Increasing Valuations of Risk Financial Assets, Real Disposable Income and Consumption Expenditures, Prices of Personal Consumption Expenditures, Cyclically Stagnating Real Disposable Income Per Capita, Financial Repression, Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, World Cyclical Slow Growth, Government Intervention in Globalization, and Global Recession Risk
Carlos M. Pelaez
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020
II Stagnating Real Disposable Income and Consumption Expenditures
IIB1 Stagnating Real Disposable Income and Consumption Expenditures
IB2 Financial Repression
IIB Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide
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
IIA Destruction of Household Nonfinancial Wealth with Stagnating Total Real Wealth. The valuable report on Financial Accounts of the United States formerly Flow of Funds Accounts of the United States provided by the Board of Governors of the Federal Reserve System (https://www.federalreserve.gov/releases/z1/default.htm https://www.federalreserve.gov/apps/fof/) is rich in important information and analysis. Table IIA-1, updated in this blog for every new quarterly release, shows the balance sheet of US households combined with nonprofit organizations in 2007, 2017, 2018 and IIIQ2019. Assets increased to $121.0 trillion in 2017 by $35.9 trillion relative to 2007 or 42.2 percent. Assets increased to $122.2 billion in 2018 by $37.1 trillion relative to 2007 or 43.7 percent. Assets increased to 130.2 billion in IIIQ2019 by $45.1 billion or 53.0 percent. Liabilities increased from $14.5 trillion in 2007 to $15.5 trillion in 2017, by $1042.1 billion or increase of 7.2 percent. Liabilities increased $1527.0 billion or 10.5 percent from 2007 to 2018. Liabilities increased $1881.7 billion or 13.0 percent from 2007 to IIIQ2019. Net worth increased from $70,597.0 billion in 2007 to $113,832.4 billion in 1IIQ2019 by $43,235.4 billion or 61.2 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 256.759 in Sep 2019 (http://www.bls.gov/cpi/data.htm) or 22.2 percent. Net worth adjusted by CPI inflation increased 31.9 percent from 2007 to IIIQ2019. Nonfinancial assets increased $8,699.7 billion from $30,543.9 billion in 2007 to $39,243.6 billion in IIIQ2019 or 28.5 percent. There was increase from 2007 to IIIQ2019 of $7,114.8 billion in real estate assets or by 27.6 percent. Real estate assets adjusted for CPI inflation increased 4.4 percent between 2007 and IIIQ2019. 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 | 2017 | 2018 | IIIQ2019 | |
Assets | 85,101.2 | 121,010.7 | 122,249.5 | 130,218.2 |
Nonfinancial | 30,543.9 | 35,973.7 | 37,866.3 | 39,243.6 |
Real Estate | 25,747.2 | 30,069.0 | 31,711.2 | 32,862.0 |
Durable Goods | 4,473.9 | 5,302.6 | 5,519.3 | 5,717.4 |
Financial | 54,557.3 | 85,037.0 | 84,383.2 | 90,974.6 |
Deposits | 5,918.2 | 9,263.7 | 9,673.4 | 10,019.3 |
Debt Secs. | 3,556.3 | 4,580.4 | 5,223.0 | 5,499.4 |
Mutual Fund Shares | 4,520.4 | 8,632.2 | 7,942.4 | 9,068.1 |
Equities Corporate | 9664.2 | 17,462.9 | 15,590.6 | 18,042.3 |
Equity Noncorporate | 8,930.1 | 12,187.8 | 12,724.2 | 13,519.2 |
Pension | 16,401.5 | 25,919.1 | 25,904.2 | 27,322.7 |
Liabilities | 14,504.1 | 15,546.2 | 16,031.1 | 16,385.8 |
Home Mortgages | 10,625.9 | 10,050.6 | 10,321.0 | 10,517.4 |
Consumer Credit | 2,609.5 | 3828.3 | 4009.7 | 4,129.5 |
Net Worth | 70,597.0 | 105,464.5 | 106,218.4 | 113,832.4 |
Notes: Deposits: Total Time and Savings Deposits FL15303005; Net Worth = Assets – Liabilities
Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. https://www.federalreserve.gov/releases/z1/current/default.htm
The explanation of the sharp contraction of household wealth can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:
“On the maturity date T, the firm must either pay the promised payment of B to the debtholders or else the current equity will be valueless. Clearly, if at time T, V(T) > B, the firm should pay the bondholders because the value of equity will be V(T) – B > 0 whereas if they do not, the value of equity would be zero. If V(T) ≤ B, then the firm will not make the payment and default the firm to the bondholders because otherwise the equity holders would have to pay in additional money and the (formal) value of equity prior to such payments would be (V(T)- B) < 0.”
Pelaez and Pelaez (The Global Recession Risk (2007), 208-9) apply this analysis to the US housing market in 2005-2006 concluding:
“The house market [in 2006] is probably operating with low historical levels of individual equity. There is an application of structural models [Duffie and Singleton 2003] to the individual decisions on whether or not to continue paying a mortgage. The costs of sale would include realtor and legal fees. There could be a point where the expected net sale value of the real estate may be just lower than the value of the mortgage. At that point, there would be an incentive to default. The default vulnerability of securitization is unknown.”
There are multiple important determinants of the interest rate: “aggregate wealth, the distribution of wealth among investors, expected rate of return on physical investment, taxes, government policy and inflation” (Ingersoll 1987, 405). Aggregate wealth is a major driver of interest rates (Ibid, 406). Unconventional monetary policy, with zero fed funds rates and flattening of long-term yields by quantitative easing, causes uncontrollable effects on risk taking that can have profound undesirable effects on financial stability. Excessively aggressive and exotic monetary policy is the main culprit and not the inadequacy of financial management and risk controls.
The net worth of the economy depends on interest rates. In theory, “income is generally defined as the amount a consumer unit could consume (or believe that it could) while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is a flow that is obtained by applying a rate of return, r, to a stock of wealth, W, or Y = rW (Ibid). According to a subsequent restatement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption decisions is the long-run expected yield from wealth r*W. This yield was named permanent income: Y* = r*W” (Darby 1974, 229), where * denotes permanent. The simplified relation of income and wealth can be restated as:
W = Y/r (1)
Equation (1) shows that as r goes to zero, r →0, W grows without bound, W→∞.
Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment but the exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at close to zero interest rates, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).
The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4).
There are significant elements of the theory of bank financial fragility of Diamond and Dybvig (1983) and Diamond and Rajan (2000, 2001a, 2001b) that help to explain the financial fragility of banks during the credit/dollar crisis (see also Diamond 2007). The theory of Diamond and Dybvig (1983) as exposed by Diamond (2007) is that banks funding with demand deposits have a mismatch of liquidity (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 58-66). A run occurs when too many depositors attempt to withdraw cash at the same time. All that is needed is an expectation of failure of the bank. Three important functions of banks are providing evaluation, monitoring and liquidity transformation. Banks invest in human capital to evaluate projects of borrowers in deciding if they merit credit. The evaluation function reduces adverse selection or financing projects with low present value. Banks also provide important monitoring services of following the implementation of projects, avoiding moral hazard that funds be used for, say, real estate speculation instead of the original project of factory construction. The transformation function of banks involves both assets and liabilities of bank balance sheets. Banks convert an illiquid asset or loan for a project with cash flows in the distant future into a liquid liability in the form of demand deposits that can be withdrawn immediately.
In the theory of banking of Diamond and Rajan (2000, 2001a, 2001b), the bank creates liquidity by tying human assets to capital. The collection skills of the relationship banker convert an illiquid project of an entrepreneur into liquid demand deposits that are immediately available for withdrawal. The deposit/capital structure is fragile because of the threat of bank runs. In these days of online banking, the run on Washington Mutual was through withdrawals online. A bank run can be triggered by the decline of the value of bank assets below the value of demand deposits.
Pelaez and Pelaez (Regulation of Banks and Finance 2009b, 60, 64-5) find immediate application of the theories of banking of Diamond, Dybvig and Rajan to the credit/dollar crisis after 2007. It is a credit crisis because the main issue was the deterioration of the credit portfolios of securitized banks as a result of default of subprime mortgages. It is a dollar crisis because of the weakening dollar resulting from relatively low interest rate policies of the US. It caused systemic effects that converted into a global recession not only because of the huge weight of the US economy in the world economy but also because the credit crisis transferred to the UK and Europe. Management skills or human capital of banks are illustrated by the financial engineering of complex products. The increasing importance of human relative to inanimate capital (Rajan and Zingales 2000) is revolutionizing the theory of the firm (Zingales 2000) and corporate governance (Rajan and Zingales 2001). Finance is one of the most important examples of this transformation. Profits were derived from the charter in the original banking institution. Pricing and structuring financial instruments was revolutionized with option pricing formulas developed by Black and Scholes (1973) and Merton (1973, 1974, 1998) that permitted the development of complex products with fair pricing. The successful financial company must attract and retain finance professionals who have invested in human capital, which is a sunk cost to them and not of the institution where they work.
The complex financial products created for securitized banking with high investments in human capital are based on houses, which are as illiquid as the projects of entrepreneurs in the theory of banking. The liquidity fragility of the securitized bank is equivalent to that of the commercial bank in the theory of banking (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65). Banks created off-balance sheet structured investment vehicles (SIV) that issued commercial paper receiving AAA rating because of letters of liquidity guarantee by the banks. The commercial paper was converted into liquidity by its use as collateral in SRPs at the lowest rates and minimal haircuts because of the AAA rating of the guarantor bank. In the theory of banking, default can be triggered when the value of assets is perceived as lower than the value of the deposits. Commercial paper issued by SIVs, securitized mortgages and derivatives all obtained SRP liquidity on the basis of illiquid home mortgage loans at the bottom of the pyramid. The run on the securitized bank had a clear origin (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65):
“The increasing default of mortgages resulted in an increase in counterparty risk. Banks were hit by the liquidity demands of their counterparties. The liquidity shock extended to many segments of the financial markets—interbank loans, asset-backed commercial paper (ABCP), high-yield bonds and many others—when counterparties preferred lower returns of highly liquid safe havens, such as Treasury securities, than the risk of having to sell the collateral in SRPs at deep discounts or holding an illiquid asset. The price of an illiquid asset is near zero.”
Gorton and Metrick (2010H, 507) provide a revealing quote to the work in 1908 of Edwin R. A. Seligman, professor of political economy at Columbia University, founding member of the American Economic Association and one of its presidents and successful advocate of progressive income taxation. The intention of the quote is to bring forth the important argument that financial crises are explained in terms of “confidence” but as Professor Seligman states in reference to historical banking crises in the US, the important task is to explain what caused the lack of confidence. It is instructive to repeat the more extended quote of Seligman (1908, xi) on the explanations of banking crises:
“The current explanations may be divided into two categories. Of these the first includes what might be termed the superficial theories. Thus it is commonly stated that the outbreak of a crisis is due to lack of confidence,--as if the lack of confidence was not in itself the very thing which needs to be explained. Of still slighter value is the attempt to associate a crisis with some particular governmental policy, or with some action of a country’s executive. Such puerile interpretations have commonly been confined to countries like the United States, where the political passions of democracy have had the fullest way. Thus the crisis of 1893 was ascribed by the Republicans to the impending Democratic tariff of 1894; and the crisis of 1907 has by some been termed the ‘[Theodore] Roosevelt panic,” utterly oblivious of the fact that from the time of President Jackson, who was held responsible for the troubles of 1837, every successive crisis had had its presidential scapegoat, and has been followed by a political revulsion. Opposed to these popular, but wholly unfounded interpretations, is the second class of explanations, which seek to burrow beneath the surface and to discover the more occult and fundamental causes of the periodicity of crises.”
Scholars ignore superficial explanations in the effort to seek good and truth. The problem of economic analysis of the credit/dollar crisis is the lack of a structural model with which to attempt empirical determination of causes (Gorton and Metrick 2010SB). There would still be doubts even with a well-specified structural model because samples of economic events do not typically permit separating causes and effects. There is also confusion is separating the why of the crisis and how it started and propagated, all of which are extremely important.
In true heritage of the principles of Seligman (1908), Gorton (2009EFM) discovers a prime causal driver of the credit/dollar crisis. The objective of subprime and Alt-A mortgages was to facilitate loans to populations with modest means so that they could acquire a home. These borrowers would not receive credit because of (1) lack of funds for down payments; (2) low credit rating and information; (3) lack of information on income; and (4) errors or lack of other information. Subprime mortgage “engineering” was based on the belief that both lender and borrower could benefit from increases in house prices over the short run. The initial mortgage would be refinanced in two or three years depending on the increase of the price of the house. According to Gorton (2009EFM, 13, 16):
“The outstanding amounts of Subprime and Alt-A [mortgages] combined amounted to about one quarter of the $6 trillion mortgage market in 2004-2007Q1. Over the period 2000-2007, the outstanding amount of agency mortgages doubled, but subprime grew 800%! Issuance in 2005 and 2006 of Subprime and Alt-A mortgages was almost 30% of the mortgage market. Since 2000 the Subprime and Alt-A segments of the market grew at the expense of the Agency (i.e., the government sponsored entities of Fannie Mae and Freddie Mac) share, which fell from almost 80% (by outstanding or issuance) to about half by issuance and 67% by outstanding amount. The lender’s option to rollover the mortgage after an initial period is implicit in the subprime mortgage. The key design features of a subprime mortgage are: (1) it is short term, making refinancing important; (2) there is a step-up mortgage rate that applies at the end of the first period, creating a strong incentive to refinance; and (3) there is a prepayment penalty, creating an incentive not to refinance early.”
The prime objective of successive administrations in the US during the past 20 years and actually since the times of Roosevelt in the 1930s has been to provide “affordable” financing for the “American dream” of home ownership. The US housing finance system is mixed with public, public/private and purely private entities. The Federal Home Loan Bank (FHLB) system was established by Congress in 1932 that also created the Federal Housing Administration in 1934 with the objective of insuring homes against default. In 1938, the government created the Federal National Mortgage Association, or Fannie Mae, to foster a market for FHA-insured mortgages. Government-insured mortgages were transferred from Fannie Mae to the Government National Mortgage Association, or Ginnie Mae, to permit Fannie Mae to become a publicly-owned company. Securitization of mortgages began in 1970 with the government charter to the Federal Home Loan Mortgage Corporation, or Freddie Mac, with the objective of bundling mortgages created by thrift institutions that would be marketed as bonds with guarantees by Freddie Mac (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 42-8). In the third quarter of 2008, total mortgages in the US were $12,057 billion of which 43.5 percent, or $5423 billion, were retained or guaranteed by Fannie Mae and Freddie Mac (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 45). In 1990, Fannie Mae and Freddie Mac had a share of only 25.4 percent of total mortgages in the US. Mortgages in the US increased from $6922 billion in 2002 to $12,088 billion in 2007, or by 74.6 percent, while the retained or guaranteed portfolio of Fannie and Freddie rose from $3180 billion in 2002 to $4934 billion in 2007, or by 55.2 percent.
According to Pinto (2008) in testimony to Congress:
“There are approximately 25 million subprime and Alt-A loans outstanding, with an unpaid principal amount of over $4.5 trillion, about half of them held or guaranteed by Fannie and Freddie. Their high risk activities were allowed to operate at 75:1 leverage ratio. While they may deny it, there can be no doubt that Fannie and Freddie now own or guarantee $1.6 trillion in subprime, Alt-A and other default prone loans and securities. This comprises over 1/3 of their risk portfolios and amounts to 34% of all the subprime loans and 60% of all Alt-A loans outstanding. These 10.5 million unsustainable, nonprime loans are experiencing a default rate 8 times the level of the GSEs’ 20 million traditional quality loans. The GSEs will be responsible for a large percentage of an estimated 8.8 million foreclosures expected over the next 4 years, accounting for the failure of about 1 in 6 home mortgages. Fannie and Freddie have subprimed America.”
In perceptive analysis of growth and macroeconomics in the past six decades, Rajan (2012FA) argues that “the West can’t borrow and spend its way to recovery.” The Keynesian paradigm is not applicable in current conditions. Advanced economies in the West could be divided into those that reformed regulatory structures to encourage productivity and others that retained older structures. In the period from 1950 to 2000, Cobet and Wilson (2002) find that US productivity, measured as output/hour, grew at the average yearly rate of 2.9 percent while Japan grew at 6.3 percent and Germany at 4.7 percent (see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). In the period from 1995 to 2000, output/hour grew at the average yearly rate of 4.6 percent in the US but at lower rates of 3.9 percent in Japan and 2.6 percent in the US. Rajan (2012FA) argues that the differential in productivity growth was accomplished by deregulation in the US at the end of the 1970s and during the 1980s. In contrast, Europe did not engage in reform with the exception of Germany in the early 2000s that empowered the German economy with significant productivity advantage. At the same time, technology and globalization increased relative remunerations in highly-skilled, educated workers relative to those without skills for the new economy. It was then politically appealing to improve the fortunes of those left behind by the technological revolution by means of increasing cheap credit. As Rajan (2012FA) argues:
“In 1992, Congress passed the Federal Housing Enterprises Financial Safety and Soundness Act, partly to gain more control over Fannie Mae and Freddie Mac, the giant private mortgage agencies, and partly to promote affordable homeownership for low-income groups. Such policies helped money flow to lower-middle-class households and raised their spending—so much so that consumption inequality rose much less than income inequality in the years before the crisis. These policies were also politically popular. Unlike when it came to an expansion in government welfare transfers, few groups opposed expanding credit to the lower-middle class—not the politicians who wanted more growth and happy constituents, not the bankers and brokers who profited from the mortgage fees, not the borrowers who could now buy their dream houses with virtually no money down, and not the laissez-faire bank regulators who thought they could pick up the pieces if the housing market collapsed. The Federal Reserve abetted these shortsighted policies. In 2001, in response to the dot-com bust, the Fed cut short-term interest rates to the bone. Even though the overstretched corporations that were meant to be stimulated were not interested in investing, artificially low interest rates acted as a tremendous subsidy to the parts of the economy that relied on debt, such as housing and finance. This led to an expansion in housing construction (and related services, such as real estate brokerage and mortgage lending), which created jobs, especially for the unskilled. Progressive economists applauded this process, arguing that the housing boom would lift the economy out of the doldrums. But the Fed-supported bubble proved unsustainable. Many construction workers have lost their jobs and are now in deeper trouble than before, having also borrowed to buy unaffordable houses. Bankers obviously deserve a large share of the blame for the crisis. Some of the financial sector’s activities were clearly predatory, if not outright criminal. But the role that the politically induced expansion of credit played cannot be ignored; it is the main reason the usual checks and balances on financial risk taking broke down.”
In fact, Raghuram G. Rajan (2005) anticipated low liquidity in financial markets resulting from low interest rates before the financial crisis that caused distortions of risk/return decisions provoking the credit/dollar crisis and global recession from IVQ2007 to IIQ2009. Near zero interest rates of unconventional monetary policy induced excessive risks and low liquidity in financial decisions that were critical as a cause of the credit/dollar crisis after 2007. Rajan (2012FA) argues that it is not feasible to return to the employment and income levels before the credit/dollar crisis because of the bloated construction sector, financial system and government budgets.
Table IIA-2 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 65.9 percent in the US national home price index between Oct 2000 and Oct 2005. Prices rose 70.9 percent in the US national index from Oct 2000 to Oct 2006. House prices rose 29.5 percent between Oct 2003 and Oct 2005 for the US national propelled by low fed funds rates of 1.0 percent between Jul 2003 and Jul 2004. Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Jun 2004 until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decline of yields of mortgage-backed securities with intended decrease in mortgage rates. Similarly, between Oct 2003 and Oct 2006 the US national increased 33.4 percent. House prices have increased from Oct 2006 to Oct 2019 by 15.4 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Oct 2019, house prices increased 3.3 percent in the US national. Table IIA-1 also shows that house prices increased 97.2 percent between Oct 2000 and Oct 2019 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 15.1 percent in Oct 2019 from the peak in Jun 2006 and increased 15.1 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 annual growth rate between Dec 1987 and Dec 2018 is 3.6 percent for the US national. The average rate for the US national was 3.6 percent from Dec 1987 to Dec 2018 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 2018 was 3.6 percent for the US national.
Table IIA-2, US, Percentage Changes of Standard & Poor’s Case-Shiller National Home Price Indices, Not Seasonally Adjusted, ∆%
US National | |
∆% Oct 2000 to Oct 2003 | 28.1 |
∆% Oct 2000 to Oct 2005 | 65.9 |
∆% Oct 2003 to Oct 2005 | 29.5 |
∆% Oct 2000 to Oct 2006 | 70.9 |
∆% Oct 2003 to Oct 2006 | 33.4 |
∆% Oct 2005 to Oct 2019 | 18.8 |
∆% Oct 2006 to Oct 2019 | 15.4 |
∆% Oct 2009 to Oct 2019 | 43.0 |
∆% Oct 2010 to Oct 2019 | 48.4 |
∆% Oct 2011 to Oct 2019 | 53.5 |
∆% Oct 2012 to Oct 2019 | 47.6 |
∆% Oct 2013 to Oct 2019 | 33.1 |
∆% Oct 2014 to Oct 2019 | 27.3 |
∆% Oct 2015 to Oct 2019 | 21.3 |
∆% Oct 2016 to Oct 2019 | 15.4 |
∆% Oct 2017 to Oct 2019 | 8.8 |
∆% Oct 2018 to Oct 2019 | 3.3 |
∆% Oct 2000 to Oct 2019 | 97.2 |
∆% Peak Jun 2006 to Oct 2019 | 15.1 |
∆% Peak Jul 2006 to Oct 2019 | 15.1 |
Average ∆% Dec 1987-Dec 2018 | 3.6 |
Average ∆% Dec 1987-Dec 2000 | 3.6 |
Average ∆% Dec 1992-Dec 2000 | 4.5 |
Average ∆% Dec 2000-Dec 2018 | 3.6 |
Source: https://us.spindices.com/index-family/real-estate/sp-corelogic-case-shiller
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 0.5 percent in Oct 2019 and the NSA index increased 0.1 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.
Table IIA-3, US, Monthly Percentage Change of S&P Corelogic Case-Shiller National Home Price Indices, Seasonally Adjusted and Not Seasonally Adjusted, ∆%
December 2010 | -0.1 | -0.8 | |||||
January 2011 | -0.4 | -1.1 | |||||
February 2011 | -0.8 | -0.9 | |||||
March 2011 | -0.3 | 0.0 | |||||
April 2011 | 0.0 | 1.0 | |||||
May 2011 | -0.1 | 1.1 | |||||
June 2011 | 0.0 | 0.9 | |||||
July 2011 | -0.1 | 0.3 | |||||
August 2011 | -0.3 | -0.4 | |||||
September 2011 | -0.5 | -1.1 | |||||
October 2011 | -0.5 | -1.3 | |||||
November 2011 | -0.6 | -1.3 | |||||
December 2011 | -0.3 | -1.1 | |||||
January 2012 | 0.0 | -0.7 | |||||
February 2012 | -0.1 | -0.1 | |||||
March 2012 | 1.0 | 1.4 | |||||
April 2012 | 0.9 | 1.9 | |||||
May 2012 | 0.7 | 1.9 | |||||
June 2012 | 0.6 | 1.5 | |||||
July 2012 | 0.5 | 0.8 | |||||
August 2012 | 0.4 | 0.3 | |||||
September 2012 | 0.4 | -0.2 | |||||
October 2012 | 0.5 | -0.3 | |||||
November 2012 | 0.7 | 0.0 | |||||
December 2012 | 0.6 | -0.1 | |||||
January 2013 | 0.9 | 0.3 | |||||
February 2013 | 0.6 | 0.6 | |||||
March 2013 | 1.5 | 1.9 | |||||
April 2013 | 1.0 | 2.0 | |||||
May 2013 | 0.9 | 1.9 | |||||
June 2013 | 0.9 | 1.7 | |||||
July 2013 | 0.9 | 1.2 | |||||
August 2013 | 0.9 | 0.7 | |||||
September 2013 | 0.8 | 0.2 | |||||
October 2013 | 0.6 | -0.1 | |||||
November 2013 | 0.5 | -0.1 | |||||
December 2013 | 0.6 | -0.1 | |||||
January 2014 | 0.6 | 0.1 | |||||
February 2014 | 0.4 | 0.3 | |||||
March 2014 | 0.3 | 0.8 | |||||
April 2014 | 0.2 | 1.1 | |||||
May 2014 | 0.2 | 1.1 | |||||
June 2014 | 0.2 | 0.9 | |||||
July 2014 | 0.3 | 0.6 | |||||
August 2014 | 0.4 | 0.2 | |||||
September 2014 | 0.4 | -0.1 | |||||
October 2014 | 0.4 | -0.2 | |||||
November 2014 | 0.4 | -0.1 | |||||
December 2014 | 0.4 | -0.1 | |||||
January 2015 | 0.4 | -0.1 | |||||
February 2015 | 0.3 | 0.2 | |||||
March 2015 | 0.4 | 0.9 | |||||
April 2015 | 0.3 | 1.1 | |||||
May 2015 | 0.3 | 1.1 | |||||
June 2015 | 0.3 | 0.9 | |||||
July 2015 | 0.4 | 0.6 | |||||
August 2015 | 0.5 | 0.3 | |||||
September 2015 | 0.5 | 0.1 | |||||
October 2015 | 0.6 | 0.0 | |||||
November 2015 | 0.6 | 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 | 0.3 | 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 | 0.3 | 0.8 | |||||
July 2018 | 0.3 | 0.5 | |||||
August 2018 | 0.4 | 0.2 | |||||
September 2018 | 0.3 | 0.0 | |||||
October 2018 | 0.4 | 0.0 | |||||
November 2018 | 0.3 | -0.1 | |||||
December 2018 | 0.2 | -0.2 | |||||
January 2019 | 0.2 | -0.2 | |||||
February 2019 | 0.2 | 0.1 | |||||
March 2019 | 0.3 | 0.7 | |||||
April 2019 | 0.3 | 0.9 | |||||
May 2019 | 0.2 | 0.8 | |||||
June 2019 | 0.1 | 0.6 | |||||
July 2019 | 0.2 | 0.4 | |||||
August 2019 | 0.4 | 0.2 | |||||
September 2019 | 0.4 | 0.1 | |||||
October 2019 | 0.5 | 0.1 |
Source: https://us.spindices.com/index-family/real-estate/sp-corelogic-case-shiller
Table IIA-4 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2008 and 2009. Total assets fell $9.1 trillion or 10.7 percent from 2007 to 2008 and $8.0 trillion or 9.4 percent to 2009. Net worth fell $9.0 trillion from 2007 to 2008 or 12.8 percent and $7.8 trillion to 2009 or 11.0 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 | 85,101.2 | 75,962.3 | -9,138.9 | 77,115.0 | -7,986.2 |
Non | 30,543.9 | 27,983.3 | -2,560.6 | 26,018.9 | -4,525.0 |
RE | 25,747.2 | 23,063.7 | -2,683.5 | 21,082.3 | -4,664.9 |
FIN | 54,557.3 | 47,979.0 | -6,578.3 | 51,096.1 | -3,461.2 |
LIAB | 14,504.1 | 14,400.6 | -103.5 | 14,278.6 | -225.5 |
NW | 70,597.0 | 61,561.7 | -9,035.3 | 62,836.3 | -7,760.7 |
A: Assets; Non FIN: Nonfinancial Assets; RE: Real Estate; FIN: Financial Assets; LIAB: Liabilities; NW: Net Worth
Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. 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 68.1 percent of GDP in IIIQ2019 (https://cmpassocregulationblog.blogspot.com/2020/01/fluctuating-valuations-of-risk.html and earlier https://cmpassocregulationblog.blogspot.com/2019/11/fluctuating-valuations-of-risk.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IIIQ2019, real estate increased in value by $7114.8 billion and financial assets increased $36,417.3 billion for net gain of real estate and financial assets of $43,532.1 billion, explaining most of the increase in net worth of $43,235.4 billion obtained by deducting the increase in liabilities of $1881.7 billion from the increase of assets of $45,117.0 billion (with minor rounding error). Net worth increased from $70,597.0 billion in IVQ2007 to $113,832.4 billion in IIIQ2019 by $43,235.4 billion or 61.2 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 256.759 in Sep 2019 (http://www.bls.gov/cpi/data.htm) or 22.2 percent. Net worth adjusted by CPI inflation increased 31.9 percent from 2007 to IIIQ2019. Real estate assets adjusted for CPI inflation increased 4.4 percent from 2007 to IIIIQ2019. 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 2.3 percent on average in the cyclical expansion in the 41 quarters from IIIQ2009 to IIIQ2019. 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 IIIQ2019 (https://www.bea.gov/system/files/2019-12/gdp3q19_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/2020/01/fluctuating-valuations-of-risk.html and earlier https://cmpassocregulationblog.blogspot.com/2019/11/fluctuating-valuations-of-risk.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 and at 7.9 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2020/01/fluctuating-valuations-of-risk.html and earlier https://cmpassocregulationblog.blogspot.com/2019/11/fluctuating-valuations-of-risk.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 IIIQ2019 would have accumulated to 41.5 percent. GDP in IIIQ2019 would be $22,303.2 billion (in constant dollars of 2012) if the US had grown at trend, which is higher by $3182.1 billion than actual $19,121.1 billion. There are more than three trillion dollars of GDP less than at trend, explaining the 18.5 million unemployed or underemployed equivalent to actual unemployment/underemployment of 10.8 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2019/12/increase-in-valuations-of-risk.html and earlier https://cmpassocregulationblog.blogspot.com/2019/11/increasing-valuations-of-risk-financial.html). US GDP in IIIQ2019 is 14.3 percent lower than at trend. US GDP grew from $15,762.0 billion in IVQ2007 in constant dollars to $19,121.1 billion in IIIQ2019 or 21.3 percent at the average annual equivalent rate of 1.7 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 3.0 percent per year from Nov 1919 to Nov 2019. Growth at 3.0 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 154.0282 in Nov 2019. The actual index NSA in Nov 2019 is 104.7173 which is 32.0 percent below trend. 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 159.4601 in Nov 2019. The actual index NSA in Nov 2019 is 104.7173, which is 34.3 percent below trend. Manufacturing output grew at average 1.9 percent between Dec 1986 and Nov 2019. Using trend growth of 1.9 percent per year, the index would increase to 135.5290 in Nov 2019. The output of manufacturing at 104.7173 in Nov 2019 is 22.7 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 105.8734 in Nov 2019 or 22.6 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 160.7359 in Nov 2019. The NAICS index at 105.8734 in Nov 2019 is 34.1 below trend. The NAICS manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999 to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output index from 106.6777 in Dec 2007 to 130.4112 in Nov 2019. The NAICS index at 105.8734 in Nov 2019 is 18.8 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 2017, 2018 and IIIQ2019
Value 2007 | Change to 2017 | Change to 2018 | Change to 2019 | |
Assets | 85,101.2 | 35,909.5 | 37,148.3 | 45,117.0 |
Nonfinancial | 30,543.9 | 5,429.8 | 7,322.4 | 8,699.7 |
Real Estate | 25,747.2 | 4,321.8 | 5,964.0 | 7,114.8 |
Financial | 54,557.3 | 30,479.7 | 29,825.9 | 36,417.3 |
Liabilities | 14,504.1 | 1,042.1 | 1,527.0 | 1,881.7 |
Net Worth | 70,597.0 | 34,867.5 | 35,621.4 | 43,235.4 |
Net Worth = Assets – Liabilities
Source: Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. https://www.federalreserve.gov/releases/z1/current/default.htm
The comparison of net worth of households and nonprofit organizations in the entire economic cycle from IQ1980 (and from IVQ1979) to IQ1993 and from IVQ2007 to IIIQ2019 is in Table IIA-5. The data reveal the following facts for the cycles in the 1980s:
- IVQ1979 to IQ1993. Net worth increased 180.7 percent from IVQ1979 to IQ1993, the all items CPI index increased 87.2 percent from 76.7 in Dec 1979 to 143.6 in Mar 1993 and real net worth increased 49.9 percent.
- IQ1980 to IVQ1985. Net worth increased 66.6 percent, the all items CPI index increased 36.5 percent from 80.1 in Mar 1980 to 109.3 in Dec 1985 and real net worth increased 22.1 percent.
- IVQ1979 to IVQ1985. Net worth increased 70.1 percent, the all items CPI index increased 42.5 percent from 76.7 in Dec 1979 to 109.3 in Dec 1985 and real net worth increased 19.4 percent.
- IQ1980 to IQ1989. Net worth increased 121.5 percent, the all items CPI index increased 52.7 percent from 80.1 in Mar 1980 to 122.3 in Mar 1989 and real net worth increased 45.1 percent.
- IQ1980 to IIQ1989. Net worth increased 126.1 percent, the all items CPI index increased 54.9 percent from 80.1 in Mar 1980 to 124.1 in Jun 1989 and real net worth increased 45.9 percent.
- IQ1980 to IIIQ1989. Net worth increased 131.9 percent, the all items CPI index increased 56.1 percent from 80.1 in Mar 1980 to 125.0 in Sep 1989 and real net worth increased 48.6 percent.
- IQ1980 to IVQ1989. Net worth increased 136.3 percent, the all items CPI index increased 57.4 from 80.1 in Mar 1980 to 126.1 in Dec 1989 and real net worth increased 50.1 percent.
- IQ1980 to IQ1990. Net worth increased 137.6 percent, the all items CPI index increased 60.7 percent from 80.1 in Mar 1980 to 128.7 in Mar 1990 and real net worth increased 47.9 percent.
- IQ1980 to IIQ1990. Net worth increased 140.2 percent, the all items CPI index increased 62.2 percent from 80.1 in Mar 1980 to 129.9 in Jun 1990 and real net worth increased 48.1 percent
- IQ1980 to IIIQ1990. Net worth increased 138.4 percent, the all items CPI index increased 65.7 percent from 80.1 in Mar 1980 to 132.7 in Jun 1990 and real net worth increased 43.9 percent.
- IQ1980 to IVQ1990. Net worth increased 143.1 percent, the all items CPI index increased 67.0 percent from 80.1 in Mar 1980 to 133.8 in Dec 1990 and real net worth increased 45.5 percent. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). This new cyclical contraction explains the contraction of net worth in IIIQ1990
- IQ1980 to IQ1991. Net worth increased 149.4 percent, the all items CPI index increased 68.5 percent from 80.1 in Mar 1980 to 135.0 in Mar 1991 and real net worth increased 48.0 percent.
- IQ1980 to IIQ1991. Net worth increased 149.9 percent, the all items CPI index increased 69.8 percent from 80.1 in Mar 1980 to 136.0 in Jun 1991 and real net worth increased 47.2 percent.
- IQ1980 to IIIQ1991. Net worth increased 152.9 percent, the all items CPI index increased 71.3 percent from 80.1 in Mar 1980 to 137.2 in Sep 1991 and real net worth increased 47.6 percent.
- IQ1980 to IVQ1991. Net worth increased 159.2 percent, the all items CPI index increased 72.2 percent from 80.1 in Mar 1980 to 137.9 in Dec 1991 and real net worth increased 50.6 percent.
- IQ1980 to IQ1992. Net worth increased 160.2 percent, the all items CPI index increased 73.9 percent from 80.1 in Mar 1980 to 139.3 in Mar 1992 and real net worth increased 49.6 percent.
- IQ1980 to IIQ1992. Net worth increased 161.1 percent, the all items CPI index increased 75.0 percent from 80.1 in Mar 1980 to 140.2 in Jun 1992 and real net worth increased 49.2 percent.
- IQ1980 to IIIQ1992. Net worth increased 164.9 percent, the all items CPI index increased 76.4 percent from 80.1 in Mar 1980 to 141.3 in Sep 1992 and real net worth increased 50.2 percent.
- IQ1980 to IVQ1992. Net worth increased 171.3, the all items CPI index increased 77.2 percent from 80.1 in Mar 1980 to 141.9 in Dec 1992 and real net worth increased 53.2 percent.
- IQ1980 to IQ1993. Net worth increased 174.9 percent, the all items CPI increased 79.3 percent from 80.1 in Mar 1980 to 143.6 in Mar 1993 and real net worth increased 53.3 percent.
There is comparatively weaker performance in the current economic cycle:
- IVQ2007 to IIIQ2019. Net worth increased 61.2 percent, the all items CPI increased 22.2 percent from 210.036 in Dec 2007 to 256.759 in Sep 2019 and real or inflation adjusted net worth increased 31.9 percent. Real estate assets adjusted for inflation increased 4.4 percent. Growth of real net worth at the long-term average of 3.2 percent per year from IVQ1945 to IIIQ2019 would have accumulated to 44.8 percent in the entire cycle from IVQ2007 to IIIQ2019, much higher than actual 31.9 percent.
The explanation is partly in the sharp decline of wealth of households and nonprofit organizations and partly in the mediocre growth rates of the cyclical expansion beginning in IIIQ2009. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.3 percent on average in the cyclical expansion in the 41 quarters from IIIQ2009 to IIIQ2019. 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 IIIQ2019 (https://www.bea.gov/system/files/2019-12/gdp3q19_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/2020/01/fluctuating-valuations-of-risk.html and earlier https://cmpassocregulationblog.blogspot.com/2019/11/fluctuating-valuations-of-risk.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 and at 7.9 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2020/01/fluctuating-valuations-of-risk.html and earlier https://cmpassocregulationblog.blogspot.com/2019/11/fluctuating-valuations-of-risk.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 IIIQ2019 would have accumulated to 41.5 percent. GDP in IIIQ2019 would be $22,303.2 billion (in constant dollars of 2012) if the US had grown at trend, which is higher by $3182.1 billion than actual $19,121.1 billion. There are more than three trillion dollars of GDP less than at trend, explaining the 18.5 million unemployed or underemployed equivalent to actual unemployment/underemployment of 10.8 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2019/12/increase-in-valuations-of-risk.html and earlier https://cmpassocregulationblog.blogspot.com/2019/11/increasing-valuations-of-risk-financial.html). US GDP in IIIQ2019 is 14.3 percent lower than at trend. US GDP grew from $15,762.0 billion in IVQ2007 in constant dollars to $19,121.1 billion in IIIQ2019 or 21.3 percent at the average annual equivalent rate of 1.7 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 3.0 percent per year from Nov 1919 to Nov 2019. Growth at 3.0 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 154.0282 in Nov 2019. The actual index NSA in Nov 2019 is 104.7173 which is 32.0 percent below trend. 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 159.4601 in Nov 2019. The actual index NSA in Nov 2019 is 104.7173, which is 34.3 percent below trend. Manufacturing output grew at average 1.9 percent between Dec 1986 and Nov 2019. Using trend growth of 1.9 percent per year, the index would increase to 135.5290 in Nov 2019. The output of manufacturing at 104.7173 in Nov 2019 is 22.7 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 105.8734 in Nov 2019 or 22.6 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 160.7359 in Nov 2019. The NAICS index at 105.8734 in Nov 2019 is 34.1 below trend. The NAICS manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999 to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output index from 106.6777 in Dec 2007 to 130.4112 in Nov 2019. The NAICS index at 105.8734 in Nov 2019 is 18.8 percent below trend under this alternative calculation.
Period IQ1980 to IQ1993 | |
Net Worth of Households and Nonprofit Organizations USD Millions | |
IVQ1979 IQ1980 | 9,102.0 9,294.5 |
IVQ1985 IIIQ1986 IVQ1986 IQ1987 IIQ1987 IIIQ1987 IVQ1987 IQ1988 IIQ1988 IIIQ1988 IVQ1988 IQ1989 IIQ1989 IIIQ1989 IVQ1989 IQ1990 IIQ1990 | 15,486.5 16,540.0 17,110.0 17,731.0 18,021.7 18,433.2 18,379.1 18,888.9 19,327.5 19,649.4 20,157.8 20,591.0 21,013.6 21,556.3 21,959.1 22,088.1 22,326.5 |
III1990 | 22,158.8 |
IV1990 | 22,593.2 |
I1991 | 23,184.3 |
IIQ1991 | 23,230.4 |
IIIQ1991 | 23,506.1 |
IVQ1991 | 24,092.7 |
IQ1992 | 24,182.5 |
IIQ1992 | 24,268.9 |
IIIQ1992 | 24,621.0 |
IVQ1992 | 25,219.6 |
IQ1993 | 25,548.8 |
∆ USD Billions IVQ1985 IVQ1979 to IQ1993 IQ1980-IVQ1985 IQ1980-IIIQ1986 IQ1980-IVQ1986 IQ1980-IQ1987 IQ1980-IIQ1987 IQ1980-IIIQ1987 IQ1980-IVQ1987 IQ1980-IQ1988 IQ1980-IIQ1988 IQ1980-IIIQ1988 IQ1980-IVQ1988 IQ1980-IQ1989 IQ1980-IIQ1989 IQ1980-IIIQ1989 IQ1980-IVQ1989 IQ1980-IQ1990 IQ1980-IIQ1990 | +6,192.0.0 ∆%66.6 R∆22.1 +16,446.8 ∆%180.7R∆%49.9 +6,192.0.0∆%66.6 R∆%22.1 +7,245.5 ∆%78.0 R∆%29.3 +7,815.5 ∆%84.1 R∆%33.4 +8,436.5 ∆%90.8 R∆%36.3 +8,727.2 ∆%93.9 R∆%36.8 +9,138.7 ∆%98.3 R∆%38.1 +9084.6 ∆%97.7 R∆%37.3 +9594.4 ∆%103.2 R∆%39.7 +10,033.0 ∆%107.9 R∆%41.2 +10,354.9 ∆%111.4 R∆%41.4 +10,863.3 ∆%116.9 R∆%44.2 +11296.5 ∆%121.5 R∆%45.1 +11,719.1 ∆%126.1 R∆% 45.9 +12,261.8 ∆%131.9 R∆% 48.6 +12,664.6 ∆%136.3 R∆%50.1 +12,793.6 ∆%137.6 R∆%47.9 +13,032.0 ∆%140.2 R∆%48.1 |
IQ1980-IIIQ1990 | +12,864.3∆%138.4 R∆%43.9 |
IQ1980-IVQ1990 | +13,298.7 ∆%143.1 R∆%45.5 |
IQ1980-IQ1991 | +13,889.8 ∆%149.4 R∆%48.0 |
IQ1980-IIQ1991 | +13,935.9 ∆%149.9 R∆%47.2 |
IQ1980-IIIQ1991 | +14,211.6 ∆%152.9 R∆%47.6 |
IQ1980-IVQ1991 | +14,798.2 ∆%159.2 R∆%50.6 |
IQ1980-IQ1992 | +14,888.0 ∆%160.2 R∆%49.6 |
IQ1980-IIQ1992 | +14,974.4 ∆%161.1 R∆%49.2 |
IQ1980-IIIQ1992 | +15,326.5 ∆%164.9 R∆%50.2 |
IQ1980-IVQ1992 | +15,925.1 ∆%171.3 R∆%53.2 |
IQ1980-IQ1993 | +16,254.3 ∆%174.9 R∆%53.3 |
Period IVQ2007 to IIIQ2019 | |
Net Worth of Households and Nonprofit Organizations USD Millions | |
IVQ2007 | 70,597.0 |
IIIQ2019 | 113,832.4 |
∆ USD Billions | +43,235.4 ∆%61.2 R∆%31.9 |
Net Worth = Assets – Liabilities. R∆% real percentage change or adjusted for CPI percentage change.
Source: Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. https://www.federalreserve.gov/releases/z1/current/default.htm
Chart IIA-1 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ2007 to IIIQ2019. There is remarkable stop and go behavior in this series with two sharp declines and two standstills in the 40 quarters of expansion of the economy beginning in IIIQ2009. The increase in net worth of households and nonprofit organizations is the result of increases in valuations of risk financial assets and compressed liabilities resulting from zero interest rates. Wealth of households and nonprofits organization increased 31.9 percent from IVQ2007 to IIIQ2019 when adjusting for consumer price inflation. Net worth of households and nonprofit organizations fell 3.5 percent from 110,106.1 billion in IIIQ2018 to 106,218.4 billion in IVQ2018 or $3,887.7 billion. Financial assets decreased 4.7 percent from 88,587.6 billion in IIIQ2018 to 84,383.2 billion in IVQ2018 or $4,204.4. Corporate equities fell 16.1 percent from $18,583.7 billion in IIIQ2018 to $15,590.6 billion in IVQ2018 or $2,993.1 billion. These are the revised data in the report of Dec 12, 2019, for IIIQ2019.
Chart IIA-1, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ2007 to IIIQ2019
Source: Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. https://www.federalreserve.gov/releases/z1/current/default.htm
Chart IIA-2 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1979 to IQ1993. There are changes in the rates of growth of wealth suggested by the changing slopes but there is smooth upward trend. There was significant financial turmoil during the 1980s. Benston and Kaufman (1997, 139) find that there was failure of 1150 US commercial and savings banks between 1983 and 1990, or about 8 percent of the industry in 1980, which is nearly twice more than between the establishment of the Federal Deposit Insurance Corporation in 1934 through 1983. More than 900 savings and loans associations, representing 25 percent of the industry, were closed, merged or placed in conservatorships (see Pelaez and Pelaez, Regulation of Banks and Finance (2008b), 74-7). The Financial Institutions Reform, Recovery and Enforcement Act of 1989 (FIRREA) created the Resolution Trust Corporation (RTC) and the Savings Association Insurance Fund (SAIF) that received $150 billion of taxpayer funds to resolve insolvent savings and loans. The GDP of the US in 1989 was $5641.6 billion (http://www.bea.gov/iTable/index_nipa.cfm), such that the partial cost to taxpayers of that bailout was around 2.66 percent of GDP in a year. The Bureau of Economic Analysis estimates US GDP in 2018 at $20,580.2 billion, such that the bailout would be equivalent to cost to taxpayers of about $547.4 billion in current GDP terms. A major difference with the Troubled Asset Relief Program (TARP) for private-sector banks is that most of the costs were recovered with interest gains whereas in the case of savings and loans there was no recovery. Money center banks were under extraordinary pressure from the default of sovereign debt by various emerging nations that represented a large share of their net worth (see Pelaez 1986). Net worth of households and nonprofit organizations increased 180.7 percent from IVQ1979 to IQ1993 and 49.9 percent when adjusting for consumer price inflation. Net worth of households and nonprofit organizations increased 174.9 percent from IQ1980 to IQ1993 and 53.3 percent when adjusting for consumer price inflation. The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). This new cyclical contraction explains the contraction followed by stability of net worth in the final segment followed by mild increase and then rising trend in Chart IIA-2.
Chart IIA-2, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1979 to IQ1993
Source: Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. https://www.federalreserve.gov/releases/z1/current/default.htm
Chart IIA-3 of the Board of Governors of the Federal Reserve System provides US wealth of households and nonprofit organizations from IVQ1945 at $806.7 billion to IIIQ2019 at $113,832.4 billion or increase of 14,010.9 percent. The consumer price index not seasonally adjusted was 18.2 in Dec 1945 jumping to 256.759 in IIIQ2019 or increase of 1,310.8 percent. There was a gigantic increase of US net worth of households and nonprofit organizations over 73.75 years with inflation-adjusted increase from $44.324 in dollars of 1945 to $443.343 in IIIQ2019 or 900.2 percent. In a simple formula: {[($113,832.4/806.7)/(256.759/18.2)-1]100 = 900.2%}. Wealth of households and nonprofit organizations increased from $806.7 billion at year-end 1945 to $113,832.4 billion at the end of IIIQ2019 or 14,010.9 percent. The consumer price index increased from 18.2 in Dec 1945 to 256.759 in Sep 2019 or 1,310.8 percent. Net wealth of households and nonprofit organizations in dollars of 1945 increased from $44.324 in 1945 to $443.343 in IIIQ2019 or 900.2 percent at the average yearly rate of 3.2 percent. US real GDP grew at the average rate of 2.9 percent from 1945 to 2018 (http://www.bea.gov/iTable/index_nipa.cfm). The combination of collapse of values of real estate and financial assets during the global recession of IVQ2007 to IIIQ2009 caused sharp contraction of net worth of US households and nonprofit organizations. Recovery has been in stop-and-go fashion during the worst cyclical expansion in the 73.5 years when US GDP grew at 2.3 percent on average in the forty-0ne quarters between IIIQ2009 and IIIQ2019 (https://cmpassocregulationblog.blogspot.com/2020/01/fluctuating-valuations-of-risk.html and earlier https://cmpassocregulationblog.blogspot.com/2019/11/fluctuating-valuations-of-risk.html). US GDP was $228.0 billion in 1945 and net worth of households and nonprofit organizations $806.7 billion for ratio of wealth to GDP of 3.54. The ratio of net worth of households and nonprofits of $70,597.0 billion in 2007 to GDP of $14,451.9 billion was 4.88. The ratio of net worth of households and nonprofits of $106,218.4 billion in 2018 to GDP of $20,580.2 billion was 5.16. The final data point in Chart IIA-3 is net worth of household and nonprofit institutions at $113,382.4 billion in IIIQ2019 for increase of 14,010.9 percent relative to $806.7 billion in IVQ1945. CPI adjusted net worth of household and nonprofit institutions increased from $44.324 in IVQ1945 to $443.343 in IIIQ2019 or 900.2 percent at the annual equivalent rate of 3.2 percent. Net worth of households and nonprofit organizations fell 3.5 percent from 110,106.1 billion in IIIQ2018 to 106,218.4 billion in IVQ2018 or $3,887.7 billion. Financial assets decreased 4.7 percent from 88,587.6 billion in IIIQ2018 to 84,383.2 billion in IVQ2018 or $4,204.4. Corporate equities fell 16.1 percent from $18,583.7 billion in IIIQ2018 to $15,590.6 billion in IVQ2018 or $2,993.1 billion. These are the revised data in the report of Dec 12, 2019, for IIIQ2019.
Chart IIA-3, Net Worth of Households and Nonprofit Organizations in Millions of Dollars, IVQ1945 to IIIQ2019
Source: Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. https://www.federalreserve.gov/releases/z1/current/default.htm
Table IIA-6 provides percentage changes of nonfinancial domestic sector debt. Households increased debt by 10.5 percent in 2006 but reduced debt from 2010 to 2011. Households have increased debt moderately since 2012. Financial repression by zero fed funds rates or negative interest rates intends to increase debt and reduce savings. Business had not been as exuberant in acquiring debt and has been increasing debt benefitting from historically low costs while increasing cash holdings to around $2 trillion by swelling undistributed profits because of the uncertainty of capital budgeting. The key to growth and hiring consists in creating the incentives for business to invest and hire. States and local government were forced into increasing debt by the decline in revenues but began to contract in IQ2011, decreasing again from IQ2011 to IVQ2011, increasing at 2.1 percent in IIQ2012 and decreasing at 0.2 percent in IIIQ2012 and 2.6 percent in IVQ2012. State and local government increased debt at 1.9 percent in IQ2013 and decreased at 1.1 percent in IIQ2013. State and local government decreased debt at 3.0 percent in IIIQ2013 and at 2.8 percent in IVQ2013. State and local government reduced debt at 1.7 percent in IQ2014 and decreased at 0.4 percent in IIQ2014. State and local government reduced debt at 2.7 percent in IIIQ2014 and increased at 0.7 percent in IVQ2014. State and local government increased debt at 1.6 percent in IQ2015 and increased at 0.3 percent in IIIQ2015. State and local government decreased debt at 0.9 percent in IVQ2015. State and local government increased debt at 0.7 percent in IQ2016 and increased at 2.4 percent in IIQ2016. State and local government increased debt at 0.7 percent in IIIQ2016. Opposite behavior is for the federal government that has been rapidly accumulating debt but without success in the self-assigned goal of promoting economic growth. Financial repression constitutes seigniorage of government debt (http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-financial.html http://cmpassocregulationblog.blogspot.com/2011/05/global-inflation-seigniorage-monetary.html).
Table IIA-6, US, Percentage Change of Nonfinancial Domestic Sector Debt
Total | Households | Business | Federal | State & | |
IIIQ2019 | 6.3 | 3.3 | 5.7 | 10.4 | 0.5 |
IIQ2019 | 3.1 | 4.3 | 4.4 | 2.1 | -2.5 |
IQ2019 | 6.0 | 2.1 | 6.9 | 9.8 | -1.2 |
IVQ2018 | 3.4 | 2.8 | 4.6 | 3.7 | -1.6 |
IIIQ2018 | 4.1 | 3.4 | 3.9 | 5.9 | -1.5 |
IIQ2018 | 4.0 | 3.6 | 3.3 | 5.7 | -0.4 |
IQ2018 | 6.7 | 3.0 | 3.9 | 14.3 | -3.2 |
IVQ2017 | 3.8 | 5.1 | 4.9 | 1.8 | 4.0 |
IIIQ2017 | 4.5 | 2.6 | 6.1 | 6.0 | -0.6 |
IIQ2017 | 4.6 | 4.2 | 6.4 | 4.4 | -1.0 |
IQ2017 | 3.3 | 3.8 | 6.0 | 1.7 | -2.2 |
IVQ2016 | 2.0 | 2.6 | 1.8 | 2.1 | -0.3 |
IIIQ2016 | 5.2 | 4.4 | 6.0 | 6.1 | 0.7 |
IIQ2016 | 4.5 | 3.7 | 4.2 | 6.0 | 2.4 |
IQ2016 | 5.5 | 2.4 | 9.2 | 6.2 | 0.7 |
IVQ2015 | 8.0 | 4.1 | 5.9 | 15.6 | -0.9 |
IIIQ2015 | 2.1 | 1.3 | 5.3 | 0.6 | 0.3 |
IIQ2015 | 4.7 | 3.8 | 8.2 | 3.4 | 0.2 |
IQ2015 | 3.0 | 2.2 | 7.5 | -0.3 | 1.6 |
IVQ2014 | 3.7 | 2.3 | 6.4 | 3.1 | 0.7 |
2018 | 4.6 | 3.2 | 4.0 | 7.6 | -1.6 |
2017 | 4.2 | 4.0 | 6.0 | 3.7 | -0.0 |
2016 | 4.5 | 3.2 | 5.3 | 5.6 | 1.1 |
2015 | 4.4 | 2.4 | 7.0 | 5.0 | 0.4 |
2014 | 4.1 | 2.1 | 6.5 | 5.4 | -1.2 |
2013 | 3.7 | 1.7 | 4.5 | 6.7 | -1.7 |
2012 | 4.8 | 1.0 | 5.0 | 10.1 | 0.1 |
2011 | 3.6 | 0.0 | 2.6 | 10.8 | -1.2 |
2010 | 4.4 | -0.6 | -0.8 | 18.5 | 2.7 |
2009 | 3.7 | 0.5 | -3.9 | 20.4 | 4.7 |
2008 | 5.7 | 0.0 | 5.7 | 21.4 | 1.4 |
2007 | 8.1 | 7.1 | 12.5 | 4.7 | 6.2 |
2006 | 8.4 | 10.5 | 9.8 | 3.9 | 4.4 |
Note: Quarterly data for IQ2016 and earlier and annual data for 2007 and earlier are from prior reports.
Source: Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. https://www.federalreserve.gov/releases/z1/current/default.htm
Federal Reserve System, Sep 20. https://www.federalreserve.gov/releases/z1/current/default.htm
Table IIA-7 provides wealth of US households and nonprofit organizations since 2005 in billions of current dollars at the end of period, NSA. Wealth fell from $70,597 billion in 2007 to $62,836 billion in 2009 or 11.0 percent and to $68,312 billion in 2011 or 3.2 percent. Wealth increased 61.2 percent from 2007 to IIIQ2019, increasing 31.9 percent after adjustment for inflation, primarily because of bloating financial assets while nonfinancial assets declined/stagnated cyclically in real terms. Net worth of households and nonprofit organizations fell 3.5 percent from 110,106.1 billion in IIIQ2018 to 106,218.4 billion in IVQ2018 or $3,887.7 billion. Financial assets decreased 4.7 percent from 88,587.6 billion in IIIQ2018 to 84,383.2 billion in IVQ2018 or $4,204.4. Corporate equities fell 16.1 percent from $18,583.7 billion in IIIQ2018 to $15,590.6 billion in IVQ2018 or $2,993.1 billion. These are the revised data in the report of Dec 12, 2019, for IIIQ2019.
Quarter | Net Worth |
IIIQ2019 | 113,832 |
IIQ2019 | 113,259 |
IQ2019 | 111,397 |
IVQ2018 | 106,218 |
IIIQ2018 | 110,106 |
IIQ2018 | 107,985 |
IQ2018 | 106,147 |
IVQ2017 | 105,465 |
IIIQ2017 | 102,827 |
IIQ2017 | 100,699 |
IQ2017 | 98,990 |
IVQ2016 | 96,844 |
IIIQ2016 | 95,667 |
IIQ2016 | 93,510 |
IQ2016 | 92,052 |
IVQ2015 | 91,133 |
IIIQ2015 | 89,539 |
IIQ2015 | 90,597 |
IQ2015 | 90,146 |
IVQ2014 | 88,211 |
IIIQ2014 | 86,326 |
IIQ2014 | 85,865 |
IQ2014 | 84,057 |
IVQ2013 | 82,537 |
IIIQ2013 | 80,099 |
IIQ2013 | 77,494 |
IQ2013 | 76,284 |
IVQ2012 | 73,423 |
2018 | 106,218 |
2017 | 105,465 |
2016 | 96,844 |
2015 | 91,133 |
2014 | 88,211 |
2013 | 82,537 |
2012 | 73,423 |
2011 | 68,312 |
2010 | 67,125 |
2009 | 62,836 |
2008 | 61,562 |
2007 | 70,597 |
2006 | 69,143 |
2005 | 64,547 |
Source: Board of Governors of the Federal Reserve System. 2019. Flow of funds, balance sheets and integrated macroeconomic accounts: third quarter 2019. Washington, DC, Federal Reserve System, Dec 12. https://www.federalreserve.gov/releases/z1/current/default.htm
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.
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