

21.9

21.0

Spain

24.4

22.1

19.6

17.7

16.6

EMDE

NA

NA

NA

NA

NA

Brazil

6.8

8.3

11.3

12.1

11.6

Russia

5.2

5.6

5.5

5.5

5.5

India

NA

NA

NA

NA

NA

China

4.1

4.0

4.0

4.0

4.0

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

Source: IMF World Economic Outlook

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

The database of the WEO (http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx) is used to construct the debt/GDP ratios of regions and countries in Table I-3. The concept used is general government debt, which consists of central government debt, such as Treasury debt in the US, and all state and municipal debt. Net debt is provided for all countries except for the only available gross debt for China, Russia and India. The net debt/GDP ratio of the G7 increases from 82.8 in 2014 to 83.1 in 2018. G7 debt is pulled by the high debt of Japan that reaches 120.1 percent of GDP in 2018. US general government debt increases from 80.3 percent of GDP in 2014 to 83.1 percent of GDP in 2018. Debt/GDP ratios of countries with sovereign debt difficulties in Europe are particularly worrisome. General government net debts of Italy, Greece and Portugal exceed 100 percent of GDP or are expected to exceed 100 percent of GDP by 2018. The only country with relatively lower debt/GDP ratio is Spain with 78.6 in 2014, increasing to 80.4 in 2018. Ireland’s debt/GDP ratio decreases from 86.3 in 2014 to 65.9 in 2018. Fiscal adjustment, voluntary or forced by defaults, may squeeze further economic growth and employment in many countries as analyzed by Blanchard (2012WEOApr). Defaults could feed through exposures of banks and investors to financial institutions and economies in countries with sounder fiscal affairs.

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

 

% Debt/
GDP 2014

% Debt/
GDP 2015

% Debt/
GDP 2016

% Debt/
GDP 2017

% Debt/
GDP 2018

World

NA

NA

NA

NA

NA

G7

82.8

81.8

83.0

83.1

83.1

Canada

28.1

25.2

27.6

26.4

25.1

France

87.4

87.4

88.3

89.1

89.1

DE

50.1

47.8

45.0

42.7

40.6

Italy

112.5

112.5

113.3

113.8

113.0

Japan

126.2

118.4

119.8

119.9

120.1

UK

79.5

80.4

80.7

80.4

80.2

US

80.3

80.5

81.5

82.4

83.1

Euro Area

68.3

67.5

67.0

66.3

65.3

DE

50.1

47.8

45.0

42.7

40.6

France

87.4

87.4

88.3

89.1

89.1

Italy

112.5

112.5

113.3

113.8

113.0

POT

120.0

121.6

121.0

121.1

120.1

Ireland

86.3

71.8

69.9

67.8

65.9

Greece*

180.1

179.4

181.3

180.7

181.5

Spain

78.6

80.2

80.4

80.4

80.4

EMDE*

40.7

44.3

47.3

48.5

49.5

Brazil

33.1

35.6

48.2

51.5

53.4

Russia*

15.9

15.9

17.0

17.1

17.3

India*

68.3

69.6

69.5

67.8

66.1

China*

39.8

42.6

46.2

49.3

52.0

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

The primary balance consists of revenues less expenditures but excluding interest revenues and interest payments. It measures the capacity of a country to generate sufficient current revenue to meet current expenditures. There are various countries with primary surpluses in 2014: Germany 1.7 percent and Italy 1.4 percent. There are also various countries with expected primary surpluses by 2018: Portugal 1.8 percent, Italy 2.1 percent and so on. Most countries in Table I-4 face significant fiscal adjustment in the future without “fiscal space.” Investors in government securities may require higher yields when the share of individual government debts hit saturation shares in portfolios. The tool of analysis of Cochrane (2011Jan, 27, equation (16)) is the government debt valuation equation:

(Mt + Bt)/Pt = Et∫(1/Rt, t+τ)st+τdτ (1)

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

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

 

% GDP 2014

% GDP 2015

% GDP 2016

% GDP 2017

% GDP 2018

World

NA

NA

NA

NA

NA

G7

-2.0

-1.4

-1.8

-1.6

-1.6

Canada

0.0

-0.5

-1.2

-1.7

-1.6

France

-1.9

-1.6

-1.5

-1.6

-1.2

DE

1.7

1.9

1.9

1.5

1.4

Italy

1.4

1.3

1.4

1.1

2.1

Japan

-5.6

-3.1

-4.0

-3.9

-3.3

UK

-3.8

-2.9

-1.4

-1.0

-0.4

US

-2.2

-1.6

-2.3

-1.9

-2.2

Euro Area

-0.2

0.1

0.3

0.3

0.5

DE

1.7

1.9

1.9

1.5

1.4

France

-1.9

-1.6

-1.5

-1.6

-1.2

Italy

1.4

1.3

1.4

1.1

2.1

POT

-2.8

-0.1

1.6

2.1

1.8

Ireland

-0.3

0.5

1.3

1.6

1.7

Greece

0.0

0.2

3.3

1.8

2.0

Spain

-2.9

-2.4

-2.2

-0.9

-0.4

EMDE

-0.9

-2.7

-3.0

-2.5

-1.9

Brazil

-0.6

-1.9

-2.5

-2.3

-1.1

Russia

-0.7

-3.1

-3.1

-2.1

-1.3

India

-2.8

-2.5

-1.8

-1.6

-1.7

China

-0.4

-2.2

-3.0

-2.7

-2.3

*General Government Net Lending/Borrowing

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

The database of the World Economic Outlook of the IMF (http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx) is used to obtain government net lending/borrowing as percent of GDP in Table I-5. Interest on government debt is added to the primary balance to obtain overall government fiscal balance in Table I-5. For highly indebted countries there is an even tougher challenge of fiscal consolidation. Adverse expectations on the success of fiscal consolidation may drive up yields on government securities that could create hurdles to adjustment, growth and employment.

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

 

% GDP 2014

% GDP 2015

% GDP 2016

% GDP 2017

% GDP 2018

World

NA

NA

NA

NA

NA

G7

-3.8

-3.0

-3.5

-3.3

-3.3

Canada

-0.5

-1.1

-1.9

-2.4

-2.2

France

-4.0

-3.5

-3.3

-3.2

-2.8

DE

0.3

0.7

0.8

0.6

0.6

Italy

-3.0

-2.7

-2.4

-2.4

-1.4

Japan

-6.2

-3.5

-4.2

-4.0

-3.3

UK

-5.6

-4.4

-3.1

-2.8

-2.1

US

-4.2

-3.5

-4.4

-4.1

-4.5

Euro Area

-2.6

-2.1

-1.7

-1.5

-1.2

DE

0.3

0.7

0.8

0.6

0.6

France

-4.0

-3.5

-3.3

-3.2

-2.8

Italy

-3.0

-2.7

-2.4

-2.4

-1.4

POT

-7.2

-4.4

-2.3

-1.9

-2.2

Ireland

-3.7

-1.9

-0.9

-0.5

-0.3

Greece

-4.1

-3.4

0.0

-1.5

-1.0

Spain

-5.9

-5.1

-4.6

-3.3

-2.7

EMDE

-2.5

-4.6

-4.8

-4.4

-3.9

Brazil

-6.0

-10.3

-9.0

-9.1

-7.5

Russia

-1.1

-3.4

-3.7

-2.6

-1.9

India

-7.3

-7.1

-6.6

-6.4

-6.3

China

-0.9

-2.8

-3.7

-3.7

-3.4

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

There were some hopes that the sharp contraction of output during the global recession would eliminate current account imbalances. Table I-6 constructed with the database of the WEO (http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx) shows that external imbalances have been maintained in the form of current account deficits and surpluses. China’s current account surplus is 2.6 percent of GDP for 2014 and is projected to stabilize at 1.2 percent of GDP in 2018. At the same time, the current account deficit of the US is 2.3 percent of GDP in 2014 and is projected at 23.3percent of GDP in 2018. The current account surplus of Germany is 7.3 percent for 2014 and remains at a high 8.0 percent of GDP in 2018. Japan’s current account surplus is 0.8 percent of GDP in 2014 and increases to 4.3 percent of GDP in 2018.

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

 

% CA/
GDP 2014

% CA/
GDP 2015

% CA/
GDP 2016

% CA/
GDP 2017

% CA/
GDP 2018

World

NA

NA

NA

NA

NA

G7

-0.7

-0.6

-0.4

-0.4

-0.7

Canada

-2.3

-3.4

-3.3

-2.9

-2.7

France

-1.1

-0.2

-1.1

-0.9

-0.5

DE

7.3

8.3

8.5

8.2

8.0

Italy

1.9

1.6

2.7

2.0

1.8

Japan

0.8

3.1

3.9

4.2

4.3

UK

-4.7

-4.3

-4.4

-3.3

-2.9

US

-2.3

-2.6

-2.6

-2.7

-3.3

Euro Area

2.5

3.0

3.4

3.0

3.0

DE

7.3

8.3

8.5

8.2

8.0

France

-1.1

-0.2

-0.5

-0.4

-0.3

Italy

1.9

1.6

2.7

2.0

1.8

POT

0.1

0.1

0.8

-0.3

-0.4

Ireland

1.7

10.2

4.7

4.7

4.7

Greece

-2.1

0.1

-0.6

-0.3

0.0

Spain

1.0

1.4

2.0

1.5

1.6

EMDE

0.6

-0.2

-0.3

-0.3

-0.3

Brazil

-4.3

-3.3

-1.3

-1.3

-1.7

Russia

2.8

5.1

1.7

3.3

3.5

India

-1.3

-1.1

-0.9

-1.5

-1.5

China

2.6

2.7

1.8

1.3

1.2

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

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

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

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

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

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

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

  • In emerging Asia, particularly China, greater flexibility in exchange rates is critical to allow necessary appreciations, as is strengthening domestic demand, lessening reliance on export-led growth strategies, and actions to strengthen financial sectors.
  • In oil-producing countries, accelerated investment in capacity, increased economic diversification, enhanced exchange rate flexibility in some cases.
  • Other current account surplus countries should encourage domestic consumption and investment, increase micro-economic flexibility and improve investment climates.

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

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

The database of the WEO (http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx) is used to construct Table I-7 with fiscal and current account imbalances projected for 2016 and 2018. The WEO finds the need to rebalance external and domestic demand (IMF 2011WEOSep xvii):

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

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

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

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

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

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

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

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

(“expenditure reduction”) in deficit economies.

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

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

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

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

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

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

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

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

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

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

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

reducing their net external liabilities.”

Table I-7, Fiscal Deficit, Current Account Deficit and Government Debt as % of GDP and 2016 Dollar GDP

 

GDP
$B

2016

FD
%GDP
2016

CAD
%GDP
2016

Debt
%GDP
2016

FD%GDP
2018

CAD%GDP
2018

Debt
%GDP
2018

US

18569

-2.3

-2.6

81.5

-2.2

-3.3

83.1

Japan

4939

-4.0

3.9

119.8

-3.3

4.3

120.1

UK

2629

-1.4

-4.4

80.7

-0.4

-2.9

80.2

Euro

11879

0.3

3.4

67.0

0.5

3.0

65.3

Ger

3467

1.9

8.5

45.0

1.4

8.0

40.6

France

2463

-1.5

-1.1

88.4

-1.2

-0.5

89.1

Italy

1851

1.4

2.7

113.3

2.1

1.8

113.0

Can

1529

-1.2

-3.3

27.6

-1.6

-2.7

25.1

China

11218

-3.0

1.8

46.2

-2.3

1.2

52.0

Brazil

1799

-2.5

-1.3

46.2

-1.1

-1.7

53.4

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

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

Source: IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

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

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

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

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

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

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

The prospects of survival of the euro zone are dire. Table I-8 is constructed with IMF World Economic Outlook database (http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx) for GDP in USD billions, primary net lending/borrowing as percent of GDP and general government debt as percent of GDP for selected regions and countries in 2017.

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

 

GDP 2017
USD Billions

Primary Net Lending Borrowing
% GDP 2017

General Government Net Debt
% GDP 2017

World

77,988

    

Euro Zone

11,729

0.3

66.3

Portugal

203

2.1

121.1

Ireland

294

1.6

67.8

Greece

193

1.8

180.7**

Spain

1,232

-0.9

80.4

Major Advanced Economies G7

36,007

-1.6

83.1

United States

19,417

-1.9

82.4

UK

2,497

-1.0

80.4

Germany

3,423

1.5

42.7

France

2,420

-1.6

89.1

Japan

4,841

-3.9

119.9

Canada

1,600

-1.7

26.4

Italy

1,807

1.1

113.8

China

11,795

-2.7

49.3***

*Net Lending/borrowing**Gross Debt

Source: IMF World Economic Outlook

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

The data in Table I-8 are used for some very simple calculations in Table I-9. The column “Net Debt USD Billions 2017” in Table I-9 is generated by applying the percentage in Table I-8 column “General Government Net Debt % GDP 2017” to the column “GDP 2017 USD Billions.” The total debt of France and Germany in 2017 is $3617.8 billion, as shown in row “B+C” in column “Net Debt USD Billions 2017.” The sum of the debt of Italy, Spain, Portugal, Greece and Ireland is $3840.8 billion, adding rows D+E+F+G+H in column “Net Debt USD billions 2017.” There is some simple “unpleasant bond arithmetic” in the two final columns of Table I-9. Suppose the entire debt burdens of the five countries with probability of default were to be guaranteed by France and Germany, which de facto would be required by continuing the euro zone. The sum of the total debt of these five countries and the debt of France and Germany is shown in column “Debt as % of Germany plus France GDP” to reach $7,458.6 billion, which would be equivalent to 127.7 percent of their combined GDP in 2017. Under this arrangement, the entire debt of selected members of the euro zone including debt of France and Germany would not have nil probability of default. The final column provides “Debt as % of Germany GDP” that would exceed 217.9 percent if including debt of France and 154.9 percent of German GDP if excluding French debt. The unpleasant bond arithmetic illustrates that there is a limit as to how far Germany and France can go in bailing out the countries with unsustainable sovereign debt without incurring severe pains of their own such as downgrades of their sovereign credit ratings. A central bank is not typically engaged in direct credit because of remembrance of inflation and abuse in the past. There is also a limit to operations of the European Central Bank in doubtful credit obligations. Wriston (1982) would prove to be wrong again that countries do not bankrupt but would have a consolation prize that similar to LBOs the sum of the individual values of euro zone members outside the current agreement exceeds the value of the whole euro zone. Internal rescues of French and German banks may be less costly than bailing out other euro zone countries so that they do not default on French and German banks. Analysis of fiscal stress is quite difficult without including another global recession in an economic cycle that is already mature by historical experience.

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

 

Net Debt USD Billions

2017

Debt as % of Germany Plus France GDP

Debt as % of Germany GDP

A Euro Area

7,776.3

    

B Germany

1,461.6

  

$7458.6 as % of $3423 =217.9%

$5302.4 as % of $3423 =154.9%

C France

2,156.2

    

B+C

3,617.8

GDP $5843

Total Debt

$7,458.6

Debt/GDP: 127.7%

  

D Italy

2,056.4

    

E Spain

990.5

    

F Portugal

245.8

    

G Greece

348.8

    

H Ireland

199.3

    

Subtotal D+E+F+G+H

3,840.8

    

Source: calculation with IMF data IMF World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

World trade projections of the IMF are in Table I-10. There is increasing growth of the volume of world trade of goods and services from 3.8 percent in 2017 to 4.1 percent in 2017, increasing to 4.3 percent in 2018. Growth improves to 4.2 percent on average from 2017 to 2021. World trade would be slower for advanced economies while emerging and developing economies (EMDE) experience faster growth. World economic slowdown would be more challenging with lower growth of world trade.

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

 

2017

2018

2019

Average ∆% 2017-2021

World Trade Volume (Goods and Services)

3.8

4.1

4.3

4.2

Exports Goods & Services

3.6

4.0

4.1

4.0

Imports Goods & Services

3.9

4.2

4.4

4.3

Average Oil Price USD/Barrel

42.84

55.23

55.06

Average ∆% 2009-2018

75.41

Average Annual ∆% Export Unit Value of Manufactures

-5.4

2.8

1.7

Average ∆% 2009-2018

0.0

Exports of Goods & Services

2016

2017

2018

Average ∆% 2009-2018

EMDE

2.5

3.6

4.3

3.6

G7

2.1

3.5

3.2

2.8

Imports Goods & Services

        

EMDE

1.9

4.5

4.3

3.9

G7

2.4

4.0

4.0

2.6

Terms of Trade of Goods & Services

        

EMDE

-1.2

1.3

-0.4

-0.5

G7

0.9

-0.5

0.1

0.3

Terms of Trade of Goods

        

EMDE

-1.4

1.4

-0.4

-0.5

G7

1.2

-0.2

0.3

0.3

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

Source: International Monetary Fund World Economic Outlook databank

http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx

I United States Housing Collapse. Data and other information continue to provide depressed conditions in the US housing market in a longer perspective, with recent improvement at the margin. Table IIB-1 shows sales of new houses in the US at seasonally adjusted annual equivalent rate (SAAR). House sales fell in 28 of 75 months from Feb 2011 to Mar 2017 with monthly declines of 5 in 2011, 4 in 2012, 4 in 2013, 6 in 2014, 3 in 2015 and 6 in 2016. In Jan-Apr 2012, house sales increased at the annual equivalent rate of 11.8 percent and at 22.3 percent in May-Sep 2012. There was significant strength in Sep-Dec 2011 with annual equivalent rate of 48.4 percent. Sales of new houses fell 7.0 percent in Oct 2012 with increase of 9.5 percent in Nov 2012. Sales of new houses rebounded 10.8 percent in Jan 2013 with annual equivalent rate of 51.5 percent from Oct 2012 to Jan 2013 because of the increase of 10.8 percent in Jan 2013. New house sales increased at annual equivalent 9.9 percent in Feb-Mar 2013. New house sales weakened, decreasing at 2.3 percent in annual equivalent from Apr to Dec 2013 with significant volatility illustrated by decline of 18.8 percent in Jul 2013 and increase of 11.3 percent in Oct 2013. New house sales fell 1.1 percent in Dec 2013. New house sales increased 1.4 percent in Jan 2014 and fell 5.4 percent in Feb 2014, decreasing 3.1 percent in Mar 2014. New house sales decreased 2.2 percent in Apr 2014 and increased 12.7 percent in May 2014. New house sales fell 8.0 percent in Jun 2014 and decreased 3.4 percent in Jul 2014. New house sales jumped 11.7 percent in Aug 2014 and increased 3.8 percent in Sep 2014. New House sales increased 1.7 percent in Oct 2014 and fell 5.9 percent in Nov 2014. House sales fell at the annual equivalent rate of 2.6 percent in Sep-Nov 2014. New house sales increased 10.3 percent in Dec 2014 and increased 6.5 percent in Jan 2015. Sales of new houses increased 4.8 percent in Feb 2015 and fell 10.7 percent in Mar 2015. House sales increased 2.0 percent in Apr 2015. The annual equivalent rate in Dec 2014-Apr 2015 was 31.6 percent. New house sales increased 1.4 percent in May 2015 and fell 6.9 percent in Jun 2015, increasing 5.5 percent in Jul 2015. New house sales fell at annual equivalent 1.6 percent in May-Jul 2015. New house sales increased 1.4 percent in Aug 2015 and fell 9.5 percent in Sep 2015. New house sales decreased at annual equivalent 40.3 percent in Aug-Sep 2015. New house sales increased 4.6 percent in Oct 2015 and increased 6.3 percent in Nov 2015, increasing 5.9 percent in Dec 2015. New house sales increased at the annual equivalent rate of 92.2 percent in Oct-Dec 2015. New house sales decreased 2.2 percent in Jan 2016 at the annual equivalent rate of minus 23.4 percent. New house sales decreased 0.2 percent in Feb 2016 and increased 2.3 percent in Mar 2016. New house sales jumped at 6.1 percent in Apr 2016. New house sales increased at the annual equivalent rate of 37.7 percent in Feb-Apr 2016. New house sales decreased 0.7 percent in May 2016 and decreased 1.4 percent in Jun 2016. New house sales jumped 11.5 percent in Aug 2016. New house sales increased at the annual equivalent rate of 42.0 percent in May-Jul 2016. New house sales fell 10.1 percent in Aug 2016 and increased 1.6 percent in Sep 2016, changing 0.0 percent in Oct 2016. New house sales fell at the annual equivalent rate of minus 30.4 percent in Aug-Oct 2016. New house sales increased at 0.9 percent in Nov 2016 and fell at 3.8 percent in Dec 2016. New house sales fell at 16.4 percent annual equivalent in Nov-Dec 2016. New house sales increased at 6.2 percent in Jan 2017 and increased at 0.3 percent in Feb 2017. New house sales increased at 5.8 percent in Mar 2017. New house sales increased at 61.3 percent annual equivalent in Jan-Mar 2017. There are wide monthly oscillations. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), analyze how builders have provided financial assistance to home buyers, including those short of cash and with weaker credit background, explaining the rise in new home sales and the highest gap between prices of new and existing houses. The 30-year conventional mortgage rate increased from 3.40 on Apr 25, 2013 to 4.58 percent on Aug 22, 2013 (http://www.federalreserve.gov/releases/h15/data.htm), which could also be a factor in recent weakness with improvement after the rate fell to 4.26 in Nov 2013. The conventional mortgage rate rose to 4.48 percent on Dec 26, 2013 and fell to 4.32 percent on Jan 30, 2014. The conventional mortgage rate increased to 4.37 percent on Feb 26, 2014 and 4.40 percent on Mar 27, 2014. The conventional mortgage rate fell to 4.14 percent on Apr 22, 2014, stabilizing at 4.14 on Jun 26, 2014. The conventional mortgage rate stood at 3.93 percent on Aug 20, 2015 and at 3.91 percent on Sep 17, 2015. The conventional mortgage rate was at 3.79 percent on Oct 22, 2015. The conventional mortgage rate was 3.97 percent on Nov 20, 2015. The conventional mortgage rate was 3.97 percent on Dec 18, 2015, and 3.92 percent on Jan 14, 2016. The conventional mortgage rate was 3.65 percent on Feb 19, 2016. The commercial mortgage rate was 3.73 percent on Mar 17, 2016 and 3.59 percent on Apr 21, 2016. The conventional mortgage rate was 3.58 on May 19, 2016. The conventional mortgage rate was 3.54 percent on Jun 19, 2016 and 3.45 percent on Jul 21, 2016. The conventional mortgage rate was 3.43 percent on Aug 18, 2016 and 3.48 percent on Sep 22, 2016. The conventional mortgage rate was 3.94 on Nov 17, 2016 and 4.30 percent on Dec 22. The conventional mortgage rate was 4.19 percent on Jan 26, 2017 and 4.15 percent on Feb 17, 2017. The conventional mortgage rate was 4.1 percent on Mar 16, 2017. The conventional mortgage rate was 3.97 percent on Apr 20, 2017. The conventional mortgage rate measured in a survey by Freddie Mac (http://www.freddiemac.com/pmms/ http://www.freddiemac.com/pmms/abtpmms.htm) is the “interest rate a lender would charge to lend mortgage money to a qualified borrower.”

Table IIB-1, US, Sales of New Houses at Seasonally-Adjusted (SA) Annual Equivalent Rate, Thousands and % 

 

SA Annual Rate
Thousands

∆%

Mar 2017

621

5.8

Feb

587

0.3

Jan

585

6.2

AE ∆% Jan-Feb

  

61.3

Dec 2016

551

-3.8

Nov

573

0.9

AE ∆% Nov-Dec

  

-16.4

Oct

568

0.0

Sep

568

1.6

Aug

559

-10.1

AE ∆% Aug-Oct

  

-30.4

Jul

622

11.5

Jun

558

-1.4

May

566

-0.7

AE ∆% May-Jul

  

42.0

Apr

570

6.1

Mar

537

2.3

Feb

525

-0.2

AE ∆% Feb-Apr

  

37.7

Jan

526

-2.2

AE ∆% Jan

  

-23.4

Dec 2015

538

5.9

Nov

508

6.3

Oct

478

4.6

AE ∆% Oct-Dec

  

92.2

Sep

457

-9.5

Aug

505

1.4

AE ∆% Aug-Sep

  

-40.3

Jul

498

5.5

Jun

472

-6.9

May

507

1.4

AE ∆% May-Jul

  

-1.6

Apr

500

2.0

Mar

490

-10.7

Feb

549

4.8

Jan

524

6.5

Dec 2014

492

10.3

AE ∆% Dec-Apr

  

31.6

Nov

446

-5.9

Oct

474

1.7

Sep

466

3.8

AE ∆% Sep-Nov

  

-2.6

Aug

449

11.7

Jul

402

-3.4

Jun

416

-8.0

May

452

12.7

Apr

401

-2.2

Mar

410

-3.1

Feb

423

-5.4

Jan

447

1.4

AE ∆% Jan-Aug

  

2.6

Dec 2013

441

-1.1

Nov

446

0.5

Oct

444

11.3

Sep

399

5.0

Aug

380

1.1

Jul

376

-18.8

Jun

463

7.7

May

430

-4.7

Apr

451

0.4

AE ∆% Apr-Dec

  

-2.3

Mar

449

2.3

Feb

439

-0.7

AE ∆% Feb-Mar

  

9.9

Jan

442

10.8

Dec 2012

399

1.8

Nov

392

9.5

Oct

358

-7.0

AE ∆% Oct-Jan

  

51.5

Sep

385

2.7

Aug

375

1.6

Jul

369

2.5

Jun

360

-2.7

May

370

4.5

AE ∆% May-Sep

  

22.3

Apr

354

0.0

Mar

354

-3.3

Feb

366

9.3

Jan

335

-1.8

AE ∆% Jan-Apr

  

11.8

Dec 2011

341

4.0

Nov

328

3.8

Oct

316

3.9

Sep

304

1.7

AE ∆% Sep-Dec

  

48.4

Aug

299

1.0

Jul

296

-1.7

Jun

301

-1.3

May

305

-1.6

AE ∆% May-Aug

  

-10.3

Apr

310

3.3

Mar

300

11.1

Feb

270

-12.1

Jan

307

-5.8

AE ∆% Jan-Apr

  

-14.2

Dec 2010

326

13.6

AE: Annual Equivalent

Source: US Census Bureau

http://www.census.gov/construction/nrs/

There is additional information of the report of new house sales in Table IIB-2. The stock of unsold houses fell from rates of 6 to 8 percent of sales in 2011 to 4 to 5 percent in 2013 and 5.2 percent in Mar 2017. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), find that inventories of houses have declined as investors acquire distressed houses of higher quality. Median and average house prices oscillate. In Mar 2017, median prices of new houses sold not seasonally adjusted (NSA) increased 7.5 percent after decreasing 4.8 percent in

Feb 2017. Average prices increased 3.9 percent in Mar 2017 and increased 5.2 percent in Feb 2017. Between Dec 2010 and Mar 2017, median prices increased 30.6 percent, partly concentrated in increases of 6.9 percent in Feb 2016, 6.1 percent in Nov 2015, 2.5 percent in Sep 2015, 14.5 percent in Oct 2014, 4.0 percent in Aug 2014, 4.0 percent in May 2014 and 5.2 percent in Mar 2014. Average prices increased 33.1 percent between Dec 2010 and Mar 2017, with increases of 5.2 percent in Mar 2016, 5.4 percent in Sep 2015, 3.8 percent in Jul 2015 and 20.3 percent in Oct 2014. Between Dec 2010 and Dec 2012, median prices increased 7.1 percent and average prices increased 2.6 percent. Price increases concentrated in 2012 with increase of median prices of 18.2 percent from Dec 2011 to Dec 2012 and of average prices of 13.8 percent. Median prices increased 16.9 percent from Dec 2012 to Dec 2014, with increase of 14.5 percent in Oct 2014, while average prices increased 24.8 percent, with increase of 20.3 percent in Oct 2014. Median prices decreased 1.0 percent from Dec 2014 to Dec 2015 while average prices fell 4.1 percent. Median prices increased 11.3 percent from Dec 2015 to Dec 2016 while average prices increased 8.9 percent. Median prices increased 1.2 percent from Mar 2016 to Mar 2017 while average prices increased 5.6 percent. Robbie Whelan, writing on “New homes hit record as builders cap supply,” on May 24, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323475304578500973445311276.html?mod=WSJ_economy_LeftTopHighlights), finds that homebuilders are continuing to restrict the number of new homes for sale. Restriction of available new homes for sale increases prices paid by buyers.

Table IIB-2, US, New House Stocks and Median and Average New Homes Sales Price

 

Unsold*
Stocks in Equiv.
Months
of Sales
SA %

Median
New House Sales Price USD
NSA

Month
∆%

Average New House Sales Price USD
NSA

Month
∆%

Mar 2017

5.2

315,100

7.5

388,200

3.9

Feb

5.4

293,100

-4.8

373,600

5.2

Jan

5.4

308,000

-7.4

355,100

-9.0

Dec 2016

5.6

332,700

4.5

390,100

7.0

Nov

5.2

318,300

5.4

364,600

7.0

Oct

5.2

302,000

-6.7

340,600

-8.6

Sep

5.1

323,700

7.0

372,800

2.2

Aug

5.2

302,400

2.5

364,700

2.7

Jul

4.6

295,000

-8.3

355,000

-2.6

Jun

5.2

321,600

8.6

364,300

4.1

May

5.1

296,000

-7.9

350,000

-7.9

Apr

5.1

321,300

3.2

380,000

3.3

Mar

5.5

311,400

0.0

367,700

5.2

Feb

5.5

311,300

6.9

349,400

-4.4

Jan

5.5

291,100

-2.6

365,600

2.1

Dec 2015

5.2

299,000

-5.7

358,100

-5.0

Nov

5.4

317,000

6.1

376,800

2.7

Oct

5.6

298,700

-2.9

366,900

-0.2

Sep

5.8

307,600

2.5

367,800

5.4

Aug

5.2

300,200

1.4

348,800

2.0

Jul

5.2

296,000

2.4

341,900

3.8

Jun

5.5

289,200

0.6

329,300

-3.4

May

5.0

287,400

-1.8

340,800

1.8

Apr

5.0

292,700

-0.2

334,700

-5.1

Mar

5.0

293,400

-0.2

352,700

-0.9

Feb

4.5

293,900

0.7

355,900

0.0

Jan

4.8

292,000

-3.3

356,000

-4.7

Dec 2014

5.1

302,000

-0.2

373,500

4.1

Nov

5.7

302,700

1.1

358,800

-6.6

Oct

5.3

299,400

14.5

384,000

20.3

Sep

5.3

261,500

-10.4

319,100

-10.4

Aug

5.5

291,700

4.0

356,200

3.2

Jul

6.1

280,400

-2.3

345,200

2.1

Jun

5.7

287,000

0.5

338,100

4.5

May

5.1

285,600

4.0

323,500

-0.5

Apr

5.7

274,500

-2.8

325,100

-1.9

Mar

5.6

282,300

5.2

331,500

1.7

Feb

5.3

268,400

-0.5

325,900

-3.4

Jan

5.1

269,800

-2.1

337,300

5.0

Dec 2013

5.1

275,500

-0.6

321,200

-4.3

Nov

5.0

277,100

4.8

335,600

0.0

Oct

4.9

264,300

-2.0

335,700

4.4

Sep

5.5

269,800

5.7

321,400

3.4

Aug

5.5

255,300

-2.6

310,800

-5.8

Jul

5.4

262,200

0.9

329,900

7.8

Jun

4.1

259,800

-1.5

306,100

-2.5

May

4.5

263,700

-5.6

314,000

-6.8

Apr

4.3

279,300

8.5

337,000

12.3

Mar

4.1

257,500

-2.9

300,200

-3.9

Feb

4.2

265,100

5.4

312,500

1.8

Jan

4.0

251,500

-2.6

306,900

2.6

Dec 2012

4.5

258,300

5.4

299,200

2.9

Nov

4.6

245,000

-0.9

290,700

1.9

Oct

4.9

247,200

-2.9

285,400

-4.1

Sep

4.5

254,600

0.6

297,700

-2.6

Aug

4.6

253,200

6.7

305,500

8.2

Jul

4.6

237,400

2.1

282,300

3.9

Jun

4.8

232,600

-2.8

271,800

-3.2

May

4.7

239,200

1.2

280,900

-2.4

Apr

4.9

236,400

-1.4

287,900

1.5

Mar

4.9

239,800

0.0

283,600

3.5

Feb

4.8

239,900

8.2

274,000

3.1

Jan

5.3

221,700

1.4

265,700

1.1

Dec 2011

5.3

218,600

2.0

262,900

5.2

Nov

5.7

214,300

-4.7

250,000

-3.2

Oct

6.0

224,800

3.6

258,300

1.1

Sep

6.3

217,000

-1.2

255,400

-1.5

Aug

6.5

219,600

-4.5

259,300

-4.1

Jul

6.7

229,900

-4.3

270,300

-1.0

Jun

6.6

240,200

8.2

273,100

4.0

May

6.6

222,000

-1.2

262,700

-2.3

Apr

6.7

224,700

1.9

268,900

3.1

Mar

7.2

220,500

0.2

260,800

-0.8

Feb

8.1

220,100

-8.3

262,800

-4.7

Jan

7.3

240,100

-0.5

275,700

-5.5

Dec 2010

7.0

241,200

9.8

291,700

3.5

*Percent of new houses for sale relative to houses sold

Source: US Census Bureau

http://www.census.gov/construction/nrs/

The depressed level of residential construction and new house sales in the US is evident in Table IIB-3 providing new house sales not seasonally adjusted in Jan-Feb of various years. New house sales increased 11.2 percent from Jan-Mar 2016 to Jan-Mar 2017. Sales of new houses are higher in Jan-Mar 2017 relative to Jan-Mar 2015 with increase of 14.6 percent. Sales of new houses are higher in Jan-Mar 2017 relative to Jan-Mar 2014 with increase of 39.3 percent. Sales of new houses in Jan-Mar 2017 are substantially lower than in many years between 1971 and 2016 except for the years from 2008 to 2017. There are only six other increases of 36.7 percent relative to Jan-Mar 2013, 71.3 percent relative to Jan-Mar 2012, 109.9 percent relative to Jan-Mar 2011, 71.3 percent relative to Jan-Mar 2010 and 77.4 percent relative to Jan-Mar 2009. New house sales in Jan-Mar 2017 are 5.7 percent higher than in Jan-Mar 2008. Sales of new houses in Jan-Mar 2017 are lower by 30.4 percent relative to Jan-Mar 2007, 47.7 percent relative to 2006, 54.6 percent relative to 2005 and 52.5 percent relative to 2004. The housing boom peaked in 2005 and 2006 when increases in fed funds rates to 5.25 percent in Jun 2006 from 1.0 percent in Jun 2004 affected subprime mortgages that were programmed for refinancing in two or three years on the expectation that price increases forever would raise home equity. Higher home equity would permit refinancing under feasible mortgages incorporating full payment of principal and interest (Gorton 2009EFM; see other references in http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Sales of new houses in Jan 2017 relative to the same period in 2003 fell 41.8 percent and 37.9 percent relative to the same period in 2002. Similar percentage declines are also for 2017 relative to years from 2000 to 2004. Sales of new houses in Jan-Mar 2017 fell 3.2 per cent relative to the same period in 1995. The population of the US was 179.3 million in 1960 and 281.4 million in 2000 (Hobbs and Stoops 2002, 16). Detailed historical census reports are available from the US Census Bureau at (http://www.census.gov/population/www/censusdata/hiscendata.html). The estimate of the US population is 418.8 million in 2015. The US population increased by 133.6 percent from 1960 to 2015. The final row of Table IIB-3 reveals catastrophic data: sales of new houses in Jan-Mar 2017 of 149 thousand units are lower by 4.5 percent relative to 156 thousand units of houses sold in Jan-Mar 1971, which is the ninth year when data become available in 1963. The civilian noninstitutional population increased from 122.416 million in 1963 to 253.538 million in 2016, or 107.1 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

Table IIB-3, US, Sales of New Houses Not Seasonally Adjusted, Thousands and %

 

Not Seasonally Adjusted Thousands

Jan-Mar 2017

149

Jan-Mar 2016

134

Jan-Mar 2017/Jan-Mar 2016

11.2

Jan-Mar 2015

130

∆% Jan-Mar 2017/Jan-Mar 2015

14.6

Jan-Mar 2014

107

∆% Jan-Mar 2017/Jan-Mar 2014

39.3

Jan-Mar 2013

109

∆% Jan-Mar 2017/Jan-Mar 2013

36.7

Jan-Mar 2012

87

∆% Jan-Mar 2017/Jan-Mar 2012

71.3

Jan-Mar 2011

71

∆% Jan-Mar 2017/Jan-Mar 2011

109.9

Jan-Mar 2010

87

∆% Jan-Mar 2017/ 
Jan-Mar 2010

71.3

Jan-Mar 2009

84

∆% Jan-Mar 2017/ 
Jan-Mar 2009

77.4

Jan-Mar 2008

141

∆% Jan-Mar 2017/ 
Jan-Mar 2008

5.7

Jan-Mar 2007

214

∆% Jan-Mar 2017/
Jan-Mar 2007

-30.4

Jan-Mar 2006

285

∆% Jan-Mar 2017/Jan-Mar 2006

-47.7

Jan-Mar 2005

328

∆% Jan-Mar 2017/Jan-Mar 2005

-54.6

Jan-Mar 2004

314

∆% Jan-Mar 2017/Jan-Mar 2004

-52.5

Jan-Mar 2003

256

∆% Jan-Mar 2017/
Jan-Mar 2003

-41.8

Jan-Mar 2002

240

∆% Jan-Mar 2017/
Jan-Mar 2002

-37.9

Jan-Mar 2001

251

∆% Jan-Mar 2017/
Jan-Mar 2001

-40.6

Jan-Mar 2000

233

∆% Jan-Mar 2017/
Jan-Mar 2000

-36.1

Jan-Mar 1995

154

∆% Jan-Mar 2017/
Jan-Mar 1995

-3.2

Jan-Mar 1971

156

∆% Jan-Mar 2017/
Jan-Mar 1971

-4.5

*Computed using unrounded data

Source: US Census Bureau

http://www.census.gov/construction/nrs/

The revised level of 306 thousand new houses sold in 2011 is the lowest since 560 thousand in 1963 in the 53 years of available data while the level of 368 thousand in 2012 is only higher than 323 thousand in 2010. The level of sales of new houses of 437 thousand in 2014 is the lowest from 1963 to 2009 with exception of 412 thousand in 1982 and 436 thousand in 1981. The population of the US increased 129.4 million from 179.3 million in 1960 to 308.7 million in 2010, or 72.2 percent. The estimate of the US population is 418.8 million in 2015. The US population increased 133.6 percent from 1960 to 2015. The civilian noninstitutional population increased from 122.416 million in 1963 to 253.538 million in 2016, or 107.1 percent (http://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

The civilian noninstitutional population is the universe of the labor force. In fact, there is no year from 1963 to 2013 in Table IIA-4 with sales of new houses below 400 thousand with the exception of the immediately preceding years of 2009, 2010, 2011 and 2012.

Table IIB-4, US, New Houses Sold, NSA Thousands

Period

Sold during Period

1963

560

1964

565

1965

575

1966

461

1967

487

1968

490

1969

448

1970

485

1971

656

1972

718

1973

634

1974

519

1975

549

1976

646

1977

819

1978

817

1979

709

1980

545

1981

436

1982

412

1983

623

1984

639

1985

688

1986

750

1987

671

1988

676

1989

650

1990

534

1991

509

1992

610

1993

666

1994

670

1995

667

1996

757

1997

804

1998

886

1999

880

2000

877

2001

908

2002

973

2003

1,086

2004

1,203

2005

1,283

2006

1,051

2007

776

2008

485

2009

375

2010

323

2011

306

2012

368

2013

429

2014

437

2015

501

2016

561

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-1 of the US Bureau of the Census shows the sharp decline of sales of new houses in the US. Sales rose temporarily until about mid 2010 but then declined to a lower plateau followed by increase, stability and new oscillating increase.

Chart IIB-1, US, New One-Family Houses Sold in the US, SAAR (Seasonally Adjusted Annual Rate) 

Source: US Census Bureau

https://www.census.gov/construction/nrs/img/c25_curr.gif

Table IIB-5. The percentage change of new house sales from 1963 to 2016 is 0.0 percent. Between 1991 and 2001, sales of new houses rose 78.4 percent at the average yearly rate of 6.0 percent. Between 1995 and 2005 sales of new houses increased 92.4 percent at the yearly rate of 6.8 percent. There are similar rates in all years from 2000 to 2005. The boom in housing construction and sales began in the 1980s and 1990s. The collapse of real estate culminated several decades of housing subsidies and policies to lower mortgage rates and borrowing terms (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 42-8). Sales of new houses sold in 2016 fell 16.0 percent relative to the same period in 1995 and 56.4 percent relative to 2005.

Table IIB-5, US, Percentage Change and Average Yearly Rate of Growth of Sales of New One-Family Houses

 

∆%

Average Yearly % Rate

1963-2016

0.2

NA

1991-2001

78.4

6.0

1995-2005

92.4

6.8

2000-2005

46.3

7.9

1995-2016

-15.9

NA

2000-2016

-36.0

NA

2005-2016

-56.3

NA

NA: Not Applicable

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-2 of the US Bureau of the Census provides the entire monthly sample of new houses sold in the US between Jan 1963 and Mar 2017 without seasonal adjustment. The series is almost stationary until the 1990s. There is sharp upward trend from the early 1990s to 2005-2006 after which new single-family houses sold collapse to levels below those in the beginning of the series.

Chart IIB-2, US, New Single-family Houses Sold, NSA, 1963-2017

Source: US Census Bureau

http://www.census.gov/construction/nrs/

The available historical annual data of median and average prices of new houses sold in the US between 1963 and 2016 is in Table IIB-6. On a yearly basis, median and average prices reached a peak in 2007 and then fell substantially. There is recovery in 2012-2016.

Table IIB-6, US, Median and Average Prices of New Houses Sold, Annual Data

Period

Median

Average

1963

$18,000

$19,300

1964

$18,900

$20,500

1965

$20,000

$21,500

1966

$21,400

$23,300

1967

$22,700

$24,600

1968

$24,700

$26,600

1969

$25,600

$27,900

1970

$23,400

$26,600

1971

$25,200

$28,300

1972

$27,600

$30,500

1973

$32,500

$35,500

1974

$35,900

$38,900

1975

$39,300

$42,600

1976

$44,200

$48,000

1977

$48,800

$54,200

1978

$55,700

$62,500

1979

$62,900

$71,800

1980

$64,600

$76,400

1981

$68,900

$83,000

1982

$69,300

$83,900

1983

$75,300

$89,800

1984

$79,900

$97,600

1985

$84,300

$100,800

1986

$92,000

$111,900

1987

$104,500

$127,200

1988

$112,500

$138,300

1989

$120,000

$148,800

1990

$122,900

$149,800

1991

$120,000

$147,200

1992

$121,500

$144,100

1993

$126,500

$147,700

1994

$130,000

$154,500

1995

$133,900

$158,700

1996

$140,000

$166,400

1997

$146,000

$176,200

1998

$152,500

$181,900

1999

$161,000

$195,600

2000

$169,000

$207,000

2001

$175,200

$213,200

2002

$187,600

$228,700

2003

$195,000

$246,300

2004

$221,000

$274,500

2005

$240,900

$297,000

2006

$246,500

$305,900

2007

$247,900

$313,600

2008

$232,100

$292,600

2009

$216,700

$270,900

2010

$221,800

$272,900

2011

$227,200

$267,900

2012

$245,200

$292,200

2013

$268,900

$324,500

2014

$282,800

$345,800

2015

$296,400

$360,600

2016

$316,200

$372,500

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Table IIB-7. Prices rose sharply between 2000 and 2005. In fact, prices in 2016 are higher than in 2000. Between 2006 and 2016, median prices of new houses sold increased 31.3 percent and average prices increased 25.4 percent. Between 2015 and 2016, median prices increased 6.7 percent and average prices increased 3.3 percent.

Table IIB-7, US, Percentage Change of New Houses Median and Average Prices, NSA, ∆%

 

Median New 
Home Sales Prices ∆%

Average New Home Sales Prices ∆%

∆% 2000 to 2003

15.4

19.0

∆% 2000 to 2005

42.5

43.5

∆% 2000 to 2016

87.1

80.0

∆% 2005 to 2016

31.3

25.4

∆% 2000 to 2006

45.9

47.8

∆% 2006 to 2016

28.3

21.8

∆% 2009 to 2016

45.9

37.5

∆% 2010 to 2016

42.6

36.5

∆% 2011 to 2016

39.2

39.0

∆% 2012 to 2016

29.0

27.5

∆% 2013 to 2016

17.6

14.8

∆% 2014 to 2016

11.8

7.7

∆% 2015 to 2016

6.7

3.3

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-3 of the US Census Bureau provides the entire series of new single-family sales median prices from Jan 1963 to Mar 2017. There is long-term sharp upward trend with few declines until the current collapse. Median prices increased sharply during the Great Inflation of the 1960s and 1970s and paused during the savings and loans crisis of the late 1980s and the recession of 1991. Housing subsidies throughout the 1990s caused sharp upward trend of median new house prices that accelerated after the fed funds rate of 1 percent from 2003 to 2004. There was sharp reduction of prices after 2006 with recovery recently above earlier prices.

Chart IIB-3, US, Median Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1963-2017

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-4 of the US Census Bureau provides average prices of new houses sold from the mid-1970s to Mar 2017. There is similar behavior as with median prices of new houses sold in Chart IIB-3. The only stress occurred in price pauses during the savings and loans crisis of the late 1980s and the collapse after 2006 with recent recovery.

Chart IIB-4, US, Average Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1975-2017

Source: US Census Bureau

http://www.census.gov/construction/nrs/

Chart IIB-5 of the Board of Governors of the Federal Reserve System provides the rate for the 30-year conventional mortgage, the yield of the 30-year Treasury bond and the rate of the overnight federal funds rate, monthly, from 1954 to 2016. All rates decline throughout the period from the Great Inflation of the 1970s through the following Great Moderation and until currently. In Apr 1971, the fed funds rate was 4.15 percent and the conventional mortgage rate 7.31 percent. In November 2012, the fed funds rate was 0.16 percent, the yield of the 30-year Treasury 2.80 percent and the conventional mortgage rate 3.35. The final segment shows an increase in the yield of the 30-year Treasury to 3.61 percent in July 2013 with the fed funds rate at 0.09 percent and the conventional mortgage at 4.37 percent. The final data point shows marginal decrease of the conventional mortgage rate to 3.60 percent in May 2016 with the yield of the 30-year Treasury bond at 2.63 percent and overnight rate on fed funds at 0.37 percent. The recent increase in interest rates if sustained could affect the US real estate market. Shayndi Raice and Nick Timiraos, writing on “Banks cut as mortgage boom ends,” on Jan 9, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303754404579310940019239208), analyze the drop in mortgage applications to a 13-year low, as measured by the Mortgage Bankers Association. Nick Timiraos, writing on “Demand for home loans plunges,” on Apr 24, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304788404579522051733228402?mg=reno64-wsj), analyzes data in Inside Mortgage Finance that mortgage lending of $235 billion in IQ2014 is 58 percent lower than a year earlier and 23 percent below IVQ2013. Mortgage lending collapsed to the lowest level in 14 years. In testimony before the Committee on the Budget of the US Senate on May 8, 2004, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm): “One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.”

Chart IIB-5, US, Thirty-year Conventional Mortgage, Thirty-year Treasury Bond and Overnight Federal Funds Rate, Monthly, 1954-2016

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

Chart IIB-5A of the Board of Governors of the Federal Reserve System provides the yield of the 30-year Treasury bond and the rate of the overnight federal funds rate, monthly, from 1954 to 2017. The Board of Governors of the Federal Reserve System discontinued the conventional mortgage rate in its data bank. The final data point is 0.79 percent for the fed funds rate in Mar 2017 and 3.08 percent for the thirty-year Treasury bond. The conventional mortgage rate stood at 4.20 percent in Mar 2017.

Chart IIB-5A, US, Thirty-year Treasury Bond and Overnight Federal Funds Rate, Monthly, 2001-2017

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

Table IIB-8, US, Fed Funds Rate, Thirty Year Treasury Bond and Conventional Mortgage Rate, Monthly, Percent per Year, Dec 2012 to Feb 2017

 

Fed Funds Rate

Yield of Thirty Year Constant Maturity

Conventional Mortgage Rate

2012-12

0.16

2.88

3.35

2013-01

0.14

3.08

3.41

2013-02

0.15

3.17

3.53

2013-03

0.14

3.16

3.57

2013-04

0.15

2.93

3.45

2013-05

0.11

3.11

3.54

2013-06

0.09

3.40

4.07

2013-07

0.09

3.61

4.37

2013-08

0.08

3.76

4.46

2013-09

0.08

3.79

4.49

2013-10

0.09

3.68

4.19

2013-11

0.08

3.80

4.26

2013-12

0.09

3.89

4.46

2014-01

0.07

3.77

4.43

2014-02

0.07

3.66

4.30

2014-03

0.08

3.62

4.34

2014-04

0.09

3.52

4.34

2014-05

0.09

3.39

4.19

2014-06

0.10

3.42

4.16

2014-07

0.09

3.33

4.13

2014-08

0.09

3.2

4.12

2014-09

0.09

3.26

4.16

2014-10

0.09

3.04

4.04

2014-11

0.09

3.04

4.00

2014-12

0.12

2.83

3.86

2015-01

0.11

2.46

3.67

2015-02

0.11

2.57

3.71

2015-03

0.11

2.63

3.77

2015-04

0.12

2.59

3.67

2015-05

0.12

2.96

3.84

2015-06

0.13

3.11

3.98

2015-07

0.13

3.07

4.05

2015-08

0.14

2.86

3.91

2015-09

0.14

2.95

3.89

2015-10

0.12

2.89

3.80

2015-11

0.12

3.03

3.94

2015-12

0.24

2.97

3.96

2016-01

0.34

2.86

3.87

2016-02

0.38

2.62

3.66

2016-03

0.36

2.68

3.69

2016-04

0.37

2.62

3.61

2016-05

0.37

2.63

3.60

2016-06

0.38

2.45

3.57

2016-07

0.39

2.23

3.44

2016-08

0.40

2.26

3.44

2016-09

0.40

2.35

3.46

2016-10

0.40

2.50

3.47

2016-11

0.41

2.86

3.77

2016-12

0.54

3.11

4.20

2017-01

0.65

3.02

4.15

2017-02

0.66

3.03

4.17

2017-03

0.79

3.08

4.20

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

http://www.freddiemac.com/pmms/pmms30.htm

IIB2 United States House Prices. The Federal Housing Finance Agency (FHFA), which regulates Fannie Mae and Freddie Mac, provides the FHFA House Price Index (HPI) that “is calculated using home sales price information from Fannie Mae and Freddie Mac-acquired mortgages” (http://fhfa.gov/webfiles/24216/q22012hpi.pdf 1). The Federal Housing Finance Agency (FHFA), which regulates Fannie Mae and Freddie Mac, provides the FHFA House Price Index (HPI) that “is calculated using home sales price information from Fannie Mae and Freddie Mac-acquired mortgages” (http://fhfa.gov/webfiles/24216/q22012hpi.pdf 1). Table IIA2-1 provides the FHFA HPI for purchases only, which shows behavior similar to that of the Case-Shiller index but with lower magnitudes. House prices catapulted from 2000 to 2003, 2005 and 2006. From IVQ2000 to IVQ2006, the index for the US as a whole rose 55.0 percent, with 62.1 percent for New England, 72.0 percent for Middle Atlantic, 71.2 percent for South Atlantic but only by 33.1 percent for East South Central. Prices fell relative to 2014 for the US and all regions from 2006 with exception of increase of 2.6 percent for East South Central. Prices for the US increased 4.9 percent in IVQ2014 relative to IVQ2013 and 12.9 percent from IVQ2012 to IVQ2014. From IVQ2000 to IVQ2014, prices rose for the US and the four regions in Table IIA2-1.

Table IIA2-1, US, FHFA House Price Index Purchases Only NSA ∆%

 

United States

New England

Middle Atlantic

South Atlantic

East South Central

IVQ2000
to
IVQ2003

24.0

40.6

35.8

25.9

11.0

IVQ2000
to
IVQ2005

50.5

65.0

67.6

62.9

25.4

IVQ2000 to
IVQ2006

55.0

62.1

72.0

71.2

33.1

IVQ2005 to
IVQ2014

-1.5

-8.7

-2.3

-7.4

8.9

IVQ2006
to
IVQ2014

-4.4

-7.1

-4.8

-11.9

2.6

IVQ2007 to
IVQ2014

-1.9

-5.1

-5.0

-8.6

0.7

IVQ2011 to
IVQ2014

18.9

7.3

6.9

19.9

11.8

IVQ2012 to
IVQ2014

12.9

6.8

5.7

13.8

8.6

IVQ2013 to IVQ2014

4.9

2.5

2.2

5.1

4.2

IVQ2000 to
IVQ2014

48.3

144.27

50.6

138.40

63.7

127.30

50.9

140.28

36.6

146.07

Source: Federal Housing Finance Agency

http://www.fhfa.gov/KeyTopics/Pages/House-Price-Index.aspx

Data of the FHFA HPI for the remaining US regions are in Table IIA2-2. Behavior is not very different from that in Table IIA2-1 with the exception of East North Central. House prices in the Pacific region doubled between 2000 and 2006. Although prices of houses declined sharply from 2005 and 2006 to 2014 with exception of West South Central and West North Central, there was still appreciation relative to 2000.

Table IIA2-2, US, FHFA House Price Index Purchases Only NSA ∆%

 

West South Central

West North Central

East North Central

Mountain

Pacific

IVQ2000
to
IVQ2003

11.1

18.3

14.7

18.9

44.6

IVQ2000
to
IVQ2005

23.9

31.0

23.8

58.0

107.7

IVQ2000 to IVQ2006

31.6

33.7

23.7

68.6

108.7

IVQ2005 to
IVQ2014

26.6

4.7

-5.4

-2.6

-14.7

IVQ2006
to
IVQ2014

19.1

2.6

-5.4

-8.7

-15.1

IVQ2007 to
IVQ2014

15.2

3.2

-2.1

-5.6

-6.0

IVQ2011 to
IVQ2014

18.1

13.5

14.2

32.9

37.6

IVQ2012 to
IVQ2014

12.1

8.9

11.1

17.9

24.4

IVQ2013 to IVQ2014

5.9

4.0

4.6

5.5

7.3

IVQ2000 to IVQ2014

56.8

145.53

37.1

158.59

17.1

155.13

53.9

172.46

77.1

132.21

Source: Federal Housing Finance Agency

http://www.fhfa.gov/KeyTopics/Pages/House-Price-Index.aspx

Monthly and 12-month percentage changes of the FHFA House Price Index are in Table IIA2-3. Percentage monthly increases of the FHFA index were positive from Apr to Jul 2011 with exception of declines in May and Aug 2011 while 12-month percentage changes improved steadily from around minus 6.0 percent in Mar to May 2011 to minus 4.4 percent in Jun 2011. The FHFA house price index fell 0.6 percent in Oct 2011 and fell 3.1 percent in the 12 months ending in Oct 2011. There was significant recovery in Nov 2011 with increase in the house price index of 0.5 percent and reduction of the 12-month rate of decline to 2.3 percent. The house price index rose 0.4 percent in Dec 2011 and the 12-month percentage change improved to minus 1.3 percent. There was further improvement with revised change of minus 0.3 percent in Jan 2012 and decline of the 12-month percentage change to minus 1.3 percent. The index improved to positive change of 0.3 percent in Feb 2012 and increase of 0.1 percent in the 12 months ending in Feb 2012. There was strong improvement in Mar 2012 with gain in prices of 0.9 percent and 2.0 percent in 12 months. The house price index of FHFA increased 0.6 percent in Apr 2012 and 2.5 percent in 12 months and improvement continued with increase of 0.6 percent in May 2012 and 3.3 percent in the 12 months ending in May 2012. Improvement consolidated with increase of 0.4 percent in Jun 2012 and 3.4 percent in 12 months. In Jul 2012, the house price index increased 0.2 percent and 3.3 percent in 12 months. Strong increase of 0.6 percent in Aug 2012 pulled the 12-month change to 4.2 percent. There was another increase of 0.6 percent in Oct and 5.1 percent in 12 months followed by increase of 0.5 percent in Nov 2012 and 5.1 percent in 12 months. The FHFA house price index increased 0.7 percent in Jan 2013 and 6.4 percent in 12 months. Improvement continued with increase of 0.5 percent in Apr 2013 and 7.1 percent in 12 months. In May 2013, the house price indexed increased 0.8 percent and 7.3 percent in 12 months. The FHFA house price index increased 0.6 percent in Jun 2013 and 7.6 percent in 12 months. In Jul 2013, the FHFA house price index increased 0.6 percent and 8.1 percent in 12 months. Improvement continued with increase of 0.4 percent in Aug 2013 and 7.8 percent in 12 months. In Sep 2013, the house price index increased 0.5 percent and 7.8 percent in 12 months. The house price index increased 0.4 percent in Oct 2013 and 7.6 percent in 12 months. In Nov 2013, the house price index changed 0.0 percent and increased 7.1 percent in 12 months. The house price index rose 0.5 percent in Dec 2013 and 7.2 percent in 12 months. Improvement continued with increase of 0.6 percent in Jan 2014 and 7.1 percent in 12 months. In Feb 2014, the house price index increased 0.4 percent and 6.8 percent in 12 months. The house price index increased 0.4 percent in Mar 2014 and 6.1 percent in 12 months. In Apr 2014, the house price index increased 0.3 percent and increased 5.8 percent in 12 months. The house price index increased 0.2 percent in May 2014 and 5.1 percent in 12 months. In Jun 2014, the house price index increased 0.4 percent and 4.9 percent in 12 months. The house price index increased 0.4 percent in Jul 2014 and 4.7 percent in 12 months. In Sep 2014, the house price index increased 0.2 percent and increased 4.5 percent in 12 months. The house price index increased 0.5 percent in Oct 2014 and 4.5 percent in 12 months. In Nov 2014, the house price index increased 0.5 percent and 5.0 percent in 12 months. The house price index increased 0.8 percent in Dec 2014 and increased 5.3 percent in 12 months. In Feb 2015, the house price index increased 0.6 percent and increased 5.3 percent in 12 months. The house price index increased 0.4 percent in Mar 2015 and 5.4 percent in 12 months. In Apr 2015, the house price index increased 0.5 percent and 5.5 percent in 12 months. The house price index increased 0.5 percent in May 2015 and 5.8 percent in 12 months. House prices increased 0.4 percent in Jun 2015 and 5.7 percent in 12 months. The house price index increased 0.4 percent in Jul 2015 and increased 5.7 percent in 12 months. House prices increased 0.2 percent in Aug 2015 and increased 5.4 percent in 12 months. In Sep 2015, the house price index increased 0.8 percent and increased 6.0 percent in 12 months. The house price index increased 0.4 percent in Oct 2015 and increased 6.0 percent in 12 months. House prices increased 0.6 percent in Nov 2015 and increased 6.2 percent in 12 months. The house price index increased 0.5 percent in Dec 2015 and increased 5.8 percent in 12 months. House prices increased 0.5 percent in Jan 2016 and increased 6.2 percent in 12 months. The house price index increased 0.3 percent in Feb 2016 and increased 5.8 percent in 12 months. House prices increased 1.0 percent in Mar 2016 and increased 6.4 percent in 12 months. The house price index increased 0.3 percent in Apr 2016 and increased 6.1 percent in 12 months. House prices increased 0.4 percent in May 2016 and increased 5.9 percent in 12 months. The house price index increased 0.4 percent in Jun 2016 and increased 5.9 percent in 12 months. House prices increased 0.5 percent in Jul 2016 and increased 6.0 percent in 12 months. The house price index increased 0.7 percent in Aug 2016 and increased 6.5 percent in 12 months. House prices increased 0.7 percent in Sep 2016 and increased 6.5 percent in 12 months. The house price index increased 0.3 percent in Oct 2016 and increased 6.3 percent in 12 months. House prices increased 0.7 percent in Nov 2016 and increased 6.4 percent in 12 months. The house price index increased 0.4 percent in Dec 2016 and increased 6.3 percent in 12 months. House prices increased 0.2 percent in Jan 2017 and increased 5.9 percent in 12 months. In Feb 2017, the house price index increased 0.8 percent and increased 6.5 percent in 12 months.

Table IIA2-3, US, FHFA House Price Index Purchases Only SA. Month and NSA 12-Month ∆%

 

Month ∆% SA

12 Month ∆% NSA

Feb 2017

0.8

6.5

Jan

0.2

5.9

Dec 2016

0.4

6.3

Nov

0.7

6.4

Oct

0.3

6.3

Sep

0.7

6.5

Aug

0.7

6.5

Jul

0.5

6.0

Jun

0.4

5.9

May

0.4

5.9

Apr

0.3

6.1

Mar

1.0

6.4

Feb

0.3

5.8

Jan

0.5

6.2

Dec 2015

0.5

5.8

Nov

0.6

6.2

Oct

0.4

6.0

Sep

0.8

6.0

Aug

0.2

5.4

Jul

0.4

5.7

Jun

0.4

5.7

May

0.5

5.8

Apr

0.5

5.5

Mar

0.4

5.4

Feb

0.6

5.3

Jan

0.2

4.9

Dec 2014

0.8

5.3

Nov

0.5

5.0

Oct

0.5

4.6

Sep

0.2

4.5

Aug

0.5

4.8

Jul

0.4

4.7

Jun

0.4

4.9

May

0.2

5.1

Apr

0.3

5.8

Mar

0.4

6.1

Feb

0.4

6.8

Jan

0.6

7.1

Dec 2013

0.5

7.2

Nov

0.0

7.1

Oct

0.4

7.6

Sep

0.5

7.8

Aug

0.4

7.8

Jul

0.6

8.1

Jun

0.6

7.6

May

0.8

7.3

Apr

0.5

7.1

Mar

1.2

7.2

Feb

0.6

6.8

Jan

0.7

6.4

Dec 2012

0.5

5.3

Nov

0.5

5.1

Oct

0.6

5.1

Sep

0.5

3.9

Aug

0.6

4.2

Jul

0.2

3.3

Jun

0.4

3.4

May

0.6

3.3

Apr

0.6

2.5

Mar

0.9

2.0

Feb

0.3

0.1

Jan

-0.3

-1.3

Dec 2011

0.4

-1.3

Nov

0.5

-2.3

Oct

-0.6

-3.1

Sep

0.6

-2.4

Aug

-0.3

-3.8

Jul

0.3

-3.5

Jun

0.4

-4.4

May

-0.3

-5.9

Apr

0.2

-5.7

Mar

-0.9

-5.9

Feb

-1.1

-5.1

Jan

-0.4

-4.5

Dec 2010

  

-3.9

Dec 2009

  

-2.0

Dec 2008

  

-10.3

Dec 2007

  

-3.3

Dec 2006

  

2.4

Dec 2005

  

9.8

Dec 2004

  

10.2

Dec 2003

  

8.0

Dec 2002

  

7.8

Dec 2001

  

6.7

Dec 2000

  

7.2

Dec 1999

  

6.1

Dec 1998

  

5.9

Dec 1997

  

3.4

Dec 1996

  

2.8

Dec 1995

  

3.0

Dec 1994

  

2.5

Dec 1993

  

3.1

Dec 1992

  

2.4

Source: Federal Housing Finance Agency

http://www.fhfa.gov/DataTools

The bottom part of Table IIA2-3 provides 12-month percentage changes of the FHFA house price index since 1992 when data become available for 1991. Table IIA2-4 provides percentage changes and average rates of percent change per year for various periods. Between 1992 and 2016, the FHFA house price index increased 131.4 percent at the yearly average rate of 3.6 percent. In the period 1992-2000, the FHFA house price index increased 39.3 percent at the average yearly rate of 4.2 percent. The average yearly rate of price increase accelerated to 7.5 percent in the period 2000-2003, 8.5 percent in 2000-2005 and 7.5 percent in 2000-2006. At the margin, the average rate jumped to 10.0 percent in 2003-2005 and 7.4 percent in 2003-2006. House prices measured by the FHFA house price index increased 7.9 percent at the average yearly rate of 0.8 percent between 2006 and 2016 and 10.5 percent between 2005 and 2016 at the average yearly rate of 0.9 percent.

Table IIA2-4, US, FHFA House Price Index, Percentage Change and Average Rate of Percentage Change per Year, Selected Dates 1992-2016

Dec

∆%

Average ∆% per Year

1992-2016

131.4

3.6

1992-2000

39.3

4.2

2000-2003

24.2

7.5

2000-2005

50.3

8.5

2003-2005

21.0

10.0

2005-2016

10.5

0.9

2000-2006

53.9

7.5

2003-2006

23.9

7.4

2006-2016

7.9

0.8

Source: Federal Housing Finance Agency

http://www.fhfa.gov/DataTools

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, 2014, 2015 and IVQ2016. The contraction caused a strong shock to US wealth. Assets fell from $80.9 trillion in 2007 to $77.1 trillion in 2011 (http://www.federalreserve.gov/releases/z1/Current/) even after nine consecutive quarters of growth beginning in IIIQ2009 (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/04/mediocre-cyclical-economic-growth-with.html and earlier https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html), for decline of $3.8 trillion or 4.7 percent. Assets stood at $101.9 trillion in 2015 for gain of $21.0 trillion relative to $80.9 trillion in 2007 or increase by 26.0 percent, using unrounded data for percentage calculations. Assets increased to $107.9 trillion in IVQ2016 by $27.0 trillion relative to 2007 or 33.4 percent. Liabilities declined from $14.4 trillion in 2007 to $13.6 trillion in 2011 or by $752.8 billion equivalent to decline by 5.2 percent. Liabilities increased $182.7 billion or 1.3 percent from 2007 to 2015. Liabilities increased from $14.4 trillion in 2007 to $15.1 trillion in IVQ2016, by $691.0 billion or increase of 4.8 percent. Net worth shrank from $66.5 trillion in 2007 to $63.4 trillion in 2011, that is, $3.1 trillion equivalent to decline of 4.7 percent. Net worth increased from $66,499.3 billion in 2007 to $92,805.4 billion in IVQ2016 by $26,306.1 billion or 39.6 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 241.432 in Dec 2016 (http://www.bls.gov/cpi/data.htm) or 14.9 percent. Net worth adjusted by CPI inflation increased 21.4 percent from 2007 to IVQ2016. Nonfinancial assets increased $4352.8 billion from $28,078.6 billion in 2007 to $32,431.4 billion in IVQ2016 or 15.5 percent. There was increase from 2007 to IVQ2016 of $3259.3 billion in real estate assets or by 14.0 percent. Real estate assets adjusted for CPI inflation fell 0.8 percent between 2007 and IVQ2016. 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

2014

2015

IVQ2016

Assets

80,912.4

98,172.3

101,918.0

107,909.5

Nonfinancial

28,078.6

28,718.8

30,496.8

32,431.4

  Real Estate

23,269.1

23,212.7

24,790.1

26,528.4

  Durable Goods

  4,476.0

5,052.9

  5,236.8

5,417.9

Financial

52,833.9

69,453.5

71,421.3

75,478.1

  Deposits

  5,968.2

7,891.0

  8,391.3

9,102.0

  Debt Secs.

  3,951.4

3,979.2

  4,422.7

4,246.0

  Mutual Fund Shares

   4,314.9

6,726.2

   6,504.3

6,851.5

  Equities Corporate

   10,046.8

14,357.4

   14,189.7

15,874.2

  Equity Noncorporate

   8,816.4

10,103.0

   10,834.2

11,249.3

  Pension

15,080.9

20,666.8

21,256.1

22,259.4

Liabilities

14,413.1

14,288.1

14,631.0

15,104.1

  Home Mortgages

10,613.1

9,454.9

  9,536.2

9,753.7

  Consumer Credit

   2,609.9

3,318.0

   3,535.7

3,764.7

Net Worth

66,499.3

83,884.2

87,287.1

92,805.4

Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2017. Flow of funds, balance sheets and integrated macroeconomic accounts: fourth quarter 2016. Washington, DC, Federal Reserve System, Mar 9. http://www.federalreserve.gov/releases/z1/.

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 94.3 percent in the 10-city composite of the Case-Shiller home price index, 77.2 percent in the 20-city composite and 61.0 percent in the US national home price index between Feb 2000 and Feb 2005. Prices rose around 100 percent from Feb 2000 to Feb 2006, increasing 121.6 percent for the 10-city composite, 101.7 percent for the 20-city composite and 80.5 percent in the US national index. House prices rose 36.4 percent between Feb 2003 and Feb 2005 for the 10-city composite, 31.1 percent for the 20-city composite and 26.2 percent for the US national propelled by low fed funds rates of 1.0 percent between Dec 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 Feb 2003 and Feb 2006, the 10-city index gained 55.6 percent; the 20-city index increased 49.2 percent; and the US national 41.4 percent. House prices have fallen from Feb 2006 to Feb 2017 by 7.2 percent for the 10-city composite and 4.8 percent for the 20-city composite, increasing 2.2 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 Feb 2017, house prices increased 5.2 percent in the 10-city composite, increasing 5.9 percent in the 20-city composite and 5.8 percent in the US national. Table IIA-1 also shows that house prices increased 105.6 percent between Feb 2000 and Feb 2017 for the 10-city composite, increasing 92.0 percent for the 20-city composite and 84.5 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 8.4 percent from the peak in Jun 2006 to Feb 2017 and the 20-city composite fell 6.3 percent from the peak in Jul 2006 to Feb 2017. The US national increased 0.5 percent in Feb 2017 from the peak of the 10-city composite in Jun 2006 and changed 0.0 percent from the peak of the 20-city composite to 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 2016 for the 10-city composite was 3.8 percent and 3.5 percent for the US national. Data for the 20-city composite are available only beginning in Jan 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 3.5 percent from Dec 1987 to Dec 2016 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 2016 was 3.8 percent while the rate of the 20-city composite was 3.5 percent and 3.4 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

∆% Feb 2000 to Feb 2003

42.4

35.2

27.6

∆% Feb 2000 to Feb 2005

94.3

77.2

61.0

∆% Feb 2003 to Feb 2005

36.4

31.1

26.2

∆% Feb 2000 to Feb 2006

121.6

101.7

80.5

∆% Feb 2003 to Feb 2006

55.6

49.2

41.4

∆% Feb 2005 to Feb 2017

5.8

8.4

14.6

∆% Feb 2006 to Feb 2017

-7.2

-4.8

2.2

∆% Feb 2009 to Feb 2017

34.0

35.2

25.7

∆% Feb 2010 to Feb 2017

32.1

34.3

29.7

∆% Feb 2011 to Feb 2017

36.0

39.2

34.7

∆% Feb 2012 to Feb 2017

41.4

44.3

38.5

∆% Feb 2013 to Feb 2017

30.3

32.1

27.8

∆% Feb 2014 to Feb 2017

15.2

17.0

16.0

∆% Feb 2015 to Feb 2017

10.1

11.6

11.3

∆% Feb 2016 to Feb 2017

5.2

5.9

5.8

∆% Feb 2000 to Feb 2017

105.6

92.0

84.5

∆% Peak Jun 2006 Feb 2017

-8.4

  

0.5

∆% Peak Jul 2006 Feb 2017

  

-6.3

0.0

Average ∆% Dec 1987-Dec 2016

3.8

NA

3.5

Average ∆% Dec 1987-Dec 2000

3.8

NA

3.6

Average ∆% Dec 1992-Dec 2000

5.0

NA

4.5

Average ∆% Dec 2000-Dec 2016

3.8

3.5

3.4

Source: http://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 Feb 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/516352_cshomeprice-release-0425.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 0.9 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. Except for Mar through Apr 2012, 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 0.3 percent in Feb 2017 and the 20-city increased 0.4 percent. The 20-city SA increased 0.6 percent in Feb 2017 and the 20-city composite SA increased 0.7 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 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

Feb 2017

0.6

0.3

0.7

0.4

Jan

0.9

0.2

0.9

0.2

Dec 2016

0.9

0.3

0.9

0.3

Nov

0.9

0.2

0.9

0.2

Oct

0.5

0.0

0.6

0.0

Sep

0.4

0.0

0.7

0.1

Aug

0.2

0.3

0.0

0.3

Jul

0.0

0.5

0.1

0.5

Jun

0.0

0.7

0.1

0.8

May

-0.2

0.8

0.0

0.9

Apr

-0.2

1.0

-0.4

1.1

Mar

1.1

0.9

1.3

0.9

Feb

0.5

0.2

0.5

0.2

Jan

0.6

-0.1

0.6

0.0

Dec 2015

0.5

-0.1

0.6

0.0

Nov

0.7

-0.1

0.7

0.0

Oct

0.5

-0.1

0.6

0.0

Sep

0.5

0.1

0.7

0.1

Aug

0.2

0.2

0.0

0.3

Jul

0.1

0.6

0.2

0.7

Jun

0.1

0.9

0.2

1.0

May

0.1

1.1

0.1

1.1

Apr

-0.2

1.1

-0.3

1.1

Mar

0.9

0.8

1.2

0.9

Feb

0.9

0.5

0.9

0.5

Jan

0.6

-0.1

0.6

-0.1

Dec 2014

0.7

0.0

0.7

0.0

Nov

0.5

-0.3

0.5

-0.2

Oct

0.5

-0.1

0.5

-0.1

Sep

0.3

-0.1

0.4

-0.1

Aug

0.0

0.2

0.0

0.2

Jul

0.0

0.6

0.0

0.6

Jun

0.1

1.0

0.1

1.0

May

0.0

1.1

0.1

1.1

Apr

-0.1

1.1

-0.2

1.2

Mar

0.9

0.8

1.1

0.9

Feb

0.5

0.0

0.5

0.0

Jan

0.7

-0.1

0.6

-0.1

Dec 2013

0.6

-0.1

0.6

-0.1

Nov

0.8

0.0

0.8

-0.1

Oct

0.9

0.2

0.9

0.2

Sep

1.1

0.7

1.1

0.7

Aug

1.1

1.3

1.1

1.3

Jul

1.1

1.9

1.1

1.8

Jun

1.2

2.2

1.1

2.2

May

1.3

2.5

1.4

2.5

Apr

1.6

2.6

1.3

2.6

Mar

1.4

1.3

1.5

1.3

Feb

1.0

0.3

0.9

0.2

Jan

0.8

0.0

0.9

0.0

Dec 2012

0.9

0.2

0.9

0.2

Nov

0.6

-0.3

0.7

-0.2

Oct

0.6

-0.2

0.7

-0.1

Sep

0.6

0.3

0.6

0.3

Aug

0.6

0.8

0.6

0.9

Jul

0.6

1.5

0.7

1.6

Jun

1.0

2.1

1.1

2.3

May

1.0

2.2

1.1

2.4

Apr

0.5

1.4

0.4

1.4

Mar

0.1

-0.1

0.2

0.0

Feb

-0.2

-0.9

0.0

-0.8

Jan

-0.2

-1.1

-0.2

-1.0

Dec 2011

-0.5

-1.2

-0.4

-1.1

Nov

-0.6

-1.4

-0.5

-1.3

Oct

-0.6

-1.3

-0.6

-1.4

Sep

-0.4

-0.6

-0.5

-0.7

Aug

-0.2

0.1

-0.2

0.1

Jul

0.0

0.9

0.0

1.0

Jun

-0.1

1.0

-0.1

1.2

May

-0.2

1.0

-0.2

1.0

Apr

-0.1

0.6

-0.2

0.6

Mar

-0.7

-1.0

-0.7

-1.0

Feb

-0.4

-1.3

-0.3

-1.2

Jan

-0.3

-1.1

-0.3

-1.1

Dec 2010

-0.2

-0.9

-0.2

-1.0

Source: http://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 $10.4 trillion or 12.8 percent from 2007 to 2008 and $8.8 trillion or 10.9 percent to 2009. Net worth fell $10.4 trillion from 2007 to 2008 or 15.7 percent and $8.7 trillion to 2009 or 13.0 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

80,912.4

70,517.5

-10,394.9

72,079.1

-8,833.3

Non
FIN

28,078.6

24,403.5

-3,675.1

23,414.6

-4,664.0

RE

23,269.1

19,469.3

-3,799.8

18,458.2

-4,810.9

FIN

52,833.9

46,114.0

-6,719.9

48,664.5

-4,169.4

LIAB

14,413.1

14,326.9

-86.20

14,126.4

-286.7

NW

66,499.3

56,190.6

-10,308.7

57,952.7

-8,546.6

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. 2017. Flow of funds, balance sheets and integrated macroeconomic accounts: fourth quarter 2016. Washington, DC, Federal Reserve System, Mar 9. http://www.federalreserve.gov/releases/z1/.

IIC Decline of United States Homeownership. The US Census Bureau measures the homeownership rate by “dividing the number of owner-occupied housing units by the number of occupied housing units or households” (http://quickfacts.census.gov/qfd/meta/long_HSG445213.htm). The rate of homeownership of the US quarterly from 1965 to 2017 is in Table IIA-3. The rate of homeownership increased from 63.5 in IQ1966 to 64.4 in IVQ1969. The rate of homeownership rose from 64.0 in IVQ1970 to 65.5 in IVQ1980, declining to 63.8 in IVQ1989. The rate of homeownership increased to 66.9 in IVQ1999, reaching 69.0 in IVQ2005. The rate of homeownership fell to 63.6 in IQ2017.

Table IIA-3, US, Home Ownership Rate, 1964-2017, NSA, %

Year

1st Quarter

2nd Quarter

3rd Quarter

4th Quarter

1956

NA

NA

NA

NA

1957

NA

NA

NA

NA

1958

NA

NA

NA

NA

1959

NA

NA

NA

NA

1960

NA

NA

NA

NA

1961

NA

NA

NA

NA

1962

NA

NA

NA

NA

1963

NA

NA

NA

NA

1964

NA

NA

NA

NA

1965

62.9

62.9

62.9

63.4

1966

63.5

63.2

63.3

63.8

1967

63.3

63.9

63.8

63.5

1968

63.6

64.1

64.1

63.6

1969

64.1

64.4

64.4

64.4

1970

64.3

64

64.4

64

1971

64

64.1

64.4

64.5

1972

64.3

64.5

64.3

64.4

1973

64.9

64.4

64.4

64.4

1974

64.8

64.8

64.6

64.4

1975

64.4

64.9

64.6

64.5

1976

64.6

64.6

64.9

64.8

1977

64.8

64.5

65

64.9

1978

64.8

64.4

65.2

65.4

1979

64.8

64.9

65.8

65.4

1980

65.5

65.5

65.8

65.5

1981

65.6

65.3

65.6

65.2

1982

64.8

64.9

64.9

64.5

1983

64.7

64.7

64.8

64.4

1984

64.6

64.6

64.6

64.1

1985

64.1

64.1

63.9

63.5

1986

63.6

63.8

63.8

63.9

1987

63.8

63.8

64.2

64.1

1988

63.7

63.7

64

63.8

1989

63.9

63.8

64.1

63.8

1990

64

63.7

64

64.1

1991

63.9

63.9

64.2

64.2

1992

64

63.9

64.3

64.4

1993

64.2

64.4

64.7

64.6

1994

63.8

63.8

64.1

64.2

1995

64.2

64.7

65

65.1

1996

65.1

65.4

65.6

65.4

1997

65.4

65.7

66

65.7

1998

65.9

66

66.8

66.4

1999

66.7

66.6

67

66.9

2000

67.1

67.2

67.7

67.5

2001

67.5

67.7

68.1

68

2002

67.8

67.6

68

68.3

2003

68

68

68.4

68.6

2004

68.6

69.2

69

69.2

2005

69.1

68.6

68.8

69

2006

68.5

68.7

69

68.9

2007

68.4

68.2

68.2

67.8

2008

67.8

68.1

67.9

67.5

2009

67.3

67.4

67.6

67.2

2010

67.1

66.9

66.9

66.5

2011

66.4

65.9

66.3

66

2012

65.4

65.5

65.5

65.4

2013

65

65

65.3

65.2

2014

64.8

64.7

64.4

64

2015

63.7

63.4

63.7

63.8

2016

63.5

62.9

63.5

63.7

2017

63.6

NA

NA

NA

Source: United States Bureau of the Census

http://www.census.gov/housing/hvs/index.html

Chart IIA-1 of the US Census Bureau provides the rate of homeownership of the US from 1965 to 2017. There are four periods in US homeownership. The rate of homeownership increased in an upward trend from 1965 to 1980. The rate fell in the 1980s and stabilized until 1995. The rate then increased sharply from 1996 to 2005. In the current period, the rate of homeownership shows the sharpest downward trend in available data from 2005 to 2017.

Chart IIA-1, US Home Ownership Rate, Quarterly, 1964-2017, %

Source: US Bureau of the Census

http://www.census.gov/housing/hvs/index.html

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

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