Dollar Devaluation and Yuan Revaluation, FOMC Changed Long-Run Goals
and Monetary Policy Strategy to Target “Inflation Moderately Above 2 Percent
For Some Time” If Inflation Had Been Below 2 Percent “Persistently,” US GDP
Contracted at SAAR of 31.7 Percent in IIQ2020 and Decreased 9.1 Percent
Relative to a Year Earlier In the Global Recession, with Output in the US Reaching a High
in Feb 2020 (https://www.nber.org/cycles.html), in the
Lockdown of Economic Activity in the COVID-19 Event, Mediocre Cyclical United
States Economic Growth with GDP Five Trillion Dollars Below Trend in the Lost Economic Cycle of the Global
Recession with Economic Growth Underperforming Below Trend Worldwide,
Cyclically Stagnating Real Private Fixed Investment, Swelling Undistributed
Corporate Profits with Profit Contraction in the Global Recession, with Output in the US
Reaching a High in Feb 2020 (https://www.nber.org/cycles.html), in the
Lockdown of Economic Activity in the COVID-19 Event, Increasing US New Home Sales
and Home Prices, World Inflation Waves with Increasing Price Levels In Most
Countries and Regions Worldwide, World Cyclical Slow Growth, and Government
Intervention in Globalization: Part V
Carlos M. Pelaez
© Carlos M. Pelaez, 2009,
2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.
IA Mediocre
Cyclical United States Economic Growth
IA1
Stagnating Real Private Fixed Investment
IA2
Swelling Undistributed Corporate Profits
IID United States Terms of International Trade
IIA United States
Housing Collapse
IIA1 Sales of New Houses
IIA2
United States House Prices
I World
Inflation Waves
IA Appendix: Transmission of
Unconventional Monetary Policy
IB1 Theory
IB2 Policy
IB3 Evidence
IB4 Unwinding Strategy
IC United
States Inflation
IC Long-term US Inflation
ID Current US Inflation
IE Theory and Reality
of Economic History, Cyclical Slow Growth Not Secular Stagnation and Monetary
Policy Based on Fear of Deflation
III World Financial Turbulence
IV Global Inflation
V World Economic
Slowdown
VA United States
VB Japan
VC China
VD Euro Area
VE Germany
VF France
VG Italy
VH United Kingdom
VI Valuation of Risk
Financial Assets
VII Economic
Indicators
VIII Interest Rates
IX Conclusion
References
Appendixes
Appendix I The Great Inflation
IIIB Appendix on Safe
Haven Currencies
IIIC Appendix on
Fiscal Compact
IIID Appendix on
European Central Bank Large Scale Lender of Last Resort
IIIG Appendix on Deficit Financing of Growth and the
Debt Crisis
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 |
24.0 |
40.6 |
35.8 |
25.9 |
11.0 |
|
IVQ2000 |
50.5 |
65.0 |
67.6 |
62.9 |
25.4 |
|
IVQ2000 to |
55.0 |
62.1 |
72.0 |
71.2 |
33.1 |
|
IVQ2005 to |
-1.5 |
-8.7 |
-2.3 |
-7.4 |
8.9 |
|
IVQ2006 |
-4.4 |
-7.1 |
-4.8 |
-11.9 |
2.6 |
|
IVQ2007 to |
-1.9 |
-5.1 |
-5.0 |
-8.6 |
0.7 |
|
IVQ2011 to |
18.9 |
7.3 |
6.9 |
19.9 |
11.8 |
|
IVQ2012 to |
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 |
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 |
11.1 |
18.3 |
14.7 |
18.9 |
44.6 |
|
IVQ2000 |
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 |
26.6 |
4.7 |
-5.4 |
-2.6 |
-14.7 |
|
IVQ2006 |
19.1 |
2.6 |
-5.4 |
-8.7 |
-15.1 |
|
IVQ2007 to |
15.2 |
3.2 |
-2.1 |
-5.6 |
-6.0 |
|
IVQ2011 to |
18.1 |
13.5 |
14.2 |
32.9 |
37.6 |
|
IVQ2012 to |
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 4.5 percent in Jun 2011. The house price index increased 0.6
percent in Jan 2019 and increased 5.7 percent in 12 months. House prices
increased 0.4 percent in Feb 2019 and increased 5.3 percent in 12 months. The
house price index increased 0.2 percent in Mar 2019 and increased 5.2 percent
in 12 months. House prices increased 0.6 percent in Apr 2019 and increased 5.5
percent in 12 months. The house price index increased 0.4 percent in May 2019
and increased 5.3 percent in 12 months. House prices increased 0.2 percent in
Jun 2019 and increased 5.0 percent in 12 months. The house price index
increased 0.6 percent in Jul 2019 and increased 5.2 percent in 12 months. House
prices increased 0.2 percent in Aug 2019 and increased 4.9 percent in 12
months. The house price index increased 0.9 percent in Sep 2019 and increased
5.5 percent in 12 months. House prices increased 0.4 percent in Oct 2019 and
increased 5.4 percent in 12 months. The house price index increased 0.4 percent
in Nov 2019 and increased 5.3 percent in 12 months. House prices increased 0.8
percent in Dec 2019 and increased 5.7 percent in 12 months. The house price
index increased 0.5 percent in Jan 2020 and increased 5.7 percent in 12 months.
House prices increased 0.8 percent in Feb 2020 and increased 6.1 percent in 12
months. The house price index increased 0.2 percent in Mar 2020 and increased
6.1 percent in 12 months. House prices increased 0.1 percent in May 2020 and
increased 5.6 percent in 12 months. The house price index decreased 0.2 percent
in May 2020 and increased 4.9 percent in 12 months. House prices increased 0.9
percent in Jun 2020 and increased 5.7 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 |
||||
|
6/1/2020 |
0.9 |
5.7 |
|||
|
5/1/2020 |
-0.2 |
4.9 |
|||
|
4/1/2020 |
0.1 |
5.6 |
|||
|
3/1/2020 |
0.2 |
6.1 |
|||
|
2/1/2020 |
0.8 |
6.1 |
|||
|
1/1/2020 |
0.5 |
5.7 |
|||
|
12/1/2019 |
0.8 |
5.7 |
|||
|
11/1/2019 |
0.4 |
5.3 |
|||
|
10/1/2019 |
0.4 |
5.4 |
|||
|
9/1/2019 |
0.9 |
5.5 |
|||
|
8/1/2019 |
0.2 |
4.9 |
|||
|
7/1/2019 |
0.6 |
5.2 |
|||
|
6/1/2019 |
0.2 |
5 |
|||
|
5/1/2019 |
0.4 |
5.3 |
|||
|
4/1/2019 |
0.6 |
5.5 |
|||
|
3/1/2019 |
0.2 |
5.2 |
|||
|
2/1/2019 |
0.4 |
5.3 |
|||
|
1/1/2019 |
0.6 |
5.7 |
|||
|
12/1/2018 |
0.4 |
5.9 |
|||
|
11/1/2018 |
0.5 |
5.9 |
|||
|
10/1/2018 |
0.5 |
6 |
|||
|
9/1/2018 |
0.2 |
6.1 |
|||
|
8/1/2018 |
0.6 |
6.3 |
|||
|
7/1/2018 |
0.4 |
6.4 |
|||
|
6/1/2018 |
0.4 |
6.6 |
|||
|
5/1/2018 |
0.5 |
6.6 |
|||
|
4/1/2018 |
0.3 |
6.6 |
|||
|
3/1/2018 |
0.3 |
7 |
|||
|
2/1/2018 |
0.7 |
7.4 |
|||
|
1/1/2018 |
0.8 |
7.4 |
|||
|
12/1/2017 |
0.4 |
6.4 |
|||
|
11/1/2017 |
0.6 |
6.5 |
|||
|
10/1/2017 |
0.6 |
6.4 |
|||
|
9/1/2017 |
0.5 |
6.4 |
|||
|
8/1/2017 |
0.7 |
6.6 |
|||
|
7/1/2017 |
0.6 |
6.3 |
|||
|
6/1/2017 |
0.3 |
6.1 |
|||
|
5/1/2017 |
0.4 |
6.5 |
|||
|
4/1/2017 |
0.7 |
6.6 |
|||
|
3/1/2017 |
0.7 |
6.3 |
|||
|
2/1/2017 |
0.8 |
6.4 |
|||
|
1/1/2017 |
0 |
5.7 |
|||
|
12/1/2016 |
0.5 |
6.3 |
|||
|
11/1/2016 |
0.5 |
6.1 |
|||
|
10/1/2016 |
0.6 |
6.1 |
|||
|
9/1/2016 |
0.6 |
6 |
|||
|
8/1/2016 |
0.5 |
6 |
|||
|
7/1/2016 |
0.5 |
5.6 |
|||
|
6/1/2016 |
0.6 |
5.6 |
|||
|
5/1/2016 |
0.4 |
5.6 |
|||
|
4/1/2016 |
0.4 |
5.8 |
|||
|
3/1/2016 |
0.8 |
5.8 |
|||
|
2/1/2016 |
0.1 |
5.4 |
|||
|
1/1/2016 |
0.5 |
6 |
|||
|
12/1/2015 |
0.4 |
5.5 |
|||
|
11/1/2015 |
0.6 |
5.7 |
|||
|
10/1/2015 |
0.5 |
5.6 |
|||
|
9/1/2015 |
0.6 |
5.6 |
|||
|
8/1/2015 |
0.2 |
5.1 |
|||
|
7/1/2015 |
0.5 |
5.4 |
|||
|
6/1/2015 |
0.4 |
5.3 |
|||
|
5/1/2015 |
0.6 |
5.5 |
|||
|
4/1/2015 |
0.3 |
5.1 |
|||
|
3/1/2015 |
0.4 |
5.2 |
|||
|
2/1/2015 |
0.8 |
5.1 |
|||
|
1/1/2015 |
0.1 |
4.7 |
|||
|
12/1/2014 |
0.6 |
5 |
|||
|
11/1/2014 |
0.5 |
4.8 |
|||
|
10/1/2014 |
0.6 |
4.4 |
|||
|
9/1/2014 |
0.1 |
4.1 |
|||
|
8/1/2014 |
0.5 |
4.6 |
|||
|
7/1/2014 |
0.4 |
4.4 |
|||
|
6/1/2014 |
0.5 |
4.7 |
|||
|
5/1/2014 |
0.2 |
4.8 |
|||
|
4/1/2014 |
0.3 |
5.5 |
|||
|
3/1/2014 |
0.3 |
5.8 |
|||
|
2/1/2014 |
0.4 |
6.4 |
|||
|
1/1/2014 |
0.5 |
6.6 |
|||
|
12/1/2013 |
0.5 |
6.8 |
|||
|
11/1/2013 |
0.1 |
6.7 |
|||
|
10/1/2013 |
0.3 |
7.2 |
|||
|
9/1/2013 |
0.6 |
7.5 |
|||
|
8/1/2013 |
0.3 |
7.3 |
|||
|
7/1/2013 |
0.6 |
7.7 |
|||
|
6/1/2013 |
0.6 |
7.4 |
|||
|
5/1/2013 |
0.8 |
7.2 |
|||
|
4/1/2013 |
0.5 |
7 |
|||
|
3/1/2013 |
1 |
7 |
|||
|
2/1/2013 |
0.7 |
6.7 |
|||
|
1/1/2013 |
0.7 |
6.2 |
|||
|
12/1/2012 |
0.5 |
5.1 |
|||
|
11/1/2012 |
0.5 |
4.8 |
|||
|
10/1/2012 |
0.5 |
4.8 |
|||
|
9/1/2012 |
0.4 |
3.8 |
|||
|
8/1/2012 |
0.6 |
4.1 |
|||
|
7/1/2012 |
0.3 |
3.2 |
|||
|
6/1/2012 |
0.4 |
3.1 |
|||
|
5/1/2012 |
0.6 |
3.1 |
|||
|
4/1/2012 |
0.5 |
2.1 |
|||
|
3/1/2012 |
0.9 |
1.8 |
|||
|
2/1/2012 |
0.2 |
-0.2 |
|||
|
1/1/2012 |
-0.3 |
-1.3 |
|||
|
12/1/2011 |
0.3 |
-1.5 |
|||
|
11/1/2011 |
0.5 |
-2.5 |
|||
|
10/1/2011 |
-0.6 |
-3.3 |
|||
|
9/1/2011 |
0.6 |
-2.5 |
|||
|
8/1/2011 |
-0.3 |
-4 |
|||
|
7/1/2011 |
0.2 |
-3.7 |
|||
|
6/1/2011 |
0.4 |
-4.5 |
|||
|
5/1/2011 |
-0.3 |
-5.9 |
|||
|
4/1/2011 |
0.2 |
-5.7 |
|||
|
3/1/2011 |
-1 |
-5.9 |
|||
|
2/1/2011 |
-0.9 |
-5.1 |
|||
|
1/1/2011 |
-0.5 |
-4.5 |
|||
|
12/1/2010 |
-0.8 |
-3.9 |
|||
|
12/1/2009 |
-1.1 |
-2 |
|||
|
12/1/2008 |
-0.3 |
-10.5 |
|||
|
12/1/2007 |
-0.5 |
-3.4 |
|||
|
12/1/2006 |
0.1 |
2.3 |
|||
|
12/1/2005 |
0.6 |
9.8 |
|||
|
12/1/2004 |
0.9 |
10.2 |
|||
|
12/1/2003 |
0.8 |
8 |
|||
|
12/1/2002 |
0.7 |
7.8 |
|||
|
12/1/2001 |
0.6 |
6.7 |
|||
|
12/1/2000 |
0.6 |
7.1 |
|||
|
12/1/1999 |
0.5 |
6.1 |
|||
|
12/1/1998 |
0.5 |
5.9 |
|||
|
12/1/1997 |
0.3 |
3.4 |
|||
|
12/1/1996 |
0.3 |
2.7 |
|||
|
12/1/1995 |
0.4 |
3 |
|||
|
12/1/1994 |
0 |
2.5 |
|||
|
12/1/1993 |
0.5 |
3.1 |
|||
|
12/1/1992 |
-0.1 |
2.4 |
Source: Federal
Housing Finance Agency
https://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 2019,
the FHFA house price index increased 170.2 percent at the yearly average rate
of 3.8 percent. In the period 1992-2000, the FHFA house price index increased
39.2 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 7.4 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 26.3 percent at the
average yearly rate of 1.8 percent between 2006 and 2019 and 29.2 percent
between 2005 and 2019 at the average yearly rate of 1.8 percent.
|
Dec |
∆% |
Average ∆% per Year |
|
1992-2019 |
170.2 |
3.8 |
|
1992-2000 |
39.2 |
4.2 |
|
2000-2003 |
24.2 |
7.5 |
|
2000-2005 |
50.2 |
8.5 |
|
2003-2005 |
21.0 |
10.0 |
|
2005-2019 |
29.2 |
1.8 |
|
2000-2006 |
53.7 |
7.4 |
|
2003-2006 |
23.8 |
7.4 |
|
2006-2019 |
26.3 |
1.8 |
Source: Federal
Housing Finance Agency
https://www.fhfa.gov/DataTools
The explanation
of the sharp contraction of household wealth can probably be found in the
origins of the financial crisis and global recession. Let V(T)
represent the value of the firm’s equity at time T and B stand
for the promised debt of the firm to bondholders and assume that corporate
management, elected by equity owners, is acting on the interests of equity
owners. Robert C. Merton (1974, 453) states:
“On the
maturity date T, the firm must either pay the promised payment of B
to the debtholders or else the current equity will be valueless. Clearly, if at
time T, V(T) > B, the firm should pay the
bondholders because the value of equity will be V(T) – B >
0 whereas if they do not, the value of equity would be zero. If V(T)
≤ B, then the firm will not make the payment and default the firm to the
bondholders because otherwise the equity holders would have to pay in
additional money and the (formal) value of equity prior to such payments would
be (V(T)- B) < 0.”
Pelaez and
Pelaez (The Global Recession Risk (2007), 208-9) apply this analysis to
the US housing market in 2005-2006 concluding:
“The house
market [in 2006] is probably operating with low historical levels of individual
equity. There is an application of structural models [Duffie and Singleton
2003] to the individual decisions on whether or not to continue paying a
mortgage. The costs of sale would include realtor and legal fees. There could
be a point where the expected net sale value of the real estate may be just
lower than the value of the mortgage. At that point, there would be an
incentive to default. The default vulnerability of securitization is unknown.”
There are
multiple important determinants of the interest rate: “aggregate wealth, the
distribution of wealth among investors, expected rate of return on physical
investment, taxes, government policy and inflation” (Ingersoll 1987, 405).
Aggregate wealth is a major driver of interest rates (Ibid, 406).
Unconventional monetary policy, with zero fed funds rates and flattening of long-term
yields by quantitative easing, causes uncontrollable effects on risk taking
that can have profound undesirable effects on financial stability. Excessively
aggressive and exotic monetary policy is the main culprit and not the
inadequacy of financial management and risk controls.
The net worth
of the economy depends on interest rates. In theory, “income is generally
defined as the amount a consumer unit could consume (or believe that it could)
while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is
a flow that is obtained by applying a rate of return, r, to a stock of
wealth, W, or Y = rW (Ibid). According to a subsequent
restatement: “The basic idea is simply that individuals live for many years and
that therefore the appropriate constraint for consumption decisions is the
long-run expected yield from wealth r*W. This yield was named permanent
income: Y* = r*W” (Darby 1974, 229), where * denotes permanent.
The simplified relation of income and wealth can be restated as:
W = Y/r
(1)
Equation (1)
shows that as r goes to zero, r →0, W grows without bound,
W→∞.
Lowering the
interest rate near the zero bound in 2003-2004 caused the illusion of permanent
increases in wealth or net worth in the balance sheets of borrowers and also of
lending institutions, securitized banking and every financial institution and
investor in the world. The discipline of calculating risks and returns was
seriously impaired. The objective of monetary policy was to encourage
borrowing, consumption and investment but the exaggerated stimulus resulted in
a financial crisis of major proportions as the securitization that had worked
for a long period was shocked with policy-induced excessive risk, imprudent
credit, high leverage and low liquidity by the incentive to finance everything
overnight at close to zero interest rates, from adjustable rate mortgages
(ARMS) to asset-backed commercial paper of structured investment vehicles
(SIV).
The
consequences of inflating liquidity and net worth of borrowers were a global
hunt for yields to protect own investments and money under management from the
zero interest rates and unattractive long-term yields of Treasuries and other
securities. Monetary policy distorted the calculations of risks and returns by
households, business and government by providing central bank cheap money.
Short-term zero interest rates encourage financing of everything with
short-dated funds, explaining the SIVs created off-balance sheet to issue
short-term commercial paper to purchase default-prone mortgages that were
financed in overnight or short-dated sale and repurchase agreements (Pelaez and
Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation
of Banks and Finance, 59-60, Globalization and the State Vol. I,
89-92, Globalization and the State Vol. II, 198-9, Government
Intervention in Globalization, 62-3, International Financial
Architecture, 144-9). ARMS were created to lower monthly mortgage payments
by benefitting from lower short-dated reference rates. Financial institutions
economized in liquidity that was penalized with near zero interest rates. There
was no perception of risk because the monetary authority guaranteed a minimum
or floor price of all assets by maintaining low interest rates forever or
equivalent to writing an illusory put option on wealth. Subprime mortgages were
part of the put on wealth by an illusory put on house prices. The housing
subsidy of $221 billion per year created the impression of ever increasing
house prices. The suspension of auctions of 30-year Treasuries was designed to
increase demand for mortgage-backed securities, lowering their yield, which was
equivalent to lowering the costs of housing finance and refinancing. Fannie and
Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked
with leverage of 75:1 under Congress-provided charters and lax oversight. The
combination of these policies resulted in high risks because of the put option
on wealth by near zero interest rates, excessive leverage because of cheap rates,
low liquidity because of the penalty in the form of low interest rates and
unsound credit decisions because the put option on wealth by monetary policy
created the illusion that nothing could ever go wrong, causing the
credit/dollar crisis and global recession (Pelaez and Pelaez, Financial
Regulation after the Global Recession, 157-66, Regulation of Banks, and
Finance, 217-27, International Financial Architecture, 15-18, The
Global Recession Risk, 221-5, Globalization and the State Vol. II,
197-213, Government Intervention in Globalization, 182-4).
There are
significant elements of the theory of bank financial fragility of Diamond and
Dybvig (1983) and Diamond and Rajan (2000, 2001a, 2001b) that help to explain
the financial fragility of banks during the credit/dollar crisis (see also
Diamond 2007). The theory of Diamond and Dybvig (1983) as exposed by Diamond
(2007) is that banks funding with demand deposits have a mismatch of liquidity
(see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 58-66).
A run occurs when too many depositors attempt to withdraw cash at the same
time. All that is needed is an expectation of failure of the bank. Three
important functions of banks are providing evaluation, monitoring and liquidity
transformation. Banks invest in human capital to evaluate projects of borrowers
in deciding if they merit credit. The evaluation function reduces adverse
selection or financing projects with low present value. Banks also provide
important monitoring services of following the implementation of projects,
avoiding moral hazard that funds be used for, say, real estate speculation
instead of the original project of factory construction. The transformation
function of banks involves both assets and liabilities of bank balance sheets.
Banks convert an illiquid asset or loan for a project with cash flows in the
distant future into a liquid liability in the form of demand deposits that can
be withdrawn immediately.
In the theory
of banking of Diamond and Rajan (2000, 2001a, 2001b), the bank creates
liquidity by tying human assets to capital. The collection skills of the
relationship banker convert an illiquid project of an entrepreneur into liquid
demand deposits that are immediately available for withdrawal. The
deposit/capital structure is fragile because of the threat of bank runs. In
these days of online banking, the run on Washington Mutual was through
withdrawals online. A bank run can be triggered by the decline of the value of
bank assets below the value of demand deposits.
Pelaez and
Pelaez (Regulation of Banks and Finance 2009b, 60, 64-5) find immediate
application of the theories of banking of Diamond, Dybvig and Rajan to the
credit/dollar crisis after 2007. It is a credit crisis because the main issue
was the deterioration of the credit portfolios of securitized banks as a result
of default of subprime mortgages. It is a dollar crisis because of the
weakening dollar resulting from relatively low interest rate policies of the
US. It caused systemic effects that converted into a global recession not only
because of the huge weight of the US economy in the world economy but also
because the credit crisis transferred to the UK and Europe. Management skills
or human capital of banks are illustrated by the financial engineering of complex
products. The increasing importance of human relative to inanimate capital
(Rajan and Zingales 2000) is revolutionizing the theory of the firm (Zingales
2000) and corporate governance (Rajan and Zingales 2001). Finance is one of the
most important examples of this transformation. Profits were derived from the
charter in the original banking institution. Pricing and structuring financial
instruments was revolutionized with option pricing formulas developed by Black
and Scholes (1973) and Merton (1973, 1974, 1998) that permitted the development
of complex products with fair pricing. The successful financial company must
attract and retain finance professionals who have invested in human capital,
which is a sunk cost to them and not of the institution where they work.
The complex
financial products created for securitized banking with high investments in
human capital are based on houses, which are as illiquid as the projects of
entrepreneurs in the theory of banking. The liquidity fragility of the securitized
bank is equivalent to that of the commercial bank in the theory of banking
(Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65). Banks
created off-balance sheet structured investment vehicles (SIV) that issued
commercial paper receiving AAA rating because of letters of liquidity guarantee
by the banks. The commercial paper was converted into liquidity by its use as
collateral in SRPs at the lowest rates and minimal haircuts because of the AAA
rating of the guarantor bank. In the theory of banking, default can be
triggered when the value of assets is perceived as lower than the value of the
deposits. Commercial paper issued by SIVs, securitized mortgages and
derivatives all obtained SRP liquidity on the basis of illiquid home mortgage
loans at the bottom of the pyramid. The run on the securitized bank had a clear
origin (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65):
“The increasing
default of mortgages resulted in an increase in counterparty risk. Banks were
hit by the liquidity demands of their counterparties. The liquidity shock
extended to many segments of the financial markets—interbank loans,
asset-backed commercial paper (ABCP), high-yield bonds and many others—when
counterparties preferred lower returns of highly liquid safe havens, such as
Treasury securities, than the risk of having to sell the collateral in SRPs at
deep discounts or holding an illiquid asset. The price of an illiquid asset is
near zero.”
Gorton and Metrick (2010H, 507) provide a
revealing quote to the work in 1908 of Edwin R. A. Seligman, professor of
political economy at Columbia University, founding member of the American
Economic Association and one of its presidents and successful advocate of
progressive income taxation. The intention of the quote is to bring forth the
important argument that financial crises are explained in terms of “confidence”
but as Professor Seligman states in reference to historical banking crises in
the US, the important task is to explain what caused the lack of confidence. It
is instructive to repeat the more extended quote of Seligman (1908, xi) on the
explanations of banking crises:
“The current
explanations may be divided into two categories. Of these the first includes
what might be termed the superficial theories. Thus it is commonly stated that
the outbreak of a crisis is due to lack of confidence,--as if the lack of
confidence was not in itself the very thing which needs to be explained. Of
still slighter value is the attempt to associate a crisis with some particular
governmental policy, or with some action of a country’s executive. Such puerile
interpretations have commonly been confined to countries like the United
States, where the political passions of democracy have had the fullest way.
Thus the crisis of 1893 was ascribed by the Republicans to the impending
Democratic tariff of 1894; and the crisis of 1907 has by some been termed the
‘[Theodore] Roosevelt panic,” utterly oblivious of the fact that from the time
of President Jackson, who was held responsible for the troubles of 1837, every
successive crisis had had its presidential scapegoat, and has been followed by
a political revulsion. Opposed to these popular, but wholly unfounded
interpretations, is the second class of explanations, which seek to burrow beneath
the surface and to discover the more occult and fundamental causes of the
periodicity of crises.”
Scholars ignore
superficial explanations in the effort to seek good and truth. The problem of
economic analysis of the credit/dollar crisis is the lack of a structural model
with which to attempt empirical determination of causes (Gorton and Metrick
2010SB). There would still be doubts even with a well-specified structural
model because samples of economic events do not typically permit separating
causes and effects. There is also confusion is separating the why of the crisis
and how it started and propagated, all of which are extremely important.
In true
heritage of the principles of Seligman (1908), Gorton (2009EFM) discovers a
prime causal driver of the credit/dollar crisis. The objective of subprime and
Alt-A mortgages was to facilitate loans to populations with modest means so
that they could acquire a home. These borrowers would not receive credit
because of (1) lack of funds for down payments; (2) low credit rating and
information; (3) lack of information on income; and (4) errors or lack of other
information. Subprime mortgage “engineering” was based on the belief that both
lender and borrower could benefit from increases in house prices over the short
run. The initial mortgage would be refinanced in two or three years depending
on the increase of the price of the house. According to Gorton (2009EFM, 13,
16):
“The
outstanding amounts of Subprime and Alt-A [mortgages] combined amounted to
about one quarter of the $6 trillion mortgage market in 2004-2007Q1. Over the
period 2000-2007, the outstanding amount of agency mortgages doubled, but
subprime grew 800%! Issuance in 2005 and 2006 of Subprime and Alt-A mortgages
was almost 30% of the mortgage market. Since 2000 the Subprime and Alt-A
segments of the market grew at the expense of the Agency (i.e., the government
sponsored entities of Fannie Mae and Freddie Mac) share, which fell from almost
80% (by outstanding or issuance) to about half by issuance and 67% by
outstanding amount. The lender’s option to rollover the mortgage after an
initial period is implicit in the subprime mortgage. The key design features of
a subprime mortgage are: (1) it is short term, making refinancing important;
(2) there is a step-up mortgage rate that applies at the end of the first
period, creating a strong incentive to refinance; and (3) there is a prepayment
penalty, creating an incentive not to refinance early.”
The prime
objective of successive administrations in the US during the past 20 years and
actually since the times of Roosevelt in the 1930s has been to provide
“affordable” financing for the “American dream” of home ownership. The US
housing finance system is mixed with public, public/private and purely private
entities. The Federal Home Loan Bank (FHLB) system was established by Congress
in 1932 that also created the Federal Housing Administration in 1934 with the
objective of insuring homes against default. In 1938, the government created
the Federal National Mortgage Association, or Fannie Mae, to foster a market
for FHA-insured mortgages. Government-insured mortgages were transferred from
Fannie Mae to the Government National Mortgage Association, or Ginnie Mae, to
permit Fannie Mae to become a publicly-owned company. Securitization of
mortgages began in 1970 with the government charter to the Federal Home Loan
Mortgage Corporation, or Freddie Mac, with the objective of bundling mortgages
created by thrift institutions that would be marketed as bonds with guarantees by
Freddie Mac (see Pelaez and Pelaez, Financial Regulation after the Global
Recession (2009a), 42-8). In the third quarter of 2008, total mortgages in
the US were $12,057 billion of which 43.5 percent, or $5423 billion, were
retained or guaranteed by Fannie Mae and Freddie Mac (Pelaez and Pelaez, Financial
Regulation after the Global Recession (2009a), 45). In 1990, Fannie Mae and
Freddie Mac had a share of only 25.4 percent of total mortgages in the US.
Mortgages in the US increased from $6922 billion in 2002 to $12,088 billion in
2007, or by 74.6 percent, while the retained or guaranteed portfolio of Fannie
and Freddie rose from $3180 billion in 2002 to $4934 billion in 2007, or by
55.2 percent.
According to
Pinto (2008) in testimony to Congress:
“There are
approximately 25 million subprime and Alt-A loans outstanding, with an unpaid
principal amount of over $4.5 trillion, about half of them held or guaranteed
by Fannie and Freddie. Their high risk activities were allowed to operate at
75:1 leverage ratio. While they may deny it, there can be no doubt that Fannie
and Freddie now own or guarantee $1.6 trillion in subprime, Alt-A and other
default prone loans and securities. This comprises over 1/3 of their risk
portfolios and amounts to 34% of all the subprime loans and 60% of all Alt-A
loans outstanding. These 10.5 million unsustainable, nonprime loans are
experiencing a default rate 8 times the level of the GSEs’ 20 million
traditional quality loans. The GSEs will be responsible for a large percentage
of an estimated 8.8 million foreclosures expected over the next 4 years,
accounting for the failure of about 1 in 6 home mortgages. Fannie and Freddie
have subprimed America.”
In
perceptive analysis of growth and macroeconomics in the past six decades, Rajan
(2012FA) argues that “the West can’t borrow and spend its way to recovery.” The
Keynesian paradigm is not applicable in current conditions. Advanced economies
in the West could be divided into those that reformed regulatory structures to
encourage productivity and others that retained older structures. In the period
from 1950 to 2000, Cobet and Wilson (2002) find that US productivity, measured
as output/hour, grew at the average yearly rate of 2.9 percent while Japan grew
at 6.3 percent and Germany at 4.7 percent (see Pelaez and Pelaez, The Global Recession Risk (2007),
135-44). In the period from 1995 to
2000, output/hour grew at the average yearly rate of 4.6 percent in the US but
at lower rates of 3.9 percent in Japan and 2.6 percent in the US. Rajan (2012FA)
argues that the differential in productivity growth was accomplished by
deregulation in the US at the end of the 1970s and during the 1980s. In
contrast, Europe did not engage in reform with the exception of Germany in the
early 2000s that empowered the German economy with significant productivity
advantage. At the same time, technology and globalization increased relative
remunerations in highly-skilled, educated workers relative to those without
skills for the new economy. It was then politically appealing to improve the
fortunes of those left behind by the technological revolution by means of
increasing cheap credit. As Rajan (2012FA) argues:
“In 1992, Congress passed the Federal Housing Enterprises
Financial Safety and Soundness Act, partly to gain more control over Fannie Mae
and Freddie Mac, the giant private mortgage agencies, and partly to promote
affordable homeownership for low-income groups. Such policies helped money flow
to lower-middle-class households and raised their spending—so much so that
consumption inequality rose much less than income inequality in the years
before the crisis. These policies were also politically popular. Unlike when it
came to an expansion in government welfare transfers, few groups opposed
expanding credit to the lower-middle class—not the politicians who wanted more
growth and happy constituents, not the bankers and brokers who profited from
the mortgage fees, not the borrowers who could now buy their dream houses with
virtually no money down, and not the laissez-faire bank regulators who thought
they could pick up the pieces if the housing market collapsed. The Federal
Reserve abetted these shortsighted policies. In 2001, in response to the
dot-com bust, the Fed cut short-term interest rates to the bone. Even though
the overstretched corporations that were meant to be stimulated were not
interested in investing, artificially low interest rates acted as a tremendous
subsidy to the parts of the economy that relied on debt, such as housing and
finance. This led to an expansion in housing construction (and related
services, such as real estate brokerage and mortgage lending), which created
jobs, especially for the unskilled. Progressive economists applauded this
process, arguing that the housing boom would lift the economy out of the
doldrums. But the Fed-supported bubble proved unsustainable. Many construction
workers have lost their jobs and are now in deeper trouble than before, having
also borrowed to buy unaffordable houses. Bankers obviously deserve a large
share of the blame for the crisis. Some of the financial sector’s activities
were clearly predatory, if not outright criminal. But the role that the
politically induced expansion of credit played cannot be ignored; it is the
main reason the usual checks and balances on financial risk taking broke down.”
In fact, Raghuram G. Rajan (2005) anticipated low
liquidity in financial markets resulting from low interest rates before the
financial crisis that caused distortions of risk/return decisions provoking the
credit/dollar crisis and global recession from IVQ2007 to IIQ2009. Near zero
interest rates of unconventional monetary policy induced excessive risks and
low liquidity in financial decisions that were critical as a cause of the
credit/dollar crisis after 2007. Rajan (2012FA) argues that it is not feasible
to return to the employment and income levels before the credit/dollar crisis
because of the bloated construction sector, financial system and government
budgets.
Table IIA-2 shows the euphoria of prices during
the housing boom and the subsequent decline. House prices rose 64.0 percent in
the US national home price index between Jun 2000 and Jun 2005. Prices rose 76.0
percent in the US national index from Jun 2000 to Jun 2006. House prices rose 29.1
percent between Jun 2003 and Jun 2005 for the US national propelled by low fed
funds rates of 1.0 percent between Jul 2003 and Jul 2004. Fed funds rates increased by 0.25 basis
points at every meeting of the Federal Open Market Committee (FOMC) from Jun 2004
until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of
auctions of the 30-year Treasury bond caused decrease of yields of
mortgage-backed securities with intended increase in mortgage rates. Similarly,
between Jun 2003 and Jun 2006 the US national increased 38.5 percent. House
prices have increased from Jun 2006 to Jun 2020 by 19.1 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 Jun 2020, house prices increased 4.3 percent in the US national.
Table IIA-1 also shows that house prices increased 109.6 percent between Jun
2000 and Jun 2020 for the US national. House prices are close to the lowest
level since peaks during the boom before the financial crisis and global
recession. The US national increased 19.1 percent in Jun 2020 from the peak in
Jun 2006 and increased 19.1 percent from the peak in Jul 2006. The final part
of Table II-2 provides average annual percentage rates of growth of the house
price indexes of Standard & Poor’s Case-Shiller. The average rate for the
US national was 3.6 percent from Dec 1987 to Dec 2019 and 3.6 percent from Dec
1987 to Dec 2000. Although the global recession affecting the US between
IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly
above 30 percent, the average annual growth rate between Dec 2000 and Dec 2019
was 3.6 percent for the US national.
Table IIA-1,
US, Percentage Changes of Standard & Poor’s Case-Shiller National Home
Price Indices, Not Seasonally Adjusted, ∆%
|
|
US National |
|
∆% Jun 2000
to Jun 2003 |
27.1 |
|
∆% Jun 2000
to Jun 2005 |
64.0 |
|
∆% Jun 2003
to Jun 2005 |
29.1 |
|
∆% Jun 2000
to Jun 2006 |
76.0 |
|
∆% Jun 2003
to Jun 2006 |
38.5 |
|
∆% Jun 2005
to Jun 2020 |
27.8 |
|
∆% Jun 2006
to Jun 2020 |
19.1 |
|
∆% Jun 2009
to Jun 2020 |
46.7 |
|
∆% Jun 2010
to Jun 2020 |
48.8 |
|
∆% Jun 2011
to Jun 2020 |
54.9 |
|
∆% Jun 2012
to Jun 2020 |
53.5 |
|
∆% Jun 2013
to Jun 2020 |
40.5 |
|
∆% Jun 2014
to Jun 2020 |
32.2 |
|
∆% Jun 2015
to Jun 2020 |
26.7 |
|
∆% Jun 2016
to Jun 2020 |
20.8 |
|
∆% Jun 2017
to Jun 2020 |
14.3 |
|
∆% Jun 2018
to Jun 2020 |
7.7 |
|
∆% Jun 2019
to Jun 2020 |
4.3 |
|
∆% Jun 2000
to Jun 2020 |
109.6 |
|
∆% Peak Jun
2006 to Jun 2020 |
19.1 |
|
∆% Peak Jul
2006 to Jun 2020 |
19.1 |
|
Average ∆%
Dec 1987-Dec 2019 |
3.6 |
|
Average ∆%
Dec 1987-Dec 2000 |
3.6 |
|
Average ∆%
Dec 1992-Dec 2000 |
4.5 |
|
Average ∆%
Dec 2000-Dec 2019 |
3.6 |
Monthly house prices
increased sharply from Feb 2013 to Jan 2014 for both the SA and NSA national
house price, as shown in Table IIA-3. In Jan 2013, the seasonally adjusted
national house price index increased 0.9 percent and the NSA increased 0.3.
House prices increased at high monthly percentage rates from Feb to Nov 2013.
The most important seasonal factor in house prices is school changes for
wealthier homeowners with more expensive houses. With seasonal adjustment,
house prices fell from Dec 2010 throughout Mar 2011 and then increased in every
month from Apr to Jul 2011 but fell in every month from Aug 2011 to Feb 2012.
The not seasonally adjusted index registers increase in Mar 2012 of 1.4
percent. Not seasonally adjusted house
prices increased 1.9 percent in Apr 2012 and at high monthly percentage rates
through Aug 2012. House prices not seasonally adjusted stalled from Oct 2012 to
Dec 2012 and surged from Feb to Sep 2013, decelerating in Oct 2013-Jan 2014.
House prices grew at fast rates in Mar-Jul 2014. The SA national house price index
increased 0.2 percent in May 2020 and the NSA index increased 0.6 percent.
Declining house prices cause multiple adverse effects of which two are quite
evident. (1) There is a disincentive to buy houses in continuing price
declines. (2) More mortgages could be losing fair market value relative to
mortgage debt. Another possibility is a wealth effect that consumers restrain
purchases because of the decline of their net worth in houses.
Table IIA-2,
US, Monthly Percentage Change of S&P Corelogic Case-Shiller National Home
Price Indices, Seasonally Adjusted and Not Seasonally Adjusted, ∆%
|
|
|
SA ∆% |
|
|
NSA ∆% |
|
December 2010 |
-0.1 |
-0.8 |
|||
|
January 2011 |
-0.4 |
-1.1 |
|||
|
February 2011 |
-0.8 |
-0.9 |
|||
|
March 2011 |
-0.3 |
0.0 |
|||
|
April 2011 |
0.0 |
1.0 |
|||
|
May 2011 |
-0.1 |
1.1 |
|||
|
June 2011 |
0.0 |
0.9 |
|||
|
July 2011 |
-0.1 |
0.3 |
|||
|
August 2011 |
-0.3 |
-0.4 |
|||
|
September
2011 |
-0.5 |
-1.1 |
|||
|
October 2011 |
-0.5 |
-1.3 |
|||
|
November 2011 |
-0.6 |
-1.3 |
|||
|
December 2011 |
-0.3 |
-1.1 |
|||
|
January 2012 |
0.0 |
-0.7 |
|||
|
February 2012 |
-0.1 |
-0.1 |
|||
|
March 2012 |
1.0 |
1.4 |
|||
|
April 2012 |
0.9 |
1.9 |
|||
|
May 2012 |
0.7 |
1.9 |
|||
|
June 2012 |
0.6 |
1.5 |
|||
|
July 2012 |
0.5 |
0.8 |
|||
|
August 2012 |
0.4 |
0.3 |
|||
|
September
2012 |
0.4 |
-0.2 |
|||
|
October 2012 |
0.5 |
-0.3 |
|||
|
November 2012 |
0.7 |
0.0 |
|||
|
December 2012 |
0.6 |
-0.1 |
|||
|
January 2013 |
0.9 |
0.3 |
|||
|
February 2013 |
0.6 |
0.6 |
|||
|
March 2013 |
1.5 |
1.9 |
|||
|
April 2013 |
1.0 |
2.0 |
|||
|
May 2013 |
0.9 |
1.9 |
|||
|
June 2013 |
0.9 |
1.7 |
|||
|
July 2013 |
0.9 |
1.2 |
|||
|
August 2013 |
0.9 |
0.7 |
|||
|
September
2013 |
0.8 |
0.2 |
|||
|
October 2013 |
0.6 |
-0.1 |
|||
|
November 2013 |
0.5 |
-0.1 |
|||
|
December 2013 |
0.6 |
0.0 |
|||
|
January 2014 |
0.6 |
0.1 |
|||
|
February 2014 |
0.4 |
0.3 |
|||
|
March 2014 |
0.3 |
0.8 |
|||
|
April 2014 |
0.2 |
1.1 |
|||
|
May 2014 |
0.2 |
1.1 |
|||
|
June 2014 |
0.2 |
0.9 |
|||
|
July 2014 |
0.3 |
0.6 |
|||
|
August 2014 |
0.4 |
0.2 |
|||
|
September
2014 |
0.4 |
-0.1 |
|||
|
October 2014 |
0.4 |
-0.2 |
|||
|
November 2014 |
0.4 |
-0.1 |
|||
|
December 2014 |
0.4 |
-0.1 |
|||
|
January 2015 |
0.4 |
-0.1 |
|||
|
February 2015 |
0.3 |
0.2 |
|||
|
March 2015 |
0.4 |
0.9 |
|||
|
April 2015 |
0.3 |
1.1 |
|||
|
May 2015 |
0.3 |
1.1 |
|||
|
June 2015 |
0.3 |
0.9 |
|||
|
July 2015 |
0.4 |
0.6 |
|||
|
August 2015 |
0.5 |
0.3 |
|||
|
September
2015 |
0.5 |
0.1 |
|||
|
October 2015 |
0.6 |
0.0 |
|||
|
November 2015 |
0.5 |
0.1 |
|||
|
December 2015 |
0.5 |
0.0 |
|||
|
January 2016 |
0.4 |
0.0 |
|||
|
February 2016 |
0.2 |
0.1 |
|||
|
March 2016 |
0.3 |
0.8 |
|||
|
April 2016 |
0.3 |
1.1 |
|||
|
May 2016 |
0.4 |
1.0 |
|||
|
June 2016 |
0.4 |
0.9 |
|||
|
July 2016 |
0.4 |
0.6 |
|||
|
August 2016 |
0.6 |
0.4 |
|||
|
September
2016 |
0.5 |
0.2 |
|||
|
October 2016 |
0.5 |
0.0 |
|||
|
November 2016 |
0.6 |
0.1 |
|||
|
December 2016 |
0.5 |
0.1 |
|||
|
January 2017 |
0.6 |
0.1 |
|||
|
February 2017 |
0.3 |
0.2 |
|||
|
March 2017 |
0.4 |
0.8 |
|||
|
April 2017 |
0.4 |
1.1 |
|||
|
May 2017 |
0.4 |
1.1 |
|||
|
June 2017 |
0.4 |
0.9 |
|||
|
July 2017 |
0.5 |
0.7 |
|||
|
August 2017 |
0.7 |
0.4 |
|||
|
September
2017 |
0.6 |
0.2 |
|||
|
October 2017 |
0.5 |
0.1 |
|||
|
November 2017 |
0.6 |
0.2 |
|||
|
December 2017 |
0.6 |
0.2 |
|||
|
January 2018 |
0.6 |
0.1 |
|||
|
February 2018 |
0.5 |
0.4 |
|||
|
March 2018 |
0.4 |
0.8 |
|||
|
April 2018 |
0.4 |
1.0 |
|||
|
May 2018 |
0.3 |
0.9 |
|||
|
June 2018 |
0.4 |
0.8 |
|||
|
July 2018 |
0.2 |
0.4 |
|||
|
August 2018 |
0.4 |
0.2 |
|||
|
September
2018 |
0.3 |
0.0 |
|||
|
October 2018 |
0.4 |
0.0 |
|||
|
November 2018 |
0.2 |
-0.1 |
|||
|
December 2018 |
0.2 |
-0.2 |
|||
|
January 2019 |
0.2 |
-0.2 |
|||
|
February 2019 |
0.2 |
0.1 |
|||
|
March 2019 |
0.2 |
0.7 |
|||
|
April 2019 |
0.3 |
0.9 |
|||
|
May 2019 |
0.2 |
0.8 |
|||
|
June 2019 |
0.2 |
0.6 |
|||
|
July 2019 |
0.1 |
0.4 |
|||
|
August 2019 |
0.4 |
0.2 |
|||
|
September
2019 |
0.4 |
0.1 |
|||
|
October 2019 |
0.4 |
0.0 |
|||
|
November 2019 |
0.4 |
0.1 |
|||
|
December 2019 |
0.4 |
0.1 |
|||
|
January 2020 |
0.5 |
0.0 |
|||
|
February 2020 |
0.5 |
0.4 |
|||
|
March 2020 |
0.5 |
0.9 |
|||
|
April 2020 |
0.4 |
1.0 |
|||
|
May 2020 |
0.0 |
0.6 |
|||
|
June 2020 |
0.2 |
0.6 |
Table IIA-4 summarizes the brutal drops in
assets and net worth of US households and nonprofit organizations from 2007 to
2008 and 2009. Total assets fell $9.1 trillion or 10.7 percent from 2007 to
2008 and $8.1 trillion or 9.5 percent to 2009. Net worth fell $9.0 trillion
from 2007 to 2008 or 12.8 percent and $7.9 trillion to 2009 or 11.1 percent.
Subsidies to housing prolonged over decades together with interest rates at 1.0
percent from Jun 2003 to Jun 2004 inflated valuations of real estate and risk financial
assets such as equities. The increase of fed funds rates by 25 basis points
until 5.25 percent in Jun 2006 reversed carry trades through exotic vehicles
such as subprime adjustable rate mortgages (ARM) and world financial markets. Short-term zero interest rates encourage financing of
everything with short-dated funds, explaining the SIVs created off-balance
sheet to issue short-term commercial paper to purchase default-prone mortgages
that were financed in overnight or short-dated sale and repurchase agreements
(Pelaez and Pelaez, Financial Regulation after the Global Recession,
50-1, Regulation of Banks and Finance, 59-60, Globalization and the
State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government
Intervention in Globalization, 62-3, International Financial
Architecture, 144-9).
Table IIA-4,
Difference of Balance Sheet of Households and Nonprofit Organizations, Billions
of Dollars from 2007 to 2008 and 2009
|
|
2007 |
2008 |
Change to
2008 |
2009 |
Change to
2009 |
|
A |
85,146.2 |
76,021.1 |
-9,125.1 |
77,057.6 |
-8,088.6 |
|
Non |
30,542.4 |
27,983.3 |
-2,559.1 |
26,022.0 |
-4,520.4 |
|
RE |
25,745.7 |
23,063.6 |
-2,682.1 |
21,085.5 |
-4,660.2 |
|
FIN |
54,603.9 |
48,037.8 |
-6,566.1 |
51,035.6 |
-3,568.3 |
|
LIAB |
14,502.0 |
14,398.4 |
-103.6 |
14,276.0 |
-226.0 |
|
NW |
70,644.2 |
61,622.7 |
-9,021.5 |
62,781.6 |
-7,862.6 |
Source: Board
of Governors of the Federal Reserve System. 2020. Flow of funds, balance
sheets and integrated macroeconomic accounts: first quarter 2020.
Washington, DC, Federal Reserve System, Jun 11. https://www.federalreserve.gov/releases/z1/current/default.htm
The apparent improvement in Table IIA-4A is mostly because of
increases in valuations of risk financial assets by the carry trade from zero
interest rates to leveraged exposures in risk financial assets such as stocks,
high-yield bonds, emerging markets, commodities and so on. Zero interest rates
also act to increase net worth by reducing debt or liabilities. The net worth
of households has become an instrument of unconventional monetary policy by
zero interest rates in the theory that increases in net worth increase
consumption that accounts for 67.7 percent of GDP in IQ2020 (https://cmpassocregulationblog.blogspot.com/2020/06/mediocre-cyclical-united-states.html and earlier https://cmpassocregulationblog.blogspot.com/2020/05/mediocre-cyclical-united-states_31.html), generating
demand to increase aggregate economic activity and employment. There are
neglected and counterproductive risks in unconventional monetary policy. Between
2007 and IQ2020, real estate increased in value by $8204.6 billion and
financial assets increased $32,391.1 billion for net gain of real estate and
financial assets of $40,595.7 billion, explaining most of the increase in net
worth of $40,143.0 billion obtained by deducting the increase in liabilities of
$2131.8 billion from the increase of assets of $42,274.9 billion (with minor
rounding error). Net worth increased from $70,644.2 billion in IVQ2007 to
$110,787.2 billion in IQ2020 by $40,143.0 billion or 56.8 percent. The US
consumer price index for all items increased from 210.036 in Dec 2007 to
258.115 in Mar 2020 (https://www.bls.gov/cpi/data.htm) or 22.9
percent. Net worth adjusted by CPI inflation increased 27.6 percent from 2007
to IQ2020. Real estate assets adjusted for CPI inflation increased 7.3 percent
from 2007 to IQ2020. There are multiple complaints that unconventional monetary
policy concentrates income on wealthier individuals because of their holdings
of financial assets while the middle class has gained less because of fewer
holdings of financial assets and higher share of real estate in family wealth.
There is nothing new in these arguments. Interest rate ceilings on deposits and
loans have been commonly used. The Banking Act of 1933 imposed prohibition of
payment of interest on demand deposits and ceilings on interest rates on time
deposits. These measures were justified by arguments that the banking panic of
the 1930s was caused by competitive rates on bank deposits that led banks to
engage in high-risk loans (Friedman, 1970, 18; see Pelaez and Pelaez, Regulation
of Banks and Finance (2009b), 74-5). The objective of policy was to prevent
unsound loans in banks. Savings and loan institutions complained of unfair
competition from commercial banks that led to continuing controls with the
objective of directing savings toward residential construction. Friedman (1970,
15) argues that controls were passive during periods when rates implied on demand
deposit were zero or lower and when Regulation Q ceilings on time deposits were
above market rates on time deposits. The Great Inflation or stagflation of the
1960s and 1970s changed the relevance of Regulation Q. Friedman (1970, 26-7)
predicted the future:
“The banks have been forced into costly structural
readjustments, the European banking system has been given an unnecessary
competitive advantage, and London has been artificially strengthened as a
financial center at the expense of New York.”
In short, Depression regulation exported the US financial system
to London and offshore centers. What is vividly relevant currently from this
experience is the argument by Friedman (1970, 27) that the controls affected
the most people with lower incomes and wealth who were forced into accepting
controlled-rates on their savings that were lower than those that would be
obtained under freer markets. As Friedman (1970, 27) argues:
“These are the people who have the fewest
alternative ways to invest their limited assets and are least sophisticated
about the alternatives.” Long-term economic performance in the United States consisted
of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent
per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy
returned to trend growth after adverse events such as wars and recessions. The
key characteristic of adversities such as recessions was much higher rates of
growth in expansion periods that permitted the economy to recover output, income
and employment losses that occurred during the contractions. Over the business
cycle, the economy compensated the losses of contractions with higher growth in
expansions to maintain trend growth of GDP of 3 percent and of GDP per capita
of 2 percent. US economic growth has been at only 2.1 percent on average in the
cyclical expansion in the 43 quarters from IIIQ2009 to IQ2020 and in the global
recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event. Boskin (2010Sep) measures
that the US economy grew at 6.2 percent in the first four quarters and 4.5
percent in the first 12 quarters after the trough in the second quarter of
1975; and at 7.7 percent in the first four quarters and 5.8 percent in the
first 12 quarters after the trough in the first quarter of 1983 (Professor
Michael J. Boskin, Summer of Discontent, Wall
Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are
new calculations using the revision of US GDP and personal income data since 1929
by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the
third estimate of GDP for IQ2020 (https://www.bea.gov/sites/default/files/2020-06/gdp1q20_3rd.pdf). The
average of 7.7 percent in the first four quarters of major cyclical expansions
is in contrast with the rate of growth in the first four quarters of the
expansion from IIIQ2009 to IIQ2010 of only 2.8 percent obtained by dividing GDP
of $15,557.3 billion in IIQ2010 by GDP of $15,134.1 billion in IIQ2009
{[($15,557.3/$15,134.1) -1]100 = 2.8%], or accumulating the quarter on quarter
growth rates (https://cmpassocregulationblog.blogspot.com/2020/06/mediocre-cyclical-united-states.html and earlier https://cmpassocregulationblog.blogspot.com/2020/05/mediocre-cyclical-united-states_31.html). The
expansion from IQ1983 to IQ1986 was at the average annual growth rate of 5.7 percent, 5.3 percent from
IQ1983 to IIIQ1986, 5.1 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983
to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to
IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to
IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to
IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989,
4.6 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5
percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent
from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from
IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983
to IIIQ1991, 3.7 percent from IQ1983 to IVQ1991, 3.7 percent from IQ1983 to
IQ1992, 3.7 percent from IQ1983 to IIQ1992, 3.7 percent from IQ1983 to
IIIQ2019, 3.8 percent from IQ1983 to IVQ1992, 3.7 percent from IQ1983 to
IQ1993, 3.6 percent from IQ1983 to IIQ1993, 3.6 percent from IQ1983 to IIIQ1993
and at 7.9 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2020/06/mediocre-cyclical-united-states.html and earlier https://cmpassocregulationblog.blogspot.com/2020/05/mediocre-cyclical-united-states_31.html). The
National Bureau of Economic Research (NBER) dates a contraction of the US from
IQ1990 (Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The
expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP
contracted 1.3 percent from the pre-recession peak of $8983.9 billion of
chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). The US
maintained growth at 3.0 percent on average over entire cycles with expansions
at higher rates compensating for contractions. Growth at trend in the entire
cycle from IVQ2007 to IQ2020 and in the global recession with output in the US
reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event would have accumulated to
43.6 percent. GDP in IQ2020 would be $22,634.2 billion (in constant dollars of
2012) if the US had grown at trend, which is higher by $3656.8 billion than
actual $18,977.4 billion. There are more than three trillion dollars of GDP
less than at trend, explaining the 41.3 million unemployed or underemployed
equivalent to actual unemployment/underemployment of 23.9 percent of the
effective labor force with the largest part originating in the global recession
with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19 event (https://cmpassocregulationblog.blogspot.com/2020/07/increase-of-total-nonfarm-payroll-jobs.html and earlier https://cmpassocregulationblog.blogspot.com/2020/06/creation-of-three-million-private.html). Unemployment is decreasing while employment is increasing in
initial adjustment of the lockdown of economic activity in the global recession
resulting from the COVID-19 event (https://www.bls.gov/cps/employment-situation-covid19-faq-june-2020.pdf). US GDP in IQ2020 is 16.2 percent lower than at trend. US GDP
grew from $15,762.0 billion in IVQ2007 in constant dollars to $18,977.4
billion in IQ2020 or 20.4 percent at the average annual equivalent rate of 1.5
percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10
percent below trend. Cochrane (2016May02) measures GDP growth in the US at
average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per
year from 2000 to 2015 with only at 2.0 percent annual equivalent in the
current expansion. Cochrane (2016May02) proposes drastic changes in regulation
and legal obstacles to private economic activity. The US missed the opportunity
to grow at higher rates during the expansion and it is difficult to catch up
because growth rates in the final periods of expansions tend to decline. The US
missed the opportunity for recovery of output and employment always afforded in
the first four quarters of expansion from recessions. Zero interest rates and
quantitative easing were not required or present in successful cyclical expansions
and in secular economic growth at 3.0 percent per year and 2.0 percent per
capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of
secular stagnation. There is similar
behavior in manufacturing. There is classic research on analyzing deviations of
output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975,
Sargent and Sims 1977). The long-term trend is growth of manufacturing at
average 2.9 percent per year from Jun 1919 to Jun 2020. Growth at 2.9 percent
per year would raise the NSA index of manufacturing output (SIC, Standard
Industrial Classification) from 108.2987 in Dec 2007 to 154.8159 in Jun 2020.
The actual index NSA in Jun 2020 is 95.097 which is 38.6 percent below trend.
The underperformance of manufacturing in Jun 2020 originates partly in the
earlier global recession augmented by the current global recession with output
in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the
lockdown of economic activity in the COVID-19. Manufacturing grew at the
average annual rate of 3.3 percent between Dec 1986 and Dec 2006. Growth at 3.3
percent per year would raise the NSA index of manufacturing output (SIC,
Standard Industrial Classification) from 108.2987 in Dec 2007 to 162.5089 in
Jun 2020. The actual index NSA in Jun 2020 is 95.0970, which is 41.5 percent
below trend. Manufacturing output grew at average 1.6 percent between Dec 1986
and Jun 2020. Using trend growth of 1.6 percent per year, the index would
increase to 132.0671 in Jun 2020. The output of manufacturing at 95.0970 in Jun
2020 is 28.0 percent below trend under this alternative calculation. Using the NAICS (North American Industry Classification
System), manufacturing output fell from the high of 110.5147 in Jun 2007 to the
low of 86.3800 in Apr 2009 or 21.8 percent. The NAICS manufacturing index
increased from 86.3800 in Apr 2009 to 96.1857 in Jun 2020 or 11.4 percent. The
NAICS manufacturing index increased at the annual equivalent rate of 3.5
percent from Dec 1986 to Dec 2006. Growth at 3.5 percent would increase the
NAICS manufacturing output index from 106.6777 in Dec 2007 to 163.9940 in Jun
2020. The NAICS index at 96.1857 in Jun 2020 is 41.3 below trend. The NAICS
manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999
to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output
index from 106.6777 in Dec 2007 to 131.6999 in Jun 2020. The NAICS index at
96.1857 in Jun 2020 is 27.0 percent below trend under this alternative
calculation.
Table IIA-4A,
US, Difference of Balance Sheet of Households and Nonprofit Organizations
Billions of Dollars from 2007 to 2018, 2019 and IQ2020
|
Value 2007 |
Change to 2018 |
Change to
2019 |
Change to
IQ2020 |
|
|
Assets |
85,146.2 |
36,606.7 |
48,738.6 |
42,274.9 |
|
Nonfinancial |
30,542.4 |
7,320.2 |
9,399.9 |
9,883.7 |
|
Real Estate |
25,745.7 |
5,961.8 |
7,771.3 |
8,204.6 |
|
Financial |
54,603.9 |
29,286.4 |
39,338.5 |
32,391.1 |
|
Liabilities |
14,502.0 |
1,523.5 |
2,047.4 |
2,131.8 |
|
Net Worth |
70,644.2 |
35,083.2 |
46,691.2 |
40,143.0 |
Notes: Deposits: Total Time and Savings Deposits FL15303005;
Net Worth = Assets – Liabilities
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